bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive bioinformatics analysis reveals common potential mechanisms, progression markers, and immune cells of coronary virus disease 2019 and atrial fibrillation
Authors: Lu Yang , Zhao Ning , Du Yimei 
Published: October 2022

ObjectivesAtrial fibrillation (AF) is the most common arrhythmia in coronary virus disease 2019 (COVID-19) patients, especially in severe patients. A history of AF can exacerbate COVID-19 symptoms. COVID-19 Patients with new-onset AF have prolonged hospital stays and increased death risk. However, the mechanisms and targets of the interaction between COVID-19 and AF have not been elucidated.Materials and methodsWe used a series of bioinformatics analyses to understand biological pathways, protein-protein interaction (PPI) networks, gene regulatory networks (GRNs), and protein-chemical interactions between COVID-19 and AF and constructed an AF-related gene signature to assess COVID-19 severity and prognosis.ResultsWe found folate and one-carbon metabolism, calcium regulation, and TFG-β signaling pathway as potential mechanisms linking COVID-19 and AF, which may be involved in alterations in neutrophil metabolism, inflammation, and endothelial cell function. We identified hug genes and found that NF-κb, hsa-miR-1-3p, hsa-miR-124-3p, valproic acid, and quercetin may be key regulatory molecules. We constructed a 3-gene signature consisting of ARG1, GIMAP7, and RFX2 models for the assessment of COVID-19 severity and prognosis, and found that they are associated with neutrophils, T cells, and hematopoietic stem cells, respectively.ConclusionOur study reveals a dysregulation of metabolism, inflammation, and immunity between COVID-19 and AF, and identified several therapeutic targets and progression markers. We hope that the results will reveal important insights into the complex interactions between COVID-19 and AF that will drive novel drug development and help in severity assessment.
Drug-induced torsades de pointes: Disproportionality analysis of the United States Food and Drug Administration adverse event reporting system
Authors: Wu Ziyang , Zhou Pengxiang , He Na , Zhai Suodi 
Published: October 2022

ObjectiveThis study aimed to identify the most common and top drugs associated with the risk of torsades de pointes (TdP) based on the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database.Materials and methodsWe used OpenVigil 2.1 to query FAERS database and data from the first quarter of 2004 to the third quarter of 2021 were retrieved. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify TdP cases. We listed the most common drugs associated with the reported TdP cases. Then, the reporting odds ratio (ROR) and the proportional reporting ratio (PRR) for the reporting association between different drugs and TdP risk were calculated. Meanwhile, comparisons were conducted with the QT drug lists of CredibleMeds® in an attempt to identify drugs with a potential risk of TdP that were not on the list.ResultsA total of 9,217,181 adverse event reports were identified, of which 3,807 (0.04%) were related to TdP. TdP was more likely to occur in the elderly and females. Amiodarone (464 cases) was associated with most cases of TdP. According to the disproportionality analysis, the top five drugs with the highest ROR and PRR were tolazoline (ROR 1615.11, 95% confidence interval [CI] 455.59–5725.75, PRR 969.46, χ2 2960.10), levomethadyl (ROR 1211.01, 95% CI 302.75–4844.04, PRR 807.67, χ2 1677.03), ibutilide (ROR 1118.74, 95% CI 425.00–2944.91, PRR 765.77, χ2 3845.27), halofantrine (ROR 660.55, 95% CI 184.21–2368.69, PRR 519.22, χ2 1076.31), and isoproterenol (ROR 352.20, 95% CI 227.19–546.00, PRR 307.82, χ2 6692.53). Approximately half of the top 50 drugs (22 for ROR, 30 for PRR) were not outlined on the QT drug lists of CredibleMeds®.ConclusionApproximately half of the top risk drugs (22 for ROR, 30 for PRR) were not outlined in the QT drug lists of CredibleMeds®. Notably, potential risks are of great importance and should be closely monitored in clinical practice. Also, further research is needed to investigate the association between these drugs and TdP.
Over than three-year follow-up results of thermal ablation for papillary thyroid carcinoma: A systematic review and meta-analysis
Authors: Xue JiaNan , Teng DengKe , Wang Hui 
Published: October 2022

BackgroundThis study is a meta-analysis based on evidence-based medicine to explore the long-term (≥3 years) efficacy of thermal ablation in the treatment of papillary thyroid carcinoma (PTC).MethodsWe searched the PubMed, Embase, and Cochrane Library databases for studies published during the time between the establishment of the databases through June 2022. We included 13 non-randomized-controlled trials (non-RCTs) that reported the application of ultrasound-guided thermal ablation in PTC. We excluded studies that were repeated publications, research without full text, contained incomplete information, lacked data extraction, involved animal experiments, reviews, and systematic reviews. STATA 15.1 software was used to analyze the data.ResultsTumor volume after thermal ablation at 3-year follow-up was significantly lower than pre-ablation (standardized mean difference [SMD] = -1.06, 95% CI: -1.32~-0.80). The pooled results indicated that the maximum diameter after thermal ablation at 3-year follow-up was significantly lower than pre-ablation (SMD = -1.93, 95% CI: -12.13~-1.73). The pooled results indicated that volume reduction rate (VRR) after thermal ablation at 3-year follow-up was 98.91% (95% CI: 97.98–99.83%), and complete disappearance rate (CDR) after thermal ablation at 3-year follow-up was 83% (95% CI: 67–94%). In addition, the incidence of newly discovered mPTC and lymph node metastases after thermal ablation was 0.3% (95% CI: 0.0–1.0%) and 0.0% (95% CI: 0.0–0.0%), respectively.ConclusionOverall, the long-term (≥3 years) efficacy of ultrasound-guided thermal ablation in the treatment of PTC was significant, with favorable disease progression. Ultrasound-guided thermal ablation can be considered an alternative approach for patients with PTC who refuse surgery or are unable to undergo surgery.
Nomogram for preoperative estimation of histologic grade in gastrointestinal neuroendocrine tumors
Authors: Wu Zhi-Qi , Li Yan , Sun Na-Na , Xu Qin , Zhou Jing , Su Kan-Kan , Goyal Hemant , Xu Hua-Guo 
Published: October 2022

BackgroundThe treatment strategies and prognosis for gastroenteropancreatic neuroendocrine tumors were associated with tumor grade. Preoperative predictive grading could be of great benefit in the selection of treatment options for patients. However, there is still a lack of effective non-invasive strategies to detect gastrointestinal neuroendocrine tumors (GI-NETs) grading preoperatively.MethodsThe data on 147 consecutive GI-NETs patients was retrospectively collected from January 1, 2012, to December 31, 2019. Logistic regression was used to construct a predictive model of gastrointestinal neuroendocrine tumor grading using preoperative laboratory and imaging parameters.The validity of the model was assessed by area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).ResultsThe factors associated with GI-NETs grading were age, tumor size, lymph nodes, neuron-specific enolase (NSE), hemoglobin (HGB) and sex, and two models were constructed by logistic regression for prediction. Combining these 6 factors, the nomogram was constructed for model 1 to distinguish between G3 and G1/2, achieving a good AUC of 0.921 (95% CI: 0.884-0.965), and the sensitivity, specificity, accuracy were 0.9167, 0.8256, 0.8630, respectively. The model 2 was to distinguish between G1 and G2/3, and the variables were age, tumor size, lymph nodes, NSE, with an AUC of 0.847 (95% CI: 0.799-0.915), and the sensitivity, specificity, accuracy were 0.7882, 0.8710, 0.8231, respectively. Two online web servers were established on the basis of the proposed nomogram to facilitate clinical use. Both models showed an excellent calibration curve through 1000 times bootstrapped dataset and the clinical usefulness were confirmed using decision curve analysis.ConclusionThe model served as a valuable non-invasive tool for differentiating between different grades of GI-NETs, personalizing the calculation which can lead to a rational treatment choice.
A prognostic pyroptosis-related LncRNA classifier associated with the immune landscape and therapy efficacy in glioma
Authors: Zhong Jiasheng , Liu Jie , Huang Zhilin , Zheng Yaofeng , Chen Jiawen , Ji Jingsen , Chen Taoliang , Ke Yiquan 
Published: October 2022

Background: Glioma has the highest fatality rate among intracranial tumours. Besides, the heterogeneity of gliomas leads to different therapeutic effects even with the same treatment. Developing a new signature for glioma to achieve the concept of “personalised medicine” remains a significant challenge.Method: The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were searched to acquire information on glioma patients. Initially, correlation and univariate Cox regression analyses were performed to screen for prognostic pyroptosis-related long noncoding RNAs (PRLs). Secondly, 11 PRLs were selected to construct the classifier using certain algorithms. The efficacy of the classifier was then detected by the “timeROC” package for both the training and validation datasets. CIBERSORT and ESTIMATE packages were applied for comparing the differences (variations) in the immune landscape between the high- and low-risk groups. Finally, the therapeutic efficacy of the chemotherapy, radiotherapy, and immunotherapy were assessed using the “oncoPredict” package, survival analysis, and the tumour immune dysfunction and exclusion (TIDE) score, respectively.Results: A classifier comprising 11 PRLs was constructed. The PRL classifier exhibits a more robust prediction capacity for the survival outcomes in patients with gliomas than the clinical characteristics irrespective of the dataset (training or validation dataset). Moreover, it was found that the tumour landscape between the low- and high-risk groups was significantly different. A high-risk score was linked to a more immunosuppressive tumour microenvironment. According to the outcome prediction and analysis of the chemotherapy, patients with different scores showed different responses to various chemotherapeutic drugs and immunotherapy. Meanwhile, the patient with glioma of WHO grade Ⅳ or aged &gt;50 years in the high risk group had better survival following radiotherapy.Conclusion: We constructed a PRL classifier to roughly predict the outcome of patients with gliomas. Furthermore, the PRL classifier was linked to the immune landscape of glioma and may guide clinical treatments.
QTL mapping and genomic prediction of resistance to wheat head blight caused by Fusarium verticillioides
Authors: Song Junqiao , Pang Yuhui , Wang Chunping , Zhang Xuecai , Zeng Zhankui , Zhao Dehui , Zhang Leiyi , Zhang Yong 
Published: October 2022

Fusarium head blight (FHB), is one of the destructive fugue diseases of wheat worldwide caused by the Fusarium verticillioides (F.v). In this study, a population consisting of 262 recombinant inbred lines (RILs) derived from Zhongmai 578 and Jimai 22 was used to map Quantitative Trait Locus (QTL) for FHB resistance, with the genotype data using the wheat 50 K single nucleotide polymorphism (SNP) array. The percentage of symptomatic spikelet (PSS) and the weighted average of PSS (PSSW) were collected for each RIL to represent their resistance to wheat head blight caused by F.v. In total, 22 QTL associated with FHB resistance were identified on chromosomes 1D, 2B, 3B, 4A, 5D, 7A, 7B, and 7D, respectively, from which 10 and 12 QTL were detected from PSS and PSSW respectively, explaining 3.82%–10.57% of the phenotypic variances using the inclusive composite interval mapping method. One novel QTL, Qfhb. haust-4A.1, was identified, explaining 10.56% of the phenotypic variation. One stable QTL, Qfhb. haust-1D.1 was detected on chromosome 1D across multiple environments explaining 4.39%–5.70% of the phenotypic variation. Forty-seven candidate genes related to disease resistance were found in the interval of Qfhb. haust-1D.1 and Qfhb. haust-4A.1. Genomic prediction accuracies were estimated from the five-fold cross-validation scheme ranging from 0.34 to 0.40 for PSS, and from 0.34 to 0.39 for PSSW in in-vivo inoculation treatment. This study provided new insight into the genetic analysis of resistance to wheat head blight caused by F.v, and genomic selection (GS) as a potential approach for improving the resistance of wheat head blight.
Construction of prognostic signature of breast cancer based on N7-Methylguanosine-Related LncRNAs and prediction of immune response
Authors: Cao Jin , Liang Yichen , Gu J. Juan , Huang Yuxiang , Wang Buhai 
Published: October 2022

Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients.Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature’s usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups.Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients’ immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy.Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients’ customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy.
Short-term safety and immunogenicity of inactivated and peptide-based SARS-CoV-2 vaccines in patients with endocrine-related cancer
Authors: Song Rui , Liu Li , Pan Qingbo , Liu Jin , Tan Jiahe , Deng Juan , Deng Qin , Lin Zijin , Chen Min , Peng Mingli , Ren Hong , Ming Jia 
Published: October 2022

BackgroundThe aim of this study was to explore the short-term safety and immunogenicity of inactivated and peptide-based SARS-CoV-2 vaccines in patients with endocrine-related cancer (ER).MethodsEighty-eight patients with ER cancer and 82 healthy controls who had completed a full course of inactivated or peptide-based SARS-CoV-2 vaccines were recruited. Adverse events (AEs) were recorded. Responses to receptor-binding domain IgG antibody (anti-RBD-IgG), neutralizing antibodies (NAbs) and RBD+ memory B cells (MBCs) were evaluated.ResultsApproximately 26.14% (23/88) of patients with ER cancer reported AEs within 7 days, which was comparable to that reported by healthy controls (24.39%, 20/82). Both the overall seroprevalence of anti-RBD-IgG and NAbs was obviously lower in the cancer group (70.45% vs. 86.59%, P &lt; 0.05; 69.32% vs. 82.93%, P &lt; 0.05, respectively). Anti-RBD-IgG and NAbs titers exhibited similar results, and dropped gradually over time. Patients with ongoing treatment had an attenuated immune response, especially in patients receiving active chemotherapy. The frequency of overall RBD+ MBCs was similar between the two groups, but the percentage of active MBCs was remarkably reduced in patients with ER cancer. Unlike antibody titers, MBCs responses were relatively constant over time.ConclusionInactivated and peptide-based COVID-19 vaccines were well tolerated, but with lower immunogenicity for ER cancer patients. More intensive antibody monitoring and timely booster immunization is recommended for patients with ER cancer presenting disordered subpopulations of RBD+ MBCs.
The carotid body: A novel key player in neuroimmune interactions
Authors: Katayama Pedro L. , Leirão Isabela P. , Kanashiro Alexandre , Menani José V. , Zoccal Daniel B. , Colombari Débora S. A. , Colombari Eduardo 
Published: October 2022

The idea that the nervous system communicates with the immune system to regulate physiological and pathological processes is not new. However, there is still much to learn about how these interactions occur under different conditions. The carotid body (CB) is a sensory organ located in the neck, classically known as the primary sensor of the oxygen (O2) levels in the organism of mammals. When the partial pressure of O2 in the arterial blood falls, the CB alerts the brain which coordinates cardiorespiratory responses to ensure adequate O2 supply to all tissues and organs in the body. A growing body of evidence, however, has demonstrated that the CB is much more than an O2 sensor. Actually, the CB is a multimodal sensor with the extraordinary ability to detect a wide diversity of circulating molecules in the arterial blood, including inflammatory mediators. In this review, we introduce the literature supporting the role of the CB as a critical component of neuroimmune interactions. Based on ours and other studies, we propose a novel neuroimmune pathway in which the CB acts as a sensor of circulating inflammatory mediators and, in conditions of systemic inflammation, recruits a sympathetic-mediated counteracting mechanism that appears to be a protective response.
Unsupervised clustering algorithms improve the reproducibility of dynamic contrast-enhanced magnetic resonance imaging pulmonary perfusion quantification in muco-obstructive lung diseases
Authors: Konietzke Marilisa , Triphan Simon M. F. , Eichinger Monika , Bossert Sebastian , Heller Hartmut , Wege Sabine , Eberhardt Ralf , Puderbach Michael U. , Kauczor Hans-Ulrich , Heußel Gudula , Heußel Claus P. , Risse Frank , Wielpütz Mark O. 
Published: October 2022

BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows the assessment of pulmonary perfusion, which may play a key role in the development of muco-obstructive lung disease. One problem with quantifying pulmonary perfusion is the high variability of metrics. Quantifying the extent of abnormalities using unsupervised clustering algorithms in residue function maps leads to intrinsic normalization and could reduce variability.PurposeWe investigated the reproducibility of perfusion defects in percent (QDP) in clinically stable patients with cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD).Methods15 CF (29.3 ± 9.3y, FEV1%predicted = 66.6 ± 15.8%) and 20 COPD (66.5 ± 8.9y, FEV1%predicted = 42.0 ± 13.3%) patients underwent DCE-MRI twice 1 month apart. QDP, pulmonary blood flow (PBF), and pulmonary blood volume (PBV) were computed from residue function maps using an in-house quantification pipeline. A previously validated MRI perfusion score was visually assessed by an expert reader.ResultsOverall, mean QDP, PBF, and PBV did not change within 1 month, except for QDP in COPD (p &lt; 0.05). We observed smaller limits of agreement (± 1.96 SD) related to the median for QDP (CF: ± 38%, COPD: ± 37%) compared to PBF (CF: ± 89%, COPD: ± 55%) and PBV (CF: ± 55%, COPD: ± 51%). QDP correlated moderately with the MRI perfusion score in CF (r = 0.46, p &lt; 0.05) and COPD (r = 0.66, p &lt; 0.001). PBF and PBV correlated poorly with the MRI perfusion score in CF (r =−0.29, p = 0.132 and r =−0.35, p = 0.067, respectively) and moderately in COPD (r =−0.57 and r =−0.57, p &lt; 0.001, respectively).ConclusionIn patients with muco-obstructive lung diseases, QDP was more robust and showed a higher correlation with the MRI perfusion score compared to the traditionally used perfusion metrics PBF and PBV.
Conversion of ER, PR, HER2 and Ki-67 and Prognosis in breast cancer metastases to the brain
Authors: Jiaxin Chen , Jinmei Zhou , Huiqiang Zhang , Xuexue Wu , Xiaobo Wang , Shaohua Zhang , Yanhong Tai , Zefei Jiang , Tao Wang 
Published: October 2022

ObjectiveThis study aimed to analyze the expression levels of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 proliferation index in the brain metastatic lesions and primary lesions in Chinese patients with breast cancer brain metastasis (BCBM) and determine the correlation between their changes and patients' survival.MethodsA retrospective analysis was performed on patients with BCBM. The clinical characteristic of these patients was collected. The differences in the expression levels of the ER, PR, HER-2, and Ki-67 index between the primary lesions and brain lesions were evaluated, and the association between the differences and survival was analyzed.ResultsThe conversion rate of anyone receptor (ER, PR, or HER2) between the primary lesions and brain metastatic lesions was 45.0% (18/40), of which the ER inconsistency rate was 25.0%, the PR inconsistency rate was 22.5%, and the HER-2 inconsistency rate was 15.0%, and the receptor conversion resulted in a subtype conversion of 27.5% (11/40). The patients with HER-2 expression discordance between the primary lesions and the brain metastatic lesions had significantly longer survival times (58.9 vs. 26.4 months, P = 0.04) after diagnosis of brain metastases.ConclusionIn this study, 45.0% of breast cancer patients developed biomarker-conversion between the primary lesions and brain metastatic lesions, and the differences in the expression levels of the ER, PR, and HER-2, the change in Ki-67 index between the primary lesions and brain lesions may predict patients' survival.