bluuebunny/crossref_metadata_2025_split huggingface dataset:
In VivoMechanisms of Chemotherapy-Induced Acute Follicle Loss in the Human Ovary: An Individual-Oocyte Transcriptomic Analysis from Human Ovarian Xenografts
Authors: Titus S. , Szymanska K.J. , Musul B. , Turan V. , Taylan E. , Garcia-Milian R. , Mehta S. , Oktay K. 
Published: June 2020

AbstractGonadotoxic chemotherapeutics, such as cyclophosphamide, cause early menopause and infertility in women. Earlier histological studies showed ovarian reserve depletion via severe DNA damage and apoptosis, but others suggested activation of PI3K/PTEN/Akt pathway and follicle ‘burn-out’ as a cause. Using a human ovarian xenograft model, we performed single-cell RNA-sequencing on laser-captured individual primordial follicle oocytes 12h after a single cyclophosphamide injection to determine the mechanisms of acute follicle loss after gonadotoxic chemotherapy. RNA-sequencing showed 190 differentially expressed genes between the cyclophosphamide- and vehicle-exposed oocytes. Ingenuity Pathway Analysis predicted a significant decrease in the expression of anti-apoptotic pro-AktPECAM1(p=2.13E-09),IKBKE(p=0.0001), andANGPT1(p=0.003), and reduced activation of PI3K/PTEN/Akt after cyclophosphamide. The qRT-PCR and immunostaining confirmed that in primordial follicle oocytes, cyclophosphamide did not change the expressions ofAkt(p=0.9),rpS6(p=0.3),Foxo3a(p=0.12) and anti-apoptoticBcl2(p=0.17), nor affect their phosphorylation status. There was significantly increased DNA damage by γH2AX (p=0.0002) and apoptosis by active-caspase-3 (p=0.0001) staining in the primordial follicles and no change in the growing follicles 12h after chemotherapy. These data suggest that the mechanism of acute follicle loss by cyclophosphamide is via apoptosis, rather than growth activation of primordial follicle oocytes in the human ovary.One Sentence SummarySingle-cell transcriptomic interrogation of primordial follicles in human ovarian xenografts reveals that chemotherapy causes acute ovarian reserve depletion by inducing a pro-apoptotic state rather than activating pathways that result in follicle growth initiation.
Zebrafishfollistatin-like 1bregulates cardiac contraction during early development
Authors: Zeng Xin-Xin I. , Ocorr Karen , Ensberg Erik J. , Dong P. Duc si 
Published: June 2020

AbstractExtracellular glycoprotein Follistatin-like protein 1 (FSTL1) has been reported to be involved in multiple signaling pathways and biological processes during development and disease. In addition, some mouse studies have suggested an inhibitory role of FSTL1 in BMP signaling, in certain context. Yet, whether FSTL1 has biological functions in early heart development are largely unknown. In our functional studies, CRISPR/Cas9 genome editing was used to createfstl1aandfstl1binsertion/deletion mutations in zebrafish and our results suggest thatfstl1bis important in regulating heart development during early embryogenesis.in situhybridization revealed thatfstl1btranscripts are expressed in the developing zebrafish heart, andfstl1bhomozygous (-/-) mutant exhibited pericardial edema and showed significantly reduced contractility in the ventricle, with incomplete penetrance. We found that zebrafishfstl1b (-/-)mutant hearts formed a collapsed ventricle with strong reductions in the sarcomere structure protein alpha-actinin, although the number of cardiomyocytes was comparable to wild type control siblings. Further, normal levels offstl1bseems to prevent the expansion of Bmp signaling into ventricular myocytes, which is consistent with the previously established model of Bmp-dependent cardiac contraction. Together these results reveal the zebrafish orthologfstl1bregulates sarcomere structure and cardiac contractile function. In vertebrate developing heart, it might function as a key component in a novel pathway that constrains Bmp signaling from ventricular myocytes.
Diverse scientific benchmarks for implicit membrane energy functions
Authors: Alford Rebecca F. , Gray Jeffrey J. 
Published: June 2020

AbstractEnergy functions are fundamental to biomolecular modeling. Their success depends on robust physical formalisms, efficient optimization, and high-resolution data for training and validation. Over the past 20 years, progress in each area has advanced soluble protein energy functions. Yet, energy functions for membrane proteins lag behind due to sparse and low-quality data, leading to overfit tools. To overcome this challenge, we assembled a suite of 12 tests on independent datasets varying in size, diversity, and resolution. The tests probe an energy function’s ability to capture membrane protein orientation, stability, sequence, and structure. Here, we present the tests and use thefranklin2019energy function to demonstrate them. We then present a vision for transforming these “small” datasets into “big data” that can be used for more sophisticated energy function optimization. The tests are available through the Rosetta Benchmark Server (https://benchmark.graylab.jhu.edu/) and GitHub (https://github.com/rfalford12/Implicit-Membrane-Energy-Function-Benchmark).
Remote homology search with hidden Potts models
Authors: Wilburn Grey W. , Eddy Sean R. 
Published: June 2020

AbstractMost methods for biological sequence homology search and alignment work with primary sequence alone, neglecting higher-order correlations. Recently, statistical physics models called Potts models have been used to infer all-by-all pairwise correlations between sites in deep multiple sequence alignments, and these pairwise couplings have improved 3D structure predictions. Here we extend the use of Potts models from structure prediction to sequence alignment and homology search by developing what we call a hidden Potts model (HPM) that merges a Potts emission process to a generative probability model of insertion and deletion. Because an HPM is incompatible with efficient dynamic programming alignment algorithms, we develop an approximate algorithm based on importance sampling, using simpler probabilistic models as proposal distributions. We test an HPM implementation on RNA structure homology search benchmarks, where we can compare directly to exact alignment methods that capture nested RNA base-pairing correlations (stochastic context-free grammars). HPMs perform promisingly in these proof of principle experiments.Author summaryComputational homology search and alignment tools are used to infer the functions and evolutionary histories of biological sequences. Most widely used tools for sequence homology searches, such as BLAST and HMMER, rely on primary sequence conservation alone. It should be possible to make more powerful search tools by also considering higher-order covariation patterns induced by 3D structure conservation. Recent advances in 3D protein structure prediction have used a class of statistical physics models called Potts models to infer pairwise correlation structure in multiple sequence alignments. However, Potts models assume alignments are given and cannot build new alignments, limiting their use in homology search. We have extended Potts models to include a probability model of insertion and deletion so they can be applied to sequence alignment and remote homology search using a new model we call a hidden Potts model (HPM). Tests of our prototype HPM software show promising results in initial benchmarking experiments, though more work will be needed to use HPMs in practical tools.
Rewiring the specificity of extra-cytoplasmic function sigma factors
Authors: Todor Horia , Osadnik Hendrik , Campbell Elizabeth A. , Myers Kevin S. , Donohue Timothy J. , Gross Carol A. 
Published: June 2020

SUMMARYBacterial genomes are being sequenced at an exponentially increasing rate, but our inability to decipher their transcriptional wiring limits our ability to derive new biology from these sequences.De novodetermination of regulatory interactions requires accurate prediction of regulators’ DNA binding and precise determination of biologically significant binding sites. Here, we address these challenges by solving the DNA-specificity code of extra-cytoplasmic function sigma factors (ECF σs), a major family of bacterial regulators, and determining their regulons. We generated an aligned collection of ECF σs and their promoters by leveraging the auto-regulatory nature of ECF σs as a means of promoter discovery and analyzed it to identify and characterize the conserved amino acid – nucleotide interactions that determine promoter specificity. This enabledde novoprediction of ECF σ specificity, which we combined with a statistically rigorous phylogenetic foot-printing pipeline based on precomputed orthologs to predict the direct targets of ∼67% of ECF σs. This global survey indicated that ECF σs play varied roles: some are global regulators controlling many genes throughout the genome that are important under many conditions, while others are local regulators, controlling few closely linked genes in response to specific stimuli. This analysis reveals important organizing principles of bacterial gene regulation and presents a conceptual and computational framework for deciphering gene regulatory networks.
Anti-retroviral therapy and serum protein levels in HIV-1 seropositive patients: a five-year retrospective study
Authors: Shedrac Akor Egbunu , Haruna Musa , Gloria Eneojo-Abah Eleojo , Nma Yisa Benjamin , Titus Emmanuel Friday , Musa Dickson Achimugu , Oguche Joel Ikojo , Shaibu Serah , Tijani Salami , Bukbuk David , Abah Samuel Eneọjọ 
Published: June 2020

AbstractBackgroundSerum proteins designated as liver function biomarkers are used to evaluate patients for hepatic dysfunction. Hepatic effect of Anti-Retroviral Therapy (ART) needs further studies in HIV mono-infected patients. In this study, clinically defined patient datasets were analysed for protein levels in HIV-1 mono-infected seropositive patients with and without ART.Materials and MethodsData were collected for the study groups, consisting of the control group and HIV-1 mono-infected seropositive patients with and without ART and were analysed statistically for differences among the groups. All subjects in the patient groups attended University of Maiduguri Teaching Hospital, Nigeria for a period of 5 years.ResultThe protein levels on initiation of ART were significantly higher than baseline levels (prior to ART). However, continuous use of ART for 5-year period did not induce any further significant change in protein levels. Receiver Operating Characteristic (ROC) curves shows that both Albumin (ALB) and Total protein (TP) levels discriminated among the study groups. The baseline levels of ALB in seropositive patients are significantly lower to levels on initiation of ART.ConclusionContinuous ART did not cause any further significant change in levels of liver function proteins than was observed on ART initiation. Hence, liver damage on continuous ART is not implied. Both ALB and TP levels could be important in HIV management of patients. Initiation of ART appears to elevate the low ALB level via a yet unknown mechanism and indicates possible role of ALB in ART mechanism of action.
Prevalence and risks of severe events for cancer patients with COVID-19 infection: a systematic review and meta-analysis
Authors: Su Qiang , Hu Jie-xuan , Lin Hai-shan , Zhang Zheng , Zhu Emily C. , Zhang Chen-guang , Wang Di-ya , Gao Zu-hua , Cao Bang-wei 
Published: June 2020

SummaryBackgroundThe corona virus disease 2019 (COVID-19) pandemic poses a severe challenge to public health, especially to those patients with underlying diseases. In this meta-analysis, we studied the prevalence of cancer among patients with COVID-19 infection and their risks of severe events.MethodsWe searched the Pubmed, Embase and MedRxiv databases for studies between December 2019 and May 3, 2020 using the following key words and terms: sars-cov-2, covid-19, 2019-ncov, 2019 novel coronavirus, corona virus disease-2019, clinical, clinical characteristics, clinical course, epidemiologic features, epidemiology, and epidemiological characteristics. We extracted data following PICO (patient, intervention, comparison and outcome) chart. Statistical analyses were performed with R Studio (version 3.5.1) on the group-level data. We assessed the studies’ risk of bias in accordance to the adjusted Joanna Briggs Institute. We estimated the prevalence or risks for severe events including admission into intensive care unit or death using meta-analysis with random effects.FindingsOut of the 2,551 studies identified, 32 studies comprising 21,248 participants have confirmed COVID-19. The total prevalence of cancer in COVID-19 patients was 3.97% (95% CI, 3.08% to 5.12%), higher than that of the total cancer rate (0.29%) in China. Stratification analysis showed that the overall cancer prevalence of COVID-19 patients in China was 2.59% (95% CI, 1.72% to 3.90%), and the prevalence reached 3.79% in Wuhan (95% CI, 2.51% to 5.70%) and 2.31% (95% CI, 1.16% to 4.57%) in other areas outside Wuhan in China. The incidence of ICU admission in cancer patients with COVID-19 was 26.80% (95% CI, 21.65% to 32.67%) and the mortality was 24.32% (95% CI, 13.95% to 38.91%), much higher than the overall rates of COVID-19 patients in China. The fatality in COVID patients with cancer was lower than those with cardiovascular disease (OR 0.49; 95% CI, 0.34 to 0.71; p=0.39), but comparable with other comorbidities such as diabetes (OR 1.32; 95% CI, 0.42 to 4.11; p=0.19), hypertension (OR 1.27; 95% CI, 0.35 to 4.62; p=0.13), and respiratory diseases (OR 0.79; 95% CI, 0.47 to 1.33; p=0.45).InterpretationThis comprehensive meta-analysis on the largest number of patients to date provides solid evidence that COVID-19 infection significantly and negatively affected the disease course and prognosis of cancer patients. Awareness of this could help guide clinicians and health policy makers in combating cancer in the context of COVID-19 pandemic.FundingBeijing Natural Science Foundation Program and Scientific Research Key Program of Beijing Municipal Commission of Education (KZ202010025047).
Initial experience with short-course corticosteroids in a small cohort of adults with severe COVID-19 in a tertiary care hospital in India
Authors: Jha Sanjiv , Shetty Kiran , Vadi Sonali , Phadtare Sourabh , Kothari Vatsal , Raut Abhijit , Shah Sweta , Bhargava Pallavi , Singhal Tanu 
Published: June 2020

AbstractSevere COVID 19 disease is associated with high morbidity and mortality with limited therapeutic options. The role of glucocorticoids in treatment of COVID 19 has been riddled with controversy. The study site has been using glucocorticoids in patients with severe COVID 19 since the first few patients of COVID 19 that were admitted. In the initial cohort of 7 patients with severe COVID disease, use of methylprednisolone in a dose of 30 mg twice daily was associated with rapid improvement in oxygenation and decline in CRP levels. While six patients made a complete clinical recovery, one patient died. There were no secondary infections.
Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis
Authors: Ardle Angela Mc , Kwasnik Anna , Szenpetery Agnes , Jones Melissa , Hernandez Belinda , Meenagh Micheal , Parnell Andrew , de Jager Wilco , de Roock Sytze , FitzGerald Oliver , Pennington Stephen 
Published: June 2020

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.
Practical recommendations for staying physically active during the COVID-19 pandemic: A systematic literature review
Authors: Bentlage Ellen , Ammar Achraf , Chtourou Hamdi , Trabelsi Khaled , How Daniella , Ahmed Mona , Brach Michael 
Published: June 2020

AbstractBackgroundDue to home-confinement and social isolation of during the Covid-19 pandemic, reductions in performing physical activities were observed. A main consequence of inactivity is a poorer general health and a higher mortality rate. Therefore, it is important to inform the public about practical recommendations for staying physically active, especially during the current Covid-19 pandemic.MethodsThrough a systematic review of literature in two databases (Pubmed/Medline; Web of Science), studies were analysed which include practical recommendations for staying active during Covid-19 (Q1), or if they did not explicitly deal with Covid-19, research with useful results regarding the adaption to the present situation (Q2).ResultsCurrently, there are 6 studies published which are related to the first research question. In total, 26 papers, were found to correlate to the second one.ConclusionResearchers need to be more specific in the exact recommendations for different age-groups and various health statuses. Key sources are the websites of the World Health Organization and the American Heart Association. In addition, exergames need to be adaptable to restrictions by product designers and to integrate social interaction-functions. Furthermore, it is essential that governmental actions need to be taken, with the help of researchers, to inform citizens about possible physical activities, with precise examples, clarification of benefits of the exercises, the exact exercise with duration, intensity and other substitute tasks for different age-groups and for people with diseases.
Analysis and Forecast of COVID-19 Pandemic in Pakistan
Authors: Malik Abdul Bari 
Published: June 2020

AbstractThe COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.
Transmission of Respiratory Infectious Diseases between Neighboring Cities using Agent-based Model and Compartmental Model
Authors: Buhat Christian Alvin H. , Lutero Destiny SM. , Olave Yancee H. , Torres Monica C. , Rabajante Jomar F. 
Published: June 2020

AbstractWe formulate an agent-based model and a compartmental model (SEIR) that simulate the spread of a respiratory infectious disease between two neighboring cities. We consider preventive measures such as implementation of social distancing and lockdown in a city, as well as the effect of protective gears or practices. The chance of travelling to another city and within the city during lockdown, and initial percentage of exposed and infected individuals on both cities influence the increase in the number of newly-infected individuals on both models. Our simulations show that (i) increase in exposed individuals results in increase in number of new infections, hence the need for increased testing-isolation efforts; (ii) protection level of 75-100% effectiveness impedes disease transmission; (iii) travelling within city or to other city can be an option given that strict preventive measures (e.g., non-pharmaceutical interventions) are observed; and (iv) the ideal set-up for neighboring cities is to implement lockdown when there is high risk of disease local transmission while individuals observe social distancing, maximizing protective measures, and isolating those that are exposed. The results of the agent-based and compartmental models show similar qualitative dynamics; the differences are due to different spatio-temporal heterogeneity and stochasticity. These models can aid decision makers in designing infectious disease-related policies to protect individuals while continuing population movement.
The effect of smoking on multiple sclerosis: a mendelian randomization study
Authors: Mitchell Ruth E , Bates Kirsty , Wootton Robyn E , Harroud Adil , Richards J. Brent , Smith George Davey , Munafò Marcus R 
Published: June 2020

AbstractThe causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian Randomization (MR) to examined whether this association is causal using genetic variants identified in genome-wide association studies (GWAS) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility was measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.