bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of nomogram to predict long-term prognosis of critically ill patients with acute myocardial infarction
Authors: Tang Yiyang , Zha Lihuang , Zeng Xiaofang , Feng Yilu , Lin Wenchao , Liu Zhenghui , Yu Zaixin 
Published: August 2020

AbstractBackgroundAcute myocardial infarction (AMI) is a common critical illness in the cardiovascular field, with poor prognosis. This study aimed to construct a nomogram to predict long-term survival of critically ill patients with AMI, which helps to assess severity, guide treatment, and improve prognosis.Methods and resultsThe clinical data of patients with AMI was extracted from the database MIMIC-III v1.4. The Cox proportional hazards models were performed to identify the independently prognostic factors, and a nomogram for predicting long-term survival of AMI patients was developed based on the multifactor analysis, of which discriminative ability and accuracy was evaluated by concordance index (C-index) and calibration curve.ResultsA total of 1202 patients were included in the analysis, of which 841 were divided into the training set and 361 were the validation. Multivariate analysis shown that age, blood urea nitrogen, respiratory rate, SAPSII score, cardiogenic shock, cardiac arrhythmias, and respiratory failure served as the independently predictive factors, which were incorporated into the nomogram. Moreover, the nomogram shown favorable performance for predicting 4-year survival of AMI patients with the C-index of 0.788 [95% confidence interval (CI): 0.763 to 0.813] and 0.783 (95% CI: 0.748 to 0.818) in the training and validation set, respectively.ConclusionThe nomogram we constructed here can accurately predict the long-term survival of patients with AMI.
Rates of COVID-19-related Outcomes in Cancer compared to non-Cancer Patients
Authors: Sun Lova , Surya Sanjna , Le Anh N. , Desai Heena , Doucette Abigail , Gabriel Peter , Ritchie Marylyn , Rader Daniel , Maillard Ivan , Bange Erin , Huang Alexander , Vonderheide Robert H. , DeMichele Angela , Verma Anurag , Mamtani Ronac , Maxwell Kara N. 
Published: August 2020

AbstractCancer patients are a vulnerable population postulated to be at higher risk for severe COVID-19 infection. Increased COVID-19 morbidity and mortality in cancer patients may be attributable to age, comorbidities, smoking, healthcare exposure, and cancer treatments, and partially to the cancer itself. Most studies to date have focused on hospitalized patients with severe COVID-19, thereby limiting the generalizability and interpretability of the association between cancer and COVID-19 severity. We compared outcomes of SARS-CoV-2 infection in 323 patients enrolled prior to the pandemic in a large academic biobank (n=67 cancer patients and n=256 non-cancer patients). After adjusting for demographics, smoking status, and comorbidities, a diagnosis of cancer was independently associated with higher odds of hospitalization (OR 2.16, 95% CI 1.12-4.18) and 30-day mortality (OR 5.67, CI 1.49-21.59). These associations were primarily driven by patients with active cancer. These results emphasize the critical importance of preventing SARS-CoV-2 exposure and mitigating infection in cancer patients.
Depression following traumatic brain injury is characterised by dominant and recurring brain loops in self-referential areas
Authors: Pappas Ioannis , Moreno-López Laura , Carroll Ellen L. , Manktelow Anne , Outtrim Joanne G. , Coles Jonathan P. , Newcombe Virginia F. , Sahakian Barbara J. , Menon David K. , Stamatakis Emmanuel A. 
Published: August 2020

AbstractDepression is a major albeit neglected complication in patients with traumatic brain injury (TBI). Elucidating its neural correlates remains an important milestone with respect to understanding the disorder and helping with the rehabilitation process. Towards this direction, neuropsychological theories have proposed abnormal brain dynamics as the neural basis of depressive symptomatology. This observational study addressed the question of whether depression in TBI patients is related to abnormal brain dynamics using a sample of 81 TBI patients with depressive symptomatology. To explore brain dynamics we employed the Hidden Markov model that utilises resting-state fMRI data to identify the states that the brain visits sequentially during scanning. Spatial (highest activated regions) and temporal (occupancy, switching rate) characteristics of these states were used to analyse the networks involved and probe differences between depressed and non-depressed TBI patients. We found a significant positive association between depression score and the fractional occupancy and switching rate of two specific states that distinguished between depressed and non-depressed TBI patients. These states spanned default mode, subcortical and cerebellar regions while also forming a temporally coherent “metastate” that the depressed brain would recurrently visit. Depression in TBI patients is characterised by abnormal recruitment and repetitive sequencing between certain neural networks. These results point to the existence of a reinforced, self-referential circuitry that could provide the basis for targeted therapies during the recovery process.
The medical signature of musicians: A Phenome-wide association study using an Electronic Health Record database
Authors: Niarchou Maria , Lin George , Lense Miriam D. , Gordon Reyna , Davis Lea 
Published: August 2020

AbstractBackgroundBeing a musician is a physically and psychologically demanding undertaking. A limited set of previous studies suggest musicians may be at higher risk for a unique set of medical and mental health problems. To address the limitations of previous studies, we examined trends in the medical care of musicians in Vanderbilt’s Electronic Health Record research database.MethodsWe mined clinical notes for a principled collection of keywords and regular expressions which indicated that the patient was a musician. We identified 9,803 “musicians” that we matched for sex, median age (across the medical record), ethnicity, race, length of record (in days) and number of visits with 49,015 controls. We fitted 1,263 logistic regression models (one for each phenotype classification).Results257 medical diagnoses were significantly more prevalent in musicians than controls after strict Bonferroni adjustment for the total number of phenotypes tested (p-value<7.6 × 10−6). Diseases of the larynx and the vocal cords (OR=2.32, p<2.84 × 10−191), and hearing loss (OR=1.36, p=5.98 × 10−97) were among the top associations. Anxiety disorder (OR=1.25, p=7.67 × 10−71), and Major depressive disorder (OR=1.21, p=4.88 × 10−36) were also strongly associated with musician status. However, 15 phenotypes were significantly more prevalent in non-musicians than musicians, including Coronary atherosclerosis (OR=0.91, p=1.77 × 10−10), and Ischemic Heart Disease (OR=0.92, p=1.65 × 10−09).ConclusionsAlthough being a musician was related to a large number of occupational health problems, we also identified protective effects of musicianship in which certain diagnoses were less common in musicians than in non-musicians, indicating that active musical engagement could have similar health benefits to athletic engagement.Key messagesIn a sample of 14,379 musician cases and 71,895 matched controls identified in an Electronic Health Record database, we conducted the first and largest study to date to identify the medical diagnoses associated with musician patients in an EHR context.We replicated previous associations of musician status with medical problems, including respiratory and hearing problems as well as mental health problems.We identified a number of protective effects by observing diagnoses such as cardiovascular disease, respiratory failure, and renal failure, that were less common in musicians than in controls, in line with literature indicating that active musical engagement has similar health benefits to athletic engagement.
Responsible modelling: Unit testing for infectious disease epidemiology
Authors: Lucas Tim CD , Pollington Timothy M , Davis Emma L , Hollingsworth T Déirdre 
Published: August 2020

AbstractInfectious disease epidemiology is increasingly reliant on large-scale computation and inference. Models have guided health policy for epidemics including COVID-19 and Ebola and endemic diseases such as malaria and tuberculosis. Yet a single coding bug may bias results, leading to incorrect conclusions and wrong actions that could cause avoidable harm. We are ethically obliged to ensure our code is as free of error as possible. Unit testing is a coding method to avoid such bugs, but unit testing is rarely used in epidemiology. We demonstrate through simple examples how unit testing can handle the particular quirks of infectious disease models.
The Common Interests of Health Protection and the Economy: Evidence from Scenario Calculations of COVID-19 Containment Policies
Authors: Dorn Florian , Khailaie Sahamoddin , Stoeckli Marc , Binder Sebastian C. , Lange Berit , Lautenbacher Stefan , Peichl Andreas , Vanella Patrizio , Wollmershäuser Timo , Fuest Clemens , Meyer-Hermann Michael 
Published: August 2020

AbstractSeveral countries use shutdown strategies to contain the spread of the COVID-19 epidemic, at the expense of massive economic costs. While this suggests a conflict between health protection and economic objectives, we examine whether the economically optimal exit strategy can be reconciled with the containment of the epidemic. We use a novel combination of epidemiological and economic simulations for scenario calculations based on empirical evidence from Germany. Our findings suggest that a prudent opening is economically optimal, whereas costs are higher for a more extensive opening process. This rejects the view that there is a conflict with health protection. Instead, it is in the common interest of public health and the economy to relax non-pharmaceutical interventions in a manner that keeps the epidemic under control.
The limits of estimating COVID-19 intervention effects using Bayesian models
Authors: Bryant Patrick , Elofsson Arne 
Published: August 2020

AbstractTo limit the rapid spread of COVID-19, most governments have introduced different non-pharmaceutical interventions, which might have severe costs for society. Therefore, it is crucial to evaluate the most cost-effective interventions, using, for instance, Bayesian modelling. Such modelling efforts have deemed lockdown to account for 81% of the reduction in R​0, contributing to government policies. Here, we show that these conclusions are unsupported and that policies therefore should not be based on these studies.https://www.eurosurveillance.org/for-authors
Vaccine optimization for COVID-19, who to vaccinate first?
Authors: Matrajt Laura , Eaton Julie , Leung Tiffany , Brown Elizabeth R. 
Published: August 2020

AbstractA vaccine, when available, will likely become our best tool to control the current COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under a wide variety of assumptions. We find that a vaccine with effectiveness ≥50% would be enough to substantially mitigate the ongoing pandemic provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, it is optimal to allocate vaccine to high-risk (older) age-groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age-groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization.
Probing nanoscale diffusional heterogeneities in cellular membranes through multidimensional single-molecule and super-resolution microscopy
Authors: Yan Rui , Chen Kun , Xu Ke 
Published: August 2020

ABSTRACTDiffusion properties notably determine the behavior of biomembranes. Here we report the concurrent nanoscale fine-mapping of membrane topography, diffusivity, and packing order in live mammalian cells through a synergy of single-molecule and super-resolution methods. By identifying a bright, lipophilic fluorescence turn-on probe that enables sustained single-molecule imaging of cellular membranes under stroboscopic excitation, we accumulate the positions and transient displacements of >106probe molecules to achieve super-resolution topography and diffusivity mapping. We thus determine a trend that the membrane diffusivity drops with increased lipid packing order when comparing the endoplasmic reticulum (ER) membrane, plasma membrane, and nanodomains induced by cholera toxin B. Utilizing our nanoscale mapping capability, we further unveil reduced diffusivity in the ER membrane at ER-plasma membrane contact sites. By next integrating spectrally resolved single-molecule imaging, we show this localized diffusion slowdown is not due to altered lipid packing order, but may instead be attributed to local protein crowding. Our integrated multidimensional single-molecule approach thus unveils and differentiates between nanoscale diffusional heterogeneities of different origins in live-cell membranes.
Inhibition of Severe Acute Respiratory Syndrome Coronavirus 2 main protease by tafenoquinein vitro
Authors: Chen Yeh , Yang Wen-Hao , Huang Li-Min , Wang Yu-Chuan , Yang Chia-Shin , Liu Yi-Liang , Hou Mei-Hui , Tsai Chia-Ling , Chou Yi-Zhen , Huang Bao-Yue , Hung Chian-Fang , Hung Yu-Lin , Chen Jin-Shing , Chiang Yu-Ping , Cho Der-Yang , Jeng Long-Bin , Tsai Chang-Hai , Hung Mien-Chie 
Published: August 2020

AbstractThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the current pandemic, coronavirus disease 2019 (COVID-19), has taken a huge toll on human lives and the global economy. Therefore, effective treatments against this disease are urgently needed. Here, we established a fluorescence resonance energy transfer (FRET)-based high-throughput screening platform to screen compound libraries to identify drugs targeting the SARS-CoV-2 main protease (Mpro), in particular those which are FDA-approved, to be used immediately to treat patients with COVID-19. Mpro has been shown to be one of the most important drug targets among SARS-related coronaviruses as impairment of Mproblocks processing of viral polyproteins which halts viral replication in host cells. Our findings indicate that the anti-malarial drug tafenoquine (TFQ) induces significant conformational change in SARS-CoV-2 Mproand diminishes its protease activity. Specifically, TFQ reduces the α-helical content of Mpro, which converts it into an inactive form. Moreover, TFQ greatly inhibits SARS-CoV-2 infection in cell culture system. Hence, the current study provides a mechanistic insight into the mode of action of TFQ against SARS-CoV-2 Mpro. Moreover, the low clinical toxicity of TFQ and its strong antiviral activity against SARS-CoV-2 should warrant further testing in clinical trials.
De NovoDesigned Peptide and Protein Hairpins Self-assemble into Sheets and Nanoparticles
Authors: Galloway Johanna M. , Bray Harriet E. V. , Shoemark Deborah K. , Hodgson Lorna R. , Coombs Jennifer , Mantell Judith M. , Rose Ruth S. , Ross James F. , Morris Caroline , Harniman Robert L. , Wood Christopher W. , Arthur Christopher , Verkade Paul , Woolfson Derek N. 
Published: August 2020

AbstractThe design and assembly of peptide based materials has advanced considerably, leading to a variety of fibrous, sheet and nanoparticle structures. A remaining challenge is to account for and control different possible supramolecular outcomes accessible to the same or similar peptide building blocks. Here we present ade novopeptide system that forms nanoparticles or sheets depending on the strategic placement of a ‘disulfide pin’ between two elements of secondary structure that drive self-assembly. Specifically, we join homodimerizing and homotrimerizingde novocoiled-coil α-helices with a flexible linker to generate a series of linear peptides. The helices are pinned back-to-back, constraining them as hairpins by a disulfide bond placed either proximal or distal to the linker. Computational modeling and advanced microscopy show that the proximally pinned hairpins self-assemble into nanoparticles, whereas the distally pinned constructs form sheets. These peptides can be made synthetically or recombinantly to allow both chemical modifications and the introduction of whole protein cargoes as required.
Systems Biology behind immunoprotection of both Sheep and Goats after Sungri/96 PPRV vaccination
Authors: Wani Sajad Ahmad , Praharaj Manas Ranjan , Sahu Amit R , Khan Raja Ishaq Nabi , Rajak Kaushal Kishor , Muthuchelvan Dhanavelu , Sahoo Aditya , Mishra Bina , Singh R. K. , Mishra Bishnu Prasad , Gandham Ravi Kumar 
Published: August 2020

AbstractImmune response is a highly coordinated cascade involving all the subsets of PBMCs. In this study, RNA-Seq analysis of PBMC subsets - CD4+, CD8+, CD14+, CD21+ and CD335+ cells from day 0 and day 5 of Sungri/96 Peste des Petits Ruminants vaccinated sheep and goats was done to delineate the systems biology behind immune - protection of the vaccine in sheep and goats. Assessment of the immune response processes enriched by the differentially expressed genes in all the subsets suggested a strong dysregulation towards development of early inflammatory microenvironment, which is very much required for differentiation of monocytes to macrophages, and for activation and migration of dendritic cells into the draining lymph nodes. The protein - protein interaction networks among the antiviral molecules (IFIT3, ISG15, MX1, MX2, RSAD2, ISG20, IFIT5 and IFIT1) and common DEGs across PBMCs subsets in both the species identified ISG15 to be an ubiquitous hub, that helps in orchestrating antiviral host response against PPRV. IRF7 was found to be the key master regulator activated in most of the subsets in sheep and goats. Most of the pathways were found to be inactivated in B - lymphocytes of both the species indicating that 5 dpv is too early a time point for the B - lymphocytes to react. The cell mediated immune response and humoral immune response pathways were found more enriched in goats than in sheep. Though, animals from both the species survived the challenge, a contrast in pathway activation was observed in CD335+ cells.ImportancePeste des petits ruminants (PPR) by PPRV is an OIE listed acute, contagious transboundary viral disease of small ruminants. Attenuated Sungri/96 PPRV vaccine used all over India against this PPR, provides long-lasting robust innate and adaptive immune response. The early antiviral response was found mediated through type I interferon independent ISGs expression. However, systems biology behind this immune response is unknown. In this study, in vivo transcriptome profiling of PBMC subsets (CD4+, CD8+, CD14+, CD21+ and CD335+) in vaccinated goats and sheep (at 5 days of post vaccination) was done to understand this systems biology. Though there are a few differences in the systems biology across cells (specially the NK cells) between sheep and goats, the co-ordinated response that is inclusive of all the cell subsets was found to be towards induction of strong innate immune response, which is needed for an appropriate adaptive immune response.
Design, Performance Evaluation and Investigation of the Dynamic Mechanisms of Earthworm-Microorganisms interactions for wastewater treatment through Vermifiltration technology
Authors: Arora Sudipti , Saraswat Sakshi , Mishra Rinki , Rajvanshi Jayana , Sethi Jasmine , Nag Aditi , Saxena Sonika 
Published: August 2020

AbstractThe present study points to the relevance of the earthworms-microorganism’s symbiotic and synergistic interactions that drive the wastewater treatment by identifying the most essential mechanisms underlying the removal of contaminants during vermifiltration technology. Previous studies have showed the presence of earthworms improves treatment performance of vermifilter (VF), but earthworm microbial community dynamics, their structure and functional characteristics in VF were not fully investigated. To investigate the effects of earthworms on the inherent microbial community of the VF, the present study envisages the dynamics of the complex symbiosis of earthworms & microorganisms associated to the treatment mechanisms. In this study, the design, operations and performance evaluation and influent, effluent and filter media layer were investigated for microbial diversity inside the earthworm population, along with the antimicrobial activity, enzymatic activity, and protein profiling assays. The results showed that earthworm gut microbial communities were dominated byGammaproteobacteria, and the percentages arrived to 59–60% of the microbial species detected, while filter media layer showed presence ofFirmicutesandActinobacteria. The protein profiling of the microbiota associated with the VF showed that earthworms feeding and earthworm–microorganism interaction were responsible for enhanced treatment performance. The finding provides an insight into the complex earthworm microbial dynamics and mechanisms for wastewater treatment in VF. Furthermore, earthworm predation strongly regulated microbial biomass while improving microbial activity, and is deciphered as the possible mechanisms behind the vermifiltration technology.
nMAGMA: a network enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia
Authors: Yang Anyi , Chen Jingqi , Zhao Xing-Ming 
Published: August 2020

AbstractMotivationAnnotating genetic variants from summary statistics of genome-wide association studies (GWAS) is crucial for predicting risk genes of various disorders. The multi-marker analysis of genomic annotation (MAGMA) is one of the most popular tools for this purpose, where MAGMA aggregates signals of single nucleotide polymorphisms (SNPs) to their nearby genes. However, SNPs may also affect genes in a distance, thus missed by MAGMA. Although different upgrades of MAGMA have been proposed to extend gene-wise variant annotations with more information (e.g. Hi-C or eQTL), the regulatory relationships among genes and the tissue-specificity of signals have not been taken into account.ResultsWe propose a new approach, namely network-enhanced MAGMA (nMAGMA), for gene-wise annotation of variants from GWAS summary statistics. Compared with MAGMA and H-MAGMA, nMAGMA significantly extends the lists of genes that can be annotated to SNPs by integrating local signals, long-range regulation signals, and tissue-specific gene networks. When applied to schizophrenia, nMAGMA is able to detect more risk genes (217% more than MAGMA and 57% more than H-MAGMA) that are reasonably involved in schizophrenia compared to MAGMA and H-MAGMA. Some disease-related functions (e.g. the ATPase pathway in Cortex) tissues are also uncovered in nMAGMA but not in MAGMA or H-MAGMA. Moreover, nMAGMA provides tissue-specific risk signals, which are useful for understanding disorders with multi-tissue origins.