bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers
Authors: He Chun-Ming , Zhang Xin-Di , Zhu Song-Xin , Zheng Jia-Jie , Wang Yu-Ming , Wang Qing , Yin Hang , Fu Yu-Jie , Xue Song , Tang Jian , Zhao Xiao-Jing 
Published: September 2022

Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p &lt; 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p &lt; 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.
Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma
Authors: Yang Jiaqi , Zhang Jian , Na Song , Wang Zhizhou , Li Hanshuo , Su Yuxin , Ji Li , Tang Xin , Yang Jun , Xu Lu 
Published: September 2022

BackgroundDespite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel.MethodsSingle cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel.ResultsThe malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel.ConclusionsOverall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.
Cuproptosis-related gene FDX1 expression correlates with the prognosis and tumor immune microenvironment in clear cell renal cell carcinoma
Authors: Wang Tao , Liu Yufeng , Li Qing , Luo Yang , Liu Dawei , Li Bin 
Published: September 2022

BackgroundCuproptosis, a newly discovered form of cell death, is regulated by protein lipoylation and is related to mitochondrial metabolism. However, further research is needed to determine how the cuproptosis-related gene ferredoxin 1 (FDX1) affects the tumor immune response and its prognostic significance in clear cell renal cell carcinoma (ccRCC).MethodsThe Cancer Genome Atlas was used to screen for FDX1 gene expression in ccRCC and healthy tissue samples. The results were validated using the Gene Expression Omnibus and the Human Protein Atlas. Multivariable analysis and Kaplan-Meier survival curves were used to examine the relationship between FDX1 gene expression, clinicopathological parameters, and overall survival (OS). The protein network containing FDX1 gene interaction was constructed using the online Search Tool for the Retrieval of Interacting Genes/Proteins. The relationship between FDX1 gene expression and immune cell infiltration in ccRCC was examined using Gene Ontology, gene set enrichment analysis (GSEA), and a single-sample GSEA. Using the Gene Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource databases, we investigated the relationship between FDX1 gene expression, the degree of immune cell infiltration, and the corresponding gene marker sets.ResultsccRCC samples had significantly (p &lt; 0.05) lower FDX1 gene expression levels than normal tissue samples. Lower FDX1 gene expression levels were strongly associated with higher cancer grades and more advanced tumor–node–metastasis stages. The findings of multivariate and univariate analyses illustrated that the OS in ccRCC patients with low FDX1 expression is shorter than in patients with high FDX1 expression (p &lt; 0.05). Ferredoxin reductase and CYP11A1 are key proteins interacting with the FDX1 gene, and ccRCC with an FDX1 enzyme defect was associated with a low number of invading immune cells and their corresponding marker.ConclusionIn ccRCC, decreased FDX1 expression was linked to disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration.
Risk Factors for Acquired Stenotrophomonas maltophilia Pneumonia in Intensive Care Unit: A Systematic Review and Meta-Analysis
Authors: Wang Neng , Tang Congchen , Wang Lichun 
Published: September 2022

Background and Aims:Stenotrophomonas maltophilia is increasingly found in critically ill patients, but it is considered a pathogen of limited pathogenicity and therefore it is not often targeted. We systematically evaluated risk factors for S. maltophilia pneumonia in ICU patients for better clinical management.Methods: Prospective and retrospective studies of S. maltophilia infection in the ICU from database establishment to August 8, 2021, were searched through PubMed, web of science, Cochrane Library Embase and CNKI. The literature was independently screened and extracted by two authors according to inclusion and exclusion criteria, evaluated for quality by the NOS scale, and meta-analyzed by stata 14.0 software.Results: A total of eight studies with a sample size of 2,320 cases were included. Meta-analysis showed that APACHE-II score &gt; 20 (OR = 10.98, 95% CI: 5.67 ~ 21.26), COPD (OR = 3.97, 95% CI: 2.39 ~ 6.61), malignant tumor (OR = 2.15, 95% CI: 1.03 ~ 4.50), mechanical ventilation (OR = 8.75, 95% CI: 2.59 ~ 29.58), tracheotomy (OR = 6.12, 95% CI: 2.06 ~ 18.18), endotracheal intubation (OR = 4.25, 95% CI: 2.30 ~ 7.84), β- Lactamase inhibitors (OR = 9.98, 95% CI: 1.51 ~ 65.96), aminoglycosides (OR = 4.01, 95% CI: 2.06 ~ 7.80), carbapenems (OR = 2.82, 95% CI: 1.49 ~ 5.31), and quinolones (OR = 2.17, 95% CI: 1.21 ~ 3.89) were risk factors for ICU-acquired S. maltophilia pneumonia.Conclusion: Many risk factors are associated with S. maltophilia pneumonia in ICU patients. Clinical workers should pay more attention to assessing the risk of infection in ICU patients and enhance the prevention and management of high-risk groups, which will help reduce their risk of S. maltophilia infection.
Anticoagulant for treatment and prophylaxis of venous thromboembolism patients with renal dysfunction: A systematic review and network meta-analysis
Authors: Fan Guohui , Wang Dingyi , Zhang Meng , Luo Xufei , Zhai Zhenguo , Wu Sinan 
Published: September 2022

ObjectiveThe aim of this study was to compare the efficacy and safety for particular regimen and dosage in venous thromboembolism (VTE) patients with renal insufficiency.MethodsEnglish language searches of PubMed, Embase, and Web of Science (inception to May 2021). RCTs evaluating anticoagulants for VTE treatment at acute phase, extension phase, and VTE prophylaxis in patients with renal insufficiency and reporting efficacy (death, recurrence, or occurrence of VTE) and safety (bleeding) outcomes were selected. The methodological quality of each study included was assessed at the outcome level using the risk-of-bias assessment tool developed by the Cochrane Bias Methods Group.ResultsTwenty-one trials that involved 76,574 participants and 8,972 (11.7%) patients with renal insufficiency were enrolled, including 10 trials on VTE treatment in acute phase (3–12 months), four trials on VTE treatment in extension phase (6–36 months), and seven trials for VTE prophylaxis. For acute VTE treatment, compared with dabigatran etexilate, apixaban (RR 5.90, 95%CI 1.00–34.60) and rivaroxaban (RR 6.18, 95%CI 1.17–32.75) were significantly associated with increased risk of death or recurrence. For extension treatment of VTE, aspirin had the highest probability of the most effective and safest treatment, followed by apixaban. For VTE prophylaxis, compared with enoxaparin, desirudin was associated with lower risk of VTE occurrence (RR 0.56, 95% CI 0.34–0.91), but had higher risk of bleeding than dabigatran etexilate.ConclusionThe network meta-analysis informs the optimal choice of anticoagulants and their particular dosage for treatment and prophylaxis of VTE patients comorbid renal insufficiency.Systematic review registrationwww.crd.york.ac.uk/prospero/, identifier: CRD42021254086.
Safety and efficacy of tyrosine kinase inhibitors for the treatment of multiple sclerosis: A systematic review and meta-analysis from randomized controlled trials
Authors: Yan Zeya , Gu Feng , Wang Zilan , Meng Jiahao , Tao Xinyu , Dai Qiling , Wang Wei , Liu Meirong , Wang Zhong 
Published: September 2022

BackgroundMultiple sclerosis (MS), an autoimmune disease, is characterized by inflammatory demyelinating lesions in the white matter of the central nervous system. Drugs targeting tyrosine kinase, a critical component of immune cell receptor signaling, have been developed to treat MS. However, the exact efficacy and safety of tyrosine kinase inhibitors (TKIs) are still controversial, and comprehensive analysis with a high level of evidence is needed.MethodsMedline, Embase, Cochrane Library, and Clinicaltrials.gov for randomized controlled trials (RCTs) evaluating TKIs versus placebo for MS were searched up to April 1st, 2022. The risk ratio (RR) and mean difference (MD) or standard mean difference (SMD) were analyzed using dichotomous outcomes and continuous outcomes, respectively, with a random effect model.ResultsA total of 1,043 patients derived from four clinical trials were included to investigate the efficacy and safety of TKI therapy for MS. According to our analysis, TKIs decreased the cumulative number of gadolinium-enhancing lesions on T1-weighted MRI with the application of high dose (SMD = −0.61, 95% CI: −0.93 to −0.30, P = 0.0001). Meanwhile, TKIs prevented the expanded disability status scale (EDSS) from rising (MD = −0.10, 95% CI: −0.19 to −0.00, P = 0.046). In terms of MS relapse, TKIs have not revealed an obvious statistical difference compared with placebo (RR = 0.96, 95% CI: 0.55–1.65, P = 0.8755). However, more adverse events seem to occur in the TKIs group, both for adverse events (RR = 1.12, 95% CI: 1.05–1.19, P = 0.0009) and serious adverse events (RR = 1.91, 95% CI: 1.30–2.81, P = 0.001).ConclusionTyrosine kinase inhibitors have shown promise in treating MS. Generally, TKIs that attain the effective dose demonstrate definite efficacy and have tolerable side effects. More clinical trials and validation are needed, and we anticipate that TKIs will be a viable alternative for MS patients.
Identification of tumor antigens and immune subtypes in breast cancer for mRNA vaccine development
Authors: Li Ruo Qi , Wang Wei , Yan Lei , Song Li Ying , Guan Xin , Zhang Wei , Lian Jing 
Published: September 2022

BackgroundPoor prognosis, resistance to chemotherapy, insensitivity to radiotherapy, and a high prevalence of adverse drug reactions remain urgent issues for breast cancer (BC) patients. Increased knowledge of tumor immunobiology and vaccine development suggests the possibility of cancer vaccination. Here, we investigated potential BC-associated antigens for the development of an anti-BC mRNA vaccine and populations suitable for mRNA vaccination.MethodsGene expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). The single-cell sequencing data were obtained from the Single Cell Portal platform. cBioPortal was used to visualize and compare genetic alterations. Correlations between immune cell infiltration and antigen expression were visualized with the Tumor Immune Estimation Resource (TIMER). Immune subtypes were identified by consensus clustering and analysis of immune infiltration. Biomarkers for the assessment of mRNA vaccination suitability were investigated.ResultsThree tumor-associated antigens, CD74, IRF1, and PSME2, that showed overexpression, amplification, and mutation and were linked with prognosis and immune cell infiltration, were identified. Single-cell sequencing analysis showed the expression of the three tumor-associated antigens in different cells of BC. Three immune subtypes were identified among BC patients, with Cluster B patients having a tumor microenvironment conducive to immunotherapy. These subtypes also showed different expression patterns of immune checkpoints, immune cell death-promoting genes, and response to immune checkpoint inhibitor (ICI) therapy. Thus, we identified five biomarkers that could be applied for assessing vaccination suitability and predicted drugs that would be appropriate for patients unsuited for vaccination.ConclusionsOur findings suggest new directions for the development of mRNA vaccines against breast cancer.
Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors
Authors: Huang Weize , Stader Felix , Chan Phyllis , Shemesh Colby S. , Chen Yuan , Gill Katherine L. , Jones Hannah M. , Li Linzhong , Rossato Gianluca , Wu Benjamin , Jin Jin Y. , Chanu Pascal 
Published: September 2022

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients.Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations.Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old.Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including Cmin, Cmax, and AUCtau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults.Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.
The role of illness perceptions on medication nonadherence among patients with hypertension: A multicenter study in indonesia
Authors: Alfian Sofa D. , Annisa Nurul , Perwitasari Dyah A. , Coelho Andre , Abdulah Rizky 
Published: September 2022

Introduction: Nonadherence to antihypertensive medications is recognized as a significant cause of treatment failure. Therefore, identifying its underlying factors, particularly from the patient’s perspective, is essential for developing tailored intervention strategies. The objective of this study was to evaluate the associations between different domains of illness perception and medication nonadherence among patients with hypertension in Indonesia.Patients and methods: A multicenter cross-sectional study was conducted among patients with hypertension aged 18 years old and older who were using antihypertensive medications in the last 3 months in the community health centers in the three cities in Indonesia. The different domains of illness perception (e.g., consequences, timeline, personal control, treatment control, identity, concerns, comprehension, and emotional response) and medication nonadherence were assessed using a validated Brief Illness Perceptions Questionnaire (BIPQ) and Medication Adherence Report Scale (MARS), respectively. A logistic regression analysis was conducted to evaluate the associations between the different domains of illness perception and medication nonadherence adjusting for confounders. The odds ratios (ORs) and 95% confidence intervals (CIs) were reported.Results: A total of 440 participants were included, whom 41.8% reported nonadherence to antihypertensive medications. The majority of the participants were females (64.3%) and aged between 60 and 69 years old (39.5%). The treatment control (OR: 0.80, 95% confidence interval: 0.7–10.90), patient’s comprehension of hypertension (OR: 0.89, 95% CI: 0.820–0.97), and patient’s emotions (OR: 0.93, 95% CI: 0.88–0.99) were significantly associated with medication nonadherence. No significant associations were observed between the other domains of illness perception and medication nonadherence.Conclusion: Different dimensions of illness perception were associated with non-adherence to antihypertensive medications. Educational interventions should be developed based on patients’ perception of their illness.
Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke
Authors: Pohl Johannes , Ryser Alain , Veerbeek Janne Marieke , Verheyden Geert , Vogt Julia Elisabeth , Luft Andreas Rüdiger , Easthope Chris Awai 
Published: September 2022

Background: Stroke leads to motor impairment which reduces physical activity, negatively affects social participation, and increases the risk of secondary cardiovascular events. Continuous monitoring of physical activity with motion sensors is promising to allow the prescription of tailored treatments in a timely manner. Accurate classification of gait activities and body posture is necessary to extract actionable information for outcome measures from unstructured motion data. We here develop and validate a solution for various sensor configurations specifically for a stroke population.Methods: Video and movement sensor data (locations: wrists, ankles, and chest) were collected from fourteen stroke survivors with motor impairment who performed real-life activities in their home environment. Video data were labeled for five classes of gait and body postures and three classes of transitions that served as ground truth. We trained support vector machine (SVM), logistic regression (LR), and k-nearest neighbor (kNN) models to identify gait bouts only or gait and posture. Model performance was assessed by the nested leave-one-subject-out protocol and compared across five different sensor placement configurations.Results: Our method achieved very good performance when predicting real-life gait versus non-gait (Gait classification) with an accuracy between 85% and 93% across sensor configurations, using SVM and LR modeling. On the much more challenging task of discriminating between the body postures lying, sitting, and standing as well as walking, and stair ascent/descent (Gait and postures classification), our method achieves accuracies between 80% and 86% with at least one ankle and wrist sensor attached unilaterally. The Gait and postures classification performance between SVM and LR was equivalent but superior to kNN.Conclusion: This work presents a comparison of performance when classifying Gait and body postures in post-stroke individuals with different sensor configurations, which provide options for subsequent outcome evaluation. We achieved accurate classification of gait and postures performed in a real-life setting by individuals with a wide range of motor impairments due to stroke. This validated classifier will hopefully prove a useful resource to researchers and clinicians in the increasingly important field of digital health in the form of remote movement monitoring using motion sensors.