bluuebunny/crossref_metadata_2025_split huggingface dataset:
County Jail Incarceration Rates and County Mortality Rates in the United States, 1987–2016
Authors: Kajeepeta Sandhya , Rutherford Caroline G. , Keyes Katherine M. , El-Sayed Abdulrahman M. , Prins Seth J. 
Published: January 2020

Objectives. To evaluate the relationship between changes in county jail incarceration rates and subsequent county mortality rates across the United States. Methods. We analyzed county jail incarceration rates from the Bureau of Justice Statistics from 1987 to 2016 for 1884 counties and mortality rates from the National Vital Statistics System. We fit 1-year-lagged quasi-Poisson 2-way fixed-effects models, controlling for unmeasured stable county characteristics, and measured time-varying confounders, including county poverty and crime rates. Results. A within-county increase in jail incarceration rates from the first to second quartile was associated with a 2.5% increase in mortality rates, adjusting for confounders (risk ratio [RR] = 1.03; 95% confidence interval [CI] = 1.02, 1.03). This association followed a dose–response relationship and was stronger for mortality among those aged 15 to 34 years (RR = 1.07; 95% CI = 1.06, 1.09). Conclusions. Within-county increases in jail incarceration rates are associated with increases in subsequent mortality rates after adjusting for important confounders. Public Health Implications. Our findings add to the growing body of empirical evidence of the harms of mass incarceration. The criminal justice reform and decarceration movements can use these findings as they develop strategies to end mass incarceration.
Monitoring the Pulse of a Well Through Sealed Wellbore Pressure Monitoring, a Breakthrough Diagnostic With a Multi-Basin Case Study
Authors: Haustveit Kyle , Elliott Brendan , Haffener Jackson , Ketter Chris , O'Brien Josh , Almasoodi Mouin , Moos Sheldon , Klaassen Trevor , Dahlgren Kyle , Ingle Trevor , Roberts Jon , Gerding Eric , Borell Jarret , Sharma Sundeep , Deeg Wolfgang 
Published: January 2020

Abstract
Over the past decade the shale revolution has driven a dramatic increase in hydraulically stimulated wells. Since 2010, hundreds of thousands of hydraulically fractured stages have been completed on an annual basis in the US alone. It is well known that the geology and geomechanical features vary along a lateral due to landing variations, structural changes, depletion impacts, and intra-well shadowing. The variations along a lateral have the potential to impact the fluid distribution in a multi-cluster stimulation which can impact the drainage pattern and ultimately the economics of the well and unit being exploited. Due to the lack of low-cost, scalable diagnostics capable of monitoring cluster efficiency, most wells are completed using geometric cluster spacing and the same pump schedule across a lateral with known variations.
A breakthrough patent-pending pressure monitoring technique using an offset sealed wellbore as a monitoring source has led to advancements in quantifying cluster efficiencies of hydraulic stimulations in real-time. To date, over 1,500 stages have been monitored using the technique. Sealed Wellbore Pressure Monitoring (SWPM) is a low-cost, non-intrusive method used to evaluate and quantify fracture growth rates and fracture driven interactions during a hydraulic stimulation. The measurements can be made with only a surface pressure gauge on a monitor well.
SWPM provides insight into a wide range of fracture characteristics and can be applied to improve the understanding of hydraulic fractures in the following ways:
Qualitative cluster efficiency/fluid distribution Fracture count in the far-field Fracture height and fracture half-length Depletion identification and mitigation Fracture model calibration Fracture closure time estimation
The technique has been validated using low frequency Distributed Acoustic Sensing (DAS) strain monitoring, microseismic monitoring, video-based downhole perforation imaging, and production logging. This paper will review multiple SWPM case studies collected from projects performed in the Anadarko Basin (Meramec), Permian Delaware Basin (Wolfcamp), and Permian Delaware Basin (Leonard/Avalon).
A qualitative transcriptional signature to reclassify histological grade of ER-positive breast cancer patients
Authors: Li Jing , Jiang Wenbin , Liang Qirui , Liu Guanghao , Dai Yupeng , Zheng Hailong , Yang Jing , Cai Hao , Guo Zheng 
Published: January 2020

Abstract

PurposeHistological grade (HG) is commonly adopted as a prognostic factor for ER-positive breast cancer patients. However, HG evaluation methods, such as the pathological Nottingham grading system, are highly subjective with only 50%-85% inter-observer agreements. Specifically, the subjectivity in the pathological assignment of the intermediate grade (HG2) breast cancers, comprising of about half of breast cancer cases, results in uncertain disease outcomes prediction. Here, we developed a qualitative transcriptional signature, based on within-sample relative expression orderings (REOs) of gene pairs, to define HG1 and HG3 and reclassify pathologically-determined HG2 (denoted as pHG2) breast cancer patients.ResultsFrom the gene pairs with significantly stable REOs in pathologically-determined HG1 (denoted as pHG1) samples and reversely stable REOs in pathologically-determined HG3 (denoted as pHG3) samples, concordantly identified from seven datasets, we extracted a signature which could determine the HG state of samples through evaluating whether the within-sample REOs match with the patterns of the pHG1 REOs or pHG3 REOs. A sample was classified into the HG3 group if at least a half of the REOs of the 10 gene pairs signature within this sample voted for HG3; otherwise, HG1. Using four datasets including samples of early stage (I–II) ER-positive breast cancer patients who accepted surgery only, we validated that this signature was able to reclassify pHG2 patients into HG1 and HG3 groups with significantly different survival time. For the original pHG1 and pHG3 patients, the signature could also more accurately and objectively stratify them into distinct prognostic groups. And the up-regulated and down down-regulated genes in HG1 compared with HG3 involved in cell proliferation and extracellular signal transduction pathways respectively. By comparing with existing signatures, 10-GPS was with prognostic significance and was more aligned with survival of patients especially for pHG2 samples.ConclusionsThe transcriptional qualitative signature can provide an objective assessment of HG states of ER-positive breast cancer patients, especially for reclassifying patients with pHG2, to assist decision making on clinical therapy.
Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample.
Authors: Barros Jorge , Morales Susana , García Arnol , Echávarri Orietta , Fischman Ronit , Szmulewicz Marta , Moya Claudia , Núñez Catalina , Tomicic Alemka 
Published: January 2020

Abstract

This study aimed to determine conditional dependence relationships of variables that contribute to psychological vulnerability associated with suicide risk. A Bayesian network (BN) was developed and applied to establish conditional dependence relationships among variables for each individual subject studied. These conditional dependencies represented the different states that patients could experience in relation to suicidal behavior (SB). The clinical sample included 650 mental health patients with mood and anxiety symptomatology. The results mainly indicated that variables within the Bayesian network are part of each patient’s state of psychological vulnerability and have the potential to impact such states and that these variables coexist and are relatively stable over time. These results have enabled us to offer a tool to detect states of psychological vulnerability associated with suicide risk. If we accept that suicidal behaviors (vulnerability, ideation, and suicidal attempts) exist in constant change and are unstable, we can investigate what individuals experience at specific moments to become better able to intervene in a timely manner to prevent such behaviors. Future testing of the tool developed in this study is needed, not only in specialized mental health environments but also in other environments with high rates of mental illness, such as primary healthcare facilities and educational institutions (schools and universities).
Increased plasma concentration of cell-free DNA precedes disease recurrence in children with high-risk neuroblastoma
Authors: Su Yan , Wang Lijun , Jiang Chiyi , Yue Zhixia , Fan Hongjun , Hong Huimin , Duan Chao , Jin Mei , Zhang Dawei , Qiu Lihua , Cheng Xianfeng , Xu Zhong , Ma Xiaoli 
Published: January 2020

Abstract
Background: Neuroblastoma is the most common extracranial solid tumor of childhood. The high rate of recurrence is associated with a low survival rate for patients with high-risk neuroblastoma. There is thus an urgent need to identify effective predictive biomarkers of disease recurrence. Methods: A total of 116 patients with high-risk neuroblastoma were recruited at Beijing Children’s Hospital between February 2015 and December 2017. All patients received multidisciplinary treatment, were evaluated for the therapeutic response, and then initiated on maintenance treatment. Blood samples were collected at the beginning of maintenance treatment, every 3 months thereafter, and at the time of disease recurrence. Plasma levels of cell-free DNA (cfDNA) were quantified by qPCR. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of plasma cfDNA concentration to predict recurrence. Results: Of the 116 patients, 36 (31.0%) developed recurrence during maintenance treatment. The median time to recurrence was 19.00, 9.00, and 8.00 months for patients who had achieved complete response (n = 6), partial response (n = 25), and stable disease (n = 5), respectively, after multidisciplinary treatment. The median plasma cfDNA concentration at the time of recurrence was significantly higher than the concentration in recurrence-free patients throughout maintenance treatment (29.34 ng/mL vs 10.32 ng/mL). Patients recorded a plasma cfDNA level ≥29 ng/mL an average of 0.55 months before diagnosis of disease recurrence. ROC analysis of the power of plasma cfDNA to distinguish between patients with or without recurrence yielded an area under the curve of 0.825, with optimal sensitivity and specificity of 80.6% and 71.3%, respectively, at a cfDNA level of 12.93 ng/mL. Conclusions: High plasma cfDNA concentration is a potential molecular marker to signal disease recurrence in patients with high-risk neuroblastoma.
Factors determining recurrence in transient global amnesia
Authors: Tynas Rebecca , Panegyres Peter K 
Published: January 2020

Abstract
Background: Aetiology of transient global amnesia (TGA) remains uncertain, though many have been proposed, including ischaemic, migrainous or epileptic pathologies. Methods: We attempted to determine risk factors for TGA, as well as prognostic factors that may cause recurrence. We evaluated clinical history, family history and magnetic resonance diffusion-weighted imaging (DWI) studies of 93 prospective patients with TGA. Patients were followed from 2004-2016. Fifteen of 93 (16%) patients experienced a recurrence of TGA. Results: Among precipitating events, physical activities inducing Valsalva-like manoeuvres were most common, followed by emotional stress. Eighty-four patients had possible comorbidities or risk factors for TGA, though no single risk factor was ubiquitous. Risk factors associated with recurrence were head injury (isolated vs. recurrent, 16.7% vs. 53.5%, p < 0.01), depression (isolated vs. recurrent, 15.4% vs 46.7%, p = 0.01) and family history of dementia (isolated vs. recurrent, 20.5% vs. 46.7%, p = 0.03). Of 15 patients with confirmed recurrent TGA, two developed dementia and four subjective memory impairment. DWI lesions were observed in 24 patients and were located anywhere within the hippocampus. Conclusions: DWI lesions were not significantly associated with outcomes (recurrence, subjective memory impairment, dementia). We have found that depression, previous head injury and family history of dementia may predict TGA recurrence.
Exploring and analysing single cell multi-omics data with VDJView
Authors: Samir Jerome , Rizzetto Simone , Gupta Money , Luciani Fabio 
Published: January 2020

AbstractBackground Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.Results We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.Conclusions VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview .
Systematic analysis of the basic/helix-loop-helix (bHLH) transcription factor family in pummelo (Citrus grandis) and identification of the key members involved in the response to iron deficiency
Authors: Zhang Xiao-Yong , Qiu Jie-Ya , Hui Qiu-Ling , Xu Yuan-Yuan , He Yi-Zhong , Peng Liang-Zhi , fu xing-zheng 
Published: January 2020

Abstract
Background Iron (Fe) deficiency is a common problem in citrus production. As the second largest superfamily of transcription factors (TFs), the basic/helix-loop-helix (bHLH) proteins have been shown to participate in the regulation of Fe homeostasis and a series of other biological and developmental processes in plants. However, this family of members in citrus and their functions in citrus Fe deficiency are still largely unknown. Results In this study, we identified a total of 128 CgbHLHs from pummelo ( Citrus grandis ) genome that were classified into 18 subfamilies by phylogenetic comparison with Arabidopsis thaliana bHLH proteins. All of these CgbHLHs were randomly distributed on nine known (125 genes) and one unknown (3 genes) chromosomes, and 12 and 47 of them were identified to be tandem and segmental duplicated genes, respectively. Sequence analysis showed detailed characteristics of their intron-exon structures, bHLH domain and conserved motifs. Gene ontology (GO) analysis suggested that most of CgbHLHs were annotated to the nucleus, DNA-binding transcription factor activity, response to abiotic stimulus, reproduction, post-embryonic development, flower development and photosynthesis. In addition, 27 CgbHLH proteins were predicted to have direct or indirect protein-protein interactions. Based on GO annotation, RNA sequencing data in public database and qRT-PCR results, several of CgbHLHs were identified as the key candidates that respond to iron deficiency. Conclusions In total, 128 CgbHLH proteins were identified from pummelo, and their detailed sequence and structure characteristics and putative functions were analyzed. This study provides comprehensive information for further functional elucidation of CgbHLH genes in citrus.
Lenticulostriate arteries appearance before thrombectomy predicts good outcome in acute middle cerebral artery occlusion
Authors: Liu Feifeng , Chen Chen , Hong Lan , Shen Hao , Cao Wenjie , Dong Qiang , Yang Xinyi , Guo Mengruo , Li Ying , Xiao Yaping , Cheng Xin , Li Gang 
Published: January 2020

Abstract
Purpose: Endovascular therapy is widely used in acute large vessel occlusion. This study investigated whether imaging of lateral lenticulostriate arteries(LSAs) before thrombectomy would potentially be helpful for predicting prognosis of patients with acute M1 segment of middle cerebral artery occlusion(MCAO).Methods: 59 consecutive patients with acute M1 segment of MCAO treated with mechanical thrombectomy at two comprehensive stroke center were analyzed. Patients were categorized into LSA+ (appearing of lateral LSAs) and LSA- (sparing of lateral LSAs) group according to preprocedural digital substraction angiography (DSA). Baseline data and clinical outcomes were compared. A good clinical outcome was defined as a modified Rankin Scale score of 0 to 2 at 3 months. The association between clinical and imaging parameters and functional outcome was evaluated with logistic regression analysis.Results: LSA+ was shown in 36 patients (61%). LSA+ group had a significantly higher proportion of good outcome (72.2% vs. 8.7%, OR 27.3,95% CI 5.38-138.4, P<0.001), lower risk of symptomatic intracranial haemorrhages (sICH) ( 8.3% vs. 47.8%,OR 0.10,95% CI 0.02-0.42, P=0.001) and lower mortality in hospital (5.6% vs. 34.8%, OR 0.11,95% CI 0.02 -0.58, P<0.004) compared with LSA- group. Patients in LSA+ group had lower baseline NIHSS score(P<0.01) and NIHSS score at 14 days(P<0.01) and smaller infarct core volume (P=0.016) on computed tomography perfusion imaging (CTP) compared to the LSA- group. Multivariate logistic regression analysis showed that a small infarct core volume (OR 6.74,95% CI 1.148-39.569, P=0.035) and LSA+( OR 22.114,95% CI 3.339-146.470, P=0.001) were associated with a good clinical outcome.Conclusions: Our data suggest that appearance of lateral LSAs before mechanical thrombectomy would be potentially helpful for predicting favorable prognosis of patients with acute M1 segment of MCAO.
Separating the signal from the noise in metagenomic cell-free DNA sequencing
Authors: Burnham Philip , Gomez-Lopez Nardhy , Heyang Michael , Cheng Alexandre Pellan , Lenz Joan Sesing , Dadhania Darshana , Lee John Richard , Suthanthiran Manikkam , Romero Roberto , De Vlaminck Iwijn 
Published: January 2020

Abstract

Background: Cell-free DNA (cfDNA) in blood, urine and other biofluids provides a unique window into human health. A proportion of cfDNA is derived from bacteria and viruses, creating opportunities for the diagnosis of infection via metagenomic sequencing. The total biomass of microbial-derived cfDNA in clinical isolates is low, which makes metagenomic cfDNA sequencing susceptible to contamination and alignment noise. Results: Here, we report Low Biomass Background Correction (LBBC), a bioinformatics noise filtering tool informed by the uniformity of the coverage of microbial genomes and the batch variation in the absolute abundance of microbial cfDNA. We demonstrate that LBBC leads to a dramatic reduction in false positive rate while minimally affecting the true positive rate for a cfDNA test to screen for urinary tract infection. We next performed high throughput sequencing of cfDNA in amniotic fluid collected from term uncomplicated pregnancies or those complicated with clinical chorioamnionitis with and without intra-amniotic infection. Conclusions: The data provide unique insight into the properties of fetal and maternal cfDNA in amniotic fluid, demonstrate the utility of cfDNA to screen for intra-amniotic infection, support the view that the amniotic fluid is sterile during normal pregnancy, and reveal cases of intra-amniotic inflammation without infection at term.
Protein kinase A is involved in neuropathic pain by activating the p38MAPK pathway to mediate spinal cord cell apoptosis
Authors: Deng Yajun , Yang Liang , Xie Qiqi , Yang Fengbiao , Li Guoqiang , Zhang Guangzhi , Li Shaoping , Wu Zuolong , Wang Jing , Kang Xuewen 
Published: January 2020

Abstract
The authors have withdrawn this preprint from Research Square
Predictive value of gamma-glutamyl transpeptidase to lymphocyte count ratio in hepatocellular carcinoma patients with microvascular invasion
Authors: Zhang Hongxing , Zhou Yu , Li Yicheng , Qin Wanying , Zi Yunhua , Liu Yulan , Qiu Xiaoying , Xu Hongyuan , Liao Weijia , Huang Zhaoquan 
Published: January 2020

Abstract
Background: Microvascular invasion (MVI) is an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC). However, there is still a lack of preoperative markers to predict MVI in HCC. This study intends to explore the potential application value of the gamma-glutamyl transpeptidase (GGT) to lymphocyte count ratio (GLR) in predicting MVI in HCC and provide guidance for clinical diagnosis and treatment.Methods: From March 2010 to December 2015, 230 HCC patients who underwent surgical treatment in the Affiliated Hospital of Guilin Medical University were selected. Clinicopathological parameters between the MVI group (n = 115) and the non-MVI group (n = 115) were comparatively analyzed. The GLR was used as the potential risk factor for HCC with MVI, and its optimal cut-off value was estimated by using the receiver operating characteristic (ROC) curve. The Kaplan-Meier method was used to analyze the survival of HCC patients, and univariate and multivariate Cox regression analyses were used to establish independent predictors affecting postoperative HCC patients.Results: The GLR levels in the MVI group and non-MVI group were 84.83 ± 61.84 and 38.42 ± 33.52 (p < 0.001), respectively. According to ROC curve analysis, the optimal cut-off value of GLR was 56.0, and the area under the ROC curve (AUC) was 0.781 (95% CI, 0.719-0.833) for the risk prediction of MVI in HCC patients. Multivariate analysis showed that tumor size > 5 cm, HCC combined with MVI and GLR > 56.0 were independent risk factors for poor prognosis in HCC patients. In addition, compared with the non-MVI group, patients in the MVI group had shorter progression-free survival (PFS) and overall survival (OS).Conclusion: GLR could be a predictive biomarker of HCC after operation and a potential predictor of HCC combined with MVI.