bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Musculoskeletal Limitations on Cardiac Rehabilitation Participation
Authors: Supervia Marta , Medina-Inojosa Jose R. , Pérez-Terzic Carmen M. , Sharma Saurabh , Goel Kashish , Vickers Douglas Kristin , Salz Karen , Thomas Randal J. 
Published: June 2021

Background: To help clarify a potential barrier to cardiac rehabilitation (CR) participation we sought to examine the association between musculoskeletal limitations (MSLs) and CR enrollment and participation.Methods: Consecutive CR eligible individuals hospitalized for a cardiac event (myocardial infarction, percutaneous coronary intervention, and/or coronary artery bypass graft) between the months of November 2007 and May 2008, were asked to complete a mailed survey within 2 weeks after hospital discharge, assessing demographic factors, Patient Health Questionnaire (PHQ-9), participation in CR and MSLs through a validated MSLs screening tool. CR enrollment rates were compared between patients with and without MSLs.Results: Three hundred and twenty-one (37%) of patients contacted responded to our survey, including 228 males (71%), with a mean age 68 ± 10.8 years, of whom 98% were Caucasian. Eighty-two percent of responders reported a musculoskeletal disorder at the time of hospital discharge. Arthritis was the most frequent diagnosis (45%). Muscle or joint pain sufficient to limit the ability to do moderate exercise was reported in 52% of the respondents. Problems with balance affected 37%, of whom 45% reported a fall within the previous year. No significant difference in CR enrollment was observed in respondents with and without MSLs [OR = 0.98, 95% CI (0.88–1.09), p = 0.750]. Similar results were found when severity and number of MSLs were taken into account. However, we found that when compared to those without MSLs, the presence of MSLs was associated with lower CR participation (OR = 0.80, 95%, CI: 0.65–0.97, p = 0.0252).Conclusion: Despite a high prevalence of MSLs among CR-eligible patients, we found no association between MSLs and CR enrollment. However, patients with MSLs attended significantly fewer CR sessions as compared to patients without them. CR programs should consider providing additional support and interventions to patients with MSLs in order to optimize their adherence to prescribed CR sessions.
Holey Graphene–Enabled Solvent-Free Preparation of Ultrahigh Mass Loading Selenium Cathodes for High Areal Capacity Lithium–Selenium Batteries
Authors: Plaza-Rivera Christian O. , Viggiano Rocco P. , Dornbusch Donald A. , Wu James J. , Connell John W. , Lin Yi 
Published: June 2021

Solvents and binders are typical requirements in conventional lithium ion battery electrode fabrication to enable intimate material mixing, mechanical robustness, and reproducibility. However, for high energy density conversion chemistry cathodes such as sulfur (S) and selenium (Se), the time-consuming solvent-based methods are proven unreliable to achieve high mass loading cathodes with sufficient quality. Here, we report a facile solvent-free and binder-free method to prepare high mass loading composite Se cathodes that is enabled by the use of holey graphene (hG) as a lightweight conductive scaffold. Holey graphene is a derivative of graphene and can be dry-pressed into robust discs by itself. It can also serve as a matrix to host materials such as Se for composite disc preparation in a mix-and-press process free of solvent and binder. The method allows the preparation of ultrahigh Se content cathodes (up to 90 wt% Se) and ultrahigh Se mass loading (up to 15.6 mg cm−2 in this work). These cathodes exhibit excellent Se utilization, high areal capacity (up to 9 mAh cm−2), and good rate performance. The dry-press approach also allows for the preparation of a layered composite cathode architecture, where a thin hG layer is inserted between the composite and the current collector to improve the electrical contact. A solvent-free approach is also used to prepare hG-based hybrids with metal sulfides to be incorporated into a composite cathode to help entrap soluble polyselenide intermediates. The hybrid material is compatible with the solvent-free mix-and-press electrode fabrication approach and shows promise in improving the Se retention. While further improvements are still required, this work demonstrates the outstanding potential of using this facile, solvent-free approach enabled by hG for fabrication of high-performance, high mass loading conversion chemistry cathodes.
Detecting lncRNA–Cancer Associations by Combining miRNAs, Genes, and Prognosis With Matrix Factorization
Authors: Yan Huan , Chai Hua , Zhao Huiying 
Published: June 2021

Motivation: Long non-coding RNAs (lncRNAs) play important roles in cancer development. Prediction of lncRNA–cancer association is necessary for efficiently discovering biomarkers and designing treatment for cancers. Currently, several methods have been developed to predict lncRNA–cancer associations. However, most of them do not consider the relationships between lncRNA with other molecules and with cancer prognosis, which has limited the accuracy of the prediction.Method: Here, we constructed relationship matrices between 1,679 lncRNAs, 2,759 miRNAs, and 16,410 genes and cancer prognosis on three types of cancers (breast, lung, and colorectal cancers) to predict lncRNA–cancer associations. The matrices were iteratively reconstructed by matrix factorization to optimize low-rank size. This method is called detecting lncRNA cancer association (DRACA).Results: Application of this method in the prediction of lncRNAs–breast cancer, lncRNA–lung cancer, and lncRNA–colorectal cancer associations achieved an area under curve (AUC) of 0.810, 0.796, and 0.795, respectively, by 10-fold cross-validations. The performances of DRACA in predicting associations between lncRNAs with three kinds of cancers were at least 6.6, 7.2, and 6.9% better than other methods, respectively. To our knowledge, this is the first method employing cancer prognosis in the prediction of lncRNA–cancer associations. When removing the relationships between cancer prognosis and genes, the AUCs were decreased 7.2, 0.6, and 5% for breast, lung, and colorectal cancers, respectively. Moreover, the predicted lncRNAs were found with greater numbers of somatic mutations than the lncRNAs not predicted as cancer-associated for three types of cancers. DRACA predicted many novel lncRNAs, whose expressions were found to be related to survival rates of patients. The method is available at https://github.com/Yanh35/DRACA.
Visualization and Analysis of Gene Expression in Stanford Type A Aortic Dissection Tissue Section by Spatial Transcriptomics
Authors: Li Yan-Hong , Cao Ying , Liu Fen , Zhao Qian , Adi Dilare , Huo Qiang , Liu Zheng , Luo Jun-Yi , Fang Bin-Bin , Tian Ting , Li Xiao-Mei , Liu Di , Yang Yi-Ning 
Published: June 2021

Background: Spatial transcriptomics enables gene expression events to be pinpointed to a specific location in biological tissues. We developed a molecular approach for low-cell and high-fiber Stanford type A aortic dissection and preliminarily explored and visualized the heterogeneity of ascending aortic types and mapping cell-type-specific gene expression to specific anatomical domains.Methods: We collected aortic samples from 15 patients with Stanford type A aortic dissection and a case of ascending aorta was randomly selected followed by 10x Genomics and spatial transcriptomics sequencing. In data processing of normalization, component analysis and dimensionality reduction analysis, different algorithms were compared to establish the pipeline suitable for human aortic tissue.Results: We identified 19,879 genes based on the count level of gene expression at different locations and they were divided into seven groups based on gene expression trends. Major cell that the population may contain are indicated, and we can find different main distribution of different cell types, among which the tearing sites were mainly macrophages and stem cells. The gene expression of these different locations and the cell types they may contain are correlated and discussed in terms of their involvement in immunity, regulation of oxygen homeostasis, regulation of cell structure and basic function.Conclusion: This approach provides a spatially resolved transcriptome− and tissue-wide perspective of the adult human aorta and will allow the application of human fibrous aortic tissues without any effect on genes in different layers with low RNA expression levels. Our findings will pave the way toward both a better understanding of Stanford type A aortic dissection pathogenesis and heterogeneity and the implementation of more effective personalized therapeutic approaches.
The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning
Authors: Chen Yan , Sun Zepang , Chen Wanlan , Liu Changyan , Chai Ruoyang , Ding Jingjing , Liu Wen , Feng Xianzhen , Zhou Jun , Shen Xiaoyi , Huang Shan , Xu Zhongqing 
Published: June 2021

BackgroundGastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies.MethodsBased on the abundance of tumor-infiltrating immune cells in GC patients from The Cancer Genome Atlas, we used unsupervised consensus clustering algorithm to identify robust clusters of patients, and assessed their reproducibility in an independent cohort from Gene Expression Omnibus. We further confirmed the feasibility of our immune subtypes in five independent pan-cancer cohorts. Finally, functional enrichment analyses were provided, and a deep learning model studying the pathological images was constructed to identify the immune subtypes.ResultsWe identified and validated three reproducible immune subtypes presented with diverse components of tumor-infiltrating immune cells, molecular features, and clinical characteristics. An immune-inflamed subtype 3, with better prognosis and the highest immune score, had the highest abundance of CD8+ T cells, CD4+ T–activated cells, follicular helper T cells, M1 macrophages, and NK cells among three subtypes. By contrast, an immune-excluded subtype 1, with the worst prognosis and the highest stromal score, demonstrated the highest infiltration of CD4+ T resting cells, regulatory T cells, B cells, and dendritic cells, while an immune-desert subtype 2, with an intermediate prognosis and the lowest immune score, demonstrated the highest infiltration of M2 macrophages and mast cells, and the lowest infiltration of M1 macrophages. Besides, higher proportion of EVB and MSI of TCGA molecular subtyping, over expression of CTLA4, PD1, PDL1, and TP53, and low expression of JAK1 were observed in immune subtype 3, which consisted with the results from Gene Set Enrichment Analysis. These subtypes may suggest different immunotherapy strategies. Finally, deep learning can predict the immune subtypes well.ConclusionThis study offers a conceptual frame to better understand the tumor immune microenvironment of GC. Future work is required to estimate its reference value for the design of immune-related studies and immunotherapy selection.
Early Prediction of Mortality, Severity, and Length of Stay in the Intensive Care Unit of Sepsis Patients Based on Sepsis 3.0 by Machine Learning Models
Authors: Su Longxiang , Xu Zheng , Chang Fengxiang , Ma Yingying , Liu Shengjun , Jiang Huizhen , Wang Hao , Li Dongkai , Chen Huan , Zhou Xiang , Hong Na , Zhu Weiguo , Long Yun 
Published: June 2021

Background: Early prediction of the clinical outcome of patients with sepsis is of great significance and can guide treatment and reduce the mortality of patients. However, it is clinically difficult for clinicians.Methods: A total of 2,224 patients with sepsis were involved over a 3-year period (2016–2018) in the intensive care unit (ICU) of Peking Union Medical College Hospital. With all the key medical data from the first 6 h in the ICU, three machine learning models, logistic regression, random forest, and XGBoost, were used to predict mortality, severity (sepsis/septic shock), and length of ICU stay (LOS) (&gt;6 days, ≤ 6 days). Missing data imputation and oversampling were completed on the dataset before introduction into the models.Results: Compared to the mortality and LOS predictions, the severity prediction achieved the best classification results, based on the area under the operating receiver characteristics (AUC), with the random forest classifier (sensitivity = 0.65, specificity = 0.73, F1 score = 0.72, AUC = 0.79). The random forest model also showed the best overall performance (mortality prediction: sensitivity = 0.50, specificity = 0.84, F1 score = 0.66, AUC = 0.74; LOS prediction: sensitivity = 0.79, specificity = 0.66, F1 score = 0.69, AUC = 0.76) among the three models. The predictive ability of the SOFA score itself was inferior to that of the above three models.Conclusions: Using the random forest classifier in the first 6 h of ICU admission can provide a comprehensive early warning of sepsis, which will contribute to the formulation and management of clinical decisions and the allocation and management of resources.
The Impact of Portal Vein Thrombosis on the Prognosis of Patients With Cirrhosis: A Retrospective Propensity-Score Matched Study
Authors: Chen Zhiji , Ran Tao , Cao Haiyan , Xu Feng , Zhou Zhi-hang , He Song 
Published: June 2021

Objectives: To investigate the impact of portal vein thrombosis (PVT) on cirrhosis decompensation and survival of cirrhosis.Methods: In this retrospective observational study between January 2012 and August 2020, 117 patients with cirrhotic PVT and 125 patients with cirrhosis were included. Propensity score matching (PSM) was applied to reduce the bias. The clinical characteristics of non-tumoral PVT in cirrhosis and its influence on cirrhosis decompensation and survival were analyzed.Results: The median follow-up for the PVT group was 15 (8.0–23.0) months and for the non-thrombosis group 14 (8.0–23.5) months. The presence of PVT was related with esophageal varices, higher Child-Pugh score and MELD score (P &lt; 0.05). Most PVTs were partial (106/117). Non-occlusive PVT disappeared on later examinations in 32/106 patients (30.19%), of which six patients reappeared. All the 11 patients with occlusive PVT remained occlusive, among which five patients (45.45%) developed portal cavernoma. There was no significant correlation between PVT and decompensation or survival before or after PSM. Multivariate analysis identified only Child-Pugh score (HR = 2.210, 95% CI: 1.332–3.667) and serum sodium level (HR = 0.818, 95% CI: 0.717–0.933) as independent factors for death.Conclusion: Though PVT is associated with greater Child-Pugh score and MELD score, it has no significant impact on the progression of cirrhosis.
Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma
Authors: Yang Yuan , Wu Guozhi , Li Qiang , Zheng Ya , Liu Min , Zhou Lingshan , Chen Zhaofeng , Wang Yuping , Guo Qinghong , Ji Rui , Zhou Yongning 
Published: June 2021

Background: Hepatocellular carcinoma (HCC) is one of the highly heterogeneous cancers that lacks an effective risk model for prognosis prediction. Therefore, we searched for angiogenesis-related immune genes that affected the prognosis of HCC to construct a risk model and studied the role of this model in HCC.Methods: In this study, we collected the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. Pearson correlation analysis was performed to identify the association between immune genes and angiogenesis-related genes. Consensus clustering was applied to divide patients into clusters A and B. Subsequently, we studied the differentially expressed angiogenesis-related immune genes (DEari-genes) that affected the prognosis of HCC. The most significant features were identified by least absolute shrinkage and selection operator (LASSO) regression, and a risk model was constructed. The reliability of the risk model was evaluated in the TCGA discovery cohort and the ICGC validation cohort. In addition, we compared the novel risk model to the previous models based on ROC analysis. ssGSEA analysis was used for function evaluation, and pRRophetic was utilized to predict the sensitivity of administering chemotherapeutic agents.Results: Cluster A patients had favorable survival rates. A total of 23 DEari-genes were correlated with the prognosis of HCC. A five-gene (including BIRC5, KITLG, PGF, SPP1, and SHC1) signature-based risk model was constructed. After regrouping the HCC patients by the median score, we could effectively discriminate between them based on the adverse survival outcome, the unique tumor immune microenvironment, and low chemosensitivity.Conclusion: The five-gene signature-based risk score established by ari-genes showed a promising clinical prediction value.
To Explore the Predictive Power of Visuomotor Network Dysfunctions in Mild Cognitive Impairment and Alzheimer’s Disease
Authors: Staal Justine , Mattace-Raso Francesco , Daniels Hennie A. M. , van der Steen Johannes , Pel Johan J. M. 
Published: June 2021

BackgroundResearch into Alzheimer’s disease has shifted toward the identification of minimally invasive and less time-consuming modalities to define preclinical stages of Alzheimer’s disease.MethodHere, we propose visuomotor network dysfunctions as a potential biomarker in AD and its prodromal stage, mild cognitive impairment with underlying the Alzheimer’s disease pathology. The functionality of this network was tested in terms of timing, accuracy, and speed with goal-directed eye-hand tasks. The predictive power was determined by comparing the classification performance of a zero-rule algorithm (baseline), a decision tree, a support vector machine, and a neural network using functional parameters to classify controls without cognitive disorders, mild cognitive impaired patients, and Alzheimer’s disease patients.ResultsFair to good classification was achieved between controls and patients, controls and mild cognitive impaired patients, and between controls and Alzheimer’s disease patients with the support vector machine (77–82% accuracy, 57–93% sensitivity, 63–90% specificity, 0.74–0.78 area under the curve). Classification between mild cognitive impaired patients and Alzheimer’s disease patients was poor, as no algorithm outperformed the baseline (63% accuracy, 0% sensitivity, 100% specificity, 0.50 area under the curve).Comparison with Existing Method(s)The classification performance found in the present study is comparable to that of the existing CSF and MRI biomarkers.ConclusionThe data suggest that visuomotor network dysfunctions have potential in biomarker research and the proposed eye-hand tasks could add to existing tests to form a clear definition of the preclinical phenotype of AD.
Cisplatin Ototoxicity: Examination of the Impact of Dosing, Infusion Times, and Schedules In Pediatric Cancer Patients
Authors: Camet Miranda L. , Spence Anne , Hayashi Susan S. , Wu Ningying , Henry Jennifer , Sauerburger Kara , Hayashi Robert J. 
Published: June 2021

BackgroundSensorineural hearing loss is a well-known side effect of cisplatin (CDDP). There is limited research on the effect of dosing, infusion times, and schedules of cisplatin administration and their impact on hearing loss.MethodsA retrospective review of 993 pediatric patients’ medical and audiological charts from August 1990 to March 2015 was conducted using stringent inclusion criteria to characterize patients with hearing loss. 248 of these patients received CDDP. Of these, 216 patients had sufficient CDDP infusion data to assess for sensorineural hearing loss attributable to CDDP and its associated risk factors. Chart reviews were performed to extract clinical data including CDDP dosing information. Demographic and clinical characteristics were summarized by descriptive statistics, and univariate and multivariate logistic regressions were performed to examine the relationship between hearing loss and specific parameters of cisplatin administration (amount infused per dose, prescribed infusion time, total number of doses, number of doses per cycle, number of cycles, cumulative cisplatin exposure). Stepwise variable selection procedure was performed in the multivariate model building to extract the best subset of risk factors for the prediction of hearing loss and worsening ototoxicity grade using an established ototoxicity grading scale from the International Society of Pediatric Oncology (SIOP).ResultsA total of 153 patients with complete medical and audiologic data were evaluable for analysis. Hearing loss was identified in 72.6% of the patients. Multivariate analysis revealed that age [OR=0.90 (0.84-0.97), p-value=0.0086], radiation to any part of the body, [OR=3.20 (1.29-7.93), p-value=0.012], amount infused per dose (mg/m2) [OR=1.018 (1.002-1.033), p-value=0.029], and cumulative cisplatin exposure (mg/m 2) [OR=1.004 (1-1.008), p-value=0.027] were associated with hearing loss. Similar associations were also found between these risk factors and worsening SIOP grade.ConclusionIn one of the largest studies examining the influence of CDDP dosing and schedules on hearing loss, we found the amount of CDDP infused per dose is a significant risk factor. Considerations in designing regimens that reduce the amount of CDDP infused per dose may reduce the risk of hearing loss. Randomized prospective trials are needed.
Novel Prognostic Biomarkers in Metastatic and Locally Advanced Colorectal Cancer: Micronuclei Frequency and Telomerase Activity in Peripheral Blood Lymphocytes
Authors: Nikolouzakis Taxiarchis Konstantinos , Vakonaki Elena , Stivaktakis Polychronis D. , Alegakis Athanasios , Berdiaki Aikaterini , Razos Nikolaos , Souglakos John , Tsatsakis Aristidis , Tsiaoussis John 
Published: June 2021

PurposeDue to the current practice on colorectal cancer (CRC) management, chemoresistance is most often recognized at the end of the treatment. Therefore, effective and easy-to-use prognostic biomarkers are needed.Experimental DesignWe evaluated the prognostic significance of two novel CRC biomarkers: a) micronuclei frequency (MNf) in 55 metastatic CRC (mCRC) and 21 locally advanced rectal cancer (laRC) patients using cytokinesis block micronucleus assay (CBMN assay) and b) telomerase activity (TA) in 23 mCRC and five laRC patients using TRAP-ELISA. Both biomarkers were evaluated in peripheral blood lymphocytes (PBLs) before, at the middle, and at the end of the therapy (approximately 0, 3, and 6 months) for mCRC patients before, at the end of the therapy, and after surgery for laRC patients.ResultsOverall, MNf demonstrated significant prognostic value since a decrease of MNf less than 29% between middle and initial MNf measurements can discriminate between progressive and stable/responsive disease with sensitivity of 36% and specificity of 87.0% while being able to identify responsive disease with sensitivity of 72.7% and specificity of 59.3%. On the other hand, TA presented a significant trend of increase (p = 0.07) in patients with progressive disease at the middle measurement.ConclusionsThe findings of this study suggest that the MN frequency may serve as a promising prognostic biomarker for the monitoring of the treatment response of patients with CRC, while TA should be evaluated in a larger group of patients to further validate its significance.