bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protein Fold Classification using Graph Neural Network and Protein Topology Graph
Authors: Sayeed Suri Dipannita , Wolf Jan Niclas , Koch Ina , Song Guang 
Published: August 2022

AbstractProtein fold classification reveals key structural information about proteins that is essential for understanding their function. While numerous approaches exist in the literature that classifies protein fold from sequence data using machine learning, there is hardly any approach that classifies protein fold from the secondary or tertiary structure data using deep learning. This work proposes a novel protein fold classification technique based on graph neural network and protein topology graphs. Protein topology graphs are constructed according to definitions in the Protein Topology Graph Library from protein secondary structure level data and their contacts. To the best of our knowledge, this is the first approach that applies graph neural network for protein fold classification. We analyze the SCOPe 2.07 data set, a manually and computationally curated database that classifies known protein structures into their taxonomic hierarchy and provides predefined labels for a certain number of entries from the Protein Data Bank. We also analyze the latest version of the CATH data set. Experimental results show that the classification accuracy is at around 82% − 100% under certain settings. Due to the rapid growth of structural data, automating the structure classification process with high accuracy using structural data is much needed in the field. This work introduces a new paradigm of protein fold classification that meets this need. The implementation of the model for protein fold classification and the datasets are available here https://github.com/SuriDipannitaSayeed/ProteinFoldClassification.gitAuthor summaryClassification of protein structures is traditionally done using manual curation, evolutionary relationship, or sequence comparison-based methods. Applying machine learning and deep learning to protein structure classification is a comparatively new trend that holds great promises for automating the structure classification process. Advance deep learning technique like Graph Neural Network is still unexplored in this respect. SCOP and CATH are two traditional databases that provide the hierarchical taxonomic classification of protein structures. This work provides a novel computational approach that classifies protein folds in SCOP and CATH with graph neural network, performing a graph classification task.
Cortical distribution of neurofilaments associates with pathological hallmarks and MRI measures of atrophy and diffusivity in Parkinson’s disease
Authors: Frigerio Irene , Laansma Max A , Lin Chen-Pei , Hermans Emma JM , Bouwman Maud MA , Bol John GJM , Galis-de Graaf Yvon , Hepp Dagmar H , Rozemuller Annemieke JM , Barkhof Frederik , van de Berg Wilma DJ , Jonkman Laura E 
Published: August 2022

AbstractIncreased neurofilament levels in biofluids, commonly used as a proxy for axonal degeneration in the brain, have been found in Parkinson’s disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB), and correlate with MRI biomarkers. The aim of the current study was to unravel the regional distribution of cortical neurofilaments and their association with pathology load and MRI measures of atrophy and diffusivity in the post-mortem brain.Using a within-subject post-mortem MRI-pathology approach, we included 9 PD, 12 PDD/DLB and 18 age-matched control donors. Cortical thickness and mean diffusivity (MD) metrics were extracted respectively from 3DT1 and DTI at 3Tin-situMRI. After autopsy, pSer129 alpha-synuclein (pSer129-αSyn), p-tau, and amyloid-beta, together with neurofilament light-chain (NfL) and phosphorylated neurofilament medium- and heavy-chain (p-NfM/H) immunoreactivity were quantified in 7 cortical regions, and studied in detail with confocal-laser scanning microscopy. The correlations between MRI and pathological measures were studied using linear mixed models.Compared to controls, p-NfM/H immunoreactivity was increased in all cortical regions in PD and PDD/DLB, whereas NfL immunoreactivity was mainly increased in the parahippocampal and entorhinal cortex in PDD/DLB. NfL-positive neurons showed degenerative morphological features and axonal fragmentation. Increased p-NfM/H correlated with p-tau load, and NfL correlated with pSer129-αSyn but more strongly with p-tau load in PDD/DLB. Lastly, neurofilament immunoreactivity correlated with cortical thinning in PD and with increased cortical MD in PDD/DLB.Taken together, increased neurofilament immunoreactivity suggests underlying axonal injury and neurofilament accumulation in morphologically altered neurons with increasing pathological burden. Importantly, we demonstrate that such neurofilament markers at least partly explain MRI measures that are associated with the neurodegenerative process.
A contractile injection system mediates developmentally regulated intra-strain cell death in Streptomyces coelicolor
Authors: Vladimirov Maria , Zhang Ruo , Mak Stefanie , Nodwell Justin R. , Davidson Alan R. 
Published: August 2022

AbstractExtracellular contractile injection systems (eCIS) are encoded in diverse clades of bacterial species. Although closely related to contractile phage tails, these entities can inject toxic proteins into eukaryotic cells. The roles of eCIS in mediating cytotoxic activities has led to a view of them as defense mechanisms that are not central to normal bacterial lifecycles. Here, we provide evidence that eCIS play an entirely distinct role in Streptomyces coelicolor (Sco), where they appear to participate in the complex developmental process of this species. In particular, we have shown that Sco produces eCIS particles as a part of its normal growth cycle and that strains lacking functional eCIS particles exhibit pronounced alterations in their developmental program. Most intriguingly, eCIS-deficient mutants display significantly reduced levels of cell death and altered morphology during liquid growth. These data suggest that Sco eCIS function by inducing intra-strain lethality rather than by attacking foreign species.
HIV-1 latent infection triggers broader epigenomic and transcriptional changes in protein-coding and long non-coding RNAs than active infection of SupT1 cells
Authors: Lê-Bury Gabrielle , Chen Yao , Rhen Jordan M. , Grenier Jennifer K. , Singhal Amit , Russell David G. , Boliar Saikat 
Published: August 2022

ABSTRACTLatent HIV-1 infection poses a major challenge in complete viral remission and cure. HIV-1 latency is a multi-dimensional, dynamic process and many aspects of how the viral latency is established and maintained still remains incompletely characterized. Here, we have investigated the host chromatin organization and transcriptomic changes in active- and latently-infected SupT1 cells. We employed an in vitro model of HIV-1 latency in SupT1 cells using a dual-reporter virus, HIVGKO, which enables high purity sorting and characterization of active- and latently-infected cells. We found a significant divergence in chromatin organization and gene expression pattern between active and latent infection compared to uninfected cells. Latent infection results in a repressive reorganization of the host chromatin, while active infection leads to an overall increase in chromatin accessibility. A stronger correlation was also observed between chromatin accessibility and gene expression in latent infection, which was manifested in a greater alteration of the cellular transcriptome in latent than active infection, for both protein-coding and long-non-coding RNAs (lncRNAs). We identified a number of novel lncRNAs associated with either active and latent infection. A reversal in expression pattern of latency-associated lncRNAs following PMA-induced reactivation indicated their infection-state-specific expression and potential roles in HIV-1 latency. Taken together, this integrated, comparative study revealed that latent HIV-1 infection requires a substantially greater alteration in cellular epigenome and transcriptome. Understanding of the distinct cellular states conducive to active and latent infection may support devising strategies for specific modulation of host cellular functions as a curative intervention for HIV-1.
Nanopore Translocation of Topologically Linked DNA Catenanes
Authors: Rheaume Sierra N. , Klotz Alexander R. 
Published: August 2022

AbstractThe electrical signal associated with a biopolymer translocating through a nanoscale pore depends depends on the size, topology, and configuration of each molecule. Building upon recent interest in using solid-state nanopores for studying the topology of knotted and supercoiled DNA, we present the first experimental observations of topologically linked catenanes translocating through a solid-state nanopore. Using restriction enzymes, linked circular molecules were isolated from the mitochondrial DNA of Crithidia fasciculata, a structure known as a kinetoplast that is comprised of thousands of topologically interlocked minicircles. Digested kinetoplasts produce a spectrum of catenane topologies, which are identified from their nanopore translocation signals by spikes in the blockade current associated with the topological linkages. We identify the translocation signatures of 2-catenanes, linear and triangular 3-catenanes, and several types of 4- and 5-catenanes as well as more complex structures. Measurements of the translocation time of 2- and 3-catenanes suggest that topological friction between the linkages and the pore slows the translocation time of these structures, as predicted in recent simulations.
Group B streptococcal membrane vesicles induce proinflammatory cytokine production and are sensed in an NLRP3 inflammasome-dependent mechanism in human macrophages
Authors: McCutcheon Cole R. , Gaddy Jennifer A. , Aronoff David M. , Manning Shannon D. , Petroff Margaret G. 
Published: August 2022

ABSTRACTGroup BStreptococcus(GBS) is a major cause of fetal and neonatal mortality worldwide. Many of the adverse effects associated with invasive GBS are associated with inflammation that leads to chorioamnionitis, preterm birth, sepsis, and meningitis; therefore, understanding bacterial factors that promote inflammation is of critical importance. Membrane vesicles (MVs), which are produced by many pathogenic and non-pathogenic bacteria, may modulate host inflammatory responses. In mice, GBS MVs injected intra-amniotically can induce preterm birth and fetal death. Although it is known that GBS MVs induce large-scale leukocyte recruitment into infected tissues, the immune effectors driving these responses are unclear. Here, we hypothesized that macrophages respond to GBS-derived MVs by producing proinflammatory cytokines and are recognized through one or more pattern recognition receptors. We show that THP-1 macrophage-like cells produce high levels of neutrophil- and monocyte-specific chemokines in response to MVs derived from different clinical isolates of GBS. Interleukin (IL)-1β was significantly upregulated in response to MVs, which was independent of NF-kB signaling but dependent on both caspase-1 and NLRP3. These data indicate that MVs contain one or more pathogen-associated molecular patterns that can be sensed by the immune system. Furthermore, this study identifies the NLRP3 inflammasome as a novel sensor of GBS MVs. Our data additionally indicate that MVs may serve as immune effectors that can be targeted for immunotherapeutics, particularly given that similar responses were observed across this subset of GBS isolates.
Characteristics of People with Type I or Type II Diabetes with and without a History of Homelessness: A Population-based Cohort Study
Authors: Wiens Kathryn , Bai Li , Austin Peter C , Ronksley Paul E , Hwang Stephen W , Spackman Eldon , Booth Gillian L , Campbell David JT 
Published: August 2022

AbstractIntroductionHomelessness poses unique barriers to diabetes management. Population-level data on the risks of diabetes outcomes among people experiencing homelessness are needed to inform resource investment. The aim of this study was to create a population cohort of people with diabetes with a history of homelessness to understand their unique demographic and clinical characteristics and improve long-term health outcomes.MethodsOntario residents with diabetes were identified in administrative hospital databases between 2006 and 2020. A history of homelessness was identified using a validated algorithm. Demographic and clinical characteristics were compared between people with and without a history of homelessness. Propensity score matching was used to create a cohort of people with diabetes experiencing homelessness matched to comparable non-homeless controls.ResultsOf the 1,455,567 patients with diabetes who used hospital services, 0.7% (n=8,599) had a history of homelessness. Patients with a history of homelessness were younger (mean: 54 vs 66 years), more likely to be male (66% vs 51%) and more likely to live in a large urban centre (25% vs 7%). Notably, they were also more likely to be diagnosed with mental illness (49% vs 2%) and be admitted to a designated inpatient mental health bed (37% versus 1%). A suitable match was found for 5219 (75%) people with documented homelessness. The derived matched cohort was balanced on important demographic and clinical characteristics.ConclusionPeople with diabetes experiencing homelessness have unique characteristics that may require additional supports. Population-level comparisons can inform the delivery of tailored diabetes care and self-management resources.
Risk factors, temporal dependence, and seasonality of human ESBL-producing E. coli and K. pneumoniae colonisation in Malawi: a longitudinal model-based approach
Authors: Sammarro Melodie , Rowlingson Barry , Cocker Derek , Chidziwisano Kondwani , Jacob Shevin T. , Kajumbula Henry , Mugisha Lawrence , Musoke David , Lester Rebecca , Morse Tracy , Feasey Nicholas , Jewell Chris 
Published: August 2022

AbstractBackgroundAntimicrobial resistance (AMR) represents an important threat to achieving the sustainable development goals in Sub-Saharan Africa (sSA). sSA is reported to have the highest estimated death rate attributable to AMR, with Extended-Spectrum Beta-Lactamase-producing Enterobacterales, such as Klebsiella pneumoniae and Escherichia coli, representing the greatest challenge. However, the dynamics of human colonisation with such bacteria in the sSA community setting are not well known. Inadequate water, sanitation and hygiene (WASH) infrastructure and associated behaviours are thought to play an important role in transmission of AMR-bacteria, and an improved understanding of the temporal dynamics of within-household transmission could help inform the design of public health policies that interrupt transmission of AMR-bacteria.Methods and FindingsIn this 18-month study, individuals from households in diverse areas of Southern Malawi were recruited and human stool samples were longitudinally collected. Using microbiological data and household surveys, we built a multivariable hierarchical harmonic logistic regression model to identify risk factors for colonisation with ESBL-producing E. coli and K. pneumoniae, reflecting household structure and temporal correlation of colonisation status between timepoints.Important risk factors were identified, with men having a lower risk of becoming colonised with ESBL-producing E. coli (OR 0.786 CrI[0.678-0.910]) and the use of a tube well or a borehole as a water drinking source highly increasing the risk of becoming colonised (OR 1.550 CrI[1.003-2.394]). Coming into contact with standing water also appeared to be negatively associated with colonisation status (OR 0.749 CrI[0.574-0.978]). For ESBL-producing K. pneumoniae, having recently taken a course of antibiotics increased the risk of being colonised (OR 1.281 CrI[1.049-1.565]). We also found a negative association between eating from shared plates and colonisation with ESBL-producing K. pneumoniae (OR 0.672 CrI[0.460-0.980]). Finally, we detected a temporal correlation range of eight to eleven weeks, providing evidence that within-household transmission occurs within this time frame.ConclusionsWe suggest that interventions aimed at preventing transmission might have the best impact when targeted at the household-level and focused on a combination of improving WASH infrastructure and modifying associated behaviours. Additionally, we showed that antibiotic use is important when looking at colonisation with ESBL-producing K. pneumoniae and therefore infection prevention and control measures and antibiotic use and stewardship training could help in reducing transmission.
ADuLT: An efficient and robust time-to-event GWAS
Authors: Pedersen Emil M. , Agerbo Esben , Plana-Ripoll Oleguer , Steinbach Jette , Krebs Morten Dybdahl , Hougaard David M. , Werge Thomas , Nordentoft Merete , Børglum Anders D. , Musliner Katherine L. , Ganna Andrea , Schork Andrew J. , Mortensen Preben B. , McGrath John J. , Privé Florian , Vilhjálmsson Bjarni J. 
Published: August 2022

AbstractProportional hazards models have previously been proposed to analyse time-to-event phenotypes in genome-wide association studies(GWAS). While proportional hazards models have many useful applications, their ability to identify genetic associations under different generative models where ascertainment is present in the analysed data is poorly understood. This includes widely used study designs such as case-control and case-cohort designs (e.g. the iPSYCH study design) where cases are commonly ascertained.Here we examine how recently proposed and computationally efficient Cox regression for GWAS perform under different generative models with and without ascertainment. We also propose the age-dependent liability threshold model (ADuLT), first introduced as the underlying model for the LT-FH++ method, as an alternative approach for time-to-event GWAS. We then benchmark ADuLT with SPACox and standard case-control GWAS using simulated data with varying degrees of ascertainment. We find Cox regression GWAS to underperform when cases are strongly ascertained (cases are oversampled by a factor larger than 5), regardless of the generative model used. In contrast, we found ADuLT to be robust to case-control ascertainment, while being much faster to run. We then used the methods to conduct GWAS for four psychiatric disorders, ADHD, Autism, Depression, and Schizophrenia in the iPSYCH case-cohort sample, which has a strong case-ascertainment. Summarising across all four mental disorders, ADuLT found 20 independent genome-wide significant associations, while case-control GWAS found 17 and SPACox found 8, consistent with our simulation results.As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information have the opportunity to increase power in analyses. We find that ADuLT to be a robust time-to-event GWAS method that performs on par with or better than Cox-regression GWAS, both in simulations and real data analyses of four psychiatric disorders. ADuLT has been implemented in an R package called LTFHPlus, and is available on GitHub.
NRX-101 (D-cycloserine plus lurasidone) vs. lurasidone for the maintenance of initial stabilization after ketamine in patients with severe bipolar depression with acute suicidal ideation and behavior: A randomized prospective phase 2 trial
Authors: Nierenberg Andrew , Lavin Philip , Javitt Daniel C. , Shelton Richard , Matthew Sanjay , Besthof Robert A , Javitt Jonathan C. 
Published: August 2022

ABSTRACTObjectivesWe tested the hypothesis that after initial improvement with intravenous ketamine in patients with bipolar disorder (BD) with severe depression and acute suicidal thinking or behavior, a fixed-dose combination of oral D-cycloserine (DCS) and lurasidone (NRX-101) can maintain improvement more effectively lurasidone alone.MethodsThis was a multi-center, double-blind, two-stage, parallel randomized trial. Adult BD patients with depression and suicidal ideation or behavior were infused with ketamine or saline (Stage 1); those who improved were randomized to a fixed dose combination of DCS and lurasidone vs. lurasidone alone (Stage 2) to maintain the improvement achieved in Stage 1. Depression was measured by the Montgomery Åsberg Depression Rating Scale (MADRS) and suicidal thinking and behavior was measured by the Columbia Suicide Severity Rating Scale (C-SSRS); global improvement was measured by the clinical global severity scale (CGI-S).ResultsThirty-seven patients were screened and 22 were enrolled, randomized, and treated. All 22 patients treated in Stage 1 (17 with ketamine and 5 with saline) were enrolled into Stage 2 and 11 completed the study. The fixed dose combination of DCS and lurasidone was significantly more effective than lurasidone alone in maintaining improvement in depression (MADRS LMS Δ-7.7; p=.03) and reducing suicidal ideation, as measured by C-SSRS (Δ-1.5; p=0.02) and by CGI-SS (Δ-2.9; p=0.03), and with a non-statistically significant decrease in depressive relapse (0% vs. 40%; p=0.07). This sequential treatment regimen did not cause any significant safety events and demonstrated improvements in patient reported side effects.ConclusionsSequential treatment of a single infusion of ketamine followed by NRX-101 maintenance is a promising therapeutic approach for reducing depression and suicidal ideation in patients with bipolar depression who require hospitalization due to acute suicidal ideation and behavior. On the basis of these findings, Breakthrough Therapy Designation was awarded and a Special Protocol Agreement was granted by the FDA for a registrational trial.
Triple network model of brain connectivity changes related to adverse mood effects in an oral contraceptive placebo-controlled trial
Authors: Hidalgo-Lopez Esmeralda , Engman Jonas , Sundström Poromaa Inger , Gingnell Malin , Pletzer Belinda 
Published: August 2022

AbstractCombined oral contraceptives (COC) are among the most commonly used contraceptive methods worldwide, and mood side effects are the major reason for discontinuation of treatment. We here investigate the directed connectivity patterns associated with the mood side effects of an androgenic COC in a double-blind randomized, placebo-controlled trial in women with a history of affective COC side effects (n=34). We used spectral dynamic causal modeling on a triple network model consisting of the default mode network (DMN), salience network (SN) and executive central network (ECN). Within this framework, we assessed the treatment-related changes in directed connectivity associated with adverse mood side effects. Overall, during COC use, we found a pattern of enhanced connectivity within the DMN and decreased connectivity within the ECN. The dorsal anterior cingulate cortex mediates an increased recruitment of the DMN by the ECN during treatment. Mood lability was the most prominent COC-induced symptom and also arose as the side effect most consistently related to connectivity changes. Connections that were related to increased mood lability showed increased connectivity during COC treatment, while connections that were related to decreased mood lability showed decreased connectivity during COC treatment. Among these, the connections with the highest effect size could also predict the participants’ treatment group above chance.Significance StatementMood side effects are the major reason for discontinuation of oral contraceptive (OC) use. However, the neural substrate underlying these adverse mood effects is still unknown. Here, we investigate the connectivity changes during OC use in women with a history of OC-related mood side effects. We show that mood lability experienced during OC use relates to connectivity patterns previously reported across different mood disorders. The dorsal anterior cingulate cortex, crucial for emotional and cognitive regulation, arose as a mediator area between networks. These neural dynamics during OC treatment may affect cognitive processes underlying mood stability. These findings have important implications for women’s mental health and well-being.