bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparison Study between Autism Spectrum Disorder and Typically Control in Graph Frequency Bands Using Graph and Triadic Interaction Metrics
Authors: Jafadideh Alireza Talesh , Mohammadzadeh Asl Babak 
Published: November 2021

AbstractMany researchers using many different approaches have attempted to find features discriminating between autism spectrum disorder (ASD) and typically control (TC) subjects. In this study, this attempt has been continued by analyzing global metrics of functional graphs and metrics of functional triadic interactions of the brain in the low, middle, and high-frequency bands (LFB, MFB, and HFB) of the structural graph. The graph signal processing (GSP) provided the combinatorial usage of the functional graph of resting-state fMRI and structural graph of DTI. In comparison to TCs, ASDs had significantly higher clustering coefficients in the MFB, higher efficiencies and strengths in the MFB and HFB, and lower small-world propensity in the HFB. These results show over-connectivity, more global integration, and probably decreased local specialization in ASDs compared to TCs. Triadic analysis showed that the numbers of unbalanced triads were significantly lower for ASDs in the MFB. This finding may show the reason for restricted and repetitive behavior in ASDs. Also, in the MFB and HFB, the numbers of balanced triads and the energies of triadic interactions were significantly higher and lower for ASDs, respectively. These findings may reflect the disruption of the optimum balance between functional integration and specialization. All of these results demonstrated that the significant differences between ASDs and TCs existed in the MFB and HFB of the structural graph when analyzing the global metrics of the functional graph and triadic interaction metrics. In conclusion, the results demonstrate the promising perspective of GSP for attaining discriminative features and new knowledge, especially in the case of ASD.
Graphical Abstract
A Method for Computationally Constructing Eukaryotic Synthetic Signal Peptide Sequences
Authors: Daly Grant T. , Prakash Aishwarya , Benton Ryan G. , Johnsten Tom 
Published: November 2021

ABSTRACTWe developed a computational method for constructing synthetic signal peptides from a base set of signal peptides (SPs) and non-SP sequences. A large number of structured “building blocks”, represented as m-step ordered pairs of amino acids, are extracted from the base. Using a straightforward procedure, the building blocks enable the construction of a diverse set of synthetic SPs that could be utilized for industrial and therapeutic purposes. We have validated the proposed methodology using existing sequence prediction platforms such as Signal-BLAST and MULocDeep. In one experiment, 9,555 protein sequences were generated from a large randomly selected set of “building blocks”. Signal-BLAST identified 8,444 (88%) of the sequences as signal peptides. In addition, the Signal-BLAST tool predicted that the generated synthetic sequences belonged to 854 distinct eukaryotic organisms. Here, we provide detailed descriptions and results from various experiments illustrating the potential usefulness of the methodology in generating signal peptide protein sequences.
Systematic in silico discovery of novel solute carrier-like proteins from proteomes
Authors: Gyimesi Gergely , Hediger Matthias A. 
Published: November 2021

AbstractSolute carrier (SLC) proteins represent the largest superfamily of transmembrane transporters. While many of them play key biological roles, their systematic analysis has been hampered by their functional and structural heterogeneity. Based on available nomenclature systems, we hypothesized that many as yet unidentified SLC transporters exist in the human genome, which await further systematic analysis. Here, we present criteria for defining “SLC-likeness” to curate a set of “SLC-like” protein families from the Transporter Classification Database (TCDB) and Protein families (Pfam) databases. Computational sequence similarity searches surprisingly identified ∼120 more proteins in human with potential SLC-like properties compared to previous annotations. Interestingly, several of these have documented transport activity in the scientific literature. To complete the overview of the “SLC-ome”, we present an algorithm to classify SLC-like proteins into protein families, investigating their known functions and evolutionary relationships to similar proteins from 6 other clinically relevant experimental organisms, and pinpoint structural orphans. We envision that our work will serve as a stepping stone for future studies of the biological function and the identification of the natural substrates of the many under-explored SLC transporters, as well as for the development of new therapeutic applications, including strategies for personalized medicine and drug delivery.
Host exposure to symbionts and ecological drift generate divergence in parasite community assembly
Authors: Grunberg Rita L. , Joyner Brooklynn N. , Mitchell Charles E. 
Published: November 2021

AbstractThe initial colonization of a host by symbionts, ranging from parasites to mutualists, can generate priority effects that alter within-host interactions and the trajectory of parasite community assembly. At the same time, variation in parasite communities among hosts can also stem from stochastic processes. Community ecology theory posits that multiple processes (e.g. dispersal, selection and drift) interact to generate variation in community structure, but these processes are rarely considered simultaneously during community assembly. To test the role of these processes in a parasite community, we experimentally simulated dispersal of three symbionts by factorially inoculating individual plants of tall fescue with two foliar fungal parasites, Colletotrichum cereale and Rhizoctonia solani, and a hypothesized mutualist endophyte, Epichloë coenophiala. We then tracked parasite infections longitudinally in the field. After the initial inoculations, hosts were exposed to a common pool of parasites in the field, which we expected to cause parasite communities to converge towards a similar community state. To test for convergence, we analyzed individual hosts’ parasite community trajectories in multivariate space. In contrast to our expectation, there was no signal of convergence. Instead, parasite community trajectories generally diverged over time between treatment groups and the magnitude of divergence depended on the symbiont species inoculated. Parasite communities of hosts that were inoculated with only the mutualist, Epichloë, showed significant trends of divergence relative to all other symbiont inoculation treatments. In contrast, hosts inoculated with only Rhizoctonia did not exhibit clear trends of divergence when compared to other parasite inoculations. Further, co-inoculation with both parasite species resulted in faster rates of divergence and greater temporal change in parasite communities relative to hosts inoculated with only the parasite Colletotrichum. As predicted by existing theory, parasite communities showed evidence of drift during the beginning of the experiment, which contributed to among-host divergence in parasite community structure. Overall, these data provide evidence that initial dispersal of symbionts produced persistent changes in parasite community structure via ecological selection, that drift was important during the early stages of parasite community assembly, and together, dispersal, selection and drift resulted in parasite community divergence.Open Research statementThe data and code that support the findings of this study are available through Zenodo at https://doi.org/10.5281/zenodo.5714452
Putting the theory into ‘burstlet theory’: A biophysical model of bursts and burstlets in the respiratory preBötzinger complex
Authors: Phillips Ryan S. , Rubin Jonathan E. 
Published: November 2021

AbstractInspiratory breathing rhythms arise from synchronized neuronal activity in a bilaterally distributed brainstem structure known as the preBötzinger complex (preBötC). In in vitro slice preparations containing the preBötC, extracellular potassium must be elevated above physiological levels (to 7 − 9 mM) to observe regular rhythmic respiratory motor output in the hypoglossal nerve to which the preBötC projects. Reexamination of how extracellular K+ affects preBötC neuronal activity has revealed that low amplitude oscillations persist at physiological levels. These oscillatory events are sub-threshold from the standpoint of transmission to motor output and are dubbed burstlets. Burstlets arise from synchronized neural activity in a rhythmogenic neuronal subpopulation within the preBötC that in some instances may fail to recruit the larger network events, or bursts, required to generate motor output. The fraction of subthreshold preBötC oscillatory events (burstlet fraction) decreases sigmoidally with increasing extracellular potassium. These observations underlie the burstlet theory of respiratory rhythm generation. Experimental and computational studies have suggested that recruitment of the non-rhythmogenic component of the preBötC population requires intracellular Ca2+ dynamics and activation of a calcium-activated non-selective cationic current. In this computational study, we show how intracellular calcium dynamics driven by synaptically triggered Ca2+ influx as well as Ca2+ release/uptake by the endoplasmic reticulum in conjunction with a calcium-activated non-selective cationic current can explain all of the key observations underlying the burstlet theory of respiratory rhythm generation. Thus, we provide a mechanistic basis to unify the experimental findings on rhythm generation and motor output recruitment in the preBötC.
Constructing threat probability, fear behaviour, and aversive prediction error in the brainstem
Authors: Strickland Jasmin A. , McDannald Michael A. 
Published: November 2021

AbstractWhen faced with potential threat we must estimate its probability, respond advantageously, and leverage experience to update future estimates. Threat estimates are the proposed domain of the forebrain, while behaviour is elicited by the brainstem. Yet, the brainstem is also a source of prediction error, a learning signal to acquire and update threat estimates. Neuropixels probes allowed us to record single-unit activity across a 21-region brainstem axis during probabilistic fear discrimination with foot shock outcome. Against a backdrop of diffuse behaviour signaling, a brainstem network with a dorsal hub signaled threat probability. Neuronal function remapping during the outcome period gave rise to brainstem networks signaling prediction error and shock on multiple timescales. The results reveal construction of threat probability, behaviour, and prediction error along a single brainstem axis.One-Sentence SummaryThe brainstem constructs threat probability, behaviour, and prediction error from neuronal building blocks.
Short-Term Effects of Strengthening Exercises of Lower Limb Rehabilitation Protocol on Pain, Stiffness, Physical Function and Body Mass Index among Knee Osteoarthritis Participants Who Were Overweight or Obese: A Clinical Trial
Authors: Rafiq Muhammad Tariq , Abdul Hamid Mohamad Shariff , Hafiz Eliza 
Published: November 2021

AbstractBackgroundOsteoarthritis (OA) of the knee is defined as a progressive disease of the synovial joints and is characterized by wear and tear of cartilage and underlying bone. This study aimed to determine the short-term effects of the lower limb rehabilitation protocol (LLRP) on pain, stiffness, physical function, and body mass index (BMI) among knee OA participants who were overweight or obese.MethodologySingle blinded randomized controlled trial of one-month duration was conducted at Rehmatul-Lil-Alameen Postgraduate Institute, Lahore, Pakistan. Fifty overweight or obese participants with knee OA were randomly divided into two groups by a computer-generated number. Participants in the Rehabilitation Protocol Group (RPG) were provided with leaflets explaining the strengthening exercises of the LLRP and instruction of daily care (IDC), while the participants in the Control Group (CG) were provided with leaflets explaining IDC only for a duration of four weeks. The primary outcome measures were the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores for pain, stiffness, and physical function. The secondary outcome measures were BMI, exercise adherence, and patients’ satisfaction by the numeric rating scale ranging from 0 to 10. Paired Samples t-test was used to analyze the differences within groups from baseline to post-test evaluations. The analysis of variance 2 × 2 factor was used to analyze the difference of BMI, knee pain, stiffness, and physical function between the groups.ResultsParticipants in the RPG and CG reported a statistically significant reduction in knee pain, and stiffness (p ≤ 0.05) within group. The reduction in the scores of knee pain was higher in participants of the RPG than the CG (p = 0.001). Additionally, participants in the RPG reported greater satisfaction (p = 0.001), higher self-reported exercise adherence (p = 0.010) and coordinator-reported exercise adherence (p = 0.046) compared to the participants in the CG.ConclusionShort-term effects of the LLRP appear to reduce knee pain and stiffness only, but not physical function and BMI.TRIAL REGISTRATIONName: Iranian Registry of Clinical TrialsNumber: IRCT20191221045846N2Date of registration: June 28, 2020Registration timing: prospective
Turning green: the impact of changing to more eco-friendly respiratory healthcare. A carbon and cost analysis of Dutch prescription data
Authors: Have Pieter ten , van Hal Peter Th. W. , Wichers Iris , Kooistra Johan , Hagedoorn Paul , Brakema Evelyn , Chavannes Niels , de Heer Pauline , Ossebaard Hans C 
Published: November 2021

AbstractObjectivesDry powder inhalers (DPIs) and soft mist inhalers have a substantially lower global warming potential than pressurized metered-dose inhalers (pMDIs). To help mitigate climate change, we assessed the potential emission reduction in CO2-equivalents when replacing pMDIs by non-propellant inhalers in Dutch respiratory healthcare, and estimated the associated costs.DesignWe performed a four-step analysis based on data from two national databases of two independent governmental bodies (the Dutch National Healthcare Institute and the Dutch Healthcare Authority). First, we calculated the number of patients with chronic obstructive pulmonary disease and asthma that were using inhalation medication (2020). Second, we calculated the number and total of daily defined doses of pMDIs and non-propellant inhalers (NPIs) that include dry powder inhalers and soft mist inhalers, as well as the number of spacers per patient dispensed by non-hospital based pharmacies in 2020. Third, we estimated the potential reduction in greenhouse gas emission if 70% of patients would switch from using pMDIs to using NPIs as eco-friendly alternatives. Fourth, we performed a budget impact analysis.ResultsIn 2020, 1.4 million patients used inhalers for COPD or asthma treatment. A total of 460 million defined daily doses (DDDs) from inhalers were dispensed, of which – after the exclusion of nebulizers – 50.4% through pMDIs. We estimated that this usage could be reduced by 70% which would lead to an annual reduction in greenhouse gas emission of 77 - 84 million kg. CO2-eq. saving at best EUR 49.8 million per year.ConclusionsIn the Netherlands, substitution of pMDIs to NPIs for eligible patients is theoretically safe and in accordance with medical guidelines, while reducing greenhouse gas emission by 80 million kg. CO2-eq. on average and saving at best EUR 49.8 million per year. This study confirms the potential climate and economic benefit of delivering a more eco-friendly respiratory care.Strengths and limitations of this studyGiven availability and reliability of the data, the present analysis can easily be replicated elsewhere which allows for international comparison and aggregation.Implementation challenges remain underexposed.
Modelling of time-to-events in an ambispective study: illustration with the analysis ofABOblood groups on venous thrombosis recurrence
Authors: Munsch Gaëlle , Goumidi Louisa , van Hylckama Vlieg Astrid , Ibrahim-Kosta Manal , Bruzelius Maria , Deleuze Jean-François , Rosendaal Frits R. , Jacqmin-Gadda Hélène , Morange Pierre-Emmanuel , Trégouët David-Alexandre 
Published: November 2021

ABSTRACTIn studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. In an ambispective design, when the risk factors studied are independent of time, including both pre- and post-inclusion events in the analyses increases the statistical power but may lead to a selection bias. To avoid such a bias, we propose a survival analysis weighted by the inverse of the survival probability at the time of data collection about the events.This method is applied to the study of the association of ABO blood groups with the risk of venous thromboembolism (VT) recurrence in the MARTHA and MEGA cohorts. The former relying on an ambispective design and the latter on a standard prospective one. In the combined sample totalling 2,752 patients including 993 recurrences, compared with the O1 group, A1 has an increased risk (Hazard Ratio (HR) of 1.18, p=4.2×10−3), homogeneously in MARTHA and in MEGA. The same trend (HR=1.19, p=0.06) was observed for the less frequent A2 group.In conclusion, this work clarified the association ofABOblood groups with the risk of VT recurrence. Besides, the methodology proposed here to analyse time-independent risk factors of events in an ambispective design has an immediate field of application in the context of genome wide association studies.
Meta-topologies define distinct anatomical classes of brain tumors linked to histology and survival
Authors: Kernbach Julius M. , Delev Daniel , Neuloh Georg , Clusmann Hans , Bzdok Danilo , Eickhoff Simon B. , Staartjes Victor E. , Vasella Flavio , Weller Michael , Regli Luca , Serra Carlo , Krayenbühl Niklaus , Akeret Kevin 
Published: November 2021

AbstractBackgroundThe current WHO classification integrates histological and molecular features of brain tumors. The aim of this study was to identify generalizable topological patterns with the potential to add an anatomical dimension to the classification of brain tumors.MethodsWe applied non-negative matrix factorization as an unsupervised pattern discovery strategy to the fine-grained topographic tumor profiles of 936 patients with primary and secondary brain tumors. From the anatomical features alone, this machine learning algorithm enabled the extraction of latent topological tumor patterns, termed meta-topologies. The optimal parts-based representation was automatically determined in 10,000 split-half iterations. We further characterized each meta-topology’s unique histopathologic profile and survival probability, thus linking important biological and clinical information to the underlying anatomical patternsResultsIn primary brain tumors, six meta-topologies were extracted, each detailing a transpallial pattern with distinct parenchymal and ventricular compositions. We identified one infratentorial, one allopallial, three neopallial (parieto-occipital, frontal, temporal) and one unisegmental meta-topology. Each meta-topology mapped to distinct histopathologic and molecular profiles. The unisegmental meta-topology showed the strongest anatomical-clinical link demonstrating a survival advantage in histologically identical tumors. Brain metastases separated to an infra- and supratentorial meta-topology with anatomical patterns highlighting their affinity to the cortico-subcortical boundary of arterial watershed areas.ConclusionsUsing a novel data-driven approach, we identified generalizable topological patterns in both primary and secondary brain tumors Differences in the histopathologic profiles and prognosis of these anatomical tumor classes provide insights into the heterogeneity of tumor biology and might add to personalized clinical decision making.
Efficacy of vasopressin, steroid, and epinephrine protocol for in-hospital cardiac arrest resuscitation: A systematic review and meta-analysis of randomized controlled trials with trial sequential analysis
Authors: Satti Danish Iltaf , Lee Yan Hiu Athena , Leung Keith Sai Kit , Hui Jeremy Man Ho , Kot Thompson Ka Ming , Babar Arslan , Wai Abraham KC , Liu Tong , Roever Leonardo , Tse Gary , Chan Jeffrey Shi Kai ,   International Health Informatics Study (IHIS) Network
Published: November 2021

AbstractAimTo assess the effect of vasopressin, steroid and epinephrine (VSE) combination therapy on return of spontaneous circulation (ROSC) after in-hospital cardiac arrest (IHCA), and test the conclusiveness of evidence using trial sequential analysis (TSA).MethodsThe systematic search included PubMed, EMBASE, Scopus, and Cochrane Central Register of Controlled Trials. Randomized controlled trials that included adult patients with in-hospital cardiac arrest, with at least one group receiving combined vasopressin, epinephrine and steroid therapy were selected. Data was extracted independently by two reviewers. The main outcome of interest was ROSC. Other outcomes included survival to hospital discharge with good neurological outcomes and survival to 30 and 90 days with good neurological outcomes.ResultsWe included a total of three randomized controlled trials (n=869 patients). Results showed that Vasopressin, steroid and epinephrine combination therapy increased return of spontaneous circulation (risk ratio, 1.32; 95% CI, 1.18-1.47) as compared to placebo. Trial sequential analysis demonstrated that the existing evidence is conclusive. This was also validated by the alpha-spending adjusted relative risk (1.32 [1.16, 1.49], p<0.0001). Other outcomes could not be meta-analysed due to differences in timeframe in the included studies.ConclusionsVSE combination therapy administered in cardiopulmonary resuscitation led to improved rates of return of spontaneous circulation. Future trials of vasopressin, steroid and epinephrine combination therapy should evaluate survival to hospital discharge, neurological function and long-term survival.