bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Risk Score Based on Eight Hepatocellular Carcinoma- Immune Gene Expression Can Predict the Prognosis of the Patients
Authors: Ye Dingde , Liu Yaping , Li Guoqiang , Sun Beicheng , Peng Jin , Xu Qingxiang 
Published: November 2021

BackgroundHepatocellular carcinoma (HCC) is one of the malignant tumors with high morbidity and mortality worldwide. Immunotherapy has emerged as an increasingly important cancer treatment modality. However, the potential relationship between immune genes and HCC still needs to be explored. The purpose of this study is to construct a new prognostic risk signature to predict the prognosis of HCC patients based on the expression of immune-related genes (IRGs) and explore its potential mechanism.MethodsWe analyzed the gene expression data of 332 HCC patient samples and 46 adjacent normal tissues samples (Solid Tissue Normal including cirrhotic tissue) in The Cancer Genome Atlas (TCGA) database and clinical characteristics. We analyzed the gene expression data, identified differentially expressed IRGs in HCC tissues, filtered IRGs with prognostic value to construct an IRG signature, and classified patients into high and low gene expression groups based on the expression of IRGs in their tumor tissues. We also investigated the potential molecular mechanisms of IRGs through a bioinformatics approach using Protein-Protein Interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis and Gene Ontology (GO) database analysis. Differentially expressed IRGs associated with significant clinical outcomes (SIRGs) were identified by univariate Cox regression analysis. An immune-related risk score model (IRRSM) was established based on Lasso Cox regression analysis and multivariate Cox regression analysis. Based on the IRRSM, the immune score of the patients was calculated, and the patients were divided into high-risk and low-risk patients according to the median score, and the differences in survival between the two groups were compared. Then, the correlation analysis between the IRRSM and clinical characteristics was performed, and the IRRSM was validated using the International Cancer Genome Consortium (ICGC) database.ResultsThe IRRSM was eventually constructed and confirmed to be an independent prognostic model for HCC patients. The IRRSM was shown to be positively correlated with the infiltration of four types of immune cells.ConclusionOur results showed that some SIRGs have potential value for predicting the prognosis and clinical outcomes of HCC patients. IRGs affect the prognosis of HCC patients by regulating the tumor immune microenvironment (TIME). This study provides a new insight for immune research and treatment strategies in HCC patients.
Radiomics Analysis of Contrast-Enhanced CT for the Preoperative Prediction of Microvascular Invasion in Mass-Forming Intrahepatic Cholangiocarcinoma
Authors: Xiang Fei , Wei Shumei , Liu Xingyu , Liang Xiaoyuan , Yang Lili , Yan Sheng 
Published: November 2021

BackgroundMicrovascular invasion (MVI) has been shown to be closely associated with postoperative recurrence and metastasis in patients with intrahepatic cholangiocarcinoma (ICC). We aimed to develop a radiomics prediction model based on contrast-enhanced CT (CECT) to distinguish MVI in patients with mass-forming ICC.Methods157 patients were included and randomly divided into training (n=110) and test (n=47) datasets. Radiomic signatures were built based on the recursive feature elimination support vector machine (Rfe-SVM) algorithm. Significant clinical-radiologic factors were screened, and a clinical model was built by multivariate logistic regression. A nomogram was developed by integrating radiomics signature and the significant clinical risk factors.ResultsThe portal phase image radiomics signature with 6 features was constructed and provided an area under the receiver operating characteristic curve (AUC) of 0.804 in the training and 0.769 in the test datasets. Three significant predictors, including satellite nodules (odds ratio [OR]=13.73), arterial hypo-enhancement (OR=4.31), and tumor contour (OR=4.99), were identified by multivariate analysis. The clinical model using these predictors exhibited an AUC of 0.822 in the training and 0.756 in the test datasets. The nomogram combining significant clinical factors and radiomics signature achieved satisfactory prediction efficacy, showing an AUC of 0.886 in the training and 0.80 in the test datasets.ConclusionsBoth CECT radiomics analysis and radiologic factors have the potential for MVI prediction in mass-forming ICC patients. The nomogram can further improve the prediction efficacy.
Quantification of Differential Metabolites in Dried Blood Spots Using Second-Tier Testing for SCADD/IBDD Disorders Based on Large-Scale Newborn Screening in a Chinese Population
Authors: Zhou Wei , Cai Heng , Li Huizhong , Ji Zhe , Gu Maosheng 
Published: November 2021

Background: Although newborn screening (NBS) for metabolic defects using the marker butyl carnitine (C4) combined with the C4-to-acetylcarnitine ratio is adequate, the incorporation of novel parameters may improve differential testing for these disorders without compromising sensitivity.Methods: Analytical and clinical performance was evaluated by MS/MS using 237 initially positive neonatal samples between March 2019 and March 2020 at the Newborn Screening Center of Xuzhou Maternity and Child Health Care Hospital. Additionally, second-tier testing by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with the quantification of ethylmalonate (EMA) or isobutyryl-glycine (IBG) in dried blood spots (DBSs) was performed to reduce the false-positive rate.Results: We reviewed initial MS/MS data for DBSs from 469,730 neonates, and a second-tier test was performed using 237 samples that exceeded the C4 concentration cutoff value. Eleven variants of the ACADS gene were identified, with c.1031A&gt;G (p.E344G) being the most common. Fifteen ACAD8 mutations were identified in seven patients, and Swiss modeling and amino acid conservation analyses were conducted for the novel variants. Based on a retrospective analysis of EMA and IBG, the application of second-tier tests before the release of neonatal screening results reduced referrals by over 91.89% and improved the positive predictive value (PPV) for short-chain acyl-CoA dehydrogenase deficiency/isobutyryl-CoA dehydrogenase deficiency (SCADD/IBDD) screening.Conclusion: A screening algorithm including EMA/IBG improves target differential testing for NBS and may eliminate unnecessary referrals while maintaining 100% sensitivity. Second-tier screening using UPLC-MS/MS as a rapid and convenient supplemental DNA sequencing method may be beneficial for differential detection.
Non-invasive Metabolomic Profiling of Embryo Culture Medium Using Raman Spectroscopy With Deep Learning Model Predicts the Blastocyst Development Potential of Embryos
Authors: Zheng Wei , Zhang Shuoping , Gu Yifan , Gong Fei , Kong Lingyin , Lu Guangxiu , Lin Ge , Liang Bo , Hu Liang 
Published: November 2021

Purpose: This study aimed to establish a non-invasive predicting model via Raman spectroscopy for evaluating the blastocyst development potential of day 3 high-quality cleavage stage embryos.Methods: Raman spectroscopy was used to detect the metabolic spectrum of spent day 3 (D3) embryo culture medium, and a classification model based on deep learning was established to differentiate between embryos that could develop into blastocysts (blastula) and that could not (non-blastula). The full-spectrum data for 80 blastula and 48 non-blastula samples with known blastocyst development potential from 34 patients were collected for this study.Results: The accuracy of the predicting method was 73.53% and the main different Raman shifts between blastula and non-blastula groups were 863.5, 959.5, 1,008, 1,104, 1,200, 1,360, 1,408, and 1,632 cm–1 from 80 blastula and 48 non-blastula samples by the linear discriminant method.Conclusion: This study demonstrated that the developing potential of D3 cleavage stage embryos to the blastocyst stage could be predicted with spent D3 embryo culture medium using Raman spectroscopy with deep learning classification models, and the overall accuracy reached at 73.53%. In the Raman spectroscopy, ribose vibration specific to RNA were found, indicating that the difference between the blastula and non-blastula samples could be due to materials that have similar structure with RNA. This result could be used as a guide for biomarker development of embryo quality assessment in the future.
Advanced Age Is Associated With Catatonia in Critical Illness: Results From the Delirium and Catatonia Prospective Cohort Investigation
Authors: Connell Jennifer , Kim Ahra , Brummel Nathan E. , Patel Mayur B. , Vandekar Simon N. , Pandharipande Pratik , Dittus Robert S. , Heckers Stephan , Ely E. Wes , Wilson Jo Ellen 
Published: November 2021

Introduction: Catatonia, characterized by motor, behavioral and affective abnormalities, frequently co-occurs with delirium during critical illness. Advanced age is a known risk factor for development of delirium. However, the association between age and catatonia has not been described. We aim to describe the occurrence of catatonia, delirium, and coma by age group in a critically ill, adult population.Design: Convenience cohort, nested within two clinical trials and two observational cohort studies.Setting: Intensive care units in an academic medical center in Nashville, TN.Patients: 378 critically ill adult patients on mechanical ventilation and/or vasopressors.Measurements and Main Results: Patients were assessed for catatonia, delirium, and coma by independent and blinded personnel, the Bush Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit (ICU) and the Richmond Agitation and Sedation Scale. Of 378 patients, 23% met diagnostic criteria for catatonia, 66% experienced delirium, and 52% experienced coma during the period of observation. There was no relationship found between age and catatonia severity or age and presence of specific catatonia items. The prevalence of catatonia was strongly associated with age in the setting of critical illness (p &lt; 0.05). Delirium and comas' association with age was limited to the setting of catatonia.Conclusion: Given the significant relationship between age and catatonia independent of coma and delirium status, these data demonstrate catatonia's association with advanced age in the setting of critical illness. Future studies can explore the causative factors for this association and further elucidate the risk factors for acute brain dysfunction across the age spectrum.
Association of Cigarette Smoking With Male Cognitive Impairment and Metal Ions in Cerebrospinal Fluid
Authors: Li Hui , Mu Qingshuang , Kang Yimin , Yang Xiaoyu , Shan Ligang , Wang Meiling , Li Cunbao , Liu Yanlong , Wang Fan 
Published: November 2021

Objective: Cigarette smoking might accelerate cognitive impairment; however, this has never been investigated using human cerebrospinal fluid (CSF). We conducted this study to investigate the association between cigarette smoking and cognitive impairment through metal ions in CSF.Methods: We obtained 5-ml CSF samples from routine lumbar puncture procedures in patients undergoing anterior cruciate ligament reconstruction before surgery in China. A total of 180 Chinese males were recruited (80 active smokers and 100 non-smokers). We measured specific cigarette-related neurotoxic metal ions in CSF, including iron, copper, zinc, lead, aluminum, and manganese. Sociodemographic data and history of smoking were obtained. The Montreal Cognitive Assessment (MoCA) was applied.Results: Active smokers had fewer years of education (11.83 ± 3.13 vs. 13.17 ± 2.60, p = 0.01), and higher age (33.70 ± 10.20 vs. 29.76 ± 9.58, p = 0.01) and body mass index (25.84 ± 3.52 vs. 24.98 ± 4.06, p =0.03) than non-smokers. Compared to non-smokers, active smokers had significantly higher CSF levels of iron, zinc, lead, and aluminum and lower MoCA scores (all p &lt; 0.05). Average daily numbers of cigarettes smoked negatively correlated with the MoCA scores (r = −0.244, p = 0.048). In young smokers, CSF manganese levels negatively correlated with MoCA scores (r = −0.373, p = 0.009).Conclusions and Relevance: Cigarette smoking might be associated with male cognitive impairment, as shown by lower MoCA scores and higher levels of CSF iron, zinc, lead, and aluminum in active smokers. This might be early evidence of cigarette smoking accelerating male cognitive impairment.
Neuropsychiatric Symptoms Exacerbate the Cognitive Impairments in Patients With Late-Life Depression
Authors: Zhang Min , Chen Ben , Zhong Xiaomei , Zhou Huarong , Wang Qiang , Mai Naikeng , Wu Zhangying , Chen Xinru , Peng Qi , Zhang Si , Yang Minfeng , Lin Gaohong , Ning Yuping 
Published: November 2021

Background: Neuropsychiatric symptoms (NPS) and cognitive impairments are both common in patients with late-life depression (LLD). However, the relationship between NPS and cognitive functions in LLD patients remains unclear. The current study aims to explore the effects of NPS on cognitive impairments in LLD patients.Methods: Two hundred and sixty-two LLD patients and 141 normal controls (NC) were recruited. Exploratory factor analysis was used to extract factors from the Neuropsychiatric Inventory (NPI). Correlation, mediation, and moderation analyses were used to explore whether NPS exacerbated the cognitive impairments in LLD and whether NPS exhibited different effects on cognitive impairments in acute-state LLD (aLLD) and recovery-state LLD (rLLD).Results: Three main factors were extracted from the NPI, including emotional, behavioral, and psychotic factors. The patients with LLD exhibited worse cognition and higher NPI scores, and the scores of NPI-total and three extracted factors were negatively associated with cognitive scores. The mediation analyses exhibited that NPI-total and behavioral factor scores increase the difference in cognition scores between LLD and NC groups. The mediation analyses exhibited that behavioral factor score played a greater effect on impairing MMSE in the rLLD group than in the aLLD group. Additionally, behavioral factor score was in a trend to be negatively associated with Mini-Mental State Examination (MMSE) score changes at a one-year follow-up (p = 0.051).Conclusions: NPS, especially behavioral symptoms, exacerbate cognitive impairments in LLD and may contribute to residual cognitive impairment in rLLD patients. Early intervention for behavioral symptoms in LLD patients may be beneficial to their long-term clinical prognosis.
Sleep Quality and Mental Health of Medical Students in Greece During the COVID-19 Pandemic
Authors: Eleftheriou Anna , Rokou Aikaterini , Arvaniti Aikaterini , Nena Evangelia , Steiropoulos Paschalis 
Published: November 2021

Background-Aim: Medical students have been greatly affected by the COVID-19 pandemic due to their educational program, which comprises theoretical knowledge and also clinical duties, making them vulnerable to viral exposures and possibly affecting their everyday life. The aim of this study was to explore changes in sleep and mental health parameters among medical students in Greece during the second year of the pandemic.Methods: This cross-sectional study comprised students of all medical schools in Greece (n = 7), using an anonymous online survey. Participants completed the following questionnaires: Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), Fatigue Severity Scale (FSS), General Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9). Statistical analysis was conducted with the use of SPSS v.26 (IBM SPSS, Armonk NY, USA).Results: Out of the 562 received responses, 559 met the inclusion criteria. The largest proportion of the respondents came from 4th-year (27.8%) and the majority of the sample were females (69.8%). Only 5.9% of the participants reported having been infected by SARS-COV-2. Most of the respondents experienced insomnia (65.9%, mean AIS score: 7.59 ± 4.24), poor sleep quality (52.4%, mean PSQI score: 6.6 ± 3.25) and increased fatigue (48.5%, mean 35.82 ± 11.74). Moderate to severe symptoms of anxiety (mean 9.04 ± 5.66) and depression (mean 9.36 ± 6.15) were noted. Suicidal ideation was found in 16.7% of the sample, while use of sleeping pills in the previous month was reported by 8.8% (n = 47). Further analysis revealed independent associations between sleep and mental health parameters. Higher AIS score was associated with greater FSS score; higher PSQI scores with higher GAD-7 and PHQ-9 scores. Additionally, female students were found to be significantly more affected than males by the COVID-19 pandemic, displaying higher levels of insomnia, sleep disturbances, anxiety and depression. In addition, those with a history of COVID-19 infection or in close proximity with a positive case reported significantly more significant post-traumatic symptoms in IES-COVID-19 questionnaire.Conclusions: In the aftermath of the COVID-19 pandemic, prevalence of sleep and mental health disorders among Greek medical students is significant, highlighting the need for better surveillance of students' wellbeing and subsequent counseling, with special focus on female students and other affected groups.
The Association Between Psychological Symptoms and Self-Reported Temporomandibular Disorders Pain Symptoms in Children and Adolescents
Authors: Al-Khotani Amal , Meisha Dalia E. , Al Sayegh Samaa , Hedenberg-Magnusson Britt , Ernberg Malin , Christidis Nikolaos 
Published: November 2021

Background: Several studies have reported an association between temporomandibular disorder pain (TMD-P) and emotional disorders in children and adolescents. However, no studies have reported if self-reported TMD-P in Saudi Arabia is associated with psychosocial symptoms. Therefore, the current study aimed to evaluate the association between self-reported TMD-P with depression, anxiety and somatic problems in children and adolescents in Saudi Arabia. The hypothesis was that there is an association between self-reported TMD-P and psychological symptoms among children and adolescents.Materials and Methods: The included participants were randomly selected boys and girls aged between 10 and 18 years, with a mean (SD) age of 14.0 (2.3) years. Out of 633 children and adolescents that were invited to participate, 509 voluntarily agreed to participate, and 466 completed all questionnaires. The questionnaires included items retrieved from the Youth Self Report (YSR) and Axis II of the Research Diagnostic Criteria for TMD (RDC/TMD) besides demographic data, medical history, and presence of oral parafunctions. To assess the presence of self-reported TMD-Pain, each participant was verbally asked two validated questions regarding the presence of TMD-P and dysfunction (2Q-TMD).Results: Self-reported TMD-P in children and adolescents was significantly associated with anxiety, depression, somatic symptoms, and social problems (P &lt; 0.0001). Further, the frequencies of anxiety, depression, and somatic disorders were more evident among children and adolescents who suffered from TMD-P (P &lt; 0.0001). The odds of reporting TMD-P in children and adolescents was 1.4 times for border line and clinical diagnosis scores for anxiety and withdrawal depression domains, and 2.6 times for the somatic symptoms' domains. However, in the multiple regression model after controlling for possible confounders, only somatic symptoms and social scores were significant. Moreover, self-reported TMD-P was twice as prevalent among girls compared to boys.Conclusion: This study reports a significant association between psychosocial burden and presence of self-reported TMD-Pain, with a stronger impact on girls than boys. There were significantly higher number of participants with self-reported TMD-P reporting a poor oral and general health. In addition, self-reported TMD-P was higher among those with borderline and clinically diagnosed anxiety/depression scores. Based on this finding, the current study supports that an early approach and recognition of children and adolescents with anxiety, depression, somatic symptoms, and TMD problems. This could result in a lesser burden for these children and adolescents both in regard to pain and psychosocial implications with increased quality of life.
Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players
Authors: Goodin Peter , Gardner Andrew J. , Dokani Nasim , Nizette Ben , Ahmadizadeh Saeed , Edwards Suzi , Iverson Grant L. 
Published: November 2021

Background: Exposure to thousands of head and body impacts during a career in contact and collision sports may contribute to current or later life issues related to brain health. Wearable technology enables the measurement of impact exposure. The validation of impact detection is required for accurate exposure monitoring. In this study, we present a method of automatic identification (classification) of head and body impacts using an instrumented mouthguard, video-verified impacts, and machine-learning algorithms.Methods: Time series data were collected via the Nexus A9 mouthguard from 60 elite level men (mean age = 26.33; SD = 3.79) and four women (mean age = 25.50; SD = 5.91) from the Australian Rules Football players from eight clubs, participating in 119 games during the 2020 season. Ground truth data labeling on the captures used in this machine learning study was performed through the analysis of game footage by two expert video reviewers using SportCode and Catapult Vision. The visual labeling process occurred independently of the mouthguard time series data. True positive captures (captures where the reviewer directly observed contact between the mouthguard wearer and another player, the ball, or the ground) were defined as hits. Spectral and convolutional kernel based features were extracted from time series data. Performances of untuned classification algorithms from scikit-learn in addition to XGBoost were assessed to select the best performing baseline method for tuning.Results: Based on performance, XGBoost was selected as the classifier algorithm for tuning. A total of 13,712 video verified captures were collected and used to train and validate the classifier. True positive detection ranged from 94.67% in the Test set to 100% in the hold out set. True negatives ranged from 95.65 to 96.83% in the test and rest sets, respectively.Discussion and conclusion: This study suggests the potential for high performing impact classification models to be used for Australian Rules Football and highlights the importance of frequencies &lt;150 Hz for the identification of these impacts.