bluuebunny/crossref_metadata_2025_split huggingface dataset:
Collateral sensitivity and cross resistance in six species of bacteria exposed to six classes of antibiotics
Authors: Wang Xinyu , Nong Luyuan , Schaar Gioia , Jonker Martijs , de leeuw Wim , ter Kuile Benno H. 
Published: December 2024

AbstractDe novoresistance can be developed in bacteria because of exposure to sublethal concentrations of antibiotics. Once the strain has become resistant to an initial antibiotic, this can cause cross-resistance or collateral sensitivity to a second antimicrobial. Specific collateral sensitivity is rarely conserved across species because the mechanisms triggered in different microorganisms to resist antibiotics are often different. In this study, we explored which collateral sensitivity or cross resistance networks are present in six species of bacteria with inducedde novo-resistance. These six species were induced to become resistant to amoxicillin/cefepime, enrofloxacin, kanamycin, tetracycline, erythromycin and chloramphenicol(1). After that, the collateral sensitivity and the cross-resistance networks were evaluated by measuring increase or decrease of MIC of thirteen antibiotics that are often used in the clinic. Collateral sensitivity for kanamycin occurred in five species of strains resistant to chloramphenicol and tetracycline and for β-lactam in strains of five species resistant to kanamycin. Further genetic analysis clarified thatfusAconsistently mutated in five species of bacteria madede novoresistant against kanamycin, suggesting thatfusAoperates in parallel with the other mechanisms related to antimicrobial resistance Based on considerations of resistance, a treatment protocol starting with chloramphenicol/tetracycline, followed by kanamycin and ending with amoxicillin may eliminate bacteria that have developed resistance against the initial treatment.
Multi-Omics Mapping of Gut Microbiota’s Role in Progesterone Metabolism
Authors: Brandon-Mong Guo-Jie , Chen Mei-Jou , Gicana Ronnie G , Wang Hurng-Yi , Li Chi-Ying , Wu Tien-Yu , Chou Chia-Hung , Tu Yi-An , Chang Yu-Yuan , Lai Yi-Li , Li Po-Ting , Tseng Yu-Lin , Hsiao Tsun-Hsien , Chiang Yin-Ru 
Published: December 2024

AbstractBackgroundThe female reproductive hormone, progesterone, is crucial in regulating the menstrual cycle and maintaining pregnancy. Despite known correlations between gut microbiota, sex hormones, and host phenotypes, the metabolic fates of progesterone in the human gut remain unclear.ResultsHere, an integrated multi-omics approach was employed to investigate gut microbiota-mediated progesterone metabolism. Fresh fecal samples were collected from infertile women with progesterone treatment (n = 14). Progesterone (1 mM) was amended into fecal cultures to enrich progesterone-metabolizing gut microbes, and the key players were identified through culturomics-based metagenomics analysis. Microbial functions were predicted by tracking temporal changes in metabolite profiles and microbial abundances. The prevalence of progesterone metabolism genes among gut microbiota was explored through functional genomics analysis. Pregnanolone was identified as the primary microbial metabolite of gut progesterone. Members of Enterobacteriaceae and Veillonellaceae were identified as crucial pregnanolone producers; progesterone metabolism genes were abundant in these bacterial families. Moreover, these bacterial families showed significant abundance differences among healthy women (n = 19) and women with miscarriages (n = 41).ConclusionsThis study provides potent therapeutic targets for improving progesterone bioavailability and demonstrates stereoselective production of neurosteroids using characterized bacterial strains and their corresponding metabolic pathways.HighlightsThe microorganisms in the human gut can convert progesterone into several neurologically active steroids.Progesterone is primarily converted into pregnanolone by the gut microbiota in women with infertility.Members of the bacterial families Enterobacteriaceae and Veillonellaceae play key roles in the pregnanolone production.Genes involved in pregnanolone production are prevalent in the genomes of Enterobacteriaceae and Veillonellaceae.The abundances of Enterobacteriaceae and Veillonellaceae differ significantly between women who experienced healthy pregnancies and those who experienced miscarriages.
Utilising Nanopore direct RNA sequencing of blood from patients with sepsis for discovery of co- and post-transcriptional disease biomarkers
Authors: He Jingni , Ganesamoorthy Devika , Chang Jessie J-Y , Zhang Josh , Trevor Sharon L , Gibbons Kristen S , McPherson Stephen J , Kling Jessica C. , Schlapbach Luregn J , Blumenthal Antje ,   the RAPIDS Study Group, Coin Lachlan JM 
Published: December 2024

ABSTRACTBackgroundRNA sequencing of whole blood has been increasingly employed to find transcriptomic signatures of disease states. These studies traditionally utilize short-read sequencing of cDNA, missing important aspects of RNA expression such as differential isoform abundance and poly(A) tail length variation.MethodsWe used Oxford Nanopore Technologies long-read sequencing to sequence native mRNA extracted from whole blood from 12 patients with suspected bacterial and viral sepsis, and compared with results from matching Illumina short-read cDNA sequencing data. Additionally, we explored poly(A) tail length variation, novel transcript identification and differential transcript usage.ResultsThe correlation of gene count data between Illumina cDNA and Nanopore RNA-sequencing strongly depended on the choice of analysis pipeline;NanoCountfor Nanopore andKallistofor Illumina data yielded the highest mean Pearson’s correlation of 0.93 at gene level and 0.74 at transcript isoform level. We identified 18 genes significantly differentially polyadenylated and 4 genes with significant differential transcript usage between bacterial and viral infection. Gene ontology gene set enrichment analysis of poly(A) tail length revealed enrichment of long tails in signal transduction and short tails in oxidoreductase molecular functions. Additionally, we detected 594 non-artifactual novel transcript isoforms, including 9 novel isoforms for Immunoglobulin lambda like polypeptide 5 (IGLL5).ConclusionsNanopore RNA- and Illumina cDNA-gene counts are strongly correlated, indicating that both platforms are suitable for discovery and validation of gene count biomarkers. Nanopore direct RNA-seq provides additional advantages by uncovering additional post- and co-transcriptional biomarkers, such as poly(A) tail length variation and transcript isoform usage.
Social isolation and mortality risk in late-stage older Japanese: A longitudinal study of community-dwelling residents from 2020 to 2024
Authors: Okawa Yukari 
Published: December 2024

AbstractSocial isolation presents a high risk for mortality. Evidence is limited, however, for older adults, especially in Japan, a country whose life expectancy at birth is the longest in the world. This retrospective longitudinal study included homebound Japanese citizens aged ≥75 years who underwent voluntary checkups conducted by Zentsuji City, Kagawa Prefecture, Japan from 2000 to 2024. The relationship between social isolation and mortality was assessed using the Cox proportional hazards model. Social isolation was defined as having no regular contact with family or friends, and survival information was confirmed by the city’s database as of 1 July, 2024. Of the 3,366 participants (male: 42.4%), 3,024 (male: 42.6%) remained in the final cohort. At study entry, socially isolated participants tended to be older and have fewer exercising habits, worse self-rated health status, worse life satisfaction, and no family members in the same household with them. The mean follow-up time was 2.47 years, during which 9.1% of the participants died. Mortality risk was 2.37 times higher (95% confidence interval [CI]: 1.61–3.48) for socially isolated individuals than for those who were not socially isolated, after controlling for covariates such as physical status, self-rated health, lifestyle, life satisfaction, and sharing a household with family members. The results showed a consistent trend, even after excluding participants with short follow-up periods. Consequently, when evaluating mortality risks for older adults, it is important to consider whether they are socially isolated.
Opinions of the UK general public in using artificial intelligence and “opt-out” models of consent in medical research
Authors: Heseltine-Carp William , Thurston Mark , Allen Michael , Browning Daniel , Courtman Megan , Kasabe Aishwarya , Ifeachor Emmanuel , Mullin Stephen 
Published: December 2024

AbstractBackgroundDue to its complexity, Artificial Intelligence often requires large, confidential clinical datasets. 20-30% of the general public remain sceptical of Artificial Intelligence in healthcare due to concerns of data security, patient-practitioner communication, and commercialisation of data/models to third parties. A better understanding of public concerns of Artificial Intelligence is therefore needed, especially in the context of stroke research.AimsWe aimed to evaluate the opinion of patients and the public in acquiring large clinical datasets using an “opt-out” consent model, in order to train an AI-based tool to predict the future risk of stroke from routine healthcare data. This was in the context of our project ABSTRACT, a UK Medical Research Council study which aims to use AI to predict future risk of stroke from routine hospital data.MethodsOpinions were gathered from those with lived experience of stroke/TIA, caregivers, and the general public through an online survey, semi-structured focus groups, and 1:1 interviews. Participants were asked about their perceived importance of the project, the acceptability of handling deidentified routine healthcare data without explicit consent, and the acceptability of acquiring these data via an opt-out model of consent model by members within and outside of the routine clinical care team.ResultsOf the 83 that participated, 34% of which had a history of stroke/TIA. Nearly all (99%) supported the project’s aims in using AI to predict stroke risk, acquiring data via an opt-out consent model, and the handling of pseudonymized data by members within and outside of the routine clinical care team.ConclusionBoth the general public and those with lived experience of stroke/TIA are generally supportive of using large, de-identified medical datasets to train AI models for stroke risk prediction under an opt-out consent model, provided the research is transparent, ethically sound, and beneficial to public health.
Addressing inequalities in vaccination coverage among children aged 12 to 23 months in ten Sub-Saharan African countries: Insights from DHS and MIS Data (2017-2022)
Authors: Xavier Sancho Pedro , Mahoche Manuel , Rondó Patrícia Helen , da Silva Ageo Mário , Flores-Ortiz Renzo , Victor Audêncio 
Published: December 2024

AbstractIntroductionVaccination is one of the most effective public health interventions for preventing and controlling infectious diseases, particularly in low- and middle-income countries. This study analyzed disparities in vaccination coverage among children aged 12 to 23 months in ten Sub-Saharan African (SSA) countries.MethodsA cross-sectional study using data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) collected between 2017 and 2022 in ten Sub-Saharan African countries. The primary outcome was full vaccination coverage. Logistic regression models were applied to identify factors associated with the outcome.ResultsFull vaccination coverage rates varied significantly across countries, with Gambia presenting the highest rate (86.4%) and Guinea the lowest (21.2%). Factors associated with full vaccination coverage included place of residence, maternal education and age, economic status, place of delivery, possession of a health card, and attendance at prenatal care services.ConclusionThe study highlighted significant disparities in vaccination coverage among children in Sub-Saharan Africa, influenced by sociodemographic and economic factors. Investing in maternal education, improving economic conditions, and strengthening healthcare infrastructure are essential measures to reduce these inequalities.
Establishing a relationship between iron-based blood measures and structural brain changes using neural networks in UK Biobank
Authors: Sammet Joshua , Alhasani Kholod , Chung Ejin , Cheung Jedidiah , Liu Qiang , Patel Raihaan , Suri Sana , Nevado-Holgado Alejo , Winchester Laura 
Published: December 2024

ABSTRACTBackgroundDisturbance of iron homeostasis in both the brain and blood is linked to cognitive impairment and neurodegenerative diseases. Investigation of the associations between changes in blood measurements and the accompanying structural changes in the brain, represented by susceptibility-weighted imaging, would generate evidence of a shared physiopathology between modalities, however linear approaches using derived imaging measures have not detected this relationship.MethodBrain SWI of 4436 participants from UK Biobank at the first imaging visit were used to build a convolutional neural network (CNN) predicting the haemoglobin level. Haemoglobin concentration was grouped in three sets percentiles creating prediction classes. Attention maps were extracted from the CNN using Integrated Gradients to identify which brain regions allowed the CNN to correctly classify haemoglobin.ResultsThe model predicted haemoglobin level >99% accuracy for three classes and >85% accuracy for ten classes. Using attention maps to understand the model’s decision process, we identified regions of interest for the 3-class model. Four out of the nine regions were located in the cerebral cortex. Changes in the right thalamus and the white matter tracts between the temporal gyrus, putamen, hippocampus, and thalamus regions were associated to high haemoglobin class.ConclusionOur model accurately predicted haemoglobin levels from SWI suggesting an association between the iron measures. Furthermore, it was possible to identify brain areas used by the CNN for decision-making. Using this integrated model of iron modalities will give a more comprehensive view of iron homeostasis and the potential associations with neurodegenerative diseases such as dementia.
APOE Genotype and Statin Response: Evidence from the UK Biobank Baseline Assessment and Linked Mortality Data
Authors: Asiimwe Innocent G. , Jorgensen Andrea L. , Pirmohamed Munir ,   Multimorbidity Mechanism and Therapeutic Research Collaborative
Published: December 2024

AbstractIntroductionAPOEgenotype may influence response to statin therapy. We examined the relationship betweenAPOEgenotype, statin use, lipid biomarkers and mortality using data from the UK Biobank.MethodsUK Biobank baseline assessment data and linked mortality records (389,843–452,189 participants) were analysed. Linear regression and Cox proportional hazards models assessed associations betweenAPOEgenotype, statin use, and lipid biomarkers (Apolipoprotein A, Apolipoprotein B, HDL cholesterol [HDLC], LDL cholesterol [LDLC], Lipoprotein A, Total Cholesterol, Triglycerides) as well as mortality, adjusting for clinical and genetic covariates.ResultsSignificant interactions betweenAPOEgenotype and statin use were observed for most lipid biomarkers at the Bonferroni-adjusted threshold (P< 0.007), including Apolipoprotein A (P= 0.0065), Apolipoprotein B (P< 2.00e-16), LDLC, Total Cholesterol, and Triglycerides (allP< 2.00e-16), and HDLC (P= 0.0001). Lipoprotein A was not significant (P= 0.104). Population-level trends did not always translate to individual outcomes; for example, statin-treatedε4ε4carriers showed significant LDLC reductions but their LDLC levels remained higher than those of untreatedε2ε2individuals.APOEgenotype was significantly associated with all-cause death (trendP< 2.00e-16) and cardiovascular-related death (P= 1.55e-10). Theε4ε4genotype had the highest risk, with respective hazard ratios of 1.51 (95% CI: 1.41– 1.62) and 1.54 (1.33–1.77). However, theAPOE:statin use interaction was not significant.ConclusionTheAPOEgenotype influences lipid biomarker levels, with statin use associated with favourable changes across all genotypes. The magnitude of these changes depends on both the APOE genotype and baseline lipid levels.
Sleep architecture correlates with neurological and neurobehavioral short- and mid-term outcome in a sample of very preterm infants
Authors: Uccella Sara , Marazzotta Valentina , Preiti Deborah , Battaglini Marcella , Burlando Gaia , Roascio Monica , Rossi Andrea , Arnulfo Gabriele , Ramenghi Luca Antonio , Nobili Lino 
Published: December 2024

AbstractNewborns spend most of their time sleeping. This activity fosters neurodevelopment. Prematurity, defined by birth occurring prior the 37thweek of gestation, disrupts normal brainin-uteroprogramming, with long-lasting consequences that carry a high social burden. Sleep alterations may contribute to these sequelae. In this pilot study we aimed to describe the 24-hours distribution of sleep states among very preterm infants (VPI), and to correlate it with neurobehavioral assessment up to 6 months of corrected age (CA). Secondly, we aimed to assess if the presence of a brain lesion detected at MRI could affect sleep duration, architecture, and quality.Ten VPI were assessed at 32 weeks PMA with a 24-hours video-polysomnography and received a neurobehavioral examination at the time of the recording, at term equivalent age (TEA), and at 6 months CA. Analysis of sleep stages distribution and transitions, and power spectra were conducted.Total sleep time and amount of quiet sleep positively correlated with neurological, and neurobehavioral assessment at 32 weeks PMA, at TEA, and at 6 months CA, while Sleep Onset Active Sleep (SOAS) had a negative association. Infants carrying brain lesions showed lower Total Sleep time accompanied by a higher prevalence of AS+SOAS and showed a gradient for higher power of posterior slow activity (slow δ and δ) during SOAS in the left hemisphere posterior regions.Understanding sleep dynamics among preterm infants might provide future therapeutic/management strategies, which need to encompass sleep care.
Prioritizing Parkinson’s disease risk genes in genome-wide association loci
Authors: Lange Lara M. , Cerquera-Cleves Catalina , Schipper Marijn , Panagiotaropoulou Georgia , Braun Alice , Kraft Julia , Awasthi Swapnil , Bell Nathaniel , Posthuma Danielle , Ripke Stephan , Blauwendraat Cornelis , Heilbron Karl 
Published: December 2024

AbstractRecent advancements in Parkinson’s disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging. Our aim was to prioritize genes underlying PD GWAS signals.The polygenic priority score (PoPS) is a similarity-based gene prioritization method that integrates genome-wide information from MAGMA gene-level association tests and more than 57,000 gene-level features, including gene expression, biological pathways, and protein-protein interactions. We applied PoPS to data from the largest published PD GWAS in East Asian- and European-ancestries.We identified 120 independent associations withP< 5×10−8and prioritized 46 PD genes across these loci based on their PoPS scores, distance to the GWAS signal, and presence of non-synonymous variants in the credible set. Alongside well-established PD genes (e.g., TMEM175andVPS13C), some of which are targeted in ongoing clinical trials (i.e.,SNCA,LRRK2, andGBA1), we prioritized genes with a plausible mechanistic link to PD pathogenesis (e.g., RIT2, BAG3, andSCARB2). Many of these genes hold potential for drug repurposing or novel therapeutic developments for PD (i.e., FYN, DYRK1A, NOD2, CTSB, SV2C,andITPKB). Additionally, we prioritized potentially druggable genes that are relatively unexplored in PD (XPO1, PIK3CA, EP300, MAP4K4, CAMK2D, NCOR1,andWDR43).We prioritized a high-confidence list of genes with strong links to PD pathogenesis that may represent our next-best candidates for disease-modifying therapeutics. We hope our findings stimulate further investigations and preclinical work to facilitate PD drug development programs.
Basal forebrain volume and concurrent hallucinations and mild cognitive impairment in Parkinson’s disease
Authors: Adamo Sabrina M. , Mutreja Vaishali , Statucka Marta , Kaya Batu , Schmitz Taylor W. , Ruocco Anthony C. , Cohn Melanie 
Published: December 2024

ABSTRACTBackgroundVisual hallucinations (VH) and mild cognitive impairment (MCI) often co-occur in Parkinson’s Disease (PD). Each symptom in isolation is associated with cholinergic basal forebrain (BF) atrophy. However, it is unclear whether BF integrity relates to one symptom preferentially or to their co-occurrence, and whether this relationship is specific to the nucleus basalis of Meynert (Ch4 & Ch4p) or extends to other BF nuclei (Ch1-2 & Ch3).ObjectivesTo bridge the literature on MCI, VH, and the BF by examining associations between total and subregional BF volumes with VH, MCI, and concurrent symptomology.MethodsWe used clinical and structural MRI data in PD patients (n=296) with or without VH (n=75; n=221), and with intact cognition or MCI (n=115; n=181), evaluated prior to deep brain stimulation. One-way ANCOVAs were run for each region (total BF, Ch1-2, Ch3, Ch4, and Ch4p). The independent variable was either cognitive status, VH status, or a combined factor with three levels (Intact Cognition-noVH, MCI-noVH, and MCI-VH), and covariates included intracranial volume, age, levodopa-equivalent dose, and dopamine agonist therapy (yes/no).ResultsWe demonstrate main effects of MCI on BF, Ch4, and Ch1-2volumes, but not of VH. Subgroup analyses show reduced BF and Ch4 volumes in patients with both symptoms (d=0.44) relative to patients with neither.ConclusionsWe show dissociations within the cholinergic system in PD, where reduced volume of different BF nuclei relates to MCI only versus the combination of symptoms. We provide support for the “cholinergic phenotype”.