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Reviews are paid by on-demand review requests and by donations. Below is today's biomedical research from Biorxiv, Medrxiv, and Arxiv.

New | 4 December 2022 | Medrxiv link | Write review

Background: Stress occurring during pregnancy is associated with perturbances in maternal psychology and physiology, and results in adverse pregnancy and birth outcomes. However, little attention has been given to understand maternal stress and its potential negative consequences in many low- and middle-income countries. We aimed to investigate whether pregnancy is associated with greater stress and lower psychological resilience among women living in Jimma, Southwest Ethiopia. Method: An institution-based comparative cross-sectional study design was implemented in Jimma University Medical Center from 15 September to 30 November 2021. Women attending antenatal care and family planning services were invited to participate in the study. Participants were interviewed using the Perceived Stress Scale (PSS-10), Brief Resilience Scale (BRS), distress questionnaire-5, and the Household Food Insecurity Access Scale (HFIAS). Linear regression analysis was used to test associations of pregnancy (exposure) with outcomes of stress and resilience scores, while adjusting for potential confounders. Stress and resilience were mutually adjusted for one another in the final model. Results: A total of 166 pregnant and 154 non-pregnant women participated, with mean age of 27.0 SD 5.0 and 29.5 SD 5.3 years respectively. Pregnancy was associated with increased stress score by 4.1 points ({beta}=4.1; 95% CI: 3.0, 5.2), and with reduced resilience by 3.3 points ({beta}=3.3; 95% CI: -4.5, -2.2) in a fully adjusted model. In mutually-adjusted models, pregnancy was independently associated with greater stress ({beta}=2.9, 95% CI 1.8, 3.9) and lower resilience ({beta}=-1.3, 95% CI: -2.5, -0.2) compared to non-pregnant women. Conclusion: In this low income setting, pregnancy is associated with greater vulnerability in the mental health of women, characterized by greater perceived stress and diminished resilience. Context-relevant interventions to improve resilience and reduce stress could help improve the health and wellbeing of mothers, with potential benefits for their offspring. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Objective: Depression requiring treatment in the postpartum period (PPD) significantly impacts maternal and neonatal health. While preventive management of depression in pregnancy has been shown to decrease the negative effects, current methods for identifying at-risk patients are insufficient. Given the complexity of the diagnosis and interplay of clinical/demographic factors, we tested if machine learning (ML) techniques can accurately identify patients at risk of PPD. Study Design: This is a retrospective cohort study of the NIH Nulliparous Pregnancy Outcomes Study (nuMoM2b) which enrolled 10,038 nulliparous people. The primary outcome was PPD. We constructed and optimized four ML models using distributed random forest modeling based on the nuMoM2b dataset. Model 1 utilized only readily obtainable sociodemographic data. Model 2 added maternal pre-pregnancy mental health data. Model 3 utilized recursive feature elimination to construct a parsimonious model. Model 4 further titrated the input data to exclude pre-pregnancy mental health variables. Results: Of 8454 births, 338 (4%) were complicated by PPD. Model 3 was the highest performing, demonstrating the area under the receiver operating characteristics curve (AUC) of 0.91(+/-0.02). Models 1-3 identified the 9 variables most predictive of depression hierarchically ranging from BMI (highest), prior depression, age, income, medications, education, past medical history, race, and prior anxiety (lowest). In model 4, the AUC remained at 0.80(+/-0.04). Conclusions: Counterintuitively, the presence of pre-pregnancy mental health conditions is not the most predictive factor of PPD. Furthermore, PPD can be predicted with high accuracy for individual patients using antepartum information commonly found in the EMR. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

The ARTIC protocol uses a multiplexed PCR approach with two primer pools tiling the entire SARS-CoV-2 genome. Primer pool updates are necessary for accurate amplicon sequencing of evolving SARS-CoV-2 variants with novel mutations. The suitability of the ARTIC V4 and updated V4.1 primer scheme was assessed using whole genome sequencing of Omicron from clinical samples using Oxford Nanopore Technology. Analysis of Omicron BA.1 genomes revealed that 93.22% of clinical samples generated improved genome coverage at 50x read depth with V4.1 primers when compared to V4 primers. Additionally, the V4.1 primers improved coverage of BA.1 across amplicons 76 and 88, which resulted in the detection of the variant defining mutations G22898A, A26530G and C26577G. The Omicron BA.2 sub-variant (VUI-22JAN-01) replaced BA.1 as the dominant variant by March 2022, and analysis of 168 clinical samples showed reduced coverage across amplicons 15 and 75. Upon further interrogation of primer binding sites, a mutation at C4321T (present in 163/168, 97% of 30 samples) was identified as a possible cause of complete dropout of amplicon 15. Furthermore, two mutations were identified within the primer binding regions for amplicon 75: A22786C (present in 90% of samples) and C22792T (present in 12.5% of samples). Together, these mutations may result in reduced coverage of amplicon 75 and further primer updates would allow the identification of the two BA.2 defining mutations present in amplicon 75; A22688G and T22679C. This work highlights the need for ongoing surveillance of primer matches as circulating variants evolve and change. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Patients with chronic anemia, or low blood hemoglobin levels, are frequently subjected to the cost, inconvenience, and discomfort of traditional hematology analyzer-based measurements of blood hemoglobin levels via complete blood counts. Elimination of the need for complete blood count testing for hemoglobin screening is an unmet clinical need that we previously addressed by developing a non-invasive smartphone app that estimates hemoglobin levels via image analysis of fingernail bed images. In this work, we present additional data yielding significant improvement upon our previously established technology and describe the clinical validation, and real-world translation of the technology into a commercial product. To improve accuracy and create a clinical use case, we trained the app algorithm on individuals with chronic anemia to personalize the image analysis algorithm for estimating hemoglobin levels. Individual-level differences associated with using the app (variations between individuals, how a user captures images, the specific smartphone they use, the lighting conditions in the location they take the pictures, and biological variability within a population) appear to be the greatest source of measurement variability within larger sample sets. Therefore, we hypothesized that personalization of the algorithm could correct for user-to-user variability and translate to improved accuracy at the individual level. To test this hypothesis, we trained and tested personalized algorithms for individuals in clinical and real world settings. We enrolled 35 chronically anemic subjects [a chronic kidney disease (CKD) cohort] in a clinical study wherein the app algorithm was trained using complete blood count data and paired fingernail bed images, then tested against complete blood count data at subsequent study timepoints. After personalization, testing data revealed a mean absolute error (MAE) of 0.74 g/dL with a root mean squared error (RMSE) of 0.97 g/dL across all testing visits across all subjects, a significant improvement when compared to performance without personalization in the same user group (1.36 g/dL MAE and 1.70 g/dL RMSE, p = 3.13E-11). The app was also used in the real world by real app users who self-reported lab/complete blood count blood draw results. App performance findings were consistent with analysis of self-reported data from 17 individuals using our app. After training of the individual app algorithm in the real world, testing data revealed a mean absolute error (MAE) of 0.62 g/dL with a root mean squared error (RMSE) of 0.85 g/dL when 4 training data points were used, an improvement when compared to performance of the app without personalization in the same user group (0.71 g/dL MAE and 1.27 g/dL RMSE). The personalized app accuracy is similar to that of other noninvasive Hgb measurement technologies currently on the market as medical devices with US Food & Drug Administration (US FDA) clearance. Thus, our technology represents a significant step forward towards true personalized medicine in a digital healthcare setting. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Overlapping symptoms and copathologies are common in closely related neurodegenerative diseases (NDDs). Investigating genetic risk variants across these NDDs can give further insight into disease manifestations. In this study we have leveraged genome-wide single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) summary statistics to cluster patients based on their genetic status across identified risk variants for five NDDs (Alzheimer's disease [AD], Parkinson's disease [PD], amyotrophic lateral sclerosis [ALS], Lewy body dementia [LBD], and frontotemporal dementia [FTD]). The multi-disease and disease-specific clustering results presented here provide evidence that NDDs have more overlapping genetic etiology than previously expected and how neurodegeneration should be viewed as a spectrum of symptomology. These clustering analyses also show potential subsets of patients with these diseases that are significantly depleted for any known common genetic risk factors suggesting environmental or other factors at work. Establishing that NDDs with overlapping pathologies share genetic risk loci, future research into how these variants might have different effects on downstream protein expression, pathology and NDD manifestation in general is important for refining and treating NDDs. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Importance: Advanced stage non-small cell lung cancer (NSCLC) patients with no driver mutations are typically treated with immune checkpoint inhibitor (ICI)-based therapy, either in the form of monotherapy or concurrently with chemotherapy, while treatment modality selection is based mainly on programmed death ligand 1 (PD-L1) expression levels in the tumor. However, PD-L1 assays are only moderately predictive of therapeutic benefit. Objective: To develop a novel decision-making tool for physicians treating NSCLC patients on whether to administer immune checkpoint inhibitor (ICI) therapy alone or in combination with chemotherapy. Design, setting, and participants: This multicenter observational study includes patients from an ongoing clinical trial (PROPHETIC; NCT04056247). Patients were recruited from 13 different centers (total n=425; 58 patients were excluded) from June 2016 and June 2021. Plasma samples were obtained prior to treatment initiation, and deep proteomic profiling was conducted. PROphet computational model for predicting clinical benefit (CB) probability at 12 months was developed based on the plasma proteomic profile. The model performance was validated in a blinded manner. Following validation, training and prediction was performed over the entire cohort using cross-validation methodology. The patients were divided into four groups based on their PD-L1 expression level combined with their CB probability, and the survival outcome was examined for each group. The data were analyzed from July to October 2022. Main outcome and measures: Clinical benefit from ICI-based treatment, overall survival (OS) and progression-free survival (PFS). Results: The model displayed strong predictive capability with an AUC of 0.78 (p-value = 5.00e-05), outperforming a PD-L1-based predictive model (AUC = 0.62; p-value 2.76e-01), and exhibited a significant difference in OS and PFS between patients with low and high CB probabilities. When combining CB probability with PD-L1 expression levels, four patient subgroups were identified; (i) patients with PD-L1>=50% and a negative PROphet result who significantly benefit from ICI-chemotherapy combination therapy compared to ICI monotherapy; (ii) patients with PD-L1[≥]50% and a positive PROphet result who benefit similarly from either treatment modalities; (iii) patients with PD-L1<50% and a negative PROphet result who do not benefit from either treatment modalities; (iv) patients with PD-L1<50% and a positive PROphet score who benefit from combination therapy. Conclusions and relevance: The PROphet model displayed good performance for prediction of CB at 12 months based on a plasma sample obtained prior to treatment. Our findings further demonstrate a potential clinical utility for informing treatment decisions for NSCLC patients treated with ICIs by adding resolution to the PD-L1 biomarker currently used to guide treatment selection, thereby enabling to select the most suitable treatment modality for each patient. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Background Cardiovascular disease (CVD) is a leading cause of death globally. Angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB), compared in the ONTARGET trial, each prevent CVD. However, trial populations may not be representative of the general population. Methods Using trial replication methods within routine-care data, we explored replicability of the ONTARGET trial. For people prescribed an ACEi and/or an ARB in the UK Clinical Practice Research Datalink CPRD GOLD from 1/1/2001-31/7/2019, we applied trial criteria and propensity-score methods to create an ONTARGET trial-eligible cohort. Comparing ARB to ACEi, using Cox-proportional hazards models, we estimated hazard ratios for the primary composite trial outcome (cardiovascular death, myocardial infarction, stroke, or hospitalisation for heart failure), as well as secondary outcomes. As the pre-specified criteria were met confirming trial replicability, we then explored treatment effect heterogeneity of ACEi and ARB among three trial-underrepresented subgroups: females, those aged [≥] years and those with chronic kidney disease. Findings In the trial-eligible population (n=137,155), results for the primary outcome met pre-specified criteria for similarity to the ONTARGET trial and demonstrated similar effects of ARB and ACEi, (HR 0.97 [95% CI: 0.93, 1.01]). When extending to trial-underrepresented groups, similar treatment effects of ARB and ACEi were observed by sex (P=0.09), age (P=0.70) and chronic kidney disease status (P=0.10). Interpretation We were able to replicate the results of the ONTARGET trial using routinely-collected healthcare data. Results suggest that trial findings were generalisable to population subgroups underrepresented in the trial. Funding GlaxoSmithKline | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Short-term forecasts can provide predictions of how an epidemic will change in the near future and form a central part of outbreak mitigation and control. Renewal-equation based models are increasingly popular. They infer key epidemiological parameters from historical epidemiological data and forecast future epidemic dynamics without requiring complex mechanistic assumptions. However, these models typically ignore interaction between age-groups, partly due to challenges in parameterising a time varying interaction matrix. Social contact data collected regularly by the CoMix survey during the COVID-19 epidemic in England, provide a means to inform interaction between age-groups in real-time. We developed an age-specific forecasting framework and applied it to two age-stratified time-series: incidence of SARS-CoV-2 infection, estimated from a national infection and antibody prevalence survey; and, reported cases according to the UK national COVID-19 dashboard. Jointly fitting our model to social contact data from the CoMix study, we inferred a time-varying next generation matrix which we used to project infections and cases in the four weeks following each of 29 forecast dates between October 2021 and November 2022. We evaluated the forecasts using proper scoring rules and compared performance with three other models with alternative data and specifications alongside two naive baseline models. Overall, incorporating age-interaction improved forecasts of infections and the CoMix-data-informed model was the best performing model at time horizons between two and four weeks. However, this was not true when forecasting cases. We found that age-group-interaction was most important for predicting cases in children and older adults. The contact-data-informed models performed best during the winter months of 2020 - 2021, but performed comparatively poorly in other periods. We highlight challenges regarding the incorporation of contact data in forecasting and offer proposals as to how to extend and adapt our approach, which may lead to more successful forecasts in future. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Rationale: The impact of aortic valve stenosis (AS) on systemic endothelial function independent of standard modifiable risk factors (SMuRFs) is unknown. Objective: We hypothesized that AS induces subclinical hemoglobin release from red blood cells (RBCs) following transvalvular passage due to post-stenotic aberrant blood flow and that cell-free hemoglobin (fHb) may limit endothelial NO bioavailability, affecting vascular function. Methods and Results: AS induces swirling blood flow in the ascending aorta which impairs RBC integrity with consecutive release of fHb. Indeed, swirl flow magnitude assessed by 4D flow cardiac magnetic resonance correlates with fHb levels. Elevated systemic fHb reduces NO bioavailability and thus impairs endothelial cell function as evidenced by impaired flow mediated dilation (FMD). In addition, we here demonstrate impaired FMD in an experimental model of AS utilising C57BL/6 mice with preserved left ventricular function and without cardiovascular risk factors. In this model, endothelial dysfunction is accompanied by significantly increased fHb, exaggerated NO consumption and increased plasma levels of nitroso species and the final NO oxidation product, nitrate. Scavenging of fHb by infusion of haptoglobin reversed these deleterious effects. There observations were verified by transfer experiments with human plasma (sampled from patients with AS sheduled for TAVR) using a murine aortic ring bioassay system where the plasma from AS patients induced endothelial dysfunction when compared to plasma from control individuals without AS. Importantly, these deleterious effects were reversed by successful aortic valve replacement via TAVR independent of SMuRFs. Conclusions: In aortic valve stenosis, increases in post-valvular swirl blood flow in the ascending aorta induces subclinical hemolysis that impairs NO bioavailability. Thus, AS itself promotes systemic endothelial dysfunction independent of other established risk factors. Transcatheter aortic valve replacement limits NO scavenging by realigning of postvalvular blood flow to normal physiological patterns. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Although Candida spp., is a common cause of bloodstream infections and is often associated with high mortality rates, its resistance to antifungal drugs, and the molecular mechanisms involved have been poorly studied in Colombia. Here, 123 bloodstream isolates of Candida spp. were collected. MALDI-TOF MS identification and fluconazole (FLC) susceptibility patterns were assessed on all isolates. Subsequently, sequencing of ERG11, TAC1 or MRR1, and efflux pumps were performed for resistant isolates. Out of 123 clinical strains, C. albicans accounted for 37.4%, followed by C. tropicalis 26.8%, C. parapsilosis 19.5%, C. auris 8.1%, C. glabrata 4.1%, C. krusei 2.4% and C. lusitaniae 1.6%. Resistance to FLC reached 18%. Erg11 amino acid substitutions associated with FLC-resistance (Y132F, K143R or T220L) were found in 58% of 19 FLC-resistant isolates. Furthermore, novel mutations were found in all genes studied. Regarding efflux pumps, 42% of 19 FLC-resistant Candida spp strains showed significant efflux activity. Finally, six of the 19 FLC-resistant isolates neither harbored resistance-associated mutations nor showed efflux pump activity. Although C. albicans remain the most predominant species, non-C. albicans species comprise a high proportion (62.6%). Among FLC-resistant species, C. auris (70%) and C. parapsilosis (25%) displayed the highest percentages of resistance. In 68% of FLC-resistant isolates, a mechanism that could explain their phenotype was found (e.g. mutations, flux pump activity or both). We provide evidence that endemic isolates harbor amino acid substitutions related with resistance to one of the most used molecules in the hospital setting, with Y132F being the most frequently detected one. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Background: Antiretroviral Therapy-associated adverse effects and comorbidities are still pervasive in people living with HIV, especially metabolic syndrome (MetS), which is on the rise and occurring at early age. However, there is paucity of data on MetS in children and adolescents living with HIV (CALWH), particularly in sub-Saharan Africa. We investigated the age-dependent prevalence of components of MetS in this population. Methods: A cross-sectional pilot study of CALWH treated at the Baylor Uganda Clinical Centre of Excellence in Kampala, Uganda. Using stratified by age group and sex random sampling, participants were recruited from May to August 2021. At enrollment, we collected data on participant demographics, anthropometric measurements, HIV disease characteristics, and past medical history and obtained blood for fasting levels of glucose, insulin, triglycerides, total cholesterol, and high-density lipoprotein (HDL) cholesterol. The primary outcome of MetS was defined by both the International Diabetes Federation (IDF) and Adult Treatment Panel (ATPIII) criteria. We estimated the prevalence of MetS and its components for all participants and by the stratification factors. Results: We enrolled 90 children and adolescents: <10 y/o (N=30), 10 to <16 y/o (N=30), and [≥]16 (N=30) y/o. Fifty-one percent were females. The prevalence of MetS was 1.11% (1 of 90) using either IDF or ATPIII criteria for all participants, and 3.33% for [≥]16-year group. Over 55% of participants had [≥]1 IDF component, with 47% having low HDL cholesterol; 14% of participants had early insulin resistance using the HOMA index. The proportion of early insulin resistance was 6.67%, 23.33%, and 13.33% for the three age groups, respectively. Two participants (6.67%) in the 10 to <16 years group had significant insulin resistance. For every 1-year increase in age, HOMA index increased by 0.04 (95% Confidence Interval 0.01, 0.08), p=0.02. Conclusions: The high prevalence of components of MetS, particularly low HDL and early insulin resistance, are of concern. With increasing survival of CALWH into adulthood and increased lifetime exposure to ART, the frequency of MetS in this population may rise, increasing the lifetime risk for associated health problems, such as type 2 diabetes, myocardial infarction, stroke, and nonalcoholic fatty liver disease. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Objective: To evaluate the cost-effectiveness of a personalised medicine strategy for Crohns disease in the UK, using early targeted top-down therapy compared to standard of care. Materials & Methods: A decision tree leading into a Markov state-transition model was constructed, allowing comparison of two treatment approaches: 1) standard of care therapy following established UK clinical guidelines (step-up treatment) and 2) a personalised medicine strategy in which patients identified as high-risk of subsequent relapse using a prognostic biomarker receive top-down anti-TNF treatment at diagnosis. The model facilitated comparison of both costs and Quality Adjusted Life Years (QALYs) in a hypothetical cohort of newly diagnosed Crohns disease patients with sensitivity analyses undertaken to model the impact of key assumptions. Results: Early personalised treatment with anti-TNF based combination therapy resulted in an incremental cost-effectiveness ratio (ICER) of GBP2,176 per quality-adjusted life year (QALY), with GBP717 incremental costs and 0.330 incremental QALYs, substantially below the NICE cost-effectiveness threshold of between GBP20,000 and GBP30,000 per QALY. Additional costs relating to earlier biologic use were offset by incremental QALYS and reductions in costs driven by fewer disease flares and hospitalisations. Sensitivity analysis across a wide range of parameter assumptions did not impact on the models conclusion. Conclusion: A personalised medicine strategy using anti-TNF therapy at diagnosis in Crohns disease to patients at high risk of subsequent relapse is highly likely to be a cost-effective use of resources in the UK National Health Service. Keywords: Prognostic test, Biomarker, Personalised medicine, Cost-effectiveness, Crohns disease | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Background Booster vaccines providing protection against emergent SARS-CoV-2 variants are needed. In an international phase 3 study, we evaluated booster vaccines containing prototype (D614) and/or Beta (B.1.351) variant recombinant spike proteins and AS03 adjuvant (CoV2 preS dTM-AS03). Methods Adults, primed 4-10 months earlier with mRNA (BNT162b2, mRNA-1273]), adenovirus-vectored (Ad26.CoV2.S, ChAdOx1nCoV-19) or adjuvanted protein (CoV2 preS dTM-AS03 [D614]) vaccines and stratified by age (18-55 and [≥]56 years), were boosted with monovalent (MV) D614 (5[≥]g, n=1285), MV (B.1351) (5g, n=707) or bivalent (BiV) (2.5[≥]g D614 plus 2.5[≥]g B.1.351, n=625) CoV2 preS dTM-AS03. SARS-CoV-2-naive adults (controls, n=479) received a primary series (two injections, 21 days apart) of CoV2 preS dTM-AS03 containing 10g D614. Antibodies to D614G, B.1.351 and Omicron BA.2 and BA.1 variants were evaluated using validated pseudovirus (lentivirus) neutralization (PsVN) assay. D614G or B.1.351 PsVN titers 14 days (D15) post-booster were compared with pre-booster (D1) titers in BNT162b2-primed participants (18-55 years old) and controls (D36), for each booster formulation (co-primary objectives). Safety was evaluated throughout the trial. Results of a planned interim analysis are presented. Results Among BNT162b2-primed adults (18-55 years old), PsVN titers against D614G or B.1.351 were significantly higher post-booster than anti-D614G titers post-primary vaccination in controls, for all booster formulations, with an anti-D614G GMT ratio (98.3% CI) of 2.16 (1.69; 2.75) for MV(D614), an anti-B.1.351 ratio of 1.96 (1.54; 2.50) for MV (B.1.351) and anti-D614G and anti-B.1.351 ratios of 2.34 (1.84; 2.96) and 1.39 (1.09; 1.77), respectively, for BiV. All booster formulations elicited cross-neutralizing antibodies against Omicron BA.2 across vaccine priming subgroups and against Omicron BA.1 (evaluated in BNT162b2-primed participants). Similar patterns in antibody responses were observed for participants aged [≥]56 years. No safety concerns were identified. Conclusion CoV2 preS dTM-AS03 boosters demonstrated acceptable safety and elicited robust neutralizing antibodies against multiple variants, regardless of priming vaccine. ClinicalTrials.gov: NCT04762680 | Make paid

New | 4 December 2022 | Medrxiv link | Write review

BACKGROUND: With widespread transmission of the Omicron SARS-CoV-2 variant, reinfections have become increasingly common. Here, we explored the role hybrid immunity, primary infection severity, and variant predominance on the risk of reinfection and severe COVID-19 during periods of Omicron predominance in Mexico. METHODS: We analyzed reinfections in Mexico in individuals with [≥]90 days from a previous primary infection using a national surveillance registry of SARS-CoV-2 cases from March 3rd, 2020, until August 13th, 2022. Immunity-generating events included primary infection, partial or full vaccination and vaccine boosting. Reinfections were matched by age and sex with controls with primary SARS-CoV-2 infection and negative RT-PCR or antigen test [≥]90 days after infection to explore risk factors for reinfection and reinfection-associated severe COVID-19. We also explored the protective role of heterologous vs. homologous vaccine boosters against reinfection or severe COVID-19 in fully vaccinated individuals. RESULTS: We detected 231,202 SARS-CoV-2 reinfections in Mexico, with most occurring in unvaccinated individuals (41.55%). Over 207,623 reinfections occurred during periods of Omicron (89.8%), BA.1 (36.74%) and BA.5 (33.67%) subvariant predominance and a case-fatality rate of 0.22%. Vaccination protected against reinfection, without significant influence of the order of immunity-generating events and provided >90% protection against severe reinfections. Heterologous booster schedules were associated with ~11% and ~54% lower risk for reinfection and reinfection-associated severe COVID-19 respectively, modified by time-elapsed since the last immunity-generating event. CONCLUSIONS: SARS-CoV-2 reinfections have increased during periods of Omicron predominance. Hybrid immunity provides protection against reinfection and reinfection-associated severe COVID-19, with potential benefit from heterologous booster schemes. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

Background: Research demonstrates that SARS-CoV-2 infection (COVID-19) among adults disproportionately impacts racial and ethnic minorities and those living in lower-income communities. Similar research in children is limited due, in part, to the relatively low incidence in children compared to adults. This analysis, conducted as part of the RECOVER Initiative, explores this question. Methods: Electronic health record (EHR) data from PEDSnet, a multi-institutional research network of pediatric healthcare organizations, were geocoded and linked to two indices of contextual social deprivation: the Area Deprivation Index and the Child Opportunity Index. Univariate statistics were employed to test the association between each index and COVID19 positivity among children ages 0-20 tested at one of six Childrens hospitals. Multivariate logistic regression was used to explore the relationship between these social context indices and racial disparities in positivity, controlling co-variates. Results: Both ADI and COI were significantly associated with COVID-19 positivity in univariate and adjusted models, particularly in the pre-delta and delta variant waves. ADI showed a stronger association. Higher rates of positivity were found for non-Hispanic Black, Hispanic, and multi-racial children compared to non-Hispanic White children. These racial disparities remained significant after control for either index and other variables. Conclusion: ADI and COI are significantly associated with COVID-19 test positivity in a population of children and adolescents tested in childrens hospital settings. These social contextual variables do not fully explain racial disparities arguing that racial disparities are not solely a reflection of socioeconomic status. Future disparities research should consider both race and social context. | Make paid

New | 4 December 2022 | Medrxiv link | Write review

The Polio eradication campaign has been set back substantially since 2020 due to the COVID-19 pandemic. Recent detections of poliovirus transmission in multiple high-income countries suggest suboptimal population immunity in many parts of the world even though polio vaccination has been included in routine childhood immunization for decades. We reviewed polio vaccination schedules and vaccine uptake in the Western Pacific Region countries and assessed the potential shortfall in population immunity against polio resurgence across these populations. In addition, we conducted a repeated cross-sectional study between 2021 and 2022 in the Western Pacific Region to understand factors contributing to polio vaccine hesitancy. Our results reveal potential shortfalls in population immunity against polio in Western Pacific Region and provide insights into how vaccination programs and campaigns can be strengthened to ensure continual progress towards polio eradication. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

In agricultural crops, forests and grasslands, water deficit often occurs in the presence of cues from neighbouring vegetation. However, most studies have addressed separately the mechanisms of plant growth responses to these two aspects of the environment. Here we show that transferring Arabidopsis thaliana seedlings to agar containing polyethylene glycol (PEG) to restrict water availability reduces hypocotyl growth responses to shade without simultaneous affecting cotyledon expansion or its response to shade. Water restriction diminished the activity of the PHYTOCHROME INTERACTING FACTOR 4 (PIF4), PIF5, PIF3 and PIF3-LIKE 1 gene promoters, particularly in seedlings exposed to simulated shade. The response of PIF4 expression to PEG required the presence of its positive morning regulators CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY), which also reduced their expression in response to PEG. Water restriction diminished the nuclear abundance of PIF4 in hypocotyl cells only in the seedlings exposed to shade. In addition to the changes in PIF4 levels, post-transcriptional processes also contributed to the response to PEG. Hypocotyl growth showed significant triple interaction among water availability, shade and the presence of PIF4, PIF5 and PIF3. Collectively, these results unveil PIFs as a hub that interlinks shade and drought information to control growth. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Infectious disease dynamics operate across biological scales: pathogens replicate within hosts, but transmit among hosts and populations. Functional changes in the pathogen-host interaction thus generate cascading effects from molecular to landscape scales. We investigated within-host dynamics and among-host transmission of three strains of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask (i) How do viral and immune dynamics vary among FMDV strains? (SAT1, 2, 3); (ii) Which viral and immune parameters determine viral fitness within hosts?; and (iii) How do within-host dynamics relate to virus transmission among hosts? Our data reveal contrasting within-host dynamics among viral strains. However, SAT2 elicited more rapid and effective immune responses than SAT1 and SAT3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates against FMDVs, but not by variation among individual hosts in viral growth rate. By contrast, our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo; and that adaptive immune activation rate determines the infectious period. Together, these parameters define the basic reproductive number of the virus, suggesting that viral invasion potential may be predictable from within-host dynamics. Future work should test the generality of these findings by including additional FMDV strains, and create a multi-scale model to link within-host and between-host dynamics explicitly. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Spike-and-wave discharges (SWDs), generated by the cortico-thalamo-cortical (CTC) network, are pathological, large amplitude oscillations and the hallmark of absence seizures (ASs). SWDs begin in a cortical initiation network in both humans and animal models, including the Genetic Absence Epilepsy Rats from Strasbourg (GAERS), where it is located in the primary somatosensory cortex (S1). The behavioral manifestation of an AS occurs when SWDs spread from the cortical initiation site to the whole brain, however, the mechanisms behind this rapid propagation remain unclear. Here we investigated these processes beyond the principal CTC network, in higher-order (HO) thalamic nuclei (lateral posterior (LP) and posterior (PO) nuclei) since their diffuse connectivity and known facilitation of intracortical communications make these nuclei key candidates to support SWD generation and maintenance. In freely moving GAERS, multi-site LFP in LP, PO and multiple cortical regions revealed a novel feature of SWDs: during SWDs there are short periods (named SWD-breaks) when cortical regions far from S1, such the primary visual cortex (V1), become transiently unsynchronized from the ongoing EEG rhythm. Inactivation of HO nuclei with local muscimol injections or optogenetic perturbation of HO nuclei activity increased the occurrence of SWD-breaks and the former intervention also increased the SWD propagation-time from S1. The neural underpinnings of these findings were explored further by silicon probe recordings from single units of PO which uncovered two previously unknown groups of excitatory neurons based on their burst firing dynamics at SWD onset. Moreover, a switch from tonic to burst firing at SWD onset was shown to be an important feature since it was much less prominent for non-generalized events, i.e. SWDs that remained local to S1. Additionally, one group of neurons showed a reverse of this switch during SWD-breaks, demonstrating the importance of this firing pattern throughout the SWD. In summary, these results support the view that multiple HO thalamic nuclei are utilized at SWD onset and contribute to cortical synchrony throughout the paroxysmal discharge. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Developing leaves undergo a vast array of age-related changes as they mature. These include physiological, hormonal and morphological changes that determine their adaptation plasticity towards adverse conditions. Waterlogging induces leaf epinasty in tomato, and the magnitude of leaf bending is intricately related to the age-dependent cellular and hormonal response. We now show that ethylene, the master regulator of epinasty, is differentially regulated throughout leaf development, giving rise to age-dependent epinastic responses. Young leaves have a higher basal ethylene production, but are less responsive to waterlogging-induced epinasty, as they have a higher capacity to convert the root-borne and mobilized ACC into the inactive conjugate MACC. Ethylene stimulates cell elongation relatively more at the adaxial petiole side, by activating auxin biosynthesis and locally inhibiting its transport through PIN4 and PIN9 in older and mature leaves. As a result, auxins accumulate in the petiole base of these leaves and enforce partially irreversible epinastic bending upon waterlogging. Young leaves maintain their potential to transport auxins, both locally and through the vascular tissue, leading to enhanced flexibility to dampen the epinastic response and a faster upwards repositioning during reoxygenation. This mechanism also explains the observed reduction of epinasty during and its recovery after waterlogging in the anthocyanin reduced (are) and Never ripe (Nr) mutants, both characterized by higher auxin flow. Our work has demonstrated that waterlogging activates intricate hormonal crosstalk between ethylene and auxin, controlled in an age-dependent way. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Carbohydrate Active enZymes (CAZymes) are pivotal in biological processes including energy metabolism, cell structure maintenance, signalling and pathogen recognition. Bioinformatic prediction and mining of CAZymes improves our understanding of these activities, and enables discovery of candidates of interest for industrial biotechnology, particularly the processing of organic waste for biofuel production. CAZy (www.cazy.org) is a high-quality, manually-curated and authoritative database of CAZymes that is often the starting point for these analyses. Automated querying, and integration of CAZy data with other public datasets would constitute a powerful resource for mining and exploring CAZyme diversity. However, CAZy does not itself provide methods to automate queries, or integrate annotation data from other sources (except by following hyperlinks) to support further analysis. To overcome these limitations we developed cazy_webscraper, a command-line tool that retrieves data from CAZy and other online resources to build a local, shareable, and reproducible database that augments and extends the authoritative CAZy database. cazy_webscraper's integration of curated CAZyme annotations with their corresponding protein sequences, up to date taxonomy assignments, and protein structure data facilitates automated large-scale and targeted bioinformatic CAZyme family analysis and candidate screening. This tool has found widespread uptake in the community, with over 20,000 downloads. We demonstrate the use and application of cazy_webscraper to: (i) augment, update and correct CAZy database accessions; (ii) explore taxonomic distribution of CAZymes recorded in CAZy, identifying underrepresented taxa and unusual CAZy class distributions; and (iii) investigate three CAZymes having potential biotechnological application for degradation of biomass, but lacking a representative structure in the PDB database. We describe in general how cazy_webscraper facilitates functional, structural and evolutionary studies to aid identification of candidate enzymes for further characterisation, and specifically note that CAZy provides supporting evidence for recent expansion of the Auxiliary Activities (AA) CAZy family in eukaryotes, consistent with functions potentially specific to eukaryotic lifestyles. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Nutrient intake drives secretion of insulin and insulin-like peptides that stimulate glucose uptake, nutrient storage, protein synthesis and cell growth. The Drosophila genome encodes seven insulin- like peptides (Dilps) that bind to a single known insulin receptor to drive growth and nutrient storage. Whether Dilps respond uniformly to changes in dietary nutrients is unknown. Here we characterized the endocrine response to starvation and dietary sugar and protein in mid-third instar Drosophila larvae, measuring circulating Dilp2, derived from insulin-producing cells in the brain, and Dilp6, produced by the fat body. Starvation led to a 90% reduction in circulating Dilp2 without affecting circulating Dilp6 levels. Dietary protein, but not sugar, restored hemolymph Dilp2 from starved levels, while elevated and imbalanced ratios of sugar to protein led to modest reductions in circulating Dilp2. In contrast, hemolymph Dilp6 was increased by a sugar-only diet. Surprisingly, dietary protein strongly reduced circulating Dilp6 levels. Dietary sugar drives glycogen and triglyceride storage, and levels of these stored nutrients positively correlate with Dilp6. Protein in the diet promotes whole-animal growth, which correlates strongly with circulating Dilp2. Our data show that Dilp2 and Dilp6 secretion are regulated in opposite ways by distinct dietary nutrients. These findings raise the question of how the single known insulin receptor integrates divergent signals from distinct Dilps to control growth and metabolism. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

In tomato, downward leaf bending is a morphological adaptation towards waterlogging, which has been shown to induce a range of metabolic and hormonal changes. This kind of functional trait is often the result of a complex interplay of regulatory processes starting at the gene level, gated through a plethora of signaling cascades and modulated by environmental cues. Through phenotypical screening of a population of 54 tomato accessions in a Genome Wide Association Study (GWAS), we have identified target genes potentially involved in plant growth and survival during waterlogging and subsequent recovery. Changes in both plant growth rate and epinastic descriptors revealed several associations to genes possibly supporting metabolic activity in low oxygen conditions in the root zone. In addition to this general reprogramming, some of the targets were specifically associated to leaf angle dynamics, indicating these genes might play a role in the induction, maintenance or recovery of differential petiole elongation in tomato during waterlogging. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Biomolecular condensates are intracellular membrane-less accumulations of proteins and other molecules at a higher concentration than the rest of the cell. The recent characterization of condensates as liquid-like assemblies has stimulated profound interest in how physical properties of condensates impact molecular biology. Intriguingly, condensates have been shown to be essential to multiple different cellular processes and underlying aspects of various diseases. Yet, the physics of condensate formation remains unsolved. Here, it is shown that intrinsically disordered protein-protein binding alone provides energetically favorable thermodynamics for condensate formation. The reduction in free energy achieved through increased binding at high condensate concentrations can overcome the entropic cost of de-mixing. Formation of condensates is governed by the ratio of total protein concentration to binding affinity ([protein]total/Kd). Yet, stable condensation is only possible through interactions with rapid binding dynamics. The model prediction and experimental observation that condensates are no longer formed at high [protein]total/Kd ratios redefines our understanding of condensate physics and impact on cellular biology. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Inference and interpretation of evolutionary processes - in particular of the types and targets of natural selection affecting coding sequences, are critically influenced by the assumptions built into statistical models for such analyses. If certain aspects of the substitution process (even when they are not of direct interest) are presumed absent or are modeled with too crude of a simplification, estimates of key model parameters can become biased - often systematically, and lead to poor statistical performance. Here, we performed a detailed characterization of how modeling instantaneous multi-nucleotide (or multi-hit, MH) substitutions impacts dN/dS based inference of episodic diversifying selection at the level of the entire alignment. The inclusion of MH reduces the rate (1.37-fold or 26.8%) at which positive selection is called based on the analysis of N = 9,861 empirical data-sets, while offering significantly better statistical fit to sequence data in 8.37% of cases. Through additional simulation studies, we show that this reduction is not simply due to loss of power because of additional model complexity. After a detailed examination of 21 benchmark alignments and a new high-resolution analysis showing which parts of the alignment provide support for positive selection, we reveal that MH substitutions occurring along shorter branches in the tree are largely responsible for discrepant results in selection detection. Our results add to the growing body of literature which examines decades-old modeling assumptions and finds them to be problematic for biological data analysis. Because multi-nucleotide substitutions have a significant impact on natural selection detection even at the level of an entire gene, we recommend that routine selection analysis of this type consider their inclusion. To facilitate this procedure, we developed a simple model testing selection detection framework able to screen an alignment for positive selection with two biologically important confounding processes: synonymous rate variation, and multi-nucleotide instantaneous substitutions. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

The biological function of natural non-coding RNAs (ncRNA) is tightly bound to their molecular structure. Sequence analyses such as multiple sequence alignments (MSA) are the bread and butter of bio-molecules functional analysis; however, analyzing sequence and structure simultaneously is a difficult task. In this work, we propose CARNAGE (Clustering/Alignment of RNA with Graph-network Embedding), which leverages a graph neural network encoder to imprint structural information into a sequence-like embedding; therefore, downstream sequence analyses now account implicitly for structural constraints. In contrast to the traditional "supervised" alignment approaches, we trained our network on a masking problem, independent from the alignment or clustering problem. Our method is very versatile and has shown good performances in 1) designing RNAs sequences, 2) clustering sequences, and 3) aligning multiple sequences only using the simplest Needleman and Wunsch's algorithm. Not only can this approach be readily extended to RNA tridimensional structures, but it can also be applied to proteins. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Although tremendous progress has been made in understanding the mechanisms leading to cancer, those governing metastases are still poorly understood. E-cadherin (Ecad) is a cell-cell adhesion molecule essential for tissue homeostasis, and its loss often correlates with the dissemination of human cancers. However, whether and how the loss of Ecad triggers the full metastatic program is largely unknown. Here, we show that the loss of Ecad promotes melanoma lung metastases in females. The loss of Ecad, after the induction of estrogen receptor a; (ERa) expression, activates gastrin-releasing peptide receptor (GRPR) expression. GRPR promotes cellular processes essential for metastasis formation through Gaq and YAP1 signaling and its pharmacological inhibition reduces metastasis in vivo. This study reveals an Ecad-ER-GRPR metastatic sex dimorphism axis in melanoma that is conserved in human breast cancer and provides proof of concept that the G-coupled receptor GRPR is a therapeutic target for metastasis. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

ABSTRACT By utilizing the Human Phenotype Ontology (HPO), recent approaches to prioritizing disease-causing genes for patients become popular. However, these approaches do not comprehensively use information about phenotypes of diseases and patients. We present a new method called Phen2Disease that calculates similarity scores between two phenotype sets of patients and diseases by which to prioritize diseases and genes. Specifically, we calculate three scores of information content-based similarities using the phenotypes, and their combination as the respective benchmarks, and integrate them as a final score. Comprehensive experiments were conducted on six real data cohorts with 2051 cases and two simulated data cohorts with 1000 cases. Compared with the three state-of-the-art methods, if we only use phenotype information and HPO knowledge base, Phen2Disease outperformed all of them, particularly in cohorts with the less average numbers of HPO terms. We have found that patients with higher information content scores had more specific information so their predictions would be more accurate. In addition, Phen2Disease has high interpretability with ranked diseases and patient HPO terms provided. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Chloroplast DNA is methylated in the kelp Saccharina japonica, in contrast to most plants. Its function is yet largely unexplored. We detected methylation in the chloroplast DNA of the congener Saccharina latissima, a non - model macroalgal species of high ecological (wild populations) and economical (wild and cultured populations) importance in the North Atlantic. To the functional relevance of chloroplast DNA methylation, we compared for the first time methylation patterns between wild and cultured kelp from different climatic regions (High-Arctic (79 {degrees}N) and temperate (53 {degrees}N), laboratory samples at 5 {degrees}C, 10 {degrees}C and 15 {degrees}C). Our results suggest genome -wide differences in methylated sites, and methylation level, between the climatic regions. At gene level, our data found functions related to photosynthesis to be the predominant affected case only for differential methylation between origins, but not between growth conditions. Here, sample origin led to significant differences between cultivated and wild samples due to differential methylation of genes related to DNA replication in the Spitsbergen samples. Both findings indicate that origin and cultivation strongly affected the chloroplast methylome, but differently. Similar methylomes for samples from the same origin -- independent from whether they grow in the wild or in the lab -- suggest that origin- specific methylation marks on the chloroplast genome are inherited. However, the capacity for rapid adaptation (to cultivation conditions) could be shown for Saccharina latissima during this study. Given that DNA - methylation affects gene expression, our study suggests that lab - cultivation alters epigenetically determined kelp chloroplast characteristics at least to the same degree as ecotypic differentiation does. | Make paid

New | 4 December 2022 | Biorxiv link | Write review

Motivation: While many pipelines have been developed for calling genotypes using RNA-sequencing data, they all have adapted DNA genotype callers that do not model biases specific to RNA-sequencing such as reference panel bias or allele specific expression. Results: Here, we present BBmix, a Bayesian Beta-Binomial mixture model that first learns the expected distribution of read counts for each genotype, and then deploys those learned parameters to call genotypes probabilistically. We benchmarked our model on a wide variety of datasets and showed that our method generally performed better than competitors, mainly due to an increase of up to 1.4% in the accuracy of heterozygous calls. Moreover, BBmix can be easily incorporated into standard pipelines for calling genotypes. We further show that parameters are generally transferable within datasets, such that a single learning run of less than one hour is sufficient to call genotypes in a large number of samples. Availability: We implemented BBmix as an R package that is available for free under a GPL-2 licence at https://gitlab.com/evigorito/bbmix and accompanying pipeline at https://gitlab.com/evigorito/bbmix_pipeline. | Make paid