bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring interaction between genetically predicted body mass index and serum 25-hydroxyvitamin D levels on the odds for psoriasis in UK Biobank and the HUNT Study: A factorial Mendelian randomisation study
Authors: Jenssen Marita , Arora Nikhil , Løset Mari , Åsvold Bjørn Olav , Thomas Laurent , Gangsø Bekkevold Ole-Jørgen , Mai Xiao-Mei , Sun Yi-Qian , Furberg Anne-Sofie , Jorde Rolf , Wilsgaard Tom , Danielsen Kjersti , Brumpton Ben Michael 
Published: July 2024

AbstractBackgroundMendelian randomisation (MR) studies show that higher body mass index (BMI) and lower 25-hydroxyvitamin D (25[OH]D) increase psoriasis risk. The combined effect of these factors has not been explored using factorial MR.MethodsUsing cross-sectional data from UK Biobank (UKB, n=398 404) and the Trøndelag Health Study (HUNT, n=86 648), we calculated polygenic risk scores for BMI and 25(OH)D to estimate odds ratios for psoriasis using 2×2 and continuous factorial MR. We quantified additive interaction by relative excess risk due to interaction (RERI)-estimates. We also performed traditional observational analyses in UKB.ResultsThere were 12 207 (3.1%) participants with psoriasis in UKB and 7794 (9.0%) in HUNT. In 2×2 factorial MR, we found no evidence of relative excess risk for psoriasis due to interaction between genetically predicted higher BMI and lower 25(OH)D, neither in UKB (RERI −0.01, 95% confidence interval (CI) −0.08, 0.07) nor in HUNT (RERI −0.04, 95% CI −0.14, 0.06). The same was observed in the continuous factorial MR and observational analyses.ConclusionsThis study did not find evidence of interaction between BMI and 25(OH)D on the risk of psoriasis. Given minor differences in measured BMI and 25(OH)D between groups, small effects may have been undetected.
Returning Research Results That Indicate Risk of Alzheimer Disease Dementia to Healthy Participants in Longitudinal Studies (WeSHARE)
Authors: Hartz Sarah M. , Goswami Spondita , Oliver Amy , Evans Alissa , Jackson Sacha , Linnenbringer Erin , Moulder Krista , Morris John C. , Mozersky Jessica 
Published: July 2024

ABSTRACTIntroductionReturning research results that indicate risk of Alzheimer disease (AD) - a disease for which no meaningful treatments or cure exist - to cognitively normal participants is controversial. AD is thought to begin many years before clinical signs and symptoms begin. During this time, individuals are cognitively normal, but have biomarkers that indicate pathophysiological changes in the brain. With this study, we aim to evaluate impact of returning research results on cognitively normal participants recruited from a longitudinal observational cohort on aging at the Knight Alzheimer Disease Research Center (Knight ADRC) at Washington University in St. Louis.Methods and analysisOur study uses a 2-year, delayed-start randomized clinical trial design. Participants are randomized to receive their research results either in 2-4 weeks or 1 year after informed consent. We plan to approach approximately 260 participants who have research results from previous genetic and biomarker testing at the Knight ADRC. The primary cognitive outcomes are 1-year change in subjective cognitive score (Clinical Dementia Rating (CDR®) sum of boxes), objective cognitive score (psychometric composite score), and the primary psychosocial outcome is Impact of Event-Revised score 1 year after return of research results.Ethics and disseminationThis study has been approved by the WUSM Institutional Review Board (IRB) and the Human Research Protection Office (HRPO). Results from these trials are shared through conferences and publications.Trial registration numberNCT04699786.Strengths and limitations of this studyThis study empirically evaluates how returning research AD biomarkers impacts participants both psychologically and cognitively using a randomized delayed-start clinical trialMultiple research AD biomarkers are synthesized into a single estimate for AD dementia riskA delayed-start design is necessary because it is unethical to withhold research results from participants but may limit the generalizability of the results because all participants will be receiving their research results
Inference of ecological networks and possibilistic dynamics based on Boolean networks from observations and prior knowledge
Authors: Paulevé Loïc , Gaucherel Cédric 
Published: July 2024

AbstractBeing able to infer the interactions between a set of species from observations of the system is of paramount importance to obtain explaining and predictive models in ecology. We tackled this challenge by employing qualitative modeling frameworks and logic methods for the synthesis of mathematical models that can integrate both observations and expert knowledge on the system. After devising a formal link between ecological networks and the causal structure of Boolean networks, we applied a generic model synthesis engine to infer Boolean models that are able to reproduce the observed dynamics of a protist community. Our inference method supports optimization criteria to derive most parsimonious and most precise models. It is also able to integrate prior knowledge on the ecological network, adding constraints on impossible interactions, which is necessary to obtain realistic predictions. Such constraints may however prove to be too strict, in which case our method is able to conclude on the absence of a model compatible with both the observations and the input hypotheses. We demonstrated our methodology on experimental data of a protist system, and showed its ability to recover essential and sufficient ecological interactions to explain the observed dynamics.
Designer DNA nanocages modulate anti-oxidative and anti-inflammatory responses in tumor associated macrophages
Authors: Vaswani Payal , Bhatia Dhiraj 
Published: July 2024

AbstractCancer is a complex disease, with multiple treatment modalities, but no definitive cure. The tumor microenvironment contributes to the complexity of the disease by forming a niche of multiple cell types supporting each other to carry out various cellular functions. Tumor associated macrophages are one such kind of cells which support the tumor microenvironment via immunosuppression. DNA tetrahedron (TD), a widely explored DNA nanocage, has shown a lot of potential in therapeutics. However, the role of TD still remains quite unexplored in immunology. Here, we first establish the anti-oxidative and anti-inflammatory role of TD. We then proceed with using TD as a therapeutic agent in tumor associated macrophages by modulating the response of PD-L1. The findings of this work create a base for TD in biological applications such as cancer immunotherapy.Graphical AbstractImmunomodulatory effects of DNA nanocages on tumour associated macrophages
Capturing gait parameters during asymmetric overground walking using ultra-wideband radars: A preliminary study
Authors: Hadjipanayi Charalambos , Yin Maowen , Constandinou Timothy G. 
Published: July 2024

AbstractThis study investigates the deployability of commercially available impulse-radio ultra-wideband radar (UWB) sensors, in accurately detecting and analysing gait patterns during asymmetric overground locomotion. An adjustable knee brace was fitted on the right knee of 10 able-bodied participants, in five different confinement angles, during a 6-meter walking task to simulate asymmetric walking patterns. A computationally efficient signal processing framework extracts seven spatiotemporal gait parameters from six UWB radar signals, based on their joint Range-Doppler-Time representation. Gait asymmetry was quantified using primarily the symmetry ratio metric of step times. Validated against the gold standard motion capture system, radar-based gait parameters were estimated with 88.2-98.8% accuracy for all settings. By capturing step time symmetry ratios with 95.6±2.8% accuracy, the radar system can effectively distinguish between different gait impairment levels.
Regulation of proteostasis by sleep through autophagy inDrosophilamodels of Alzheimer’s Disease
Authors: Ortiz-Vega Natalie , Lobato Amanda G. , Canic Tijana , Zhu Yi , Lazopulo Stanislav , Syed Sheyum , Zhai R. Grace 
Published: July 2024

AbstractSleep and circadian rhythm dysfunctions are common clinical features of Alzheimer’s Disease (AD). Increasing evidence suggests that in addition to being a symptom, sleep disturbances can also drive the progression of neurodegeneration. Protein aggregation is a pathological hallmark of AD, however the molecular pathways behind how sleep affects protein homeostasis remain elusive. Here we demonstrate that sleep modulation influences proteostasis and the progression of neurodegeneration inDrosophilamodels of Tauopathy. We show that sleep deprivation enhanced Tau aggregational toxicity resulting in exacerbated synaptic degeneration. In contrast, sleep induction using gaboxadol led to reduced hyperphosphorylated Tau accumulation in neurons as a result of modulated autophagic flux and enhanced clearance of ubiquitinated Tau, suggesting altered protein processing and clearance that resulted in improved synaptic integrity and function. These findings highlight the complex relationship between sleep and autophagy, in regulating protein homeostasis, and the neuroprotective potential of sleep-enhancing therapeutics to slow the progression or delay the onset of neurodegeneration.
Replacing non-biomedical concepts improves embedding of biomedical concepts
Authors: Niyonkuru Enock , Soto Gomez Mauricio , Casiraghi Elena , Antogiovanni Stephan , Blau Hannah , Reese Justin T , Valentini Giorgio , Robinson Peter N 
Published: July 2024

AbstractObjectivesConcept embeddings are low-dimensional vector representations of concepts such as MeSH:D009203 (Myocardial Infarction), whose similarity in the embedded vector space reflects their semantic similarity. Here, we test the hypothesis that non-biomedical concept synonym replacement can improve the quality of biomedical concepts embeddings.Materials and methodsWe developed an approach that leverages WordNet to replace sets of synonyms with the most common representative of the synonym set.ResultsWe tested our approach on 1055 concept sets and found that, on average, the mean intracluster distance was reduced by 8% in the vector-space. Assuming that homophily of related concepts in the vector space is desirable, our approach tends to improve the quality of embeddings.Discussion and ConclusionThis pilot study shows that non-biomedical synonym replacement tends to improve the quality of embeddings of biomedical concepts using the Word2Vec algorithm. We have implemented our approach in a freely available Python package available athttps://github.com/TheJacksonLaboratory/wn2vec.
Poly(allylamine)/tripolyphosphate nanocomplex coacervate as a NLRP3-dependent systemic adjuvant for vaccine development
Authors: Rizzo Gastón P. , Sanches Rodrigo C. , Chavero Camila , Bianchi Daiana S. , Apuzzo Eugenia , Herrera Santiago E. , Agazzi Maximiliano L. , Cortez M. Lorena , Marmisollé Waldemar A. , Keitelman Irene A. , Trevani Analía S. , Oliveira Sergio C. , Azzaroni Omar , Smaldini Paola L. , Docena Guillermo H. 
Published: July 2024

ABSTRACTNanotechnology plays a crucial role in vaccine development. It allows the design of functional nanoparticles (NPs) that can act both as antigen carriers and as adjuvants to enhance the immune response. The present study aims to evaluate complex coacervate-like NPs composed of poly(allylamine hydrochloride) (PAH) and tripolyphosphate (TPP) as a safe vehicle and adjuvant for systemic vaccines. We investigated the activation of different antigen-presenting cells (APCs) with NPs and their adjuvanticity in Balbc/c and different KO mice that were intraperitoneally immunized with NP-OVA.We found that NPs increased the expression of CD86 and MHCII and promoted the production and secretion of interleukin-1β (IL-1β) and IL-18 through the inflammasome NLRP3 when macrophages and dendritic cells were co-incubated with LPS and NPs. We evidenced an unconventional IL-1β release through the autophagosome pathway. The inhibition of autophagy with 3-methyladenine reduced the LPS/NPs-induced IL-1β secretion. Additionally, our findings showed that the systemic administration of mice with NP-OVA triggered a significant induction of serum OVA-specific IgG and IgG2a, an increased secretion of IFN-γ by spleen cells, and high frequencies of LT CD4+IFN-γ+and LT CD8+IFN-γ+. Our findings show that NPs promoted the inflammasome activation of innate cells with Th1-dependent adjuvant properties, making them valuable for formulating novel preventive or therapeutic vaccines for infectious and non-infectious diseases.Graphical Abstract
tauX: A Gene Expression Ratio Strategy to Improve Machine Learning Applications in Precision Medicine
Authors: Pfeil Jacob , Ma Liqian , Lo Hin Ching , Turan Tolga , McLaughlin R. Tyler , Shi Xu , Villarruel Severiano , Wilson Stephen , Zhao Xi , Samayoa Josue , Halliwill Kyle 
Published: July 2024

AbstractMachine learning algorithms identify patterns that would otherwise be difficult to observe in high-dimensional molecular and clinical data. For this reason, machine learning has the potential to have a profound impact on clinical decision making and drug target discovery. Nevertheless, there remain considerable technical challenges in adapting these tools for clinical use. These challenges include clinical feature engineering, model selection, and defining optimal strategies for model training. For cancer care, RNA sequencing of patient tumor biopsies has already proven to be a powerful molecular assay to characterize tumor-intrinsic and -extrinsic phenotypes influencing therapeutic response. To improve the predictive performance of RNA-sequencing data, we developed the tauX machine learning framework to refine gene expression features and improve the performance of machine learning algorithms. The tauX framework uses aggregated ratios of positively and negatively associated predictive genes to simplify the prediction task. We showed a significant improvement in predictive performance using a large database of synthetic gene expression profiles. We also show how the tauX framework can be used to elucidate the mechanisms of response and resistance to checkpoint blockade therapy using data from the Stand Up to Cancer (SU2C) Lung Response Cohort and The Cancer Genome Atlas (TCGA). The tauX strategy achieved superior predictive performance compared to models built upon established feature engineering strategies or widely used cancer gene expression signatures. The tauX framework is available as a freely deployable docker container (https://hub.docker.com/r/pfeiljx/taux).
Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease
Authors: Wolf Maximilian , Lange Julian , Benndorf Dirk , Welz Lina , Nikolaus Susanna , Sievers Laura , Tran Florian , Schallert Kay , Hellwig Patrick , Schreiber Stefan , Gunzer Matthias , Rosenstiel Philip , Reichl Udo , Aden Konrad , Heyer Robert 
Published: July 2024

AbstractBackgroundThe gut microbiome is an important contributor to the development and the course of inflammatory bowel disease (IBD). While changes in the gut microbiome composition were observed in response to IBD therapy using biologics, studies elucidating human and microbial proteins and pathways in dependence on therapy success are sparse.MethodsFecal samples of a cohort of IBD patients were collected before and after 14 weeks of treatment with three different biologics. Clinical disease activity scores were used to determine the clinical response and remission. Fecal metaproteomes of remitting patients (n=12) and of non-remitting patients (n=12) were compared before treatment and changes within both groups were assessed over sampling time to identify functional changes and potential human and microbial biomarkers.ResultsThe abundance of proteins associated with the intestinal barrier, neutrophilic granulocytes, and immunoglobulins significantly decreased in remitting patients. In contrast, an increase of those proteins was observed in non-remitting patients. There were significant changes in pathways of microbial metabolism in samples from patients with remission after therapy. This included, for example, an increased abundance of proteins from butyrate fermentation. Finally, new potential biomarkers for the prediction and monitoring of therapy success could be identified, e.g. human lysosome-associated membrane glycoprotein 1, a cytotoxicity marker, or microbial anthranilate synthase component 2, a part of the tryptophan metabolism.ConclusionsDistinct changes of proteins related to gut inflammation and gut microbiome metabolism showed whether IBD remission was achieved or not. This suggests that metaproteomics could be a useful tool for monitoring remission in IBD therapies.
Patient information needs for transparent and trustworthy artificial intelligence in healthcare
Authors: Stroud Austin M. , Minteer Sarah A. , Zhu Xuan , Ridgeway Jennifer L. , Miller Jennifer E. , Barry Barbara A. 
Published: July 2024

AbstractBackgroundAs health systems incorporate artificial intelligence (AI) into various aspects of patient care, there is growing interest in understanding how to ensure transparent and trustworthy implementation. However, little attention has been given to what information patients need about these technologies to promote transparency of their use.MethodsWe conducted three asynchronous online focus groups with 42 patients across the United States discussing perspectives on their information needs for trust and uptake of AI, focusing on its use in cardiovascular care. Data were analyzed using a rapid content analysis approach.ResultsOur results suggest that patients have a set of core information needs, including specific information factors pertaining to the AI model, oversight, and healthcare experience, that are relevant to calibrating trust as well as perspectives concerning information delivery, disclosure, consent, and physician AI use.ConclusionsIdentifying patient information needs is a critical starting point for calibrating trust in healthcare AI systems and designing strategies for information delivery. These findings highlight the importance of patient-centered engagement when considering approaches for transparent healthcare AI.
Cryptic recombination and transposition drive structural variation to shape genomic plasticity and life history traits in a host generalist fungal plant pathogen
Authors: Derbyshire Mark C , Newman Toby E , Khentry Yuphin , Michael Pippa J , Bennett Sarita Jane , Rijal Lamichhane Ashmita , Graham-Taylor Carolyn , Chander Subhash , Camplone Claudia , Vicini Simone , Esquivel-Garcia Laura , Coutu Cathy , Hegedus Dwayne , Clarkson John , Lindbeck Kurt , Kamphuis Lars G 
Published: July 2024

AbstractBackgroundAn understanding of plant pathogen evolution is important for sustainable management of crop diseases. Plant pathogen populations must maintain adequate heritable phenotypic variability to survive. Polymorphisms >= 50 bp, known as structural variants (SVs), could contribute strongly to this variability by disrupting gene activities. SV acquisition is largely driven by mobile genetic elements called transposons, though a less appreciated source of SVs is erroneous meiotic double-strand break repair. The relative impacts of transposons and recombination on SV diversity and the overall contribution of SVs to phenotypic variability is elusive, especially in host generalists.ResultsWe use 25 high quality genomes to create a graphical pan-genome of the globally distributed host-generalist crop pathogenSclerotinia sclerotiorum. Outcrossing and recombination rates in this self-fertile species have been debated. Using bisulfite sequencing, and short read data from 190 strains, we show thatS. sclerotiorumhas many hallmarks of eukaryotic meiosis, including recombination hot and cold spots, centromeric and genic recombination suppression, and rapid linkage disequilibrium decay. Using a new statistic that captures average pairwise structural variation, we show that recombination and transposons make distinct contributions to SV diversity. Furthermore, despite only 5 % of genes being dispensable, SVs often had a stronger impact than other variants across 14 life history traits measured in 103 distinct strains.ConclusionTransposons and recombination make distinct contributions to SV diversity inS. sclerotiorum. Despite limited gene content diversity, SVs may strongly impact phenotypic variability. This sheds light on the genomic forces shaping adaptive flexibility in host generalists.
GTestimate: Improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator
Authors: Fahrenberger Martin , Esk Christopher , von Haeseler Arndt 
Published: July 2024

AbstractBackgroundSingle-cell RNA-seq suffers from unwanted technical variation between cells, caused by its complex experiments and shallow sequencing depths. Many conventional normalization methods try to remove this variation by calculating the relative gene expression per cell. However, their choice of the Maximum Likelihood estimator is not ideal for this application.ResultsWe presentGTestimate, a new normalization method based on the Good-Turing estimator, which improves upon conventional normalization methods by accounting for unobserved genes. To validateGTestimatewe developed a novel cell targeted PCR-amplification approach (cta-seq), which enables ultra-deep sequencing of single cells. Based on this data we show that the Good-Turing estimator improves relative gene expression estimation and cell-cell distance estimation. Finally, we useGTestimate’s compatibility with Seurat workflows to explore three common example data-sets and show how it can improve downstream results.ConclusionBy choosing a more suitable estimator for the relative gene expression per cell, we were able to improve scRNA-seq normalization, with potentially large implications for downstream results.GTestimateis available as an easy-to-use R-package and compatible with a variety of workflows, which should enable widespread adoption.
Bulk and Single-cell Transcriptomic Brain Data Identify Overlapping Processes and Cell-types with Human AUD and Mammalian Models of Alcohol Use
Authors: Huggett Spencer B. , Selveraj Sharmila , McGeary John E. , Ikeda Ami , Yuan Emerald , Loeffel Lauren B. , Palmer Rohan H.C. 
Published: July 2024

AbstractThis study explores the neurobiological underpinnings of alcohol use disorder (AUD) by integrating bulk and single-cell transcriptomic data from humans, primates, and mice across three brain regions associated with addiction (i.e., prefrontal cortex (PFC), nucleus accumbens (NAc), and central amygdala (CeA)). We compared AUD RNA expression and cell-type abundance from 92 human brain to data from 53 primates and 90 mice engaged in diverse alcohol use paradigms. The findings revealed significant and reproducible correlations between human AUD and mammalian models of alcohol use that vary by tissue, species, and behavioral paradigm. The strongest correlations occurred between primate and mouse models of binge drinking (i.e., high drinking in the dark). Certain primate models demonstrated that the brain RNA correlations with human alcohol use disorder (AUD) were approximately 40% as strong as the correlations observed within human samples themselves. By integrating single-cell transcriptomic data, this study observed decreased oligodendrocyte proportions in the PFC and NAc of human AUD with similar trends in animal models. Gene co-expression network analyses revealed conserved systems associated with human AUD and animal models of heavy/binge alcohol consumption. Gene co-expression networks were enriched for pathways related to inflammation, myelination, and synaptic plasticity and the genes within them accounted for ∼20% of the heritability in human alcohol consumption. Identified hub genes were associated with relevant traits (e.g., impulsivity, motivation) in humans and mice. This study sheds light on conserved biological entities underlying AUD and chronic alcohol use, providing insights into the cellular, genetic, and neuromolecular basis across species.