A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation.

BACKGROUND: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC). OBJECTIVE: This study aims to highlight the current limitations of existing NLP algorithm development approaches that are exacerbated by NLP tasks surrounding emergent clinical concepts and to illustrate our approach to addressing these issues through the use case of developing an NLP system for the signs and symptoms of COVID-19 and PASC. METHODS: We used 2 preexisting studies on PASC as a baseline to determine a set of concepts that should be extracted by NLP. This concept list was then used in conjunction with the Unified Medical Language System to autonomously generate an expanded lexicon to weakly annotate a training set, which was then reviewed by a human expert to generate a fine-tuned NLP algorithm. The annotations from a fully human-annotated test set were then compared with NLP results from the fine-tuned algorithm. The NLP algorithm was then deployed to 10 additional sites that were also running our NLP infrastructure. Of these 10 sites, 5 were used to conduct a federated evaluation of the NLP algorithm. RESULTS: An NLP algorithm consisting of 12,234 unique normalized text strings corresponding to 2366 unique concepts was developed to extract COVID-19 or PASC signs and symptoms. An unweighted mean dictionary coverage of 77.8% was found for the 5 sites. CONCLUSIONS: The evolutionary and time-critical nature of the PASC NLP task significantly complicates existing approaches to NLP algorithm development. In this work, we present a hybrid approach using the Open Health Natural Language Processing Toolkit aimed at addressing these needs with a dictionary-based weak labeling step that minimizes the need for additional expert annotation while still preserving the fine-tuning capabilities of expert involvement.

Efficacy of providing energy expenditure information to guide weight loss interventions in people with obesity: A randomized controlled trial.

Resting energy expenditure (REE) and metabolic fuel utilization (carbohydrate or fat) proxied by respiratory quotient (RQ) from indirect calorimetry enables more precise measurement of energy needs and fat oxidation capacity. The study compared the effectiveness of providing energy expenditure information during diet and exercise weight intervention versus standard of care (SOC) on weight loss outcomes. Fifty-two participants with obesity were recruited from a specialist weight loss service, randomized 1:1 to intervention (INT) or SOC only. Participants in INT received four-weekly dietetic counselling, using biofeedback from energy expenditure data to recommend caloric restriction and physical activity goals, in addition to SOC. The primary outcome was the mean difference in weight loss between both groups after 24 weeks. Secondary outcomes include participant acceptability and tolerability using indirect calorimetry. Participants in the INT group demonstrated additional weight loss (-2.3 kg [95% CI: -3.1, -1.5]; p <.001), reduced waist circumference (-3.9 cm [95% CI: -5.48, -2.26]; p <.001), and decreased body fat percentage (-1.5% [95% CI:-2.31, -0.72], p <.001), compared to SOC, after adjusting for baseline body mass index, age, and sex. Forty-two percent (10/24) of participants in INT group achieved the minimum clinically significant threshold of 5% weight loss from baseline, compared to 8% (2/26) in the SOC group (p = .007). Participant acceptability and tolerability of indirect calorimetry were high, with mean scores of 4.5 ± 0.6 and 4.2 ± 0.7 (5-point Likert scale). The study establishes the safety and practical integration of biofeedback using indirect calorimetry promoting improved self-regulation and enhancing weight loss.

Adoption of the OMOP CDM for Cancer Research using Real-world Data: Current Status and Opportunities.

Background: The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) that is developed and maintained by the Observational Health Data Sciences and Informatics (OHDSI) community supports large scale cancer research by enabling distributed network analysis. As the number of studies using the OMOP CDM for cancer research increases, there is a growing need for an overview of the scope of cancer research that relies on the OMOP CDM ecosystem. Objectives: In this study, we present a comprehensive review of the adoption of the OMOP CDM for cancer research and offer some insights on opportunities in leveraging the OMOP CDM ecosystem for advancing cancer research. Materials and Methods: Published literature databases were searched to retrieve OMOP CDM and cancer-related English language articles published between January 2010 and December 2023. A charting form was developed for two main themes, i.e., clinically focused data analysis studies and infrastructure development studies in the cancer domain. Results: In total, 50 unique articles were included, with 30 for the data analysis theme and 23 for the infrastructure theme, with 3 articles belonging to both themes. The topics covered by the existing body of research was depicted. Conclusion: Through depicting the status quo of research efforts to improve or leverage the potential of the OMOP CDM ecosystem for advancing cancer research, we identify challenges and opportunities surrounding data analysis and infrastructure including data quality, advanced analytics methodology adoption, in-depth phenotypic data inclusion through NLP, and multisite evaluation.

Power analyses to inform Duplex Sequencing study designs for MutaMouse liver and bone marrow.

Regulatory genetic toxicology testing is essential for identifying potentially mutagenic hazards. Duplex Sequencing (DS) is an error-corrected next-generation sequencing technology that provides substantial advantages for mutation analysis over conventional mutagenicity assays including: improved accuracy of mutation detection, ability to measure changes in mutation spectrum, and applicability across diverse biological models. To apply DS for regulatory toxicology testing, power analyses are required to determine suitable sample sizes and study designs. In this study, we explored study designs to achieve sufficient power for various effect sizes in chemical mutagenicity assessment. We collected data from MutaMouse bone marrow and liver samples that were analyzed by DS using TwinStrand's Mouse Mutagenesis Panel. Average duplex reads achieved in two separates studies on liver and bone marrow were 8.4 × 108 (± 7.4 × 107) and 9.5 × 108 (± 1.0 × 108), respectively. Baseline mean mutation frequencies (MF) were 4.6 × 10-8 (± 6.7 × 10-9) and 4.6 × 10-8 (± 1.1 × 10-8), with estimated standard deviations for the animal-to-animal random effect of 0.15 and 0.20, for liver and bone marrow, respectively. We conducted simulation analyses based on these empirically derived parameters. We found that a sample size of four animals per group is sufficient to obtain over 80% power to detect a two-fold change in MF relative to baseline. In addition, we estimated the minimal total number of informative duplex bases sequenced with different sample sizes required to retain power for various effect sizes. Our work provides foundational data for establishing suitable study designs for mutagenicity testing using DS.

The tales of two cities: use of evidence for introducing 20 miles per hour speed limits in Edinburgh and Belfast (United Kingdom).

BACKGROUND: In 2016, large-scale 20 miles per hour speed limits were introduced in the United Kingdom cities of Edinburgh and Belfast. This paper investigates the role that scientific evidence played in the policy decisions to implement lower speed limits in the two cities. METHODS: Using a qualitative case study design, we undertook content analysis of a range of documents to explore and describe the evolution of the two schemes and the ways in which evidence informed decision-making. In total, we identified 16 documents for Edinburgh, published between 2006 and 2016, and 19 documents for Belfast, published between 2002 and 2016. FINDINGS: In both cities, evidence on speed, collisions and casualties was important for initiating discussions on large-scale 20 mph policies. However, the narrative shifted over time to the idea that 20 mph would contribute to a wider range of aspirations, none of which were firmly grounded in evidence, but may have helped to neutralize opposing discourses. DISCUSSION AND CONCLUSIONS: The relationship between evidence and decision-making in Edinburgh and Belfast was neither simple nor linear. Widening of the narrative appears to have helped to frame the idea in such a way that it had broad acceptability, without which there would have been no implementation, and probably a lot more push back from vested interests and communities than there was.

Polyethylene Terephthalate Microplastics Generated from Disposable Water Bottles Induce Interferon Signaling Pathways in Mouse Lung Epithelial Cells.

Microplastics (MPs) are present in ambient air in a respirable size fraction; however, their potential impact on human health via inhalation routes is not well documented. In the present study, methods for a lab-scale generation of MPs from regularly used and littered plastic articles were optimized. The toxicity of 11 different types of MPs, both commercially purchased and in-lab prepared MPs, was investigated in lung epithelial cells using cell viability, immune and inflammatory response, and genotoxicity endpoints. The underlying mechanisms were identified by microarray analysis. Although laborious, the laboratory-scale methods generated a sufficient quantity of well characterized MPs for toxicity testing. Of the 11 MPs tested, the small sized polyethylene terephthalate (PETE) MPs prepared from disposable water bottles induced the maximum toxicity. Specifically, the smaller size PETE MPs induced a robust activation of the interferon signaling pathway, implying that PETE MPs are perceived by cells by similar mechanisms as those employed to recognize pathogens. The PETE MPs of heterogenous size and shapes induced cell injury, triggering cell death, inflammatory cascade, and DNA damage, hallmark in vitro events indicative of potential in vivo tissue injury. The study establishes toxicity of specific types of plastic materials in micron and nano size.

Loss to Follow Up Among Glaucoma Patients: An IRIS® Registry (Intelligent Research in Sight) Retrospective Cohort Analysis.

PURPOSE: To identify prevalence of and risk factors for loss to follow up (LTFU) among a national cohort of patients with primary open-angle glaucoma (POAG). METHODS: This retrospective cohort study analyzed data from the IRIS® Registry (Intelligent Research in Sight) database from 2014 through 2019 to assess LTFU among adult patients with POAG. POAG patients with at least one clinical encounter in 2014 were included. LTFU was defined as exceeding one year without a clinical encounter during the study period. RESULTS: Among 553,663 glaucoma patients, 277,019 (50%) became LTFU, of whom 184,548 (67%) never returned to care and 92,471 (33%) re-established follow-up after a lapse. Risk of LTFU was greatest among those younger than 60 years (RR = 1.38; 95% CI: 1.36-1.39) or older than 80 years (RR = 1.39; 95% CI: 1.38-1.40) compared to those in their 60s. Compared to White race, risk for LTFU was highest among Native Hawaiian/Pacific Islander (RR = 1.24; 95% CI: 1.17-1.31), Hispanic ethnicity (RR = 1.19; 95% CI: 1.18-1.20), and Black race (RR = 1.10; 95% CI: 1.09-1.11). Medicare insurance was associated with lower risk of LTFU (RR = 0.79; 95% CI: 0.78-0.79), whereas unknown/missing/no insurance was associated with greater risk (RR = 1.33; 95% CI: 1.32-1.34), compared to private insurance. Compared to mild-stage POAG, risk of LTFU was higher for moderate-stage (RR = 1.10; 95% CI: 1.08-1.13) and severe-stage disease (RR = 1.35; 95% CI: 1.32-1.38). CONCLUSION: We found a 50% prevalence of LTFU among POAG patients in the IRIS Registry over a 6-year study period, with greater risk among minority groups and those with more advanced disease.

TGFß1, SMAD and ß-catenin in pulmonary arteries of smokers, patients with small airway disease and COPD: potential drivers of EndMT.

We previously reported pulmonary arterial remodelling and active endothelial-to-mesenchymal transition (EndMT) in smokers and patients with early chronic obstructive pulmonary disease (COPD). In the present study, we aimed to evaluate the role of different drivers of EndMT. Immunohistochemical staining for EndMT drivers, TGF-ß1, pSMAD-2/3, SMAD-7, and ß-catenin, was performed on lung resections from 46 subjects. Twelve were non-smoker-controls (NC), six normal lung function smokers (NLFS), nine patients with small-airway diseases (SAD), nine mild-moderate COPD-current smokers (COPD-CS) and ten COPD-ex-smokers (COPD-ES). Histopathological measurements were done using Image ProPlus softwarev7.0. We observed lower levels of total TGF-ß1 (P<0.05) in all smoking groups than in the non-smoking control (NC). Across arterial sizes, smoking groups exhibited significantly higher (P<0.05) total and individual layer pSMAD-2/3 and SMAD-7 than in the NC group. The ratio of SAMD-7 to pSMAD-2/3 was higher in COPD patients compared with NC. Total ß-catenin expression was significantly higher in smoking groups across arterial sizes (P<0.05), except for COPD-ES and NLFS groups in small and medium arteries, respectively. Increased total ß-catenin was positively correlated with total S100A4 in small and medium arteries (r = 0.35, 0.50; P=0.02, 0.01, respectively), with Vimentin in medium arteries (r = 0.42, P=0.07), and with arterial thickness of medium and large arteries (r = 0.34, 0.41, P=0.02, 0.01, respectively). This is the first study uncovering active endothelial SMAD pathway independent of TGF-ß1 in smokers, SAD, and COPD patients. Increased expression of ß-catenin indicates its potential interaction with SMAD pathway, warranting further research to identify the deviation of this classical pathway.

High-throughput transcriptomics toxicity assessment of eleven data-poor bisphenol A alternatives.

Bisphenol A (BPA), a widely used chemical in the production of plastics and epoxy resins, has garnered significant attention due to its association with adverse health effects, particularly its endocrine-disrupting properties. Regulatory measures aimed at reducing human exposure to BPA have led to a proliferation of alternative chemicals used in various consumer and industrial products. While these alternatives serve to reduce BPA exposure, concerns have arisen regarding their safety and potential toxicity as regrettable substitutes. Previous efforts have demonstrated that in vitro high-throughput transcriptomics (HTTr) studies can be used to assess the endocrine-disrupting potential of BPA alternatives, and this strategy produces transcriptomic points-of-departure (tPODs) that are protective of human health when compared to the PODs from traditional rodent studies. In this study, we used in vitro HTTr to assess the potential for toxicity of eleven data-poor legacy chemicals sharing structural similarities to BPA. Human breast cancer MCF-7 cells were exposed to BPA and 11 alternatives at concentrations ranging from 0.1 to 25 µM to assess toxicity. Analysis of global transcriptomic changes and a previously characterized estrogen receptor alpha (ERα) transcriptomic biomarker signature revealed that 9 of 11 chemicals altered gene expression relative to controls. One of the chemicals (2,4'-Bisphenol A) activated the ERα biomarker at the same concentration as BPA (i.e., 4,4'-BPA) but was deemed to be more potent as it induced global transcriptomic changes at lower concentrations. These results address data gaps in support of ongoing screening assessments to identify BPA alternatives with hazard potential and help to identify potential candidates that may serve as safer alternatives.

Early childhood development strategy for the world's children with disabilities.

Early childhood is foundational for optimal and inclusive lifelong learning, health and well-being. Young children with disabilities face substantial risks of sub-optimal early childhood development (ECD), requiring targeted support to ensure equitable access to lifelong learning opportunities, especially in low- and middle-income countries. Although the Sustainable Development Goals, 2015-2030 (SDGs) emphasise inclusive education for children under 5 years with disabilities, there is no global strategy for achieving this goal since the launch of the SDGs. This paper explores a global ECD framework for children with disabilities based on a review of national ECD programmes from different world regions and relevant global ECD reports published since 2015. Available evidence suggests that any ECD strategy for young children with disabilities should consists of a twin-track approach, strong legislative support, guidelines for early intervention, family involvement, designated coordinating agencies, performance indicators, workforce recruitment and training, as well as explicit funding mechanisms and monitoring systems. This approach reinforces parental rights and liberty to choose appropriate support pathway for their children. We conclude that without a global disability-focussed ECD strategy that incorporates these key features under a dedicated global leadership, the SDGs vision and commitment for the world's children with disabilities are unlikely to be realised.

Conflict and catastrophe-related severe burn injuries: A challenging setting for antimicrobial decision-making.

Severe burns are a major component of conflict-related injuries and can result in high rates of mortality. Conflict and disaster-related severe burn injuries present unique challenges in logistic, diagnostic and treatment options, while wider conflict is associated with driving local antimicrobial resistance. We present a targeted review of available literature over the last 10 years on the use of systemic antimicrobial antibiotics in this setting and, given limited available data, provide an expert consensus discussion. While international guidelines do not tend to recommend routine use of prophylactic systemic antibiotics, the challenges of conflict settings and potential for polytrauma are likely to have ongoing impacts on antimicrobial decision-making and use. Efforts must be made to develop a suitable evidence base in this unique setting. In the interim, a pragmatic approach to balancing selective pressures of antimicrobial use with realistic access is possible.

Conceptualisation of health among young people: a protocol for systematic review and thematic synthesis of qualitative studies.

BACKGROUND: Self-reported health is a widely used health indicator in surveys and questionnaires. The measure gained attention when research identified its association with mortality in the 1970s and 1980s. The measure is also associated with morbidity and other health outcomes such as the utilisation of health services. Self-reported health is a particularly useful measure for young people because this age group is generally clinically healthy. However, it is known that many chronic conditions have long latency periods that are initiated early in life. Because of its predictive nature, self-reported health can be used to estimate young people's current and future health. Despite its widespread use, however, self-reported health remains a poorly understood concept. This paper presents the protocol for a systematic review that will identify and synthesise qualitative studies that investigate the factors that are considered by young people when they assess their health, and when they talk about health overall. METHODS: The population of the review is young people aged 10-24 years, with or without health conditions. We will search the databases of MEDLINE (Ovid®), PsycINFO (APA PsycNet), ProQuest Sociology Collection, and Web of Science Core Collection™. We will also utilise techniques of reference checking and forward citation searching, as this strategy has been shown to result in a higher number of high-quality studies in social science systematic reviews. Google Scholar and Google Search were used during preliminary searches; Google Scholar will be utilised for forward citation searching. We will include studies written in English, German, or Finnish; there will be no lower date limit. One reviewer will screen all citations. A second reviewer will independently screen a sample of 20% of the abstracts. Data will be extracted by one researcher, two other researchers will independently review all data extracted, and quality appraisal will be completed by the first reviewer. We will utilise the Quality Framework for the appraisal of included articles and thematic synthesis of qualitative studies. DISCUSSION: The results of this systematic review will improve the understanding of the factors that are considered during the self-assessments of health; this will improve the interpretation of the results of quantitative research. Also, an improved understanding of the conceptualisation of health will inform the development of health policies and interventions that support young people's health. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022367519.

Factors Associated with Nonreturn after Loss to Follow-Up from Glaucoma Care: An IRIS® Registry Retrospective Analysis.

PURPOSE: Loss to follow-up (LTFU) in primary open-angle glaucoma (POAG) can lead to undertreatment, disease progression, and irreversible vision loss. Patients who become LTFU either eventually re-establish glaucoma care after a lapse or never return to the clinic. The purpose of this study is to examine a large population of patients with POAG who became LTFU to determine the proportion that return to care and to identify demographic and clinical factors associated with nonreturn after LTFU. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: Patients with a diagnosis of POAG with a clinical encounter in 2014 in the IRIS® Registry (Intelligent Research in Sight). METHODS: We examined follow-up patterns for 553 663 patients with POAG who had an encounter in the IRIS Registry in 2014 by following their documented clinic visits through 2019. LTFU was defined as exceeding 1 calendar year without an encounter. Within the LTFU group, patients were classified as returning after a lapse in care (return after LTFU) or not (nonreturn after LTFU). MAIN OUTCOME MEASURES: Proportion of patients with nonreturn after LTFU and baseline demographic and clinical characteristics associated with nonreturn among LTFU patients with POAG. RESULTS: Among 553 663 patients with POAG, 277 019 (50%) had at least 1 episode of LTFU over the 6-year study period. Within the LTFU group, 33% (92 471) returned to care and 67% (184 548) did not return to care. Compared to those who returned to care, LTFU patients with nonreturn were more likely to be older (age >80 years; relative risk [RR] = 1.48; 95% confidence interval [CI]: 1.47-1.50), to have unknown/missing insurance (RR = 1.31; 95% CI: 1.30-1.33), and to have severe-stage POAG (RR = 1.13; 95% CI: 1.11-1.15). Greater POAG severity and visual impairment were associated with nonreturn with a dose-dependent relationship in the adjusted model that accounted for demographic characteristics. Among those with return after LTFU, almost all returned within 2 years of last appointment (82 201; 89%) rather than 2 or more years later. CONCLUSIONS: Half of patients with POAG in the IRIS Registry had at least 1 period of LTFU, and two thirds of LTFU patients with POAG did not return to care. More effort is warranted to re-engage the vulnerable patients with POAG who become LTFU. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2.

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. Study Design: Retrospective. Setting: Clinical data in the National COVID Cohort Collaborative database (N3C). Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48-3.78; P < 0.001), delta (OR, 3.03; CI, 2.94-3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90-3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35-9.27; P < 0.001). Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings.

The N-terminal domain of Type IV-A1 CRISPR-associated DinG is vulnerable to proteolysis.

CasDinG is an ATP-dependent 5'-3' DNA helicase essential for bacterial Type IV-A1 CRISPR associated immunity. CasDinG contains an essential N-terminal domain predicted to bind DNA. To better understand the role of the N-terminal domain, we attempted to co-crystallize CasDinG with DNA substrates. We successfully crystallized CasDinG in a tightly packed, crystal conformation with previously unobserved unit cell dimensions. However, the structure lacked electron density for a bound DNA substrate and the CasDinG N-terminal domain. Additionally, the tight crystal packing disallowed space for the N-terminal domain, indicating that the N-terminal domain was proteolyzed before crystallization. Follow up experiments revealed that the N-terminal domain of CasDinG is proteolyzed after a few days at room temperature, but is protected from proteolysis at 4°C. These data provide a distinct x-ray crystal structure of CasDinG and indicate the essential N-terminal domain of CasDinG is prone to proteolysis.

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project.

BACKGROUND: Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. METHODS: We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades. RESULTS: Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH. CONCLUSIONS: Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.

Gut microbiota-mediated polyphenol metabolism is restrained by parasitic whipworm infection and associated with altered immune function in mice.

Polyphenols are phytochemicals commonly found in plant-based diets which have demonstrated immunomodulatory and anti-inflammatory properties. However, the interplay between polyphenols and pathogens at mucosal barrier surfaces has not yet been elucidated in detail. Here, we show that proanthocyanidin (PAC) polyphenols interact with gut parasites to influence immune function and gut microbial-derived metabolites in mice. PAC intake inhibited mastocytosis during infection with the small intestinal roundworm Heligmosomoides polygyrus, and altered the host tissue transcriptome at the site of infection with the large intestinal whipworm Trichuris muris, with a notable enhancement of type-1 inflammatory and interferon-driven gene pathways. In the absence of infection, PAC intake promoted the expansion of Turicibacter within the gut microbiota, increased fecal short chain fatty acids, and enriched phenolic metabolites such as phenyl-γ-valerolactones in the cecum. However, these putatively beneficial effects were reduced in PAC-fed mice infected with T. muris, suggesting concomitant parasite infection can attenuate gut microbial-mediated PAC catabolism. Collectively, our results suggest an inter-relationship between a phytonutrient and infection, whereby PAC may augment parasite-induced inflammation (most prominently with the cecum dwelling T. muris), and infection may abrogate the beneficial effects of health-promoting phytochemicals.

Impact of temperature on physical and cognitive performance in elite female football players during intermittent exercise.

There is limited research on female football players, especially related to their physical and cognitive performance under different climactic conditions. We analyzed the impact of a hot environmental temperature on physical performance and anticipation in elite female football players during a fatigue-inducing intermittent protocol. Elite female players (n = 21) performed the countermovement jump (CMJ) and responded to filmed sequences of offensive play under two distinct environmental temperatures (i.e., mild environment temperature- 20°C and 30% rh versus hot environment temperature- 38°C and 80% rh), interspersed by 1-week interval. Linear mixed models were used. CMJ performance declined following the intermittent protocol on both temperature conditions (p < 0.05). Moreover, there were significant main effects for protocol on CMJ speed (m/s) (p = 0.001; ηp 2 = 0.12), CMJ power (p = 0.002; ηp 2 = 0.11), and CMJ Heightmax (p = 0.002; ηp 2 = 0.12). After performing the intermittent protocol, exposure to a hot temperature caused a greater decline in anticipation accuracy (mild temperature = 64.41% vs. hot temperature = 53.44%; p < 0.001). Our study shows impaired performance in elite female football players following an intermittent protocol under hot compared with mild environmental conditions. We report decreased performance in both CMJ and anticipation performance under hotter conditions. The results reveal that exposure to hot temperatures had a negative effect on the accuracy of their anticipatory behaviors. We consider the implication of the work for research and training interventions.

Visualization strategies to aid interpretation of high-dimensional genotoxicity data.

This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seven biomarker responses resulting from the exposure of TK6 cells to each of 126 diverse chemicals over a range of concentrations. Obviously, challenges associated with visualizing seven biomarker responses were further complicated whenever there was a desire to represent the entire 126 chemical data set as opposed to results from a single chemical. Scatter plots, spider plots, parallel coordinate plots, hierarchical clustering, principal component analysis, toxicological prioritization index, multidimensional scaling, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are each considered in turn. Our report provides a comparative analysis of these techniques. In an era where multiplexed assays and machine learning algorithms are becoming the norm, stakeholders should find some of these visualization strategies useful for efficiently and effectively interpreting their high-dimensional data.