bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy
Authors: Lam Sai-Kit , Zhang Yuanpeng , Zhang Jiang , Li Bing , Sun Jia-Chen , Liu Carol Yee-Tung , Chou Pak-Hei , Teng Xinzhi , Ma Zong-Rui , Ni Rui-Yan , Zhou Ta , Peng Tao , Xiao Hao-Nan , Li Tian , Ren Ge , Cheung Andy Lai-Yin , Lee Francis Kar-Ho , Yip Celia Wai-Yi , Au Kwok-Hung , Lee Victor Ho-Fun , Chang Amy Tien-Yee , Chan Lawrence Wing-Chi , Cai Jing 
Published: January 2022

PurposeTo investigate the role of different multi-organ omics-based prediction models for pre-treatment prediction of Adaptive Radiotherapy (ART) eligibility in patients with nasopharyngeal carcinoma (NPC).Methods and MaterialsPre-treatment contrast-enhanced computed tomographic and magnetic resonance images, radiotherapy dose and contour data of 135 NPC patients treated at Hong Kong Queen Elizabeth Hospital were retrospectively analyzed for extraction of multi-omics features, namely Radiomics (R), Morphology (M), Dosiomics (D), and Contouromics (C), from a total of eight organ structures. During model development, patient cohort was divided into a training set and a hold-out test set in a ratio of 7 to 3 via 20 iterations. Four single-omics models (R, M, D, C) and four multi-omics models (RD, RC, RM, RMDC) were developed on the training data using Ridge and Multi-Kernel Learning (MKL) algorithm, respectively, under 10-fold cross validation, and evaluated on hold-out test data using average area under the receiver-operator-characteristics curve (AUC). The best-performing single-omics model was first determined by comparing the AUC distribution across the 20 iterations among the four single-omics models using two-sided student t-test, which was then retrained using MKL algorithm for a fair comparison with the four multi-omics models.ResultsThe R model significantly outperformed all other three single-omics models (all p-value&lt;0.0001), achieving an average AUC of 0.942 (95%CI: 0.938-0.946) and 0.918 (95%CI: 0.903-0.933) in training and hold-out test set, respectively. When trained with MKL, the R model (R_MKL) yielded an increased AUC of 0.984 (95%CI: 0.981-0.988) and 0.927 (95%CI: 0.905-0.948) in training and hold-out test set respectively, while demonstrating no significant difference as compared to all studied multi-omics models in the hold-out test sets. Intriguingly, Radiomic features accounted for the majority of the final selected features, ranging from 64% to 94%, in all the studied multi-omics models.ConclusionsAmong all the studied models, the Radiomic model was found to play a dominant role for ART eligibility in NPC patients, and Radiomic features accounted for the largest proportion of features in all the multi-omics models.
Is Laryngeal Squamous Cell Carcinoma Related to Helicobacter pylori?
Authors: Huang Yan , Gu Min , Wu Qi , Zhu Juanfen , Wu Jian , Wang Peipei , Wang Meihua , Luo Judong 
Published: January 2022

BackgroundLaryngeal carcinoma is a primary malignant tumor originating from the laryngeal mucosa. In recent years, an increasing number of studies have confirmed that Helicobacter pylori may play a role in the occurrence and development of laryngeal cancer. We conducted a systematic review and meta-analysis to identify and emphasize the relationship between laryngeal cancer and Helicobacter pylori infection.MethodsWe actively searched for systematic reviews of PubMed, Embase, Web of Science, and Cochrane libraries to select studies that met the recommended guidelines. A total of 1756 patients with laryngeal cancer were included in this study to assess the association of Helicobacter pylori in the larynx with laryngeal cancer. A subassessment of the risk of bias for each study that met the inclusion criteria was carried out. To illustrate the reasons for heterogeneity, we performed a subgroup analysis to determine the type of study, the quality of the article, the diagnostic method, and the impact of exposure factors.ResultsThe meta-analysis included a total of 17 case-control studies on the association between Helicobacter pylori in the larynx and laryngeal cancer. Our meta-analysis showed that Helicobacter pylori infection in the larynx significantly increased the risk of malignant tumors in the larynx (odds ratio, 2.96; 95% CI, 1.83-4.78; P&lt;0.00001; I2 = 86%). They still existed when we controlled for patients’ exposure to smoking factors (odds ratio, 3.86; 95% CI, 1.89–7.88).ConclusionThis systematic review and meta-analysis showed an association between Helicobacter pylori and laryngeal cancer. These findings are consistent with the understanding that chronic inflammatory tissue insult may lead to the development of malignancy. Controlling risk factors will help us identify patients with an increased risk of laryngeal cancer.
Pan-Cancer Analysis Reveals Genomic and Clinical Characteristics of TRPV Channel-Related Genes
Authors: Wang Xiaoxuan , Li Guanghao , Zhang Yidan , Li Lanfang , Qiu Lihua , Qian Zhengzi , Zhou Shiyong , Wang Xianhuo , Li Qiang , Zhang Huilai 
Published: January 2022

BackgroundTransient Receptor Potential channels (TRPs), a class of ion channels, were first described two decades ago. Many TRP family members are major participants in nociception and integration of heat and pain signals. Recent studies have revealed that subfamilies of this channel, such as members of transient receptor potential vanilloid (TRPV) channels, play important roles in breast, ovarian, prostate, and pancreatic cancers.MethodsWe performed a comprehensive analysis of TRPVs in 9125 tumor samples of 33 cancer types using multi-omics data extracted from The Cancer Genome Atlas (TCGA). We identified differences in mRNA expression in a pan-cancer analysis, and the genomic characteristics of single nucleotide variations, copy number variations, methylation features, and miRNA–mRNA interactions using data from TCGA. Finally, we evaluated the sensitivity and resistance to drugs targeting TRPV channel-related genes using the Cancer Therapeutics Response Portal (CTRP) and the Genomics of Drug Sensitivity in Cancer (GDSC) database. Finally, we validated the drug sensitive data and the importance of TRPV6 in two cancer cell lines using q-PCR assay, CCK8 assay, EdU assay and scratch assay.ResultsExtensive genetic alterations in TRPV channel-related genes and differences in gene expression were associated with the activity of cancer marker-related pathways. TRPV channel-related genes can be used as prognostic biomarkers. Several potential drugs, such as lapatinib, that may target TRPV channel-related genes were identified by mining the genomics of drug sensitivity.ConclusionThis study revealed the genomic changes and clinical characteristics of TRPV channel-related regulatory factors in 33 types of tumors. This analysis may help uncover the TRPV channel-related genes associated with tumorigenesis. We also proposed novel strategies for tumor treatment.
Metabolism-Associated Gene Signatures for FDG Avidity on PET/CT and Prognostic Validation in Hepatocellular Carcinoma
Authors: Lee Hyunjong , Choi Joon Young , Joung Je-Gun , Joh Jae-Won , Kim Jong Man , Hyun Seung Hyup 
Published: January 2022

IntroductionThe prognostic value of F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) in hepatocellular carcinoma (HCC) was established in previous reports. However, there is no evidence suggesting the prognostic value of transcriptomes associated with tumor FDG uptake in HCC. It was aimed to elucidate metabolic genes and functions associated with FDG uptake, followed by assessment of those prognostic value.MethodsSixty HCC patients with Edmondson–Steiner grade II were included. FDG PET/CT scans were performed before any treatment. RNA sequencing data were obtained from tumor and normal liver tissue. Associations between each metabolism-associated gene and tumor FDG uptake were investigated by Pearson correlation analyses. A novel score between glucose and lipid metabolism-associated gene expression was calculated. In The Cancer Genome Atlas Liver Hepatocellular Carcinoma dataset, the prognostic power of selected metabolism-associated genes and a novel score was evaluated for external validation.ResultsNine genes related to glycolysis and the HIF-1 signaling pathway showed positive correlations with tumor FDG uptake; 21 genes related to fatty acid metabolism and the PPAR signaling pathway demonstrated negative correlations. Seven potential biomarker genes, PFKFB4, ALDOA, EGLN3, EHHADH, GAPDH, HMGCS2, and ENO2 were identified. A metabolic gene expression balance score according to the dominance between glucose and lipid metabolism demonstrated good prognostic value in HCC.ConclusionsThe transcriptomic evidence of this study strongly supports the prognostic power of FDG PET/CT and indicates the potential usefulness of FDG PET/CT imaging biomarkers to select appropriate patients for metabolism-targeted therapy in HCC.
Global PARITY: Study Design for a Multi-Centered, International Point Prevalence Study to Estimate the Burden of Pediatric Acute Critical Illness in Resource-Limited Settings
Authors: Abbas Qalab , Holloway Adrian , Caporal Paula , López-Barón Eliana , Agulnik Asya , Remy Kenneth E. , Appiah John A. , Attebery Jonah , Fink Ericka L. , Lee Jan Hau , Hooli Shubhada , Kissoon Niranjan , Miller Erika , Murthy Srinivas , Muttalib Fiona , Nielsen Katie , Puerto-Torres Maria , Rodrigues Karla , Sakaan Firas , Rodrigues Adriana Teixeira , Tabor Erica A. , von Saint Andre-von Arnim Amelie , Wiens Matthew O. , Blackwelder William , He David , Kortz Teresa B. , Bhutta Adnan T. 
Published: January 2022

BackgroundThe burden of pediatric critical illness and resource utilization by children with critical illness in resource limited settings (RLS) are largely unknown. Without specific data that captures key aspects of critical illness, disease presentation, and resource utilization for pediatric populations in RLS, development of a contextual framework for appropriate, evidence-based interventions to guide allocation of limited but available resources is challenging. We present this methods paper which describes our efforts to determine the prevalence, etiology, hospital outcomes, and resource utilization associated with pediatric acute, critical illness in RLS globally.MethodsWe will conduct a prospective, observational, multicenter, multinational point prevalence study in sixty-one participating RLS hospitals from North, Central and South America, Africa, Middle East and South Asia with four sampling time points over a 12-month period. Children aged 29 days to 14 years evaluated for acute illness or injury in an emergency department) or directly admitted to an inpatient unit will be enrolled and followed for hospital outcomes and resource utilization for the first seven days of hospitalization. The primary outcome will be prevalence of acute critical illness, which Global PARITY has defined as death within 48 hours of presentation to the hospital, including ED mortality; or admission/transfer to an HDU or ICU; or transfer to another institution for a higher level-of-care; or receiving critical care-level interventions (vasopressor infusion, invasive mechanical ventilation, non-invasive mechanical ventilation) regardless of location in the hospital, among children presenting to the hospital. Secondary outcomes include etiology of critical illness, in-hospital mortality, cause of death, resource utilization, length of hospital stay, and change in neurocognitive status. Data will be managed via REDCap, aggregated, and analyzed across sites.DiscussionThis study is expected to address the current gap in understanding of the burden, etiology, resource utilization and outcomes associated with pediatric acute and critical illness in RLS. These data are crucial to inform future research and clinical management decisions and to improve global pediatric hospital outcomes.
Deep Learning-Based Analytic Models Based on Flow-Volume Curves for Identifying Ventilatory Patterns
Authors: Wang Yimin , Li Qiasheng , Chen Wenya , Jian Wenhua , Liang Jianling , Gao Yi , Zhong Nanshan , Zheng Jinping 
Published: January 2022

IntroductionSpirometry, a pulmonary function test, is being increasingly applied across healthcare tiers, particularly in primary care settings. According to the guidelines set by the American Thoracic Society (ATS) and the European Respiratory Society (ERS), identifying normal, obstructive, restrictive, and mixed ventilatory patterns requires spirometry and lung volume assessments. The aim of the present study was to explore the accuracy of deep learning-based analytic models based on flow–volume curves in identifying the ventilatory patterns. Further, the performance of the best model was compared with that of physicians working in lung function laboratories.MethodsThe gold standard for identifying ventilatory patterns was the rules of ATS/ERS guidelines. One physician chosen from each hospital evaluated the ventilatory patterns according to the international guidelines. Ten deep learning models (ResNet18, ResNet34, ResNet18_vd, ResNet34_vd, ResNet50_vd, ResNet50_vc, SE_ResNet18_vd, VGG11, VGG13, and VGG16) were developed to identify patterns from the flow–volume curves. The patterns obtained by the best-performing model were cross-checked with those obtained by the physicians.ResultsA total of 18,909 subjects were used to develop the models. The ratio of the training, validation, and test sets of the models was 7:2:1. On the test set, the best-performing model VGG13 exhibited an accuracy of 95.6%. Ninety physicians independently interpreted 100 other cases. The average accuracy achieved by the physicians was 76.9 ± 18.4% (interquartile range: 70.5–88.5%) with a moderate agreement (κ = 0.46), physicians from primary care settings achieved a lower accuracy (56.2%), while the VGG13 model accurately identified the ventilatory pattern in 92.0% of the 100 cases (P &lt; 0.0001).ConclusionsThe VGG13 model identified ventilatory patterns with a high accuracy using the flow–volume curves without requiring any other parameter. The model can assist physicians, particularly those in primary care settings, in minimizing errors and variations in ventilatory patterns.
Professional Quality of Life Among Physicians and Nurses Working in Portuguese Hospitals During the Third Wave of the COVID-19 Pandemic
Authors: Serrão Carla , Martins Vera , Ribeiro Carla , Maia Paulo , Pinho Rita , Teixeira Andreia , Castro Luísa , Duarte Ivone 
Published: January 2022

BackgroundIn the last 2 weeks of January 2021, Portugal was the worst country in the world in incidence of infections and deaths due to COVID-19. As a result, the pressure on the healthcare system increased exponentially, exceeding its capacities and leaving hospitals in near collapse. This scenario caused multiple constraints, particularly for hospital medical staff. Previous studies conducted at different moments during the pandemic reported that COVID-19 has had significant negative impacts on healthcare workers’ psychological health, including stress, anxiety, depression, burnout, post-traumatic stress symptoms, and sleep disturbances. However, there are many uncertainties regarding the professional quality of life of hospital nurses and physicians. To address gaps in previous research on secondary traumatic stress, we focused on healthcare workers working in hospitals affected by a major traumatic event: the third wave of COVID-19.ObjectivesThe aim of the present study was to identify the contribution of personal and work-related contextual variables (gender, age, parental status, occupation, years of experience, working with patients affected by COVID-19) on professional quality of life of healthcare workers.MethodsCross-sectional study with a web-based questionnaire given to physicians and nurses working in a hospital setting. A total of 853 healthcare professionals (276 physicians and 586 nurses; median age 37 years old) participated in the survey assessing professional quality of life compassion satisfaction, secondary traumatic stress, and burnout. Factors of professional quality of life were assessed using regression analysis.ResultsMost of the participants showed moderate (80%; n = 684) or high (18%; n = 155) levels of compassion satisfaction, whereas the majority of them experienced moderate levels of burnout (72%; n = 613) and secondary traumatic stress (69%; n = 592). The analyzed variables demonstrated no differences between professionals who were directly or not involved in the care of COVID-19 patients. Parental status was found to be a significant factor in compassion satisfaction. Female gender was significantly associated with more susceptibility to secondary traumatization. Factors that may potentially contribute to burnout include years of professional experience and the number of work hours per week.ConclusionThe COVID-19 pandemic has created a new challenge for the healthcare system. Burnout and secondary traumatic stress can lead to medical errors and impact standards of patient care, particularly compromising compassionate care. It is therefore recommended that hospitals develop psychoeducational initiatives to support professionals in dealing with barriers to compassion.
European Validation of the Self-Evaluation of Negative Symptoms (SNS): A Large Multinational and Multicenter Study
Authors: Dollfus Sonia , Mucci Armida , Giordano Giulia M. , Bitter István , Austin Stephen F. , Delouche Camille , Erfurth Andreas , Fleischhacker W. Wolfgang , Movina Larisa , Glenthøj Birte , Gütter Karoline , Hofer Alex , Hubenak Jan , Kaiser Stefan , Libiger Jan , Melle Ingrid , Nielsen Mette Ø. , Papsuev Oleg , Rybakowski Janusz K. , Sachs Gabriele , Üçok Alp , Brando Francesco , Wojciak Pawel , Galderisi Silvana 
Published: January 2022

BackgroundNegative symptoms are usually evaluated with scales based on observer ratings and up to now self-assessments have been overlooked. The aim of this paper was to validate the Self-evaluation of Negative Symptoms (SNS) in a large European sample coming from 12 countries. We wanted to demonstrate: (1) good convergent and divergent validities; (2) relationships between SNS scores and patients' functional outcome; (3) the capacity of the SNS compared to the Brief Negative Symptom Scale (BNSS) to detect negative symptoms; and (4) a five-domain construct in relation to the 5 consensus domains (social withdrawal, anhedonia, alogia, avolition, blunted affect) as the best latent structure of SNS.MethodsTwo hundred forty-five subjects with a DSM-IV diagnosis of schizophrenia completed the SNS, the Positive and Negative Syndrome Scale (PANSS), the BNSS, the Calgary Depression Scale for Schizophrenia (CDSS), and the Personal and Social Performance (PSP) scale. Spearman's Rho correlations, confirmatory factor analysis investigating 4 models of the latent structure of SNS and stepwise multiple regression were performed.ResultsSignificant positive correlations were observed between the total score of the SNS and the total scores of the PANSS negative subscale (r = 0.37; P &lt; 0.0001) and the BNSS (r = 0.43; p &lt; 0.0001). SNS scores did not correlate with the level of insight, parkinsonism, or the total score of the PANSS positive subscale. A positive correlation was found between SNS and CDSS (r = 0.35; p &lt; 0.0001). Among the 5 SNS subscores, only avolition subscores entered the regression equation explaining a lower functional outcome. The 1-factor and 2-factor models provided poor fit, while the 5-factor model and the hierarchical model provided the best fit, with a small advantage of the 5-factor model. The frequency of each negative dimension was systematically higher using the BNSS and the SNS vs. the PANSS and was higher for alogia and avolition using SNS vs. BNSS.ConclusionIn a large European multicentric sample, this study demonstrated that the SNS has: (1) good psychometric properties with good convergent and divergent validities; (2) a five-factor latent structure; (3) an association with patients' functional outcome; and (4) the capacity to identify subjects with negative symptoms that is close to the BNSS and superior to the PANSS negative subscale.
Rehabilitation and Return-to-Work of Patients Acquiring COVID-19 in the Workplace: A Study Protocol for an Observational Cohort Study
Authors: Müller Katrin , Zwingmann Katharina , Auerswald Tina , Berger Ivo , Thomas Andreas , Schultz Anna-Lena , Wilhelm Eva , Weber Rainer-Christian , Kolb Franziska , Wastlhuber Alois , Meder Sylvia , Stegbauer Michael 
Published: January 2022

BackgroundIn 2020, the novel coronavirus disease (COVID-19) developed into a worldwide pandemic. The course of COVID-19 is diverse, non-specific, and variable: Affected persons suffer from physical, cognitive, and psychological acute and long-term consequences. The symptoms influence everyday life activities, as well as work ability in the short or long-term. Healthcare professionals are considered particularly vulnerable to COVID-19 compared to the general population. In Germany, COVID-19 is recognized as an occupational disease or a work-related accident under certain conditions. Disease-specific rehabilitation is recommended for patients following acute COVID-19 to recover physical and neuropsychological performance and to improve work ability. Currently, there are limited findings on the short-term or long-term impact of COVID-19 as a recognized occupational disease or work-related accident, as well as on rehabilitation programs and associated influencing factors. Thus, the present research project will investigate these questions.MethodsFor this observational cohort study, post-acute patients with COVID-19 as a recognized occupational disease or work-related accident according to the insurance regulations for COVID-19 will be recruited at the BG Hospital for Occupational Disease in Bad Reichenhall, Germany. All participants will complete a comprehensive multimodal and interdisciplinary inpatient rehabilitation program for a duration of at least 3 weeks, beginning after their acute COVID-19 infection and depending on their individual indication and severity of disease. Participants will complete medical, functional, motor, psychological, and cognitive measurements at four time points (at the beginning (T1) and end (T2) of inpatient rehabilitation; 6 (T3) and 12 (T4) months after the beginning of inpatient rehabilitation).DiscussionThe present research project will help to assess and describe long-term effects of COVID-19 as a recognized occupational disease or work-related accident on physical and neuropsychological health, as well as on everyday activities and work ability of affected insured persons. In addition, this study will investigate influencing factors on severity and course of COVID-19. Furthermore, we will examine rehabilitation needs, measures, occurring specifics, and the feasibility of the rehabilitation procedure and disease development in the patients. The results of the intended study will further advance common recommendations for targeted and tailored rehabilitation management and participation in inpatient rehabilitation.Clinical Trial Registrationwww.drks.de, identifier: DRKS00022928.