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1. Analyzing Speech Motor Movement using Surface Electromyography in Minimally Verbal Adults with Autism Spectrum Disorder

Author

Zulfikar, Wazeer, Protyasha, Nishat, Canales, Camila, Patel, Heli, Williamson, James, Sarnie, Laura, Nowinski, Lisa, Kosmyna, Nataliya, Townsend, Paige, Yuditskaya, Sophia, Talkar, Tanya, Sarawgi, Utkarsh Oggy, McDougle, Christopher, Quatieri, Thomas, Maes, Pattie, and Mody, Maria

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Human-Computer Interaction
Abstract

Adults who are minimally verbal with autism spectrum disorder (mvASD) have pronounced speech difficulties linked to impaired motor skills. Existing research and clinical assessments primarily use indirect methods such as standardized tests, video-based facial features, and handwriting tasks, which may not directly target speech-related motor skills. In this study, we measure activity from eight facial muscles associated with speech using surface electromyography (sEMG), during carefully designed tasks. The findings reveal a higher power in the sEMG signals and a significantly greater correlation between the sEMG channels in mvASD adults (N=12) compared to age and gender-matched neurotypical controls (N=14). This suggests stronger muscle activation and greater synchrony in the discharge patterns of motor units. Further, eigenvalues derived from correlation matrices indicate lower complexity in muscle coordination in mvASD, implying fewer degrees of freedom in motor control.

Published
2024

4. Cognitive, functional, and neuropsychiatric correlates of regional tau pathology in autopsy-confirmed chronic traumatic encephalopathy

Author

Alosco, Michael L., White, Micaela, Bell, Carter, Faheem, Farwa, Tripodis, Yorghos, Yhang, Eukyung, Baucom, Zachary, Martin, Brett, Palmisano, Joseph, Dams-O’Connor, Kristen, Crary, John F., Goldstein, Lee E., Katz, Douglas I., Dwyer, Brigid, Daneshvar, Daniel H., Nowinski, Christopher, Cantu, Robert C., Kowall, Neil W., Stern, Robert A., Alvarez, Victor E., Huber, Bertrand Russell, Stein, Thor D., McKee, Ann C., and Mez, Jesse

Published
2024
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5. The impact of the war in Ukraine on the prevalence of MDR/RR-TB in Poland

Author

A. Nowinski, E. Augustynowicz-Kopeć, J. Garnczarek, A. Halicka, M. Koszela, W. Litwiniuk, D. Maj, I. Mazur, J. Niestrój-Ostrowska, R. Podlasin, A. Regulska, M. Wielopolska, J. Wyrwiński, S. Wesołowski, and M. Korzeniewska-Koseła

Subjects
poland, ukraine, mdr/rr-tb, mdr tb, war, refugees, Diseases of the respiratory system, RC705-779
Abstract

BACKGROUND: The 2022 invasion of Ukraine by the Russian Federation triggered a refugee crisis, affecting the multidrug-/rifampicin-resistant TB (MDR/RR-TB) prevalence in neighbouring countries. This study examines the epidemiological trends and characteristics of MDR/RR-TB patients in Poland, focusing on the relative contribution of Ukrainian refugees. METHODS: Data from the Polish National Tuberculosis Registry and EPIC Project database, covering MDR/RR-TB cases reported between 2010 and Q1 2024, were analysed. RESULTS: The study included 794 MDR/RR-TB cases, showing a demographic shift post-2022. During the 10-year period up to 2021, a median of 48 MDR/RR-TB cases were reported annually in Poland. After 2022, these numbers doubled: 104 cases were reported in 2022 and 101 cases in 2023. Simultaneously, the number of Ukrainian MDR/RR-TB patients increased from 77 (13%) during 2010–2021 to 127 (58%) from 2022 to Q1 2024. CONCLUSION: Poland is observing an increased number of cases of MDR/RR-TB associated with the large number of displaced Ukrainian citizens who are now residing in Poland. There is a need to monitor the epidemiology of MDR/RR-TB and seek optimal screening and management strategies for TB among refugees from countries with high MDR/RR-TB incidence in Poland and Europe.

Published
2025
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6. Flow separation control design with experimental validation

Author

Arnoult, T., Acher, G., Nowinski, V., Vuillemin, P., Briat, C., Pernod, P., Ghouila-Houri, C., Talbi, A., Garnier, E., and Poussot-Vassal, C.

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Flow control aims at modifying a natural flow state to reach an other flow state considered as advantageous. In this paper, active feedback flow separation control is investigated with two different closed-loop control strategies, involving a reference signal tracking architecture. Firstly, a data-driven control law, leading to a linear (integral) controller is employed. Secondly, a phenomenological/model-driven approach, leading to a non-linear positive (integral) control strategy is investigated. While the former benefits of a tuning simplicity, the latter prevents undesirable effects and formally guarantees closed-loop stability. Both control approaches were validated through wind tunnel experiments of flow separation over a movable NACA 4412 plain flap. These control laws were designed with respect to hot film measurements, performed over the flap for different deflection angles. Both control approaches proved efficient in avoiding flow separation. The main contribution of this work is to provide practitioners simple but yet efficient ways to design a flow separation controller. In addition, a complete validation campaign data-set is provided.

Published
2023

7. Phosphate starvation signaling increases mitochondrial membrane potential through respiration-independent mechanisms.

Author

Ouyang, Yeyun, Jeong, Mi-Young, Cunningham, Corey, Berg, Jordan, Toshniwal, Ashish, Hughes, Casey, Seiler, Kristina, Van Vranken, Jonathan, Cluntun, Ahmad, Lam, Geanette, Winter, Jacob, Akdogan, Emel, Dove, Katja, Nowinski, Sara, West, Matthew, Odorizzi, Greg, Gygi, Steven, Dunn, Cory, Winge, Dennis, and Rutter, Jared

Subjects
D. melanogaster, S. cerevisiae, cell biology, human, mitochondria, mitochondrial membrane potential, phosphate, Animals, Membrane Potential, Mitochondrial, Phosphates, Saccharomyces cerevisiae, Adenosine Triphosphate, Respiration, Mammals
Abstract

Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both by inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of mitochondrial membrane potential is observed in primary and immortalized mammalian cells as well as in Drosophila. These data suggest that mitochondrial membrane potential is subject to environmental stimuli and intracellular signaling regulation and raise the possibility for therapeutic enhancement of mitochondrial function even in defective mitochondria.

Published
2024

8. Mobile Toolbox sequences task: development and validation of a remote, smartphone-based working memory test.

Author

Slotkin, Jerry, Kaat, Aaron, Young, Stephanie, Dworak, Elizabeth, Novack, Miriam, Shono, Yusuke, Adam, Hubert, Nowinski, Cindy, Pila, Sarah, Hosseinian, Zahra, Varela Diaz, Maria, Almonte-Correa, Anyelo, Alperin, Keith, Camacho, Monica, Landavazo, Bernard, Nosheny, Rachel, Weiner, Michael, and Gershon, Richard

Subjects
NIH Toolbox, cognition, mobile assessment, validation, working memory
Abstract

OBJECTIVE: The ability to assess cognitive skills remotely is increasing with the widespread use and availability of smartphones. The Mobile Toolbox (MTB) is a measurement system that includes Sequences, a new measure of working memory designed specifically for smartphones. This study describes the development of Sequences and presents the studies conducted to evaluate its psychometric properties. METHODS: We developed a new measure of working memory that can be self-administered remotely using an iOS or Android smartphone. In Sequences, a series of numbers and letters are shown on the screen one at a time, and the participant must first tap the letters they see in alphabetical order, followed by tapping the numbers in ascending numerical order. The Sequences measure was evaluated for usability and feasibility across two pilot studies and then assessed in this validation study (which included a total sample size of N = 1,246). Psychometric properties of the new measure were evaluated in three studies involving participants aged 18-90 years. In Study 1 (N = 92), participants completed MTB measures in a laboratory setting. They were also administered both an equivalent NIH Toolbox (NIHTB) measure along with external measures of similar constructs. In Study 2 (N = 1,007), participants were administered NIHTB measures in the laboratory and then completed MTB measures remotely on their own devices. In Study 3 (N = 147), participants completed MTB measures twice, remotely on their own devices, with a 2-week interval between sessions. RESULTS: Sequences exhibited moderately high correlations with a comparable NIHTB test and external measures of a similar construct, while exhibiting a lower correlation with an unrelated test, as hypothesized. Internal consistency was high, but test-retest reliability was moderate. When controlling for age, phone operating system (iOS vs. Android) and sex assigned at birth did not significantly impact performance; however, there was a significant difference between individuals who completed college and those with a high school education or lower. CONCLUSION: The results support the validity of Sequences as a measure of working memory for remote self-administered use. The internal consistency was strong, with moderate test-retest reliability that is likely a function of the tests unproctored self-administration method. The findings suggest that Sequences is appropriate for use with adults aged 18-90 years in remote self-administered designs that focus on group results.

Published
2024

9. Mobile Toolbox sequences task: development and validation of a remote, smartphone-based working memory test

Author

Jerry Slotkin, Aaron J. Kaat, Stephanie Ruth Young, Elizabeth M. Dworak, Miriam A. Novack, Yusuke Shono, Hubert Adam, Cindy J. Nowinski, Sarah Pila, Zahra Hosseinian, Maria Varela Diaz, Anyelo Almonte-Correa, Keith Alperin, Monica R. Camacho, Bernard Landavazo, Rachel L. Nosheny, Michael W. Weiner, and Richard C. Gershon

Subjects
cognition, working memory, mobile assessment, NIH Toolbox, validation, Psychology, BF1-990
Abstract

ObjectiveThe ability to assess cognitive skills remotely is increasing with the widespread use and availability of smartphones. The Mobile Toolbox (MTB) is a measurement system that includes Sequences, a new measure of working memory designed specifically for smartphones. This study describes the development of Sequences and presents the studies conducted to evaluate its psychometric properties.MethodsWe developed a new measure of working memory that can be self-administered remotely using an iOS or Android smartphone. In Sequences, a series of numbers and letters are shown on the screen one at a time, and the participant must first tap the letters they see in alphabetical order, followed by tapping the numbers in ascending numerical order. The Sequences measure was evaluated for usability and feasibility across two pilot studies and then assessed in this validation study (which included a total sample size of N = 1,246). Psychometric properties of the new measure were evaluated in three studies involving participants aged 18–90 years. In Study 1 (N = 92), participants completed MTB measures in a laboratory setting. They were also administered both an equivalent NIH Toolbox (NIHTB) measure along with external measures of similar constructs. In Study 2 (N = 1,007), participants were administered NIHTB measures in the laboratory and then completed MTB measures remotely on their own devices. In Study 3 (N = 147), participants completed MTB measures twice, remotely on their own devices, with a 2–week interval between sessions.ResultsSequences exhibited moderately high correlations with a comparable NIHTB test and external measures of a similar construct, while exhibiting a lower correlation with an unrelated test, as hypothesized. Internal consistency was high, but test-retest reliability was moderate. When controlling for age, phone operating system (iOS vs. Android) and sex assigned at birth did not significantly impact performance; however, there was a significant difference between individuals who completed college and those with a high school education or lower.ConclusionThe results support the validity of Sequences as a measure of working memory for remote self-administered use. The internal consistency was strong, with moderate test-retest reliability that is likely a function of the test's unproctored self-administration method. The findings suggest that Sequences is appropriate for use with adults aged 18–90 years in remote self-administered designs that focus on group results.

Published
2025
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10. Near vision assessment for adults using the NIH Toolbox

Author

John-Christopher A. Finley, Jerry Slotkin, Cindy J. Nowinski, Katy Bedjeti, Nicholas Volpe, Sandra Weintraub, and Richard Gershon

Subjects
near vision, visual acuity, NIH Toolbox, cognitive, neurology, neuropsychology, Neurology. Diseases of the nervous system, RC346-429
Abstract

IntroductionThe National Institutes of Health (NIH) Toolbox Near Visual Acuity Test is a novel digitized measure designed to provide an assessment of near vision in a time-and cost-effective manner. This study is the first to report the psychometric properties of the NIH Toolbox Near Visual Acuity Test in a sample of community-dwelling middle-aged and older adults.MethodsNinety-eight adults (ages 40–81) completed the tablet-based near vision test and the gold standard chart-based near vision test. Performance on the tablet-and chart-based near vision tests was expressed in logarithmic units. Chart-and tablet-based administration order was counterbalanced. To assess test–retest reliability, the NIH Toolbox Near Visual Acuity Test was administered twice within the same day. Additionally, two equivalent versions of the chart-based test were randomly assigned to participants.ResultsAnalyses revealed that test–retest reliability of the NIH Toolbox Near Visual Acuity Test was good (intraclass correlation = 0.87, p

Published
2025
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12. Determination of Effect Sizes for Power Analysis for Microbiome Studies Using Large Microbiome Databases.

Author

Rahman, Gibraan, McDonald, Daniel, Gonzalez, Antonio, Vázquez-Baeza, Yoshiki, Jiang, Lingjing, Casals-Pascual, Climent, Hakim, Daniel, Dilmore, Amanda Hazel, Nowinski, Brent, Peddada, Shyamal, and Knight, Rob

Subjects
Software, Databases, Factual, Microbiota, Gastrointestinal Microbiome, bioinformatics, effect size, microbiome, statistics, Human Genome, Complementary and Integrative Health, Genetics, Networking and Information Technology R&D (NITRD)
Abstract

Herein, we present a tool called Evident that can be used for deriving effect sizes for a broad spectrum of metadata variables, such as mode of birth, antibiotics, socioeconomics, etc., to provide power calculations for a new study. Evident can be used to mine existing databases of large microbiome studies (such as the American Gut Project, FINRISK, and TEDDY) to analyze the effect sizes for planning future microbiome studies via power analysis. For each metavariable, the Evident software is flexible to compute effect sizes for many commonly used measures of microbiome analyses, including α diversity, β diversity, and log-ratio analysis. In this work, we describe why effect size and power analysis are necessary for computational microbiome analysis and show how Evident can help researchers perform these procedures. Additionally, we describe how Evident is easy for researchers to use and provide an example of efficient analyses using a dataset of thousands of samples and dozens of metadata categories.

Published
2023

13. Decreased myelin proteins in brain donors exposed to football-related repetitive head impacts

Author

Alosco, Michael L, Ly, Monica, Mosaheb, Sydney, Saltiel, Nicole, Uretsky, Madeline, Tripodis, Yorghos, Martin, Brett, Palmisano, Joseph, Delano-Wood, Lisa, Bondi, Mark W, Meng, Gaoyuan, Xia, Weiming, Daley, Sarah, Goldstein, Lee E, Katz, Douglas I, Dwyer, Brigid, Daneshvar, Daniel H, Nowinski, Christopher, Cantu, Robert C, Kowall, Neil W, Stern, Robert A, Alvarez, Victor E, Mez, Jesse, Huber, Bertrand Russell, McKee, Ann C, and Stein, Thor D

Subjects
Biological Psychology, Psychology, Acquired Cognitive Impairment, Brain Disorders, Neurodegenerative, Neurosciences, Neurological, Good Health and Well Being, myelin, cerebrovascular disease, chronic traumatic encephalopathy, repetitive head impacts, white matter, Clinical sciences, Biological psychology
Abstract

American football players and other individuals exposed to repetitive head impacts can exhibit a constellation of later-life cognitive and neuropsychiatric symptoms. While tau-based diseases such as chronic traumatic encephalopathy can underpin certain symptoms, contributions from non-tau pathologies from repetitive head impacts are increasingly recognized. We examined cross-sectional associations between myelin integrity using immunoassays for myelin-associated glycoprotein and proteolipid protein 1 with risk factors and clinical outcomes in brain donors exposed to repetitive head impacts from American football. Immunoassays for myelin-associated glycoprotein and proteolipid protein 1 were conducted on dorsolateral frontal white matter tissue samples of 205 male brain donors. Proxies of exposure to repetitive head impacts included years of exposure and age of first exposure to American football play. Informants completed the Functional Activities Questionnaire, Behavior Rating Inventory of Executive Function-Adult Version (Behavioral Regulation Index), and Barratt Impulsiveness Scale-11. Associations between myelin-associated glycoprotein and proteolipid protein 1 with exposure proxies and clinical scales were tested. Of the 205 male brain donors who played amateur and professional football, the mean age was 67.17 (SD = 16.78), and 75.9% (n = 126) were reported by informants to be functionally impaired prior to death. Myelin-associated glycoprotein and proteolipid protein 1 correlated with the ischaemic injury scale score, a global indicator of cerebrovascular disease (r = -0.23 and -0.20, respectively, Ps < 0.01). Chronic traumatic encephalopathy was the most common neurodegenerative disease (n = 151, 73.7%). Myelin-associated glycoprotein and proteolipid protein 1 were not associated with chronic traumatic encephalopathy status, but lower proteolipid protein 1 was associated with more severe chronic traumatic encephalopathy (P = 0.03). Myelin-associated glycoprotein and proteolipid protein 1 were not associated with other neurodegenerative disease pathologies. More years of football play was associated with lower proteolipid protein 1 [beta = -2.45, 95% confidence interval (CI) [-4.52, -0.38]] and compared with those who played

Published
2023

16. An Initial Exploratory Examination of the Sensitivity and Specificity of MyCog Mobile Using the Mini-Cog as a Proxy for Suspected Cognitive Impairment

Author

Stephanie Ruth Young, Elizabeth Dworak, Greg Byrne, Yusuke Shono, Manrui Zhang, Julia Yoshino Benavente, Lihua Yao, Mike Bass, Laura Curtis, Maria Varela Diaz, Callie Jones, Richard Gershon, Michael Wolf, and Cindy Nowinski

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

Objectives: To help promote early detection of cognitive impairment in primary care, MyCog Mobile was designed as a cognitive screener that can be self-administered remotely on a personal smartphone. We explore the potential utility of MyCog Mobile in primary care by comparing MyCog Mobile to a commonly used screener, Mini-Cog. Methods: A sample of 200 older adults 65+ years (mean age = 72.56 years), completed the Mini-Cog and MyCog Mobile, which includes 2 memory measures and 2 executive functioning measures. A logistic regression model was conducted to predict failing Mini-Cog scores (≤2) based on MyCog Mobile measures. Results: A total of 20 participants earned a Mini-Cog score ≤2. MyCog Mobile demonstrated an AUC of 0.83 (95% bootstrap CI [0.75, 0.95]), sensitivity of 0.76 (95% bootstrap CI [0.63, 0.97]), and specificity of .88 (95% bootstrap CI [0.63, 0.10]). The subtest Name Matching from MyFaces and MySorting were the only significant predictors of failed Mini-Cogs. Conclusions: MyCog Mobile demonstrated sensitivity and specificity to identify participants who failed the Mini-Cog, and may show promise as a screening tool for cognitive impairment in older adults. Further research is necessary to establish the clinical utility of MyCog Mobile in a larger sample using documented clinical diagnoses.

Published
2024
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17. TB among refugees from Ukraine in European countries

Author

G. de Vries, J.P. Guthmann, B. Häcker, B. Hauer, K. Nordstrand, A. Nowinski, and H. Soini

Subjects
tuberculosis, epidemiology, refugees, screening, ukraine, Diseases of the respiratory system, RC705-779
Abstract

BACKGROUND: Since the Russian Federation’s invasion of Ukraine, millions of refugees have moved to neighbouring European countries. We assessed the burden of TB in these refugees and surveyed screening approaches. METHODS: We conducted a survey among 30 European Union/European Economic Area and 13 other European countries, requesting population data on migrant residents and refugees with country of birth (COB) Ukraine, the number of TB notifications among people with COB Ukraine and countries’ screening policies for refugees from Ukraine. RESULTS: In 2021, the number of migrants born in Ukraine was 1.7 million in the 34 responding countries, and increased with 5.2 million refugees from Ukraine to 6.9 million in 2022. These countries notified 207 TB cases in people with COB Ukraine in 2021 (TB notification rate 12.0/100,000) and 887 in 2022 (TB notification rate 12.8/100,000), of which 228 (26%) had multidrug-resistant/rifampicin-resistant TB (MDR/RR-TB). TB notification rates were higher in countries advising screening for all (16.9/100,000) or specific groups of refugees from Ukraine (14.7/100,000) compared to those without screening (7.2/100,000). CONCLUSION: TB rates found in people from Ukraine were lower than the expected rate of 44 per 100,000, but higher in host countries recommending screening. Our study underscores the need for adequate TB health services for refugees from Ukraine to ensure tailored diagnosis and treatment, especially for MDR/RR-TB.

Published
2024
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19. Transcriptional programming mediated by the histone demethylase KDM5C regulates dendritic cell population heterogeneity and function

Author

Hannah Guak, Matthew Weiland, Alexandra Vander Ark, Lukai Zhai, Kin Lau, Mario Corrado, Paula Davidson, Ebenezer Asiedu, Batsirai Mabvakure, Shelby Compton, Lisa DeCamp, Catherine A. Scullion, Russell G. Jones, Sara M. Nowinski, and Connie M. Krawczyk

Subjects
CP: Immunology, CP: Molecular biology, Biology (General), QH301-705.5
Abstract

Summary: Functional and phenotypic heterogeneity of dendritic cells (DCs) play crucial roles in facilitating the development of diverse immune responses essential for host protection. Here, we report that KDM5C, a histone lysine demethylase, regulates conventional or classical DC (cDC) and plasmacytoid DC (pDC) population heterogeneity and function. Mice deficient in KDM5C in DCs have increased proportions of cDC2Bs and cDC1s, which is partly dependent on type I interferon (IFN) and pDCs. Loss of KDM5C results in an increase in Ly6C− pDCs, which, compared to Ly6C+ pDCs, have limited ability to produce type I IFN and more efficiently stimulate antigen-specific CD8 T cells. KDM5C-deficient DCs have increased expression of inflammatory genes, altered expression of lineage-specific genes, and decreased function. In response to Listeria infection, KDM5C-deficient mice mount reduced CD8 T cell responses due to decreased antigen presentation by cDC1s. Thus, KDM5C is a key regulator of DC heterogeneity and critical driver of the functional properties of DCs.

Published
2024
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20. Spontaneous Headshake after a Kinematic Event (SHAAKE): Evaluating the Utility of a Potential New Sign in the Diagnosis of Concussion

Author

Christopher J. Nowinski, Samantha C. Bureau, Hye Chang Rhim, Ross D. Zafonte, Robert C. Cantu, and Daniel H. Daneshvar

Subjects
concussion, head injury, headshake after a kinematic event, Medicine (General), R5-920
Abstract

Background/Objectives: Diagnosing concussions is problematic, in part due to the invisible nature of concussion symptoms, in addition to personal and interpersonal factors that influence symptom reporting. As a result, observable signs of concussion can ensure concussions are identified and appropriately treated. Here, we define a potential novel sign, the spontaneous headshake after a kinematic event (SHAAKE) and evaluate its utility in the diagnosis of concussion. Methods: A cross-sectional survey study of 347 athletes (age 27, IQR: 25–29; 47.6% female; highest level of play: college—46.1%, high school—41.2%) identified whether SHAAKE occurred, the reasons underlying SHAAKEs, and its utility for self-reported concussion. Sensitivity and positive predictive value were calculated across all sports and these parameters, as well as estimates for specificity and negative predictive value leveraging published helmet sensor data, were calculated for football players. Results: The median number of times participants reported SHAAKE was 5 (IQR: 3–10), with 4 (IQR: 2–7) associated with a self-reported concussion. Overall, 84.9% of participants reported concussion symptoms as the most common reason for their SHAAKEs. Across all sports, SHAAKE had a sensitivity of 49.6% and positive predictive value 72.4% for diagnosing concussion. In football players, SHAAKE had a sensitivity of 52.3%, estimated specificity of 99.9%, positive predictive value of 91.9%, and estimated negative predictive value of 99.5% for diagnosing self-reported concussion. Conclusions: These results demonstrate that nearly three-quarters of athletes reported a SHAAKE associated with a self-reported concussion, which supports the potential for SHAAKE to be used as a concussion screening tool.

Published
2024
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21. Applying the Bradford Hill Criteria for Causation to Repetitive Head Impacts and Chronic Traumatic Encephalopathy

Author

Nowinski, Christopher J, Bureau, Samantha C, Buckland, Michael E, Curtis, Maurice A, Daneshvar, Daniel H, Faull, Richard LM, Grinberg, Lea T, Hill-Yardin, Elisa L, Murray, Helen C, Pearce, Alan J, Suter, Catherine M, White, Adam J, Finkel, Adam M, and Cantu, Robert C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Neurodegenerative, chronic traumatic encephalopathy, repetitive head impact, Bradford Hill, causation, punch drunk, public health, epidemiology, Neurosciences, Psychology, Clinical sciences, Biological psychology
Abstract

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with a history of repetitive head impacts (RHI). CTE was described in boxers as early as the 1920s and by the 1950s it was widely accepted that hits to the head caused some boxers to become "punch drunk." However, the recent discovery of CTE in American and Australian-rules football, soccer, rugby, ice hockey, and other sports has resulted in renewed debate on whether the relationship between RHI and CTE is causal. Identifying the strength of the evidential relationship between CTE and RHI has implications for public health and medico-legal issues. From a public health perspective, environmentally caused diseases can be mitigated or prevented. Medico-legally, millions of children are exposed to RHI through sports participation; this demographic is too young to legally consent to any potential long-term risks associated with this exposure. To better understand the strength of evidence underlying the possible causal relationship between RHI and CTE, we examined the medical literature through the Bradford Hill criteria for causation. The Bradford Hill criteria, first proposed in 1965 by Sir Austin Bradford Hill, provide a framework to determine if one can justifiably move from an observed association to a verdict of causation. The Bradford Hill criteria include nine viewpoints by which to evaluate human epidemiologic evidence to determine if causation can be deduced: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. We explored the question of causation by evaluating studies on CTE as it relates to RHI exposure. Through this lens, we found convincing evidence of a causal relationship between RHI and CTE, as well as an absence of evidence-based alternative explanations. By organizing the CTE literature through this framework, we hope to advance the global conversation on CTE mitigation efforts.

Published
2022

22. Lessons from Detecting Cognitive Impairment Including Dementia (DetectCID) in Primary Care.

Author

Bernstein Sideman, Alissa, Chalmer, Rachel, Ayers, Emmeline, Gershon, Richard, Verghese, Joe, Wolf, Michael, Ansari, Asif, Arvanitis, Marina, Bui, Nhat, Chen, Pei, Chodos, Anna, Corriveau, Roderick, Curtis, Laura, Ehrlich, Amy R, Tomaszewski Farias, Sarah E, Goode, Collette, Hill-Sakurai, Laura, Nowinski, Cindy J, Premkumar, Mukund, Rankin, Katherine P, Ritchie, Christine S, Tsoy, Elena, Weiss, Erica, and Possin, Katherine L

Subjects
Humans, Dementia, Diagnosis, Differential, Cognition Disorders, Aged, Primary Health Care, Cognitive Dysfunction, Cognitive assessment, dementia, detection, diagnosis, implementation evaluation, mild cognitive impairment, primary care, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Behavioral and Social Science, Clinical Research, Brain Disorders, Health Services, Neurodegenerative, Aging, Good Health and Well Being, Clinical Sciences, Neurosciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

BackgroundCognitive impairment, including dementia, is frequently under-detected in primary care. The Consortium for Detecting Cognitive Impairment, including Dementia (DetectCID) convenes three multidisciplinary teams that are testing novel paradigms to improve the frequency and quality of patient evaluations for detecting cognitive impairment in primary care and appropriate follow-up.ObjectiveOur objective was to characterize the three paradigms, including similarities and differences, and to identify common key lessons from implementation.MethodsA qualitative evaluation study with dementia specialists who were implementing the detection paradigms. Data was analyzed using content analysis.ResultsWe identified core components of each paradigm. Key lessons emphasized the importance of engaging primary care teams, enabling primary care providers to diagnose cognitive disorders and provide ongoing care support, integrating with the electronic health record, and ensuring that paradigms address the needs of diverse populations.ConclusionApproaches are needed that address the arc of care from identifying a concern to post-diagnostic management, are efficient and adaptable to primary care workflows, and address a diverse aging population. Our work highlights approaches to partnering with primary care that could be useful across specialties and paves the way for developing future paradigms that improve differential diagnosis of symptomatic cognitive impairment, identifying not only its presence but also its specific syndrome or etiology.

Published
2022

23. Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Author

Moharam, S.A., Abdalasalam, Sabriya, Abdalhadi, Alaa Abdalfattah, Abdalla, Naana Reyam, Abdalla, Walaa, Abdalrheem, Almthani Hamza, Abdalsalam, Ashraf, Abdeewi, Saedah, Abdelgaum, Esraa Hassan, Abdelhalim, Mohamed, Abdelkabir, Mohammed, Abdelrahman, Israa, Abdukahil, Sheryl Ann, Abdulbaqi, Lamees Adil, Abdulhamid, Salaheddin, Abdulhamid, Widyan, Abdulkadir, Nurul Najmee, Abdulwahed, Eman, Abdunabi, Rawad, Abe, Ryuzo, Abel, Laurent, Abodina, Ahmed Mohammed, Abrous, Amal, Absil, Lara, Jabal, Kamal Abu, Salah, Nashat Abu, Abusalama, Abdurraouf, Abuzaid, Tareg Abdallah, Acharya, Subhash, Acker, Andrew, Adam, Elisabeth, Adem, Safia, Ademnou, Manuella, Adewhajah, Francisca, Adrião, Diana, Afum-Adjei Awuah, Anthony, Agbogbatey, Melvin, Al Ageel, Saleh, Ahmed, Aya Mustafa, Ahmed, Musaab Mohammed, Ahmed, Shakeel, Alaraji, Zainab Ahmed, Elhefnawy Enan, Abdulrahman Ahmed, Ahmed Khalil, Reham Abdelhamid, Ahmed Mohamed Abdelaziz, Ali Mostafa, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Aisha, Ali, Aisha, Bugila, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Akwani, Chika, Al Qasim, Eman, Alajeeli, Ahmed, Alali, Ahmed, Alalqam, Razi, Alameen, Aliya Mohammed, Al-Aquily, Mohammed, Alaraji, Zinah A., Albakry, Khalid, Albatni, Safa, Alberti, Angela, Aldabbourosama, Osama, Al-dabbous, Tala, Aldhalia, Amer, Aldoukali, Abdulkarim, Alegesan, Senthilkumar, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al-Fares, Abdulrahman, Alflite, Asil, Alfoudri, Huda, Alhadad, Qamrah, Alhaddad, Hoda Salem, Mohamed Abdalla Alhasan, Maali Khalid, Alhouri, Ahmad Nabil, Alhouri, Hasan, Ali, Adam, Ali, Imran, TagElser Mohammed Ali, Maha, Abbas, Syed Ali, Abdelghafar, Yomna Ali, Sheikh, Naseem Ali, Alidjnou, Kazali Enagnon, Aljadi, Mahmoud, Aljamal, Sarah, Alkahlout, Mohammed, Alkaseek, Akram, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Almasri, Lana, Almjersah, Abdulrahman, Alqandouz, Raja Ahmed, Alrfaea, Walaa, Alrifaee, Moayad, Alsaadi, Rawan, Al-Saba'a, Yousef, Alshareea, Entisar, Alshenawy, Eslam, Altaf, Aneela, Alves, João Melo, Alves, João, Alves, Rita, Cabrita, Joana Alves, Amaral, Maria, Amer, Amro Essam, Amira, Nur, Adusei, Amos Amoako, Amuasi, John, Andini, Roberto, Andrejak, Claire, Angheben, Andrea, Angoulvant, François, Ankrah, Sophia, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, Antunes de Brito, Carlos Alexandre, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Arancibia, Francisco, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean-Benoît, Arnold-Day, Christel, Arora, Lovkesh, Arora, Rakesh, Artaud-Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashley, Elizabeth A., Ashraf, Muhammad, Ashraf, Muhammad Sheharyar, Ben Ashur, Abir, Asiedu-Bekoe, Franklin, Asif, Namra, Asim, Mohammad, Assi, Grace, Assie, Jean Baptiste, Asyraf, Amirul, Atangana, Fouda, Atia, Ahmed, Atif, Minahel, Abdelrhman Abdallahrs, Asia Atif, Atique, Anika, Atlowly, Moad, Attanyake, AM Udara Lakshan, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Ali Mohammed, Abdelmalek Awad, Axelsen, Eyvind W., Ayad, Ared, Hassan Helmi, Ahmed Ayman, Azemar, Laurène, Azizeldin, Mohammed, Azoulay, Cecile, Babatunde, Hakeem, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Bævre-Jensen, Roar, Baig, Nadia, Baillie, John Kenneth, Baird, J Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bakeer, Hibah Bileid, Bakri, Ashraf, Bal, Andriy, Balakrishnan, Mohanaprasanth, Bandoh, Irene, Bani-Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S., Barnett, Saef Umar, Barnikel, Michaela, Barrasa, Helena, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Basmaci, Romain, Basri, Muhammad Fadhli Hassin, Batool, AbdAlkarim, Battaglini, Denise, Bauer, Jules, Bautista Rincon, Diego Fernando, Dow, Denisse Bazan, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Bennett, Suzanne, Bento, Luís, Berdal, Jan-Erik, Berdeweel, Lamis, Bergeaud, Delphine, Bergin, Hazel, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianchi, Isabella, Bianco, Claudia, Bichoka, Sandra, Bidin, Farah Nadiah, Humaid, Felwa Bin, Bin Kamarudin, Mohd Nazlin, Binnawara, Muhannud, Bisoffi, Zeno, Biston, Patrick, Bitker, Laurent, Bittaye, Mustapha, Bitton, Jonathan, Blanco-Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Boccia, Filomena, Bodenes, Laetitia, Bogaert, Debby, Boivin, Anne-Hélène, Bolanga, Ariel, Bolaños, Isabela, Bolze, Pierre-Adrien, Bompart, François, Bonifasius, Aurelius, Bonney, Joe, Borges, Diogo, Borie, Raphaël, Bosse, Hans Martin, Botelho-Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Bountthasavong, Latsaniphone, Boureau, Anne-Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Boyer-Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Brandenburger, Timo, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Dorothy, Breen, Patrick, Brewster, David, Brickell, Kathy, Broadley, Tessa, Brotherton, Helen, Browne, Alex, Brozzi, Nicolas, Brunvoll, Sonja Hjellegjerde, Brusse-Keizer, Marjolein, Bryda, Petra, Buchtele, Nina, Bugaeva, Polina, Buisson, Marielle, Buonsenso, Danilo, Burhan, Erlina, Buri, Donald, Burrell, Aidan, Bustos, Ingrid G., Butnaru, Denis, Cabie, André, Cabral, Susana, Cabrita, Joana, Caceres, Eder, Cadoz, Cyril, Garcês, Rui Caetano, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Canepa, Cecilia, Cantero, Mireia, Caoili, Janice, Caraux-Paz, Pauline, Cárcel, Sheila, Cardoso, Filipa, Cardoso, Filipe, Cardoso, Nelson, Cardoso, Sofia, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie-Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire-Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castañeda, Silvia, Castanheira, Nidyanara, Castor-Alexandre, Guylaine, Castro, Ivo, Catarino, Ana, Catherine, François-Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavalli, Giulio Giovanni, Cavayas, Alexandros, Ceccato, Adrian, Ceesay, Masaneh, Cerkovnik, Shelby, Cervantes-Gonzalez, Minerva, Cevik, Muge, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Chapplain, Jean-Marc, Charpentier, Charlotte, Chas, Julie, Chaudry, Muhammad Mobin, Chávez Iñiguez, Jonathan Samuel, Chen, Anjellica, Chen, Yih-Sharng, Chenard, Léo, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung-Min, Cholley, Bernard, Chommanam, Danoy, Chopin, Marie-Charlotte, Chow, Yock Ping, Chow, Ting Soo, Christy, Nathaniel, Chua, Hiu Jian, Chua, Jonathan, Cidade, Jose Pedro, Cisneros Herreros, José Miguel, Citarella, Barbara Wanjiru, Ciullo, Anna, Clarke, Jennifer, Claure-Del Granado, Rolando, Clohisey, Sara, Codan, Cassidy, Cody, Caitriona, Coles, Jennifer, Coles, Megan, Colin, Gwenhaël, Collins, Michael, Combs, Pamela, Connolly, Jennifer, Connor, Marie, Conrad, Anne, Conway, Elaine, Cooke, Graham S., Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Couffignal, Camille, Couffin-Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Cowan, Juthaporn, Cregan, Rachel, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Csete, Marc, Cullen, Ailbhe, Cummings, Matthew, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al-Awwab, Dagens, Andrew, Dahl, John Arne, Dahly, Darren, D'Alessandro, Umberto, Daley, Peter, Dalloul, Zaina, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Damas, Juliana, Dame, Joycelyn, Damien, Cammandji, Daneman, Nick, Dantas, Jorge, D'Aragon, Frédérick, de Loughry, Gillian, de Mendoza, Diego, De Montmollin, Etienne, França, Rafael Freitas de Oliveira, Isabel de Pinho Oliveira, Ana, De Rosa, Rosanna, De Rose, Cristina, de Silva, Thushan, de Vries, Peter, Deacon, Jillian, Dean, David, Debard, Alexa, DeBenedictis, Bianca, Debray, Marie-Pierre, DeCastro, Nathalie, Dechert, William, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delamou, Alexandre, Delaveuve, Eric, Delavigne, Karen, Delfos, Nathalie M., Deligiannis, Ionna, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhangar, Pathik, Diallo, Alpha, Diallo, Souleymane Taran, Diamantis, Sylvain, Dias, André, Da Silva, Fernanda Dias, Diaz, Rodrigo, Diaz, Juan Jose, Diaz, Priscila, Dibba, Bakary K., Didier, Kévin, Diehl, Jean-Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djadda, Cedric, Djossou, Félix, Docherty, Annemarie B., Doherty, Helen, Dondorp, Arjen M., Donnelly, Christl A., Donohue, Yoann, Donohue, Sean, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Doshi, Yash, Douangdala, Phouvieng, Douglas, James Joshua, Douma, Renee, Dournon, Nathalie, Downey, Joanne, Downing, Mark, Drake, Thomas, Driscoll, Aoife, Duah, Ibrahim Kwaku, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Dubot-Pérès, Audrey, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante-Mangoni, Emanuele, Durham, Lucian, III, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol-Riise, Anne Margarita, Ean, Sim Choon, Ebo, Ada, Echeverria-Villalobos, Marco, Edelstein, Michael, Egan, Siobhan, Eggesbø, Linn Margrete, Ehzaz, Khadeja, Eira, Carla, El Sanharawi, Mohammed, El Sayed, Marwan, Elabid, Mohammed, Elagili, Mohamed Bashir, Elapavaluru, Subbarao, Elbahnasawy, Mohammad, Elboshra, Sohail, Elharrar, Brigitte, Ellerbroek, Jacobien, Ellingjord-Dale, Merete, ELMagrahi, Hamida, Elmubark, Mohammad Muatasm, Elotmani, Loubna, Eloundou, Lauren, Eloy, Philippine, Elshaikhy, Basma, Elshazly, Tarek, Elsokni, Wafa, Eltayeb, Aml Ahmed, Elyazar, Iqbal, Emad, Zarief Kamel, Embarek, Hussein, Enderle, Isabelle, Endo, Tomoyuki, Eneli, Gervais, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Esaadi, Haneen, Esperatti, Mariano, Esperou, Hélène, Santo, Catarina Espírito, Esposito-Farese, Marina, Essaka, Rachel, Essuman, Lorinda, Estevão, João, Etienne, Manuel, Everding, Anna Greti, Evers, Mirjam, Fabre, Isabelle, Fabre, Marc, Fadera, Ismaila, Abdalla Fadlalla, Asgad Osman, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J., Fakar, Zul, Fareed, Komal, Faria, Pedro, Farooq, Ahmed, Fateena, Hanan, Fathi, Mohamed, Fatima, Salem, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François-Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Benigno, Ferreira, Isabel, Ferreira, Bernardo, Ferreira, Sílvia, Ferriere, Nicolas, Ficko, Céline, Figueiredo-Mello, Claudia, Finlayson, William, Flament, Thomas, Fletcher, Tom, Florence, Aline-Marie, Florio, Letizia Lucia, Flynn, Brigid, Flynn, Deirdre, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Fontela, Patricia, Forrest, Karen, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fotso, Berline, Fourn, Erwan, Fowler, Robert A., Fraher, Marianne, Franch-Llasat, Diego, Fraser, Christophe, Fraser, John F., Freire, Marcela Vieira, Ribeiro, Ana Freitas, French, Craig, Friedrich, Caren, Fritz, Ricardo, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, Argin, G., Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean-Charles, Gagneux-Brunon, Amandine, Gai, Abdou, Gaião, Sérgio, Skeie, Linda Gail, Galal Mohamed Ramadan, Adham Mohamed, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Garcia-Diaz, Julia, Garcia-Gallo, Esteban, Garimella, Navya, Garot, Denis, Garrait, Valérie, Gauli, Basanta, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghemmeid, Malak, Ghisulal, Praveen Kumar, Ghosn, Jade, Giani, Marco, Gigante, Tristan, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Giwangkancana, Gezy, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goco, Geraldine, Goehringer, François, Goepel, Siri, Goffard, Jean-Christophe, Goh, Jin Yi, Golács, Brigitta, Golob, Jonathan, Gomez, Kyle, Gómez-Junyent, Joan, Gominet, Marie, Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Graf, Jeronimo, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Grazioli, Lorenzo, Green, Christopher A., Greene, Courtney, Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Grovogui, Fassou Mathias, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guerguerian, Anne-Marie, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Hachemi, Ali, Haddud, Abdurrahman, Hadri, Nadir, Hafez, Wael, Haidri, Fakhir Raza, Rida Hajij, Fatima Mhd, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hamdan, Shaher, Hamdi, Abdelhafeez, Hameed, Jawad, Hamer, Ansley, Hamers, Raph L., Hamidfar, Rebecca, Hammarström, Bato, Hammond, Naomi, Hammond, Terese, Han, Lim Yuen, Hanan, Matly, Haniffa, Rashan, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M., Harrison, Janet, Ekow Harrison, Samuel Bernard, Hartman, Alan, Hasan, Sulieman, Nabil Hasan, Mohammad Ali, Hasan, Mohd Shahnaz, Hashmi, Junaid, Hashmi, Madiha, Hassan, Amoni, Hassanin, Ebtisam, Hayat, Muhammad, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Helmi, Ahmed, Hendry, Ross, Hennessy, Martina, Henriquez-Trujillo, Aquiles Rodrigo, Hentzien, Maxime, Hernandez, Diana, Hershey, Andrew, Hesstvedt, Liv, Hidayah, Astarini, Higgins, Eibhlin, Higgins, Rupert, Hinton, Samuel, Hiraiwa, Hiroaki, Hirkani, Haider, Hitoto, Hikombo, Ho, Antonia, Ho, Yi Bin, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Horcajada, Juan Pablo, Houas, Ikram, Houderi, Mabrouka, Hough, Catherine L., Houltham, Stuart, Ming-Yang Hsu, Jimmy, Hulot, Jean-Sébastien, Hurd, Abby, Hussain, Iqbal, Hussein, Aliae Mohamed, Hussein, Mahmood, Ibrahim, Fatima, Ibran, Bashir, Ijaz, Samreen, Ikram, M. Arfan, Illana, Carlos Cañada, Imbert, Patrick, Ansari, Muhammad Imran, Sikander, Rana Imran, Inácio, Hugo, Dominguez, Carmen Infante, Ing, Yun Sii, Ippolito, Mariachiara, Irawany, Vera, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Istre, Mette Stausland, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jaber, Hamza, Jabot, Julien, Jackson, Clare, Jagne, Abubacarr, Jaureguiberry, Stéphane, Jaworsky, Denise, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Jimbo-Sotomayor, Ruth, Joe, Ong Yiaw, Jorge García, Ruth Noemí, Jørgensen, Silje Bakken, Joseph, Cédric, Joseph, Mark, Joshi, Swosti, Jourdain, Mercé, Jouvet, Philippe, Jung, Anna, Jung, Hanna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalleberg, Karl Trygve, Kalomoiri, Smaragdi, Ayadi Kamaluddin, Muhammad Aisar, Kamano, Armand Saloun, Che Kamaruddin, Zul Amali, Kamarudin, Nadiah, Kamineni, Kavita, Kandamby, Darshana Hewa, Kang, Kong Yeow, Kanwal, Darakhshan, Kanyawati, Dyah, Karghul, Mohamed, Karpayah, Pratap, Karsies, Todd, Kartsonaki, Christiana, Kasugai, Daisuke, Katz, Kevin, Kay, Christy, Kayyali, Lamees, Keating, Seán, Kedia, Pulak, Kelly, Andrea, Kelly, Aoife, Kelly, Claire, Kelly, Niamh, Kelly, Sadie, Kelly, Yvelynne, Kelsey, Maeve, Kennon, Kalynn, Keomany, Sommay, Kernan, Maeve, Kerroumi, Younes, Keshav, Sharma, Khail, Shams, Khaled, Sarah, Khalid, Imrana, Khalil, Antoine, Khan, Irfan, Khan, Quratul Ain, Khanal, Sushil, Khatak, Abid, Kherajani, Krish, Kho, Michelle E., Khoo, Denisa, Khoo, Ryan, Khoo, Saye, Khoso, Muhammad Nasir, Khuwaja, Amin, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kim, Jae Burm, Kimmoun, Antoine, Kindgen-Milles, Detlef, Kitamura, Nobuya, Kjetland Kjetland, Eyrun Floerecke, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R., Kobbe, Robin, Forson, Paa Kobina, Kodippily, Chamira, Vasconcelos, Malte Kohns, Koirala, Sabin, Komatsu, Mamoru, Abebrese, Franklina Korkor, Korten, Volkan, Kouba, Stephanie, Kourouma, Mohamed Lamine, Kourouma, Karifa, Kpangon, Arsène, Krawczyk, Karolina, Kredan, Ali, Krishnan, Vinothini, Krishnan, Sudhir, Kruglova, Oksana, Krund, Anneli, Kuan, Pei Xuan, Kumar, Ashok, Kumar, Deepali, Kumar, Ganesh, Kumar, Mukesh, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrios, Kutsyna, Galyna, Bedu-Addo, Ama Kwakyewaa, Kwedi, Sylvie, Kyriakoulis, Konstantinos, Lachatre, Marie, Lacoste, Marie, Laffey, John G., Lafhej, Nadhem, Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lakhey, Sanjay, Lambert, Marc, Lamontagne, François, Langelot-Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Lath, Sakshi, Latif, Naveed, Latifeh, Youssef, Launay, Odile, Laureillard, Didier, Lavie-Badie, Yoan, Law, Andy, Lawrence, Cassie, Lawrence, Teresa, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, Georges, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Le Mestre, Soizic, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, Leal, Ema, Santos, Marta Leal, Lee, Biing Horng, Lee, Heng Gee, Lee, Su Hwan, Lee, James, Lee, Jennifer, Lee, Todd C., Lee, Yi Lin, Leeming, Gary, Lefebvre, Bénédicte, Lefebvre, Laurent, Lefèvre, Benjamin, LeGac, Sylvie, Lehiste, Merili-Helen, Lelievre, Jean-Daniel, Lellouche, François, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Lennon, Jenny, León, Rafael, Leone, Marc, Lepik, Tanel, Lepiller, Quentin, Lescure, François-Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester-Grant, Amy, Letizia, Andrew, Letrou, Sophie, Levy, Bruno, Levy, Yves, Levy-Marchal, Claire, Lewandowska, Katarzyna, L'Her, Erwan, Bassi, Gianluigi Li, Liang, Janet, Liaquat, Ali, Liegeon, Geoffrey, Lim, Kah Chuan, Lim, Wei Shen, Lima, Chantre, Lina, Bruno, Lina, Lim, Lind, Andreas, Lingad, Maja Katherine, Lingas, Guillaume, Lion-Daolio, Sylvie, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Loforte, Antonio, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez-Colon, Dalia, Loschner, Anthony L., Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Lovelace-Macon, Lara, Lee Low, Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean Christophe, Luna, Carlos M., Lungu, Olguta, Lunn, Miles, Luong, Liem, Luque, Nestor, Luton, Dominique, Maasikas, Olavi, Machado, Moïse, Machado, Sara, Macheda, Gabriel, Magzoub, Mustafa, Mahieu, Rafael, Mahy, Sophie, Maia, Ana Raquel, Maier, Lars S., Ascofare, Oumou Maiga, Maillet, Mylène, Maitre, Thomas, Majeed, Nimisha Abdul, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Maltez, Fernando, Malvy, Denis, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Maráczi, Veronika, Sant′Ana Malaque, Ceila Maria, Marino, Flávio, Markowicz, Samuel, Marques, Ana, Marquis, Catherine, Marsh, Laura, Marsh, Brian, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Dori-Ann, Martin, Emily, Martin-Blondel, Guillaume, Martinelli, Alessandra, Martinez, F. Eduardo, Martin-Loeches, Ignacio, Martinot, Martin, Martín-Quiros, Alejandro, Martins, Ana, Martins, João, Martins, Nuno, Rego, Caroline Martins, Martucci, Gennaro, Martynenko, Olga, Marwali, Eva Miranda, Marzukie, Marsilla, Maslove, David, Mason, Sabina, Masood, Sobia, Masoud, Fatma, Massoma, Moise, Masumbe, Palmer, Mat Nor, Mohd Basri, Matan, Moshe, Fernandes, Henrique Mateus, Mathew, Meghena, Mathew, Christina, Mattei, Mathieu, Maulin, Laurence, May, Juergen, Maynar, Javier, Mayxay, Mayfong, Mazzoni, Thierry, Sweeney, Lisa Mc, McArthur, Colin, McCann, Naina, McCanny, Peter, McCarthy, Aine, McCarthy, Anne, McCloskey, Colin, McConnochie, Rachael, McDermott, Sherry, McDonald, Sarah E., McElroy, Aine, McElwee, Samuel, McEvoy, Natalie, McGeer, Allison, McLean, Kenneth A., McNally, Paul, McNicholas, Bairbre, Meaney, Edel, Mear-Passard, Cécile, Mechlin, Maggie, Medombou, Nastia, Mehkri, Omar, Mele, Ferruccio, Melo, Luis, Memon, Kashif Ali, Mendes, João João, Menkiti, Ogechukwu, Menon, Kusum, Mentré, France, Mentzer, Alexander J., Mercier, Emmanuelle, Mercier, Noémie, Merckx, Antoine, Mergeay-Fabre, Mayka, Mergler, Blake, Merson, Laura, Mesquita, António, Meta, Roberta, Metwally, Osama, Meybeck, Agnès, Meyer, Dan, Meynert, Alison M., Meysonnier, Vanina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Abdullah, Duha Milad, Miller, Jennene, Miranda-Maldonado, Hugo, Misnan, Nor Arisah, Eliza Mohamed, Nik Nur, Mohamed, Nouralsabah, Mohamed, Tahira Jamal, Ads, Alaa Mohamed, Mohamed Elsayed Abdelhalim, Ahmed Reda, Mohammed, Libya, Mohammed Mostafa, Shrouk Fawze, Abdelrahman Mohammedahmed, Manahil Omer, Mohammedelhassan, Omer Abdullah, Moin, Asma, Mokhtar, Walaa, Molinos, Elena, Molloy, Brenda, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Sarah, Moore, Shona C., Cely, Lina Morales, Morgom, Marwa, Moro, Lucia, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mualla, Suleiman Haitham, Muftah, Mohamed, Mufti, Aisha Kalsoom, Muh, Ng Yong, Muhaisen, Mo'nes, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Munblit, Daniel, Ali, Syed Muneeb, Munir, Nadeem, Munshi, Laveena, Murphy, Aisling, Murray, Patrick, Murris, Marlène, Murthy, Srinivas, Musaab, Himed, Mustafa, Alamin, Mustafa, Mus'ab, Mustafa, Dana, Muvindi, Himasha, Myrodia, Dimitra Melia, Mohd-Hanafiah, Farah Nadia, Nadjm, Behzad, Nagpal, Dave, Nagrebetsky, Alex, Nagybányai-Nagy, Blanka, Boudoin, Herwin Nanda, Narasimhan, Mangala, Narayanan, Nageswaran, Nasa, Prashant, Khan, Rashid Nasim, Nasrallah, Ahmad, Nassif Metri, Adel Gerges, Nazerali-Maitland, Alasdair, Neant, Nadège, Neb, Holger, Nekliudov, Nikita, Nelder, Matthew, Nelwan, Erni, Neto, Raul, Neumann, Emily, Ng, Wing Yiu, Ng, Pauline Yeung, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Niba, Nerissa, Nichol, Alistair D., Nitayavardhana, Prompak, Nonas, Stephanie, Mohd Noordin, Nurul Amani, Izzati Norharizam, Nurul Faten, North, Anita, Notari, Alessandra, Noursadeghi, Mahdad, Nowinski, Adam, Nseir, Saad, Numfor, Leonard, Nurnaningsih, Nurnaningsih, Nusantara, Dwi Utomo, Nyamankolly, Elsa, Nygaard, Anders Benteson, Brien, Fionnuala O., Callaghan, Annmarie O., O'Callaghan, Annmarie, Occhipinti, Giovanna, OConnor, Derbrenn, O'Donnell, Max, Ofori-Boadu, Lawrence, Ogston, Tawnya, Ogura, Takayuki, Oh, Tak-Hyuk, O'Halloran, Sophie, O'Hearn, Katie, Ohene, Sally-Ann, Ohshimo, Shinichiro, Oliveira, João, Oliveira, Larissa, Olliaro, Piero L., Rageh Elnaggar, Cinderella Omar, Mohammed Omer, Alsarrah Ali, Ondobo, Pierre, Ong, David S.Y., Ong, Jee Yan, Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orakzai, Saijad, Orozco-Chamorro, Claudia Milena, Ortoleva, Jamel, Elsayed Soliman, Mohamed Osama, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Eman, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Owusu, Micheal, Owusu-Asare, Ama Akyampomaa, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palacios, Amanda, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Paneru, Hem, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Parker, Melissa, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Patel, Drashti, Pathmanathan, Mohan Dass, Patrão, Luís, Patricio, Patricia, Patterson, Lisa, Pattnaik, Rajyabardhan, Paul, Christelle, Paul, Mical, Paulos, Jorge, Paxton, William A., Payen, Jean-François, Peake, Sandra L., Peariasamy, Kalaiarasu, Peek, Giles J., Peelman, Florent, Peiffer-Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D., Pereira, Rui, Perez, Daniel, Perpoint, Thomas, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov-Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gilles, Philips, Richard Odame, Phonemixay, Ooyanong, Phoutthavong, Soulichanya, Piagnerelli, Michael, Picard, Walter, Picone, Olivier, de Piero, Maria, Piersma, Djura, Pimentel, Carlos, Pinto, Raquel, Pires, Catarina, Piroth, Lionel, Pitaloka, Ayodhia, Piubelli, Chiara, Pius, Riinu, Piva, Simone, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Poli, Sergio, Pollakis, Georgios, Ponscarme, Diane, Porto, Diego Bastos, Post, Andra-Maris, Postma, Douwe F., Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Praphasiri, Viladeth, Preau, Sébastien, Prebensen, Christian, Preiser, Jean-Charles, Prinssen, Anton, Pritchard, Mark G., Dilanthi Priyadarshani, Gamage Dona, Proença, Lucia, Pudota, Sravya, Semedi, Bambang Pujo, Pulicken, Mathew, Puplampu, Peter, Purcell, Gregory, Quesada, Luisa, Quinones-Cardona, Vilmaris, Quist-Paulsen, Else, Quraishi, Mohammed, Qutishat, Fadi, Rabaa, Maia, Rabaud, Christian, Rabindrarajan, Ebenezer, Rafael, Aldo, Rafiq, Marie, Ragab, Abdelrahman, Rahardjani, Mutia, Ullah, Arslan Rahat, Haji Ab Rahman, Ahmad Kashfi, Rahman, Rozanah Abd, Rainieri, Fernando, Rajahram, Giri Shan, Ramachandran, Pratheema, Ramakrishnan, Nagarajan, Ramalho, José, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Rana, Asim, Rangappa, Rajavardhan, Ranjan, Ritika, Rapp, Christophe, Rashan, Aasiyah, Rashan, Thalha, Rasheed, Ghulam, Rasmin, Menaldi, Rätsep, Indrek, Rau, Cornelius, Ravi, Tharmini, Raza, Ali, Real, Andre, Rebaudet, Stanislas, Redl, Sarah, Reeve, Brenda, Rehman, Attaur, Rehman Khalid, Muhammad Osama, Reikvam, Dag Henrik, Reis, Renato, Rello, Jordi, Remppis, Jonathan, Remy, Martine, Ren, Hongru, Renk, Hanna, Resseguier, Anne-Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Luis Felipe, Ribeiro, Maria Ines, Ricchiuto, Antonia, Richardson, David, Richardson, Denise, Richier, Laurent, Atikah Ahmad Ridzuan, Siti Nurul, Rios, Ana L., Rishu, Asgar, Rispal, Patrick, Risso, Karine, Rivera Nuñez, Maria Angelica, Robba, Chiara, Roberto, André, Roberts, Stephanie, Roberts, Charles, Robertson, David L., Robineau, Olivier, Roca, Anna, Roche-Campo, Ferran, Rodari, Paola, Rodeia, Simão, Roessler, Bernhard, Roger, Claire, Roger, Pierre-Marie, Rojek, Amanda, Roncon-Albuquerque, Roberto, Jr., Roriz, Mélanie, Rosa-Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Patrick, Roy, Carine, Roze, Benoît, Rusmawatiningtyas, Desy, Russell, Clark D., Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadaf, Sairah, Sadat, Musharaf, Sahraei, Valla, Said, Abdurraouf, Saidani, Nadia, Sakiyalak, Pranya, Sako, Fodé Bangaly, Salah, Moamen, Salah Eldin Mohamed Abbas, Ali Alaa, Salahuddin, Nawal, Salazar, Leonardo, Saleem, Jodat, Alyasiri, Mohammed Saleh, Abu Salem, Talat Ahmed, Sales, Gabriele, Gandonniere, Charlotte Salmon, Salvator, Hélène, Samardali, Dana, Samardali, Shaden, Shaaban Aly Orabi, Yehia Samir, Sanchez, Emely, Sanchez, Olivier, Sanchez de Oliveira, Kizy, Sanchez-Miralles, Angel, Sancho-Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre-François, Săndulescu, Oana, Santos, Marlene, Sarfo-Mensah, Shirley, Banheiro, Bruno Sarmento, Sarmiento, Iam Claire E., Sarton, Benjamine, Satya, Ankana, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schnur, János, Schroll, Stephan, Schwameis, Michael, Schwartz, Gary, Scott, Janet T., Scott-Brown, James, Sedillot, Nicholas, Seitz, Tamara, Selvanayagam, Jaganathan, Selvarajoo, Mageswari, Semple, Malcolm G., Senian, Rasidah Bt, Senneville, Eric, Sepulveda, Claudia, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shahla, Hamza, Shalabi, Laila, Shames, Haitam, Shankar, Anuraj, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A., Shaw, Victoria, Sheenan, John Robert, Mohan Shetty, Dr. Rajesh, Shetty, Rohan, Shiekh, Mohiuddin, Shime, Nobuaki, Shimizu, Keiki, Shrapnel, Sally, Shrestha, Shubha Kalyan, Shrestha, Pramesh Sundar, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Siaw-Frimpong, Moses, Sibiude, Jeanne, Sibounheuang, Bountoy, Siddig, Nidhal, Siddiqui, Atif, Siddiqui, Maqsood Ahmed, Sigfrid, Louise, Sillah, Fatoumata, Sillaots, Piret, Silva, Catarina, Silva, Maria Joao, Silva, Rogério, Lim Heng, Benedict Sim, Sin, Wai Ching, Sinatti, Dario, Singh, Mahendra, Singh, Punam, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solberg, Lene Bergendal, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnès, Song, Myung Jin, Song, Rima, Song, Tae, Chia, Jack Song, Søraas, Arne, Sotto, Albert, Soum, Edouard, Sousa, Ana Chora, Sousa, Marta, Uva, Maria Sousa, Souza-Dantas, Vicente, Sow, Mamadou Saliou, Sperry, Alexandra, Spinuzza, Elisabetta, Ruwan Sri Darshana, B. P. Sanka, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thomas, Stecher, Stephanie-Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu-Cercel, Anca, Streinu-Cercel, Adrian, Strong, Geoff, Stuart, Ami, Stuart, David, Su, Richa, Subekti, Decy, Suen, Gabriel, Suen, Jacky Y., Sukumar, Prasanth, Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Suwarti, Atie, Svistunov, Andrey, Syahrin, Sarah, Sylverken, Augustina, Syrigos, Konstantinos, Sztajnbok, Jaques, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S., Tagherset, Lysa, Taib, Shahdattul Mawarni, Taleb, Sara, Talla, Cheikh, Talsma, Jelmer, Tamisier, Renaud, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Hiroyuki, Tanaka, Taku, Taniguchi, Hayato, Taqdees, Huda, Taqi, Arshad, Tardivon, Coralie, Kamal Mostafa, Yousef Tarek, Tarhabat, Ali, Tattevin, Pierre, Taufik, M Azhari, Tawfik, Hassan, Tee, Tze Yuan, Teixeira, João, Tejada, Sofia, Tellier, Marie-Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, François, Terrier, Olivier, Terzi, Nicolas, Tessier-Grenier, Hubert, Tey, Adrian, Mohd Thabit, Alif Adlan, Thakur, Anand, Tham, Zhang Duan, Thangavelu, Suvintheran, Theron, Elmi, Thibault, Vincent, Thiberville, Simon-Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Niamh, Thompson, Shaun, Thomson, Emma C., Thomson, David, Thorpe, Mathew, Thurai, Surain Raaj Thanga, Thwaites, Ryan S., Tierney, Paul, Tieroshyn, Vadim, Timashev, Peter S., Timsit, Jean-François, Tirupakuzhi Vijayaraghavan, Bharath Kumar, Tissot, Noémie, Toal, Fiona, Yang Toh, Jordan Zhien, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torre, Marta, Torres, Antoni, Torres, Margarida, Santos-Olmo, Rosario Maria Torres, Torres-Zevallos, Hernando, Tounkara, Aboubacar, Towers, Michael, Traoré, Fodé Amara, Trapani, Tony, Tromeur, Cécile, Trontzas, Ioannis, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turgeon, Alexis F., Turmel, Jean-Marie, Turtle, Lance C.W., Tveita, Anders, Twardowski, Pawel, Uchiyama, Makoto, Udayanga, PG Ishara, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad, Usuf, Effua, Uyeki, Timothy M., Vajdovics, Cristinava, Valentini, Piero, Val-Flores, Luís, Van de Velde, Stijn, van den Berge, Marcel, van der Feltz, Machteld, van der Palen, Job, van der Valk, Paul, Van Der Vekens, Nicky, Van der Voort, Peter, Van Der Werf, Sylvie, van Gulik, Laura, Van Hattem, Jarne, van Netten, Carolien, van Veen, Ilonka, Vanel, Noémie, Vanoverschelde, Henk, Varrone, Michael, Vasudayan, Shoban Raj, Vauchy, Charline, Vecham, Pavan Kumar, Veeran, Shaminee, Veislinger, Aurélie, Vencken, Sebastian, Ventura, Sara, Verbon, Annelies, Vidal, José Ernesto, Vieira, César, Vijayan, Deepak, Villar, Judit, Villeneuve, Pierre-Marc, Villoldo, Andrea, Vishwanathan, Gayatri, Visseaux, Benoit, Visser, Hannah, Vitiello, Chiara, Vongsouvath, Manivanh, Vonkeman, Harald, Vuotto, Fanny, Wahab, Suhaila Abdul, Wahab, Noor Hidayu, Wahid, Nadirah Abdul, Wainstein, Marina, Walsh, Laura, Shukeri, Wan Fadzlina Wan Muhd, Wang, Chih-Hsien, Webb, Steve, Wei, Jia, Weil, Katharina, Wen, Tan Pei, Wesam, Hassi, Wesselius, Sanne, West, T. Eoin, Wham, Murray, Whelan, Bryan, White, Nicole, Wicky, Paul Henri, Wiedemann, Aurélie, Wijaya, Surya Otto, Wille, Keith, Willems, Sue, Williams, Bailey, Williams, Patricia J., Williams, Virginie, Wils, Evert-Jan, Wittman, Jessica, Wong, Calvin, Wong, Xin Ci, Wong, Yew Sing, Wong, Teck Fung, Wright, Natalie, Xian, Lim Saio, Xynogalas, Ioannis, Binti Mohd Yakop, Siti Rohani, Yamazaki, Masaki, Yarad, Elizabeth, Yazdanpanah, Yazdan, Hing, Nicholas Yee Liang, Mahmoud Abdelaal, Abdelrahman Yehia, Yelnik, Cécile, Yeoh, Chian Hui, Yerkovich, Stephanie, Yiaye, Touxiong, Yokoyama, Toshiki, Yonis, Hodane, Yousif, Obada, Yuliarto, Saptadi, Zaaqoq, Akram, Zabbe, Marion, Zabert, Gustavo E., Zacharowski, Kai, Zahid, Masliza, Zahran, Maram, Binti Zaidan, Nor Zaila, Zambon, Maria, Zambrano, Miguel, Zanella, Alberto, Zaynah, Nurul, Zayyad, Hiba, Zoufaly, Alexander, Zucman, David, Ibáñez-Prada, Elsa D., Gonçalves, Bronner P., Baruch, Joaquin, Escher, Martina, Philippy, Fred, Kutsogiannis, Demetrios James, Vaillant, Michel, and Olliaro, Piero

Published
2024
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26. Protocol for a construct and clinical validation study of MyCog Mobile: a remote smartphone-based cognitive screener for older adults

Author

Michael Wolf, Laura M Curtis, Richard Gershon, Julia Yoshino Benavente, Greg J Byrne, Maria Varela Diaz, Lihua Yao, Cindy Nowinski, Stephanie Ruth Young, Elizabeth McManus Dworak, and Callie Madison Jones

Subjects
Medicine
Abstract

Introduction Annual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. A remote cognitive screener completed on a patient’s personal smartphone before a visit has the potential to save primary care clinics time, encourage broader screening practices and increase early detection of cognitive decline. MyCog Mobile is a promising new remote smartphone-based cognitive screening app for primary care settings. We propose a combined construct and clinical validation study of MyCog Mobile.Methods and analysis We will recruit a total sample of 300 adult participants aged 65 years and older. A subsample of 200 healthy adult participants and a subsample of 100 adults with a cognitive impairment diagnosis (ie, dementia, mild cognitive impairment, cognitive deficits or other memory loss) will be recruited from the general population and specialty memory care centres, respectively. To evaluate the construct validity of MyCog Mobile, the healthy control sample will self-administer MyCog Mobile on study-provided smartphones and be administered a battery of gold-standard neuropsychological assessments. We will compare correlations between performance on MyCog Mobile and measures of similar and dissimilar constructs to evaluate convergent and discriminant validity. To assess clinical validity, participants in the clinical sample will self-administer MyCog Mobile on a smartphone and be administered a Mini-Cog screener and these data will be combined with the healthy control sample. We will then apply several supervised model types to determine the best predictors of cognitive impairment within the sample. Area under the receiver operating characteristic curve, accuracy, sensitivity and specificity will be the primary performance metrics for clinical validity.Ethics and dissemination The Institutional Review Board at Northwestern University (STU00214921) approved this study protocol. Results will be published in peer-reviewed journals and summaries provided to the study’s funders.

Published
2024
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27. Prediction of cognitive impairment using higher order item response theory and machine learning models

Author

Lihua Yao, Yusuke Shono, Cindy Nowinski, Elizabeth M. Dworak, Aaron Kaat, Shirley Chen, Rebecca Lovett, Emily Ho, Laura Curtis, Michael Wolf, Richard Gershon, and Julia Yoshino Benavente

Subjects
MyCog, NIH Toolbox, machine learning, deep learning, IRT, higher order item response theory, Psychiatry, RC435-571
Abstract

Timely detection of cognitive impairment (CI) is critical for the wellbeing of elderly individuals. The MyCog assessment employs two validated iPad-based measures from the NIH Toolbox® for Assessment of Neurological and Behavioral Function (NIH Toolbox). These measures assess pivotal cognitive domains: Picture Sequence Memory (PSM) for episodic memory and Dimensional Change Card Sort Test (DCCS) for cognitive flexibility. The study involved 86 patients and explored diverse machine learning models to enhance CI prediction. This encompassed traditional classifiers and neural-network-based methods. After 100 bootstrap replications, the Random Forest model stood out, delivering compelling results: precision at 0.803, recall at 0.758, accuracy at 0.902, F1 at 0.742, and specificity at 0.951. Notably, the model incorporated a composite score derived from a 2-parameter higher order item response theory (HOIRT) model that integrated DCCS and PSM assessments. The study's pivotal finding underscores the inadequacy of relying solely on a fixed composite score cutoff point. Instead, it advocates for machine learning models that incorporate HOIRT-derived scores and encompass relevant features such as age. Such an approach promises more effective predictive models for CI, thus advancing early detection and intervention among the elderly.

Published
2024
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28. Impact of Li$_{2.9}$B$_{0.9}$S$_{0.1}$O$_{3.1}$ glass additive on the structure and electrical properties of the LATP-based ceramics

Author

Kwatek, K., Ślubowska, W., Trébosc, J., Lafon, O., and Nowiński, J. L.

Subjects
Physics - Chemical Physics
Abstract

The existing solid electrolytes for lithium ion batteries suffer from low total ionic conductivity, which restricts its usefulness for the lithium-ion battery technology. Among them, the NASICON-based materials, such as Li1.3Al0.3Ti1.7(PO4)3 (LATP) exhibit low total ionic conductivity due to highly resistant grain boundary phase. One of the possible approaches to efficiently enhance their total ionic conductivity is the formation of a composite material. Herein, the Li2.9B0.9S0.1O3.1 glass, called LBSO hereafter, was chosen as an additive material to improve the ionic properties of the ceramic Li1.3Al0.3Ti1.7(PO4)3 base material. The properties of this Li1.3Al0.3Ti1.7(PO4)3-xLi2.9B0.9S0.1O3.1 (0 < x < 0.3) system have been studied by means of high temperature X-ray diffractometry (HTXRD), 7Li, 11B, 27Al and 31P magic angle spinning nuclear magnetic resonance spectroscopy (MAS NMR), thermogravimetry (TG), scanning electron microscopy (SEM), impedance spectroscopy (IS) and density methods. We show here that the introduction of the foreign LBSO phase enhances their electric properties. This study reveals several interesting correlations between the apparent density, the microstructure, the composition, the sintering temperature and the ionic conductivity. Moreover, the electrical properties of the composites will be discussed in the terms of the brick-layer model (BLM). The highest value of {\sigma}tot = 1.5 x 10-4 Scm-1 has been obtained for LATP-0.1LBSO material sintered at 800{\deg}C.

Published
2020
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29. Leveraging football accelerometer data to quantify associations between repetitive head impacts and chronic traumatic encephalopathy in males

Author

Daneshvar, Daniel H., Nair, Evan S., Baucom, Zachary H., Rasch, Abigail, Abdolmohammadi, Bobak, Uretsky, Madeline, Saltiel, Nicole, Shah, Arsal, Jarnagin, Johnny, Baugh, Christine M., Martin, Brett M., Palmisano, Joseph N., Cherry, Jonathan D., Alvarez, Victor E., Huber, Bertrand R., Weuve, Jennifer, Nowinski, Christopher J., Cantu, Robert C., Zafonte, Ross D., Dwyer, Brigid, Crary, John F., Goldstein, Lee E., Kowall, Neil W., Katz, Douglas I., Stern, Robert A., Tripodis, Yorghos, Stein, Thor D., McClean, Michael D., Alosco, Michael L., McKee, Ann C., and Mez, Jesse

Published
2023
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30. Intranasal Oxytocin in Children and Adolescents with Autism Spectrum Disorder

Author

Sikich, Linmarie, Kolevzon, Alexander, King, Bryan H, McDougle, Christopher J, Sanders, Kevin B, Kim, Soo-Jeong, Spanos, Marina, Chandrasekhar, Tara, Trelles, MD Pilar, Rockhill, Carol M, Palumbo, Michelle L, Witters Cundiff, Allyson, Montgomery, Alicia, Siper, Paige, Minjarez, Mendy, Nowinski, Lisa A, Marler, Sarah, Shuffrey, Lauren C, Alderman, Cheryl, Weissman, Jordana, Zappone, Brooke, Mullett, Jennifer E, Crosson, Hope, Hong, Natalie, Siecinski, Stephen K, Giamberardino, Stephanie N, Luo, Sheng, She, Lilin, Bhapkar, Manjushri, Dean, Russell, Scheer, Abby, Johnson, Jacqueline L, Gregory, Simon G, and Veenstra-VanderWeele, Jeremy

Subjects
Biomedical and Clinical Sciences, Brain Disorders, Neurosciences, Clinical Trials and Supportive Activities, Clinical Research, Pediatric, Intellectual and Developmental Disabilities (IDD), Mental Health, Autism, Behavioral and Social Science, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Mental health, Administration, Intranasal, Adolescent, Autism Spectrum Disorder, Child, Child, Preschool, Double-Blind Method, Female, Humans, Least-Squares Analysis, Male, Oxytocin, Social Behavior, Social Skills, Treatment Failure, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundExperimental studies and small clinical trials have suggested that treatment with intranasal oxytocin may reduce social impairment in persons with autism spectrum disorder. Oxytocin has been administered in clinical practice to many children with autism spectrum disorder.MethodsWe conducted a 24-week, placebo-controlled phase 2 trial of intranasal oxytocin therapy in children and adolescents 3 to 17 years of age with autism spectrum disorder. Participants were randomly assigned in a 1:1 ratio, with stratification according to age and verbal fluency, to receive oxytocin or placebo, administered intranasally, with a total target dose of 48 international units daily. The primary outcome was the least-squares mean change from baseline on the Aberrant Behavior Checklist modified Social Withdrawal subscale (ABC-mSW), which includes 13 items (scores range from 0 to 39, with higher scores indicating less social interaction). Secondary outcomes included two additional measures of social function and an abbreviated measure of IQ.ResultsOf the 355 children and adolescents who underwent screening, 290 were enrolled. A total of 146 participants were assigned to the oxytocin group and 144 to the placebo group; 139 and 138 participants, respectively, completed both the baseline and at least one postbaseline ABC-mSW assessments and were included in the modified intention-to-treat analyses. The least-squares mean change from baseline in the ABC-mSW score (primary outcome) was -3.7 in the oxytocin group and -3.5 in the placebo group (least-squares mean difference, -0.2; 95% confidence interval, -1.5 to 1.0; P = 0.61). Secondary outcomes generally did not differ between the trial groups. The incidence and severity of adverse events were similar in the two groups.ConclusionsThis placebo-controlled trial of intranasal oxytocin therapy in children and adolescents with autism spectrum disorder showed no significant between-group differences in the least-squares mean change from baseline on measures of social or cognitive functioning over a period of 24 weeks. (Funded by the National Institute of Child Health and Human Development; SOARS-B ClinicalTrials.gov number, NCT01944046.).

Published
2021

32. Remote Self-Administration of Cognitive Screeners for Older Adults Prior to a Primary Care Visit: Pilot Cross-Sectional Study of the Reliability and Usability of the MyCog Mobile Screening App

Author

Stephanie Ruth Young, Elizabeth McManus Dworak, Greg Joseph Byrne, Callie Madison Jones, Lihua Yao, Julia Noelani Yoshino Benavente, Maria Varela Diaz, Laura Curtis, Richard Gershon, Michael Wolf, and Cindy J Nowinski

Subjects
Medicine
Abstract

BackgroundRoutine cognitive screening is essential in the early detection of dementia, but time constraints in primary care settings often limit clinicians’ ability to conduct screenings. MyCog Mobile is a newly developed cognitive screening system that patients can self-administer on their smartphones before a primary care visit, which can help save clinics’ time, encourage broader screening practices, and increase early detection of cognitive decline. ObjectiveThe goal of this pilot study was to examine the feasibility, acceptability, and initial psychometric properties of MyCog Mobile. Research questions included (1) Can older adults complete MyCog Mobile remotely without staff support? (2) Are the internal consistency and test-retest reliability of the measures acceptable? and (3) How do participants rate the user experience of MyCog Mobile? MethodsA sample of adults aged 65 years and older (N=51) self-administered the MyCog Mobile measures remotely on their smartphones twice within a 2- to 3-week interval. The pilot version of MyCog Mobile includes 4 activities: MyFaces measures facial memory, MySorting measures executive functioning, MySequences measures working memory, and MyPictures measures episodic memory. After their first administration, participants also completed a modified version of the Simplified System Usability Scale (S-SUS) and 2 custom survey items. ResultsAll participants in the sample passed the practice items and completed each measure. Findings indicate that the Mobile Toolbox assessments measure the constructs well (internal consistency 0.73 to 0.91) and are stable over an approximately 2-week delay (test-retest reliability 0.61 to 0.71). Participants’ rating of the user experience (mean S-SUS score 73.17, SD 19.27) indicated that older adults found the usability of MyCog Mobile to be above average. On free-response feedback items, most participants provided positive feedback or no feedback at all, but some indicated a need for clarity in certain task instructions, concerns about participants’ abilities, desire to be able to contact a support person or use in-app technical support, and desire for additional practice items. ConclusionsPilot evidence suggests that the MyCog Mobile cognitive screener can be reliably self-administered by older adults on their smartphones. Participants in our study generally provided positive feedback about the MyCog Mobile experience and rated the usability of the app highly. Based on participant feedback, we will conduct further usability research to improve support functionality, optimize task instructions and practice opportunities, and ensure that patients feel comfortable using MyCog Mobile. The next steps include a clinical validation study that compares MyCog Mobile to gold-standard assessments and tests the sensitivity and specificity of the measures for identifying dementia.

Published
2024
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33. Phosphate starvation signaling increases mitochondrial membrane potential through respiration-independent mechanisms

Author

Yeyun Ouyang, Mi-Young Jeong, Corey N Cunningham, Jordan A Berg, Ashish G Toshniwal, Casey E Hughes, Kristina Seiler, Jonathan G Van Vranken, Ahmad A Cluntun, Geanette Lam, Jacob M Winter, Emel Akdogan, Katja K Dove, Sara M Nowinski, Matthew West, Greg Odorizzi, Steven P Gygi, Cory D Dunn, Dennis R Winge, and Jared Rutter

Subjects
mitochondria, mitochondrial membrane potential, phosphate, Medicine, Science, Biology (General), QH301-705.5
Abstract

Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both by inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of mitochondrial membrane potential is observed in primary and immortalized mammalian cells as well as in Drosophila. These data suggest that mitochondrial membrane potential is subject to environmental stimuli and intracellular signaling regulation and raise the possibility for therapeutic enhancement of mitochondrial function even in defective mitochondria.

Published
2024
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34. Structural and electrical properties of ceramic Li-ion conductors based on Li$_{1.3}$Al$_{0.3}$Ti$_{1.7}$(PO$_4$)$_3$-LiF

Author

Kwatek, K., Ślubowska, W., Trébosc, J., Lafon, O., and Nowiński, J.

Subjects
Physics - Chemical Physics, Condensed Matter - Materials Science
Abstract

The work presents the investigations of Li1.3Al0.3Ti1.7(PO4)3-xLiF Li-ion conducting ceramics with 0 < x < 0.3 by means of X-ray diffractometry (XRD), 7Li, 19F, 27Al and 31P Magic Angle Spinning Nuclear Magnetic Resonance (MAS NMR) spectroscopy, thermogravimetry (TG), scanning electron microscopy (SEM), impedance spectroscopy (IS) and density method. It has been shown that the total ionic conductivity of both as-prepared and ceramic Li1.3Al0.3Ti1.7(PO4)3 is low due to a grain boundary phase exhibiting high electrical resistance. This phase consists mainly of berlinite crystalline phase as well as some amorphous phase containing Al3+ ions. The electrically resistant phases of the grain boundary decompose during sintering with LiF additive. The processes leading to microstructure changes and their effect on the ionic properties of the materials are discussed in the frame of the brick layer model (BLM). The highest total ionic conductivity at room temperature was measured for LATP-0.1LiF ceramic sintered at 800{\deg}C and was equal to {\sigma}tot = 1.1 x 10-4 Scm-1.

Published
2019
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35. Late fusion of deep learning and hand-crafted features for Achilles tendon healing monitoring

Author

Kapinski, Norbert, Nowosielski, Jedrzej M., Marchwiany, Maciej E., Zielinski, Jakub, Ciszkowska-Lyson, Beata, Borucki, Bartosz A., Trzcinski, Tomasz, and Nowinski, Krzysztof S.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Healing process assessment of the Achilles tendon is usually a complex procedure that relies on a combination of biomechanical and medical imaging tests. As a result, diagnostics remains a tedious and long-lasting task. Recently, a novel method for the automatic assessment of tendon healing based on Magnetic Resonance Imaging and deep learning was introduced. The method assesses six parameters related to the treatment progress utilizing a modified pre-trained network, PCA-reduced space, and linear regression. In this paper, we propose to improve this approach by incorporating hand-crafted features. We first perform a feature selection in order to obtain optimal sets of mixed hand-crafted and deep learning predictors. With the use of approx. 20,000 MRI slices, we then train a meta-regression algorithm that performs the tendon healing assessment. Finally, we evaluate the method against scores given by an experienced radiologist. In comparison with the previous baseline method, our approach significantly improves correlation in all of the six parameters assessed. Furthermore, our method uses only one MRI protocol and saves up to 60\% of the time needed for data acquisition., Comment: Paper accepted to MICCAI'19 MSKI workshop

Published
2019

36. Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks

Author

Woznicki, Piotr, Przybyszewski, Przemyslaw, Kapinski, Norbert, Zielinski, Jakub, Ciszkowska-Lyson, Beata, Borucki, Bartosz A., Trzcinski, Tomasz, and Nowinski, Krzysztof S.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Quantitative Methods
Abstract

Achilles tendon rupture is a debilitating injury, which is typically treated with surgical repair and long-term rehabilitation. The recovery, however, is protracted and often incomplete. Diagnosis, as well as healing progress assessment, are largely based on ultrasound and magnetic resonance imaging. In this paper, we propose an automatic method based on deep learning for analysis of Achilles tendon condition and estimation of its healing progress on ultrasound images. We develop custom convolutional neural networks for classification and regression on healing score and feature extraction. Our models are trained and validated on an acquired dataset of over 250.000 sagittal and over 450.000 axial ultrasound slices. The obtained estimates show a high correlation with the assessment of expert radiologists, with respect to all key parameters describing healing progress. We also observe that parameters associated with i.a. intratendinous healing processes are better modeled with sagittal slices. We prove that ultrasound imaging is quantitatively useful for clinical assessment of Achilles tendon healing process and should be viewed as complementary to magnetic resonance imaging., Comment: Paper accepted to MICCAI'19 SUSI workshop

Published
2019
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37. Properties of LiMnBO3 glasses and nanostructured glass-ceramics

Author

Michalski, P. P., Gołębiewska, A., Trébosc, J., Lafon, O., Pietrzak, T. K., Ryl, J., Nowiński, J. L., Wasiucionek, M., and Garbarczyk, J. E.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Soft Condensed Matter
Abstract

Polycrystalline LiMnBO3 is a promising cathode material for Li-ion batteries. In this work, we investigated the thermal, structural and electrical properties of glassy and nanocrystallized materials having the same chemical composition. The original glass was obtained via a standard meltquenching method. SEM and 7Li solid-state NMR indicate that it contains a mixture of two distinct glassy phases. The results suggest that the electrical conductivity of the glass is dominated by the ionic one. The dc conductivity of initial glass was estimated to be in the order of 10-18 S.cm-1 at room temperature. The thermal nanocrystallization of the glass produces a nanostructured glass-ceramics containing MnBO3 and LiMnBO3 phases. The electric conductivity of this glass-ceramics is increased by 6 orders of magnitude, compared to the starting material at room temperature. Compared to other manganese and borate containing glasses reported in the literature, the conductivity of the nanostructured glass ceramics is higher than that of the previously reported glassy materials. Such improved conductivity stems from the facilitated electronic transport along the grain boundaries.

Published
2019
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38. The NIH Toolbox: Overview of Development for Use with Hispanic Populations

Author

Gershon, Richard C, Fox, Rina S, Manly, Jennifer J, Mungas, Dan M, Nowinski, Cindy J, Roney, Ellen M, and Slotkin, Jerry

Subjects
Biomedical and Clinical Sciences, Health Sciences, Psychology, Basic Behavioral and Social Science, Behavioral and Social Science, Cognition, Culturally Competent Care, Hispanic or Latino, Humans, Language, National Institutes of Health (U.S.), Neuropsychological Tests, Translations, United States, Assessment, Culturally competent care, Hispanic Americans, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveHispanics/Latinos are the largest and fastest-growing minority population in the United States. To facilitate appropriate outcome assessment of this expanding population, the NIH Toolbox for Assessment of Neurological and Behavioral Function® (NIH Toolbox®) was developed with particular attention paid to the cultural and linguistic needs of English- and Spanish-speaking Hispanics/Latinos.MethodsA Cultural Working Group ensured that all included measures were appropriate for use with Hispanics/Latinos in both English and Spanish. In addition, a Spanish Language Working Group assessed all English-language NIH Toolbox measures for translatability.ResultsMeasures were translated following the Functional Assessment of Chronic Illness Therapy (FACIT) translation methodology for instances where language interpretation could impact scores, or a modified version thereof for more simplified translations. The Spanish versions of the NIH Toolbox Cognition Battery language measures (i.e., Picture Vocabulary Test, Oral Reading Recognition Test) were developed independently of their English counterparts.ConclusionsThe Spanish-language version of the NIH Toolbox provides a much-needed set of tools that can be selected as appropriate to complement existing protocols being conducted with the growing Hispanic/Latino population in the United States.

Published
2020

39. Thrombotic and hemorrhagic complications of COVID-19 in adults hospitalized in high-income countries compared with those in adults hospitalized in low- and middle-income countries in an international registry

Author

Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Acker, Andrew, Adam, Elisabeth, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Akwani, Chika, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al-dabbous, Tala, Alegesan, Senthilkumar, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al-Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Alves, João, Alves, Rita, Alves, João Melo, Cabrita, Joana Alves, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, François, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, de Brito, Carlos Alexandre Antunes, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Arancibia, Francisco, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean-Benoît, Arnold-Day, Christel, Arora, Lovkesh, Arora, Rakesh, Artaud-Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Assie, Jean Baptiste, Asyraf, Amirul, Atif, Minahel, Atique, Anika, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Baig, Nadia, Baillie, J. Kenneth, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani-Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S., Barnett, Saef Umar, Barnikel, Michaela, Barrasa, Helena, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Basmaci, Romain, Basri, Muhammad Fadhli Hassin, Battaglini, Denise, Bauer, Jules, Rincon, Diego Fernando Bautista, Beane, Abigail, Bedossa, Alexandra, Hong Bee, Ker, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Benny, Binny, Bento, Luís, Berdal, Jan-Erik, Bergeaud, Delphine, Bergin, Hazel, Sobrino, José Luis Bernal, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Kamarudin, Mohd Nazlin Bin, Bisoffi, Zeno, Bissuel, François, Bitker, Laurent, Bitton, Jonathan, Blanco-Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Blumberg, Lucille, Boccia, Filomena, Bodenes, Laetitia, Bogaert, Debby, Boivin, Anne-Hélène, Bolaños, Isabela, Bolze, Pierre-Adrien, Bompart, François, Borges, Diogo, Borie, Raphaël, Bosse, Hans Martin, Botelho-Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne-Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer-Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Brandenburger, Timo, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Brewster, David, Brickell, Kathy, Browne, Shaunagh, Browne, Alex, Brozzi, Nicolas, Brusse-Keizer, Marjolein, Bryda, Petra, Buchtele, Nina, Buisson, Marielle, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G., Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Garcês, Rui Caetano, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Canepa, Cecilia, Cantero, Mireia, Caraux-Paz, Pauline, Cárcel, Sheila, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie-Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire-Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castañeda, Silvia, Castanheira, Nidyanara, Castor-Alexandre, Guylaine, Castro, Ivo, Catarino, Ana, Catherine, François-Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavayas, Alexandros, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Chantalat Auger, Christelle, Chapplain, Jean-Marc, Charpentier, Charlotte, Chas, Julie, Chávez Iñiguez, Jonathan Samuel, Chen, Anjellica, Chen, Yih-Sharng, Chenard, Léo, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Chin Tho, Leong, Chirouze, Catherine, Chiumello, Davide, Cho, Sung-Min, Cholley, Bernard, Chopin, Marie-Charlotte, Chow, Ting Soo, Chua, Hiu Jian, Chua, Jonathan, Cidade, Jose Pedro, Cisneros Herreros, José Miguel, Citarella, Barbara Wanjiru, Ciullo, Anna, Clarke, Jennifer, Clarke, Emma, Claure-Del Granado, Rolando, Clohisey, Sara, Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Coles, Jennifer, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connolly, Jennifer, Connor, Marie, Conrad, Anne, Conway, Elaine, Cooke, Graham S., Copland, Mary, Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Costigan, Emma, Couffignal, Camille, Couffin-Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Cregan, Rachel, Cristella, Cosimo, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Cruz Bermúdez, Juan Luis, Cruz Rojo, Jaime, Csete, Marc, Cullen, Ailbhe, Cummings, Matthew, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al-Awwab, Dagens, Andrew, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Damas, Juliana, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A., Dantas, Jorge, D'Aragon, Frédérick, de Jong, Menno, de Loughry, Gillian, De Montmollin, Etienne, de Oliveira França, Rafael Freitas, de Pinho Oliveira, Ana Isabel, De Rosa, Rosanna, de Silva, Thushan, de Vries, Peter, Dean, David, Debard, Alexa, DeBenedictis, Bianca, Debray, Marie-Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Delfos, Nathalie M., Deligiannis, Ionna, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Dias, André, Da Silva, Fernanda Dias, Diaz, Juan Jose, Diaz, Rodrigo, Diaz, Priscila, Didier, Kévin, Diehl, Jean-Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B., Doherty, Helen, Donnelly, Maria, Donnelly, Christl A., Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante-Mangoni, Emanuele, Durham, Lucian, III, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol-Riise, Anne Margarita, Ean, Sim Choon, Echeverria-Villalobos, Marco, Egan, Siobhan, Eira, Carla, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Ellerbroek, Jacobien, Eloy, Philippine, Elshazly, Tarek, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Santo, Catarina Espírito, Esposito-Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Isabelle, Fabre, Marc, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J., Faria, Pedro, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François-Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Bernardo, Ferreira, Benigno, Ferreira, Isabel, Ferriere, Nicolas, Ficko, Céline, Figueiredo-Mello, Claudia, Fiorda, Juan, Flament, Thomas, Flateau, Clara, Fletcher, Tom, Florence, Aline-Marie, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Claire, Foley, Jean, Fonseca, Tatiana, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A., Fraher, Marianne, Franch-Llasat, Diego, Fraser, John F., Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freitas, Fritz, Ricardo, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean-Charles, Gagneux-Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia-Gallo, Esteban, Garot, Denis, Garrait, Valérie, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghosn, Jade, Giani, Marco, Gibson, Jess, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Gnall, Eric, Goehringer, François, Goepel, Siri, Goffard, Jean-Christophe, Goh, Jin Yi, Golob, Jonathan, Gómez-Junyent, Joan, Gominet, Marie, Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Gormley, Conor, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Graf, Jeronimo, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A., Greene, Courtney, Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, de Castro, Maisa Guimarães, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hadri, Nadir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hamer, Ansley, Hamidfar, Rebecca, Hammond, Terese, Hammond, Naomi, Han, Lim Yuen, Haniffa, Rashan, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M., Harrison, Janet, Ekow Harrison, Samuel Bernard, Hartman, Alan, Hashmi, Junaid, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Hendry, Ross, Hennessy, Martina, Henriquez-Trujillo, Aquiles, Hentzien, Maxime, Hernandez, Diana, Hernandez-Montfort, Jaime, Hershey, Andrew, Hesstvedt, Liv, Higgins, Eibhlin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hitoto, Hikombo, Ho, Antonia, Ho, Yi Bin, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Horcajada, Juan Pablo, Hoshino, Koji, Houas, Ikram, Hough, Catherine L., Houltham, Stuart, Ming-Yang Hsu, Jimmy, Hulot, Jean-Sébastien, Hurd, Abby, Ijaz, Samreen, Ikram, M. Arfan, Illes, Hajnal-Gabriela, Imbert, Patrick, Inácio, Hugo, Infante Dominguez, Carmen, Ing, Yun Sii, Iosifidis, Elias, Ippolito, Mariachiara, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jabot, Julien, Jackson, Clare, Janes, Victoria, Jaquet, Pierre, Jassat, Waasila, Jaud-Fischer, Coline, Jaureguiberry, Stéphane, Jaworsky, Denise, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Jimbo-Sotomayor, Ruth, Joe, Ong Yiaw, Jorge García, Ruth N., Joseph, Cédric, Joseph, Mark, Jourdain, Mercé, Jouvet, Philippe, Jung, Anna, Jung, Hanna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalomoiri, Smaragdi, Ayadi Kamaluddin, Muhammad Aisar, Che Kamaruddin, Zul Amali, Kamarudin, Nadiah, Kandamby, Darshana Hewa, Kandel, Chris, Kang, Kong Yeow, Karpayah, Pratap, Kartsonaki, Christiana, Kasugai, Daisuke, Kataria, Anant, Katz, Kevin, Kaur, Aasmine, Kay, Christy, Kayyali, Lamees, Keane, Hannah, Keating, Seán, Kelly, Claire, Kelly, Yvelynne, Kelly, Andrea, Kelly, Niamh, Kelly, Aoife, Kelly, Sadie, Kelsey, Maeve, Kennedy, Ryan, Kennon, Kalynn, Kernan, Maeve, Kerroumi, Younes, Keshav, Sharma, Khalid, Imrana, Khalil, Antoine, Khan, Coralie, Khan, Irfan, Kho, Michelle E., Khoo, Saye, Khoo, Ryan, Khoo, Denisa, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kimmoun, Antoine, Kindgen-Milles, Detlef, King, Alexander, Kitamura, Nobuya, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R., Vasconcelos, Malte Kohns, Komatsu, Mamoru, Kosgei, Caroline, Kpangon, Arsène, Krawczyk, Karolina, Krishnan, Sudhir, Krishnan, Vinothini, Kruglova, Oksana, Kumar, Deepali, Kumar, Ganesh, Vecham, Pavan Kumar, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrios, Kutsyna, Galyna, Kyriakoulis, Konstantinos, Lachatre, Marie, Lacoste, Marie, Laffey, John G., Lafhej, Nadhem, Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lalueza, Antonio, Lambert, Marc, Lamontagne, François, Langelot-Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Launay, Odile, Laureillard, Didier, Lavie-Badie, Yoan, Law, Andy, Lawrence, Teresa, Lawrence, Cassie, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, Georges, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Mestre, Soizic Le, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, LeTurnier, Paul, Leal, Ema, Santos, Marta Leal, Lee, Todd C., Lee, Su Hwan, Lee, James, Lee, Jennifer, Lee, Heng Gee, Lee, Biing Horng, Lee, Yi Lin, Leeming, Gary, Lefebvre, Bénédicte, Lefebvre, Laurent, Lefèvre, Benjamin, LeGac, Sylvie, Lelievre, Jean-Daniel, Lellouche, François, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Lennon, Jenny, León, Rafael, Leone, Marc, Leone, Michela, Lepiller, Quentin, Lescure, François-Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester-Grant, Amy, Letrou, Sophie, Levy, Bruno, Levy, Yves, Levy-Marchal, Claire, Lewandowska, Katarzyna, L'Her, Erwan, Bassi, Gianluigi Li, Liegeon, Geoffrey, Lim, Wei Shen, Lim, Kah Chuan, Lima, Chantre, Lina, Bruno, Lina, Lim, Lind, Andreas, Lingas, Guillaume, Lion-Daolio, Sylvie, Lissauer, Samantha, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez-Colon, Dalia, Loschner, Anthony L., Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Lee Low, Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean-Christophe, Bermejo, Carlos Lumbreras, Luna, Carlos M., Lungu, Olguta, Luong, Liem, Luque, Nestor, Luton, Dominique, Lwin, Nilar, Lyons, Ruth, Maasikas, Olavi, Mabiala, Oryane, Machado, Moïse, Machado, Sara, Macheda, Gabriel, Madiha, Hashmi, de la Calle, Guillermo Maestro, Mahieu, Rafael, Mahy, Sophie, Maia, Ana Raquel, Maier, Lars S., Maillet, Mylène, Maitre, Thomas, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Maltez, Fernando, Malvy, Denis, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Sant`Ana Malaque, Ceila Maria, Marino, Flávio, Markowicz, Samuel, Marques, Ana, Marquis, Catherine, Marsh, Brian, Marsh, Laura, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Emily, Martin-Blondel, Guillaume, Martinez, F. 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Mesquita, António, Metwally, Osama, Meybeck, Agnès, Meyer, Dan, Meynert, Alison M., Meysonnier, Vanina, Meziane, Amina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Miller, Jennene, Miranda-Maldonado, Hugo, Misnan, Nor Arisah, Mohamed, Tahira Jamal, Eliza Mohamed, Nik Nur, Moin, Asma, Molinos, Elena, Molloy, Brenda, Monahan, Sinead, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Shona C., Moore, Sarah, Cely, Lina Morales, Moro, Lucia, Morton, Ben, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mudara, Caroline, Muh, Ng Yong, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Murphy, Aisling, Murphy, Lorna, Murray, Patrick, Murris, Marlène, Murthy, Srinivas, Musaab, Himed, Muyandy, Gugapriyaa, Myrodia, Dimitra Melia, Nagpal, Dave, Nagrebetsky, Alex, Narasimhan, Mangala, Narayanan, Nageswaran, Nazerali-Maitland, Alasdair, Neant, Nadège, Neb, Holger, Neto, Raul, Neumann, Emily, Ng, Pauline Yeung, Ng, Wing Yiu, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Nichol, Alistair D., Nitayavardhana, Prompak, Nonas, Stephanie, Mohd Noordin, Nurul Amani, Noret, Marion, Izzati Norharizam, Nurul Faten, Norman, Lisa, Noursadeghi, Mahdad, Nowinski, Adam, Nseir, Saad, Nunez, Jose I., Nyamankolly, Elsa, Brien, Fionnuala O., Callaghan, Annmarie O., O'Callaghan, Annmarie, Occhipinti, Giovanna, OConnor, Derbrenn, O'Donnell, Max, Ogston, Tawnya, Ogura, Takayuki, Oh, Tak-Hyuk, O'Halloran, Sophie, O'Hearn, Katie, Ohshimo, Shinichiro, Oliveira, João, Oliveira, Larissa, Olliaro, Piero L., Ong, David S.Y., Ong, Jee Yan, Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orozco-Chamorro, Claudia Milena, Ortoleva, Jamel, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palacios, Amanda, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Pathmanathan, Mohan Dass, Patrão, Luís, Patricio, Patricia, Patrier, Juliette, Patterson, Lisa, Paul, Christelle, Paul, Mical, Paulos, Jorge, Paxton, William A., Payen, Jean-François, Peake, Sandra L., Peariasamy, Kalaiarasu, Jiménez, Miguel Pedrera, Peek, Giles J., Peelman, Florent, Peiffer-Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D., Pereira, Rui, Perez, Daniel, Periel, Luis, Perpoint, Thomas, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov-Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gilles, Pharand, Scott, Picard, Walter, Picone, Olivier, de Piero, Maria, Pierobon, Carola, Piersma, Djura, Pimentel, Carlos, Pinto, Raquel, Piquard, Valentine, Pires, Catarina, Pironneau, Isabelle, Piroth, Lionel, Piubelli, Chiara, Pius, Riinu, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Poli, Sergio, Pollakis, Georgios, Ponscarme, Diane, Porto, Diego Bastos, Post, Andra-Maris, Postma, Douwe F., Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Preau, Sébastien, Prebensen, Christian, Preiser, Jean-Charles, Prinssen, Anton, Pritchard, Mark G., Proença, Lucia, Pudota, Sravya, Puéchal, Oriane, Semedi, Bambang Pujo, Purcell, Gregory, Quesada, Luisa, González, Víctor Quirós, Quist-Paulsen, Else, Quraishi, Mohammed, Qutishat, Fadi, Rabaud, Christian, Rafael, Aldo, Rafiq, Marie, Rahman, Rozanah Abd, Haji Ab Rahman, Ahmad Kashfi, Rainieri, Fernando, Rajahram, Giri Shan, Ramakrishnan, Nagarajan, Ramalho, José, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Ranjan, Ritika, Rapp, Christophe, Rasmin, Menaldi, Rätsep, Indrek, Ravi, Tharmini, Real, Andre, Rebaudet, Stanislas, Redl, Sarah, Reeve, Brenda, Reid, Liadain, Reikvam, Dag Henrik, Reis, Renato, Rello, Jordi, Remppis, Jonathan, Remy, Martine, Ren, Hongru, Renk, Hanna, Resseguier, Anne-Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Tiago, Reyes, Luis Felipe, Ribeiro, Maria Ines, Richardson, David, Richardson, Denise, Richier, Laurent, Atikah Ahmad Ridzuan, Siti Nurul, Rios, Ana L., Rishu, Asgar, Rispal, Patrick, Risso, Karine, Rizer, Nicholas, Robba, Chiara, Roberto, André, Roberts, Stephanie, Robertson, David L., Robineau, Olivier, Roche-Campo, Ferran, Rodari, Paola, Rodeia, Simão, Roessler, Bernhard, Roger, Pierre-Marie, Roger, Claire, Roilides, Emmanuel, Rojek, Amanda, Romaru, Juliette, Roncon-Albuquerque, Roberto, Jr., Roriz, Mélanie, Rosa-Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Bénédicte, Rossignol, Patrick, Rousset, Stella, Roy, Carine, Roze, Benoît, Russell, Clark D., Ryan, Maria, Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadat, Musharaf, Sahraei, Valla, Saint-Gilles, Maximilien, Sakiyalak, Pranya, Salazar, Leonardo, Sales, Gabriele, Sallaberry, Stéphane, Gandonniere, Charlotte Salmon, Salvator, Hélène, Sanchez, Olivier, Sanchez, Emely, Sanchez-Miralles, Angel, Sancho-Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre-François, Sandulescu, Oana, Santos, Marlene, Sarfo-Mensah, Shirley, Sarmento Banheiro, Bruno, Sarmiento, Iam Claire E., Sarton, Benjamin, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Savvidou, Parthena, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schroll, Stephan, Schwameis, Michael, Scicluna, Brendan, Scott, Janet T., Scott-Brown, James, Sedillot, Nicholas, Seitz, Tamara, Selvarajoo, Mageswari, Semaille, Caroline, Semple, Malcolm G., Senian, Rasidah Bt, Senneville, Eric, Sepulveda, Claudia, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Balazote, Pablo Serrano, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shamsah, Mohammad, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A., Shaw, Victoria, Sheenan, John Robert, Shi, Haixia, Shime, Nobuaki, Shimizu, Keiki, Shrapnel, Sally, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Sibiude, Jeanne, Siddiqui, Atif, Sigfrid, Louise, Sillaots, Piret, Silva, Catarina, Silva, Rogério, Silva, Maria Joao, Lim Heng, Benedict Sim, Sin, Wai Ching, Singh, Punam, Singh, Budha Charan, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Smyth, Michelle, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnès, Song, Rima, Song, Myung Jin, Song, Tae, Chia, Jack Song, Sonntagbauer, Michael, Soom, Azlan Mat, Sotto, Albert, Soum, Edouard, Sousa, Marta, Sousa, Ana Chora, Uva, Maria Sousa, Souza-Dantas, Vicente, Sperry, Alexandra, Spinuzza, Elisabetta, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thomas, Stecher, Stephanie-Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu-Cercel, Adrian, Streinu-Cercel, Anca, Stuart, Ami, Stuart, David, Su, Richa, Suen, Jacky Y., Suen, Gabriel, Sukumar, Prasanth, Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Syahrin, Sarah, Syrigos, Konstantinos, Sztajnbok, Jaques, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S., Tagherset, Lysa, Taib, Shahdattul Mawarni, Taleb, Sara, Talsma, Jelmer, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Hiroyuki, Tanaka, Taku, Taniguchi, Hayato, Tardivon, Coralie, Tattevin, Pierre, Taufik, M. Azhari, Tawfik, Hassan, Tedder, Richard S., Tee, Tze Yuan, Teixeira, João, Tejada, Sofia, Tellier, Marie-Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, François, Terpstra, Pleun, Terrier, Olivier, Terzi, Nicolas, Tessier-Grenier, Hubert, Tey, Adrian, Mohd Thabit, Alif Adlan, Tham, Zhang Duan, Thangavelu, Suvintheran, Theron, Elmi, Thibault, Vincent, Thiberville, Simon-Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Shaun, Thomson, David, Thomson, Emma C., Thorpe, Mathew, Thanga Thurai, Surain Raaj, Thwaites, Ryan S., Tierney, Paul, Tieroshyn, Vadim, Timsit, Jean-François, Tissot, Noémie, Toal, Fiona, Yang Toh, Jordan Zhien, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torre, Marta, Torres, Margarida, Torres, Antoni, Torres-Zevallos, Hernando, Towers, Michael, Trapani, Tony, Trioux, Théo, Tromeur, Cécile, Trontzas, Ioannis, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turgeon, Alexis F., Turmel, Jean-Marie, Turtle, Lance C.W., Tveita, Anders, Twardowski, Pawel, Uchiyama, Makoto, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad, Uyeki, Timothy M., Vajdovics, Cristinava, Val-Flores, Luís, Valran, Amélie, Van de Velde, Stijn, van den Berge, Marcel, Van der Feltz, Machteld, van der Palen, Job, van der Valk, Paul, Van Der Vekens, Nicky, Van der Voort, Peter, Van Der Werf, Sylvie, van Gulik, Laura, Van Hattem, Jarne, van Netten, Carolien, van Someren Gréve, Frank, van Veen, Ilonka, Van Willigen, Hugo, Vanel, Noémie, Vanoverschelde, Henk, Varghese, Pooja, Varrone, Michael, Vasudayan, Shoban Raj, Vauchy, Charline, Veeran, Shaminee, Veislinger, Aurélie, Vencken, Sebastian, Ventura, Sara, Verbon, Annelies, Vidal, José Ernesto, Vieira, César, Villanueva, Joy Ann, Villar, Judit, Villeneuve, Pierre-Marc, Villoldo, Andrea, Visseaux, Benoit, Visser, Hannah, Vitiello, Chiara, Vonkeman, Harald, Vuotto, Fanny, Wahab, Noor Hidayu, Wahab, Suhaila Abdul, Wahid, Nadirah Abdul, Wainstein, Marina, Walsh, Laura, Wang, Chih-Hsien, Webb, Steve, Wei, Jia, Weil, Katharina, Wen, Tan Pei, Wesselius, Sanne, Wham, Murray, Whelan, Bryan, White, Nicole, Wicky, Paul Henri, Wiedemann, Aurélie, Wijaya, Surya Otto, Wille, Keith, Willems, Sue, Williams, Bailey, Williams, Virginie, Williams, Patricia J., Wils, Evert-Jan, Wittman, Jessica, Wong, Calvin, Wong, Xin Ci, Wong, Yew Sing, Wong, Teck Fung, Xian, Gan Ee, Xian, Lim Saio, Kuan, Pei Xuan, Xynogalas, Ioannis, Binti Mohd Yakop, Siti Rohani, Yamazaki, Masaki, Yarad, Elizabeth, Yazdanpanah, Yazdan, Liang Hing, Nicholas Yee, Yelnik, Cécile, Yeoh, Chian Hui, Yerkovich, Stephanie, Yokoyama, Toshiki, Yonis, Hodane, Yousif, Obada, Zaaqoq, Akram, Zabbe, Marion, Zacharowski, Kai, Zahid, Masliza, Zahran, Maram, Binti Zaidan, Nor Zaila, Zambon, Maria, Zambrano, Miguel, Zanella, Alberto, Zaynah, Nurul, Zayyad, Hiba, Zoufaly, Alexander, Zucman, David, Griffee, Matthew J., Bozza, Patricia T., Eddington, Devin P., Fanning, Jonathon P., Alexander, Peta M.A., and Fraser, John

Published
2023
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40. Advances in Neuroanatomy through Brain Atlasing

Author

Wieslaw L. Nowinski

Subjects
neuroanatomy, human brain atlases, neuroeducation, brain research, brain atlases in clinics, large brain projects, Human anatomy, QM1-695
Abstract

Human brain atlases are tools to gather, present, use, and discover knowledge about the human brain. The developments in brain atlases parallel the advances in neuroanatomy. The brain atlas evolution has been from hand-drawn cortical maps to print atlases to digital platforms which, thanks to tremendous advancements in acquisition techniques and computing, has enabled progress in neuroanatomy from gross (macro) to meso-, micro-, and nano-neuroanatomy. Advances in neuroanatomy have been feasible because of introducing new modalities, from the initial cadaveric dissections, morphology, light microscopy imaging and neuroelectrophysiology to non-invasive in vivo imaging, connectivity, electron microscopy imaging, genomics, proteomics, transcriptomics, and epigenomics. Presently, large and long-term brain projects along with big data drive the development in micro- and nano-neuroanatomy. The goal of this work is to address the relationship between neuroanatomy and human brain atlases and, particularly, the impact of these atlases on the understanding, presentation, and advancement of neuroanatomy. To better illustrate this relationship, a brief outline on the evolution of the human brain atlas concept, creation of brain atlases, atlas-based applications, and future brain-related developments is also presented. In conclusion, human brain atlases are excellent means to represent, present, disseminate, and support neuroanatomy.

Published
2023
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41. Primary care detection of cognitive impairment leveraging health and consumer technologies in underserved US communities: protocol for a pragmatic randomised controlled trial of the MyCog paradigm

Author

Michael Wolf, Richard Gershon, Michael Bass, Minjee Kim, Morgan Bonham, Julia Yoshino Benavente, Rebecca Lovett, Zahra Hosseinian, Greg J Byrne, Maria Varela Diaz, Lihua Yao, Andrei Adin-Cristian, Stephanie Batio, Amanda Sluis, Margaret Moran, David R Buchanan, Justin Hunt, Stephanie R Young, and Cindy Nowinski

Subjects
Medicine
Abstract

Introduction Early identification of cognitive impairment (CI), including Alzheimer’s disease and related dementias (ADRD), is a top public health priority. Yet, CI/ADRD is often undetected and underdiagnosed within primary care settings, and in health disparate populations. The MyCog paradigm is an iPad-based, self-administered, validated cognitive assessment based on the National Institutes of Health (NIH) Toolbox Cognition Battery and coupled with clinician decision-support tools that is specifically tailored for CI/ADRD detection within diverse, primary care settings.Methods and analysis We will conduct a two-arm, primary care practice-randomised (N=24 practices; 45 257 active patients at the proposed practices), pragmatic trial among geographically diverse Oak Street Health sites to test the effectiveness of the MyCog paradigm to improve early detection CI/ADRD among low socioeconomic, black and Hispanic older adults compared with usual care. Participating practices randomised to the intervention arm will impart the MyCog paradigm as a new standard of care over a 3-year implementation period; as the cognitive component for Annual Wellness Visits and for any patient/informant-reported or healthcare provider-suspected cognitive concern. Rates of detected (cognitive test suggesting impairment) and/or diagnosed (relevant International Classification of Diseases-9/10 [ICD-9/10] code) cognitive deficits, impairments or dementias including ADRD will be our primary outcome of study compared between arms. Secondary outcomes will include ADRD severity (ie, mild or later stage), rates of cognitive-related referrals and rates of family member or caregiver involvement in ADRD care planning. We will use generalised linear mixed models to account for clustered study design. Secondary models will adjust for subject, clinic or visit-specific characteristics. We will use mixed-methods approaches to examine fidelity and cost-effectiveness of the MyCog paradigm.Ethics and dissemination The Institutional Review Board at Advarra has approved the study protocol (Pro00064339). Results will be published in peer-reviewed journals and summaries will be provided to the funders of the study.Trial registration number NCT05607732.

Published
2023
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42. Taxonomy of Acute Stroke: Imaging, Processing, and Treatment

Author

Wieslaw L. Nowinski

Subjects
stroke, acute stroke, stroke management, stroke imaging, neuroimage processing, artificial intelligence, Medicine (General), R5-920
Abstract

Stroke management employs a variety of diagnostic imaging modalities, image processing and analysis methods, and treatment procedures. This work categorizes methods for stroke imaging, image processing and analysis, and treatment, and provides their taxonomies illustrated by a state-of-the-art review. Imaging plays a critical role in stroke management, and the most frequently employed modalities are computed tomography (CT) and magnetic resonance (MR). CT includes unenhanced non-contrast CT as the first-line diagnosis, CT angiography, and CT perfusion. MR is the most complete method to examine stroke patients. MR angiography is useful to evaluate the severity of artery stenosis, vascular occlusion, and collateral flow. Diffusion-weighted imaging is the gold standard for evaluating ischemia. MR perfusion-weighted imaging assesses the penumbra. The stroke image processing methods are divided into non-atlas/template-based and atlas/template-based. The non-atlas/template-based methods are subdivided into intensity and contrast transformations, local segmentation-related, anatomy-guided, global density-guided, and artificial intelligence/deep learning-based. The atlas/template-based methods are subdivided into intensity templates and atlases with three atlas types: anatomy atlases, vascular atlases, and lesion-derived atlases. The treatment procedures for arterial and venous strokes include intravenous and intraarterial thrombolysis and mechanical thrombectomy. This work captures the state-of-the-art in stroke management summarized in the form of comprehensive and straightforward taxonomy diagrams. All three introduced taxonomies in diagnostic imaging, image processing and analysis, and treatment are widely illustrated and compared against other state-of-the-art classifications.

Published
2024
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44. Estimating Achilles tendon healing progress with convolutional neural networks

Author

Kapinski, Norbert, Zielinski, Jakub, Borucki, Bartosz A., Trzcinski, Tomasz, Ciszkowska-Lyson, Beata, and Nowinski, Krzysztof S.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Quantitative assessment of a treatment progress in the Achilles tendon healing process - one of the most common musculoskeletal disorder in modern medical practice - is typically a long and complex process: multiple MRI protocols need to be acquired and analysed by radiology experts. In this paper, we propose to significantly reduce the complexity of this assessment using a novel method based on a pre-trained convolutional neural network. We first train our neural network on over 500,000 2D axial cross-sections from over 3000 3D MRI studies to classify MRI images as belonging to a healthy or injured class, depending on the patient's condition. We then take the outputs of modified pre-trained network and apply linear regression on the PCA-reduced space of the features to assess treatment progress. Our method allows to reduce up to 5-fold the amount of data needed to be registered during the MRI scan without any information loss. Furthermore, we are able to predict the healing process phase with equal accuracy to human experts in 3 out of 6 main criteria. Finally, contrary to the current approaches to regeneration assessment that rely on radiologist subjective opinion, our method allows to objectively compare different treatments methods which can lead to improved diagnostics and patient's recovery., Comment: Paper accepted to MICCAI'18

Published
2018
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45. Basalt or not? Near-infrared spectra, surface mineralogical estimates, and meteorite analogs for 33 Vp-type asteroids

Author

Hardersen, Paul S., Reddy, Vishnu, Cloutis, Edward, Nowinski, Matt, Dievendorf, Margaret, Genet, Russell M., Becker, Savan, and Roberts, Rachel

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Investigations of the main asteroid belt and efforts to constrain that population's physical characteristics involve the daunting task of studying hundreds of thousands of small bodies. Taxonomic systems are routinely employed to study the large scale nature of the asteroid belt because they utilize common observational parameters, but asteroid taxonomies only define broadly observable properties and are not compositionally diagnostic (Tholen, 1984; Carvano et al., 2010, Hasselmann et al., 2012). This work builds upon the results of Hardersen et al. (2014, 2015), which has the goal of constraining the abundance and distribution of basaltic asteroids throughout the main asteroid belt. We report on the near infrared (NIR: 0.7 to 2.5 microns) reflectance spectra, surface mineralogical characterizations, spectral band parameter analysis, and meteorite analogs for 33 Vp asteroids. NIR reflectance spectroscopy is an effective remote sensing technique to detect most pyroxene group minerals, which are spectrally distinct with two very broad spectral absorptions at 0.9 and 1.9 microns (Cloutis et al., 1986; Gaffey et al., 2002; Burbine et al., 2009). Combined with the results from Hardersen et al. (2014, 2015), we identify basaltic asteroids for 95 percent (39 of 41) of our inner-belt Vp sample, but only 25 percent (2 of 8) of the outer-belt Vp sample. Inner belt basaltic asteroids are most likely associated with 4 Vesta and represent impact fragments ejected from previous collisions. Outer belt Vp asteroids exhibit disparate spectral, mineralogic, and meteorite analog characteristics and likely originate from diverse parent bodies. The discovery of two additional likely basaltic asteroids provides additional evidence for an outer-belt basaltic asteroid population., Comment: 32 pages, 5 figures, 4 tables

Published
2018
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46. Sulfur metabolites that facilitate oceanic phytoplankton–bacteria carbon flux

Author

Landa, Marine, Burns, Andrew S, Durham, Bryndan P, Esson, Kaitlin, Nowinski, Brent, Sharma, Shalabh, Vorobev, Alexey, Nielsen, Torben, Kiene, Ronald P, and Moran, Mary Ann

Subjects
Microbiology, Biological Sciences, Genetics, Life Below Water, Alphaproteobacteria, Bacteria, Carbon, Carbon Cycle, Diatoms, Heterotrophic Processes, Oceans and Seas, Phytoplankton, Seawater, Sulfur, Environmental Sciences, Technology, Biological sciences, Environmental sciences
Abstract

Unlike biologically available nitrogen and phosphorus, which are often at limiting concentrations in surface seawater, sulfur in the form of sulfate is plentiful and not considered to constrain marine microbial activity. Nonetheless, in a model system in which a marine bacterium obtains all of its carbon from co-cultured phytoplankton, bacterial gene expression suggests that at least seven dissolved organic sulfur (DOS) metabolites support bacterial heterotrophy. These labile exometabolites of marine dinoflagellates and diatoms include taurine, N-acetyltaurine, isethionate, choline-O-sulfate, cysteate, 2,3-dihydroxypropane-1-sulfonate (DHPS), and dimethylsulfoniopropionate (DMSP). Leveraging from the compounds identified in this model system, we assessed the role of sulfur metabolites in the ocean carbon cycle by mining the Tara Oceans dataset for diagnostic genes. In the 1.4 million bacterial genome equivalents surveyed, estimates of the frequency of genomes harboring the capability for DOS metabolite utilization ranged broadly, from only 1 out of every 190 genomes (for the C2 sulfonate isethionate) to 1 out of every 5 (for the sulfonium compound DMSP). Bacteria able to participate in DOS transformations are dominated by Alphaproteobacteria in the surface ocean, but by SAR324, Acidimicrobiia, and Gammaproteobacteria at mesopelagic depths, where the capability for utilization occurs in higher frequency than in surface bacteria for more than half the sulfur metabolites. The discovery of an abundant and diverse suite of marine bacteria with the genetic capacity for DOS transformation argues for an important role for sulfur metabolites in the pelagic ocean carbon cycle.

Published
2019

47. Microbial metagenomes and metatranscriptomes during a coastal phytoplankton bloom.

Author

Nowinski, Brent, Smith, Christa B, Thomas, Courtney M, Esson, Kaitlin, Marin, Roman, Preston, Christina M, Birch, James M, Scholin, Christopher A, Huntemann, Marcel, Clum, Alicia, Foster, Brian, Foster, Bryce, Roux, Simon, Palaniappan, Krishnaveni, Varghese, Neha, Mukherjee, Supratim, Reddy, TBK, Daum, Chris, Copeland, Alex, Chen, I-Min A, Ivanova, Natalia N, Kyrpides, Nikos C, Glavina Del Rio, Tijana, Whitman, William B, Kiene, Ronald P, Eloe-Fadrosh, Emiley A, and Moran, Mary Ann

Subjects
Phytoplankton, Dinoflagellida, Bacteria, Archaea, Eutrophication, California, Metagenome, Transcriptome
Abstract

Metagenomic and metatranscriptomic time-series data covering a 52-day period in the fall of 2016 provide an inventory of bacterial and archaeal community genes, transcripts, and taxonomy during an intense dinoflagellate bloom in Monterey Bay, CA, USA. The dataset comprises 84 metagenomes (0.8 terabases), 82 metatranscriptomes (1.1 terabases), and 88 16S rRNA amplicon libraries from samples collected on 41 dates. The dataset also includes 88 18S rRNA amplicon libraries, characterizing the taxonomy of the eukaryotic community during the bloom. Accompanying the sequence data are chemical and biological measurements associated with each sample. These datasets will facilitate studies of the structure and function of marine bacterial communities during episodic phytoplankton blooms.

Published
2019

49. Pilot Testing of the MyCog Assessment: Rapid Detection of Cognitive Impairment in Everyday Clinical Settings

Author

Laura M. Curtis MS, Stephanie Batio MS, Julia Yoshino Benavente MPH, Yusuke Shono PhD, Cindy Nowinski MD, PhD, Rebecca M. Lovett PhD, Lihua Yao PhD, Richard C. Gershon PhD, Zahra Hosseinian MA, and Michael S. Wolf PhD, MPH, MA

Subjects
Geriatrics, RC952-954.6
Abstract

Cognitive impairment (CI) and dementia can have profound social and emotional effects on older adults. Early detection of CI is imperative both to the identification of potentially treatable conditions and to provide services to minimize the effects of CI in cases of dementia. While primary care settings are ideal for identifying CI, it frequently goes undetected. We tailored a brief, iPad-based, cognitive assessment (MyCog) for primary care settings and piloted it in a sample of older adults. Eighty participants were recruited from an existing cohort study and completed a brief, in-person interview. CI was determined based on a diagnosis of dementia or CI in their medical record or based on a comprehensive cognitive battery performed within the past 18 months. MyCog had a sensitivity of 79% and specificity of 82%, offering a practical, scalable, primary care assessment for the routine case finding of cognitive impairment and dementia.

Published
2023
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