bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma
Authors: Xiao Lingyan , Li Qian , Huang Yongbiao , Fan Zhijie , Qin Wan , Liu Bo , Yuan Xianglin 
Published: April 2022

Background: Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD.Methods: LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan–Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR.Results: A prognostic signature based on eight ERGs (FERMT1, CTSV, CPS1, ENTPD2, SERPINB5, ITGA8, ADAMTS8, and LYPD3) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely.Conclusions: We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.
Uremic Toxin-Producing Bacteroides Species Prevail in the Gut Microbiota of Taiwanese CKD Patients: An Analysis Using the New Taiwan Microbiome Baseline
Authors: Shivani Subhashree , Kao Cheng-Yen , Chattopadhyay Amrita , Chen Jenn-Wei , Lai Liang-Chuan , Lin Wei-Hung , Lu Tzu-Pin , Huang I-Hsiu , Tsai Mong-Hsun , Teng Ching-Hao , Wu Jiunn-Jong , Hsieh Yi-Hsien , Wang Ming-Cheng , Chuang Eric Y. 
Published: April 2022

Rationale and ObjectiveGut microbiota have been targeted by alternative therapies for non-communicable diseases. We examined the gut microbiota of a healthy Taiwanese population, identified various bacterial drivers in different demographics, and compared them with dialysis patients to associate kidney disease progression with changes in gut microbiota.Study DesignThis was a cross-sectional cohort study.Settings and ParticipantsFecal samples were obtained from 119 healthy Taiwanese volunteers, and 16S rRNA sequencing was done on the V3-V4 regions to identify the bacterial enterotypes. Twenty-six samples from the above cohort were compared with fecal samples from 22 peritoneal dialysis and 16 hemodialysis patients to identify species-level bacterial biomarkers in the dysbiotic gut of chronic kidney disease (CKD) patients.ResultsSpecific bacterial species were identified pertaining to different demographics such as gender, age, BMI, physical activity, and sleeping habits. Dialysis patients had a significant difference in gut microbiome composition compared to healthy controls. The most abundant genus identified in CKD patients was Bacteroides, and at the species level hemodialysis patients showed significant abundance in B. ovatus, B. caccae, B. uniformis, and peritoneal dialysis patients showed higher abundance in Blautia producta (p ≤ 0.05) than the control group. Pathways pertaining to the production of uremic toxins were enriched in CKD patients. The abundance of the bacterial species depended on the type of dialysis treatment.ConclusionThis study characterizes the healthy gut microbiome of a Taiwanese population in terms of various demographics. In a case-control examination, the results showed the alteration in gut microbiota in CKD patients corresponding to different dialysis treatments. Also, this study identified the bacterial species abundant in CKD patients and their possible role in complicating the patients’ condition.
The Nadir Oxygen-Specific Heart Rate Response in Sleep Apnea Links With the Occurrence of Acute Myocardial Infarction
Authors: Huang Zhihua , Wu Yanpeng , Huang Kaizhuang , Chen Pingyan , Chen Jiyan , Wang Ling 
Published: April 2022

BackgroundLittle is known regarding the quantification of sleep apnea- and hypoxemia-elicited heart rate (HR) response and its prognostic significance of the cardiovascular risk. We sought to explore the impact of HR response and variability specific to obstructive sleep apnea (OSA) on the occurrence of a common cardiovascular event – acute myocardial infarction (AMI).MethodsConsecutive patients with suspected OSA were enrolled and underwent nocturnal respiratory study and electrocardiography monitoring. The minimal oxygen saturation (minSpO2) was determined from the oxygen saturation curve under a subject-specific search window. Primary HR metrics such as maximal HR in response to minSpO2 and respiratory event-specific HR variability were computed from the synchronized recordings. Multivariate regression analyses were conducted to analyze the associations between individualized HR metrics and the occurrence of AMI.ResultsOf 2,748 patients recruited, 39% (n = 1,071) had moderate-to-severe OSA (respiratory event index, REI ≥ 15), and 11.4% (n = 313) patients had AMI. Patients with AMI experienced severe OSA, severe minSpO2, and greater HR reactions. Patients with minSpO2 &lt;90% had an adjusted odds ratio (OR) of 1.48 [95% confidence interval (CI): 1.09–2.00, p = 0.012) for AMI. Notably, minSpO2-induced elevated mean HR response (HRmean &gt; 73 bpm) was significantly associated with AMI (OR 1.72, 95% CI: 1.32–2.23, p &lt; 0.001). Patients with both severe minSpO2 (&lt;90%) and elevated HRmean carried an additive OR of 2.65 (95% CI: 1.74–4.05, p &lt; 0.001) for the risk of AMI after adjustment for potential confounders. A large total power spectrum specific to respiratory events was correlated with an adjusted OR of 0.61 for AMI risk.ConclusionPatients with substantial HR reactions to OSA-induced oxygen nadir and restricted cardiac cycle shifting to respiratory events were likely at increased risk of developing AMI. Detection of nocturnal HR response to hypoxemia may help improve cardiovascular risk stratification.
Development and Comparison of Multimodal Models for Preoperative Prediction of Outcomes After Endovascular Aneurysm Repair
Authors: Wang Yonggang , Zhou Min , Ding Yong , Li Xu , Zhou Zhenyu , Shi Zhenyu , Fu Weiguo 
Published: April 2022

ObjectiveThe aim of this study was to develop and compare multimodal models for predicting outcomes after endovascular abdominal aortic aneurysm repair (EVAR) based on morphological, deep learning (DL), and radiomic features.MethodsWe retrospectively reviewed 979 patients (January 2010—December 2019) with infrarenal abdominal aortic aneurysms (AAAs) who underwent elective EVAR procedures. A total of 486 patients (January 2010–December 2015) were used for morphological feature model development and optimization. Univariable and multivariable analyses were conducted to determine significant morphological features of EVAR-related severe adverse events (SAEs) and to build a morphological feature model based on different machine learning algorithms. Subsequently, to develop the morphological feature model more easily and better compare with other modal models, 340 patients of AAA with intraluminal thrombosis (ILT) were used for automatic segmentation of ILT based on deep convolutional neural networks (DCNNs). Notably, 493 patients (January 2016–December 2019) were used for the development and comparison of multimodal models (optimized morphological feature, DL, and radiomic models). Of note, 80% of patients were classified as the training set and 20% of patients were classified as the test set. The area under the curve (AUC) was used to evaluate the predictive abilities of different modal models.ResultsThe mean age of the patients was 69.9 years, the mean follow-up was 54 months, and 307 (31.4%) patients experienced SAEs. Statistical analysis revealed that short neck, angulated neck, conical neck, ILT, ILT percentage ≥51.6%, luminal calcification, double iliac sign, and common iliac artery index ≥1.255 were associated with SAEs. The morphological feature model based on the support vector machine had a better predictive performance with an AUC of 0.76, an accuracy of 0.76, and an F1 score of 0.82. Our DCNN model achieved a mean intersection over union score of more than 90.78% for the segmentation of ILT and AAA aortic lumen. The multimodal model result showed that the radiomic model based on logistics regression had better predictive performance (AUC 0.93, accuracy 0.86, and F1 score 0.91) than the optimized morphological feature model (AUC 0.62, accuracy 0.69, and F1 score 0.81) and the DL model (AUC 0.82, accuracy 0.85, and F1 score 0.89).ConclusionThe radiomic model has better predictive performance for patient status after EVAR. The morphological feature model and DL model have their own advantages and could also be used to predict outcomes after EVAR.
Novel Compound Heterozygous PKLR Mutation Induced Pyruvate Kinase Deficiency With Persistent Pulmonary Hypertension in a Neonate: A Case Report
Authors: Lin Sha , Hua Xintian , Li Jinrong , Li Yifei 
Published: April 2022

BackgroundPulmonary hypertension could be associated with pyruvate kinase deficiency (PKD). There are few reported cases of PPHN as the first clinical manifestation of PKD. Herein we report a rare case of PKD in which the patient exhibited persistent pulmonary hypertension in the neonate (PPHN), and genetic testing helped to rapidly identify an potential association.Case presentationThe patient was a newborn boy who suffered from severe dyspnea, extreme anemia, skin pallor, and hypoxemia. Repeated echocardiography indicated persistent severe pulmonary hypertension with a calculated pulmonary artery pressure of 75 mmHg, and right ventricular hypertrophy. The administration of nitric oxide significantly reduced the pulmonary artery pressure. Whole-exome sequencing revealed a compound heterozygous mutation consisting of c.707T &gt; G and c.826_827insAGGAGCATGGGG. PolyPhen_2 and MutationTaster indicated that both the c.707T &gt; G (probability 0.999) and c.826_827insAGGAGCATGGGG (probability 0.998) mutations were disease causing. PROVEAN protein batch analysis indicated that the associated p.L236R region was deleterious (score −4.71) and damaging (SIFT prediction 0.00), and this was also the case for p.G275_V276insEEHG (deleterious score −12.00, SIFT prediction 0.00). Substantial structural changes in the transport domain of the protein were predicted using SWISS-MODEL, and indicated that both mutations led to an unstable protein structure. Thus, a novel compound heterozygous mutation of PKLR-induced PKD with PPHN was diagnosed.ConclusionThe current study suggests that molecular genetic screening is useful for identifying PPHN, particularly in children with metabolic disorders. In patients exhibiting unexplained hyperbilirubinemia combined with severe pulmonary hypertension, PKD might be a potential possible alternative explanation. Genetic screening is helpful for identifying genetic causes of pulmonary hypertension, especially in patients with PPHN. This report expands the mutation spectrum of the PKLR gene, and contributes to the genotype-phenotype map of PKD.
Transmission Electron Microscopy Study on the Effect of Thermal and Electrical Stimuli on Ge2Te3 Based Memristor Devices
Authors: Shallcross Austin , Mahalingam Krishnamurthy , Shin Eunsung , Subramanyam Guru , Alam Md Shahanur , Taha Tarek , Ganguli Sabyasachi , Bowers Cynthia , Athey Benson , Hilton Albert , Roy Ajit , Dhall Rohan 
Published: April 2022

Memristor devices fabricated using the chalcogenide Ge2Te3 phase change thin films in a metal-insulator-metal structure are characterized using thermal and electrical stimuli in this study. Once the thermal and electrical stimuli are applied, cross-sectional transmission electron microscopy (TEM) and X-ray energy-dispersive spectroscopy (XEDS) analyses are performed to determine structural and compositional changes in the devices. Electrical measurements on these devices showed a need for increasing compliance current between cycles to initiate switching from low resistance state (LRS) to high resistance state (HRS). The measured resistance in HRS also exhibited a steady decrease with increase in the compliance current. High resolution TEM studies on devices in HRS showed the presence of residual crystalline phase at the top-electrode/dielectric interface, which may explain the observed dependence on compliance current. XEDS study revealed diffusion related processes at dielectric-electrode interface characterized, by the separation of Ge2Te3 into Ge- and Te- enriched interfacial layers. This was also accompanied by spikes in O level at these regions. Furthermore, in-situ heating experiments on as-grown thin films revealed a deleterious effect of Ti adhesive layer, wherein the in-diffusion of Ti leads to further degradation of the dielectric layer. This experimental physics-based study shows that the large HRS/LRS ratio below the current compliance limit of 1 mA and the ability to control the HRS and LRS by varying the compliance current are attractive for memristor and neuromorphic computing applications.
Investigation and Application of Risk Factors of Macrosomia Based on 10,396 Chinese Pregnant Women
Authors: Yuan Xiaosong , Han Xiaoya , Jia Chenbo , Long Wei , Wang Huiyan , Yu Bin , Zhou Jun 
Published: April 2022

ObjectiveThe objective of this study was to examine the association of fetal macrosomia with maternal D-dimer and blood lipid levels, and explore whether D-dimer and blood lipids, either alone or in combination with traditional risk factors at hospital birth, could be used to predict subsequent delivery of macrosomia.MethodsFrom April 2016 to March 2017, 10,396 women with singleton pregnancy giving birth at around 28–41 weeks of gestation were recruited into the present study. D-dimer and blood lipid levels were measured at hospital admission; and data on birth outcomes were obtained from hospital records.ResultsMultivariate logistic regression analysis showed that D-dimer, triglyceride and HDL-C levels were significantly associated with risk of macrosomia independent of traditional risk factors (for D-dimer: adjusted OR: 1.33, 95% CI, 1.23–1.43; for triglyceride: adjusted OR: 1.14, 95% CI, 1.05–1.23; for HDL-C: adjusted OR: 0.35, 95% CI, 0.24–0.51, all P &lt;0.01). More importantly, incorporating D-dimer and blood lipids into the traditional model significantly increased the area under curve (AUC) for prediction of macrosomia (0.783 vs. 0.811; P &lt;0.01).ConclusionOur study demonstrates that maternal D-dimer, triglyceride, and HDL-C levels before hospital birth could be significant and independent of risk factors of fetal macrosomia. Therefore, combining D-dimer and blood lipid levels with traditional risk factors might improve the ability to predict macrosomia in gestational diabetes mellitus and normal pregnancies.
Upper-Extremity Musculoskeletal Disorders and Their Associated Factors Among Diabetes Mellitus Patients Attending at Felege Hiwot Comprehensive Specialized Hospital, Bahir Dar, Northwest Ethiopia: Cross-Sectional Study
Authors: Muluneh Assefa Gebeyehu , Adem Kedir Sany , Dawud Jemal Suleyman , Kibret Alemu Kassaw , Yitayal Melisew Mekie , Eriku Getachew Azeze 
Published: April 2022

BackgroundGlobally, diabetes mellitus (DM) is a major public health, causing functional disability among those affected. Among the common diabetes mellitus-related complications, musculoskeletal disorders had a significant negative impact on the social health quality of life and productivity of individuals. Evidence in this regard, however, is scarce in Ethiopia. Therefore, this study aimed at determining the prevalence of musculoskeletal disorders and identifying factors associated in people with diabetes in Felege Hiwot Comprehensive Specialized Hospital, northwest Ethiopia.MethodsA cross-sectional study design was employed at Felege Hiwot Comprehensive Specialized Hospital from June 01 to August 30, 2020, among 413 participants. A systematic random sampling was employed to select the study participants. A structured, pretested questionnaire was used to collect data on socio-demographic, clinical, and lifestyle characteristics. Musculoskeletal disorders were assessed through clinical and physical examination. A logistic regression model was used to explore factors associated with musculoskeletal disorders.ResultThe prevalence of musculoskeletal disorders among diabetes mellitus patients was 24% (95% CI 20, 28.3). In logistic regression, factors such as being female, older age, occupation (farmer, merchant, and retired), and long duration of diabetes were significantly associated with musculoskeletal disorders.ConclusionNearly one quarter of the study participants had musculoskeletal disorders. Special attention should be given for those individuals living with diabetes mellitus, particularly for those who are female, are older, and had a prolonged history of diabetes mellitus.
Assessing the Potential Prognostic and Immunological Role of TK1 in Prostate Cancer
Authors: Xie Hui , Guo Linpei , Wang Zhun , Peng Shuanghe , Ma Qianwang , Yang Zhao , Shang Zhiqun , Niu Yuanjie 
Published: April 2022

Background: It has been reported that thymidine kinase 1 (TK1) was up-regulated in multiple malignancies and participated in the regulation of tumor malignant behavior. However, its specific role in prostate cancer (PCa) remains unclear.Methods: TK1 expression in PCa patients and cell lines was identified via crossover analysis of the public datasets. A series of in vitro experiments and in vivo models was applied to investigate the function of TK1 in PCa. Functional enrichment analyses were further conducted to explore the underlying mechanism. Additionally, TISIDB was applied to explore the correlation between TK1 expression and tumor-infiltrating lymphocytes, immune subtypes, and immune regulatory factors.Results: TK1 expression was significantly up-regulated in PCa patients and cell lines. TK1 ablation inhibited tumor cell proliferation and migration potential, and in vivo experiments showed that TK1 inactivation can significantly restrain tumor growth. Functional enrichment analysis revealed TK1-related hub genes (AURKB, CCNB2, CDC20, CDCA5, CDK1, CENPA, CENPM, KIF2C, NDC80, NUF2, PLK1, SKA1, SPC25, ZWINT), and found that TK1 was closely involved in the regulation of cell cycle. Moreover, elevated mRNA expression of TK1 was related with higher Gleason score, higher clinical stage, higher pathological stage, higher lymph node stage, shorter overall survival, and DFS in PCa patients. Particularly, TK1 represented attenuated expression in C3 PCa and was related with infiltration of CD4+, CD8+ T cells, and dendritic cells as well as immunomodulator expression.Conclusion: Our study indicates that TK1 is a prognostic predictor correlated with poor outcomes of PCa patients, and for the first time represented that TK1 can promote the progression of PCa. Therefore, TK1 may be a potential diagnostic and prognostic biomarker, as well as a therapeutic target for PCa.
Anti-POSTN and Anti-TIMP1 Autoantibodies as Diagnostic Markers in Esophageal Squamous Cell Carcinoma
Authors: Xie Weihong , Sun Guiying , Zhu Jicun , Wang Huimin , Han Zhuo , Wang Peng 
Published: April 2022

Esophageal cancer is one of the most commonly diagnosed malignant gastrointestinal tumors. The aim of the study was to explore the diagnostic values of anti-POSTN and anti-TIMP1 autoantibodies in esophageal squamous cell carcinoma (ESCC). Differentially expressed genes (DEGs) associated with esophageal cancer were screened out by the LIMMA method in the Gene Expression Profiling Interactive Analysis (GEPIA) platform. Search Tool for the Retrieval of Interacting Genes (STRING) was used to construct the protein–protein interaction (PPI) based on highly DEGs. The candidate hub genes were the intersection genes calculated based on degree and Maximal Clique Centrality (MCC) algorithms via Cytoscape. A total of 370 participants including 185 ESCC patients and 185 matched normal controls were enrolled in enzyme-linked immunosorbent assay (ELISA) to detect the expression levels of autoantibodies corresponding to POSTN and TIMP1 proteins. A total of 375 DEGs with high expression were obtained in esophageal cancer. A total of 20 hub genes were acquired using the cytoHubba plugin by degree and MCC algorithms. The expression levels of anti-POSTN and anti-TIMP1 autoantibodies were higher in the sera of ESCC patients (p &lt; 0.05). Anti-POSTN autoantibody can diagnose ESCC patients with an AUC of 0.638 at the specificity of 90.27% and sensitivity of 27.57%, and anti-TIMP1 autoantibody can diagnose ESCC patients with an AUC of 0.585 at the specificity of 90.27% and sensitivity of 20.54% (p &lt; 0.05). In addition, anti-POSTN and anti-TIMP1 autoantibodies can distinguish ESCC patients from normal controls in most clinical subgroups (p &lt; 0.05). In conclusion, anti-POSTN and anti-TIMP1 autoantibodies may be considered the potential biomarkers in the clinical diagnosis of ESCC.