bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Accuracy of Cardiac Surface Conduction Velocity Measurements
Authors: Vigmond Edward J. , Roney Caroline , Bayer Jason , Nanthakumar Kumaraswamy 
Published: January 2024

AbstractBackground:Conduction velocity (CV) is a measure of the health of myocardial tissue. It can be measured by taking differences in activation times from intracardiac electrodes. Several factors introduce error into the measurement, amongst which, ignoring the three dimensional aspect is a major detriment. The purpose of this paper was to determine if, nonetheless, there was a specific region where CV could be accurately measured.Methods:Computer simulations of three dimensional ventricles with a realistic His-Purkinje system were performed. Ventricles also included a dense scar or diffuse fibrosis.Results:A finer spatial sampling produced better agreement with true CV. Using a error limit of 10 cm/s as a threshold, measurements taken within a region less than 2 cm from the pacing site proved to be accurate. Error increased abruptly beyond this distance. The Purkinje system and tissue fibre orientation played equally major roles in leading to a surface CV which was not reflective of the CV propagation through the tissue.Conclusions:Surface CV measurements close to the pacing site taken with an electrode spacing of at most 1 mm, give reasonable estimates of tissue CV.
Point-of-care cardiac elastography with external vibration for quantification of diastolic myocardial stiffness
Authors: Meyer Tom , Wellge Brunhilde , Barzen Gina , Knebel Fabian , Hahn Katrin , Elgeti Thomas , Fischer Thomas , Braun Jürgen , Tzschätzsch Heiko , Sack Ingolf 
Published: January 2024

AbstractBackgroundHeart failure is an increasing health problem in Western societies. Approximately 50% of patients with heart failure have preserved ejection fraction (HFpEF) and concomitant diastolic dysfunction (DD), in part caused by increased myocardial stiffness not detectable by standard echocardiography. While elastography can map tissue stiffness, cardiac applications are currently limited, especially in patients with a higher body mass index (BMI). Therefore, we developed point-of-care cardiac elastography to detect abnormal diastolic myocardial stiffness associated with DD.MethodsCardiac time-harmonic elastography (THE) using standard medical ultrasound and continuous external vibration was developed and applied to healthy controls and participants with DD due to wild-type transthyretin amyloidosis (ATTR) in this prospective single-center study between June 2020 and December 2022. A subgroup of participants with ATTR was on tafamidis treatment. Diastolic shear wave speed (SWS) was determined as surrogate marker of myocardial stiffness in different cardiac regions including the septum, posterior wall and automatically detected global left ventricular wall.ResultsA total of 130 participants were screened and 44 participants with ATTR (4 women, mean age: 80±7 years, BMI range: 20-37) and 54 healthy controls (26 women, mean age: 47±16 years, BMI range: 15-32) were included. In all analyzed regions, SWS was higher in patients than in controls providing area-under-the-curve (AUC) values (septum: 1.8±0.3m/s versus 2.9±0.6m/s, AUC=0.996; posterior wall: 1.9±0.3m/s versus 2.7±0.5m/s, AUC=0.938; global left ventricular wall: 2.0±0.3m/s versus 2.6±0.4m/s, AUC=0.912). Furthermore, SWS was reduced in participants treated with tafamidis (septum: 2.6±0.4 m/s; posterior wall: 2.4±0.3m/s; global left ventricular wall: 2.3±0.3m/s, all p<.005) suggesting the use of THE for therapy monitoring and patient management.ConclusionsCardiac THE detects abnormal myocardial stiffness in patients with DD, independent of BMI and ROI selection. Because it uses standard ultrasound components, THE can be cost-effectively implemented as a point-of-care device for widespread clinical use.
Predicting social experience from dyadic interaction dynamics: the BallGame, a novel paradigm to study social engagement
Authors: Lübbert Annika , Sengelmann Malte , Heimann Katrin , Schneider Till R. , Engel Andreas K. , Göschl Florian 
Published: January 2024

AbstractTheories of embodied cognition suggest that a shared environment and ongoing sensorimotor interaction are central for interpersonal learning and engagement. To investigate the embodied, distributed and hence dynamically unfolding nature of social cognitive capacities, we present a novel laboratory-based coordination task: the BallGame. Our paradigm requires continuous sensing and acting between two players who jointly steer a virtual ball around obstacles towards as many targets as possible. By analysing highly resolved measures of movement coordination and gaming behaviour, game-concurrent experience ratings, semi-structured interviews, and personality questionnaires, we reveal contributions from different levels of observation on social experience. In particular, successful coordination (number of targets collected) and intermittent periods of high versus low movement coordination (variability of relation) emerged as prominent predictors of social experience. Importantly, having the same (but incomplete) view on the game environment strengthened interpersonal coordination, whereas complementary views enhanced engagement and tended to generate more complex interactive behaviour. Overall, we find evidence for a critical balance between similarity and synchrony on the one hand, and variability and difference on the other, for successful engagement in social interactions. Finally, following participant reports, we highlight how interpersonal experience emerges from specific histories of coordination that are closely related to the interaction context in both space and time.
Development of non-sedating antischistosomal benzodiazepines
Authors: Mian Md Yeunus , Sharmin Dishary , Mondal Prithu , Belayet Jawad Bin , Hossain M Mahmun , McCusker Paul , Ryan Kaetlyn T. , Fedorov Alexander Y , Green Heather A , Ericksen Spencer S. , Zamanian Mostafa , Tiruveedhula V. V. N. Phani Babu , Cook James M. , Chan John D. 
Published: January 2024

AbstractThe neglected tropical disease schistosomiasis infects over 200 million people worldwide and is treated with just one broad spectrum antiparasitic drug (praziquantel). Alternative drugs are needed in the event of emerging praziquantel resistance or treatment failure. One promising lead that has shown efficacy in animal models and a human clinical trial is the benzodiazepine meclonazepam, discovered by Roche in the 1970’s. Meclonazepam was not brought to market because of dose-limiting sedative side effects. However, the human target of meclonazepam that causes sedation (GABAARs) are not orthologous to the parasite targets that cause worm death. Therefore, we were interested in whether the structure of meclonazepam could be modified to produce antiparasitic benzodiazepines that do not cause host sedation. We synthesized 18 meclonazepam derivatives with modifications at different positions on the benzodiazepine ring system and tested them forin vitroantiparasitic activity. This identified five compounds that progressed toin vivoscreening in a murine model, two of which cured parasite infections with comparable potency to meclonazepam. When these two compounds were administered to mice that were run on the rotarod test, both were less sedating than meclonazepam. These findings demonstrate the proof of concept that meclonazepam analogs can be designed with an improved therapeutic index, and point to the C3 position of the benzodiazepine ring system as a logical site for further structure-activity exploration to further optimize this chemical series.
Density dependence shapes life-history trade-offs in a food limited ungulate population
Authors: Jaggi Harman , Zuo Wenyun , Kentie Rosemarie , Gaillard Jean-Michel , Coulson Tim , Tuljapurkar Shripad 
Published: January 2024

AbstractQuantifying trade-offs within populations is an important goal in life-history and evolutionary theory. However, most studies focusing on life-history variation assume trade-offs to be static. In this paper, we provide a framework for understanding life-history variation at different densities while enabling us to reveal trade-offs that are often masked due to individual heterogeneity. We use published individual-based data from a population of Soay sheep and find density dependence strongly shapes life-history trade-offs and the distribution of lifetime reproductive success. We find trade-offs between juvenile survival and growth structures life-history variation for Soay sheep at all densities, but the intensity of the trade-offs increases with population density. At carrying capacity (K), a new trade-off appears between reproduction and juvenile survival. In addition, we find the distribution of LRS to be highly constrained atK, with mothers of prime adult sizes (∼ 25kg) contributing the most to reproduction. We also find the effects of density-dependence on demographic measures such as net reproductive rate, stable size distribution, and average vital rate functions. Our results suggest high density limits the diversity of individual life history strategies and has implications for better understanding the evolution of reproductive tactics via density-dependent selection and management of ungulates in food limited environments.
Transverse Aortic COnstriction Multi-omics Analysis (TACOMA) uncovers pathophysiological cardiac molecular mechanisms
Authors: Gjerga Enio , Dewenter Matthias , Britto-Borges Thiago , Grosso Johannes , Stein Frank , Eschenbach Jessica , Rettel Mandy , Backs Johannes , Dieterich Christoph 
Published: January 2024

AbstractTime-course multi-omics data of a murine model of progressive heart failure induced by transverse aortic constriction (TAC) provide insights into the molecular mechanisms that are causatively involved in contractile failure and structural cardiac remodelling. We employ Illumina-based transcriptomics, Nanopore sequencing, and mass spectrometry-based proteomics on samples from the left ventricle (LV) and right ventricle (RV, RNA only) of the heart at 1, 7, 21, and 56 days following TAC and Sham surgery. Here, we present TACOMA, as an interactive web-application that integrates and visualizes transcriptomics and proteomics data collected in a TAC time-course experiment. TACOMA enables users to visualize the expression profile of known and novel genes and protein products thereof. Importantly, we capture alternative splicing events by assessing differential transcript and exon usage as well. Co-expression-based clustering algorithms and functional enrichment analysis revealed overrepresented annotations of biological processes and molecular functions at the protein and gene levels. To enhance data integration, TACOMA synchronizes transcriptomics and proteomics profiles, enabling cross-omics comparisons. With TACOMA (https://shiny.dieterichlab.org/app/tacoma), we offer a rich web-based resource to uncover molecular events and biological processes implicated in contractile failure and cardiac hypertrophy. For example, we highlight: (i) changes in metabolic genes and proteins in the time course of hypertrophic growth and contractile impairment; (ii) identification of RNA splicing changes in the expression of Tpm2 isoforms between RV and LV; and (iii) novel transcripts and genes likely contributing to the pathogenesis of heart failure. We plan to extend these data with additional environmental and genetic models of heart failure to decipher common and distinct molecular changes in heart diseases of different aetiologies.Database URLhttps://shiny.dieterichlab.org/app/tacoma
Mechanical stability and unfolding pathways of parallel tetrameric G-quadruplexes probed by pulling simulations
Authors: Zhang Zhengyue , Mlýnský Vojtěch , Krepl Miroslav , Šponer Jiří , Stadlbauer Petr 
Published: January 2024

AbstractGuanine-quadruplex (GQ) is a noncanonical nucleic acid structure formed by guanine-rich DNA and RNA sequences. Folding of GQs is a complex process, many aspects of which remain elusive, despite being important for understanding of structure formation and biological functions of GQs. Pulling experiments are a common tool for acquiring insights into the folding landscape of GQs. Herein, we applied a computational pulling strategy – Steered Molecular Dynamics (SMD) simulations – combined with standard Molecular Dynamics (MD) simulations to explore the unfolding landscapes of tetrameric parallel GQs. We identified anisotropic properties of elastic conformational changes, unfolding transitions, and GQ mechanical stabilities. The vertical component of pulling force (perpendicular to the average G-quartet plane) plays a significant role in disrupting GQ structures and weakening their mechanical stabilities. We demonstrated that the magnitude of vertical force component depends on the pulling anchor positions and the number of G-quartets. Typical unfolding transitions for tetrameric parallel GQs involve base unzipping, opening of the G-stem, strand slippage and rotation to cross-like structures. The unzipping was detected as the first and dominant unfolding event and it usually started at the 3’-end. Furthermore, results from both SMD and standard MD simulations indicate that partial spiral conformations serve as a transient ensemble during the (un)folding of GQs.
Accuracy optimized neural networks do not effectively model optic flow tuning in brain area MSTd
Authors: Layton Oliver W. , Steinmetz Scott T. 
Published: January 2024

AbstractAccuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model proposed by Beyeler, Dutt, & Krichmar (2016), which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to MSTd-like optic flow tuning, we created additional CNN model variants that implement key NNMF constraints — non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer’s self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite their poor accuracy, however, neurons in the networks with the nonnegativity constraint give rise to tuning properties that align more closely with those observed in primate MSTd. Interestingly, the addition of the sparsity constraint has a negligible effect on the accuracy of self-motion estimates and model tuning properties. Across all models, we consistently observe the 90-degree offset in the preferred translation and rotation directions found in MSTd neurons, which suggests that this property could emerge through a range of potential computational mechanisms. This work offers a step towards a deeper understanding of the computational properties and constraints that describe optic flow tuning primate area MSTd.Significance StatementOne of the most exciting developments in visual neuroscience over the past decade is that convolutional artificial neural networks optimized to accurately categorize natural images effectively model neural activity in ventral visual areas of the primate brain. We explored whether accuracy-optimized neural networks account for well-established properties of MSTd, a brain area in the complementary primate dorsal stream that is involved in self-motion perception during navigation. Our findings indicate that such networks depart substantially from MSTd-like tuning, which suggests the computational goal of MSTd may not be to accurately estimate self-motion. We found that adding computational constraints inspired by an existing MSTd model that performs dimensionality reduction on afferent motion signals improves the correspondence with MSTd.
Transient destabilization of whole brain dynamics induced by DMT
Authors: Piccinini Juan Ignacio , Perl Yonatan Sanz , Pallavicini Carla , Deco Gustavo , Kringelbach Morten , Nutt David , Carhart-Harris Robin , Timmermann Christopher , Tagliazucchi Enzo 
Published: January 2024

AbstractThe transition towards the brain state induced by psychedelic drugs is frequently neglected in favor of a static description of their acute effects. We used a time-dependent whole-brain model to reproduce large-scale brain dynamics measured with fMRI from 15 volunteers under 20 mg intravenous N,N-Dimethyltryptamine (DMT), a short-acting psychedelic. To capture its transient effects, we parametrized the proximity to a global bifurcation using a pharmacokinetic equation. Simulated perturbations revealed a transient of heightened reactivity concentrated in fronto-parietal regions and visual cortices, correlated with serotonin 5HT2a receptor density, the primary target of psychedelics. These advances suggest a mechanism to explain key features of the psychedelic state and also predicts that the temporal evolution of these features aligns with pharmacokinetics. Our results contribute to understanding how psychedelics introduce a transient where minimal perturbations can achieve a maximal effect, shedding light on how short psychedelic episodes may extend an overarching influence over time.
Trajectory inference from single-cell genomics data with a process time model
Authors: Fang Meichen , Gorin Gennady , Pachter Lior 
Published: January 2024

AbstractSingle-cell transcriptomics experiments provide gene expression snapshots of heterogeneous cell populations across cell states. These snapshots have been used to infer trajectories and dynamic information even without intensive, time-series data by ordering cells according to gene expression similarity. However, while single-cell snapshots sometimes offer valuable insights into dynamic processes, current methods for ordering cells are limited by descriptive notions of “pseudotime” that lack intrinsic physical meaning. Instead of pseudotime, we propose inference of “process time” via a principled modeling approach to formulating trajectories and inferring latent variables corresponding to timing of cells subject to a biophysical process. Our implementation of this approach, called Chronocell, provides a biophysical formulation of trajectories built on cell state transitions. The Chronocell model is identifiable, making parameter inference meaningful. Furthermore, Chronocell can interpolate between trajectory inference, when cell states lie on a continuum, and clustering, when cells cluster into discrete states. By using a variety of datasets ranging from cluster-like to continuous, we show that Chronocell enables us to assess the suitability of datasets and reveals distinct cellular distributions along process time that are consistent with biological process times. We also compare our parameter estimates of degradation rates to those derived from metabolic labeling datasets, thereby showcasing the biophysical utility of Chronocell. Nevertheless, based on performance characterization on simulations, we find that process time inference can be challenging, highlighting the importance of dataset quality and careful model assessment.
Modified FRAX Score for Prediction of Fall-induced Hip Fractures; The Added Value of Fall Energy, Number, and Social Vulnerability Index
Authors: Taseh Atta , Sirls Evan , Casey George , Hearns Sarah , Doornberg Job N. , Lozano-Calderon Santiago A. , Harris Mitchel B , Ashkani-Esfahani Soheil 
Published: January 2024

AbstractBackgroundThe Fracture Risk Assessment Tool (FRAX), widely used for predicting the 10-year likelihood of hip fractures, does not incorporate factors like prior falls and sociodemographic characteristics, notably the Social Vulnerability Index (SVI). Recognizing these limitations, we aim to evaluate the predictive accuracy of FRAX by integrating fall frequency, fall energy, and SVI into the model for assessing the risk of fall-induced hip fractures.MethodsA retrospective case-control study was conducted, and patients aged ≥ 40 years with a documented diagnosis of a fall-induced hip fracture were age-matched with controls with a history of falls without an associated hip fracture. Basic demographic data, along with information about the number of prior falls and the energy of the current falls, were collected. The FRAX and SVI were calculated accordingly. Logistic regression analysis was employed to identify significant predictors. The performance of the models was evaluated and reported using appropriate metrics. Baseline characteristics of the dataset were presented as medians with interquartile ranges (IQR) or as percentages, where applicable. The significance of the identified variables was quantified using Odds Ratio (OR) along with their 95% Confidence Interval (CI). A p-value threshold of 0.05 was set for statistical significance.ResultsA total of 261 patients per group were included with a median age of 74 (IQR 67-80) and 72 (IQR 62-83) years. The FRAX score was significantly associated with the likelihood of experiencing a fall-induced hip fracture, as indicated by an OR of 1.06 (CI: 1.03-1.09). Participants with a one-time history of falls had an OR of 1.58 (CI: 1.02-2.37), compared to 1.84 (CI: 1.09-3.1) for those with multiple falls. The white race, along with the Housing Type and Transportation domain of the SVI, also demonstrated to play a role (OR= 2.85 (CI: 1.56-5.2) and OR= 0.3 (CI: 0.12-0.8), respectively).ConclusionThis study underscored the significance of factors such as fall frequency, SVI, and race in predicting fall-induced hip fractures. It also highlighted the need for further refinement of the FRAX tool. We recommend that future research should be focused on validating the impact of these sociodemographic and fall characteristics on a broader scale, along with exploring the implications of clinical surrogates related to falls.
Longitudinal Study on Seroprevalence and Immune Response to SARS-CoV-2 in a Population of Food and Retail Workers Through Transformation of ELISA Datasets
Authors: Djaïleb Abdelhadi , Parker Megan-Faye , Lavallée Étienne , Stuible Matthew , Durocher Yves , Thériault Mathieu , Santerre Kim , Gilbert Caroline , Boudreau Denis , Baz Mariana , Masson Jean-Francois , Langlois Marc-André , Trottier Sylvie , Quaglia Daniela , Pelletier Joelle N. 
Published: January 2024

AbstractSince the onset of the global pandemic caused by the emergence and spread of SARS-CoV-2 in early 2020, numerous studies have been conducted worldwide to understand our immune response to the virus. This study investigates the humoral response elicited by vaccination and by SARS-CoV-2 infection in the poorly studied food and retail workers in the Québec City area. The 1.5-year study period spans from early 2021, when vaccination became available in this region, to mid-2022, following waves of virulence due to the emergence of the first Omicron variants. Cross-correlated with data on workplace protective measures, pre-existing conditions, activities and other potentially relevant factors, this longitudinal study applies recently developed ELISA data transformation to our dataset to obtain normal distribution. This unlocked the possibility to use the ANOVA-Welsh method for statistical analysis to obtain a statistical perspective of the serological response. Our work allows the identification of factors contributing to statistically relevant differences in the humoral response of the cohort and strengthens the utility of the use of decentralized approaches to serological analysis.