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Access to authentic research is limited at the 7-12 science education level. At the same time, many local restoration projects would benefit from, but don't have access to a long-term system of monitoring. This project seeks to unite those two needs by developing a protocol for 7-12 classrooms to be able to participate in authentic research through long-term monitoring of a local restoration project. The protocol developed in this project was used by Jenison High School students at Grand Ravines Park. Grand Ravines Park is a recently acquired Ottawa County park with a history of anthropogenic disturbances. Shortly after the acquisition of the final section of the park, Ottawa County Parks and Recreation (OCPR) staff seeded the portions of the north side of the park with native grasses and forbs, and the south side of the park was not supplementally seeded. This study aimed to develop protocols for the student collection and analysis of vegetation and invertebrate biodiversity data in both the north and south sides of the park. Various metrics of plant and invertebrate biodiversity were compared between the seeded and unseeded areas. Students from Jenison High School were involved in the data collection and analysis, increasing their exposure to scientific research and field sampling and developing their scientific literacy. A long-term database was developed, with the goals of facilitating park management decisions and driving future student research questions.

In this interview study, the authors examined the process of coaching in the context of a year-long professional development initiative designed to support teachers' expertise in implementing culturally and linguistically responsive practices. Using transformative learning as a theoretical and analytical frame, they investigated 20 teachers' experiences with external coaches and identified relational and resource aspects of coaching that supported or hindered teachers' growth. In addition, data analysis showed how collaborative coaching relationships were related to teachers' movement through the phases of transformative learning. This study has implications for how external coaches work with teachers as part of professional learning and illustrates the importance of rooting the coach-teacher relationship in a shared understanding of teachers' context and lived experiences.

Majid Moshirfar,1– 3 Alex H Brown,4 Garrett N Manion,5 Kayvon A Moin,1 Phillip C Hoopes1 1Hoopes Vision Research Center, Hoopes Vision, Draper, UT, USA; 2John A. Moran Eye Center, University of Utah School of Medicine, Salt Lake City, UT, USA; 3Utah Lions Eye Bank, Murray, UT, USA; 4Department of Ophthalmology, University of Arizona College of Medicine – Phoenix, Phoenix, AZ, USA; 5Department of Ophthalmology, Creighton University School of Medicine, Omaha, NE, USACorrespondence: Majid Moshirfar, Hoopes Vision Research Center, 11820 S State St #200, Draper, UT, 84020, USA, Tel +1 801-568-0200, Fax +1 801-563-0200, Email cornea2020@me.comAbstract: Posterior capsular opacification (PCO), also known as “secondary cataract”, is a common complication following cataract surgery that can significantly impair visual acuity. The incidence of PCO varies widely in the literature, influenced by intraocular lens (IOL) type and patient risk factors. Neodymium-doped yttrium-aluminum-garnet (YAG) laser posterior capsulotomy is the standard treatment for PCO-related visual impairment. Recurrence of PCO after initial treatment with YAG capsulotomy, though more common in children, is rare in adults. Its underlying pathophysiological mechanisms are similar to that of primary PCO, which includes proliferation, migration, and/or clustering of lens epithelial cells (LECs), with subsequent reclosure of the posterior aperture. Potential risk factors for PCO recurrence that have been speculated through a comprehensive search of the current literature include younger age, female sex, high myopia, diabetes, vitrectomized status, uveitis, low-diopter IOLs, and certain IOL types with higher water content. We present a case of recurrent PCO in a highly myopic 48-year-old male following cataract surgery and implantable collamer lens (ICL) explantation who received a hydrophobic acrylic lens with 4% water content. Surgical techniques that may reduce recurrent PCO occurrence and appropriate postoperative care are emphasized to assist surgeons in their approach to patients at high-risk for this complication.Keywords: recurrent posterior capsule opacification, recurrent PCO, implantable collamer lens, ICL, repeat neodymium-doped yttrium-aluminum-garnet, repeat Nd:YAG, cataract surgery, posterior capsule reclosure, posterior capsule re-opacification, intraocular lens water content, IOL water content

Abstract Introduction The aim of this study was to compare outcomes of topography-guided laser-assisted in situ keratomileusis (TG-LASIK) and small incision lenticule extraction (SMILE®) for correcting myopia and myopic astigmatism. Methods In this prospective, randomized contralateral study, 34 patients (68 eyes) received TG-LASIK in one eye, and SMILE in their fellow eye. Efficacy, safety, predictability, higher-order aberrations, corneal tomography, biomechanics, and patient-reported outcomes (PROs) were assessed preoperatively and up to 3 months postoperatively. Results Both platforms showed comparable efficacy at 3 months (TG-LASIK 1.08 ± 0.19; SMILE 0.98 ± 0.17, p = 0.055). However, TG-LASIK demonstrated quicker visual recovery, with 63% and 89% achieving uncorrected distance visual acuity (UDVA) of 20/16 or better at 1 day and 1 week, respectively, compared to SMILE (34% and 63%; p 0.05). Reported symptoms of glare, halos, rings, starbursts, or dry eye did not significantly differ between groups at 3 months (p > 0.05). Overall, 59% of patients preferred their TG-LASIK treated eye at 1 month, but 65% of patients had no specific eye preference at 3 months. Conclusion TG-LASIK and SMILE demonstrate excellent and comparable efficacy, safety, and predictability at 3 months, but TG-LASIK offers faster postoperative visual recovery at 1 day and 1 week. TG-LASIK induces fewer HOAs than SMILE, but both procedures affect corneal biomechanics similarly. Trial Registration ClincialTrials.gov identifier, NCT05611294.

A growing body of critical care research draws on real-world data from electronic health records (EHRs). The bedside clinician has myriad data sources to aid in clinical decision-making, but the lack of data sharing and harmonization standards leaves much of this data out of reach for multi-institution critical care research. The Society of Critical Care Medicine (SCCM) Discovery Data Science Campaign convened a panel of critical care and data science experts to explore and document unique advantages and opportunities for leveraging EHR data in critical care research. This article reviews and illustrates six organizing topics (data domains and common data elements; data harmonization; data quality; data interoperability and digital infrastructure; data access, sharing, and governance; and ethics and equity) as a data science primer for critical care researchers, laying a foundation for future publications from the SCCM Discovery Data Harmonization and Sharing Guiding Principles Panel.

As part of U.S. national efforts to combat the detrimental effect of global climate change, the National Institute of Standards and Technology (NIST) was recently tasked to support efforts in direct air capture (DAC) of carbon dioxide research and deployment. In order to develop test procedures, materials, and documentary standards, key characterization methods relevant to DAC materials have been investigated and used to identify desirable properties for a potential Standard Reference Material (SRM). Select amine-supported materials that previously showed potential for DAC applications have been characterized using commonly available laboratory methods. Further insights into the adsorption characteristics have been gained from developing and applying more specialized characterization tools ideal for probing low concentrations of carbon dioxide. A broad suite of capabilities that examine relevant properties under appropriate conditions gives the most profound insights into a material’s specific performance. We advocate for even more specialized capabilities to be developed and standardized to quantitatively monitor the interactions of CO2 with molecular species in complex and often disordered systems to advance DAC and support carbon dioxide reduction (CDR) in general.

Summary: Background: Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. Methods: This study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud-computing platforms using multiple approaches (e.g., hard prompting, retrieval augmented generation, and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Confusion-matrix-based scores were used for model evaluation. Findings: We used a randomly annotated sample of 4949 note sections from 1969 patients (women: 1046 [53.1%]; age: mean, 76.0 [SD, 13.3] years), filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1996 note sections from 1161 patients (women: 619 [53.3%]; age: mean, 76.5 [SD, 10.2] years) without keyword filtering was utilised. GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models in terms of all evaluation metrics with statistical significance (p

Abstract BackgroundSystematic literature review (SLR), a robust method to identify and summarize evidence from published sources, is considered to be a complex, time-consuming, labor-intensive, and expensive task. ObjectiveThis study aimed to present a solution based on natural language processing (NLP) that accelerates and streamlines the SLR process for observational studies using real-world data. MethodsWe followed an agile software development and iterative software engineering methodology to build a customized intelligent end-to-end living NLP-assisted solution for observational SLR tasks. Multiple machine learning–based NLP algorithms were adopted to automate article screening and data element extraction processes. The NLP prediction results can be further reviewed and verified by domain experts, following the human-in-the-loop design. The system integrates explainable articificial intelligence to provide evidence for NLP algorithms and add transparency to extracted literature data elements. The system was developed based on 3 existing SLR projects of observational studies, including the epidemiology studies of human papillomavirus–associated diseases, the disease burden of pneumococcal diseases, and cost-effectiveness studies on pneumococcal vaccines. ResultsOur Intelligent SLR Platform covers major SLR steps, including study protocol setting, literature retrieval, abstract screening, full-text screening, data element extraction from full-text articles, results summary, and data visualization. The NLP algorithms achieved accuracy scores of 0.86-0.90 on article screening tasks (framed as text classification tasks) and macroaverage F1 scores of 0.57-0.89 on data element extraction tasks (framed as named entity recognition tasks). ConclusionsCutting-edge NLP algorithms expedite SLR for observational studies, thus allowing scientists to have more time to focus on the quality of data and the synthesis of evidence in observational studies. Aligning the living SLR concept, the system has the potential to update literature data and enable scientists to easily stay current with the literature related to observational studies prospectively and continuously.

Tuberculous meningitis (TBM) has considerable mortality and morbidity, and it often presents therapeutic challenges when complicated by paradoxical reactions (PRs). Here, the clinical course of four cases of TBM patients complicated by PRs in a longitudinal TB cohort is described while also providing insights from the larger clinical cohort. Research flow cytometry, biomarker analysis, and drug concentrations were performed on available samples. All participants were initiated on standard antituberculosis therapy (ATT) and enrolled at the onset of PRs (PR group) or 2–4 months after the start of ATT (controls). The four TBM participants highlighted here presented with fevers, headaches, neurological deficits, and fatigue at the initial presentation. Upon diagnosis, all were initiated on rifampin, isoniazid, pyrazinamide, and ethambutol (RHZE) at standard doses and on corticosteroids. The median time to first PR was 37 days with recrudescence of initial TBM signs and symptoms at the time of PR. At the time of referral, all participants had low drug concentrations requiring dose optimization and regimen intensification as well as recrudescent flares upon corticosteroid taper, with one individual developing enlargement of tuberculoma 1 year following completion of ATT. Based on biomarkers and flow cytometry, PRs are characterized by elevated interferon-gamma and ferritin levels in the plasma compared to controls. In the TBM participants, T-cell activation with elevated levels of inflammatory biomarkers in the cerebrospinal fluid (CSF) was seen at the time of PR. These unique and highly detailed TBM cases provide insights into the pathogenesis of PRs, which may assist with future diagnostics and treatment.

Abstract Objective Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. Methods This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. Results and conclusions The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

IntroductionKidney transplantation is the optimal treatment for end-stage kidney disease; however, premature allograft loss remains a serious issue. While many high-throughput omics studies have analyzed patient allograft biospecimens, integration of these datasets is challenging, which represents a considerable barrier to advancing our understanding of the mechanisms of allograft loss.MethodsTo facilitate integration, we have created a curated database containing all open-access high-throughput datasets from human kidney transplant studies, termed NephroDIP (Nephrology Data Integration Portal). PubMed was searched for high-throughput transcriptomic, proteomic, single nucleotide variant, metabolomic, and epigenomic studies in kidney transplantation, which yielded 9,964 studies.ResultsFrom these, 134 studies with available data detailing 260 comparisons and 83,262 molecules were included in NephroDIP v1.0. To illustrate the capabilities of NephroDIP, we have used the database to identify common gene, protein, and microRNA networks that are disrupted in patients with chronic antibody-mediated rejection, the most important cause of late allograft loss. We have also explored the role of an immunomodulatory protein galectin-1 (LGALS1), along with its interactors and transcriptional regulators, in kidney allograft injury. We highlight the pathways enriched among LGALS1 interactors and transcriptional regulators in kidney fibrosis and during immunosuppression.DiscussionNephroDIP is an open access data portal that facilitates data visualization and will help provide new insights into existing kidney transplant data through integration of distinct studies and modules (https://ophid.utoronto.ca/NephroDIP).

BackgroundVaccines serve as a crucial public health tool, although vaccine hesitancy continues to pose a significant threat to full vaccine uptake and, consequently, community health. Understanding and tracking vaccine hesitancy is essential for effective public health interventions; however, traditional survey methods present various limitations. ObjectiveThis study aimed to create a real-time, natural language processing (NLP)–based tool to assess vaccine sentiment and hesitancy across 3 prominent social media platforms. MethodsWe mined and curated discussions in English from Twitter (subsequently rebranded as X), Reddit, and YouTube social media platforms posted between January 1, 2011, and October 31, 2021, concerning human papillomavirus; measles, mumps, and rubella; and unspecified vaccines. We tested multiple NLP algorithms to classify vaccine sentiment into positive, neutral, or negative and to classify vaccine hesitancy using the World Health Organization’s (WHO) 3Cs (confidence, complacency, and convenience) hesitancy model, conceptualizing an online dashboard to illustrate and contextualize trends. ResultsWe compiled over 86 million discussions. Our top-performing NLP models displayed accuracies ranging from 0.51 to 0.78 for sentiment classification and from 0.69 to 0.91 for hesitancy classification. Explorative analysis on our platform highlighted variations in online activity about vaccine sentiment and hesitancy, suggesting unique patterns for different vaccines. ConclusionsOur innovative system performs real-time analysis of sentiment and hesitancy on 3 vaccine topics across major social networks, providing crucial trend insights to assist campaigns aimed at enhancing vaccine uptake and public health.

IntroductionNontuberculous mycobacteria (NTM) mediated infections are important to consider in cases with neuroinflammatory presentations. We aimed to characterize cases of NTM with neurological manifestations at the National Institutes of Health (NIH) Clinical Center and review the relevant literature.Materials and methodsBetween January 1995 and December 2020, six cases were identified. Records were reviewed for demographic, clinical, and radiological characteristics. A MEDLINE search found previously reported cases. Data were extracted, followed by statistical analysis to compare two groups [cases with slow-growing mycobacteria (SGM) vs. those with rapidly growing mycobacteria (RGM)] and evaluate for predictors of survival. NIH cases were evaluated for clinical and radiological characteristics. Cases from the literature were reviewed to determine the differences between SGM and RGM cases and to identify predictors of survival.ResultsSix cases from NIH were identified (age 41 ± 13, 83% male). Five cases were caused by SGM [Mycobacterium avium complex (MAC) n = 4; Mycobacterium haemophilum n = 1] and one due to RGM (Mycobacterium abscessus). Underlying immune disorders were identified only in the SGM cases [genetic (n = 2), HIV (n = 1), sarcoidosis (n = 1), and anti-interferon-gamma antibodies (n = 1)]. All cases were diagnosed using tissue analysis. A literature review found 81 reports on 125 cases (SGM n = 85, RGM n = 38, non-identified n = 2). No immune disorder was reported in 26 cases (21%). Within SGM cases, the most common underlying disease was HIV infection (n = 55, 65%), and seizures and focal lesions were more common. In RGM cases, the most common underlying condition was neurosurgical intervention or implants (55%), and headaches and meningeal signs were common. Tissue-based diagnosis was used more for SGM than RGM (39% vs. 13%, p = 0.04). Survival rates were similar in both groups (48% SGM and 55% in RGM). Factors associated with better survival were a solitary CNS lesion (OR 5.9, p = 0.01) and a diagnosis made by CSF sampling only (OR 9.9, p = 0.04).DiscussionNTM infections cause diverse neurological manifestations, with some distinctions between SGM and RGM infections. Tissue sampling may be necessary to establish the diagnosis, and an effort should be made to identify an underlying immune disorder.

IntroductionCOVID-19 patients can develop autoantibodies against a variety of secreted and membrane proteins, including some expressed on lymphocytes. However, it is unclear what proportion of patients might develop anti-lymphocyte antibodies (ALAb) and what functional relevance they might have.MethodsWe evaluated the presence and lytic function of ALAb in the sera of a cohort of 85 COVID-19 patients (68 unvaccinated and 17 vaccinated) assigned to mild (N=63), or moderate/severe disease (N=22) groups. Thirty-seven patients were followed-up after recovery. We also analyzed in vivo complement deposition on COVID-19 patients’ lymphocytes and examined its correlation with lymphocyte numbers during acute disease.ResultsCompared with healthy donors (HD), patients had an increased prevalence of IgM ALAb, which was significantly higher in moderate/severe disease patients and persisted after recovery. Sera from IgM ALAb+ patients exhibited complement-dependent cytotoxicity (CDC) against HD lymphocytes. Complement protein C3b deposition on patients’ CD4 T cells was inversely correlated with CD4 T cell numbers. This correlation was stronger in moderate/severe disease patients.DiscussionIgM ALAb and complement activation against lymphocytes may contribute to the acute lymphopenia observed in COVID-19 patients.

Background Contemporary data describing the national trends on vascular risk factor control among stroke survivors are limited. Methods and Results This is a cross‐sectional analysis of the National Health and Nutrition Examination Survey cycles 2009 to 2010 to 2017 to March 2020. Adults (≥18 years of age) with a self‐reported diagnosis of stroke were identified. Age‐adjusted trends in hypertension, diabetes, and hyperlipidemia control were examined. Sex and racial differences in vascular risk factor control were also investigated. Among 32 497 adult individuals who participated in the National Health and Nutrition Examination Survey, 1354 participants (4.2%) self‐reported a prior diagnosis of stroke (55% were women). The rates of age‐adjusted blood pressure control worsened when using the cutoff

Wearable, disposable, implantable and lightweight electronic devices all require low power consumption, typically less than 3 V. Polymerized ionic liquids represent an emerging class of dielectric materials which can enable low voltage organic thin film transistor operation (OTFT) while in the solid state, reducing the potential for toxic or flammable electrolyte leaks. Here we show that bottom gate bottom contact OTFTs were successfully fabricated using a library of 12 poly-(styrene)-b-poly(1-(4-vinylbenzyl)-3-butylimidazolium-r-poly(ethylene glycol) methyl ether methacrylate) block copolymers with varying VBBI+ and PEGMA ratios, and can achieve OTFTs that turn on between 0 and 1 V. We demonstrate that the poly(ionic liquid) microstructure dictates the self-assembly which correlates to OTFT performance. Notably, we indicate that changing the surface chemistry of the substrate the poly(ionic liquid) is cast on is less significant in driving block copolymer self-assembly compared to block ratios and the counter ion. We also report that the semiconductor crystalline domains are similar when deposited on the poly(ionic liquids), however the films differ in terms of semiconductor molecular order in the amorphous domains. Overall, we demonstrate that device performance is primarily linked to the poly(ionic liquid) self-assembly, while also highlighting the importance of both the crystalline and amorphous domains in the semiconductor structure of thin films. [ABSTRACT FROM AUTHOR]

Tuberculous meningitis (TBM) has considerable mortality and morbidity, and it often presents therapeutic challenges when complicated by paradoxical reactions (PRs). Here, the clinical course of four cases of TBM patients complicated by PRs in a longitudinal TB cohort is described while also providing insights from the larger clinical cohort. Research flow cytometry, biomarker analysis, and drug concentrations were performed on available samples. All participants were initiated on standard antituberculosis therapy (ATT) and enrolled at the onset of PRs (PR group) or 2–4 months after the start of ATT (controls). The four TBM participants highlighted here presented with fevers, headaches, neurological deficits, and fatigue at the initial presentation. Upon diagnosis, all were initiated on rifampin, isoniazid, pyrazinamide, and ethambutol (RHZE) at standard doses and on corticosteroids. The median time to first PR was 37 days with recrudescence of initial TBM signs and symptoms at the time of PR. At the time of referral, all participants had low drug concentrations requiring dose optimization and regimen intensification as well as recrudescent flares upon corticosteroid taper, with one individual developing enlargement of tuberculoma 1 year following completion of ATT. Based on biomarkers and flow cytometry, PRs are characterized by elevated interferon-gamma and ferritin levels in the plasma compared to controls. In the TBM participants, T-cell activation with elevated levels of inflammatory biomarkers in the cerebrospinal fluid (CSF) was seen at the time of PR. These unique and highly detailed TBM cases provide insights into the pathogenesis of PRs, which may assist with future diagnostics and treatment. [ABSTRACT FROM AUTHOR]

In recent years, short-form social media videos have emerged as an important source of health-related advice. In this study, we investigate whether experts or ordinary users in such videos are more effective in debunking the common misperception that talking about suicide should be avoided. We also explore a new trend on TikTok and other platforms, in which users attempt to back up their arguments by displaying scientific articles in the background of their videos. To test the effect of source type (expert vs. ordinary user) and scientific references (present or absent), we conducted a 2 × 2 between-subject plus control group experiment (n = 956). In each condition, participants were shown a TikTok video that was approximately 30 seconds long. Our findings show that in all four treatment groups, participants reduced their misperceptions on the topic. The expert was rated as being more authoritative on the topic compared to the ordinary user. However, the expert was also rated as being less credible compared to the ordinary user. The inclusion of a scientific reference did not make a difference. Thus, both experts and ordinary users may be similarly persuasive in a short-form video environment. [ABSTRACT FROM AUTHOR]

Violence among children has been considered one of the fundamental issues inhibiting optimal child well‐being and learning. Violence is widespread in Albania. Understanding the factors that affect it and the complex nature of violence itself requires looking at root social, cultural and economic factors and the normative influences on these factors. This study aimed to explore social and gender norms impacting school‐related gender‐based violence, and children's potential role in challenging these social norms. This article focuses on findings from research in two schools in Albania, particularly on what children and adult‐supporters shared about their understanding of social and gender norms that perpetuate violence, and their recommendations for policy and practice to address them. [ABSTRACT FROM AUTHOR]

Following record-high public support for improved teacher salaries, many states initiated a variety of pandemic-era reforms to teacher compensation policies to improve teacher morale and retention. In this article, we examine a minimum teacher salary reform in Missouri, a state home to a diverse geographic landscape including major metropolitan areas and large rural regions. On the one hand, we estimate eligible teachers would receive sizable salary increases averaging almost eight percent. Conversely, these teachers were located almost exclusively in the state's rural areas, effectively excluding most urban teachers and students and, due to the state's non-white ethnoracial concentration in urban metropolitan areas, virtually all of the state's non-White teachers and students. As states craft policy reforms to support their teacher workforces, attention must be devoted to the magnitude and the distribution of funding to ensure its equitable allocation across teacher and student characteristics and district urbanicity. [ABSTRACT FROM AUTHOR]

Navigating health care as a transgender adolescent presents a multitude of unique challenges that warrant careful consideration. Transgender individuals often encounter barriers such as a lack of knowledgeable health care providers, limited access to gender-affirming care, and concerns about confidentiality, safety, and acceptance. This case report of a transgender male with a history of a urinary tract infection examines the issues facing transgender adolescents in their pursuit of appropriate and sensitive health care and the need for normalizing gender-affirming medical care. [ABSTRACT FROM AUTHOR]

Background Periprocedural ischemic stroke remains a serious complication in patients undergoing transcatheter aortic valve replacement (TAVR). We used a novel robotic transcranial Doppler (TCD) system equipped with artificial intelligence (AI) for real-time continuous intraoperative neuromonitoring during TAVR to establish the safety and potential validity of this tool in detecting cerebral emboli, report the quantity and distribution of high intensity transient signals (HITS) with and without cerebral protection, and correlate HITS occurrence with various procedural steps. Methods Consecutive patients undergoing TAVR procedures during which the robotic system was used between October 2021 and May 2022 were prospectively enrolled in this pilot study. The robotic TCD system included autonomous adjustment of the TCD probes and AI-assisted post-processing of HITS and other cerebral flow parameters. Basic demographics and procedural details were recorded. Continuous variables were analyzed by a two-sample Mann-Whitney t-test and categorical variables by a χ² or Fisher test. Results Thirty-one patients were prospectively enrolled (mean age 79.9±7.6 years; 16 men (51.6%)). Mean aortic valve stenotic area was 0.7 cm² and mean aortic-ventricular gradient was 43 mmHg (IQR 31.5-50 mmHg). Cerebral protection was used in 16 cases (51.6%). Significantly fewer emboli were observed in the protection group than in the non-protection group (mean 470.38 vs 693.33; p=0.01). Emboli counts during valve positioning and implantation were significantly different in the protection and non-protection groups (mean 249.92 and 387.5, respectively; p=0.01). One (4%) transient ischemic attack occurred post-procedurally in the non-protection group. Conclusion We describe a novel real-time intraoperative neuromonitoring tool used in patients undergoing TAVR. Significantly fewer HITS were detected with protection. Valve positioning-implantation was the most significant stage for intraprocedural HITS. [ABSTRACT FROM AUTHOR]

Introduction: Kidney transplantation is the optimal treatment for end-stage kidney disease; however, premature allograft loss remains a serious issue. While many high-throughput omics studies have analyzed patient allograft biospecimens, integration of these datasets is challenging, which represents a considerable barrier to advancing our understanding of the mechanisms of allograft loss. Methods: To facilitate integration, we have created a curated database containing all open-access high-throughput datasets from human kidney transplant studies, termed NephroDIP (Nephrology Data Integration Portal). PubMed was searched for high-throughput transcriptomic, proteomic, single nucleotide variant, metabolomic, and epigenomic studies in kidney transplantation, which yielded 9,964 studies. Results: From these, 134 studies with available data detailing 260 comparisons and 83,262 molecules were included in NephroDIP v1.0. To illustrate the capabilities of NephroDIP, we have used the database to identify common gene, protein, and microRNA networks that are disrupted in patients with chronic antibody-mediated rejection, the most important cause of late allograft loss. We have also explored the role of an immunomodulatory protein galectin-1 (LGALS1), along with its interactors and transcriptional regulators, in kidney allograft injury. We highlight the pathways enriched among LGALS1 interactors and transcriptional regulators in kidney fibrosis and during immunosuppression. Discussion: NephroDIP is an open access data portal that facilitates data visualization and will help provide new insights into existing kidney transplant data through integration of distinct studies and modules (https://ophid.utoronto.ca/NephroDIP). [ABSTRACT FROM AUTHOR]

BackgroundObjectiveMethodsResultsConclusionChronic painful temporomandibular disorders (TMD) are a functional pain syndrome that embodies a spectrum of clinical manifestations and expresses great complexity through the coexistence of multiple comorbidities.Evaluate the prevalence of pain comorbidities, explore the correlation between comorbidities, kinesiophobia, catastrophizing, and pain disability at baseline, and determine variables of interest for prediction response to physiotherapy interventions at different follow-up times.This is a secondary analysis of a previously conducted randomized controlled trial (RCT). Outcomes and covariables for this secondary analysis were collected from subjects with chronic TMD (≥3 months), based on the DC/TMD diagnostic criteria, assigned to a multimodal treatment and a second manual therapy control group. The participants underwent follow-up assessment at 7 and 19 weeks. The outcomes (dependent variables) for these analyses were craniofacial pain disability, catastrophizing, and kinesiophobia. However, these outcomes were also used as covariables of interest in addition to comorbidity prevalence and severity at baseline for different analyses. We performed linear regression analyses to determine the association between our outcomes and covariables at baseline and at different follow-ups.Comorbidity severity explained craniofacial pain disability at baseline, showing a strong correlation (Standardized B: 0.40, p-value: 0.017). Higher comorbidity severity, led to higher craniofacial pain score. Comorbidity severity and baseline catastrophizing predicted a better response to treatment for craniofacial pain improvements at short and long term (R2 .22, p-value : 0.009 and R2 .19, p-value: 0.02 respectively).This study provides insight into the prevention and clinical management of chronic pain related to TMD. [ABSTRACT FROM AUTHOR]