bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya
Authors: Greenland-Bews Caitlin , Shah Sonal , Achieng Morine , Badoum Emilie S. , Bah Yaya , Barsosio Hellen C. , Brazal-Monzó Helena , Canizales Jennifer , Drabko Anna , Fraser Alice J , Hannan Luke , Jarju Sheikh , Kaboré Jean-Moise , Kujabi Mariama A. , Lesosky Maia , Manneh Jarra , Marlais Tegwen , Matthewman Julian , Nebié Issa , Onyango Eric , Ouedraogo Alphonse , Otieno Kephas , Serme Samuel S. , Sirima Sodiomon , Soulama Ben , Tangara Brian , Tiono Alfred , Wu William , Sesay Abdul Karim , Soulama Issiaka , Kariuki Simon , Drakeley Chris , ter Kuile Feiko O , Adams Emily R , Allen David J , Edwards Thomas 
Published: April 2024

AbstractThe rapid emergence and global dissemination of SARS-CoV-2 highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole genome sequencing (WGS) mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low-middle income countries (LMICs) throughout the SARS-CoV-2 pandemic. Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt curve (HRM) assays that target key variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2 positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) on the day of enrolment in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analysed using our optimised HRM assays and compared to Next Generation Sequencing (NGS) on Oxford Nanopore MinION . With NGS as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta and 93.75%/100% and 100%/99.38% for Omicron. The assays described here provide a lower-cost approach (<$1 per sample) to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya. These assays are readily adaptable and can focus on local epidemiological surveillance questions or be updated quickly to accommodate the emergence of a novel variant or adapt to novel and emerging pathogens.
Identifying risk factors for Lassa fever infection in Sierra Leone, 2019-2021
Authors: Sama Daniel Juma , Haider Najmul , Guitian Javier , Osman Abdinasir Yusuf , Ntoumi Francine , Zumla Alimuddin , Kock Richard , Ansumana Rashid 
Published: April 2024

AbstractBackgroundLassa fever (LF) virus (LASV) is endemic in Sierra Leone and poses a significant public health threat to the region; however, no risk factors for LASV infection have been reported in Sierra Leone. The objective of this study was to identify the risk factors for LASV infection in an endemic community in Sierra Leone.MethodsWe conducted a case-control study by enrolling 37 laboratory-confirmed LF cases identified through the national LF surveillance system in Sierra Leone, and 140 controls resided within a one-kilometre radius of the case household. We performed conditional multiple logistic regression analysis to identify the risk factors for LASV infection.ResultsOf the 37 cases enrolled, 23 died (62% case fatality rate). Cases were younger than controls (19.5 years vs 28.9 years, p<0.05) and more frequently female (64.8% vs. 52.8%). Compared to the controls, LF cases had contact with rodents (rats or mice) in their households more frequently in the preceding three weeks (83.8% vs.47.8%). Households with a cat reported a lower presence of rodents (73% vs 38%, p<0.01) and contributed to a lower rate of LF (48.6% vs 55.7%) although not statistically significant (p=0.56). The presence of rodents in the households (Matched Adjusted Odds Ratio [mAOR]: 11.1), and younger age (mAOR: 0.99) were independently associated with LASV infection.ConclusionRodent access to households is likely a key risk factor for LASV infection in rural Sierra Leone and potentially in other countries within the West African region. Controlling rodent access to households might help reduce household-level LASV infection in Sierra Leone.
Micronutrient deficiencies and the double burden of malnutrition in Vietnamese female adolescents: a national cross-sectional study in 2020
Authors: Tan Xiaomian , Tan Pui Yee , Som Somphos Vicheth , Nguyen Son Duy , Tran Do Thanh , Tran Nga Thuy , Tran Van Khanh , Moore J. Bernadette , Gong Yun Yun 
Published: April 2024

ABSTRACTBackgroundVietnam is facing a double burden of malnutrition, with increasing prevalence of overweight coexisting with undernutrition (stunting or thinness) and micronutrient deficiencies (MNDs). Although malnutrition during female adolescence leads to poor health outcomes with potential intergenerational effects on offspring, no studies have comprehensively investigated MNDs and nutritional status among contemporary Vietnamese female adolescents.MethodsData from 10-to 18-year-old female participants (n=1,471) in the nationally-representative Vietnam General Nutrition Survey 2020 were analysed. Blood nutritional biomarkers, anthropometric measurements, and socio-demographic data were collected and the associations between nutrition status and MNDs were analysed; with anaemia, iron deficiency (ID), iron deficiency anaemia, low serum zinc, low serum retinol, and any MNDs as specified outcomes.FindingsPrevalence of overweight, stunting, and thinness was 27·2%, 14·3%, and 6·9%, respectively. Low serum zinc was common (39·8%), as was ID (9·8%). Bivariate analyses showed that older age (16-18 years old), ethnic minority, lower wealth index, and inflammation were associated with MNDs. In adjusted logistic regressions, stunting was associated with increased odds ratio (AOR) and [95% confidence intervals] of low serum retinol (8·92 [2·26, 35·15], p<0·01), as was thinness (12·25 [3·47, 43·33], p<0·01). Stunting was also associated with increased odds of having any MNDs (1·88 [1·13, 3·12], p<0·05).InterpretationMore female adolescents were overweight than undernourished in Vietnam in 2020. However, undernutrition, low serum zinc, and ID remain prevalent. Food systems approaches should be considered to stem the stark increase in the double burden of malnutrition in young people living in Vietnam.FundingUK BBSRC BB/T008989/1.
Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response
Authors: Tong Xiaoyu , Zhao Kanhao , Fonzo Gregory A. , Xie Hua , Carlisle Nancy B. , Keller Corey J. , Oathes Desmond J. , Sheline Yvette , Nemeroff Charles B. , Trivedi Madhukar , Etkin Amit , Zhang Yu 
Published: April 2024

AbstractMajor depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2= 0.31; placebo: R2= 0.22). Remarkably, the sertraline response biomarker is further tested on an independent escitalopram-medicated cohort of MDD patients, validating its generalizability (p = 0.01) and suggesting an overlap of psychopharmacological mechanisms across selective serotonin reuptake inhibitors. Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutivenetwork constellationswith generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel and reliable insights into the intricate neuropsychopharmacology of antidepressant treatment, paving the way for advances in precision medicine and development of more targeted antidepressant therapeutics.Trial RegistrationEstablishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094
On the parameterization of mathematical models of infectious disease transmission structured by age at the start of the epidemic spread
Authors: Sarratea Santiago , Fabricius Gabriel 
Published: April 2024

AbstractEstimation of transmission and contact rate parameters among individuals in different age groups is a key point in the mathematical modeling of infectious disease transmission. Several approaches exist for this task but, given the complexity of the problem, the obtained values are always approximate estimations that hold in particular conditions. Our goal is to contribute to this task in the event of an emerging disease. We propose a methodology to estimate the contact rate parameters from the fraction of the incidence reported in each age group at the beginning of the epidemic spread. Working with an age-structured SIR model, we obtain an equation that relates the contact parameters to various epidemiological quantities that could be accessible through different sources. We apply the method to obtain information about the contact structure by age during the COVID-19 epidemic spread in Greater Buenos Aires (Argentina) in 2020. As we have the fractions of reported incidence by age but only rough estimations of other quantities involved in the method, we define several epidemiological scenarios based on various hypotheses. Using the different sets of contact parameters obtained, we evaluate control strategies and analyze the dependence of the results on our assumptions. The proposed method could be useful to obtain a fast first insight of a new emergent disease at the beginning of epidemic spread using the accessible information.
The recurrence of illness (ROI) index is a key factor in major depression that indicates increasing immune-linked neurotoxicity and vulnerability to suicidal behaviors
Authors: Maes Michael , Jirakran Ketsupar , Vasupanrajit Asara , Niu Mengqi , Zhou Bo , St. Stoyanov Drozdstoj , Tunvirachaisakul Chavit 
Published: April 2024

AbstractBackgroundThe first author of this paper introduced new precision nomothetic models for a major depressive episode (MDD) which incorporate quantitative scores that measure recurrence of illness (ROI).ObjectiveTo explore the connections between ROI and biomarkers related to an activated immune network, immune-linked neurotoxicity (INT), and a combined INT and atherogenicity index (METAMMUNE).MethodsThe study involved 67 healthy controls and 66 outpatient MDD (OMDD) participants. We utilized a Multiplex method to measure 48 cytokines, and developed INT and METAMMUNE composite scores. The measurements included triglycerides, free cholesterol, LDL and HDL-cholesterol, apolipoprotein (Apo)A1 and ApoB.ResultsA ROI index was successfully created by extracting a validated principal component, from the number of physician-rated depressive episodes, the frequency of lifetime suicidal ideation and attempts. Adverse childhood experiences accounted for 20-22% of the variance in ROI. The latter was significantly associated with INT and METAMMUNE indices, neuroticism, lifetime and current suicidal behaviors, and the phenome (p<0.001). Our analysis revealed that a significant portion (55.1%) of the variance in the OMDD phenome, which includes current suicidal behaviors, anxiety, and depression, can be accounted for by the regression on INT, ROI, and emotional neglect and abuse. A validated latent construct was successfully extracted from the three ROI components, INT and METAMMUNE indices.ConclusionsROI and associated immune-metabolic biomarkers are indicators of a shared underlying concept, specifically a ROI-neuroimmune-metabolic pathway phenotype. ROI is a crucial indicator of the rising immune-metabolic abnormalities and heightened susceptibility to suicidal tendencies and recurrence of illness.
Exploring the causal effect of placental physiology in susceptibility to mental and addictive disorders: a Mendelian randomization study
Authors: Jácome-Ferrer Pablo , Costas Javier 
Published: April 2024

AbstractBackgroundEpidemiological studies have linked low birth weight to psychiatric disorders, including substance use disorders. Genomic analyses suggest a role of placental physiology on psychiatric risk. We investigated whether this association is causally related to impaired trophoblast function.MethodsWe conducted a two-sample summary-data Mendelian randomization study using as instrumental variables genetic variants strongly associated with birth weight, whose effect is exerted through the fetal genome, and are located near genes with differential expression in trophoblasts. Eight psychiatric and substance use disorders with >10,000 samples were included as outcomes. The inverse variance weighted method was used as the main analysis and several sensitivity analyses were performed for those significant results.ResultsThe inverse variance weighted estimate, based on 14 instrumental variables, revealed an association, after correction for multiple tests, between birth weight and broadly-defined depression (beta=-0.165, 95% CI=-0.282 to -0.047, P=0.0059). Sensitivity analyses revealed absence of heterogeneity in the effect of instrumental variables, confirmed by leave-one-out analysis, MR_Egger intercept and MR_PRESSO. The effect was consistent using robust methods. Reverse causality was not detected. The effect was specifically linked to genetic variants near genes involved in trophoblast physiology instead of genes with fetal effect on birth weight or involved in placenta development.ConclusionImpaired trophoblast functioning, probably leading to reduced fetal brain oxygen and nutrient supply, is causally related to broadly-defined depression. Considering the therapeutic potential of some agents to treat fetal growth restriction, further research on the effect of trophoblast physiology on mental disorders may have future implications in prevention.
Predicting involuntary admission following inpatient psychiatric treatment using machine learning trained on electronic health record data
Authors: Perfalk Erik , Damgaard Jakob Grøhn , Bernstorff Martin , Hansen Lasse , Danielsen Andreas Aalkjær , Østergaard Søren Dinesen 
Published: April 2024

AbstractBackgroundInvoluntary admissions to psychiatric hospitals are on the rise. If patients at elevated risk of involuntary admission could be identified, prevention may be possible.ObjectivesTo develop and validate a prediction model for involuntary admission of patients receiving care within a psychiatric service system using machine learning trained on routine clinical data from electronic health records (EHRs).MethodsEHR data from all adult patients who had been in contact with the Psychiatric Services of the Central Denmark Region between 2013 and 2021 were retrieved. We derived 694 patient predictors (covering e.g., diagnoses, medication, and coercive measures) and 1,134 predictors from free text using term frequency - inverse document frequency and sentence transformers. At every voluntary inpatient discharge (prediction time), without an involuntary admission in the two years prior, we predicted involuntary admission 180 days ahead. XGBoost and Elastic Net regularized logistic regression models were trained on 85% of the dataset. The best performing model was tested on the remaining 15% of the data.ResultsThe model was trained on 50,634 voluntary inpatient discharges among 17,968 unique patients. The cohort comprised 1,672 voluntary inpatient discharges followed by an involuntary admission. The XGBoost model performed best in the training phase and obtained an area under the receiver operating curve of 0.84 in the test phase.ConclusionA machine learning model using routine clinical EHR data can accurately predict involuntary admission. If implemented as a clinical decision support tool, this model may guide interventions aimed at reducing the risk of involuntary admission.
The effect of Alzheimer’s disease and its progression on pyramidal cell gain and connectivity
Authors: Lanskey Juliette H , Jafarian Amirhossein , Karadag Melek , Kocagoncu Ece , Williams Rebecca , Yadav Pranay , Quinn Andrew J , Pitt Jemma , Thayanandan Tony , Lowe Stephen , Perkinton Michael , Timmers Maarten , Raymont Vanessa , Singh Krish D , Woolrich Mark , Nobre Anna C , Henson Richard N , Rowe James B ,   the NTAD study group
Published: April 2024

AbstractAlzheimer’s disease affects our cognitive neurophysiology by loss of neurones, synapses and neurotransmitters. An improved mechanistic understanding of the human disease will facilitate new treatments. To this end, biophysically-informed dynamic causal models can support inferences around laminar and cell-specific disease effects from human non-invasive imaging. Based on pre-clinical models and effects of cholinesterase inhibitors, we hypothesised that Alzheimer’s disease would affect the modulation of superficial pyramidal cell gain and extrinsic connectivity between pyramidal cells of different regions in hierarchical cognitive networks. Magnetoencephalography (MEG) was recorded during an auditory mismatch negativity task from healthy adults (n=14) and people with symptomatic Alzheimer’s disease or mild cognitive impairment (n=45, all amyloid-biomarker positive) at baseline and after 16 months. Fourteen people from the symptomatic group had repeat magnetoencephalography at two weeks to assess test-retest reliability. Sensor-level data were analysed using t-tests of the mismatch negativity amplitude from 140ms to 160ms. The repetition effect was assessed with repeated-measures analysis of covariance, using the average evoked response in the mismatch negativity time window as the repeated measure. An absolute, intraclass correlation model of the test-retest data assessed mismatch negativity amplitude reliability. We then fitted dynamic causal models to the evoked responses over 500ms. Second-level parametric empirical Bayes across participants examined the effect of (1) group, patients vs controls, and (2) progression, baseline vs follow-up, on the model parameters reflecting pyramidal cell gain modulation and extrinsic connectivity. There was a significant effect of both disease and progression on the mismatch negativity amplitude (patients vs controls, T=-1.80, p=0.04; patient baseline vs follow-up, T=-2.72, p=.005), which had excellent reliability (ICC=0.95, p<.001). Parametric empirical Bayes revealed strong evidence (posterior probability>95%) that Alzheimer’s disease reduced extrinsic connectivity and superficial pyramidal cell gain modulation, which was reduced further at follow up assessment. The mechanistic modelling confirmed the hypothesis that reduced superficial pyramidal cell gain modulation and extrinsic connectivity can explain the observed neurophysiological effect of Alzheimer’s disease. This approach to non-invasive magnetoencephalography data may be used for experimental medicine studies of candidate treatments, and bridge clinical to preclinical models of drug efficacy.
Pilot trial of perampanel on peritumoral hyperexcitability and clinical outcomes in newly diagnosed high-grade glioma
Authors: Tobochnik Steven , Regan Michael S. , Dorotan Maria K. C. , Reich Dustine , Lapinskas Emily , Hossain Md Amin , Stopka Sylwia , Santagata Sandro , Murphy Melissa M. , Arnaout Omar , Bi Wenya Linda , Chiocca E. Antonio , Golby Alexandra J. , Mooney Michael A. , Smith Timothy R. , Ligon Keith L. , Wen Patrick Y. , Agar Nathalie Y. R. , Lee Jong Woo 
Published: April 2024

ABSTRACTBackgroundGlutamatergic neuron-glioma synaptogenesis and peritumoral hyperexcitability promote glioma growth in a positive feedback loop. The objective of this study was to evaluate the feasibility and estimated effect sizes of the AMPA-R antagonist, perampanel, on intraoperative electrophysiologic hyperexcitability and clinical outcomes.MethodsAn open-label trial was performed comparing perampanel to standard of care (SOC) in patients undergoing resection of newly-diagnosed radiologic high-grade glioma. Perampanel was administered as a pre-operative loading dose followed by maintenance therapy until progressive disease or up to 12-months. SOC treatment involved levetiracetam for 7-days or as clinically indicated. The primary outcome of hyperexcitability was defined by intra-operative electrocorticography high frequency oscillation (HFO) rates. Seizure-freedom and overall survival (OS) were estimated by the Kaplan-Meier method. Tissue concentrations of perampanel, levetiracetam, and metabolites were measured by mass spectrometry.ResultsHFO rates were similar between perampanel-treated and SOC cohorts. The trial was terminated early after interim analysis for futility, and outcomes assessed in 11 patients (7 perampanel-treated, 4 SOC). Over a median 281 days of post-enrollment follow-up, 27% of patients had seizures, including 14% treated with perampanel and 50% treated with SOC. OS in perampanel-treated patients was similar to a glioblastoma reference cohort (p=0.81). Glutamate concentrations in surface biopsies were positively correlated with HFO rates in adjacent electrode contacts and were not significantly associated with treatment assignment or drug concentrations.ConclusionsA peri-operative loading regimen of perampanel was safe and well-tolerated, with similar peritumoral hyperexcitability as in levetiracetam-treated patients. Maintenance anti-glutamatergic therapy was not observed to impact survival outcomes.