bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy, public health impact and optimal use of the Takeda dengue vaccine
Authors: Daniels Bethan Cracknell , Ferguson Neil , Dorigatti Ilaria 
Published: August 2024

AbstractDengue is the most common arboviral infection, causing substantial morbidity and mortality globally. The licensing of Qdenga, a second-generation vaccine developed by Takeda Pharmaceuticals, is therefore timely, but the potential public health impact of vaccination across transmission settings needs to be evaluated. To address this, we characterised Qdenga’s efficacy profile using mathematical models calibrated to published clinical trial data and estimated the public health impact of routine vaccine use. We find that efficacy depends on the infecting serotype, serological status, and age. We estimate that vaccination of children aged over six years in moderate to high dengue transmission settings (seroprevalence at 9 years of age > 60%) could reduce the burden of hospitalised dengue by 10-22% on average over ten years. We find some evidence of a risk of vaccine-induced disease enhancement in seronegative vaccine recipients for dengue serotypes 3 and 4, especially for children under six years of age. Because of this, the benefits of vaccination in lower transmission settings are more uncertain, and more data on the long-term efficacy of Qdenga against serotypes 3 and 4 are needed.
Systematic Review of Brain Mechanisms of Oral Multisensory Processing related to Oral Health
Authors: Lin Chia-Shu 
Published: August 2024

AbstractOral functions related to eating, including mastication, swallowing, and taste, are fundamentally a multisensory experience, that relies on the crossmodal interaction of touch, gustation, temperature, pain, and proprioception. While a majority of studies focus on the multisensory processing related to speech, the brain mechanisms of oral multisensory processing related to eating have remained unknown. The current systematic review will summarize the findings from neuroimaging studies (mainly functional magnetic resonance imaging) focusing on the interaction of multiple sensory stimuli in human participants. Neuroimaging studies of human adults on the interaction between multiple sensory stimuli related to oral functions and published in English were identified and extracted via three electronic databases and reviewed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Nine primary studies were eligible to be included in this review. Three studies investigated the interaction of intraoral (i.e., sensorimotor, taste, and noxious) stimuli. Five studies investigated the interaction between intraoral and extraoral (i.e., auditory, olfactory, and visual) stimuli). One study investigated the audio-visual interaction on dental fear. The studies showed great diversity in the experimental design of crossmodal interaction. In terms of the brain features related to the interaction, the somatosensory and motor areas were mostly reported in the studies. The studies imply the potential application between oral neuroscience and oral healthcare, such as prosthodontic treatment and food selection. Still, the findings should be carefully interpreted due to the diversity in crossmodal interaction and inconsistency of experimental design between the studies. The current systematic review revealed that there have not been consistent findings about the underlying brain mechanisms due to the diversity in the experimental design of crossmodal interaction.
The immune response to SARS-CoV-2 as a recall response susceptible to immune imprinting: a prospective cohort study
Authors: Alvarez-Sierra Daniel , Martínez-Gallo Mónica , Sánchez-Montalvá Adrián , Fernández-Sanmartín Marco , Colobran Roger , Espinosa-Pereiro Juan , Poyatos-Canton Elísabet , Zurera-Egea Coral , Sánchez-Pla Alex , Violan Concepción , Parra Rafael , Alzayat Hammad , Vivancos Ana , Morandeira-Rego Francisco , Urban-Vargas Blanca , Martínez-Cáceres Eva , Hernández-González Manuel , Bas-Minguet Jordi , Katsikis Peter D. , Teniente-Serra Aina , Pujol-Borrell Ricardo 
Published: August 2024

ABSTRACTBackgroundThe antibody response to SARS-CoV-2 does not follow the immunoglobulin isotype pattern expected in a primary response and is inconsistent with the current interpretation of COVID-19 immunopathology as the result of a primary infection. To better understand the immune response to SARS-CoV-2, it is essential to determine whether it is primary or secondary (or recall). The analysis of highly granular immunological variable trajectories of a homogeneous cohort of patients receiving standardised medical care should discern between primary and secondary responses.MethodsThis is a prospective cohort study of 191 SARS-CoV-2 infection cases and 44 healthy controls from the second wave of COVID-19 in the Barcelona area. The study stratified patients by severity and analysed the trajectories of SARS-CoV-2 antibodies and multiple immune variables for features associated with primary and recall immune responses.FindingsIsotype-specific antibody trajectories to SARS-CoV-2 proteins revealed a pattern of recall response in 94·2% of cases. In these cases, the detailed trajectories of plasmablasts, B cells, cTfh high-resolution subsets, and cytokines were consistent with a secondary response. The transcriptomic data indicated that this cohort is strictly comparable to contemporary cohorts.ConclusionsIn most cases, the immune response to SARS-CoV-2 is a recall response. This opens the possibility that most COVID-19 cases are subjected to immune imprinting by endemic coronavirus, which, in turn, can contribute to severity by interfering with the immune response to SARS-CoV-2 and by antibody-dependent enhancement. Considering the immune responses to SARS-CoV-2 secondary provides a better perspective to interpret COVID-19 pathology.FundingGrants COV20/00416, Cov20/00654, and COV20/00388 from Instituto de Salud Carlos III (ISCIII), Madrid, Spain, co-financed by the European Regional Development Fund (ERDF).
Transparency in the secondary use of health data: Assessing the status quo of guidance and best practices
Authors: R. van den Akker Olmo , Thibault Robert T. , Ioannidis John P. A. , Schorr Susanne G. , Strech Daniel 
Published: August 2024

AbstractWe evaluated what guidance exists in the literature to improve the transparency of studies that make secondary use of health data. To find relevant literature, we searched PubMed and Google Scholar and drafted a list of health organizations based on our personal expertise. We quantitatively and qualitatively coded different types of research transparency: registration, methods reporting, results reporting, data sharing, and code sharing. We found 54 documents that provide recommendations to improve the transparency of studies making secondary use of health data, mainly in relation to study registration (n = 27) and methods reporting (n = 39). Only three documents made recommendations on data sharing or code sharing. Recommendations for study registration and methods reporting mainly came in the form of structured documents like registration templates and reporting guidelines. Aside from the recommendations aimed directly at researchers, we found 31 recommendations aimed at the wider research community, typically on how to improve research infrastructure. Limitations or challenges of improving transparency were rarely mentioned, highlighting the need for more nuance in providing transparency guidance for studies that make secondary use of health data.
Benchmarking the Confidence of Large Language Models in Clinical Questions
Authors: Omar Mahmud , Agbareia Reem , Glicksberg Benjamin S , Nadkarni Girish N , Klang Eyal 
Published: August 2024

AbstractBackground and AimThe capabilities of large language models (LLMs) to self-assess their own confidence in answering questions in the biomedical realm remain underexplored. This study evaluates the confidence levels of 12 LLMs across five medical specialties to assess their ability to accurately judge their responses.MethodsWe used 1,965 multiple-choice questions assessing clinical knowledge from internal medicine, obstetrics and gynecology, psychiatry, pediatrics, and general surgery areas. Models were prompted to provide answers and to also provide their confidence for the correct answer (0–100). The confidence rates and the correlation between accuracy and confidence were analyzed.ResultsThere was an inverse correlation (r=-0.40, p=0.001) between confidence and accuracy, where worse performing models showed paradoxically higher confidence. For instance, a top performing model, GPT4o had a mean accuracy of 74% with a mean confidence of 63%, compared to a least performant model, Qwen-2-7B, which showed mean accuracy 46% but mean confidence 76%. The mean difference in confidence between correct and incorrect responses was low for all models, ranging from 0.6% to 5.4%, with GPT4o having the highest differentiation of 5.4%.ConclusionBetter performing LLMs show more aligned overall confidence levels. However, even the most accurate models still show minimal variation in confidence between right and wrong answers. This underscores an important limitation in current LLMs’ self-assessment mechanisms, highlighting the need for further research before integration into clinical settings.
The accuracy of large language models in labelling neurosurgical ‘case-control studies’ and risk of bias assessment: protocol for a study of interrater agreement with human reviewers
Authors: Igoli Joanne , Osunronbi Temidayo , Olukoya Olatomiwa , Daniel Jeremiah Oluwatomi Itodo , Alemenzohu Hillary , Kanu Alieu , Kihunyu Alex Mwangi , Okeleke Ebuka , Oyoyo Henry , Shekoni Oluwatobi , Jesuyajolu Damilola , Alalade Andrew F 
Published: August 2024

AbstractIntroductionAccurate identification of study designs and risk of bias (RoB) assessment is crucial for evidence synthesis in research. However, mislabelling of case-control studies (CCS) is prevalent, leading to a downgraded quality of evidence. Large Language Models (LLMs), a form of artificial intelligence, have shown impressive performance in various medical tasks. Still, their utility and application in categorising study designs and assessing RoB needs to be further explored. This study will evaluate the performance of four publicly available LLMs (ChatGPT-3.5, ChatGPT-4, Claude 3 Sonnet, Claude 3 Opus) in accurately identifying CCS designs from the neurosurgical literature. Secondly, we will assess the human-LLM interrater agreement for RoB assessment of true CCS.MethodsWe identified thirty-four top-ranking neurosurgical-focused journals and searched them on PubMed/MEDLINE for manuscripts reported as CCS in the title/abstract. Human reviewers will independently assess study designs and RoB using the Newcastle-Ottawa Scale. The methods sections/full-text articles will be provided to LLMs to determine study designs and assess RoB. Cohen’s kappa will be used to evaluate human-human, human-LLM and LLM-LLM interrater agreement. Logistic regression will be used to assess study characteristics affecting performance. Ap-value < 0.05 at a 95% confidence interval will be considered statistically significant.ConclusionIf the human-LLM agreement is high, LLMs could become valuable teaching and quality assurance tools for critical appraisal in neurosurgery and other medical fields. This study will contribute to validating LLMs for specialised scientific tasks in evidence synthesis. This could lead to reduced review costs, faster completion, standardisation, and minimal errors in evidence synthesis.
Plasma and CSF neurofilament light chain distinguish neurodegenerative from primary psychiatric conditions in a clinical setting
Authors: Eratne Dhamidhu , Kang Matthew JY , Lewis Courtney , Dang Christa , Malpas Charles B , Keem Michael , Grewal Jasleen , Marinov Vladimir , Coe Amy , Kaylor-Hughes Cath , Borchard Thomas , Keng-Hong Chhoa , Waxmann Alexandra , Saglam Burcu , Kalincik Tomas , Kanaan Richard , Kelso Wendy , Evans Andrew , Farrand Sarah , Loi Samantha , Walterfang Mark , Stehmann Christiane , Li Qiao-Xin , Collins Steven , Masters Colin L , Santillo Alexander F , Zetterberg Henrik , Blennow Kaj , Berkovic Samuel F , Velakoulis Dennis ,   The MiND Study Group
Published: August 2024

ABSTRACTINTRODUCTIONMany patients with neurodegenerative disorders (ND) face diagnostic delay and misdiagnosis. We investigated blood and cerebrospinal fluid (CSF) neurofilament light chain (NfL) to distinguish ND from primary psychiatric disorders (ND), a common challenge in clinical settings.METHODSPlasma and CSF NfL levels were measured and compared between groups, adjusting for age, sex, weight.RESULTS337 participants included: 136 ND, 77 PPD, 124 Controls. Plasma NfL was 2.5 fold elevated in ND compared to PPD and had strong diagnostic performance (area under the curve, AUC 0.86, 81%/85% specificity/sensitivity) that was comparable to CSF NfL (2 fold elevated, AUC 0.89, 95%/71% specificity/sensitivity). Diagnostic performance was especially strong in younger people (40-<60years). Additional findings were cut-offs optimised for sensitivity and specificity, and issues important for future clinical translationCONCLUSIONSThis study adds important evidence for a simple blood-based biomarker to assist as a screening test for neurodegeneration and distinction from PPD, in clinical settings.
Genotyping sequence-resolved copy-number variations using pangenomes reveals paralog-specific global diversity and expression divergence of gene duplication
Authors: Ma Walfred , Chaisson Mark JP 
Published: August 2024

AbstractCopy-number variable (CNV) genes are important in evolution and disease, yet sequence variation in CNV genes remains a blindspot in large-scale studies. We present ctyper, a method that leverages pangenomes to produce allele-specific copy numbers with locally phased variants from NGS reads. Benchmarking on 3,351 CNV genes includingHLA,SMN, andCYP2D6, and 212 challenging medically-relevant (CMR) genes poorly mapped by NGS, ctyper captures 96.5% of phased variants with ≥99.1% correctness of copy number on CNV genes and 94.8% of phased variants on CMR genes. Applying alignment-free algorithms, ctyper takes only 1.5 hours to genotype a genome on a single CPU. Its results improve predictions of gene expression compared to known eQTL variants. Allele-specific expression quantified divergent expression on 7.94% of paralogs and tissue-specific biases on 4.68% of paralogs. We found reduced expression ofSMN-2 due toSMN1-conversions, potentially affecting spinal muscular atrophy, and increased expression of translocated duplications ofAMY2B. Overall, ctyper enables biobank-scale genotyping of CNV and CMR genes.
Relative phase of distributed oscillatory dynamics implements a working memory in a simple brain
Authors: Dunn Raymond L. , Costello Caitriona , Borchardt Jackson M. , Sprague Daniel Y. , Chiu Grace C. , Miller Julia M. , L’Etoile Noelle , Kato Saul 
Published: August 2024

AbstractWe report the existence of a working memory system in the nematodeC. elegansthat is employed for deferred action in a sensory-guided decision-making process. We find that the turn direction of discrete reorientations during navigation is under sensory-guided control and relies on a working memory that can persist over an intervening behavioral sequence. This memory system is implemented by the phasic interaction of two distributed oscillatory dynamical components. The interaction of oscillatory neural ensembles may be a conserved primitive of cognition across the animal kingdom.
EMMPRIN confers metabolic advantage for monocytes and macrophages to promote disease in a model of multiple sclerosis
Authors: Kaushik DK , Das A , Silva C , D’Mello C , de Almeida LGN , Ghasemi N , Neri P , Dufour A , Bahlis NJ , Xue M , Yong VW 
Published: August 2024

AbstractMonocytes and monocyte-derived macrophages have important roles in the initiation and progression of multiple sclerosis (MS). These cells undergo metabolic reprogramming to generate immunophenotypes that promote leukocyte infiltration, axonal degeneration and demyelination, worsening MS pathology. The mechanisms that dictate metabolic programs in monocytes and macrophages in MS remain unclear. We previously reported that extracellular matrix metalloproteinase inducer (EMMPRIN, CD147), a glycoprotein that acts as a chaperone of monocarboxylate transporter 4 (MCT4), assisted with glycolysis-driven pro-inflammatory phenotype in macrophages in experimental autoimmune encephalomyelitis (EAE), an animal model of MS. Using newly-generated CCR2CreERT2:EMMPRINfl/fl(CCR2:EMMP) mice, we report that presymptomatic deletion of EMMPRIN in CCR2+ monocytes prevented or reduced clinical disability of EAE. This was correspondent with decreased infiltration of leukocytes into the CNS. Single cell RNA-seq of blood monocytes from EAE and proteomics analysis of macrophages from CCR2:EMMP−/−mice revealed significant alterations in metabolic programs, particularly reduced glycolysis and elevated mitochondrial electron transport and fatty acid oxidation, which were linked to their reduced pro-inflammatory traits. Our findings implicate EMMPRIN as a key regulator of metabolic pathways that exacerbate pro-inflammatory functions of monocytes in MS.
Inhibition of heme biosynthesis triggers cuproptosis in acute myeloid leukaemia
Authors: Lewis Alexander C. , Gruber Emily , Franich Rheana , Armstrong Jessica , Kelly Madison J. , Opazo Carlos M. , Mawal Celeste H. , Birrell Alexandra , So Joan , Ting Keziah , Brown Fiona , Wei Andrew H. , Powell Jason A. , Brown Kristin K. , Johnstone Ricky W. , Kats Lev M. 
Published: August 2024

AbstractThe ubiquitous metabolite heme has diverse enzymatic and signalling functions in most mammalian cells. Cells can salvage heme from the extracellular environment or synthesise hemede novofrom succinyl-CoA and glycine through a series of 8 enzymatic reactions catalysed by heme biosynthesis enzymes (HBEs) localised in the mitochondria and the cytosol1,2. Through integrated analyses of mouse models, human cell lines and primary patient samples, we identifyde novoheme biosynthesis as a selective dependency in acute myeloid leukaemia (AML). The dependency is underpinned by a propensity of AML cells, and especially leukaemic stem cells (LSCs) to downregulate HBEs. The resultant low heme state upregulates self-renewal genes via the heme sensing transcription factor BACH1, but also places leukaemia cells on the threshold of heme starvation. Genetic or pharmacological inhibition of HBEs induces cuproptosis, a form of programmed cell death caused by copper accumulation and oligomerisation of lipoylated proteins3. Moreover, we identify pathways that are synthetic lethal with heme biosynthesis, including glycolysis, which can be leveraged for combination strategies. Altogether, our work uncovers a heme rheostat that controls gene expression and drug sensitivity in AML and implicates HBE inhibition as a novel cuproptosis trigger.
Examining NF-κB genomic interactions by ChIP-seq and CUT&Tag
Authors: Daly Allison E. , Schiffman Allison , Hoffmann Alexander , Smale Stephen T. 
Published: August 2024

AbstractAn understanding of the mechanisms and logic by which transcription factors coordinate gene regulation requires delineation of their genomic interactions at a genome-wide scale. Chromatin immunoprecipitation-sequencing (ChIP-seq) and more recent techniques, including CUT&Tag, typically reveal thousands of genomic interactions by transcription factors, but without insight into their functional roles. Due to cost and time considerations, optimization of ChIP experimental conditions is typically carried out only with representative interaction sites rather than through genome-wide analyses. Here, we describe insights gained from the titration of two chemical crosslinking reagents in genome-wide ChIP-seq experiments examining two members of the NF-κB family of transcription factors: RelA and c-Rel. We also describe a comparison of ChIP-seq and CUT&Tag. Our results highlight the large impact of ChIP-seq experimental conditions on the number of interactions detected, on the enrichment of consensus and non-consensus DNA motifs for the factor, and on the frequency with which the genomic interactions detected are located near potential target genes. We also found considerable consistency between ChIP-seq and CUT&Tag results, but with a substantial fraction of genomic interactions detected with only one of the two techniques. Together, the results demonstrate the dramatic impact of experimental conditions on the results obtained in a genome-wide analysis of transcription factor binding, highlighting the need for further scrutiny of the functional significance of these condition-dependent differences.
Epidemiological inferences from serological responses to cross-reacting pathogens
Authors: O’Driscoll Megan , Hozé Nathanaël , Lefrancq Noémie , Ribeiro Dos Santos Gabriel , Hoinard Damien , Rahman Mohammed Ziaur , Paul Kishor Kumar , Naser Titu Abu Mohd , Alam Mohammad Shafiul , Hossain Mohammad Enayet , Vanhomwegen Jessica , Cauchemez Simon , Gurley Emily S , Salje Henrik 
Published: August 2024

AbstractMultiplex immunoassays are facilitating the parallel measurement of antibody responses against multiple antigenically-related pathogens, generating a wealth of high-dimensional data which depict complex antibody-antigen relationships. In this study we develop a generalizable analytical framework to maximise inferences from multi-pathogen serological studies. We fit the model to measurements of IgG antibody binding to 10 arboviral pathogens from a cross-sectional study in northwest Bangladesh with 1,453 participants. We used our framework to jointly infer the prevalence of each pathogen by location and age, as well as the levels of between-pathogen antibody cross-reactivity. We find evidence of endemic transmission of Japanese encephalitis virus as well as recent outbreaks of dengue and chikungunya viruses in this district. Our estimates of antibody cross-reactivity were highly consistent with phylogenetic distances inferred from genetic data. Further, we demonstrated how our framework can be used to identify the presence of circulating cross-reactive pathogens that were not directly tested for, representing a potential opportunity for the detection of novel emerging pathogens. The presented analytical framework will be applicable to the growing number of multi-pathogen studies and will help support the integration of serological testing into disease surveillance platforms.