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The Venus flytrap, Dionaea muscipula, is perhaps the world's best-known botanical carnivore. The act of prey capture and digestion along with its rapidly closing, charismatic traps make this species a compelling model for studying the evolution and fundamental biology of carnivorous plants. There is a growing body of research on the genome, transcriptome, and digestome of Dionaea muscipula, but surprisingly limited information on changes in trap transcript abundance over time since feeding. Here we present the results of a comparative transcriptomics project exploring the transcriptomic changes across seven timepoints in a 72-hour time series of prey digestion and three timepoints directly comparing triggered traps with and without prey items. We document a dynamic response to prey capture including changes in abundance of transcripts with Gene Ontology (GO) annotations related to digestion and nutrient uptake. Comparisons of traps with and without prey documented 174 significantly differentially expressed genes at 1 hour after triggering and 151 genes with significantly different abundances at 24 hours. Approximately 50% of annotated protein-coding genes in Venus flytrap genome exhibit change (10041 of 21135) in transcript abundance following prey capture. Whereas peak abundance for most of these genes was observed within 3 hours, an expression cluster of 3009 genes exhibited continuously increasing abundance over the 72-hour sampling period, and transcript for these genes with GO annotation terms including both catabolism and nutrient transport may continue to accumulate beyond 72 hours. [ABSTRACT FROM AUTHOR]

The practical application of new single molecule protein sequencing (SMPS) technologies requires accurate estimates of their associated sequencing error rates. Here, we describe the development and application of two distinct parameter estimation methods for analyzing SMPS reads produced by fluorosequencing. A Hidden Markov Model (HMM) based approach, extends whatprot, where we previously used HMMs for SMPS peptide-read matching. This extension offers a principled approach for estimating key parameters for fluorosequencing experiments, including missed amino acid cleavages, dye loss, and peptide detachment. Specifically, we adapted the Baum-Welch algorithm, a standard technique to estimate transition probabilities for an HMM using expectation maximization, but modified here to estimate a small number of parameter values directly rather than estimating every transition probability independently. We demonstrate a high degree of accuracy on simulated data, but on experimental datasets, we observed that the model needed to be augmented with an additional error type, N-terminal blocking. This, in combination with data pre-processing, results in reasonable parameterizations of experimental datasets that agree with controlled experimental perturbations. A second independent implementation using a hybrid of DIRECT and Powell's method to reduce the root mean squared error (RMSE) between simulations and the real dataset was also developed. We compare these methods on both simulated and real data, finding that our Baum-Welch based approach outperforms DIRECT and Powell's method by most, but not all, criteria. Although some discrepancies between the results exist, we also find that both approaches provide similar error rate estimates from experimental single molecule fluorosequencing datasets. Author summary: Diverse new technologies are being developed for single-molecule protein sequencing, capable of identifying and quantifying mixtures of proteins at the level of individual molecules. There are many biochemical challenges intrinsic to high-throughput studies of proteins at such high sensitivity arising from their heterogeneous chemistries, sizes, and abundances. Beyond these challenges, the technologies themselves involve complex multi-step analytical processes. Thus, in developing and optimizing these technologies, it is important to consider the accuracy of each step and to have reliable approaches for estimating these accuracies. We focus on one particular single-molecule sequencing technology known as flourosequencing. We report and validate two methods for simultaneously determining the error-rates of each of the various steps of the fluorosequencing process. These new error estimation techniques will help researchers to better interpret the effects of changes to the chemistry and sample preparation used in fluorosequencing so that these steps can be improved. Further, more accurate determination of error rates will aid in the creation of better tools for the interpretation of this data. [ABSTRACT FROM AUTHOR]

Fungi are among key actors in the biogeochemical processes occurring in mangrove ecosystems. In this study, we investigated the changes of fungal communities in selected mangrove species by exploring differences in diversity, structure and the degree of ecological rearrangement occurring within the rhizospheres of four mangrove species (Sonneratia alba, Rhizophora mucronata, Ceriops tagal and Avicennia marina) at Gazi Bay and Mida Creek in Kenya. Alpha diversity investigation revealed that there were no significant differences in species diversity between the same mangrove species in the different sites. Rather, significant differences were observed in fungal richness for some of the mangrove species. Chemical parameters of the mangrove sediment significantly correlated with fungal alpha diversity and inversely with richness. The fungal community structure was significantly differentiated by mangrove species, geographical location and chemical parameters. Taxonomic analysis revealed that 96% of the amplicon sequence variants belonged to the Phylum Ascomycota, followed by Basidiomycota (3%). Predictive FUNGuild and co-occurrence network analysis revealed that the fungal communities in Gazi Bay were metabolically more diverse compared to those of Mida Creek. Overall, our results demonstrate that anthropogenic activities influenced fungal richness, community assembly and their potential ecological functions in the mangrove ecosystems investigated. [ABSTRACT FROM AUTHOR]

Cigarette smoke-induced protein aggregation damages the lung cells in emphysema and COPD; however, lung cancer cells continue to thrive, evolving to persist in the toxic environment. Here, we showed that upon the cigarette smoke condensate exposure, A549 lung cancer cells exhibit better survival and reduced level of protein aggregation when compared to non-cancerous Beas-2B and H-6053 cells. Our data suggests that upregulation of efflux pumps in cancer cells assists in reducing smoke toxicity. Specifically, we demonstrated that inhibition of the ABCG2 transporter in A549 by febuxostat or its downregulation by shRNA-mediated RNA interference resulted in a significant increase in protein aggregation due to smoke exposure. [ABSTRACT FROM AUTHOR]

Archaeological faunal remains provide key insights into human societies in the past, alongside information on previous resource utilisation and exploitation of wildlife populations. The great whales (Mysticete and sperm whales) were hunted unsustainably throughout the 16th - 20th centuries (herein defined as the modern period) leading to large population declines and variable recovery patterns among species. Humans have utilised whales as a resource through carcass scavenging for millennia; however, increasing local and regional ethnographic and archaeological evidence suggests that, prior to the modern period, hunting of the great whales was more common than previously thought; impacts of earlier hunting pressures on the population ecology of many whale species remains relatively unknown. Hunting guided by traditional ecological knowledge may have been sustainable and likely originated in societies that also incorporated opportunistic use of stranded individuals. The collation of georeferenced zooarchaeological data of the great whales between the 1st - 20th centuries CE worldwide will provide insight into the timescale and distribution of resource utilisation of the great whales and how this varied within and between societies, and may have changed over time. By comparing regions of known resource utilisation and breeding and feeding grounds of current-day whale populations, this information will subsequently be used to infer regions where whale populations were possibly lost or extirpated prior to detailed historical records. This systematic review protocol also provides a template for archaeologists, ecologists, and historians interested in using faunal remains to infer historical ecology and resource use of wild animal populations. The transparency of our data collection approach provides opportunities for reproducibility and comparability with future datasets. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study was to identify factors associated with compassion fatigue (CF) and compassion satisfaction (CS) among rural health care workers (HCWs) during the COVID-19 pandemic. The secondary purpose was to assess utilization of wellness resources and preferences for new resources. Methods: A survey was distributed (October-December 2020) and completed by faculty, clinicians and staff (n = 406) at a rural university. Measures included a modified version of the Professional Quality of Life Scale (PROQOL-21), the Patient Health Questionnaire-4 and the Brief Resilience Coping Scale. Respondents reported their use of wellness resources and their preferences for new resources. Results: The mean CF score was 21.1, the mean CS score was 26.8 and 42.0% screened positive for depression or anxiety. Few of the existing wellness resources were utilized and respondents' preferences for new wellness resources included time off (70.7%), onsite food trucks (43.0%) and support animals (36.5%). Younger age, depression and anxiety were associated with higher CF. Older age, better mental health and resilience were associated with higher CS. Conclusions: Rural HCWs have high CF, yet few utilize wellness resources. Rural health care organizations may foster wellness by providing time off for self-care, expanding mental health services and building resilience. [ABSTRACT FROM AUTHOR]

Objective: To investigate public willingness to share sensitive health information for research, health policy and clinical practice. Methods: A total of 1,003 Australian respondents answered an online, attribute-driven, survey in which participants were asked to accept or reject hypothetical choice sets based on a willingness to share their health data for research and frontline-medical support as part of an integrated health system. The survey consisted of 5 attributes: Stakeholder access for analysis (Analysing group); Type of information collected; Purpose of data collection; Information governance; and Anticipated benefit; the results of which were analysed using logistic regression. Results: When asked about their preference for sharing their health data, respondents had no preference between data collection for the purposes of clinical practice, health policy or research, with a slight preference for having government organisations manage, govern and curate the integrated datasets from which the analysis was being conducted. The least preferred option was for personal health records to be integrated with insurance records or for their data collected by privately owned corporate organisations. Individuals preferred their data to be analysed by a public healthcare provider or government staff and expressed a dislike for any private company involvement. Conclusions: The findings from this study suggest that Australian consumers prefer to share their health data when there is government oversight, and have concerns about sharing their anonymised health data for clinical practice, health policy or research purposes unless clarity is provided pertaining to its intended purpose, limitations of use and restrictions to access. Similar findings have been observed in the limited set of existing international studies utilising a stated preference approach. Evident from this study, and supported by national and international research, is that the establishment and preservation of a social license for data linkage in health research will require routine public engagement as a result of continuously evolving technological advancements and fluctuating risk tolerance. Without more work to understand and address stakeholder concerns, consumers risk being reluctant to participate in data-sharing and linkage programmes. [ABSTRACT FROM AUTHOR]

Antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target multiple epitopes on different domains of the spike protein, and other SARS-CoV-2 proteins. We developed a SARS-CoV-2 multi-antigen protein microarray with the nucleocapsid, spike and its domains (S1, S2), and variants with single (D614G, E484K, N501Y) or double substitutions (N501Y/Deletion69/70), allowing a more detailed high-throughput analysis of the antibody repertoire following infection. The assay was demonstrated to be reliable and comparable to ELISA. We analyzed antibodies from 18 COVID-19 patients and 12 recovered convalescent donors. The S IgG level was higher than N IgG in most of the COVID-19 patients, and the receptor-binding domain of S1 showed high reactivity, but no antibodies were detected against the heptad repeat domain 2 of S2. Furthermore, antibodies were detected against S variants with single and double substitutions in COVID-19 patients who were infected with SARS-CoV-2 early in the pandemic. Here we demonstrated that the SARS-CoV-2 multi-antigen protein microarray is a powerful tool for detailed characterization of antibody responses, with potential utility in understanding the disease progress and assessing current vaccines and therapies against evolving SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Background: Pregabalin is a drug used to treat neuropathic pain, and its use has increased substantially since 2007. Early trials found a strong treatment effect on pain for post-herpetic neuralgia and diabetic neuropathy. However more recent studies have failed to replicate these results. Methods: This meta-epidemiological study aimed to assess change in the reported effectiveness of pregabalin in neuropathic pain trials over time, and if a change is present, determine any associated factors. Data sources: We performed electronic searches for published trials in Medline, Embase and Cochrane Central Register of Controlled Trials databases; and unpublished trials on ClinicalTrials.gov, the EU Clinical Trials Register, and the Australia New Zealand Clinical Trials Registry with no restrictions. Study selection: We included randomized, placebo-controlled trials of pregabalin for treatment of neuropathic pain in adults. Data extraction and synthesis: Two authors independently extracted study data: sample size and mean baseline, end-point and change in pain scores with measures of variance, trial end year, publication year, clinical indication, funding source, country of study, treatment duration, treatment dose, mean age and percentage male. Primary outcome measure: We defined treatment effect as the mean difference in pain scores between pregabalin and placebo groups at trial end-point and assessed for change over time using a random-effects meta-regression, adjusted for sample size, indication, treatment duration (weeks) and treatment dose. Results: We included 38 randomized published trials (9038 participants) and found that between 2003 and 2020, the reported treatment effect of pregabalin decreased by 0.4 points (95% CI: 0.3 to 0.6; p<0.001) on an 11-point pain scale per 5-year interval, from 1.3 points (95% CI: 1.0 to 1.5) in trials conducted in 2001–2005, to 0.3 (95% CI: -0.1 to 0.7) in trials conducted in 2016–2020. The reported treatment effect was lower than the minimal clinically important difference (MCID) of 1.7 points across all time periods, doses and most indications and was not found to be associated with study characteristics. Conclusions: The reported treatment effect or analgesic efficacy of pregabalin from clinical trials has diminished over time. Clinical recommendations may need to be re-evaluated to account for recent evidence and to consider whether pregabalin therapy is indicated. [ABSTRACT FROM AUTHOR]

Introduction: Currently there is no consistent and widely accepted approach to the diagnosis of vocal cord dysfunction/inducible laryngeal obstruction (VCD/ILO). Harmonised diagnostic methods are vital to enable optimal diagnosis, advance management and enable research. We aim to obtain consensus on how expert clinicians recognise and diagnose VCD/ILO. Methods and analysis: Two-round modified Delphi, with workshop validation. Ethics and dissemination: Institutional Board Review was obtained from the Monash Health Human Research Ethics Committee. The dissemination plan is for presentation and publication. Registration details: Registered at Australia and New Zealand Clinical Trials Registry ACTRN12621001520820p. [ABSTRACT FROM AUTHOR]

Tissue factor (TF) is an evolutionarily conserved protein necessary for initiation of hemostasis. Zebrafish have two copies of the tissue factor gene (f3a and f3b) as the result of an ancestral teleost fish duplication event (so called ohnologs). In vivo physiologic studies of TF function have been difficult given early lethality of TF knockout in the mouse. We used genome editing to produce knockouts of both f3a and f3b in zebrafish. Since ohnologs arose through sub- or neofunctionalization, they can unmask unknown functions of non-teleost genes and could reveal whether mammalian TF has developmental functions distinct from coagulation. Here we show that a single copy of either f3a or f3b is necessary and sufficient for normal lifespan. Complete loss of TF results in lethal hemorrhage by 2–4 months despite normal embryonic and vascular development. Larval vascular endothelial injury reveals predominant roles for TFa in venous circulation and TFb in arterial circulation. Finally, we demonstrate that loss of TF predisposes to a stress-induced cardiac tamponade independent of its role in fibrin formation. Overall, our data suggest partial subfunctionalization of TFa and TFb. This multigenic zebrafish model has the potential to facilitate study of the role of TF in different vascular beds. Author summary: Tissue factor (TF) is a critical component in the initiation of blood coagulation. It is exposed upon blood vessel injury, which leads to blood clot formation and cessation of hemorrhage. TF is functionally conserved and likely required for survival across all vertebrate species. Due to an ancestral genomic duplication event in the teleost class of fish, zebrafish have two copies of tissue factor (referred to as ohnologs) on separate chromosomes. We exploited this aspect of the zebrafish model to study real time developmental phenotypes previously suggested in mouse studies, with the surprising finding of that the f3 ohnologs have evolved separate functions. We saw no evidence for TF in blood vessel formation, however, we did see an obvious role in protecting the integrity of the vascular space around the heart. We found that clotting was completely blocked in the total absence of TF, but loss of each individual ohnolog led to differential deficiencies in the arterial and venous circulations. This type of evolution is known as "subfunctionalization" and presents an opportunity to further understand differences between blood clot formation based on vascular location. [ABSTRACT FROM AUTHOR]

Background and objective: Lyme disease (LD) is the fifth most commonly reported notifiable infectious disease in the United States (US) with approximately 35,000 cases reported in 2019 via public health surveillance. However, healthcare claims-based studies estimate that the number of LD cases is >10 times larger than reported through surveillance. To assess the burden of LD using healthcare claims data and the effectiveness of interventions for LD prevention and treatment, it is important to use validated well-performing LD case-finding algorithms ("LD algorithms"). We conducted a systematic literature review to identify LD algorithms used with US healthcare claims data and their validation status. Methods: We searched PubMed and Embase for articles published in English since January 1, 2000 (search date: February 20, 2021), using the following search terms: (1) "Lyme disease"; and (2) "claim*" or "administrative* data"; and (3) "United States" or "the US*". We then reviewed the titles, abstracts, full texts, and bibliographies of the articles to select eligible articles, i.e., those describing LD algorithms used with US healthcare claims data. Results: We identified 15 eligible articles. Of these, seven studies used LD algorithms with LD diagnosis codes only, four studies used LD diagnosis codes and antibiotic dispensing records, and the remaining four studies used serologic test order codes in combination with LD diagnosis codes and antibiotics records. Only one of the studies that provided data on algorithm performance: sensitivity 50% and positive predictive value 5%, and this was based on Lyme disease diagnosis code only. Conclusions: US claims-based LD case-finding algorithms have used diverse strategies. Only one algorithm was validated, and its performance was poor. Further studies are warranted to assess performance for different algorithm designs and inform efforts to better assess the true burden of LD. [ABSTRACT FROM AUTHOR]

Competitive fitness assays in liquid culture have been a mainstay for characterizing experimental evolution of microbial populations. Growth of microbial strains has also been extensively characterized by colony size and could serve as a useful alternative if translated to per generation measurements of relative fitness. To examine fitness based on colony size, we established a relationship between cell number and colony size for strains of Saccharomyces cerevisiae robotically pinned onto solid agar plates in a high-density format. This was used to measure growth rates and estimate relative fitness differences between evolved strains and their ancestors. After controlling for edge effects through both normalization and agar-trimming, we found that colony size is a sensitive measure of fitness, capable of detecting 1% differences. While fitnesses determined from liquid and solid mediums were not equivalent, our results demonstrate that colony size provides a sensitive means of measuring fitness that is particularly well suited to measurements across many environments. [ABSTRACT FROM AUTHOR]

Introduction: Although several non-pharmacological interventions have been tested in the management of Fibromyalgia (FM), there is little consensus regarding the best options for the treatment of this health condition. The purpose of this network meta-analysis (NMA) is to investigate the comparative efficacy and acceptability of non-pharmacological interventions for FM, in order to assist clinical decision making through a ranking of interventions in relation to the most important clinical outcomes in these patients. Methods and analysis: We will perform a systematic search to identify randomised controlled trials of non-pharmacological interventions endorsed in guidelines and systematic reviews. Information sources searched will include major bibliographic databases without language or date restrictions (MEDLINE, Cochrane Library, EMBASE, AMED, PsycINFO and PEDro). Our primary outcomes will be pain intensity, patient-reported quality of life (QoL), and acceptability of treatment will be our secondary outcome. Risk of bias of the included trials will be assessed using the Cochrane risk of bias tool (RoB2). For each pairwise comparison between the different interventions, we will present mean differences (MDs) for pain intensity and QoL outcomes and Relative Risks (RRs) for acceptability, both with respective 95% confidence intervals (CIs). Initially, standard pairwise meta-analyses will be performed using a DerSimonian-Laird random effects model for all comparisons with at least two trials and then we will perform a frequentist NMA using the methodology of multivariate meta-analysis assuming a common heterogeneity parameter, using the mvmeta command and network suite in STATA. In the NMA, two different types of control group, such as placebo/sham and no intervention/waiting list will be combined as one node called "Control". The competing interventions will be ranked using the P-score, which is the frequentist analogue of surface under the cumulative ranking curve (SUCRA) for the outcomes of interest at immediate- (intervention duration of up to 2 weeks), short- (over 2 weeks up to 12 weeks) and long-terms (over 12 weeks). The confidence in the results from NMA will be assessed using the Confidence in Network Meta‐analysis (CINeMA) framework. Ethics and dissemination: This work synthesises evidence from previously published studies and does not require ethics review or approval. A manuscript describing the findings will be submitted for publication in a peer-reviewed scientific journal. Registration: OSF (DOI: 10.17605/OSF.IO/7MS25) and registered in the PROSPERO database (CRD42020216374). [ABSTRACT FROM AUTHOR]

Objectives: To develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs. Methods: We used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records. Results: We reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel's C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic. Conclusions: Routinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS. [ABSTRACT FROM AUTHOR]

In the Adirondack Park region of northern New York, USA, white-tailed deer (Odocoileus virginianus) and moose (Alces alces) co-occur along a temperate-boreal forest ecotone. In this region, moose exist as a small and vulnerable low-density population and over-browsing by white-tailed deer is known to reduce regeneration, sustainability, and health of forests. Here, we assess the distribution and abundance of white-tailed deer at a broad spatial scale relevant for deer and moose management in northern New York. We used density surface modeling (DSM) under a conventional distance sampling framework, tied to a winter aerial survey, to create a spatially explicit estimate of white-tailed deer abundance and density across a vast, northern forest region. We estimated 16,352 white-tailed deer (95% CI 11,762–22,734) throughout the Adirondack Park with local density ranging between 0.00–5.73 deer/km2. Most of the Adirondack Park (91.2%) supported white-tailed deer densities of ≤2 individuals/km2. White-tailed deer density increased with increasing proximity to anthropogenic land cover such as timber cuts, roads, and agriculture and decreased in areas with increasing elevation and days with snow cover. We conclude that climate change will be more favorable for white-tailed deer than for moose because milder winters and increased growing seasons will likely have a pronounced influence on deer abundance and distribution across the Adirondack Park. Therefore, identifying specific environmental conditions facilitating the expansion of white-tailed deer into areas with low-density moose populations can assist managers in anticipating potential changes in ungulate distribution and abundance and to develop appropriate management actions to mitigate negative consequences such as disease spread and increased competition for limiting resources. [ABSTRACT FROM AUTHOR]

Objective: To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD). Design: Scoping review. Data sources: Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022. Study selection: All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression. Data extraction: Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications. Results: From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models. Conclusions: Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression. [ABSTRACT FROM AUTHOR]

Background: In 1995, the CDC recommended one-dose routine varicella immunization for children <12 years of age, expanding its recommendation to two doses in 2006. Today, with widespread varicella vaccination coverage, an estimated 3.5 million cases of varicella, 9,000 hospitalizations, and 100 deaths are prevented annually in the United States. Since varicella infections are now uncommon, health care providers (HCPs) may not recognize varicella infections and may prescribe inappropriate treatment. Methods: An online survey of HCPs was conducted to assess recognition and management of varicella infections. Responses to eight varicella vignettes describing patients with varying varicella symptoms were analyzed and descriptive analyses performed. Stratified analysis comparing responses of those licensed before and in/after 1996 was also performed. Results: 153 HCPs (50 nurse practitioners, 103 doctors) completed the survey. Mean age of respondents was 44 years. 62% were female, and 82% were licensed before 1996. Varicella infection was correctly diagnosed 79% of the time. HCPs correctly recognized uncomplicated varicella vignettes 85% of the time versus 61% of the time for complicated varicella vignettes. Antibiotics were recommended 17% of the time and antivirals 18% of the time, of which 25% and 69% (respectively) were not appropriate per guidelines. HCPs licensed before 1996 were better able to recognize varicella compared to those licensed later, but prescribed more antimicrobials medications to treat varicella. Conclusions: Although most HCPs recognized varicella infection, a sizable proportion could not recognize cases with complications, and some of the varicella cases were inappropriately treated with antibiotics and/or antivirals. Additional HCP training and high vaccination coverage are important strategies to avoid inaccurate diagnoses and minimize unnecessary exposure to antimicrobial/antiviral therapies. [ABSTRACT FROM AUTHOR]

Background: Our objective was to estimate the impact of universal varicella vaccination (UVV) on the use and costs of antibiotics and antivirals for the management of varicella among children in the United States (US). Methods: A decision tree model of varicella vaccination, infections and treatment decisions was developed. Results were extrapolated to the 2017 population of 73.5 million US children. Model parameters were populated from published sources. Treatment decisions were derived from a survey of health care professionals' recommendations. The base case modelled current vaccination coverage rates in the US with additional scenarios analyses conducted for 0%, 20%, and 80% coverage and did not account for herd immunity benefits. Results: Our model estimated that 551,434 varicella cases occurred annually among children ≤ 18 years in 2017. Antivirals or antibiotics were prescribed in 23.9% of cases, with unvaccinated children receiving the majority for base case. The annual cost for varicella antiviral and antibiotic treatment was approximately $14 million ($26 per case), with cases with no complications accounting for $12 million. Compared with the no vaccination scenario, the current vaccination rates resulted in savings of $181 million (94.7%) for antivirals and $78 million (95.0%) for antibiotics annually. Scenario analyses showed that higher vaccination coverage (from 0% to 80%) resulted in reduced annual expenditures for antivirals (from $191 million to $41 million), and antibiotics ($82 million to $17 million). Conclusions: UVV was associated with significant reductions in the use of antibiotics and antivirals and their associated costs in the US. Higher vaccination coverage was associated with lower use and costs of antibiotics and antivirals for varicella management. [ABSTRACT FROM AUTHOR]

Background: Schools are primary venues of influenza amplification with secondary spread to communities. We assessed K-12 student absenteeism monitoring as a means for early detection of influenza activity in the community. Materials and methods: Between September 2014 and March 2020, we conducted a prospective observational study of all-cause (a-TOT), illness-associated (a-I), and influenza-like illness–associated (a-ILI) absenteeism within the Oregon School District (OSD), Dane County, Wisconsin. Absenteeism was reported through the electronic student information system. Students were visited at home where pharyngeal specimens were collected for influenza RT-PCR testing. Surveillance of medically-attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining the OSD. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Findings: Influenza was detected in 723 of 2,378 visited students, and in 1,327 of 4,903 MAI patients. Over six influenza seasons, a-ILI was significantly correlated with MAI in the community (r = 0.57; 95% CI: 0.53–0.63) with a one-day lead time and a-I was significantly correlated with MAI in the community (r = 0.49; 0.44–0.54) with a 10-day lead time, while a-TOT performed poorly (r = 0.27; 0.21–0.33), following MAI by six days. Discussion: Surveillance using cause-specific absenteeism was feasible and performed well over a study period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can provide early warning of seasonal influenza in time for community mitigation efforts. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Schistosomiasis is a chronic, debilitating parasitic disease infecting more than 200 million people and is second only to malaria in terms of public health importance. Due to the [...]

Background: The Covid-19 pandemic in the United Kingdom has seen two waves; the first starting in March 2020 and the second in late October 2020. It is not known whether outcomes for those admitted with severe Covid were different in the first and second waves. Methods: The study population comprised all patients admitted to a 1,500-bed London Hospital Trust between March 2020 and March 2021, who tested positive for Covid-19 by PCR within 3-days of admissions. Primary outcome was death within 28-days of admission. Socio-demographics (age, sex, ethnicity), hypertension, diabetes, obesity, baseline physiological observations, CRP, neutrophil, chest x-ray abnormality, remdesivir and dexamethasone were incorporated as co-variates. Proportional subhazards models compared mortality risk between wave 1 and wave 2. Cox-proportional hazard model with propensity score adjustment were used to compare mortality in patients prescribed remdesivir and dexamethasone. Results: There were 3,949 COVID-19 admissions, 3,195 hospital discharges and 733 deaths. There were notable differences in age, ethnicity, comorbidities, and admission disease severity between wave 1 and wave 2. Twenty-eight-day mortality was higher during wave 1 (26.1% versus 13.1%). Mortality risk adjusted for co-variates was significantly lower in wave 2 compared to wave 1 [adjSHR 0.49 (0.37, 0.65) p<0.001]. Analysis of treatment impact did not show statistically different effects of remdesivir [HR 0.84 (95%CI 0.65, 1.08), p = 0.17] or dexamethasone [HR 0.97 (95%CI 0.70, 1.35) p = 0.87]. Conclusion: There has been substantial improvements in COVID-19 mortality in the second wave, even accounting for demographics, comorbidity, and disease severity. Neither dexamethasone nor remdesivir appeared to be key explanatory factors, although there may be unmeasured confounding present. [ABSTRACT FROM AUTHOR]

Chagas disease (CD), caused by the parasite Trypanosoma cruzi, is one of nineteen neglected tropical diseases. CD is a vector-borne disease transmitted by triatomines, but CD can also be transmitted through blood transfusions, organ transplants, T. cruzi-contaminated food and drinks, and congenital transmission. While endemic to the Americas, T. cruzi infects 7–8 million people worldwide and can induce severe cardiac symptoms including apical aneurysms, thromboembolisms and arrhythmias during the chronic stage of CD. However, these cardiac clinical manifestations and CD pathogenesis are not fully understood. Using spatial metabolomics (chemical cartography), we sought to understand the localized impact of chronic CD on the cardiac metabolome of mice infected with two divergent T. cruzi strains. Our data showed chemical differences in localized cardiac regions upon chronic T. cruzi infection, indicating that parasite infection changes the host metabolome at specific sites in chronic CD. These sites were distinct from the sites of highest parasite burden. In addition, we identified acylcarnitines and glycerophosphocholines as discriminatory chemical families within each heart region, comparing infected and uninfected samples. Overall, our study indicated global and positional metabolic differences common to infection with different T. cruzi strains and identified select infection-modulated pathways. These results provide further insight into CD pathogenesis and demonstrate the advantage of a systematic spatial perspective to understand infectious disease tropism. Author summary: Chagas disease (CD) is a tropical disease caused by the parasite Trypanosoma cruzi. CD originated in the Americas but is now found globally due to population movements. CD is transmitted through a triatomine vector, organ transplants, blood transfusions, T. cruzi-contaminated food and drinks, and congenitally. It occurs in two stages, an acute stage (usually asymptomatic) and a chronic stage. Twenty to thirty percent of chronic stage cases present severe cardiac symptoms such as heart failure, localized aneurysms and cardiomyopathy. Unfortunately, what causes severe cardiac symptoms in some individuals in chronic CD is not fully understood. Therefore, we used liquid chromatography-tandem mass spectrometry to analyze the heart tissue of chronically T. cruzi-infected and uninfected mice, to understand the impact of infection on the tissue metabolome. We identified discriminatory small molecules related to T. cruzi infection and determined that regions with the highest parasite burden are distinct from the regions with the largest changes in overall metabolite profile. These locations of high metabolic perturbation provide a molecular mechanism to explain why localized cardiac symptoms occur in CD, particularly at the heart apex. Overall, our work gives insight into chronic cardiac CD symptom development and shapes a framework for novel CD treatment. [ABSTRACT FROM AUTHOR]

Background Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana. Methods and Findings We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0) for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from 40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis. Conclusions Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends., Author(s): Raphael E. Arku 1, James E. Bennett 2,3, Marcia C. Castro 4, Kofi Agyeman-Duah 5, Samilia E. Mintah 5, James H. Ware 6, Philomena Nyarko 5, John D. Spengler [...]

Background Low back pain (LBP) is a major health problem. Globally it is responsible for the most years lived with disability. The most problematic type of LBP is chronic LBP (pain lasting longer than 3 mo); it has a poor prognosis and is costly, and interventions are only moderately effective. Targeting interventions according to risk profile is a promising approach to prevent the onset of chronic LBP. Developing accurate prognostic models is the first step. No validated prognostic models are available to accurately predict the onset of chronic LBP. The primary aim of this study was to develop and validate a prognostic model to estimate the risk of chronic LBP. Methods and Findings We used the PROGRESS framework to specify a priori methods, which we published in a study protocol. Data from 2,758 patients with acute LBP attending primary care in Australia between 5 November 2003 and 15 July 2005 (development sample, n = 1,230) and between 10 November 2009 and 5 February 2013 (external validation sample, n = 1,528) were used to develop and externally validate the model. The primary outcome was chronic LBP (ongoing pain at 3 mo). In all, 30% of the development sample and 19% of the external validation sample developed chronic LBP. In the external validation sample, the primary model (PICKUP) discriminated between those who did and did not develop chronic LBP with acceptable performance (area under the receiver operating characteristic curve 0.66 [95% CI 0.63 to 0.69]). Although model calibration was also acceptable in the external validation sample (intercept = -0.55, slope = 0.89), some miscalibration was observed for high-risk groups. The decision curve analysis estimated that, if decisions to recommend further intervention were based on risk scores, screening could lead to a net reduction of 40 unnecessary interventions for every 100 patients presenting to primary care compared to a 'treat all' approach. Limitations of the method include the model being restricted to using prognostic factors measured in existing studies and using stepwise methods to specify the model. Limitations of the model include modest discrimination performance. The model also requires recalibration for local settings. Conclusions Based on its performance in these cohorts, this five-item prognostic model for patients with acute LBP may be a useful tool for estimating risk of chronic LBP. Further validation is required to determine whether screening with this model leads to a net reduction in unnecessary interventions provided to low-risk patients., Author(s): Adrian C. Traeger 1,2,*, Nicholas Henschke 3, Markus Hübscher 1,2,*, Christopher M. Williams 4, Steven J. Kamper 5, Christopher G. Maher 5, G. Lorimer Moseley 2,6, James H. McAuley [...]

Platelet-rich plasma (PRP) is a widely used autologous treatment for tendon injuries in clinics. Platelets (PLTs) are a major source of high mobility group box1 (HMGB1) that is gaining attention as a chemoattractant that can recruit stem cells to the wound area to enhance healing of injured tissues; however, the contribution of PLT HMGB1 in wounded tendon healing remains unexplored. This study investigated the effect of PLT HMGB1 within PRP on tendon healing using PLT HMGB1 knockout (KO) and GFP mice. A window defect was created in the patellar tendons of both groups of mice, and wounds were treated with either saline, PRP isolated from PLT HMGB1-KO mice, or PRP isolated from GFP mice. Seven days post-treatment, animals were sacrificed and analyzed by gross inspection, histology, and immunostaining for characteristic signs of tendon healing and repair. Our results showed that in comparison to mice treated with PRP from PLT HMGB1-KO mice, wounds treated with PRP from GFP mice healed faster and exhibited a better organization in tendon structure. Mice treated with PRP from PLT HMGB1-KO mice produced tendon tissue with large premature wound areas and low cell densities. However, wounds of PLT HMGB1-KO mice showed better healing with PRP from HMGB1-KO mice compared to saline treatment. Moreover, wounds treated with PRP from GFP mice had increased extracellular HMGB1, decreased CD68, increased stem cell markers CD146 and CD73, and increased collagen III protein expression levels compared to those treated with PRP from PLT HMGB1-KO mice. Thus, PLT HMGB1 within PRP plays an important role in tendon wound healing by decreasing inflammation, increasing local HMGB1 levels, and recruiting stem cells to the wound area in the tendon. Our findings also suggest that the efficacy of PRP treatment for tendon injuries in clinics may depend on PLT HMGB1 within PRP preparations. [ABSTRACT FROM AUTHOR]

Spatial inhibition of return (IOR) refers to the phenomenon by which individuals are slower to respond to stimuli appearing at a previously cued location compared to un-cued locations. Here with a group of older adults (n = 56, 58–80 (67.9±5.2) year old, 31 females, 18.7±3.6 years of education), we provide evidence supporting the notion that spatial IOR is mildly impaired in individuals with mild cognitive impairment (MCI) or mild Alzheimer's disease (AD), and the impairment is detectable using a double cue paradigm. Furthermore, reduced spatial IOR in high-risk healthy older individuals is associated with reduced memory and other neurocognitive task performance, suggesting that the double cue spatial IOR paradigm may be useful in detecting MCI and early AD. [ABSTRACT FROM AUTHOR]

Governments issue "stay-at-home" orders to reduce the spread of contagious diseases, but the magnitude of such orders' effectiveness remains uncertain. In the United States these orders were not coordinated at the national level during the coronavirus disease 2019 (COVID-19) pandemic, which creates an opportunity to use spatial and temporal variation to measure the policies' effect. Here, we combine data on the timing of stay-at-home orders with daily confirmed COVID-19 cases and fatalities at the county level during the first seven weeks of the outbreak in the United States. We estimate the association between stay-at-home orders and alterations in COVID-19 cases and fatalities using a difference-in-differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. Compared to counties that did not implement stay-at-home orders, the results show that the orders are associated with a 30.2 percent (11.0 to 45.2) average reduction in weekly incident cases after one week, a 40.0 percent (23.4 to 53.0) reduction after two weeks, and a 48.6 percent (31.1 to 61.7) reduction after three weeks. Stay-at-home orders are also associated with a 59.8 percent (18.3 to 80.2) average reduction in weekly fatalities after three weeks. These results suggest that stay-at-home orders might have reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities that implemented stay-at-home orders. [ABSTRACT FROM AUTHOR]

This study combined a social network analysis and whole-genome sequencing (WGS) to test for general patterns of contagious spread of a mycobacterial infection for which pathways of disease acquisition are not well understood. Our population included 275 cases diagnosed with avian mycobacteriosis that were nested in a source population of 16,430 birds at San Diego Zoo Wildlife Alliance facilities from 1992 through mid-2014. Mycobacteria species were determined using conventional methods and whole genome sequencing (WGS). Mycobacterium avium avium (MAA) and Mycobacterium genavense were the most common species of mycobacteria identified and were present in different proportions across bird taxa. A social network for the birds was constructed from the source population to identify directly and indirectly connected cases during time periods relevant to disease transmission. Associations between network connectivity and genetic similarity of mycobacteria (as determined by clusters of genotypes separated by few single nucleotide polymorphisms, or SNPs) were then evaluated in observed and randomly generated network permutations. Findings showed that some genotypes clustered along pathways of bird connectivity, while others were dispersed throughout the network. The proportion of directly connected birds having a similar mycobacterial genotype was 0.36 and significant (p<0.05). This proportion was higher (0.58) and significant for MAA but not for M. genavense. Evaluations of SNP distributions also showed genotypes of MAA were more related in connected birds than expected by chance; however, no significant patterns of genetic relatedness were identified for M. genavense, although data were sparse. Integrating the WGS analysis of mycobacteria with a social network analysis of their host birds revealed significant genetic clustering along pathways of connectivity, namely for MAA. These findings are consistent with a contagious process occurring in some, but not all, case clusters. [ABSTRACT FROM AUTHOR]

Viral infection and pathogenesis is mediated by host protein—viral protein complexes that are important targets for therapeutic intervention as they are potentially less prone to development of drug resistance. We have identified human, recombinant antibodies (Fabs) from a phage display library that bind to three HIV-host complexes. We used these Fabs to 1) stabilize the complexes for structural studies; and 2) facilitate characterization of the function of these complexes. Specifically, we generated recombinant Fabs to Vif-CBF-β-ELOB-ELOC (VCBC); ESCRT-I complex and AP2-complex. For each complex we measured binding affinities with KD values of Fabs ranging from 12–419 nM and performed negative stain electron microscopy (nsEM) to obtain low-resolution structures of the HIV-Fab complexes. Select Fabs were converted to scFvs to allow them to fold intracellularly and perturb HIV-host protein complex assembly without affecting other pathways. To identify these recombinant Fabs, we developed a rapid screening pipeline that uses quantitative ELISAs and nsEM to establish whether the Fabs have overlapping or independent epitopes. This pipeline approach is generally applicable to other particularly challenging antigens that are refractory to immunization strategies for antibody generation including multi-protein complexes providing specific, reproducible, and renewable antibody reagents for research and clinical applications. The curated antibodies described here are available to the scientific community for further structural and functional studies on these critical HIV host-factor proteins. [ABSTRACT FROM AUTHOR]

Species trees, which describe the evolutionary relationships between species, are often inferred from gene trees, which describe the ancestral relationships between sequences sampled at different loci from the species of interest. A common approach to inferring species trees from gene trees is motivated by supposing that gene tree variation is due to incomplete lineage sorting, also known as deep coalescence. One of the earliest methods motivated by deep coalescence is to find the species tree that minimizes the number of deep coalescent events needed to explain discrepancies between the species tree and input gene trees. This minimize deep coalescence (MDC) criterion can be applied in both rooted and unrooted settings. where either rooted or unrooted gene trees can be used to infer a rooted species tree. Previous work has shown that MDC is statistically inconsistent in the rooted setting, meaning that under a probabilistic model for deep coalescence, the multispecies coalescent, for some species trees, increasing the number of input gene trees does not make the method more likely to return a correct species tree. Here, we obtain analogous results in the unrooted setting, showing conditions leading to inconsistency of the MDC criterion using the multispecies coalescent model with unrooted gene trees for four taxa and five taxa. [ABSTRACT FROM AUTHOR]

The metabolic reprogramming of cancer cells creates metabolic vulnerabilities that can be therapeutically targeted. However, our understanding of metabolic dependencies and the pathway crosstalk that creates these vulnerabilities in cancer cells remains incomplete. Here, by integrating gene expression data with genetic loss-of-function and pharmacological screening data from hundreds of cancer cell lines, we identified metabolic vulnerabilities at the level of pathways rather than individual genes. This approach revealed that metabolic pathway dependencies are highly context-specific such that cancer cells are vulnerable to inhibition of one metabolic pathway only when activity of another metabolic pathway is altered. Notably, we also found that the no single metabolic pathway was universally essential, suggesting that cancer cells are not invariably dependent on any metabolic pathway. In addition, we confirmed that cell culture medium is a major confounding factor for the analysis of metabolic pathway vulnerabilities. Nevertheless, we found robust associations between metabolic pathway activity and sensitivity to clinically approved drugs that were independent of cell culture medium. Lastly, we used parallel integration of pharmacological and genetic dependency data to confidently identify metabolic pathway vulnerabilities. Taken together, this study serves as a comprehensive characterization of the landscape of metabolic pathway vulnerabilities in cancer cell lines. Author summary: Cancer cells rewire their metabolism, which creates targetable metabolic vulnerabilities. Previous analyses of metabolic vulnerabilities in cancer cells have been limited to the analysis of individual genes or metabolites. However, metabolic pathways exhibit significant cross talk and compensation for one another. We developed a computational method to answer the question: when a metabolic pathway's activity is high, which other metabolic pathways become more essential or less essential? By integrating genetic screen data with drug response data from FDA approved drugs, we identified cancer cell line dependence on metabolic pathways as opposed to individual genes. For example, we found that identifying key regulators of metabolic pathways, such as the Pentose Phosphate Pathway, may serve as a biomarker to identify which patients may benefit from antifolate chemotherapies (e.g. methotrexate, 5-fluorouracil). The efforts outlined here serve as the first characterization of the landscape of metabolic pathway vulnerabilities in cancer cell lines. Our results demonstrate the benefit of analyzing dependencies on metabolic pathways as opposed to metabolic genes. [ABSTRACT FROM AUTHOR]

Prokaryotic communities play key roles in biogeochemical transformation and cycling of nutrients in the productive mangrove ecosystem. In this study, the vertical distribution of rhizosphere bacteria was evaluated by profiling the bacterial diversity and community structure in the rhizospheres of four mangrove species (Sonneratia alba, Rhizophora mucronata, Ceriops tagal and Avicennia marina) from Mida Creek and Gazi Bay, Kenya, using DNA-metabarcoding. Alpha diversity was not significantly different between sites, but, significantly higher in the rhizospheres of S. alba and R. mucronata in Gazi Bay than in Mida Creek. Chemical parameters of the mangrove sediments significantly correlated inversely with alpha diversity metrics. The bacterial community structure was significantly differentiated by geographical location, mangrove species and sampling depth, however, differences in mangrove species and sediment chemical parameters explained more the variation in bacterial community structure. Proteobacteria (mainly Deltaproteobacteria and Gammaproteobacteria) was the dominant phylum while the families Desulfobacteraceae, Pirellulaceae and Syntrophobacteraceae were dominant in both study sites and across all mangrove species. Constrained redundancy analysis indicated that calcium, potassium, magnesium, electrical conductivity, pH, nitrogen, sodium, carbon and salinity contributed significantly to the species–environment relationship. Predicted functional profiling using PICRUSt2 revealed that pathways for sulfur and carbon metabolism were significantly enriched in Gazi Bay than Mida Creek. Overall, the results indicate that bacterial community composition and their potential function are influenced by mangrove species and a fluctuating influx of nutrients in the mangrove ecosystems of Gazi Bay and Mida Creek. [ABSTRACT FROM AUTHOR]

Epidemics may pose a significant dilemma for governments and individuals. The personal or public health consequences of inaction may be catastrophic; but the economic consequences of drastic response may likewise be catastrophic. In the face of these trade-offs, governments and individuals must therefore strike a balance between the economic and personal health costs of reducing social contacts and the public health costs of neglecting to do so. As risk of infection increases, potentially infectious contact between people is deliberately reduced either individually or by decree. This must be balanced against the social and economic costs of having fewer people in contact, and therefore active in the labor force or enrolled in school. Although the importance of adaptive social contact on epidemic outcomes has become increasingly recognized, the most important properties of coupled human-natural epidemic systems are still not well understood. We develop a theoretical model for adaptive, optimal control of the effective social contact rate using traditional epidemic modeling tools and a utility function with delayed information. This utility function trades off the population-wide contact rate with the expected cost and risk of increasing infections. Our analytical and computational analysis of this simple discrete-time deterministic strategic model reveals the existence of an endemic equilibrium, oscillatory dynamics around this equilibrium under some parametric conditions, and complex dynamic regimes that shift under small parameter perturbations. These results support the supposition that infectious disease dynamics under adaptive behavior change may have an indifference point, may produce oscillatory dynamics without other forcing, and constitute complex adaptive systems with associated dynamics. Implications for any epidemic in which adaptive behavior influences infectious disease dynamics include an expectation of fluctuations, for a considerable time, around a quasi-equilibrium that balances public health and economic priorities, that shows multiple peaks and surges in some scenarios, and that implies a high degree of uncertainty in mathematical projections. Author summary: Epidemic response in the form of social contact reduction, such as has been utilized during the ongoing COVID-19 pandemic, presents inherent tradeoffs between the economic costs of reducing social contacts and the public health costs of neglecting to do so. Such tradeoffs introduce an interactive, iterative mechanism that adds complexity to an infectious disease system. Consequently, infectious disease modeling typically has not included dynamic behavior change that must address such a tradeoff. Here, we develop a theoretical strategic model that introduces lost or gained economic and public health utility through the adjustment of social contact rates with delayed information. This model produces an equilibrium, a point of indifference where the tradeoff is neutral, and at which a disease will be endemic for a long period of time. Under small perturbations, this model exhibits complex dynamic regimes, including oscillatory behavior, runaway exponential growth, and eradication. These dynamics suggest that for epidemic responses that rely on social contact reduction, secondary waves and surges with accompanied business and school re-closures and shutdowns may be expected, and that accurate projection under such circumstances is unlikely. [ABSTRACT FROM AUTHOR]

The Nicaraguan COVID-19 situation is exceptional for Central America. The government restricts testing and testing supplies, and the true extent of the coronavirus crisis remains unknown. Dozens of deaths have been reported among health-care workers. However, statistics on the crisis' effect on health-care workers and their risk of being infected with SARS-CoV-2 are lacking. We aimed to estimate the prevalence of SARS-CoV-2 infection in health-care workers and to examine correlations with risk factors such as age, sex and comorbidities. Study participants (N = 402, median age 38.48 years) included physicians, nurses and medical assistants, from public and private hospitals, independent of symptom presentation. SARS-CoV-2 was detected on saliva samples using the loop-mediated isothermal amplification assay. A questionnaire was employed to determine subjects' COVID-19-associated symptoms and their vulnerability to complications from risk factors such as age, sex, professional role and comorbidities. The study was performed five weeks into the exponential growth period in Nicaragua. We discovered that 30.35% of health-care workers participating in our study had been infected with SARS-CoV-2. A large percentage (54.92%) of those who tested positive were asymptomatic and were still treating patients. Nearly 50% of health-care workers who tested positive were under 40, an astonishing 30.33% reported having at least one comorbidity. In our study, sex and age are important risk factors for the probability of testing positive for SARS-CoV-2 with significance being greatest among those between 30 and 40 years of age. In general, being male resulted in higher risk. Our data are the first non-governmental data obtained in Nicaragua. They shed light on several important aspects of COVID-19 in an underdeveloped nation whose government has implemented a herd-immunity strategy, while lacking an adequate healthcare system and sufficient PPE for health-care workers. These data are important for creating policies for containing the spread of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Nurses and surgeons must identify and handle specialized instruments with high temporal and spatial precision. It is crucial that they are trained effectively. Traditional training methods include supervised practices and text-based study, which may expose patients to undue risk during practice procedures and lack motor/haptic training respectively. Tablet-based simulations have been proposed to mediate some of these limitations. We implemented a learning task that simulates surgical instrumentation nomenclature encountered by novice perioperative nurses. Learning was assessed following training in three distinct conditions: tablet-based simulations, text-based study, and real-world practice. Immediately following a 30-minute training period, instrument identification was performed with comparable accuracy and response times following tablet-based versus text-based training, with both being inferior to real-world practice. Following a week without practice, response times were equivalent between real-world and tablet-based practice. While tablet-based training does not achieve equivalent results in instrument identification accuracy as real-world practice, more practice repetitions in simulated environments may help reduce performance decline. This project has established a technological framework to assess how we can implement simulated educational environments in a maximally beneficial manner. [ABSTRACT FROM AUTHOR]

To examine the differential mechanobiological responses of specific resident tendon cells, we developed an in vivo model of whole-body irradiation followed by injection of either tendon stem/progenitor cells (TSCs) expressing green fluorescent protein (GFP-TSCs) or mature tenocytes expressing GFP (GFP-TNCs) into the patellar tendons of wild type C57 mice. Injected mice were subjected to short term (3 weeks) treadmill running, specifically moderate treadmill running (MTR) and intensive treadmill running (ITR). In MTR mice, both GFP-TSC and GFP-TNC injected tendons maintained normal cell morphology with elevated expression of tendon related markers collagen I and tenomodulin. In ITR mice injected with GFP-TNCs, cells also maintained an elongated shape similar to the shape found in normal/untreated control mice, as well as elevated expression of tendon related markers. However, ITR mice injected with GFP-TSCs showed abnormal changes, such as cell morphology transitioning to a round shape, elevated chondrogenic differentiation, and increased gene expression of non-tenocyte related genes LPL, Runx-2, and SOX-9. Increased gene expression data was supported by immunostaining showing elevated expression of SOX-9, Runx-2, and PPARγ. This study provides evidence that while MTR maintains tendon homeostasis by promoting the differentiation of TSCs into TNCs, ITR causes the onset of tendinopathy development by inducing non-tenocyte differentiation of TSCs, which may eventually lead to the formation of non-tendinous tissues in tendon tissue after long term mechanical overloading conditions on the tendon. [ABSTRACT FROM AUTHOR]

Objective: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medication episodes from the clinical text to enhance our understanding of adverse effects related to Clozapine, the most effective antipsychotic drug for the management of treatment-resistant schizophrenia, but underutilised due to concerns over its side effects. Material and methods: We used data from de-identified EHRs of three mental health trusts in the UK (>50 million documents, over 500,000 patients, 2835 of which were prescribed Clozapine). We explored the prevalence of 33 adverse effects by age, gender, ethnicity, smoking status and admission type three months before and after the patients started Clozapine treatment. Where possible, we compared the prevalence of adverse effects with those reported in the Side Effects Resource (SIDER). Results: Sedation, fatigue, agitation, dizziness, hypersalivation, weight gain, tachycardia, headache, constipation and confusion were amongst the highest recorded Clozapine adverse effect in the three months following the start of treatment. Higher percentages of all adverse effects were found in the first month of Clozapine therapy. Using a significance level of (p< 0.05) our chi-square tests show a significant association between most of the ADRs and smoking status and hospital admission, and some in gender, ethnicity and age groups in all trusts hospitals. Later we combined the data from the three trusts hospitals to estimate the average effect of ADRs in each monthly interval. In gender and ethnicity, the results show significant association in 7 out of 33 ADRs, smoking status shows significant association in 21 out of 33 ADRs and hospital admission shows the significant association in 30 out of 33 ADRs. Conclusion: A better understanding of how drugs work in the real world can complement clinical trials. [ABSTRACT FROM AUTHOR]

Waiting times for organs in the United States are long and vary widely across regions. Donor registration can increase the number of potential donors, but its effect on the actual number of organ transplants depends upon several factors. First among these factors is that deceased donor organ donation requires both that death occur in a way making recovery possible and that authorization to recover organs is obtained. We estimate the potential donor death rate and donor authorization rate conditional on potential donor death by donor registration status for each state and for key demographic groups. With this information, we then develop a simple measure of the value of a new donor registration. This combined measure using information on donor authorization rates and potential death rates varies widely across states and groups, suggesting that focusing registration efforts on high-value groups and locations can significantly increase the overall number of donors. Targeting high-value states raises 26.7 percent more donors than a uniform, nationwide registration effort. Our estimates can also be used to assess alternative, but complementary, policies such as protocols to improve authorization rates for non-registered potential donors. [ABSTRACT FROM AUTHOR]

Chagas Disease, caused by the protozoan parasite Trypanosoma cruzi, is responsible for up to 41% of the heart failures in endemic areas in South America and is an emerging infection in regions of North America, Europe, and Asia. Treatment is suboptimal due to two factors. First, the lack of an adequate biomarker to predict disease severity and response to therapy; and second, up to 120-days treatment course coupled with a significant incidence of adverse effects from the drug currently used. Because the disease can manifest itself clinically a few years to decades after infection, controversy remains concerning the suitability of current drug treatment (benznidazole), and the efficacy of alternative drugs (eg posaconazole). We therefore followed the clinical course, and PCR detection of parasite burden, in a mouse model of infection for a full year following treatment with benznidazole or posaconazole. Efficacy of the two drugs depended on whether the treatment was performed during the acute model or the chronic model of infection. Posaconazole was clearly superior in treatment of acute disease whereas only benznidazole had efficacy in the chronic model. These results have important implications for the design and analysis of human clinical trials, and the use of specific drugs in specific clinical settings. Author summary: Chagas disease is a parasitic infection that can be incapacitating leading to heart failure with risk of sudden death. Currently, only one drug treatment is available, Benznidazole, but it demands a long period of treatment, has variable efficacy and leads to serious side effects that can lead to discontinuation of the treatment. An alternative therapy, the anti-fungal drug, Posaconazole, was repurposed for treatment of Chagas disease, but its use has been controversial with conflicting results in studies from different groups. In our approach, we followed the parasitic infection, disease symptoms and persistence of the pathogen in mice for a full year after treatment with Benznidazole or Posaconazole. Posaconazole treatment was more effective in the early infection (acute disease) whereas only Benznidazole had efficacy in the chronic model. This information can have important implications for the design and analysis of human clinical trials, and the use of specific drugs in specific clinical settings. [ABSTRACT FROM AUTHOR]