bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardiac Post-acute Sequelae symptoms of SARS-CoV-2 in Community-Dwelling Adults: Cross-sectional Study
Authors: Ogungbe Oluwabunmi , Gilotra Nisha A. , Davidson Patricia M. , Farley Jason E. , Dennison Himmelfarb Cheryl R. , Post Wendy S. , Commodore-Mensah Yvonne 
Published: July 2022

AbstractObjectiveTo examine risk factors for cardiac-related PASC in community-dwelling adults after acute coronavirus disease 2019 (COVID-19) infection.MethodsWe performed a cross-sectional analysis among adults who tested positive for COVID-19. Outcomes were self-reported cardiac-related PASC. We conducted stepwise multivariable logistic regression to assess association between the risk factors (existing cardiovascular disease, pre-existing conditions, days since positive test, COVID hospitalization, age, sex, education, income) and cardiac-related PASC.ResultsAmong a sample of 442 adults, mean(±SD) age was 45.4 (16.2) years, 71% female, 13% Black; 46% reported pre-existing conditions; 23% had cardiovascular (CV) risk factors; and 4% had cardiovascular diseases (CVD). The prevalence of persistent cardiac-related symptoms and newly diagnosed cardiac conditions was 43% and 27%, respectively. The odds for cardiac-related PASC were 2.01 (95%CI: 1.27-3.17) higher in persons with underlying CV risk factors/CVD than in those without. The odds for cardiac-related PASC were higher among persons with underlying pre-existing conditions (adjusted odds ratio aOR: 2.00, 95% CI:1.28-3.10) and among those who were hospitalized (aOR: 3.03, 95%CI:1.58-5.83).ConclusionsMore than a third of persons with COVID-19 reported cardiac-related PASC symptoms. Risk factors for cardiac-related PASC symptoms include underlying CV risk factors/CVD, pre-existing conditions, increasing age, and COVID-19 hospitalization. COVID-19 may play an important role in worsening the prognosis of existing CV risk factors and increasing risk of complications.Key MessagesWhat is already known on this topicInfection with SARS-CoV-2 virus may lead to persistent cardiac symptoms indicative of cardiac injury. COVID-19 may play an important role in worsening the prognosis of existing CVD and pre-existing conditions.What this study addsLittle is known about characterization of cardiac-related Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) and recovery in community-dwelling adults. Hence, this study provides further evidence on the burden of possible cardiac-related PASC symptoms and diagnosed cardiac conditions. The findings also suggest that underlying CVD, pre-existing conditions, older age, and COVID-19 hospitalization, may be risk factors for persistent cardiac-related PASC symptoms.How this study might affect research, practice or policyThese results underscore urgent needs for coordinated efforts directed at resource allocation and optimization of primary care for persons with cardiac PASC and for prevention of resulting CV events and complications
Drivers of COVID-19 policy stringency in 175 countries and territories: COVID-19 cases and deaths, gross domestic products per capita, and health expenditures
Authors: Jalloh Mohamed F. , Zeebari Zangin , Nur Sophia A. , Prybylski Dimitri , Nur Aasli A. , Hakim Avi J. , Winters Maike , Steinhardt Laura C. , Gatei Wangeci , Omer Saad B. , Brewer Noel T. , Nordenstedt Helena 
Published: July 2022

ABSTRACTObjectiveTo understand the associations of COVID-19 cases and deaths with policy stringency globally and regionally.MethodsWe modeled the marginal effects of new COVID-19 cases and deaths on policy stringency (scored 0–100) in 175 countries and territories, adjusting for gross domestic product (GDP) per capita and health expenditure (% of GDP). Time periods examined were March–August 2020, September 2020– February 2021, and March–August 2021.ResultsPolicy response to new cases and deaths was faster and more stringent early in the COVID-19 pandemic (March–August 2020) compared to subsequent periods. New deaths were more strongly associated with stringent policies than new cases. In an average week, 1 new death per 100,000 people was associated with a stringency increase of 2.1 units in March–August 2020, 1.3 units in September 2020–February 2021, and 0.7 units in March–August 2021. New deaths in Africa and the Western Pacific were associated with more stringency than in other regions. Higher health expenditure was associated with less stringent policies. GDP per capita did not have consistent patterns of associations with stringency.ConclusionsOur findings demonstrate the need for enhanced mortality surveillance to ensure policy alignment during health emergencies. Countries that invest less of their GDP in health are inclined to enact stringent policies during health emergencies than countries with more significant health expenditure.
IFNγ insufficiency during mouse intravaginal Chlamydia trachomatis infection exacerbates alternative activation in macrophages with compromised CD40 functions
Authors: Challagundla Naveen , Shah Dhruvi , Dalai Sarat K , Agrawal-Rajput Reena 
Published: July 2022

AbstractChlamydia trachomatis (C.tr), an obligate intracellular pathogen, causes asymptomatic genital infections in women and is also a leading cause of preventable blindness. Limited mouse model of chronic C.tr infection are available to study the host immune response. We have developed in vivo mice models of acute and chronic infections for C. trachomatis to explore the significance of macrophage-directed response in mediating immune activation/suppression. During chronic and repeated infections, IFNγ secretion from T cells is abated while TGFβ and IL-10 secretion is enhanced. An increase in exhaustion (PD1, CTLA4) and anergic (Klrg3, Tim3) T cell markers is also observed during chronic infection. It was observed that alternatively-activated macrophages with low CD40 expression promote Th2 and Treg differentiation and lead to sustained C. trachomatis genital infection. Macrophages infected with C. trachomatis or treated with supernatant of infected epithelial cells drive them to alternately-activated phenotype. C. trachomatis infection prevents increase in CD40 expression. Low IFNγ, as observed in chronic infection leads to incomplete clearance of bacteria and poor immune activation. C. trachomatis decapacitates IFNγ responsiveness in macrophages via hampering IFNγRI and IFNγRII expression which can be correlated with poor expression of MHC-II, CD40, iNOS and NO release even following IFNγ supplementation. Alternatively-activated macrophages during C. trachomatis infection express low CD40 rendering immunosuppressive, Th2 and Treg differentiation which could not be reverted even after IFNγ supplementation. The alternative macrophages also harbour high bacterial load and are poor responders to IFNγ, thus promoting immunosupression. Thus, C. trachomatis modulate the innate immune cells attenuating the anti-chlamydial functions of T cells in a manner that involves decreased CD40 expression on macrophages.
Manipulation of neuronal activity in the entorhinal-hippocampal circuit affects intraneuronal amyloid-β levels
Authors: Bjorkli Christiana , Ebbesen Nora C , Julian Joshua B. , Witter Menno P , Sandvig Axel , Sandvig Ioanna 
Published: July 2022

AbstractOne of the neuropathological hallmarks of Alzheimer’s disease (AD) is the accumulation of amyloid-β (Aβ) plaques, which is preceded by intraneuronal build-up of toxic, aggregated Aβ during disease progression. Aβ plaques are first deposited in the neocortex before appearing in the medial temporal lobe, and tau pathology with subsequent neurodegeneration in the latter anatomical region causes early memory impairments in patients. Current research suggests that early intraneuronal Aβ build-up may begin in superficial layers of lateral entorhinal cortex (LEC). To examine whether manipulation of neuronal activity of LEC layer II neurons affected intraneuronal Aβ levels in LEC and in downstream perforant path terminals in the hippocampus (HPC), we used a chemogenetic approach to selectively and chronically silence superficial LEC neurons in young and aged 3xTg AD mice and monitored its effect on intraneuronal Aβ levels in LEC and HPC. Chronic chemogenetic silencing of LEC neurons led to reduced early intraneuronal Aβ in LEC and in projection terminals in the HPC, compared with controls. Early intraneuronal Aβ levels in the downstream HPC correlated with activity levels in superficial layers of LEC, with the subiculum being the earliest subregion involved, and our findings give evidence to early AD neuropathology originating in select neuronal populations.
Parameter inference for enzyme and temperature constrained genome-scale models
Authors: Pettersen Jakob Peder , Almaas Eivind 
Published: July 2022

ABSTRACTThe metabolism of all living organisms is dependent on temperature, and therefore, having a good method to predict temperature effects at a system level is of importance. A recently developed Bayesian computational framework for enzyme and temperature constrained genome-scale models (etcGEM) predicts the temperature dependence of an organism’s metabolic network from thermodynamic properties of the metabolic enzymes, markedly expanding the scope and applicability of constraint-based metabolic modelling.Here, we show that the Bayesian calculation method for inferring parameters for an etcGEM is unstable and unable to estimate the posterior distribution. The Bayesian calculation method assumes that the posterior distribution is unimodal, and thus fails due to the multimodality of the problem. To remedy this problem, we developed an evolutionary algorithm which is able to obtain a diversity of solutions in this multimodal parameter space.We quantified the phenotypic consequences on six metabolic network signature reactions of the different parameter solutions resulting from use of the evolutionary algorithm. While two of these reactions showed little phenotypic variation between the solutions, the remainder displayed huge variation in flux-carrying capacity. This result indicates that the model is underdetermined given current experimental data and that more data is required to narrow down the model predictions. Finally, we made improvements to the software to reduce the running time of the parameter set evaluations by a factor of 8.5, allowing for obtaining results faster and with less computational resources.
HDAC6 inhibition partially alleviates mitochondrial trafficking defects and restores motor function in human motor neuron and zebrafish models of Charcot-Marie-Tooth Disease Type 2A
Authors: Butler Larissa , Adamson Kathryn I. , Johnson Stuart L. , Jestice Lydia H. , Price Christopher J. , Stavish Dylan , Pooranachandran Niedharsan , Malicki Jarema J. , Tsakiridis Anestis , Grierson Andrew J. , Barbaric Ivana 
Published: July 2022

AbstractCharcot Marie Tooth Disease (CMT) is a group of inherited progressive conditions affecting distal motor and sensory neurons, leading to muscle weakness, pain and loss of sensation in limbs. There are currently no treatments for this debilitating disease. To investigate disease mechanisms and facilitate treatment discovery, here we developed an in vitro model for CMT type 2A by introducing the patient-specific MFN2R94Q mutation into human embryonic stem cells (hESCs). Isogenic mutant and wild-type hESCs differentiated to spinal motor neurons with similar efficiency and gave rise to functional motor neurons in vitro. However, MFN2R94Q/+ spinal motor neurons displayed impaired mitochondrial trafficking, resulting in reduced numbers of mitochondria in distal parts of axons. Importantly, we showed that mitochondrial trafficking defects can be alleviated by treatment with an HDAC6 inhibitor. Chemical and genetic inhibition of HDAC6 also significantly rescued the motor phenotype in a zebrafish CMT2A model. Taken together, our study reveals a mutation-specific insight into CMT2A disease mechanism and confirms HDAC6 as a promising target for further therapeutic development.
Performances of bioinformatics tools for the analysis of sequencing data of Mycobacterium tuberculosis complex strains
Authors: Quagliaro Pauline , Dziri Samira , Magdoud El Alaoui Fatma , Saint Louis Patrick , de Pontual Loïc , Marin Julie , Carbonnelle Etienne , Billard-Pomares Typhaine 
Published: July 2022

AbstractWhole genome sequencing of Mycobacterium tuberculosis complex (MTBC) strains is a new and rapidly growing tool to obtain results regarding resistance, virulence factors and phylogeny of the strains. Bioinformatics tools presented as user-friendly and easy to use are available online. The objective of this work was to evaluate the performances of two bioinformatics tools, easily accessible on the internet, for the analysis of sequencing data of MTBC strains.Two hundred and twenty-seven MTBC strains isolated at the laboratory of the Avicenne Hospital between 2015 and 2021 were sequenced using Illumina®(USA) MiSeq technology. An analysis of the sequencing data was performed using the two tools Mykrobe and PhyResSE. Sequencing quality, resistance or susceptibility status and phylogeny were investigated for each strain. Genotypic resistance results were compared to the results obtained by phenotypic drug susceptibility testing performed in the hospital’s routine laboratory.Using the PhyResSE tool we found an average coverage of 98% against the reference strain H37Rv and an average depth of 119X. No information on sequencing quality was obtained with the Mykrobe tool. The concordance of each tool with the phenotypic method for determining susceptibility to first-line anti-tuberculosis drugs was 95%. Mykrobe and PhyResSE tools identified resistance to second-line anti-tuberculosis drugs in 5.3% and 5.7% of cases respectively. The sensitivity and specificity of each tool compared to the phenotypic method was respectively 70% and 98% for Mykrobe and 76% and 97% for PhyResSE. Finally, the two tools showed 99.5% agreement in lineage determination.The Mykrobe and PhyResSE bioinformatics tools were easy to use, fast and efficient. The Mykrobe tool had the advantage of being offline and its interface was more user-friendly. The use of these platforms depends on their accessibility and updating. However, their use is accessible to people not trained in bioinformatics and would allow a complementary approach to phenotypic methods for the study of MTBC strains.
Metformin Alleviates Arthrofibrosis via Fibroblast Metabolic Reprogramming
Authors: Zhu Zhenglin , Gao Shengqiang , Zhu Hui , Chen Yi , Wu Dandong , Chen Zhiyu , Zou Jing , Wu Xiangdong , Hu Ning , Chen Di , Huang Wei , Chen Hong 
Published: July 2022

AbstractBackgroundEmerging studies have suggested an essential role of fibroblast metabolic reprogramming in the pathogenesis of arthrofibrosis. The metabolic modulator metformin appears to be a therapeutic candidate for fibrotic disorders. However, whether metformin could alleviate arthrofibrosis has not been defined. In this study we have determined if treatment with metformin has the beneficial effect on arthrofibrosis and its underlying mechanism.MethodsArticular capsule samples were collected from patients with/without arthrofibrosis to perform gene and protein expression analysis. Arthrofibrosis animal model was established to examine the anti-fibrotic effect of metformin. Cell culture experiments were conducted to determine the mechanism by which metformin inhibits fibroblast activation.ResultsWe found that glycolysis was upregulated in human fibrotic articular capsules. In an arthrofibrosis animal model, intra-articular injection of metformin mitigated inflammatory reactions, downregulated expression of both fibrotic and glycolytic markers, improved range of motion of the joint, and reduced capsular fibrosis and thickening. At the cellular level, metformin inhibited the activation of fibroblasts and mitigated the abundant influx of glucose into activated fibroblasts. Interestingly, metformin prompted a metabolic shift from oxidative phosphorylation to aerobic glycolysis in activated fibroblasts, resulting in the anti-fibrotic effect of metformin.ConclusionMetformin decreased glycolysis, causing a metabolic shift toward aerobic glycolysis in activated fibroblasts and has beneficial effect on the treatment of arthrofibrosis.The translational potential of this articleThe finding of this study demonstrated the therapeutic effect of metformin on arthrofibrosis and defined novel targets for the treatment of articular fibrotic disorders.
Predicting causal citations without full text
Authors: Hoppe Travis A. , Arabi Salsabil , Hutchins B. Ian 
Published: July 2022

AbstractInsights from biomedical citation networks can be used to identify promising avenues for accelerating research and its downstream bench-to-bedside translation. Citation analysis generally assumes that each citation documents causal knowledge transfer that informed the conception, design, or execution of the main experiments. Citations may exist for other reasons. In this paper we identify a subset of citations that are unlikely to represent causal knowledge flow. Using a large, comprehensive feature set of open access data, we train a predictive model to identify such citations. The model relies only on the title, abstract, and reference set and not the full-text or future citations patterns, making it suitable for publications as soon as they are released, or those behind a paywall (the vast majority). We find that the model identifies, with high prediction scores, citations that were likely added during the peer review process, and conversely identifies with low prediction scores citations that are known to represent causal knowledge transfer. Using the model, we find that federally funded biomedical research publications represent 30% of the estimated causal knowledge transfer from basic studies to clinical research, even though these comprise only 10% of the literature, a three-fold overrepresentation in this important type of knowledge transfer. This finding underscores the importance of federal funding as a policy lever to improve human health.Significance statementCitation networks document knowledge flow across the literature, and insights from these networks are increasingly used to form science policy decisions. However, many citations are known to be not causally related to the inception, design, and execution of the citing study. This adds noise to the insights derived from these networks. Here, we show that it is possible to train a machine learning model to identify such citations, and that the model learns to identify known causal citations as well. We use this model to show that government funding drives a disproportionate amount of causal knowledge transfer from basic to clinical research. This result highlights a straightforward policy lever for accelerating improvements to human health: federal funding.
Duration of immune protection of SARS-CoV-2 natural infection against reinfection in Qatar
Authors: Chemaitelly Hiam , Nagelkerke Nico , Ayoub Houssein H. , Coyle Peter , Tang Patrick , Yassine Hadi M. , Al-Khatib Hebah A. , Smatti Maria K. , Hasan Mohammad R. , Al-Kanaani Zaina , Al-Kuwari Einas , Jeremijenko Andrew , Kaleeckal Anvar Hassan , Latif Ali Nizar , Shaik Riyazuddin Mohammad , Abdul-Rahim Hanan F. , Nasrallah Gheyath K. , Al-Kuwari Mohamed Ghaith , Butt Adeel A. , Al-Romaihi Hamad Eid , Al-Thani Mohamed H. , Al-Khal Abdullatif , Bertollini Roberto , Abu-Raddad Laith J. 
Published: July 2022

AbstractBACKGROUNDThe future of the SARS-CoV-2 pandemic hinges on virus evolution and duration of immune protection of natural infection against reinfection. We investigated duration of protection afforded by natural infection, the effect of viral immune evasion on duration of protection, and protection against severe reinfection, in Qatar, between February 28, 2020 and June 5, 2022.METHODSThree national, matched, retrospective cohort studies were conducted to compare incidence of SARS-CoV-2 infection and COVID-19 severity among unvaccinated persons with a documented SARS-CoV-2 primary infection, to incidence among those infection-naïve and unvaccinated. Associations were estimated using Cox proportional-hazard regression models.RESULTSEffectiveness of pre-Omicron primary infection against pre-Omicron reinfection was 85.5% (95% CI: 84.8-86.2%). Effectiveness peaked at 90.5% (95% CI: 88.4-92.3%) in the 7th month after the primary infection, but waned to ∼70% by the 16th month. Extrapolating this waning trend using a Gompertz curve suggested an effectiveness of 50% in the 22nd month and <10% by the 32nd month. Effectiveness of pre-Omicron primary infection against Omicron reinfection was 38.1% (95% CI: 36.3-39.8%) and declined with time since primary infection. A Gompertz curve suggested an effectiveness of <10% by the 15th month. Effectiveness of primary infection against severe, critical, or fatal COVID-19 reinfection was 97.3% (95% CI: 94.9- 98.6%), irrespective of the variant of primary infection or reinfection, and with no evidence for waning. Similar results were found in sub-group analyses for those ≥50 years of age.CONCLUSIONSProtection of natural infection against reinfection wanes and may diminish within a few years. Viral immune evasion accelerates this waning. Protection against severe reinfection remains very strong, with no evidence for waning, irrespective of variant, for over 14 months after primary infection.
Polygenic architecture of rare coding variation across 400,000 exomes
Authors: Weiner Daniel J. , Nadig Ajay , Jagadeesh Karthik A. , Dey Kushal K. , Neale Benjamin M. , Robinson Elise B. , Karczewski Konrad J. , O’Connor Luke J. 
Published: July 2022

AbstractBoth common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have discovered thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes1–3. However, rare-variant genetic architecture is not well characterized, and the relationship between common- and rare-variant architecture is unclear4. Here, we quantify the heritability explained by gene-wise burden of rare coding variants and compare the genetic architecture of common and rare variation across 22 common traits and diseases in 400,000 UK Biobank exomes5. Rare coding variants (AF = 1e-6 - 1e-3) explain 1.3% (SE = 0.03%) of phenotypic variance on average – much less than common variants – and most burden heritability is explained by ultra-rare loss-of-function variants (AF = 1e-6 - 1e-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in a limited number of significant genes (median: 6 genes explaining 19% of h2), while common-variant heritability is much more polygenic. Burden heritability is also more strongly concentrated in constrained genes (median enrichment: 4.5x vs. 2.1x for common variants), indicating that negative selection affects common- and rare-variant architecture differently. Finally, we find that burden heritability for schizophrenia and bipolar disorder6,7 is approximately 2%. Our results show that there are a tractable number of large-effect genes to discover by studying rare variants, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.