bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of disability level between Early and Late Onset Parkinson’s Disease using WHODAS 2
Authors: Nascimento Isaíra Almeida Pereira da Silva , Costa Nobrega Kátia Cirilo , Antunes Souza Bruno Rafael , Barone Isabela Carneiro , Checchio Giovanna , Ponciano Vitória Pereira , de Paula Clara Greif Cerveira , Possani Arieni Nunes , Penha Natália Cardoso , Helene André Frazão , Roque Antonio Carlos , Savica Rodolfo , Pimentel Piemonte Maria Elisa 
Published: September 2023

AbstractBackgroundParkinson’s disease (PD) is a degenerative neurological disorder that usually affects people over the age of 60. However, 10-20% of patients have an early onset of PD (EOPD).ObjectivesTo compare disability levels according to the World Health Organization Disability Assessment Schedule 2.0 (WHODAS-2) between people with EOPD and those with late-onset PD (LOPD).MethodsWe conducted a cross-sectional study with 95 EOPD patients (mean-age 44.51±4.63, H&Y 1.93±0.93) and 255 LOPD patients (mean-age 63.01±7.99, H&Y 2.02±0.95). Demographic information, clinical characteristics, cognitive evaluation by Telephone-Montreal-Cognitive-Assessment (T-MoCA), functionality self-evaluation by WHODAS-2 and the Unified-Parkinson’s-Disease-Rating-Scale (MDS-UPDRS), parts I and II, were documented for each patient by an individual remote interview.ResultsAnalysis showed a statistically significant difference between EOPD and LOPD in the cognition and activities of daily-living-related to work/school domains of WHODAS-2. T-MoCA scores confirmed more impaired cognition capacity in LOPD. The two groups had no significant differences in levodopa daily dosage, Hoehn and Yahr (H&Y) stages, disease time duration, and MDS-UPDRS I and II scores.ConclusionPeople living with EOPD face similar disability levels as those with LOPD, except for cognition, where LOPD patients exhibited higher levels of disability than EOPD and for work activities where the EOPD exhibited higher levels of disability than LODP. These results highlight the challenges faced by people with EOPD in interacting with society and living with the disease for a longer time. The WHODAS-2 can be a useful tool to assess disability and tailor interventions for people with PD of different age groups.
Representing multimorbid disease progressions using directed hypergraphs
Authors: Burke Jamie , Akbari Ashley , Bailey Rowena , Fasusi Kevin , Lyons Ronan A. , Pearson Jonathan , Rafferty James , Schofield Daniel 
Published: September 2023

AbstractObjectiveTo introduce directed hypergraphs as a novel tool for assessing the temporal relationships between coincident diseases, addressing the need for a more accurate representation of multimorbidity and leveraging the growing availability of electronic healthcare databases and improved computational resources.MethodsDirected hypergraphs offer a high-order analytical framework that goes beyond the limitations of directed graphs in representing complex relationships such as multimorbidity. We apply this approach to multimorbid disease progressions observed from two multimorbidity sub-cohorts of the SAIL Databank, after having been filtered according to the Charlson and Elixhauser comorbidity indices, respectively. After constructing a novel weighting scheme based on disease prevalence, we demonstrate the power of these higher-order models through the use of PageRank centrality to detect and classify the temporal nature of conditions within the two comorbidity indices.ResultsIn the Charlson population, we found that chronic pulmonary disease (CPD), cancer and diabetes were conditions observed early in a patient’s disease progression (predecessors), with stroke and dementia appearing later on (successors) and myocardial infarction acting as a transitive condition to renal failure and congestive heart failure. In Elixhauser, we found renal failure, neurological disorders and arrhythmia were classed as successors and hypertension, depression, CPD and cancer as predecessors, with diabetes becoming a transitive condition in the presence of obesity and alcohol abuse. The dynamics of these and other conditions changed across age and sex but not across deprivation. Unlike the directed graph, the directed hypergraph could model higher-order disease relationships, which translated into stronger classifications between successor and predecessor conditions, alongside the removal of spurious results.ConclusionThis study underscores the utility of directed hypergraphs as a powerful approach to investigate and assess temporal relationships among coincident diseases. By overcoming the limitations of traditional pairwise models, directed hypergraphs provide a more accurate representation of multimorbidity, offering insights that can significantly contribute to healthcare decision-making, resource allocation, and patient management. Further research holds promise for advancing our understanding of critical issues surrounding multimorbidity and its implications for healthcare systems.
Exact calculation of end-of-outbreak probabilities using contact tracing data
Authors: Bradbury NV , Hart WS , Lovell-Read FA , Polonsky JA , Thompson RN 
Published: September 2023

AbstractA key challenge for public health policy makers is determining when an infectious disease outbreak has finished. Following a period without cases, an estimate of the probability that no further cases will occur in future (the end-of-outbreak probability) can be used to inform whether or not to declare an outbreak over. An existing quantitative approach, based on a branching process transmission model, allows the end-of-outbreak probability to be approximated from disease incidence time series, the offspring distribution and the serial interval of the pathogen (the Nishiura method). Here, we show how the end-of-outbreak probability under the same transmission model can be calculated exactly if data describing who-infected-whom (the outbreak transmission tree) are available alongside the disease incidence time series. When such data are available, for example from contact tracing studies, our novel approach (the traced transmission method) is straightforward to use. We demonstrate this by applying the traced transmission method to data from previous outbreaks of Ebola virus disease and Nipah virus infection. For both outbreak datasets considered, we find that the traced transmission method would have determined that the outbreak was over more quickly than the Nishiura method. This highlights that consideration of contact tracing data may allow stringent control interventions to be relaxed quickly at the end of an outbreak, with only a limited risk of outbreak resurgence.
Benefit-Risk Assessment of Medical Products Using Bayesian Multi-Criteria Augmented Decision Analysis for Clinical Development
Authors: Vuong Quang , Metcalfe Rebecca K , Harari Ofir , Mills Edward J , Park Jay JH 
Published: September 2023

AbstractMulti-criteria decision analysis (MCDA) is a benefit-risk assessment tool that evaluates multiple competing benefit and risk endpoints simultaneously. MCDA has the potential to aid sponsors in making effective and informed go/no-go decisions for clinical development programs. MCDA involves assigning weights to benefit and risk endpoints based on their relative importance (i.e., utility weight) and using them to compute a single utility score that represents the overall benefit-risk profile of the treatment. However, to date, MCDA applications have not been appropriate for time-to-event data. In this paper, we introduce a novel framework known as Bayesian Multi-Criteria Augmented Decision Analysis (MCADA) that extends existing probabilistic MCDA methods to encompass time-to-event and ordinal outcomes while incorporating linear and novel non-linear functions in utility aggregation. This paper provides a comprehensive description of the statistical methodology behind the MCADA framework and demonstrates its application using a simulation study, as well as two clinical trials using IPD and aggregate data. Our simulation study found that MCADA generally achieves higher power than the existing MCDA methods due to avoidance of loss of information that occurs when survival and ordinal outcomes are dichotomized. Our two case studies show that the MCADA framework can be effectively used to produce a single utility score that reflects the overall benefit-risk profile of a treatment using both IPD and aggregate data from trials. MCADA broadens the horizon of the current MCDA framework by accommodating a wider range of data types and utility functions in the utility aggregation process.
Na+/K+ATPase-Cav1.2 nanodomain differentially regulates intracellular [Na+], [Ca2+] and local adrenergic signaling in cardiac myocytes
Authors: Karbowski Mariusz , Boyman Liron , Garber Libet , Joca Humberto C. , Verhoeven Nicolas , Coleman Andrew K. , Ward Christopher W. , Lederer W. Jonathan , Greiser Maura 
Published: September 2023

AbstractBackgroundThe intracellular Na+concentration ([Na+]i) is a crucial but understudied regulator of cardiac myocyte function. The Na+/K+ATPase (NKA) controls the steady-state [Na+]iand thereby determines the set-point for intracellular Ca2+. Here, we investigate the nanoscopic organization and local adrenergic regulation of the NKA macromolecular complex and how it differentially regulates the intracellular Na+and Ca2+homeostases in atrial and ventricular myocytes.MethodsMulticolor STORM super-resolution microscopy, Western Blot analyses, and in vivo examination of adrenergic regulation are employed to examine the organization and function of Na+nanodomains in cardiac myocytes. Quantitative fluorescence microscopy at high spatiotemporal resolution is used in conjunction with cellular electrophysiology to investigate intracellular Na+homeostasis in atrial and ventricular myocytes.ResultsThe NKAα1 (NKAα1) and the L-type Ca2+-channel (Cav1.2) form a nanodomain with a center-to center distance of ∼65 nm in both ventricular and atrial myocytes. NKAα1 protein expression levels are ∼3 fold higher in atria compared to ventricle. 100% higher atrial INKA, produced by large NKA “superclusters”, underlies the substantially lower Na+concentration in atrial myocytes compared to the benchmark values set in ventricular myocytes. The NKA’s regulatory protein phospholemman (PLM) has similar expression levels across atria and ventricle resulting in a much lower PLM/NKAα1 ratio for atrial compared to ventricular tissue. In addition, a huge PLM phosphorylation reserve in atrial tissue produces a high ß-adrenergic sensitivity of INKAin atrial myocytes. ß-adrenergic regulation of INKAis locally mediated in the NKAα1-Cav1.2 nanodomain via A-kinase anchoring proteins.ConclusionsNKAα1, Cav1.2 and their accessory proteins form a structural and regulatory nanodomain at the cardiac dyad. The tissue-specific composition and local adrenergic regulation of this “signaling cloud” is a main regulator of the distinct global intracellular Na+and Ca2+concentrations in atrial and ventricular myocytes.
Electrostatic modulation of signaling at cell membrane: Waveform- and time-dependent electric control of ERK dynamics
Authors: Hu Minxi , Li Houpu , Zhu Kan , Guo Liang , Zhao Min , Zhan Huiwang , Devreotes Peter N. , Qing Quan 
Published: September 2023

ABSTRACTDifferent exogenous electric fields (EF) can guide cell migration, disrupt proliferation, and program cell development. Studies have shown that many of these processes were initiated at the cell membrane, but the mechanism has been unclear, especially for conventionally non-excitable cells. In this study, we focus on the electrostatic aspects of EF coupling with the cell membrane by eliminating Faradaic processes with dielectric-coated microelectrodes, and show that the ERK signaling pathway of epithelial cells (MCF10A) can be both inhibited and activated by AC EF with different amplitude thresholds, peaking times and refractory periods. Interestingly, the ERK responses were sensitive to the waveform and timing of EF stimulation pulses, depicting the characteristics of electrostatic and dissipative interactions. Blocker tests and correlated changes of active Ras on the cell membrane with ERK signals indicated that both EGFR and Ras were involved in the rich ERK dynamics induced by EF. We propose that the frequency-dependent dielectric relaxation process could be an important mechanism to couple EF energy to the cell membrane region and modulate membrane protein-initiated signaling pathways, which can be further explored to precisely control cell behavior and fate with high temporal and spatial resolution.
Short-term consumption of ultra-processed semi-synthetic diets impairs the sense of smell and brain metabolism in mice
Authors: Makhlouf Melanie , Souza Débora G. , Kurian Smija , Bellaver Bruna , Ellis Hillary , Kuboki Akihito , Al-Naama Asma , Hasnah Reem , Venturin Gianina Teribele , da Costa Jaderson Costa , Venugopal Neethu , Manoel Diogo , Reisert Johannes , Tordoff Michael G. , Zimmer Eduardo R. , Saraiva Luis R. 
Published: September 2023

ABSTRACTThe prevalence of highly-palatable, ultra-processed food in our modern diet has exacerbated obesity rates and contributed to a global health crisis. While accumulating evidence suggests that chronic consumption of ultra-processed semi-synthetic food is detrimental to sensory and neural physiology, it is unclear whether its short-term intake has adverse effects. Here, we assessed how short-term consumption (<2 months) of three ultra-processed diets (one grain-based diet, and two semi-synthetic) influence olfaction and brain metabolism in mice. Our results demonstrate that short-term consumption of semi-synthetic diets, regardless of macronutrient composition, adversely affect odor-guided behaviors, physiological responses to odorants, transcriptional profiles in the olfactory mucosa and brain regions, and brain glucose metabolism and mitochondrial respiration. These findings reveal that even short periods of ultra-processed semi-synthetic food consumption are sufficient to cause early olfactory and brain abnormalities, which has the potential to alter food choices and influence the risk of developing metabolic disease.
Modelling cognitive outcomes in the UK Biobank: education, noradrenaline and frontoparietal networks
Authors: Bravo-Merodio Laura , Williams Jackie A. , Russ Dominic , Gkoutos Georgios , Brosnan Meadhbh , Bellgrove Mark A. , Chechlacz Magdalena 
Published: September 2023

ABSTRACTCognitive reserve (CR) measured by proxies of life experiences is thought to account for the heterogeneity in cognitive ageing. One hypothesis is that cognitively enriched environments acting on the noradrenergic system strengthen the right fronto-parietal networks to facilitate cognitive reserve and maintain cognition throughout the lifetime. We used machine learning and mediation analysis to model interactions between neurobiological features (genetic variants in noradrenergic signalling, structural and functional fronto-parietal connectivity) and CR (by proxy of education) on cognitive outcomes (general cognitive ability score) in the UK Biobank cohort. We show that: (1) interactions between CR and neurobiological variables more fully explain cognitive outcomes than either factor alone; (2) among the neurobiological features selected using variable importance testing, measures of fronto-parietal connectivity are the strongest mediators of the effect of CR on cognitive outcomes. Our findings offer novel insights into neurobiological basis of CR by pointing to two between-networks connectivity measures, representing connections linking the default mode network with the right fronto-parietal network, and with the executive control network, as the key facilitators of CR.
“Dark taxonomy”: a new protocol for overcoming the taxonomic impediments for dark taxa and broadening the taxon base for biodiversity assessment
Authors: Meier Rudolf , Srivathsan Amrita , Oliveira Sarah Siqueira , Balbi Maria Isabel P.A. , Ang Yuchen , Yeo Darren , Kjærandsen Jostein , Amorim Dalton de Souza 
Published: September 2023

AbstractWe are entering the 6thmass extinction with little data for “dark taxa” although they comprise most species. Much of the neglect is due to the fact that conventional taxonomic methods struggle with handling thousands of specimens belonging to hundreds of species. We thus here propose a new strategy that we call “dark taxonomy.” It addresses (1) taxonomic impediments, (2) lack of biodiversity baselines, (3) and low impact of revisionary research. Taxonomic impediments are reduced by carrying out revisions at small geographic scales to keep the number of specimens low. The risk of taxonomic error is kept low by delimiting species based on two types of data. We then show that dark taxonomy can yield important biodiversity baseline data because it uses samples obtained with biomonitoring traps. Lastly, we argue that the impact of research can be improved by publishing two manuscripts addressing different readerships. The principles of dark taxonomy are illustrated by our taxonomic treatment of Singapore’s fungus gnats (Mycetophilidae) based only on Malaise trap samples. We show that a first batch of specimens (N=1,454) contains 120 species, of which 115 are new to science thus reducing taxonomic impediments by increasing the number of described Oriental species by 25%. Species delimitation started with using DNA barcodes to estimate the number of MOTUs before “LIT” (Large-scale Integrative Taxonomy) was used to obtain the species boundaries for the 120 species by integrating morphological and molecular data. To test the taxonomic completeness of the revision, we then analyzed a second batch of 1,493 specimens and found that >97% belonged to the 120 species described based on the first batch. Indeed, the second batch only contained 18 new and rare MOTUs; i.e. our study suggests that a single revision can simultaneously yield the names for all important species and relevant biodiversity baseline data. Overall, we believe that “dark taxonomy” can quickly ready a large unknown taxon for biomonitoring.
SpatialDDLS: An R package to deconvolute spatial transcriptomics data using neural networks
Authors: Mañanes Diego , Rivero-García Inés , Jimenez-Carretero Daniel , Torres Miguel , Sancho David , Torroja Carlos , Sánchez-Cabo Fátima 
Published: September 2023

AbstractSummarySpatial transcriptomics has changed our way to study tissue structure and cellular organization. However, there are still limitations in its resolution, and most available plaXorms do not reach a single cell resolution. To address this issue, we introduce SpatialDDLS, a fast neural network-based algorithm for cell type deconvolution of spatial transcriptomics data. SpatialDDLS leverages single-cell RNA sequencing (scRNA-seq) data to simulate mixed transcriptional profiles with predefined cellular composition, which are subsequently used to train a fully-connected neural network to uncover cell type diversity within each spot. By comparing it with two state-of-the-art spatial deconvolution methods, we demonstrate that SpatialDDLS is an accurate and faster alternative to the available state-of-the art tools.Availability and implementationThe R package SpatialDDLS is available via CRAN-The Comprehensive R Archive Network:https://CRAN.R-project.org/package=SpatialDDLS. A detailed manual of the main functionalities implemented in the package can be found athttps://diegommcc.github.io/SpatialDDLS.Contactfscabo@cnic.esSupplementary informationSupplementary data are available at Bioinformatics online.
PlasmidEC and gplas2: An optimised short-read approach to predict and reconstruct antibiotic resistance plasmids inEscherichia coli
Authors: Paganini Julian A. , Kerkvliet Jesse J. , Vader Lisa , Plantinga Nienke L. , Meneses Rodrigo , Corander Jukka , Willems Rob J.L. , Arredondo-Alonso Sergio , Schürch Anita C. 
Published: September 2023

AbstractAccurate reconstruction ofEscherichia coliantibiotic resistance gene (ARG) plasmids from Illumina sequencing data has proven to be a challenge with current bioinformatic tools. In this work, we present an improved method to reconstructE. coliplasmids using short reads. We developed plasmidEC, an ensemble classifier that identifies plasmid-derived contigs by combining the output of three different binary classification tools. We showed that plasmidEC is especially suited to classify contigs derived from ARG plasmids with a high recall of 0.941. Additionally, we optimised gplas, a graph-based tool that bins plasmid-predicted contigs into distinct plasmid predictions. Gplas2 is more effective at recovering plasmids with large sequencing coverage variations and can be combined with the output of any binary classifier. The combination of plasmidEC with gplas2 showed a high completeness (median=0.818) and F1-score (median=0.812) when reconstructing ARG plasmids and exceeded the binning capacity of the reference-based method MOB-suite. In the absence of long read data, our method offers an excellent alternative to reconstruct ARG plasmids inE. coli.Data SummaryNo new sequencing data have been generated in this study. All genomes used in this research are publicly available at the GenBank and Sequence Read Archive of the National Center for Biotechnology Information. Accession numbers are specified in Supplementary Materials.Scripts to reproduce the results reported in this manuscript can be accessed athttps://gitlab.com/jpaganini/ecoli-binary-classifier. The ensemble classifier, plasmidEC, is publicly available athttps://gitlab.com/mmb-umcu/plasmidEC(release 1.3.1), and gplas2 (release 1.0.0) can be found athttps://gitlab.com/mmb-umcu/gplas2.Impact StatementEscherichia colihas emerged as a highly pervasive multidrug resistant pathogen on a global scale. The dissemination of resistance is significantly influenced by plasmids, mobile genetic elements that facilitate the transfer of antimicrobial resistance genes within and between diverse bacterial species. Consequently, precise and high-throughput identification of plasmids is imperative for effective genomic surveillance of resistance. However, accurate plasmid reconstruction remains challenging with the use of affordable short-read sequencing data. In this work, we present a novel method to accurately predict and reconstructE. coliplasmids based on Illumina data. Additionally, we demonstrate that our approach outperforms the reference-based method MOB-suite, especially when reconstructing plasmids carrying antimicrobial resistance genes.