bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early detection of patients with narcotic use disorder using a modified MEDD score based on the analysis of real-world prescription patterns
Authors: Kim Yi-Jun , Lee Kye Hwa , Kang Hye-Ryun , Cho Yoon Sook , Kang Dong Yoon , Kim Ju Han , Kim Yon Su 
Published: April 2022

ABSTRACTBackgroundAddiction to prescription narcotics is a global issue, and detection of individuals with a narcotic use disorder (NUD) at an early stage can help prevent narcotics misuse and abuse. We developed a novel index to detect early NUD based on a real-world prescription pattern analysis in a large hospital.MethodsWe analyzed narcotic prescriptions of 221 887 patients prescribed by 8737 doctors from July 2000 to June 2018. For the early detection of patients who could potentially progress to developing NUD after a long history of narcotic prescription, a weighted morphine equivalent daily dose (wt-MEDD) score was developed based on the number of prescription dates on which the actual MEDD was higher than the intended MEDD. Performance of the wt-MEDD scoring system in detecting patients diagnosed with NUD by doctors was compared with that of other NUD high risk indexes such as the MEDD scoring system, number of days on prescribed narcotics, the frequency/duration of prescription, narcotics prescription across multiple doctors, and the number of early refills of narcotics.ResultsA wt-MEDD score cut-off value of 10.5 could detect all outliers, as well as patients diagnosed with NUD with 100% sensitivity and 99.6% specificity. The wt-MEDD score showed the highest sensitivity and specificity in identifying NUD among all indexes. Further, combining the wt-MEDD score with other NUD high risk indexes improved the prediction performance.ConclusionWe developed a novel index to distinguish patients with vulnerable use patterns of narcotics. The wt-MEDD score showed excellent performance in detecting early NUD.
COVID-19 in the Mexican Social Security Institute (IMSS) population. Prevalent symptoms
Authors: Juárez-Flores Arturo , Ascencio-Montiel Iván J. , Gutiérrez Juan Pablo , Bertozzi Stefano M. , Borja-Aburto Víctor H. , Olaiz Gustavo 
Published: April 2022

AbstractBackgroundThe disease caused by the new coronavirus SARS-CoV-2, COVID-19, which appeared in early 2020 in Mexico, was the second leading cause of mortality in the country that year and has generated an increasing demand for medical care. By January 2022, 4.13 million cases and 300 thousand direct deaths have been documented.ObjectiveTo describe the main symptoms of people with a positive test for SARS-CoV-2 treated at the Mexican Institute of Social Security (IMSS) by sex, age group, and IMSS delegation.Methods4.5 million epidemiological reports were registered in the IMSS epidemiological surveillance system between February 2020 and November 2021. They were analyzed, reporting for those with either a positive PCR or rapid test, the prevalence of symptoms by sex, groups of age, and IMSS delegation.ResultsAmong the population treated at the IMSS, six symptoms are observed as the most prevalent in general, as well as by sex, age groups, and state of residence: cefalea, fever, cough, myalgia, odynophagia, and arthralgias.ConclusionsA better understanding of the clinical picture with which confirmed cases of COVID-19 present contributes to reporting timely diagnoses, considering the particularities by sex, age, and place of residence.
High prevalence of burnout syndrome among medical and nonmedical residents during the COVID-19 pandemic
Authors: Pinho Rebeca da Nóbrega Lucena , Costa Thais Ferreira , Silva Nayane Miranda , Barros Areal Adriana Ferreira , Salles André de Matos , Oliveira Andrea Pedrosa Ribeiro Alves , Esselin Rassi Carlos Henrique Reis , Gomes Ciro Martins , Silva Dayde Lane Mendonça da , Oliveira Fernando Araújo Rodrigues de , Jochims Isadora , Vaz Filho Ivan Henrique Ranulfo , Oliveira Lucas Alves de Brito , Rosal Marta Alves , Lima Marta Pinheiro , Soares Mayra Veloso Ayrimoraes , Kurisky Patrícia Shu , Pertele Viviane Cristina Uliana , Gomides Ana Paula Monteiro , Mota Licia Maria Henrique da , Albuquerque Cleandro Pires de , Simaan Cezar Kozak , Amado Veronica Moreira 
Published: April 2022

AbstractBackgroundSince the beginning of the COVID-19 pandemic, health professionals have been working under extreme conditions, increasing the risk of physical and mental illness. We evaluated the prevalence of burnout and its associated factors among postgraduate student residents in health professions during the global health crisis.MethodsHealthcare residents were recruited from all across Brazil between July and September 2020 through digital forms containing instruments for assessing burnout (Oldenburg Burnout Inventory (OLBI)), resilience (brief resilient coping scale (BRCS)) and anxiety, stress and depression (depression, anxiety and stress scale (DASS-21) and Patient Health Questionnaire (PHQ-9)). Additionally, the relationships between burnout and chronic diseases, autonomy and educational adequacy in the residency programme, personal protective equipment (PPE), workload and care for patients with COVID-19 were evaluated. The chi-square test, Student’s t test, Pearson’s correlation test and logistic regression were performed.ResultsA total of 1,313 participants were included: mean (standard deviation) age, 27.8 (4.4) years; female gender, 78.1%; white race, 59.3%; and physicians, 51.3%. The overall prevalence of burnout was 33.4%. The odds (odds ratio [95% confidence interval]) of burnout were higher in the presence of pre-existing diseases (1.76 [1.26– 2.47]) and weekly work > 60 h (1.36 [1.03–1.79]) and were lower in the presence of high resilience (0.84 [0.81–0.88]), autonomy (0.87 [0.81–0.93]), and educational structure (0.77 [0.73–0.82]), adequate availability of PPE (0.72 [0.63–0.83]) and non-white race (0.63 [0.47–0.83]). Burnout was correlated with anxiety (r = 0.47; p < 0.05), stress (r: 0.58; p < 0.05) and depression (r: 0.65; p < 0.05).ConclusionsWe observed a high prevalence of burnout among residents during the COVID-19 pandemic. Individual characteristics and conditions related to the work environment were associated with a higher or lower occurrence of the syndrome.
Triangulating evidence in health sciences with Annotated Semantic Queries
Authors: Liu Yi , Gaunt Tom R 
Published: April 2022

ABSTRACTIntegrating information from data sources representing different study designs has the potential to strengthen evidence in population health research. However, this concept of evidence “triangulation” presents a number of challenges for systematically identifying and integrating relevant information. We present ASQ (Annotated Semantic Queries), a natural language query interface to the integrated biomedical entities and epidemiological evidence in EpiGraphDB, which enables users to extract “claims” from a piece of unstructured text, and then investigate the evidence that could either support, contradict the claims, or offer additional information to the query. This approach has the potential to support the rapid review of pre-prints, grant applications, conference abstracts and articles submitted for peer review. ASQ implements strategies to harmonize biomedical entities in different taxonomies and evidence from different sources, to facilitate evidence triangulation and interpretation. ASQ is openly available athttps://asq.epigraphdb.org.
A Text Message Intervention to Support Latino Dementia Family Caregivers (CuidaTEXT): Feasibility study
Authors: Perales-Puchalt Jaime , Ramírez-Mantilla Mariana , Fracachán-Cabrera Mónica , Vidoni Eric D. , Ellerbeck Edward F. , Ramírez A. Susana , Watts Amber , Williams Kristine , Burns Jeffrey 
Published: April 2022

AbstractObjectivesTo test the feasibility, acceptability, and preliminary efficacy of CuidaTEXT: a tailored text message intervention to support Latino dementia family caregivers.MethodsCuidaTEXT is a six-month, bilingual, and bidirectional intervention tailored to caregiver needs (e.g., education, problem-solving, resources). We enrolled 24 Latino caregivers in a one-arm trial, and assessed feasibility, acceptability, and preliminary efficacy within six months.ResultsRecruitment took 61 days and enrollment took 20. None of the participants unsubscribed from CuidaTEXT, and 83.3% completed the follow up survey. Most participants (85.7%) reported reading most text messages thoroughly. Participants reported high levels of satisfaction with the intervention (3.6 on a scale from 1 to 4). CuidaTEXT helpfulness was high (3.5-3.8 on a 1 to 4 scale). Compared to baseline, at six months caregiver behavioral symptom distress (0–60) decreased from 19.8 to 12.0, and depression (0-30) from 8.8 to 5.4 (p<0.05).ConclusionsCuidaTEXT demonstrated high levels of feasibility, acceptability, and preliminary efficacy among Latino caregivers.Clinical implicationsCuidaTEXT’s feasibility and potential for widespread implementation holds promise in supporting Latino caregivers of people with dementia.
Convolutional networks for supervised mining of molecular patterns within cellular context
Authors: de Teresa Irene , Goetz Sara K. , Mattausch Alexander , Stojanovska Frosina , Zimmerli Christian E. , Toro-Nahuelpan Mauricio , Cheng Dorothy W.C. , Tollervey Fergus , Pape Constantin , Beck Martin , Kreshuk Anna , Mahamid Julia , Zaugg Judith 
Published: April 2022

AbstractCryo-electron tomograms capture a wealth of structural information on the molecular constituents of cells and tissues. We present DeePiCt (Deep Picker in Context), an open-source deep-learning framework for supervised structure segmentation and macromolecular complex localization in cellular cryo-electron tomography. To train and benchmark DeePiCt on experimental data, we comprehensively annotated 20 tomograms ofSchizosaccharomyces pombefor ribosomes, fatty acid synthases, membranes, nuclear pore complexes, organelles and cytosol. By comparing our method to state-of-the-art approaches on this dataset, we show its unique ability to identify low-abundance and low-density complexes. We use DeePiCt to study compositionally-distinct subpopulations of cellular ribosomes, with emphasis on their contextual association with mitochondria and the endoplasmic reticulum. Finally, by applying pre-trained networks to a HeLa cell dataset, we demonstrate that DeePiCt achieves high-quality predictions in unseen datasets from different biological species in a matter of minutes. The comprehensively annotated experimental data and pre-trained networks are provided for immediate exploitation by the community.
Origin of Protein Quake: Energy Waves Conducted by a Precise Mechanical Machine
Authors: Li Huiyu , Wu Shanshan , Ma Ao 
Published: April 2022

AbstractA long-standing challenge in protein biophysics is to understand protein quake in myoglobin—the structural dynamics responsible for redistributing the excess heme energy after photolysis. Despite extensive efforts, the molecular mechanism of this process remains elusive. Using the energy flow theory, we uncovered a fundamental new phenomenon: the heme energy is redistributed by energy waves with a ubiquitous fundamental frequency and two overtones. Energy waves emanate from the heme into the myoglobin backbone via a conduit of five consecutive dihedrals of the proximal histidine, then travel quickly along the backbone to reach sidechains across the protein. This mechanism is far more effective than the diffusion-based mechanism from previous studies because waves are systematic while diffusion is random. To propagate energy waves, coordinates must cooperate, resulting in collective modes that are singular vectors of the generalized work functional. These modes show task partitioning: a handful of high-energy modes generate large-scale breathing motion, which loosens up the protein matrix to enable hundreds of low-energy vibrational modes for energy transduction.
Interpreting the pervasive observation of U-shaped Site Frequency Spectra
Authors: Freund Fabian , Kerdoncuff Elise , Matuszewski Sebastian , Lapierre Marguerite , Hildebrandt Marcel , Jensen Jeffrey D. , Ferretti Luca , Lambert Amaury , Sackton Timothy B. , Achaz Guillaume 
Published: April 2022

AbstractThe standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.
Improving the fidelity of uridine analog incorporation during in vitro transcription
Authors: Chen Tien-Hao , Potapov Vladimir , Dai Nan , Ong Jennifer L. , Roy Bijoyita 
Published: April 2022

AbstractIn vitro transcribed synthetic messenger RNAs (mRNAs) represent a novel therapeutic modality and are currently being evaluated for a wide range of clinical indications. To overcome the inherent immunogenicity of the synthetic mRNAs, as well as to increase the therapeutic efficacy of the molecules, RNA sequence optimization is routinely performed and modified uridine analogs—such as pseudouridine (Ψ) and N1-methyl-pseudouridine (m1Ψ), are incorporated in the synthetic mRNA. To decipher the fidelity with which these modifications are incorporated during the in vitro transcription (IVT) process, here, we compared, the incorporation fidelity of uridine, Ψ, or m1Ψ in multiple RNA sequences with different single-subunit DNA-dependent RNA polymerases (ssRNAPs). By comparing the incorporation of each modified base to that of the unmodified equivalent, we demonstrate that m1Ψ is incorporated with higher fidelity than Ψ. Furthermore, the various ssRNAPs exhibit different error rates; however, the spectrum of mutations observed between the RNAPs is similar. We also show that the array of nucleotide misincorporation is not dependent on the template DNA sequence context and that the distribution of these misincorporated nucleotides is not localized to any specific region along the length of the RNA. Based on our findings, we introduce a novel protocol to improve uridine analog incorporation—without affecting total RNA yield—during IVT. Our proof-of-concept experiments and protocol for higher-fidelity incorporation of uridine analogs during IVT provide guidelines when choosing ssRNAPs for the generation of modified uridine—containing mRNAs in vitro.
Reelin deficiency exacerbates cocaine-induced hyperlocomotion by enhancing neuronal activity in the dorsomedial striatum
Authors: de Guglielmo Giordano , Iemolo Attilio , Nur Aisha , Turner Andrew , Montilla-Perez Patricia , Telese Francesca 
Published: April 2022

AbstractThe Reln gene encodes for the extracellular glycoprotein Reelin, which regulates several brain functions from development to adulthood, including neuronal migration, dendritic growth and branching, and synapse formation and plasticity. Human studies have implicated Reelin signaling in several neurodevelopmental and psychiatric disorders. Mouse studies using the heterozygous Reeler (HR) mice have shown that reduced levels of Reln expression are associated with deficits in learning and memory and increased disinhibition. Although these traits are relevant to substance use disorders, the role of Reelin in cellular and behavioral responses to addictive drugs remains largely unknown. Here, we compared HR mice to wild-type (WT) littermate controls to investigate the contribution of Reelin signaling to the hyper-locomotor and rewarding effects of cocaine. After a single cocaine injection, HR mice showed enhanced cocaine-induced locomotor activity compared to WT controls. After repeated injections of cocaine, Reelin deficiency also led to increased cocaine-induced locomotor sensitization, which persisted after withdrawal. In contrast, Reelin deficiency did not affect the rewarding effects of cocaine measured in the conditioned place preference assay. The elevated cocaine-induced hyper-locomotion in HR mice resulted in increased Fos expression in the dorsal medial striatum (DMS) compared to WT. Lastly, we found that Reln was highly co-expressed with the Drd1 gene, which encodes for the dopamine receptor D1, in the DMS.These findings demonstrated that Reelin signaling contributes to the locomotory effects of cocaine and improved our understanding of the neurobiological mechanisms underlying the cellular and behavioral effects of cocaine.
Benchmarking community-wide estimates of growth potential from metagenomes using codon usage statistics
Authors: Weissman JL , Peras Marie , Barnum Tyler P. , Fuhrman Jed A. 
Published: April 2022

AbstractTrait inference from mixed-species assemblages is a central problem in microbial ecology. Frequently, sequencing information from an environment is available, but phenotypic measurements from individual community members are not. With the increasing availability of molecular data for microbial communities, bioinformatic approaches that map metagenome to (meta)phenotype are needed. Recently, we developed a tool, gRodon, that enables the prediction of the maximum growth rate of an organism from genomic data on the basis of codon usage patterns. Our work and that of other groups suggests that such predictors can be applied to mixed-species communities in order to derive estimates of the average community-wide maximum growth rate. Here, we present an improved maximum growth rate predictor designed for metagenomes that corrects a persistent GC bias in the original gRodon model for metagenomic prediction. We benchmark this predictor with simulated metagenomic datasets to show that it has superior performance on mixed-species communities relative to earlier models. We go on to provide guidance on data pre-processing, and show that calling genes from assembled contigs rather than directly from reads dramatically improves performance. Finally, we apply our predictor to large-scale metagenomic datasets from marine and human microbiomes to illustrate how community-wide growth prediction can be a powerful approach for hypothesis-generation. Altogether, we provide an updated tool with clear guidelines for users about the uses and pitfalls of metagenomic prediction of the average community-wide maximal growth rate.
Tuned inhibitory firing rate and connection weights as emergent network properties
Authors: Lagzi Fereshteh , Fairhall Adrienne 
Published: April 2022

AbstractExcitatory cortical neurons show clear tuning to stimulus features, but the tuning properties of inhibitory neurons are ambiguous and have been the subject of a long debate. While inhibitory neurons have been considered to be largely untuned [1–4], recent studies show that some parvalbumin expressing (PV) neurons do show feature selectivity and participate in co-tuned subnetworks with pyramidal cells in which PV cells show high response similarity to the excitatory (E) neurons [5, 6]. Given shared input from layer 4 that drives feature tuning in excitatory subnetworks, we demonstrate that homeostatic regulation of postsynaptic firing rate governing the synaptic dynamics of the connections from PV to E cells, in combination with heterogeneity in the excitatory postsynaptic potentials (EPSP) that impinge on PV cells, results in the self-organization of PV subnetworks. We reconcile different experimental findings by showing that feature tuning of PV cells is an emerging network property that may be driven by synaptic heterogeneity, and can be inferred using population-level measures, while pairwise individual-level measures may fail to reveal inhibitory tuning. We show that such co-tuning can enhance network stability at the cost of response salience.
Seroprevalence, correlates and kinetics of SARS-CoV-2 Nucleocapsid IgG antibody in healthcare workers at a tertiary hospital: A prevaccine census study
Authors: Maina Daniel , Omuse Geoffrey , Ong’ete George , Mugaine Patrick , Sayed Shahin , Moloo Zahir , Shah Reena , Etyang Anthony , Adam Rodney 
Published: April 2022

AbstractBackgroundHealthcare workers are perceived to be a high-risk group for acquiring SAR-CoV-2 infection, and more so in countries where COVID-19 vaccination uptake is low. Serosurveillance may best determine the true extent of SARS-CoV-2 infection since most infected HCWs may be asymptomatic or present with only mild symptoms. Over time, determining the true extent of SARS-CoV-2 infection could inform hospital management and staff whether the preventive measures instituted are effective and valuable in developing targeted solutions.MethodsThis was a census survey study conducted at the Aga Khan University Hospital, Nairobi, between November 2020 and February 2021 before the implementation of the COVID-19 vaccination. The SARS-CoV-2 nucleocapsid IgG test was performed using a chemiluminescent assay.ResultsOne thousand six hundred thirty-one (1631) staff enrolled, totalling 60% of the workforce. The overall crude seroprevalence was 18.4% and the adjusted value (for assay sensitivity of 86%) was 21.4% (95% CI; 19.2-23.7). The HCW groups with higher prevalence included pharmacy (25.6%), outreach (24%), hospital-based nursing (22.2%) and catering staff (22.6%). Independent predictors of a positive IgG result included prior COVID-19 like symptoms, odds ratio (OR) 1.9 [95% confidence interval (CI) 1.3-2.9, p=0.002], and a prior positive SARS-CoV-2 PCR result OR 11.0 (CI: 7.2-18.0, p<0.001). Age, sex, comorbidities or working in a COVID-19 designated area were not associated with seropositivity. The odds of testing positive for IgG after a positive PCR test were lowest if the antibody test was performed more than 2 months later; OR 0.7 (CI: 0.48-0.95, p= 0.025).ConclusionsThe prevalence of anti-SARS-CoV-2 nucleocapsid IgG among HCWs was lower than in the general population. Staff working in clinical areas were not at increased risk when compared to staff working in non-clinical areas.
Longitudinal change in cognition in older adults in Uganda: a prospective population study
Authors: Prynn Josephine E , Davey Calum , Davis Daniel , Kuper Hannah , Mugisha Joseph , Seeley Janet 
Published: April 2022

AbstractIntroductionDementia is an important and growing issue in sub-Saharan Africa, but epidemiological data are lacking. Risk factors may differ from other regions due to high stroke incidence and HIV prevalence. Understanding the epidemiology of cognition in older adults in Africa is crucial for informing public health strategies to improve the lives of people with dementia and their carers.MethodsThe Wellbeing of Older People Study in Uganda is an open cohort of adults aged 50+ with and without HIV, established in 2009. Detailed socio-demographic and health data have been collected at four waves spanning 10 years, including cognitive assessment using internationally validated WHO-recommended tests: verbal recall, digit span, and verbal fluency. Mortality data was collected until the end of the fourth wave (2019). We examined associations of low baseline cognition scores and cognitive decline over time, care needs of people with lower cognition, and the relationship between cognition and mortality.ResultsData were collected on 811 participants. Older age, lower educational attainment, lower socio-economic position, and extremes of BMI were associated with lower cognition scores. Cognition declined faster at older ages, but rate of decline was not associated with cardiovascular disease or HIV. People with lower cognition required more assistance with Activities of Daily Living, but mortality rates were similar across the range of cognition.ConclusionsThe crucial next step will be investigating the determinants of low cognition scores and clinical dementia, to better understand the clinical relevance of these findings to inform public health planning in sub-Saharan Africa.