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Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67-1.87), easy home alcohol access (HRs=1.62-1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72-1.76), and less parental control and knowledge (HRs=.72-.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (βs=0.57-0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

Heavy alcohol drinking is a major, preventable problem that adversely impacts the physical and mental health of US young adults. Studies seeking drinking risk factors typically focus on young adults who enrolled in 4-year residential college programs (4YCP) even though most high school graduates join the workforce, military, or community colleges. We examined 106 of these understudied young adults (USYA) and 453 4YCPs from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) by longitudinally following their drinking patterns for 8 years from adolescence to young adulthood. All participants were no-to-low drinkers during high school. Whereas 4YCP individuals were more likely to initiate heavy drinking during college years, USYA participants did so later. Using mental health metrics recorded during high school, machine learning forecasted individual-level risk for initiating heavy drinking after leaving high school. The risk factors differed between demographically matched USYA and 4YCP individuals and between sexes. Predictors for USYA drinkers were sexual abuse, physical abuse for girls, and extraversion for boys, whereas 4YCP drinkers were predicted by the ability to recognize facial emotion and, for boys, greater openness. Thus, alcohol prevention programs need to give special consideration to those joining the workforce, military, or community colleges, who make up the majority of this age group.

We study the gap processes in a degenerate system of three particles interacting through their ranks. We obtain the Laplace transform of the invariant measure of these gaps, and an explicit expression for the corresponding invariant density. To derive these results, we start from the basic adjoint relationship characterizing the invariant measure, and apply a combination of two approaches: first, the invariance methodology of W. Tutte, thanks to which we compute the Laplace transform in closed form; second, a recursive compensation approach which leads to the density of the invariant measure as an infinite convolution of exponential functions. As in the case of Brownian motion with reflection or killing at the endpoints of an interval, certain Jacobi theta functions play a crucial role in our computations.

Background and aimsRecently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.Design and settingCross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years).CasesCases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.ConclusionStructural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Molecular markers are increasingly being deployed to accelerate genetic gain in crop plants. The objective of this study was to assess the potential of a mid-density genotyping panel for molecular applications in cowpea breeding. A core set of 2,602 targeted diversity array technology (DArTag) single-nucleotide polymorphisms (SNPs) was designed from an existing 51,128 Cowpea iSelect Consortium Array. The panels usefulness was assessed using 376 genotypes from different populations of known genetic backgrounds. The panel was informative, with over 78% of SNPs exceeding a minor allele frequency of 0.20. The panel decoded three stratifications in the constituted population, as was expected. Linkage disequilibrium (LD) decay was correctly depicted as slower in a biparental subset than in other populations. A known flower and seed coat color gene region was located on chromosome Vu07, suggesting that the mid-density panel may be used to hypothesize genomic regions underlying target traits in cowpea. Unexpected heterozygosity was detected in some lines and highly among F1 progenies, divulging the panels potential application in germplasm purity and hybridity verification. The study unveils the potential of an excellent genomic resource that can be tapped to enhance the development of improved cowpea cultivars.

We are grateful to Eker et al. for their thoughtful analysis and response to our publication titled Comparing Characteristics and Treatment of Brain Vascular Malformations in Children and Adults with HHT [...].

We investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge-n Seismic Survey in Oklahoma (LASSO). While it is well known that near-surface unconsolidated sediments can cause an apparent breakdown of earthquake self-similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825-station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P-wave ground motions below 8 Hz, the surface geology correlates with P-wave ground motions above 8 Hz and S-wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes (ML = 0.01–3) estimated using a standard single-spectra approach show negative correlations with the site-effect proxy, while the seismic moments show positive correlations. In contrast, the spectral-ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site-related biases requires at least 30 stations. Correcting for site-related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.

Traffic congestion is a major problem in large cities worldwide. This project uses high-frequency data from the Los Angeles metropolitan area combined with an instrument that varies spatially and temporally to estimate the causal impact of an additional vehicle mile traveled on travel times. Specifically, the research team exploits the network structure of the Los Angeles highway system and uses crashes on close alternative routes as exogenous shocks to traffic demand. To do so, the team relies on Google Maps to determine the ideal route and alternatives for over 19,000 real-world commutes. The researchers estimate that at peak times an additional trip reduces speed by, on average, 0.22%. They find the optimal toll at peak times is 33 cents per mile, with the toll being lower, even zero, off-peak. The researchers show how this toll varies over space and time, as well as report on its distributional effects. This toll would more than double highway speeds during peak times and only requires reducing vehicle miles traveled (VMT) at the peak by 10%. The resulting social welfare gains are over two billion dollars per year.View the NCST Project Webpage

Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a matrix-augmented pooling strategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date.

Exposure to traffic-related air pollution consisting of particulate matter (PM) is associated with cognitive decline leading to Alzheimer's disease (AD). In this study, we sought to examine the neurotoxic effects of exposure to ultrafine PM and how it exacerbates neuronal loss and AD-like neuropathology in wildtype (WT) mice and a knock-in mouse model of AD (AppNL-G-F/+-KI) when the exposure occurs at a prepathologic stage or at a later age with the presence of neuropathology. AppNL-G-F/+-KI and WT mice were exposed to concentrated ultrafine PM from local ambient air in Irvine, California, for 12 weeks, starting at 3 or 9 months of age. Particulate matter-exposed animals received concentrated ultrafine PM up to 8 times above the ambient levels, whereas control animals were exposed to purified air. Particulate matter exposure resulted in a marked impairment of memory tasks in prepathologic AppNL-G-F/+-KI mice without measurable changes in amyloid-β pathology, synaptic degeneration, and neuroinflammation. At aged, both WT and AppNL-G-F/+-KI mice exposed to PM showed a significant memory impairment along with neuronal loss. In AppNL-G-F/+-KI mice, we also detected an increased amyloid-β buildup and potentially harmful glial activation including ferritin-positive microglia and C3-positive astrocytes. Such glial activation could promote the cascade of degenerative consequences in the brain. Our results suggest that exposure to PM impairs cognitive function at both ages while exacerbation of AD-related pathology and neuronal loss may depend on the stage of pathology, aging, and/or state of glial activation. Further studies will be required to unveil the neurotoxic role of glial activation activated by PM exposure.

Pistachio is a nut crop domesticated in the Fertile Crescent and a dioecious species with ZW sex chromosomes. We sequenced the genomes of Pistacia vera cultivar (cv.) Siirt, the female parent, and P. vera cv. Bagyolu, the male parent. Two chromosome-level reference genomes of pistachio were generated, and Z and W chromosomes were assembled. The ZW chromosomes originated from an autosome following the first inversion, which occurred approximately 8.18 Mya. Three inversion events in the W chromosome led to the formation of a 12.7-Mb (22.8% of the W chromosome) non-recombining region. These W-specific sequences contain several genes of interest that may have played a pivotal role in sex determination and contributed to the initiation and evolution of a ZW sex chromosome system in pistachio. The W-specific genes, including defA, defA-like, DYT1, two PTEN1, and two tandem duplications of six VPS13A paralogs, are strong candidates for sex determination or differentiation. Demographic history analysis of resequenced genomes suggest that cultivated pistachio underwent severe domestication bottlenecks approximately 7640 years ago, dating the domestication event close to the archeological record of pistachio domestication in Iran. We identified 390, 211, and 290 potential selective sweeps in 3 cultivar subgroups that underlie agronomic traits such as nut development and quality, grafting success, flowering time shift, and drought tolerance. These findings have improved our understanding of the genomic basis of sex determination/differentiation and horticulturally important traits and will accelerate the improvement of pistachio cultivars and rootstocks.

The evolution of new traits enables expansion into new ecological and behavioural niches. Nonetheless, demonstrated connections between divergence in protein structure, function and lineage-specific behaviours remain rare. Here we show that both octopus and squid use cephalopod-specific chemotactile receptors (CRs) to sense their respective marine environments, but structural adaptations in these receptors support the sensation of specific molecules suited to distinct physiological roles. We find that squid express ancient CRs that more closely resemble related nicotinic acetylcholine receptors, whereas octopuses exhibit a more recent expansion in CRs consistent with their elaborated taste by touch sensory system. Using a combination of genetic profiling, physiology and behavioural analyses, we identify the founding member of squid CRs that detects soluble bitter molecules that are relevant in ambush predation. We present the cryo-electron microscopy structure of a squid CR and compare this with octopus CRs1 and nicotinic receptors2. These analyses demonstrate an evolutionary transition from an ancestral aromatic cage that coordinates soluble neurotransmitters or tastants to a more recent octopus CR hydrophobic binding pocket that traps insoluble molecules to mediate contact-dependent chemosensation. Thus, our study provides a foundation for understanding how adaptation of protein structure drives the diversification of organismal traits and behaviour.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has significantly increased depression rates, particularly in emerging adults. The aim of this study was to examine longitudinal changes in depression risk before and during COVID-19 in a cohort of emerging adults in the U.S. and to determine whether prior drinking or sleep habits could predict the severity of depressive symptoms during the pandemic.MethodsParticipants were 525 emerging adults from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a five-site community sample including moderate-to-heavy drinkers. Poisson mixed-effect models evaluated changes in the Center for Epidemiological Studies Depression Scale (CES-D-10) from before to during COVID-19, also testing for sex and age interactions. Additional analyses examined whether alcohol use frequency or sleep duration measured in the last pre-COVID assessment predicted pandemic-related increase in depressive symptoms.ResultsThe prevalence of risk for clinical depression tripled due to a substantial and sustained increase in depressive symptoms during COVID-19 relative to pre-COVID years. Effects were strongest for younger women. Frequent alcohol use and short sleep duration during the closest pre-COVID visit predicted a greater increase in COVID-19 depressive symptoms.ConclusionsThe sharp increase in depression risk among emerging adults heralds a public health crisis with alarming implications for their social and emotional functioning as this generation matures. In addition to the heightened risk for younger women, the role of alcohol use and sleep behavior should be tracked through preventive care aiming to mitigate this looming mental health crisis.

Cognitive disorders are prevalent in people with HIV (PWH) despite antiretroviral therapy. Given the heterogeneity of cognitive disorders in PWH in the current era and evidence that these disorders have different etiologies and risk factors, scientific rationale is growing for using data-driven models to identify biologically defined subtypes (biotypes) of these disorders. Here, we discuss the state of science using machine learning to understand cognitive phenotypes in PWH and their associated comorbidities, biological mechanisms, and risk factors. We also discuss methods, example applications, challenges, and what will be required from the field to successfully incorporate machine learning in research on cognitive disorders in PWH. These topics were discussed at the National Institute of Mental Health meeting on "Biotypes of CNS Complications in People Living with HIV" held in October 2021. These ongoing research initiatives seek to explain the heterogeneity of cognitive phenotypes in PWH and their associated biological mechanisms to facilitate clinical management and tailored interventions.

BackgroundMost trials comparing endovascular treatment (EVT) alone versus intravenous thrombolysis with alteplase (IVT) + EVT in directly admitted patients with a stroke are non-inferiority trials. However, the margin based on the level of uncertainty regarding non-inferiority of the experimental treatment that clinicians are willing to accept to incorporate EVT alone into clinical practice remains unknown.ObjectiveTo characterize what experienced stroke clinicians would consider an acceptable level of uncertainty for hypothetical decisions on whether to administer IVT or not before EVT in patients admitted directly to EVT-capable centers.MethodsA web-based, structured survey was distributed to a cross-section of 600 academic neurologists/neurointerventionalists. For this purpose, a response framework for a hypothetical trial comparing IVT+EVT (standard of care) with EVT alone (experimental arm) was designed. In this trial, a similar proportion of patients in each arm achieved functional independence at 90 days. Invited physicians were asked at what level of certainty they would feel comfortable skipping IVT in clinical practice, considering these hypothetical trial results.ResultsThere were 180 respondents (response rate: 30%) and 165 with complete answers. The median chosen acceptable uncertainty suggesting reasonable comparability between both treatments was an absolute difference in the rate of day 90 functional independence of 3% (mode 5%, IQR 1-5%), with higher chosen margins observed in interventionalists (aOR 2.20, 95% CI 1.06 to 4.67).ConclusionPhysicians would generally feel comfortable skipping IVT before EVT at different certainty thresholds. Most physicians would treat with EVT alone if randomized trial data suggested that the number of patients achieving functional independence at 90 days was similar between the two groups, and one could be sufficiently sure that no more than 3 out of 100 patients would not achieve functional independence at 90 days due to skipping IVT.

Hereditary hemorrhagic telangiectasia (HHT) is a rare autosomal dominant disease characterized by the development of vascular malformations (VMs) in organs such as the brain and lungs, as well as telangiectases on mucosal surfaces. Prophylactic treatment of organ VMs may prevent potential complications, such as hemorrhage. However, brain VM treatment-surgical resection, embolization, and/or radiosurgery-is not recommended for all patients due to the associated risks. Given the scarcity of data regarding HHT-related brain VM presentation and treatment trends in pediatric patients, we aim to describe the clinical presentations and the patterns of treatment of HHT-related brain VMs in a pediatric cohort, and compare pediatric trends to those of adults. Demographic and clinical data were analyzed in 114 pediatric patients with HHT-related brain VMs and compared with a cohort of 253 adult patients enrolled in the multicenter Brain Vascular Malformation Consortium HHT Project. Our data demonstrated that a higher proportion of pediatric patients with HHT-related brain VMs were symptomatic at presentation (p = 0.004). Moreover, a higher proportion of pediatric patients presented with intracranial hemorrhage (p < 0.001) and seizure (p = 0.002) compared to adult patients. Surgical resection was the most common brain VM treatment modality in both children and adults. We conclude that pediatric patients may be more likely to present with symptoms and complications from brain VMs, supporting the case for screening for brain VMs in children with HHT.

BackgroundAccurate measurement of trajectories in longitudinal studies, considered the gold standard method for tracking functional growth during adolescence, decline in aging, and change after head injury, is subject to confounding by testing experience.MethodsWe measured change in cognitive and motor abilities over four test sessions (baseline and three annual assessments) in 154 male and 165 female participants (baseline age 12-21 years) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. At each of the four test sessions, these participants were given a test battery using computerized administration and traditional pencil and paper tests that yielded accuracy and speed measures for multiple component cognitive (Abstraction, Attention, Emotion, Episodic memory, Working memory, and General Ability) and motor (Ataxia and Speed) functions. The analysis aim was to dissociate neurodevelopment from testing experience by using an adaptation of the twice-minus-once tested method, which calculated the difference between longitudinal change (comprising developmental plus practice effects) and practice-free initial cross-sectional performance for each consecutive pairs of test sessions. Accordingly, the first set of analyses quantified the effects of learning (i.e., prior test experience) on accuracy and after speed domain scores. Then developmental effects were  determined for each domain for accuracy and speed having removed the measured learning effects.ResultsThe greatest gains in performance occurred between the first and second sessions, especially in younger participants, regardless of sex, but practice gains continued to accrue thereafter for several functions. For all 8 accuracy composite scores, the developmental effect after accounting for learning was significant across age and was adequately described by linear fits. The learning-adjusted developmental effects for speed were adequately described by linear fits for Abstraction, Emotion, Episodic Memory, General Ability, and Motor scores, although a nonlinear fit was better for Attention, Working Memory, and Average Speed scores.ConclusionThus, what appeared as accelerated cognitive and motor development was, in most cases, attributable to learning. Recognition of the substantial influence of prior testing experience is critical for accurate characterization of normal development and for developing norms for clinical neuropsychological investigations of conditions affecting the brain.

ObjectiveTo describe people with gout who were diagnosed with coronavirus disease 2019 (COVID-19) and hospitalized and to characterize their outcomes.MethodsData on patients with gout hospitalized for COVID-19 between March 12, 2020, and October 25, 2021, were extracted from the COVID-19 Global Rheumatology Alliance registry. Descriptive statistics were used to describe the demographics, comorbidities, medication exposures, and COVID-19 outcomes including oxygenation or ventilation support and death.ResultsOne hundred sixty-three patients with gout who developed COVID-19 and were hospitalized were included. The mean age was 63 years, and 85% were male. The majority of the group lived in the Western Pacific Region (35%) and North America (18%). Nearly half (46%) had two or more comorbidities, with hypertension (56%), cardiovascular disease (28%), diabetes mellitus (26%), chronic kidney disease (25%), and obesity (23%) being the most common. Glucocorticoids and colchicine were used pre-COVID-19 in 11% and 12% of the cohort, respectively. Over two thirds (68%) of the cohort required supplemental oxygen or ventilatory support during hospitalization. COVID-19-related death was reported in 16% of the overall cohort, with 73% of deaths documented in people with two or more comorbidities.ConclusionThis cohort of people with gout and COVID-19 who were hospitalized had high frequencies of ventilatory support and death. This suggests that patients with gout who were hospitalized for COVID-19 may be at risk of poor outcomes, perhaps related to known risk factors for poor outcomes, such as age and presence of comorbidity.

Sour cherry (Prunus cerasus L.) is an agriculturally valuable tree that produces fruits used in a range of culinary dishes, beverages, and other products. The progenitor species and number of origins of sour cherry remain unresolved. Here, we performed phylogenetic analyses of plastid genomes and nuclear genes from nine wild species and three historically important sour cherry cultivars. Our analyses identified Prunus fruticosa and Prunus avium as the closest extant relatives of the progenitor species of tetraploid sour cherry. Furthermore, our analyses revealed P. fruticosa as the likely maternal contributor. These findings and transcriptomic datasets should serve as valuable new resources to guide future breeding efforts in sour cherry.

ObjectiveThis study examined the impact of the COVID-19 pandemic on drinking and nicotine use through June of 2021 in a community-based sample of young adults.MethodData were from 348 individuals (49% female) enrolled in a long-term longitudinal study with an accelerated longitudinal design: the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) Study. Individuals completed pre-pandemic assessments biannually from 2016 to early 2020, then completed up to three web-based, during-pandemic surveys in June 2020, December 2020, and June 2021. Assessments when individuals were 18.8-22.4 years old (N = 1,458) were used to compare drinking and nicotine use pre-pandemic vs. at each of the three during-pandemic timepoints, adjusting for the age-related increases expected over time.ResultsCompared to pre-pandemic, participants were less likely to report past-month drinking in June or December 2020, but there was an increase in drinking days among drinkers in June 2020. By June 2021, both the prevalence of past-month drinking and number of drinking days among drinks were similar to pre-pandemic levels. On average, there were no statistically significant differences between pre-pandemic and during-pandemic time points for binge drinking, typical drinking quantity, or nicotine use. Young adults who reported an adverse financial impact of the pandemic showed increased nicotine use while their peers showed stable or decreased nicotine use.ConclusionInitial effects of the pandemic on alcohol use faded by June 2021, and on average there was little effect of the pandemic on nicotine use.

PurposeAdolescence is characterized by dramatic physical, social, and emotional changes, making teens particularly vulnerable to the mental health effects of the COVID-19 pandemic. This longitudinal study identifies young adolescents who are most vulnerable to the psychological toll of the pandemic and provides insights to inform strategies to help adolescents cope better in times of crisis.MethodsA data-driven approach was applied to a longitudinal, demographically diverse cohort of more than 3,000 young adolescents (11-14 years) participating in the ongoing Adolescent Brain Cognitive Development Study in the United States, including multiple prepandemic visits and three assessments during the COVID-19 pandemic (May-August 2020). We fitted machine learning models and provided a comprehensive list of predictors of psychological distress in individuals.ResultsPositive affect, stress, anxiety, and depressive symptoms were accurately detected with our classifiers. Female sex and prepandemic internalizing symptoms and sleep problems were strong predictors of psychological distress. Parent- and youth-reported pandemic-related psychosocial factors, including poorer quality and functioning of family relationships, more screen time, and witnessing discrimination in relation to the pandemic further predicted youth distress. However, better social support, regular physical activities, coping strategies, and healthy behaviors predicted better emotional well-being.DiscussionFindings highlight the importance of social connectedness and healthy behaviors, such as sleep and physical activity, as buffering factors against the deleterious effects of the pandemic on adolescents' mental health. They also point to the need for greater attention toward coping strategies that help the most vulnerable adolescents, particularly girls and those with prepandemic psychological problems.

ObjectiveTo evaluate the impact of telemedicine use during the coronavirus disease 2019 (COVID-19) pandemic on rheumatology trainees.MethodsA voluntary, anonymous, web-based survey was administered in English, Spanish, or French from August 19 to October 5, 2020. Adult and pediatric rheumatology trainees were invited to participate via social media and email. Using multiple-choice questions and Likert scales, the survey assessed prior and current telemedicine use, impact on training, and supervision after COVID-19 prompted rapid telemedicine implementation.ResultsSurveys were received from 302 trainees from 33 countries, with 83% in adult rheumatology training programs. Reported telemedicine use increased from 13% before the pandemic to 82% during the pandemic. United States trainees predominantly used video visits, whereas outside the United States telemedicine was predominantly audio only. Most (65%) evaluated new patients using telemedicine. More respondents were comfortable using telemedicine for follow-up patients (69%) than for new patients (25%). Only 39% of respondents reported receiving telemedicine-focused training, including instruction on software, clinical skills, and billing, whereas more than half of United States trainees (59%) had training. Postconsultation verbal discussion was the most frequent form of supervision; 24% reported no supervision. Trainees found that telemedicine negatively impacted supervision (50%) and the quality of clinical teaching received (70%), with only 9% reporting a positive impact.ConclusionsDespite widespread uptake of telemedicine, a low proportion of trainees received telemedicine training, and many lacked comfort in evaluating patients, particularly new patients. Inadequate supervision and clinical teaching were areas of concern. If telemedicine remains in widespread use, ensuring appropriate trainee supervision and teaching should be prioritized.

To determine the persistent effects of the pandemic on mental health in young adults, we categorized depressive symptom trajectories and sought factors that promoted a reduction in depressive symptoms in high-risk individuals. Specifically, longitudinal analysis investigated changes in the risk for depression before and during the pandemic until December 2021 in 399 young adults (57% female; age range: 22.8 ± 2.6 years) in the United States (U.S.) participating in the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. The Center for Epidemiologic Studies Depression Scale (CES-D-10) was administered multiple times before and during the pandemic. A score ≥10 identified individuals at high-risk for depression. Self-reported sleep behavior, substance use, and coping skills at the start of the pandemic were assessed as predictors for returning to low-risk levels while controlling for demographic factors. The analysis identified four trajectory groups regarding depression risk, with 38% being at low-risk pre-pandemic through 2021, 14% showing persistent high-risk pre-pandemic through 2021, and the remainder converting to high-risk either in June 2020 (30%) or later (18%). Of those who became high-risk in June 2020, 51% were no longer at high-risk in 2021. Logistic regression revealed that earlier bedtime and, for the older participants (mid to late twenties), better coping skills were associated with this declining risk. Results indicate divergence in trajectories of depressive symptoms, with a considerable number of young adults developing persistent depressive symptoms. Healthy sleep behavior and specific coping skills have the potential to promote remittance from depressive symptoms in the context of the pandemic.

Lipoprotein(a) [Lp(a)] is an independent, genetically determined, and causal risk factor for cardiovascular disease. Laboratory data have suggested an interaction of Lp(a) with platelet function, potentially caused by its interaction with platelet receptors. So far, the potential association of Lp(a) with platelet activation and reactivity has not been proven in larger clinical cohorts. This study analyzed intrinsic platelet reactivity before loading with clopidogrel 600 mg and on-treatment platelet reactivity tested 24 h following loading in patients undergoing elective coronary angiography. Platelet reactivity was tested by optical aggregometry following stimulation with collagen or adenosine diphosphate as well as by flow cytometry. Lp(a) levels were directly measured in all patients from fresh samples. The present analysis included 1912 patients. Lp(a) levels ranged between 0 and 332 mg/dl. There was a significant association of rising levels of Lp(a) with a higher prevalence of a history of ischemic heart disease (p

ObjectiveExecutive control continues to develop throughout adolescence and is vulnerable to alcohol use. Although longitudinal assessment is ideal for tracking executive function development and onset of alcohol use, prior testing experience must be distinguished from developmental trajectories.MethodWe used the Stroop Match-to-Sample task to examine the improvement of processing speed and specific cognitive and motor control over 4 years in 445 adolescents. The twice-minus-once-tested method was used and expanded to four test sessions to delineate prior experience (i.e., learning) from development. A General Additive Model evaluated the predictive value of age and sex on executive function development and potential influences of alcohol use on development.ResultsResults revealed strong learning between the first two assessments. Adolescents significantly improved their speed processing over 4 years. Compared with boys, girls enhanced ability to control cognitive interference and motor reactions. Finally, the influence of alcohol use initiation was tested over 4 years for development in 110 no/low, 110 moderate/heavy age- and sex-matched drinkers; alcohol effects were not detected in the matched groups.ConclusionsEstimation of learning effects is crucial for examining developmental changes longitudinally. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

BackgroundThe impact and consequences of the COVID-19 pandemic on people with rheumatic disease are unclear. We developed the COVID-19 Global Rheumatology Alliance Patient Experience Survey to assess the effects of the COVID-19 pandemic on people with rheumatic disease worldwide.MethodsSurvey questions were developed by key stakeholder groups and disseminated worldwide through social media, websites, and patient support organisations. Questions included demographics, rheumatic disease diagnosis, COVID-19 diagnosis, adoption of protective behaviours to mitigate COVID-19 exposure, medication access and changes, health-care access and communication with rheumatologists, and changes in employment or schooling. Adults age 18 years and older with inflammatory or autoimmune rheumatic diseases were eligible for inclusion. We included participants with and without a COVID-19 diagnosis. We excluded participants reporting only non-inflammatory rheumatic diseases such as fibromyalgia or osteoarthritis.Findings12 117 responses to the survey were received between April 3 and May 8, 2020, and of these, 10 407 respondents had included appropriate age data. We included complete responses from 9300 adults with rheumatic disease (mean age 46·1 years; 8375 [90·1%] women, 893 [9·6%] men, and 32 [0·3%] participants who identified as non-binary). 6273 (67·5%) of respondents identified as White, 1565 (16·8%) as Latin American, 198 (2·1%) as Black, 190 (2·0%) as Asian, and 42 (0·5%) as Native American or Aboriginal or First Nation. The most common rheumatic disease diagnoses included rheumatoid arthritis (3636 [39·1%] of 9300), systemic lupus erythematosus (2882 [31·0%]), and Sjögren's syndrome (1290 [13·9%]). Most respondents (6921 [82·0%] of 8441) continued their antirheumatic medications as prescribed. Almost all (9266 [99·7%] of 9297) respondents adopted protective behaviours to limit SARS-CoV-2 exposure. A change in employment status occurred in 2524 (27·1%) of 9300) of respondents, with a 13·6% decrease in the number in full-time employment (from 4066 to 3514).InterpretationPeople with rheumatic disease maintained therapy and followed public health advice to mitigate the risks of COVID-19. Substantial employment status changes occurred, with potential implications for health-care access, medication affordability, mental health, and rheumatic disease activity.FundingAmerican College of Rheumatology.

BackgroundWe describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine.MethodsFrom 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination.ResultsWe analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%.ConclusionAmong adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring.

BackgroundWe describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine.MethodsFrom 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination.ResultsWe analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%.ConclusionAmong adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring.

Many neurological diseases are characterized by gradual deterioration of brain structure andfunction. Large longitudinal MRI datasets have revealed such deterioration, in part, by applying machine and deep learning to predict diagnosis. A popular approach is to apply Convolutional Neural Networks (CNN) to extract informative features from each visit of the longitudinal MRI and then use those features to classify each visit via Recurrent Neural Networks (RNNs). Such modeling neglects the progressive nature of the disease, which may result in clinically implausible classifications across visits. To avoid this issue, we propose to combine features across visits by coupling feature extraction with a novel longitudinal pooling layer and enforce consistency of the classification across visits in line with disease progression. We evaluate the proposed method on the longitudinal structural MRIs from three neuroimaging datasets: Alzheimer's Disease Neuroimaging Initiative (ADNI, N=404), a dataset composed of 274 normal controls and 329 patients with Alcohol Use Disorder (AUD), and 255 youths from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). In allthree experiments our method is superior to other widely used approaches for longitudinal classification thus making a unique contribution towards more accurate tracking of the impact of conditions on the brain. The code is available at https://github.com/ouyangjiahong/longitudinal-pooling.

When a transmission hotspot for an environmentally persistent pathogen establishes in otherwise high-quality habitat, the disease may exert a strong impact on a host population. However, fluctuating environmental conditions lead to heterogeneity in habitat quality and animal habitat preference, which may interrupt the overlap between selected and risky habitats. We evaluated spatio-temporal patterns in anthrax mortalities in a plains zebra (Equus quagga) population in Etosha National Park, Namibia, incorporating remote-sensing and host telemetry data. A higher proportion of anthrax mortalities of herbivores was detected in open habitats than in other habitat types. Resource selection functions showed that the zebra population shifted habitat selection in response to changes in rainfall and vegetation productivity. Average to high rainfall years supported larger anthrax outbreaks, with animals congregating in preferred open habitats, while a severe drought forced animals into otherwise less preferred habitats, leading to few anthrax mortalities. Thus, the timing of anthrax outbreaks was congruent with preference for open plains habitats and a corresponding increase in pathogen exposure. Given shifts in habitat preference, the overlap in high-quality habitat and high-risk habitat is intermittent, reducing the adverse consequences for the population.

When a transmission hotspot for an environmentally persistent pathogen establishes in otherwise high-quality habitat, the disease may exert a strong impact on a host population. However, fluctuating environmental conditions lead to heterogeneity in habitat quality and animal habitat preference, which may interrupt the overlap between selected and risky habitats. We evaluated spatio-temporal patterns in anthrax mortalities in a plains zebra (Equus quagga) population in Etosha National Park, Namibia, incorporating remote-sensing and host telemetry data. A higher proportion of anthrax mortalities of herbivores was detected in open habitats than in other habitat types. Resource selection functions showed that the zebra population shifted habitat selection in response to changes in rainfall and vegetation productivity. Average to high rainfall years supported larger anthrax outbreaks, with animals congregating in preferred open habitats, while a severe drought forced animals into otherwise less preferred habitats, leading to few anthrax mortalities. Thus, the timing of anthrax outbreaks was congruent with preference for open plains habitats and a corresponding increase in pathogen exposure. Given shifts in habitat preference, the overlap in high-quality habitat and high-risk habitat is intermittent, reducing the adverse consequences for the population.

Many neurological diseases are characterized by gradual deterioration of brain structure andfunction. Large longitudinal MRI datasets have revealed such deterioration, in part, by applying machine and deep learning to predict diagnosis. A popular approach is to apply Convolutional Neural Networks (CNN) to extract informative features from each visit of the longitudinal MRI and then use those features to classify each visit via Recurrent Neural Networks (RNNs). Such modeling neglects the progressive nature of the disease, which may result in clinically implausible classifications across visits. To avoid this issue, we propose to combine features across visits by coupling feature extraction with a novel longitudinal pooling layer and enforce consistency of the classification across visits in line with disease progression. We evaluate the proposed method on the longitudinal structural MRIs from three neuroimaging datasets: Alzheimer's Disease Neuroimaging Initiative (ADNI, N=404), a dataset composed of 274 normal controls and 329 patients with Alcohol Use Disorder (AUD), and 255 youths from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). In allthree experiments our method is superior to other widely used approaches for longitudinal classification thus making a unique contribution towards more accurate tracking of the impact of conditions on the brain. The code is available at https://github.com/ouyangjiahong/longitudinal-pooling.

Exogenous causes, such as alcohol use, and endogenous factors, such as temperament and sex, can modulate developmental trajectories of adolescent neurofunctional maturation. We examined how these factors affect sexual dimorphism in brain functional networks in youth drinking below diagnostic threshold for alcohol use disorder (AUD). Based on the 3-year, annually acquired, longitudinal resting-state functional magnetic resonance imaging (MRI) data of 526 adolescents (12-21 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) cohort, developmental trajectories of 23 intrinsic functional networks (IFNs) were analyzed for (1) sexual dimorphism in 259 participants who were no-to-low drinkers throughout this period; (2) sex-alcohol interactions in two age- and sex-matched NCANDA subgroups (N = 76 each), half no-to-low, and half moderate-to-heavy drinkers; and (3) moderating effects of gender-specific alcohol dose effects and a multifactorial impulsivity measure on IFN connectivity in all NCANDA participants. Results showed that sex differences in no-to-low drinkers diminished with age in the inferior-occipital network, yet girls had weaker within-network connectivity than boys in six other networks. Effects of adolescent alcohol use were more pronounced in girls than boys in three IFNs. In particular, girls showed greater within-network connectivity in two motor networks with more alcohol consumption, and these effects were mediated by sensation-seeking only in girls. Our results implied that drinking might attenuate the naturally diminishing sexual differences by disrupting the maturation of network efficiency more severely in girls. The sex-alcohol-dose effect might explain why women are at higher risk of alcohol-related health and psychosocial consequences than men.

In the 1970s, William Tutte developed a clever algebraic approach, based on certain "invariants", to solve a functional equation that arises in the enumeration of properly colored triangulations. The enumeration of plane lattice walks confined to the first quadrant is governed by similar equations, and has led in the past 20 years to a rich collection of attractive results dealing with the nature (algebraic, D-finite or not) of the associated generating function, depending on the set of allowed steps, taken in $\{-1, 0,1\}^2$.We first adapt Tutte's approach to prove (or reprove) the algebraicity of all quadrant models known or conjectured to be algebraic. This includes Gessel's famous model, and the first proof ever found for one model with weighted steps. To be applicable, the method requires the existence of two rational functions called invariant and decoupling function respectively. When they exist, algebraicity follows almost automatically.Then, we move to a complex analytic viewpoint that has already proved very powerful, leading in particular to integral expressions for the generating function in the non-D-finite cases, as well as to proofs of non-D-finiteness. We develop in this context a weaker notion of invariant. Now all quadrant models have invariants, and for those that have in addition a decoupling function, we obtain integral-free expressions for the generating function, and a proof that this series is D-algebraic (that is, satisfies polynomial differential equations).Keywords: Lattice walks, enumeration, differentially algebraic series, conformal mappings.Mathematics Subject Classifications: 05A15, 34K06, 39A06, 30C20, 30D05

BackgroundCopper (Cu) is an essential metal mediating a variety of vital biological reactions with its redox property. Its dyshomeostasis has been associated with accelerated cognitive decline and neurodegenerative disorders, such as Alzheimer's disease (AD). However, underlying neurotoxic mechanisms elicited by dysregulated Cu remain largely elusive. We and others previously demonstrated that exposure to Cu in drinking water significantly exacerbated pathological hallmarks of AD and pro-inflammatory activation of microglia, coupled with impaired phagocytic capacity, in mouse models of AD.MethodsIn the present study, we extended our investigation to evaluate whether chronic Cu exposure to wild-type (WT) and J20 mouse model of AD perturbs homeostatic dynamics of microglia and contributes to accelerated transformation of microglia towards degenerative phenotypes that are closely associated with neurodegeneration. We further looked for evidence of alterations in the microglial morphology and spatial memory of the Cu-exposed mice to assess the extent of the Cu toxicity.ResultsWe find that chronic Cu exposure to pre-pathological J20 mice upregulates the translation of degenerative genes and represses homeostatic genes within microglia even in the absence amyloid-beta plaques. We also observe similar expression signatures in Cu-exposed WT mice, suggesting that excess Cu exposure alone could lead to perturbed microglial homeostatic phenotypes and contribute to accelerated cognitive decline.ConclusionOur findings highlight the risk of chronic Cu exposure on cognitive decline and altered microglia activation towards degenerative phenotypes. These changes may represent one of the key mechanisms linking Cu exposure or its dyshomeostasis to an increased risk for AD.

We report on a multiparticle coincidence experiment performed at the European X-ray Free-Electron Laser at the Small Quantum Systems instrument using a COLTRIMS reaction microscope. By measuring two ions and two electrons in coincidence, we investigate double core-hole generation in O_{2} molecules in the gas phase. Single-site and two-site double core holes have been identified and their molecular-frame electron angular distributions have been obtained for a breakup of the oxygen molecule into two doubly charged ions. The measured distributions are compared to results of calculations performed within the frozen- and relaxed-core Hartree-Fock approximations.

We report on a multiparticle coincidence experiment performed at the European X-ray Free-Electron Laser at the Small Quantum Systems instrument using a COLTRIMS reaction microscope. By measuring two ions and two electrons in coincidence, we investigate double core-hole generation in O_{2} molecules in the gas phase. Single-site and two-site double core holes have been identified and their molecular-frame electron angular distributions have been obtained for a breakup of the oxygen molecule into two doubly charged ions. The measured distributions are compared to results of calculations performed within the frozen- and relaxed-core Hartree-Fock approximations.

ObjectivesTo evaluate experiences and reactions after receiving a mailed, unsolicited human papillomavirus self-sampling kit and identify psychosocial correlates of using kits.MethodsSurvey participants were underscreened women aged 30-64 who were mailed human papillomavirus kits as part of a pragmatic trial at Kaiser Permanente Washington, a United States integrated health care system. Six months after the mailing, we invited kit returners and non-returners to complete a web survey that measured psychosocial factors (e.g. cervical cancer/human papillomavirus knowledge, attitudes toward screening), experiences, and reactions to kits. We compared responses between kit returners and non-returners.ResultsComparing 116 kit returners (272 invited) and 119 non-returners (1083 invited), we found no clinically significant differences in psychosocial factors. Overall, survey respondents showed knowledge gaps in human papillomavirus natural history (82% did not know human papillomavirus infection can clear on its own) and interpreting human papillomavirus test results (37% did not know a human papillomavirus-negative result indicates low cancer risk). Kit returners found kits convenient and easy to use (>90%). The most common reason for non-return was low confidence in ability to correctly use a kit, although many non-returners (49%) indicated that they would consider future use. Women reported low trust in human papillomavirus testing to identify women at high risk for cervical cancer (52% in returners, 42% in non-returners).ConclusionsScreening programs could improve uptake and acceptability of human papillomavirus self-sampling through outreach materials that emphasize the high efficacy of human papillomavirus testing for cervical cancer screening and educate patients about how to interpret results.

Hereditary hemorrhagic telangiectasia (HHT), a rare autosomal dominant disease mostly caused by mutations in three known genes (ENG, ACVRL1, and SMAD4), is characterized by the development of vascular malformations (VMs). Patients with HHT may present with mucocutaneous telangiectasia, as well as organ arteriovenous malformations (AVMs) of the central nervous system, lungs, and liver. Genotype-phenotype correlations have been well described in adults with HHT. We aimed to investigate genotype-phenotype correlations among pediatric HHT patients. Demographic, clinical, and genetic data were collected and analyzed in 205 children enrolled in the multicenter Brain Vascular Malformation Consortium HHT Project. A chi-square test was used to determine the association between phenotypic presentations and genotype. Among 205 patients (age range: 0-18 years; mean: 11 years), ENG mutation was associated with the presence of pulmonary AVMs (p < 0.001) and brain VM (p < 0.001). The presence of a combined phenotype-defined as both pulmonary AVMs and brain VMs-was also associated with ENG mutation. Gastrointestinal bleeding was rare (4.4%), but was associated with SMAD4 genotype (p < 0.001). We conclude that genotype-phenotype correlations among pediatric HHT patients are similar to those described among adults. Specifically, pediatric patients with ENG mutation have a greater prevalence of pulmonary AVMs, brain VMs, and a combined phenotype.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

BackgroundThe cerebellum is a target of alcoholism-related brain damage in adults, yet no study has prospectively tracked deviations from normal cerebellar growth trajectories in adolescents before and after initiating drinking.MethodsMagnetic resonance imaging tracked developmental volume trajectories of 10 cerebellar lobule and vermis tissue constituents in 548 no/low drinking youths age 12 to 21 years at induction into this 5-site, NCANDA (National Consortium on Alcohol and NeuroDevelopment in Adolescence) study. Over the 3- to 4-year longitudinal examination yielding 2043 magnetic resonance imaging scans, 328 youths remained no/low drinkers, whereas 220 initiated substantial drinking after initial neuroimaging.ResultsNormal growth trajectories derived from no/low drinkers indicated that gray matter volumes of lobules V and VI, crus II, lobule VIIB, and lobule X declined faster with age in male youths than in female youths, whereas white matter volumes in crus I and crus II and lobules VIIIA and VIIIB expanded faster in female youths than in male youths; cerebrospinal fluid volume expanded faster in most cerebellar regions of male youths than female youths. Drinkers exhibited accelerated gray matter decline in anterior lobules and vermis, accelerated vermian white matter expansion, and accelerated cerebrospinal fluid volumes expansion of anterior lobules relative to youths who remained no/low drinkers. Analyses including both alcohol and marijuana did not support an independent role for marijuana in alcohol effects on cerebellar gray matter trajectories.ConclusionsAlcohol use-related cerebellar growth trajectory differences from normal involved anterior lobules and vermis of youths who initiated substantial drinking. These regions are commonly affected in alcohol-dependent adults, raising the possibility that cerebellar structures affected by youthful drinking may be vulnerable to age-alcohol interactions in later adulthood.

A central motivation for the development of x-ray free-electron lasers has been the prospect of time-resolved single-molecule imaging with atomic resolution. Here, we show that x-ray photoelectron diffraction - where a photoelectron emitted after x-ray absorption illuminates the molecular structure from within - can be used to image the increase of the internuclear distance during the x-ray-induced fragmentation of an O2 molecule. By measuring the molecular-frame photoelectron emission patterns for a two-photon sequential K-shell ionization in coincidence with the fragment ions, and by sorting the data as a function of the measured kinetic energy release, we can resolve the elongation of the molecular bond by approximately 1.2 a.u. within the duration of the x-ray pulse. The experiment paves the road toward time-resolved pump-probe photoelectron diffraction imaging at high-repetition-rate x-ray free-electron lasers.

Hereditary hemorrhagic telangiectasia (HHT), a rare autosomal dominant disease mostly caused by mutations in three known genes (ENG, ACVRL1, and SMAD4), is characterized by the development of vascular malformations (VMs). Patients with HHT may present with mucocutaneous telangiectasia, as well as organ arteriovenous malformations (AVMs) of the central nervous system, lungs, and liver. Genotype-phenotype correlations have been well described in adults with HHT. We aimed to investigate genotype-phenotype correlations among pediatric HHT patients. Demographic, clinical, and genetic data were collected and analyzed in 205 children enrolled in the multicenter Brain Vascular Malformation Consortium HHT Project. A chi-square test was used to determine the association between phenotypic presentations and genotype. Among 205 patients (age range: 0-18 years; mean: 11 years), ENG mutation was associated with the presence of pulmonary AVMs (p < 0.001) and brain VM (p < 0.001). The presence of a combined phenotype-defined as both pulmonary AVMs and brain VMs-was also associated with ENG mutation. Gastrointestinal bleeding was rare (4.4%), but was associated with SMAD4 genotype (p < 0.001). We conclude that genotype-phenotype correlations among pediatric HHT patients are similar to those described among adults. Specifically, pediatric patients with ENG mutation have a greater prevalence of pulmonary AVMs, brain VMs, and a combined phenotype.

BackgroundDue to their high energy density and compatible physical properties, several monoterpenes have been investigated as potential renewable transportation fuels, either as blendstocks with petroleum or as drop-in replacements for use in vehicles (both heavy and light-weight) or in aviation. Sustainable microbial production of these biofuels requires the ability to utilize cheap and readily available feedstocks such as lignocellulosic biomass, which can be depolymerized into fermentable carbon sources such as glucose and xylose. However, common microbial production platforms such as the yeast Saccharomyces cerevisiae are not naturally capable of utilizing xylose, hence requiring extensive strain engineering and optimization to efficiently utilize lignocellulosic feedstocks. In contrast, the oleaginous red yeast Rhodosporidium toruloides is capable of efficiently metabolizing both xylose and glucose, suggesting that it may be a suitable host for the production of lignocellulosic bioproducts. In addition, R. toruloides naturally produces several carotenoids (C40 terpenoids), indicating that it may have a naturally high carbon flux through its mevalonate (MVA) pathway, providing pools of intermediates for the production of a wide range of heterologous terpene-based biofuels and bioproducts from lignocellulose.ResultsSixteen terpene synthases (TS) originating from plants, bacteria and fungi were evaluated for their ability to produce a total of nine different monoterpenes in R. toruloides. Eight of these TS were functional and produced several different monoterpenes, either as individual compounds or as mixtures, with 1,8-cineole, sabinene, ocimene, pinene, limonene, and carene being produced at the highest levels. The 1,8-cineole synthase HYP3 from Hypoxylon sp. E74060B produced the highest titer of 14.94 ± 1.84 mg/L 1,8-cineole in YPD medium and was selected for further optimization and fuel properties study. Production of 1,8-cineole from lignocellulose was also demonstrated in a 2L batch fermentation, and cineole production titers reached 34.6 mg/L in DMR-EH (Deacetylated, Mechanically Refined, Enzymatically Hydorlized) hydrolysate. Finally, the fuel properties of 1,8-cineole were examined, and indicate that it may be a suitable petroleum blend stock or drop-in replacement fuel for spark ignition engines.ConclusionOur results demonstrate that Rhodosporidium toruloides is a suitable microbial platform for the production of non-native monoterpenes with biofuel applications from lignocellulosic biomass.

BackgroundDue to their high energy density and compatible physical properties, several monoterpenes have been investigated as potential renewable transportation fuels, either as blendstocks with petroleum or as drop-in replacements for use in vehicles (both heavy and light-weight) or in aviation. Sustainable microbial production of these biofuels requires the ability to utilize cheap and readily available feedstocks such as lignocellulosic biomass, which can be depolymerized into fermentable carbon sources such as glucose and xylose. However, common microbial production platforms such as the yeast Saccharomyces cerevisiae are not naturally capable of utilizing xylose, hence requiring extensive strain engineering and optimization to efficiently utilize lignocellulosic feedstocks. In contrast, the oleaginous red yeast Rhodosporidium toruloides is capable of efficiently metabolizing both xylose and glucose, suggesting that it may be a suitable host for the production of lignocellulosic bioproducts. In addition, R. toruloides naturally produces several carotenoids (C40 terpenoids), indicating that it may have a naturally high carbon flux through its mevalonate (MVA) pathway, providing pools of intermediates for the production of a wide range of heterologous terpene-based biofuels and bioproducts from lignocellulose.ResultsSixteen terpene synthases (TS) originating from plants, bacteria and fungi were evaluated for their ability to produce a total of nine different monoterpenes in R. toruloides. Eight of these TS were functional and produced several different monoterpenes, either as individual compounds or as mixtures, with 1,8-cineole, sabinene, ocimene, pinene, limonene, and carene being produced at the highest levels. The 1,8-cineole synthase HYP3 from Hypoxylon sp. E74060B produced the highest titer of 14.94 ± 1.84 mg/L 1,8-cineole in YPD medium and was selected for further optimization and fuel properties study. Production of 1,8-cineole from lignocellulose was also demonstrated in a 2L batch fermentation, and cineole production titers reached 34.6 mg/L in DMR-EH (Deacetylated, Mechanically Refined, Enzymatically Hydorlized) hydrolysate. Finally, the fuel properties of 1,8-cineole were examined, and indicate that it may be a suitable petroleum blend stock or drop-in replacement fuel for spark ignition engines.ConclusionOur results demonstrate that Rhodosporidium toruloides is a suitable microbial platform for the production of non-native monoterpenes with biofuel applications from lignocellulosic biomass.

BackgroundUnderstanding rhino movement behavior, especially their recursive movements, holds significant promise for enhancing rhino conservation efforts, and protecting their habitats and the biodiversity they support. Here we investigate the daily, biweekly, and seasonal recursion behavior of rhinos, to aid conservation applications and increase our foundational knowledge about these important ecosystem engineers.MethodsUsing relocation data from 59 rhinos across northern Namibia and 8 years of sampling efforts, we investigated patterns in 24-h displacement at dawn, dusk, midday, and midnight to examine movement behaviors at an intermediate scale and across daily behavioral modes of foraging and resting. To understand recursion patterns across animals' short and long-term ranges, we built T-LoCoH time use grids to estimate recursive movement by each individual. Comparing these grids to contemporaneous MODIS imagery, we investigated productivity's influence on short-term space use and recursion. Finally, we investigated patterns of recursion within a year's home range, measuring the time to return to the most intensively used patches.ResultsTwenty four-hour displacements at dawn were frequently smaller than 24-h displacements at dusk or at midday and midnight resting periods. Recursion analyses demonstrated that short-term recursion was most common in areas of median rather than maximum NDVI values. Investigated across a full year, recursion analysis showed rhinos most frequently returned to areas within 8-21 days, though visits were also seen separated by months likely suggesting seasonality in range use.ConclusionsOur results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Recursion across larger time scales is also evident, and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.