bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a radiomics nomogram for identification of severity of patients with COVID-19
Authors: Wang Jian , Xu Zhihua , Cheng Guohua , Hu Qiuxiang , He Linyang , Xia Junli , Zhu Xiandi , Yang Guangzhao , Guo Youmin , Xie Zongyu 
Published: August 2020

Abstract
Background The coronavirus disease 2019 (COVID-19) is a pandemic now, and the severe COVID-19 determines the management and treatment, even prognosis. Thus, we aim to develop and validate a radiomics nomogram for identifying severe patients with COVID-19.Methods There were 156 and 104 patients with COVID-19 enrolled in primary and validation cohorts respectively. Radiomics features were extracted from chest CT images. Least absolute shrinkage and selection operator (LASSO) method was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a predictive model, and the radiomics signature, abnormal WBC counts, and comorbidity were incorporated and presented as a radiomics nomogram. The performance of the nomogram was assessed through its calibration, discrimination, and clinical usefulness.Results The radiomics signature consisting of 4 selected features was significantly associated with clinical condition of patients with COVID-19 in the primary and validation cohorts (P < 0.001). The radiomics nomogram including radiomics signature, comorbidity and abnormal WBC counts, showed good discrimination of severe COVID-19, with an AUC of 0.972, and good calibration in the primary cohort. Application of the nomogram in the validation cohort still gave good discrimination with an AUC of 0.978 and good calibration. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful to identify the severe COVID-19.Conclusions We present an easy-to-use radiomics nomogram to identify the severe patients with COVID-19 for better guiding a prompt management and treatment.
Improving Lateral Safety Distance-Based on Feature Detection and Probabilistic Roadmaps for Unmanned Vehicle Path Planning
Authors: Wang Jianfeng , Chang Guangliang , Li Weihua , Yang Na , Wang Boqian , Sun Yuhui 
Published: August 2020

Abstract
Most of the existing path-planning algorithms do not consider lateral safe distance requirements in practical applications. Hence, in this study, a new path point selection algorithm is proposed for path planning. The algorithm first used the Harris and Line Segment Detector(LSD) algorithms to detect and obtain the corner and edge information of obstacles. A vertical line was provided to the edge of the surrounding obstacles along each corner successively. In this process, the narrow impassable area in the map was filtered and removed by setting a safety threshold, and the foot of the vertical coordinates were simultaneously obtained. The corresponding midpoint coordinates were solved by using the corner coordinates and the foot of the corresponding perpendicular coordinates. The midpoint coordinates were used as candidate points to generate path points. These candidate points are screened and relaxed using the Probabilistic Roadmaps(PRM) algorithm to obtain the series of path points required. Finally, the path was planned according to these path points and smoothed using the Quadratic polynomial interpolation method(QPMI). Through simulation experiments, the method proposed in this study can solve a unique path without randomness under given conditions, and the probability of a collision in practical applications was reduced.
Cancer Cell Nucleus Leads the Way
Authors: Renz Malte 
Published: August 2020

Abstract
ObjectiveCancer cell metastasis determines disease prognosis. During cancer cell metastasis, the cancer cell and the cancer cell nucleus have to undergo extreme shape changes. To monitor shape changes of cancer cells and cancer cell nuclei and the positioning of the cancer cell nucleus during cancer cell invasion, a customized invasion assay with 8-μm pores and reconstituted basal membrane was imaged using fluorescence live-cell microscopy.ResultsThe observed cells changed their shape from a distinct fibroblast-like spindle shape to an amoeboid shape without polarization immediately after the passage through an 8-μm pore of the invasion assay. During the process of invasion, the cancer cell centered the cancer cell nucleus over the 8-μm pore, and cancer cell nucleus and adjacent cytoplasmic areas moved first through such a pore. Seemingly testing if the largest and least deformable organelle may fit, the cancer cell nucleus led the way through the porous membrane of the invasion assay.
Analysis of mRNA-lncRNA and mRNA-lncRNA-Pathway co-expression networks based on WGCNA in developing pediatric sepsis
Authors: Zhang Xiaojuan , Cui Yuqing , Ding Xianfei , Liu Shaohua , Han Bing , Duan Xiaoguang , Zhang Haibo , Sun Tongwen 
Published: August 2020

Abstract
Background: Pediatric sepsis is a great threat in death worldwide. However, the pathogenesis has not been clearly understood until now in sepsis.Methods: This study identified differentially expressed mRNA (DEMs) and lncRNAs (DELs) based on Gene Expression Omnibus (GEO) database. And the weighted gene co-expression network analysis (WGCNA) was performed to explore co-expression modules associated with pediatric sepsis. Then Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, DEMs‑DELs and DEMs‑DELs-Pathway co-expression network analysis was conducted in selected significant module. Results: A total of 1941 DEMs and 225 DELs were used to conduct WGCNA. And the turquoise module was selected as the significant module that was associated with particular traits. The DEMs functions associated with many vital processes were also shown by GO and KEGG pathway analysis in the turquoise module. Finally, 15 DEMs and 4 DELs (GSEC, NONHSAT160878.1, XR_926068.1 and RARA-AS1) were selected as candidate biomarkers in DEMs-DELs-Pathway co-expression network. Conclusions: Our study identified 15 DEMs and 4 DELs as diagnostic markers, which could also provide more directions to study molecular mechanism of pediatric sepsis.
Cholesterol, hypertension and chronic spine problems: a logit model focusing on rural Brazilian residents in 2013
Authors: Cruz Alice Aloísia da , Garcias Marcos de Oliveira 
Published: August 2020

Abstract
Background: Over recent decades, Brazil’s health indicators have improved; however, access to the country’s health services is not homogeneous, with urban areas being better served than rural areas. The general objective of this work is to identify the influence of rural residence and other factors on the incidence of chronic spine problems, hypertension, and elevated levels of cholesterol in Brazil using the last Brazilian National Health Survey (NHS - 2013)) definitions and data. The analysis provided by this study contributes data that can be used to determine the probability of these three conditions occurring in Brazil and identifies the most vulnerable rural groups as defined by diet, physical activity, smoking, and alcohol consumption. Method: A logit model was estimated to identify the influence of the variables rural residence, sex, age, race, education, health insurance, work, Body Mass Index (BMI), consumption habits, and region of residence on the chronic conditions analyzed. Results: Results show that rural residents are 5.8% more likely to have chronic spine problems and 0.9% less likely to have hypertension than urban residents. The incidence of all conditions was lower in men than women. The Body Mass Index (BMI) value also influences the chance of having the conditions studied. Individuals with at least a secondary education were less affected by the analyzed conditions than those less educated. There were regional differences in these conditions’ incidence, mainly chronic spine problems and hypertension. Conclusions: The variables BMI, gender, and years of alcohol consumption had significance in all diseases analyzed. To correct underreporting issues, public policies should be directed to expand rural health services. Additionally, actions should be taken to raise the public's awareness of the effects of obesity and alcohol consumption on health.
Can’t see the wood for the trees: Using common likelihoods to share information regarding selection of functional form in survival analysis
Authors: Hawkins Neil , Parker Chris , Scott David A. 
Published: August 2020

Abstract
Background

The estimation of mean survival is a key consideration when estimating the cost-effectiveness of interventions. Estimation typically requires extrapolation using parametric survival analysis and may be sensitive to choice of functional form. We demonstrate a simple method that allows goodness-of-fit information to be assessed jointly across studies, where such information is believed likely to be exchangeable, to help inform the selection of functional form for parametric survival analysis.
Methods

Individual patient data for survival was estimated from digitised Kaplan-Meier curves for four trials in advanced soft tissue sarcoma. A range of parametric survival models were fitted. Two approaches were explored for identifying the preferred parametric model: (i) selecting functional forms independently for each study; and (ii) selecting a common functional form across studies. Akaike’s Information Criterion (AIC) or Bayesian Information Criterion (BIC) were used to select optimal functional form. For approach (ii) joint BIC or AIC statistics were calculated for each model by combining the components of the AIC or BIC, respectively, across studies. A bootstrap analysis was conducted to estimate the uncertainty in selection of functional form.
Results

Estimates of mean survival varied markedly according to choice of functional form. Independent selection led to different functional forms being selected for each study with considerable uncertainty regarding the optimum functional form according to AIC or BIC. In this case study, selecting an optimum functional form based on joint AIC or BIC across studies reduced uncertainty in model selection and variance in mean survival compared to selection of functional form independently.
Conclusion

Extrapolation of estimates of survival may be sensitive to choice of functional form. If it is believed, a priori, reasonable to share information regarding the choice of functional form for survival analysis across studies, estimating joint goodness-of-fit information across studies could reduce uncertainty and lead to more reliable estimates of mean survival and cost-effectiveness.
Hemodynamic and Behavioural Changes in Older Adults During Cognitively Demanding Dual-Tasks
Authors: Salzman Talia , Vallejo Diana Tobón , Polskaia Nadia , Michaud Lucas , St-Amant Gabrielle , Lajoie Yves , Fraser Sarah 
Published: August 2020

Abstract
Background: Executive functions play a fundamental role in walking by integrating information from cognitive-motor pathways. Subtle changes in brain activation and behaviour may help identify older adults who are more susceptible to executive function deficits with advancing age due to prefrontal cortex deterioration. This study aims to examine how older adults mitigate executive demands while walking during cognitively demanding tasks.Methods: Twenty healthy older adults (M = 71.8 years, SD = 6.4) performed simple reaction time (SRT), go/no-go (GNG), n-back (NBK) and double number sequence (DNS) cognitive tasks of increasing difficulty while walking (i.e., dual-task). Functional near-infrared spectroscopy (fNIRS) was used to measure the hemodynamic response (i.e., oxy- [HbO2] and deoxyhemoglobin [HbR]) changes in the prefrontal cortex (PFC) during dual- and single-tasks (i.e., walking alone). In addition, performance was measured using gait speed (m/s), response time (s) and accuracy (% correct). Results: Using repeated measures ANOVAs, neural findings demonstrated a main effect of task such that ∆HbO2 (p = 0.047) and ∆HbR (p = 0.040) decreased between single- and dual-tasks. An interaction between task and cognitive difficulty (p = 0.014) revealed that gait speed decreased in the DNS between single- and dual-tasks. A main effect of task in response time indicated that the SRT response time was faster than all other difficulty levels (p < 0.001). Accuracy performance declined between single- and dual-tasks (p = 0.028) and across difficulty levels (p < 0.001) but were not significantly different between the NBK and DNS.Conclusion: Findings suggest that a healthy older adult sample might mitigate executive demands using an automatic locomotor control strategy such that shifting conscious attention away from walking during the dual-tasks resulted in decreased ∆HbO2 and ∆HbR. However, decreased prefrontal activation was inefficient at maintaining response time and accuracy performance and may be differently affected by increasing cognitive demands.
Maternal DHA supplementation influences sex-specific disruption of placental gene expression following early prenatal stress
Authors: Jašarević Eldin , Hecht Patrick M. , Fritsche Kevin L. , Geary David C. , Rivera Rocío M. , Beversdorf David 
Published: August 2020

Abstract
Background: Early life adversity is a risk factor for early developmental perturbations and contributes to the presentation of neuropsychiatric disorders in adulthood. Neurodevelopmental disorders exhibit a strong sex-bias in susceptibility, presentation, onset and severity, although mechanisms conferring vulnerability are not well understood. Environmental perturbations during pregnancy, such as malnutrition or stress, have been associated with sex-specific reprogramming that contribute to increased disease risk in adulthood, whereby stress and nutritional insufficiency may be additive and further exacerbate poor offspring outcomes. Methods: To determine whether maternal docosahexanoic acid (DHA) supplementation effects offspring outcome following exposure to early prenatal stress (EPS), dams were fed nutritionally complete semi-purified diets that either contained adequate essential omega-6 (n-6) and omega-3 (n-3) fatty acids from corn and soy oils (control diet, CTL) or an experimental diet that was nutritionally-equivalent to the CTL diet, but contained 1% by weight DHA, a long-chain omega-3 fatty acid (22:6n-3). Dams were administered chronic variable stress during the first week of pregnancy (Embryonic day, E0.5 – 7.5). Developmental milestones were assessed at E 12.5. Results: Exposure to early prenatal stress (EPS) decreased placenta and embryo weight in males, but not females, exposed to CTL diet. DHA-enrichment reversed the sex-specific decrease in placenta and embryo weight following EPS. Early prenatal exposure upregulated expression of genes associated with oxygen and nutrient transport, including hypoxia inducible factor 3α (HIF3α), peroxisome proliferator-activated receptor alpha (PPARα), and insulin like growth binding factor 1 (IGFBP1), in placenta of CTL diet males exposed to EPS. DHA-enrichment in EPS-exposed animals abrogated male-specific upregulation of PPARα, HIF3α, and IGFBP1. Conclusions: This suggests that maternal dietary DHA enrichment may buffer against maternal stress programming of sex-specific outcomes during early development.
Converting Scores Between the PANSS and SAPS/SANS Beyond the Positive/Negative Dichotomy
Authors: Grot Stéphanie , Giguère Charles-Édouard , Smine Salima , Mongeau-Pérusse Violaine , Nguyen Dana Diem , Preda Adrian , Potvin Stéphane , Erp Theo van , Orban Pierre 
Published: August 2020

Abstract
Background: Previous work provided conversion equations for overall indices of positive and negative symptomatology between the two most widely used scales to assess symptom severity in schizophrenia, namely the Positive and Negative Syndrome Scale (PANSS) and the Scales for the Assessment of Positive/Negative Symptoms (SAPS/SANS). Our objective was to provide such conversion equations for subdomains of positive and negative symptomatology in order to better account for the diversity of symptom profiles in schizophrenia. Method: Symptoms severity was assessed using both the PANSS and SAPS/SANS in 205 patients with schizophrenia. Two exploratory factor analyses combining items from both scales were first performed separately in the positive and negative symptom domains. For each identified factor, linear regression analyses were then conducted to obtain conversion equations from the PANSS to the SAPS/SANS and vice versa. Linear regression model estimation was performed on 80% of the data, and reliability was then evaluated on the 20% remaining data using intra-class correlation coefficient between the original and predicted scores. This procedure was repeated 100 times with random samplings for each factor cross-scale conversion.Results: Three-factor solutions were favored both in the positive and negative symptom domains. Based on the nature of items that strongly loaded on the different factors, positive factors were termed ‘Hallucinations’, ‘Delusions’ and ‘Disorganization’, while negative factors were associated with ‘Expressivity’, ‘Amotivation’ and ‘Cognition’. Intra-class correlation coefficients between the original and predicted scores were good to excellent (0.68-0.87) for all regressions, but for the cognition factor which were deemed as low (0.25, 0.26).Conclusion: The symptom subdomains identified by the decomposition of the positive and negative domains were consistent with current descriptions of symptom dimensions in schizophrenia. With the exception of the cognition subdomain, symptom severity scores can be converted with good accuracy between scales, beyond the positive/negative symptom dichotomy. Conversion equations are implemented in an R Shiny app to facilitate their use by the clinical research community.
Gradually increased dyslipidemia in human immunodeficiency virus infected male patients with tenofovir plus lamivudine plus efavirenz primary treatment: a 3-year follow-up study
Authors: liu dafeng , Zhao Bennan , Zhang Xinyi , Gao Fengjiao , Kang Jun , Zheng Xue , Lan Lijuan , He Yinsheng , He Shenghua 
Published: August 2020

Abstract
IntroductionSince the start of highly active antiretroviral therapy (HAART) with TDF plus 3TC plus EFV, the long-term dynamic characteristics of lipid and purine metabolism in patients infected with human immunodeficiency virus (HIV) was unclear and worth studying.MethodsA prospective follow-up cohort study was the way. Sixty-one treatment-naive HIV infected male patients were divided into three groups based on the baseline CD4 + T cell count (26, 12, 23cases in < 200, from 200 to 350, > 350 three groups, respectively). Lipid and purine metabolism parameters of those patients within 144 weeks were analyzed.ResultTG, TC, LDL-c and HDL-c level all gradually increased within 144 weeks, but statistical significances of TC level and HDL-c level were only found (F = 4.214, 5.518, P = 0.001, 0.000 ,respectively). Moreover the percentage of hypercholesterolemia, hyper LDL cholesterolemia and hypertriglyceridemia all gradually increased, low HDL cholesterolemia gradually decreased, but there was only obvious difference of the latter (χ2 = 16.105, P = 0.0007).Furthermore the lower the baseline CD4 + T lymphocyte counts, the higher TG level, the lower TC level, LDL-c level and HDL-c level, but only significant difference of LDL-c level between three groups at baseline was found (F = 3.256,P = 0.0457).Although UA level and the percentages of hyperuricemia gradually increased within 144 weeks, but there was no significant difference between different follow-up time points groups and between three CD4 + T cell count groups (all P༞0.05).ConclusionsThese findings provide a reference for clinicians to monitor lipid metabolism parameters closely during long-term HAART with TDF plus 3TC plus EFV regimen.
Comprehensive Effect of Salt Stress and Peanut Cultivars on the Bacterial Community Structure and Diversity of Peanut Rhizosphere Soils
Authors: Xu Yang , Ding Hong , Wen Saiqun , Ci Dunwei , Zhang Guanchu , Yuan Guang , Qin Feifei , Dai Liangxiang , Zhang Zhimeng 
Published: August 2020

Abstract
Background: Plant rhizosphere bacterial communities influence plant growth and stress tolerance, which differs across cultivars and external environments. Peanut (Arachis hypogaea. L) as an important oil crop cultivated worldwide. However, relatively little is known about the comprehensive effects of environmental conditions and peanut cultivars on rhizosphere bacterial community structure and diversity. Results: Here, bacterial community structure diversity from rhizosphere soils of various susceptible and resistant peanut cultivars with or without salt stress was analyzed by 16S rRNA gene deep sequencing and quantitative PCR assays. Taxonomic analysis showed that the bacterial community predominantly consisted of phyla Actinobacteria, Proteobacteria, Chloroflexi, Acidobacteria, and Cyanobacteria. Among these bacteria, numbers of beneficial bacteria Cyanobacteria and Proteobacteria increased, while that of Acidobacteria decreased after salt treatment. Metabolic function prediction showed that the percentages of reads categorized to signaling transduction and inorganic ion transport and metabolism were higher in the salt-treated soils, which may be beneficial to plant survival and salt tolerance. Conclusions: Overall, rhizosphere bacterial community structure and population metabolism are affected by salt stress, which may be conducive to peanut stress tolerance in saline-alkali soil. The study is therefore crucially important to develop the foundation for improving the salt tolerance of peanuts via modifying the soil bacterial community.
Estimation of sensitivity and specificity and calculation of sample size for a validation study with stratified sampling
Authors: Kubota Kiyoshi , Iwagami Masao , Yamaguchi Takuhiro 
Published: August 2020

Abstract
Background:We propose and evaluate the approximation formulae for the 95% confidence intervals (CIs) of the sensitivity and specificity and a formula to estimate sample size in a validation study with stratified sampling where positive samples satisfying the outcome definition and negative samples that do not are selected with different extraction fractions. Methods:We used the delta method to derive the approximation formulae for estimating the sensitivity and specificity and their CIs. From those formulae, we derived the formula to estimate the size of negative samples required to achieve the intended precision and the formula to estimate the precision for a negative sample size arbitrarily selected by the investigator. We conducted simulation studies in a population where 4% were outcome definition positive, the positive predictive value (PPV)=0.8, and the negative predictive value (NPV)=0.96, 0.98 and 0.99. The size of negative samples, n0, was either selected to make the 95% CI fall within ± 0.1, 0.15 and 0.2 or set arbitrarily as 150, 300 and 600. We assumed a binomial distribution for the positive and negative samples. The coverage of the 95% CIs of the sensitivity and specificity was calculated as the proportion of CIs including the sensitivity and specificity in the population, respectively. For selected studies, the coverage was also estimated by the bootstrap method. The sample size was evaluated by examining whether the observed precision was within the pre-specified value.Results:For the sensitivity, the coverage of the approximated 95% CIs was larger than 0.95 in most studies but in 9 of 18 selected studies derived by the bootstrap method. For the specificity, the coverage of the approximated 95% CIs was approximately 0.93 in most studies, but the coverage was more than 0.95 in all 18 studies derived by the bootstrap method. The calculated size of negative samples yielded precisions within the pre-specified values in most of the studies.Conclusion:The approximation formulae for the 95% CIs of the sensitivity and specificity for stratified validation studies are presented. These formulae will help in conducting and analysing validation studies with stratified sampling.