bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metformin use is associated with lower risks of dementia, anxiety and depression: The Hong Kong Diabetes Study
Authors: Hui Jeremy Man Ho , Zhou Jiandong , Lee Teddy Tai Loy , Hui Kyle , Chou Oscar Hou In , Lee Yan Hiu Athena , Lee Sharen , Wong Wing Tak , Wai Abraham Ka Chung , Chang Carlin , Jeevaratnam Kamalan , Liu Tong , Tse Gary 
Published: January 2024

AbstractAimsTo compare the effects of metformin and sulphonylurea on new-onset dementia, anxiety disorder and depression, and all-cause mortality in patients with type 2 diabetes mellitus.MethodsThis is a retrospective population-based cohort study of type 2 diabetes mellitus patients exposed to either metformin or sulphonylureas attending the Hospital Authority of Hong Kong between 1stand 31stDecember 2009. The follow-up was until 31stDecember 2019. The primary outcome was a new diagnosis of dementia, and anxiety disorder/depression. Propensity score matching (1:1 ratio) between metformin and sulphonylurea users based on demographics, CAIDE score, CHA-DS-VASc score, Charlson comorbidity index, past comorbidities, medications, and total cholesterol was performed. Cox regression was used to identify significant risk predictors. Cause-specific and subdistribution hazard models were also used.ResultsA total of 89,711 patients (46% men, mean age: 67 years old [SD: 12]) followed-up for 1,579 days (SD: 650). Metformin users were at a lower risk of dementia (before: 0.78 [0.72, 0.84], P-value < 0.0001; after: 0.88 [0.80, 0.97], P-value = 0.0074), anxiety disorder and depression (before: 0.77 [0.69, 0.86], P-value < 0.0001; after: 0.71 [0.61, 0.82], P-value < 0.0001), and all-cause mortality (before: 0.69 [0.68, 0.71], P-value < 0.0001; after: 0.83 [0.80, 0.85], P-value < 0.0001). These associations remained significant in the competing risk models.ConclusionMetformin use is associated with lower risks of dementia, new-onset anxiety disorder and depression, and all-cause mortality, compared to sulphonylurea use. The protective effects of metformin and possible use in drug repurposing for indications beyond diabetes warrant further investigation.HighlightsPatients with type 2 diabetes have an increased risk of cognitive, anxiety or depressive problemsMetformin use was associated with lower risks of new diagnosis of dementia, anxiety disorder and depressionPatients who developed dementia had lower levels of albumin, alanine transaminase and HbA1c compared to those who developed anxiety disorder and depressionAppropriate glycemic control and maintenance of normal liver function are important in slowing cognitive decline in type 2 diabetes mellitus
Designing multimedia patient education materials for adolescent idiopathic scoliosis: a protocol for a feasibility randomized controlled trial of patient education videos
Authors: Oirschot Garett Van , Doherty Cailbhe 
Published: January 2024

AbstractTriple-masked three-armed feasibility parallel randomized controlled trial Multimedia patient education materials are increasingly used in healthcare. While much research focuses on optimising their scientific content, research is equally needed to optimise design and implementation. This study aims to determine the feasibility of a study examining how the implementation of scientific advice on design affects patient outcomes. Participants aged 10-18 with radiographically confirmed adolescent idiopathic scoliosis will be recruited from community settings in Ireland and randomized into usual care or receiving multimedia educational videos with or without evidence-informed design principles. Participants will be masked in the two video intervention arms, as will the therapist sending the educational videos. Outcomes will include the number of participants recruited and randomized, the number analysed post-intervention and at week eight, and the outcomes for baseline, post-intervention, and week 8. Adverse events will also be reported. This feasibility randomized controlled trial will offer insight into the feasibility of implementing advice from the literature in designing a trial of multimedia patient education materials for a population with adolescent idiopathic scoliosis.Trial is registered onClinicalTrials.govasNCT06090344.
Predicting dimensions of depression from smartphone data
Authors: Holstein Vincent L. , Akre Samir , Leenings Ramona , Chung Yoonho , Hahn Tim , Baker Justin T. 
Published: January 2024

Depressive disorders are highly prevalent but demand nuanced personalized treatment that traditional approaches in psychiatry cannot address. This gap has prompted a surge of interest in leveraging digital technology, particularly smartphones, for remote monitoring to enhance outpatient care. This study utilizes the BRIGHTEN dataset to construct interpretable prediction models for overall depression severity, measured by PHQ-9, and various depression dimensions using a factor modelling approach.Our factor model unveils a three-factor solution encompassing mood, somatic, and concentration/psychomotor-related factors. Machine learning models effectively predict both the PHQ-9 scores and individual factors, with feature importance methods analyses underscoring the influence of the PHQ-2 scale and communication-related features. These findings are corroborated by models trained on data subsets.Through nested multi-level models, we identify between-subject effects for the PHQ-2 and select communication-related features, along with within-subject effects for these features. In summary, this study underscores the robust predictive capacity of ecological momentary assessments and highlights features of potential relevance for future investigations, such as communication-related features. We advocate for future studies to assess the cost-effectiveness and intervention potential of these models.
Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification
Authors: Donker Tjibbe , Papathanassopoulos Alexis , Ghosh Hiren , Kociurzynski Raisa , Felder Marius , Grundmann Hajo , Reuter Sandra 
Published: January 2024

AbstractThe emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a new method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a-priori assigning isolates to lineages from phylogenies, based solely on the abundance of Single Nucleotide Polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, and thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a-priori assigning isolates to lineages.
How executive control and emotional reactivity influence coping strategies in psychiatric patients during the COVID-19 pandemic
Authors: Kist Josina D. , Schlüter Linda , Duyser Fleur , Mulders Peter C.R. , Vrijsen Janna N. , Collard Rose M. , van Eijndhoven Philip F.P. , Tendolkar Indira 
Published: January 2024

AbstractBackgroundDuring times of environmental challenges, adaptive coping strategies are essential to maintain mental health. Coping relies on executive control, which is often impaired in individuals with psychiatric disorders. Furthermore, emotional reactivity may interfere with executive control. Studying the association between cognitive skills and adaptive coping strategies, as well as the potential impact of emotional reactivity, could inform how we can provide mental support during large-scale adversity. In this study we examined coping strategies in a thoroughly phenotyped psychiatric cohort, the MIND-Set cohort, during the early COVID-19 pandemic stage.MethodsWe studied 1) the association between coping and both subjective and objective executive control before the pandemic, and three different coping strategies used during the pandemic, 2) the mediating role of emotional reactivity, indexed by amygdala reactivity, and 3) the moderating role of the presence of a psychiatric diagnosis in these associations. After finding no specific impact of patient or control status in this association, we decided to post-hoc study the transdiagnostic impact of depression severity in these associations.Resultsshowed 1) only a significant association between subjective executive control and a self-reported positive reappraisal style and corona-related reappraisal. However, after controlling for depression severity, this association was no longer significant. Additionally, objective executive control was only directly associated with right amygdala reactivity, while amygdala reactivity in neither of the hemispheres mediated the association between executive control and any of the coping styles. Furthermore, the type of diagnosis did not moderate the association between executive control and coping.ConclusionOur findings firstly underline the difference between self-reported and performance based executive control. While both deficits in subjective and performance based EC may play a role in the persistence of psychiatric symptomatology, this finding emphasizes how depressive symptoms or negative affect can impact reappraisal ability. As this ability is fundamental to staying resilient, treatments focused on reducing negative affect and thereby training reappraisal are pivotal in the maintenance of mental health in the entire population during environmental challenges.Competing Interest StatementThe authors have declared no competing interest.
Understanding diagnostic delay for endometriosis: a scoping review
Authors: Fryer Jodie , Mason-Jones Amanda J. , Woodward Amie 
Published: January 2024

AbstractIntroductionDiagnostic delay for endometriosis is a well-established phenomenon. Despite this, little is known about where in the health care system these delays occur or why they occur. Our review is the first attempt to synthesise and analyse this evidence.MethodsA systematic scoping review with a pre-specified protocol was used to incorporate the global mixed methods literature on diagnostic delay for endometriosis. Four databases (PubMed, MEDLINE, EMBASE, PsychINFO) were searched from inception to September 2023 with a search strategy designed specifically for each.ResultsThe search yielded 367 studies, 22 of which met the inclusion criteria. A third of studies has been published since 2020 and 65% were from high income countries. Six were qualitative and 16 were quantitative studies. The average age of onset of endometriosis was 14 years for adolescents and 20 for adults. On average, the diagnostic delay reported for endometriosis across the included studies was 6.6 years (range 1.5 to 11.3 years) but this masked the very wide differences reported between countries such as a 0.5-year delay in Brazil to a 27-year delay in the UK.DiscussionHealth system barriers included access to private healthcare for those with limited finance, physical access for those using public health systems and a general lack of knowledge amongst patients and health care professionals. Women often reported feeling unheard by health professionals. Considering the impact on individuals and the health system, addressing diagnostic delay for endometriosis must remain a priority for researchers, health care providers and policy makers.What is already known on this topicEndometriosis is currently difficult to diagnose. This results in delays in diagnosis which negatively impacts those suffering and increases the severity of pain and extent of the disease with increased costs to health systems.What this study addsThe scoping review methodology included studies using a range of methods. The longest average delay occurs in secondary care. Those seeking public health care experienced longer average delay in diagnosis compared to those seeking private health care. Improved clinical guidelines may reduce diagnostic delay.How this study might affect research, practice or policyThis is the first known review to explore diagnostic delay for endometriosis and provides an overview of the current literature. Clearer definitions of diagnostic delay for endometriosis are needed to aid in comparisons across countries. Improving education, tracking outcomes through medical records and developing non-invasive diagnostic tools will be crucial to improve women’s health.
Evaluating topography of mutational signatures with SigProfilerTopography
Authors: Otlu Burçak , Alexandrov Ludmil B. 
Published: January 2024

ABSTRACTThe mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome’s architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.
Deficiency in ribosome biogenesis causes streptomycin resistance and impairs motility inSalmonella
Authors: Lyu Zhihui , Ling Yunyi , van Hoof Ambro , Ling Jiqiang 
Published: January 2024

AbstractThe ribosome is the central hub for protein synthesis and the target of many antibiotics. Whereas the majority of ribosome-targeting antibiotics inhibit protein synthesis and are bacteriostatic, aminoglycosides promote protein mistranslation and are bactericidal. Understanding the resistance mechanisms of bacteria against aminoglycosides is not only vital for improving the efficacy of this critically important group of antibiotics but also crucial for studying the molecular basis of translational fidelity. In this work, we analyzedSalmonellamutants evolved in the presence of the aminoglycoside streptomycin (Str) and identified a novel generimPto be involved in Str resistance. RimP is a ribosome assembly factor critical for the maturation of the 30S small subunit that binds Str. Deficiency in RimP increases resistance against Str and facilitates the development of even higher resistance. DeletingrimPdecreases mistranslation and cellular uptake of Str, and further impairs flagellar motility. Our work thus highlights a previously unknown mechanism of aminoglycoside resistance via defective ribosome assembly.
GLDADec: marker-gene guided LDA modelling for bulk gene expression deconvolution
Authors: Azuma Iori , Mizuno Tadahaya , Kusuhara Hiroyuki 
Published: January 2024

AbstractInferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce GLDADec (Guided LDA Deconvolution), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to TCGA tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package athttps://github.com/mizuno-group/GLDADec.
Quantifying the advantage of multimodal data fusion for survival prediction in cancer patients
Authors: Nikolaou Nikolaos , Salazar Domingo , RaviPrakash Harish , Gonçalves Miguel , Mulla Rob , Burlutskiy Nikolay , Markuzon Natasha , Jacob Etai 
Published: January 2024

AbstractThe last decade has seen an unprecedented advance in technologies at the level of high-throughput molecular assays and image capturing and analysis, as well as clinical phenotyping and digitization of patient data. For decades, genotyping (identification of genomic alterations), the casual anchor in biological processes, has been an essential component in interrogating disease progression and a guiding step in clinical decision making. Indeed, survival rates in patients tested with next-generation sequencing have been found to be significantly higher in those who received a genome-guided therapy than in those who did not. Nevertheless, DNA is only a small part of the complex pathophysiology of cancer development and progression. To assess a more complete picture, researchers have been using data taken from multiple modalities, such as transcripts, proteins, metabolites, and epigenetic factors, that are routinely captured for many patients. Multimodal machine learning offers the potential to leverage information across different bioinformatics modalities to improve predictions of patient outcome. Identifying a multiomics data fusion strategy that clearly demonstrates an improved performance over unimodal approaches is challenging, primarily due to increased dimensionality and other factors, such as small sample sizes and the sparsity and heterogeneity of data. Here we present a flexible pipeline for systematically exploring and comparing multiple multimodal fusion strategies. Using multiple independent data sets from The Cancer Genome Atlas, we developed a late fusion strategy that consistently outperformed unimodal models, clearly demonstrating the advantage of a multimodal fusion model.
Characterization and genomic analysis of the Lyme disease spirochete bacteriophage ϕBB-1
Authors: Faith Dominick R. , Kinnersley Margie , Brooks Diane M. , Drecktrah Dan , Hall Laura S. , Luo Eric , Santiago-Frangos Andrew , Wachter Jenny , Samuels D. Scott , Secor Patrick R. 
Published: January 2024

AbstractLyme disease is a tick-borne infection caused by the spirocheteBorrelia(Borreliella)burgdorferi.Borreliaspecies have highly fragmented genomes composed of a linear chromosome and a constellation of linear and circular plasmids some of which are required throughout the enzootic cycle. Included in this plasmid repertoire by almost all Lyme disease spirochetes are the 32-kb circular plasmid cp32 prophages that are capable of lytic replication to produce infectious virions called ϕBB-1. While theB. burgdorferigenome contains evidence of horizontal transfer, the mechanisms of gene transfer between strains remain unclear. While we know that ϕBB-1 transduces cp32 and shuttle vector DNA duringin vitrocultivation, the extent of ϕBB-1 DNA transfer is not clear. Herein, we use proteomics and long-read sequencing to further characterize ϕBB-1 virions. Our studies identified the cp32pacregion and revealed that ϕBB-1 packages linear cp32s via a headful mechanism with preferentially packaging of plasmids containing the cp32pacregion. Additionally, we find ϕBB-1 packages fragments of the linear chromosome and full-length plasmids including lp54, cp26, and others. Furthermore, sequencing of ϕBB-1 packaged DNA allowed us to resolve the covalently closed hairpin telomeres for the linearB. burgdorferichromosome and most linear plasmids in strain CA-11.2A. Collectively, our results shed light on the biology of the ubiquitous ϕBB-1 phage and further implicates ϕBB-1 in the generalized transduction of diverse genes and the maintenance of genetic diversity in Lyme disease spirochetes.
Carbapenemase-producing Enterobacterales colonisation status does not lead to more frequent admissions: a linked patient study
Authors: Lydeamore Michael J , Donker Tjibbe , Wu David , Gorrie Claire , Turner Annabelle , Easton Marion , Hennessey Daneeta , Geard Nic , Howden Ben P. , Cooper Ben S. , Wilson Andrew , Peleg Anton Y , Stewardson Andrew J 
Published: January 2024

AbstractBackgroundHospitals in any given region can be considered as part of a network, where facilities are connected to one another – and hospital pathogens potentially spread – through the movement of patients between them. We sought to describe the hospital admission patterns of patients known to be colonised with carbapenemase-producing Enterobacterales (CPE), and compare them with CPE-negative patients.MethodsWe performed a linkage study in Victoria, Australia, including datasets with notifiable diseases (CPE notifications) and hospital admissions (admission dates and diagnostic codes) for the period 2011 to 2020. Where the CPE notification date occurred during a hospital admission for the same patient, we identified this as the ‘index admission’. We determined the number of distinct health services each patient was admitted to, and time to first admission to a different health service. We compared CPE-positive patients with four cohorts of CPE-negative patients, sampled based on different matching criteria.ResultsOf 528 unique patients who had CPE detected during a hospital admission, 222 (42%) were subsequently admitted to a different health service during the study period. Among these patients, CPE diagnosis tended to occur during admission to a metropolitan public hospital (86%, 190/222), whereas there was a greater number of metropolitan private (23%, 52/222) and regional public (18%, 39/222) hospitals for the subsequent admission. Median time to next admission was 4 days (IQR, 0-75 days). Admission patterns for CPE-positive patients was similar to the cohort of CPE-negative patients matched on index admission, time period, and age-adjusted Charlson comorbidity index.ConclusionsMovement of CPE-positive patients between health services is not a rare event. While the most common movement is from one public metropolitan health service to another, there is also a trend for movement from metropolitan public hospitals into private and regional hospitals. CPE-positivity does not appear to impact on hospital admission frequency and timing. These findings support the potential utility of a centralised notification and outbreak management system for CPE positive patients.