bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring by viral load and quantitative hepatitis B surface antigen in patients with hepatitis B virus infection receiving immunosuppressive therapy
Authors: Yu Hsien-Chung , Tseng Jui-Cheng , Lu Ling-Ying , Hu Jwi-Chieh , Chen Yan-Hua , Hsu Chiao-Lin , Wu Pin-Chieh , Mar Guang-Yuan , Lin Kung-Hung 
Published: April 2020

Objectives:
Hepatitis B virus reactivation in patients on immunosuppressive therapy is a critical issue. We aimed to verify the monitoring strategies of hepatitis B virus DNA and quantitative hepatitis B surface antigen in patients receiving therapies with moderate risk.

Methods:
We enrolled 25 patients with autoimmune diseases receiving immunosuppressive therapy. Liver function, hepatitis B virus DNA, and quantitative hepatitis B surface antigen were followed-up every 2 months for 24 months. The hepatitis B virus reactivation was defined as hepatitis B virus DNA reappearance or increase of >1 log IU/mL.

Results:
Patients who were hepatitis B surface antigen positive with (n = 12) or without (n = 6) antiviral prophylaxis and hepatitis B surface antigen negative (n = 7) were analyzed, and the reactivation rates were 0%, 50% and 14%, respectively. Antiviral prophylaxis prevented hepatitis B virus reactivation in hepatitis B surface antigen-positive patients (P = 0.025). Administration of high-risk steroid doses was the sole factor related to the sign of quantitative hepatitis B surface antigen increase of >0.5 log IU/mL in the first 12 months (P = 0.035, risk ratio = 0.098, 95% confidence interval = 0.011–0.847). Furthermore, no patient experienced hepatic decompensation or failure.

Conclusion:
Monitoring hepatitis B virus DNA and quantitative hepatitis B surface antigen every 2 months is safe. However, antiviral prophylaxis can prevent hepatitis B virus reactivation. For patients under steroid therapy in high-risk doses, quantitative hepatitis B surface antigen increase of >0.5 log IU/mL may signify hepatitis B virus reactivation.
Different Surgical Reconstructions for Femoral Nerve Injury
Authors: Cao Yu , Li Yuehong , Zhang Youlai , Li Shulin , Jiang Junjian , Gu Yudong , Xu Lei 
Published: April 2020

Background
Femoral nerve palsy can cause loss in quadriceps function and knee extension disability, which may lead to severe lower extremity impairment. The obturator nerve trunk transfer in the pelvic, the obturator nerve mortal branches transfer out of the pelvic, along with nerve graft, was introduced years ago to restore femoral nerve function. However, the outcomes of these procedures have never been compared. The aims of this study were to give our experiences in surgical reconstruction for femoral nerve injury and to compare the outcomes of different approaches.

Methods
Nine patients with complete femoral nerve injury have been enrolled in this study between March 2012 and July 2016. All patients were followed up for at least 2 years after surgical intervention for sural nerve graft (n = 3), obturator trunk transfer in the pelvic (n = 2), or obturator nerve mortal branches transfer out of the pelvic (n = 4).

Results
All patients gained satisfactory quadriceps Medical Research Council grade (M3–M4+) after more than 2 years of follow-up. The sural nerve graft led to the earliest recovery on average, followed by obturator nerve mortal branches transfer in the thigh level and then obturator nerve trunk transfer in the pelvic. The functional outcomes, demonstrated by Lower Extremity Functional Scale and Femoral Nerve Motor Function Scale scores, also showed that the sural nerve graft was the best on average, followed by obturator nerve trunk transfer in the pelvic and then obturator nerve mortal branches transfer in the thigh level.

Conclusions
Our results indicate that all these 3 procedures are safe and reliable ways to reconstruct femoral nerve function and can be applied to patients with different kinds of injuries. The sural nerve graft should be considered in the first place and the obturator nerve transfer at different level (trunk transfer in the pelvic or mortal branches transfer out of the pelvic) can be performed as the alternative.
Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-CoV-2
Authors: Chiara Matteo , Horner David S. , Gissi Carmela , Pesole Graziano 
Published: April 2020

AbstractPhylogenomic analysis of SARS-CoV-2 as available from publicly available repositories suggests the presence of 3 prevalent groups of viral episomes (super-clades), which are mostly associated with outbreaks in distinct geographic locations (China, USA and Europe). While levels of genomic variability between SARS-CoV-2 isolates are limited, to our knowledge, it is not clear whether the observed patterns of variability in viral super-clades reflect ongoing adaptation of SARS-CoV-2, or merely genetic drift and founder effects. Here, we analyze more than 1100 complete, high quality SARS-CoV-2 genome sequences, and provide evidence for the absence of distinct evolutionary patterns/signatures in the genomes of the currently known major clades of SARS-CoV-2. Our analyses suggest that the presence of distinct viral episomes at different geographic locations are consistent with founder effects, coupled with the rapid spread of this novel virus. We observe that while cross species adaptation of the virus is associated with hypervariability of specific protein coding regions (including the RDB domain of the spike protein), the more variable genomic regions between extant SARS-CoV-2 episomes correspond with the 3’ and 5’ UTRs, suggesting that at present viral protein coding genes should not be subjected to different adaptive evolutionary pressures in different viral strains. Although this study can not be conclusive, we believe that the evidence presented here is strongly consistent with the notion that the biased geographic distribution of SARS-CoV-2 isolates should not be associated with adaptive evolution of this novel pathogen.
Co-evolution between codon usage and Protein-Protein Interaction Networks in Bacterial genomes
Authors: Dilucca Maddalena , Cimini Giulio , Forcelloni Sergio , Giansanti Andrea 
Published: April 2020

AbstractIn this work, we study the correlation between codon usage and the network features of the PPI in bacteria genomes. We want to extend the information by Dilucca et al. (2015) about E.Coli’s genome for a set of other 34 bacteria. We use PCA techniques in the space of codon bias indices (compAI, compAI_w, tAI, NC) and GC content to show that genes with similar patterns of codon usage feature have a significantly higher probability that their encoded proteins interact within the PPI. And vice-versa, we show that interacting in the PPI have a coherent codon usage. This work could allow for future investigations into the possible effects that codon bias signal can have on the topology of protein interaction network and, as such, to improve existing bioinformatics methods for predicting protein interactions.
Pan-cancer Drivers are Recurrent Transcriptional Regulatory Heterogeneities in Early-stage Luminal Breast Cancer
Authors: Singh Shambhavi , Sutcliffe Matthew D. , Repich Kathy , Atkins Kristen A. , Harvey Jennifer A. , Janes Kevin A. 
Published: April 2020

AbstractThe heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by single-cell RNA sequencing, but these methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEGs) that were significantly variable in >50% of patients. RHEGs were not strongly confounded by dissociation artifacts, cell cycle oscillations, or driving mutations for breast cancer. Rather, we detected RHEG enrichments for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across cancer types other than breast. Heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to evaluate the effects of potential oncogenes or tumor suppressors on cancer hallmarks.Statement of significanceProfiling intratumor heterogeneity of luminal breast carcinoma cells identifies a recurrent set of genes suggesting sporadic activation of pathways known to drive other types of cancer.
Metagenomic sequencing as a clinical diagnostic tool for infectious diseases: a systematic review and meta-analysis
Authors: Govender Kumeren N. , Street Teresa L. , Sanderson Nicholas D. , Eyre David W. 
Published: April 2020

SummaryBackgroundMetagenomics has the potential to revolutionise infectious diseases diagnostics, from rapid species and antimicrobial resistance prediction, to finding unrecognised and sometimes untreated infections. Our aim was to summarise all literature on culture-independent metagenomic sequencing to describe the accuracy of species and antimicrobial resistance prediction and, describe the challenges and progress in the field.MethodsWe conducted a systematic review with meta-analysis from eligible studies retrieved from PubMed, Google Scholar and bioRxiv and, assessed risk of bias and quality using the QUADAS-2 tool. This study is registered with PROSPERO, number CRD42020163777.FindingsWe identified 36 studies, 22 of which used a species-agnostic approach to identify all possible pathogens. In these studies, the overall sensitivity and specificity of pathogen species detection were 88% (95%CI 81-92%) and 86% (95%CI 70-94%) respectively. Antimicrobial resistance prediction and comparison to phenotypic results was undertaken in six studies. Categorical agreement was 83% (95%CI 68-92%), very major (prediction sensitive, phenotype resistant) and major error (prediction resistant, phenotype sensitive) rates were 9% (95%CI 2-27%) and 1% (95%CI 0-20%) respectively. We report limited use of negative controls in studies 61% (22/36) which contribute to a major challenge of discriminating true pathogens from contamination, where there is no convergence on methodology. More efficient human DNA depletion methods are required as a median of 79% (IQR 62-96) [Range 7-98] of sequences were classified as human despite laboratory depletion techniques. The median time from sample to result was 23·5 hours (7-31) [4-144], with sequencing time accounting 10 hours (4·8-16) [1-16]. The average reported consumables cost per sample ranged from $128 to $685.InterpretationThe science and regulatory environment are rapidly developing, and its role as a routine test or test of last resort still needs to be determined, however it is likely that clinical metagenomics will be an increasing part of the clinician’s armamentarium to diagnose infectious diseases in the near future.FundingNone.
Genetic risk scores of disease and mortality capture differences in longevity, economic behavior, and insurance outcomes
Authors: Linnér Richard Karlsson , Koellinger Philipp D. 
Published: April 2020

AbstractWidespread genetic testing for diseases may cause adverse selection, escalating premiums, or discrimination in various insurance markets. Here, without systematically informing study participants of their genetic predisposition, we estimate to what extent genetic data are informative about differences in longevity, health expectations, and economic behavior. We compute measures of genetic liability (polygenic scores) for 27 common diseases and mortality risks in 9,272 participants of the Health and Retirement Study (HRS). Survival analysis suggests that the highest decile of cumulative genetic risk can distinguish a median lifespan up to 4.5 years shorter, a difference that is similar to or larger than that distinguished by conventional actuarial risk factors, including sex. Furthermore, greater genetic liability is associated with less long-term care insurance, among other economic behaviors. We conclude that the rapid developments in genetic epidemiology pose new challenges for regulating consumer genetics and insurance markets, requiring urgent attention from policymakers.
A framework for network-based epidemiological modeling of tuberculosis dynamics using synthetic datasets
Authors: Renardy Marissa , Kirschner Denise E. 
Published: April 2020

AbstractWe present a framework for discrete network-based modeling of TB epidemiology in US counties using publicly available synthetic datasets. We explore the dynamics of this modeling framework by simulating the hypothetical spread of disease over two years resulting from a single active infection in Washtenaw County, MI. We find that for sufficiently large transmission rates that active transmission outweighs reactivation, disease prevalence is sensitive to the contact weight assigned to transmissions between casual contacts (that is, contacts that do not share a household, workplace, school, or group quarter). Workplace and casual contacts contribute most to active disease transmission, while household, school, and group quarter contacts contribute relatively little. Stochastic features of the model result in significant uncertainty in the predicted number of infections over time, leading to challenges in model calibration and interpretation of model-based predictions. Finally, predicted infections were more localized by household location than would be expected if they were randomly distributed. This modeling framework can be refined in later work to study specific county and multi-county TB epidemics in the US.
Flattening the curve is not enough, we need to squash it: An explainer using a simple model
Authors: McBryde ES , Meehan MT , Trauer JM 
Published: April 2020

AbstractBackgroundAround the world there are examples of both effective control (e.g., South Korea, Japan) and less successful control (e.g., Italy, Spain, United States) of COVID-19 with dramatic differences in the consequent epidemic curves. Models agree that flattening the curve without controlling the epidemic completely is insufficient and will lead to an overwhelmed health service. A recent model, calibrated for the UK and US, demonstrated this starkly.MethodsWe used a simple compartmental deterministic model of COVID-19 transmission in Australia, to illustrate the dynamics resulting from shifting or flattening the curve versus completely squashing it.ResultsWe find that when the reproduction number is close to one, a small decrease in transmission leads to a large reduction in burden (i.e., cases, deaths and hospitalisations), but achieving this early in the epidemic through social distancing interventions also implies that the community will not reach herd immunity.ConclusionsAustralia needs not just to shift and flatten the curve, but to squash it by getting the reproduction number below one. This will require Australia to achieve transmission rates at least two thirds lower than those seen in the most severely affected countries.The knownCOVID-19 has been diagnosed in over 4,000 Australians. Up until mid-March, most were from international travel, but now we are seeing a rise in locally acquired cases.The newThis study uses a simple transmission dynamic model to demonstrate the difference between moderate changes to the reproduction number and forcing the reproduction number below one.The implicationsLowering local transmission is becoming important in reducing the transmission of COVID-19. To maintain control of the epidemic, the focus should be on those in the community who do not regard themselves as at risk.
Alterations in retrotransposition, synaptic connectivity, and myelination implicated by transcriptomic changes following maternal immune activation in non-human primates
Authors: Page Nicholas F. , Gandal Michael , Estes Myka , Cameron Scott , Buth Jessie , Parhami Sepideh , Ramaswami Gokul , Murray Karl , Amaral David , Van de Water Judy , Schumann Cynthia M. , Carter Cameron S. , Bauman Melissa D. , McAllister A. Kimberley , Geschwind Daniel H. 
Published: April 2020

AbstractBackgroundMaternal immune activation (MIA) is a proposed risk factor for multiple neurodevelopmental and psychiatric disorders, including schizophrenia. However, the molecular and neurobiological mechanisms through which MIA imparts risk for these disorders remain poorly understood. A recently developed nonhuman primate model of exposure to the viral mimic poly:ICLC during pregnancy shows abnormal social and repetitive behaviors and elevated striatal dopamine, a molecular hallmark of human psychosis, providing an unprecedented opportunity for mechanistic dissection.MethodsWe performed RNA-sequencing across four psychiatrically-relevant brain regions (prefrontal cortex, anterior cingulate, hippocampus, and primary visual cortex) from 3.5-4-year old male MIA-exposed and control offspring—an age comparable to mid adolescence in humans.ResultsWe identify 266 unique genes differentially expressed (DE) in at least one brain region with the greatest number observed in hippocampus. Co-expression networks identified region-specific alterations in synaptic signaling and oligodendrocytes. Across regions, we observed temporal and regional differences, but transcriptomic changes were largely similar across 1stor 2ndtrimester MIA exposures, including for the top DE genes—PIWIL2 and MGARP. In addition to PIWIL2, several other known regulators of retrotransposition, as well as endogenous transposable elements were dysregulated in MIA offspring.ConclusionsTogether, these results begin to elucidate the brain-level molecular mechanisms through which MIA may impart risk for psychiatric disease.
Clinical features and outcomes of 2019 novel coronavirus-infected patients with high plasma BNP levels
Authors: Liu Youbin , Liu Dehui , Song Huafeng , Chen Chunlin , Lv Mingfang , Pei Xing , Hu Zhongwei , Qin Zhihui , Li Jinglong 
Published: April 2020

AbstractAimsTo explore clinical features and outcome of 2019 novel coronavirus(2019-nCoV)-infected patients with high BNP levelsMethods and resultsData were collected from patients’ medical records, and we defined high BNP according to the plasma BNP was above > 100 pg/mL. In total,34 patients with corona virus disease 2019(COVID-19)were included in the analysis. Ten patients had high plasma BNP level. The median age for these patients was 60.5 years(interquartile range, 40-80y), and 6/10 (60%) were men. Underlying comorbidities in some patients were coronary heart disease (n=2, 20%), hypertesion (n=3,30%), heart failure (n=1,10%)and diabetes (n=2, 20%). Six (60%) patients had a history of Wuhan exposure. The most common symptoms at illness onset in patients were fever (n=7, 70%), cough (n=3, 30%), headache or fatigue(n=4,40%). These patients had higher aspartate aminotransferase(AST), troponin I, C reactive protein and lower hemoglobin, and platelet count,compared with patients with normal BNP, respectively. Compared with patients with normal BNP, patients with high BNP were more likely to develop severe pneumonia, and receive tracheal cannula, invasive mechanical ventilation, continuous renal replacement therapy, extracorporeal membrane oxygenation, and be admitted to the intensive care unit. One patient with high BNP died during the study.ConclusionHigh BNP is a common condition among patients infected with 2019-nCoV. Patients with high BNP showed poor clinical outcomes
Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality
Authors: Dudel Christian , Riffe Tim , Acosta Enrique , van Raalte Alyson , Strozza Cosmo , Myrskylä Mikko 
Published: April 2020

AbstractThe population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late April 2020, CFRs varied from 2.2% in South Korea to 13.0% in Italy. The age-structure of detected cases often explains more than two thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 13.0% between March 9 and April 22, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.