bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
Authors: Tang Pingfei , Qu Weiming , Wang Taoli , Liu Minji , Wu Dajun , Tan Lin , Zhou Hongbing 
Published: December 2021

Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.Materials and Methods: Hypoxia-related differentially expressed lncRNAs (HRDELs) were identified by conducting the differential gene expression analyses in GSE155505 and The Cancer Genome Atlas (TCGA)- liver hepatocellular carcinoma (LIHC) datasets. The HRDELs landscape in patients with HCC in TCGA-LIHC was dissected by an unsupervised clustering method. Patients in the TCGA-LIHC cohort were stochastically split into the training and testing dataset. The prognostic signature was developed using LASSO (least absolute shrinkage and selection operator) penalty Cox and multivariable Cox analyses. The tumor immune microenvironment was delineated by the single-sample gene set enrichment analysis (ssGSEA) algorithm. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to evaluate the predictive value of the constructed signature in immunotherapeutic responsiveness.Results: A total of 55 HRDELs were identified through integrated bioinformatical analyses in GSE155505 and TCGA-LIHC. Patients in the TCGA-LIHC cohort were categorized into three HRDELs-specific clusters associated with different clinical outcomes. The prognostic signature involving five hypoxia-related lncRNAs (LINC00869, CAHM, RHPN1-AS1, MKLN1-AS, and DUXAP8) was constructed in the training dataset and then validated in the testing dataset and entire TCGA-LIHC cohort. The 5-years AUC of the constructed signature for prognostic prediction reaches 0.705 and is superior to that of age, AJCC stage, and histopathological grade. Patients with high-risk scores consistently had poorer overall survival outcomes than those with low-risk scores irrespective of other clinical parameters status. The low-risk group had more abundance in activated CD8+ T cell and activated B cell and were predicted to be more responsive to immunotherapy and targeted therapy than the high-risk group.Conclusion: We established a reliable hypoxia-related lncRNAs signature that could accurately predict the clinical outcomes of HCC patients and correlate with immunotherapy response and targeted drug sensitivity, providing new insights for immunotherapy and targeted therapy in HCC.
Anti-Angiogenic Agent Combined with Anti-PD-1 Immunotherapy Showed Activity in Patients With Classical Hodgkin Lymphoma Who Have Failed Immunotherapy: A Retrospective Case Report Study
Authors: Yan Zheng , Ma Jialin , Yao Shuna , Yao Zhihua , Wang Haiying , Chu Junfeng , Zhao Shuang , Liu Yanyan 
Published: December 2021

BackgroundPD-1/PD-L1 inhibitor immunotherapy has showed impressive activity in various cancers, especially relapsed/refractory (r/r) classical Hodgkin lymphoma (cHL). However, acquired resistance is inevitable for most patients. Sometimes severe side effects also lead to treatment termination. When immunotherapy failed, alternative treatment options are limited. In the past few years, we have used the anti-angiogenic agent apatinib and PD-1 inhibitor camrelizumab to treat cHL patients who failed prior immunotherapy. In this study, we analyzed the data of these patients.Patients and MethodsPatients with r/r cHL who had failed immunotherapy and subsequently received apatinib-camrelizumab (AC) combination therapy were included in this study. Patient data were collected from medical records and follow-up system. The efficacy and safety of AC therapy were analyzed.ResultsSeven patients who failed immunotherapy were identified in our database, of which five patients acquired immunotherapy resistance and two patients experienced severe side effects. They received a combination of camrelizumab (200 mg every four weeks) and apatinib (425 mg or 250 mg per day). As of the cut-off date, these patients had received a median of 4 cycles (range, 2 - 31) of treatment. Two (2/7) patients achieved complete response, four (4/7) partial response, and one (1/7) stable disease. The median progression-free survival was 10.0 months (range, 2.0 – 27.8). Low-dose apatinib (250 mg) plus camrelizumab was well tolerated and had no unexpected side effects. Besides, no reactive cutaneous capillary endothelial proliferation was observed in AC-treated patients.ConclusionsLow dose apatinib plus camrelizumab might be a promising treatment option for r/r cHL patients who have failed immunotherapy. This combination treatment is worthy of further investigation in more patients including solid cancer patients who have failed immunotherapy.
NiVCe-Layered Double Hydroxide as Multifunctional Nanomaterials for Energy and Sensor Applications
Authors: Gonçalves Josué M. , Lima Irlan S. , Azeredo Nathália F. B. , Rocha Diego P. , de Siervo Abner , Angnes Lúcio 
Published: December 2021

Multifunctional nanomaterials have been attracting increasing attention as solutions to the existing challenges in energy systems and sensing technologies. In this regard, multifunctional NiVCe-layered double hydroxide (NiVCe-LDH) nanoparticles were synthesized by the modified sol-gel method. The analysis of this material demonstrated excellent potential for its utilization as electrode materials for hybrid supercapacitor, oxygen evolution reaction (OER), and sensor applications. The NiVCe-LDH nanoparticles delivered a specific charge of 740 C g−1 at 10 A g−1 and decent rate performance (charge retention of 68.7% at 100 A g−1), showing excellent prospects as electrode material for hybrid energy storage devices. In addition, NiVCe-LDH nanoparticles have also been successfully applied as a proof-of-concept for OER, as confirmed by their low Tafel slope of 47 mV dec−1. Finally, trimetallic NiVCe-LDH-based screen-printed electrodes were developed for the sensing of hydrogen peroxide directly in a real complex mouthwash sample, achieving a satisfactory recovery value of around 98% using a fast and simple batch injection analysis procedure. These results allow us to predict the great potential of this trimetallic hydroxide for building electrochemical sensors with good perspectives as electroactive material for OER processes and energy storage technologies.
Synergistic Excitation Mechanism of CaO-SiO2-Al2O3-SO3 Quaternary Active Cementitious System
Authors: Niu Fusheng , An Yukun , Zhang Jinxia , Chen Wen , He Shengtao 
Published: December 2021

In this study, the influence of steel slag (SS) content on the strength of the cementitious materials was investigated. The quaternary active cementitious material (CaO-SiO2-Al2O3-SO3) was prepared using various proportions of steel slag (SS), granulated blast furnace slag (BFS), and desulfurized gypsum (DG). The mechanism of synergistic excitation hydration of the cementitious materials was examined using various techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared spectrometry (FTIR). The strength of the mortar test block was initially increased and decreased later with the increase of the SS content. Mortar test block with 20% steel slag, 65% granulated blast furnace slag, and 15% desulfurized gypsum with 0.35 water-binder ratio showed the highest compressive strength of 57.3 MPa on 28 days. The free calcium oxide (f-CaO) in the SS reacted with water and produced calcium hydroxide (Ca(OH)2) which created an alkaline environment. Under the alkaline environment, the alkali-activated reaction occurred with BFS. In the early stage of hydration reaction, calcium silicate hydrate (C-S-H) gel and fibrous hydration product ettringite (AFt) crystals were formed, which provided early strength to the cementitious materials. As the hydration reaction progressed, the interlocked growth of C-S-H gel and AFt crystals continued and promoted the increase of the strength of the cementitious system.
Segmentation of Cerebral Small Vessel Diseases-White Matter Hyperintensities Based on a Deep Learning System
Authors: Shan Wei , Duan Yunyun , Zheng Yu , Wu Zhenzhou , Chan Shang Wei , Wang Qun , Gao Peiyi , Liu Yaou , He Kunlun , Wang Yongjun 
Published: December 2021

Objective: Reliable quantification of white matter hyperintensities (WHMs) resulting from cerebral small vessel diseases (CSVD) is essential for understanding their clinical impact. We aim to develop and clinically validate a deep learning system for automatic segmentation of CSVD-WMH from fluid-attenuated inversion recovery (FLAIR) imaging using large multicenter data.Method: A FLAIR imaging dataset of 1,156 patients diagnosed with CSVD associated WMH (median age, 54 years; 653 males) obtained between September 2018 and September 2019 from Beijing Tiantan Hospital was retrospectively analyzed in this study. Locations of CSVD-WMH on the FLAIR scans were manually marked by two experienced neurologists. Using the manually labeled data of 996 patients (development set), a U-shaped novel 2D convolutional neural network (CNN) architecture was trained for automatic segmentation of CSVD-WMH. The segmentation performance of the network was evaluated with per pixel and lesion level dice scores using an independent internal test set (n = 160) and a multi-center external test set (n = 90, three medical centers). The clinical suitability of the segmentation results, classified as acceptable, acceptable with minor revision, acceptable with major revision, and not acceptable, was analyzed by three independent neuroradiologists. The inter-neuroradiologists agreement rate was assessed by the Kendall-W test.Results: On the internal and external test sets, the proposed CNN architecture achieved per pixel and lesion level dice scores of 0.72 (external test set), and they were significantly better than the state-of-the-art deep learning architectures proposed for WMH segmentation. In the clinical evaluation, neuroradiologists observed the segmentation results for 95% of the patients were acceptable or acceptable with a minor revision.Conclusions: A deep learning system can be used for automated, objective, and clinically meaningful segmentation of CSVD-WMH with high accuracy.
Stem Cells Therapy for COVID-19: A Systematic Review and Meta-Analysis
Authors: Arabpour Erfan , Khoshdel Sina , Tabatabaie Negin , Akhgarzad Ali , Zangiabadian Moein , Nasiri Mohammad Javad 
Published: December 2021

Introduction: Vaccination seems to be a good solution for preventing and controlling coronavirus disease (COVID-19) pandemic, but still there are some challenges in COVID-19 vaccination. Investigating new therapeutic options for COVID-19 is necessary. The current study aimed to evaluate the safety and efficacy of stem cells in treating patients with COVID-19.Methods: We reviewed the relevant scientific literature published up to April 1, 2021. The pooled risk ratio (RR) with 95% CI was assessed using a fixed or random-effect model. We considered P &lt; 0.05 as statistically significant for publication bias. Data were analyzed by Comprehensive Meta-Analysis software, Version 2.0 (Biostat, Englewood, NJ).Results: After reviewing 1,262 records, we identified 10 studies that met the inclusion criteria. The analysis showed that stem cell therapy could significantly reduce the mortality rate (RR 0.471, 95% CI: 0.270–0.821) and morbidity (RR 0.788, 95% CI: 0.626–0.992) in patients with COVID-19; compared with the control group.Conclusions: The present study suggests that stem cell therapy has a remarkable effect on reducing mortality and morbidity of patients with COVID-19. Further large-scale studies are needed to approve these results. Defining a protocol for stem cell therapy in patients with COVID-19 can lead to achieving the best clinical outcomes.
Screening Referable Diabetic Retinopathy Using a Semi-automated Deep Learning Algorithm Assisted Approach
Authors: Wang Yueye , Shi Danli , Tan Zachary , Niu Yong , Jiang Yu , Xiong Ruilin , Peng Guankai , He Mingguang 
Published: December 2021

Purpose: To assess the accuracy and efficacy of a semi-automated deep learning algorithm (DLA) assisted approach to detect vision-threatening diabetic retinopathy (DR).Methods: We developed a two-step semi-automated DLA-assisted approach to grade fundus photographs for vision-threatening referable DR. Study images were obtained from the Lingtou Cohort Study, and captured at participant enrollment in 2009–2010 (“baseline images”) and annual follow-up between 2011 and 2017. To begin, a validated DLA automatically graded baseline images for referable DR and classified them as positive, negative, or ungradable. Following, each positive image, all other available images from patients who had a positive image, and a 5% random sample of all negative images were selected and regraded by trained human graders. A reference standard diagnosis was assigned once all graders achieved consistent grading outcomes or with a senior ophthalmologist's final diagnosis. The semi-automated DLA assisted approach combined initial DLA screening and subsequent human grading for images identified as high-risk. This approach was further validated within the follow-up image datasets and its time and economic costs evaluated against fully human grading.Results: For evaluation of baseline images, a total of 33,115 images were included and automatically graded by the DLA. 2,604 images (480 positive results, 624 available other images from participants with a positive result, and 1500 random negative samples) were selected and regraded by graders. The DLA achieved an area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy of 0.953, 0.970, 0.879, and 88.6%, respectively. In further validation within the follow-up image datasets, a total of 88,363 images were graded using this semi-automated approach and human grading was performed on 8975 selected images. The DLA achieved an AUC, sensitivity, and specificity of 0.914, 0.852, 0.853, respectively. Compared against fully human grading, the semi-automated DLA-assisted approach achieved an estimated 75.6% time and 90.1% economic cost saving.Conclusions: The DLA described in this study was able to achieve high accuracy, sensitivity, and specificity in grading fundus images for referable DR. Validated against long-term follow-up datasets, a semi-automated DLA-assisted approach was able to accurately identify suspect cases, and minimize misdiagnosis whilst balancing safety, time, and economic cost.
IL 33 Correlates With COVID-19 Severity, Radiographic and Clinical Finding
Authors: Markovic Sofija Sekulic , Jovanovic Marina , Gajovic Nevena , Jurisevic Milena , Arsenijevic Nebojsa , Jovanovic Marina , Jovanovic Milan , Mijailovic Zeljko , Lukic Snezana , Zornic Nenad , Vukicevic Vladimir , Stojanovic Jasmina , Maric Veljko , Jocic Miodrag , Jovanovic Ivan 
Published: December 2021

Objective: The increased level of interleukin (IL)-33 is considered as a predictor of severe coronavirus disease 2019 (COVID-19) infection, but its role at different stages of the disease is still unclear. Our goal was to analyze the correlation of IL-33 and other innate immunity cytokines with disease severity.Methods: In this study, 220 patients with COVID-19 were included and divided into two groups, mild/moderate and severe/critical. The value of the cytokines, clinical, biochemical, radiographic data was collected and their correlation with disease severity was analyzed.Results: Most patients in the severe/critical group were male (81.8%) and older (over 64.5 years). We found a statistically significant difference (p &lt; 0.05) in these two groups between clinical features (dyspnea, dry cough, fatigue, and auscultatory findings); laboratory [(neutrophil count, lymphocyte count, monocyte count, hemoglobin, plasma glucose, urea, creatinine, total bilirubin (TBIL), direct bilirubin (DBIL), aspartate aminotransferase (AST), albumin (ALB), lactate dehydrogenase (LDH), creatinine kinase (CK), D-dimer, C-reactive protein (CRP), procalcitonin (PCT), Fe, and Ferritin)], arterial blood gases (oxygen saturation-Sa02, partial pressure of oxygen -p02), and chest X-rays (CXR) lung findings (p = 0.000). We found a significantly higher serum concentration (p &lt; 0.05) of TNF-α, IL-1β, IL-6, IL-12, IL-23, and IL-33 in patients with COVID-19 with severe disease. In the milder stage of COVID-19, a positive correlation was detected between IL-33 and IL-1β, IL-12 and IL-23, while a stronger positive correlation between the serum values of IL-33 and TNF-α, IL-1β, IL-6, and IL-12 and IL-23 was detected in patients with COVID-19 with severe disease. A weak negative correlation (p &lt; 0.05) between pO2 and serum IL-1β, IL-12, and IL-33 and between SaO2 and serum IL-33 was noted. The positive relation (p &lt; 0.05) between the serum values of IL-33 and IL-12, IL-33 and IL-6, and IL-6 and IL-12 is proven.Conclusion: In a more progressive stage of COVID-19, increased IL-33 facilitates lung inflammation by inducing the production of various innate proinflammatory cytokines (IL-1β, IL-6, TNF-α, IL-12, and IL-23) in several target cells leading to the most severe forms of the disease. IL-33 correlates with clinical parameters of COVID-19 and might represent a promising marker as well as a therapeutic target in COVID-19.
17-Alpha-Hydroxyprogesterone vs. Placebo for Preventing of Recurrent Preterm Birth: A Systematic Review and Meta-Analysis of Randomized Trials
Authors: Almutairi Abdulaali R. , Aljohani Hadir I. , Al-fadel Nouf S. 
Published: December 2021

Background: Preterm birth (PTB) is a leading cause of neonatal morbidity and mortality.Objective: To estimate the effect of 17-alpha-hydroxyprogesterone caproate (17-OHPC) compared to placebo in singleton gestations for reducing the risk of recurrent PTB and neonatal morbidity and mortality.Work Design: Systematic review and meta-analysis.Search Strategy: Searching MEDLINE, Embase, Web of Science, SCOPUS, Cochrane Library, and clinical trial registries.Selection Criteria: Randomized controlled trials of singleton gestations with a history of PTB and treated with a weekly intramuscular injection of 17-OHPC or placebo.Data Collection and Analysis: A random meta-analysis model was performed for the PTB outcomes (&lt;32, &lt;35, and &lt;37 weeks) and neonatal outcomes (neonatal death, grade 3 or 4 intraventricular hemorrhage, respiratory distress syndrome, bronchopulmonary dysplasia, necrotizing enterocolitis, and sepsis). Effect estimates were measured by relative risk ratio (RR) with a 95% confidence interval (CI).Main Results: Six works were included. There were no statistically significant reductions in the PTB risk following the use of 17-OHPC at &lt;32 weeks (RR = 0.61, 95% CI: 0.13–2.77, and I2 = 39%), &lt;35weeks (RR = 0.60, 95% CI: 0.10–3.67, and I2 = 51%), and &lt;37 weeks (RR = 0.68, 95% CI: 0.46–1, and I2 = 75%). Furthermore, all the neonatal outcomes were statistically similar between the two groups.Conclusion: Treatment with 17-OHPC is not associated with reducing the risk of PTB or neonatal outcomes compared to placebo.
Meibomian Gland Morphology Changes After Cataract Surgery: A Contra-Lateral Eye Study
Authors: Chang Pingjun , Qian Shuyi , Xu Zhizi , Huang Feng , Zhao Yinying , Li Zhangliang , Zhao Yun-e 
Published: December 2021

Purpose: To evaluate the morphology changes of meibomian glands (MGs) after cataract surgery.Setting: Hangzhou Branch of the Eye Hospital of Wenzhou Medical University, Zhejiang, China.Methods: In this contra-lateral eye study, 40 patients received unilateral cataract surgery for age-related cataract. All the patients underwent the evaluation of non-invasive break-up time (NIBUT) and lower tear meniscus height (TMH) before the surgery and 6 months post-operatively. The MGs were evaluated via ImageJ and Meibomian Gland Bio-image Analyzer. MG dropout, length, width, area, gland diameter deformation index (DI), and gland signal index (SI) were recorded.Results: MG length, width, area, DI, and SI were significantly decreased after cataract surgery in the study group (operated eyes, P &lt; 0.001, P = 0.003, P &lt; 0.001, P = 0.001, and P &lt; 0.001, respectively) and showed no significant changes in the control group (non-operated eyes) (all P &gt; 0.05). MG loss increased more in the study group (P = 0.030), and the changes in TMH and NIBUT were not significantly different between the two eyes (both P &gt; 0.05).Conclusion: Cataract surgery aggravated meibomian gland morphology, such as MG loss, MG length, width, area, and SI, and produced no change in NIBUT and TMH at 6 months post-operatively.
Unveiling the Burden of Interactions Among Clinical Risk Factors for 1-Year Mortality in Hospitalized Older Patients
Authors: Lattanzio Fabrizia , Corigliano Valentina , Soraci Luca , Fumagalli Alessia , Onder Graziano , Volpato Stefano , Cherubini Antonio , Ruggiero Carmelinda , Cozza Annalisa , Guarasci Francesco , Corsonello Andrea 
Published: December 2021

Background: Hospitalized older patients are particularly exposed to adverse health outcomes.Objective: In this study, we aimed at investigating the prognostic interactions between disability in basic activities of daily living (BADL), cognitive impairment, low handgrip strength, anticholinergic cognitive burden (ACB), and depression on 1-year mortality.Setting and Subjects: Our series consisted of 503 older patients discharged from acute care hospitals.Methods: Disability in at least one BADL, ACB, depression, cognitive impairment, and low handgrip strength was considered in the analysis. One-year mortality was investigated by Cox regression analysis and prognostic interactions among study variables were assessed by survival tree analysis.Results: Basic activities of daily living disability, ACB, cognitive impairment, and low handgrip strength were significantly associated with 1-year mortality. Survival tree analysis showed that patients with BADL disability and high ACB carried the highest risk of poor survival [hazard ratio (HR): 16.48 (2.63–74.72)], followed by patients with BADL disability and low ACB (HR: 8.43, 95% CI: 1.85–38.87). Patients with cognitive impairment and no BADL disability were characterized by a lower but still significant risk of mortality (HR: 6.61, 95% CI: 1.51–28.97) and those with high ACB scores and good cognitive and functional performance (HR: 5.28, 95% CI: 1.13–24.55).Conclusion: Basic activities of daily living dependency, cognitive impairment, and ACB score were the three main predictors of 1-year mortality among patients discharged from acute care hospitals; the interaction between BADL dependency and ACB score wasfound to significantly affect survival. Early identification of such high-risk patients may help tailor targeted interventions to counteract their detrimental effects on prognosis.