Corrigendum: Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis.

[This corrects the article DOI: 10.3389/fneur.2022.916966.].

Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study.

PURPOSE: To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. METHODS: A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. RESULTS: Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49-9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34-.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10-.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). CONCLUSION: This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI.

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis.

Background: Stroke is the second leading cause of death worldwide, causing a considerable disease burden. Ischemic stroke is more frequent, but haemorrhagic stroke is responsible for more deaths. The clinical management and treatment are different, and it is advantageous to classify their risk as early as possible for disease prevention. Furthermore, retinal characteristics have been associated with stroke and can be used for stroke risk estimation. This study investigated machine learning approaches to retinal images for risk estimation and classification of ischemic and haemorrhagic stroke. Study design: A case-control study was conducted in the Shenzhen Traditional Chinese Medicine Hospital. According to the computerized tomography scan (CT) or magnetic resonance imaging (MRI) results, stroke patients were classified as either ischemic or hemorrhage stroke. In addition, a control group was formed using non-stroke patients from the hospital and healthy individuals from the community. Baseline demographic and medical information was collected from participants' hospital medical records. Retinal images of both eyes of each participant were taken within 2 weeks of admission. Classification models using a machine-learning approach were developed. A 10-fold cross-validation method was used to validate the results. Results: 711 patients were included, with 145 ischemic stroke patients, 86 haemorrhagic stroke patients, and 480 controls. Based on 10-fold cross-validation, the ischemic stroke risk estimation has a sensitivity and a specificity of 91.0% and 94.8%, respectively. The area under the ROC curve for ischemic stroke is 0.929 (95% CI 0.900 to 0.958). The haemorrhagic stroke risk estimation has a sensitivity and a specificity of 93.0% and 97.1%, respectively. The area under the ROC curve is 0.951 (95% CI 0.918 to 0.983). Conclusion: A fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone.

Construction of a genome instability-derived lncRNA-based risk scoring system for the prognosis of hepatocellular carcinoma.

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, genome instability-associated lncRNAs (GILncRNAs) and their performance in clinical prognostic significance in hepatocellular carcinoma (HCC) are rarely reported. Our study constructed a computational framework integrating somatic mutation information and lncRNA expression profiles of HCC genome and we identified 88 GILncRNAs of HCC. Function enrichment analysis revealed that GILncRNAs were involved in various metabolism processes and genome instability of cancer. A genome instability-derived lncRNA-based gene signature (GILncSig) was constructed using training set data. The performance of GILncSig for outcome prediction was validated in testing set and The Cancer Genome Atlas (TCGA) set. The multivariate cox regression analysis and stratification analysis demonstrated GILncSig could serve as an independent prognostic factor for the overall survival of HCC patients. The time-dependent Receiver Operating Characteristic (ROC) curve illustrated GILncSig outperformed two recently published lncRNA signatures for overall survival prediction. The combination of GILncSig and tumor protein p53 (TP53) mutation status exhibited better prognostic performance in survival evaluation compared to TP53 mutation status alone. AC145343.1 was further validated to be a risk factor for HCC in vitro among GILncSig. Overall, our study provided a novel approach for identification of genome instability-associated lncRNAs and established an independent risk score system for outcome prediction of HCC patients, which provided a new insight for exploring in-depth mechanism and potential therapy strategy.

Estimation of stroke severity with National Institutes of Health Stroke Scale grading and retinal features: A cross-sectional study.

ABSTRACT: To estimate National Institutes of Health Stroke Scale (NIHSS) grading of stroke patients with retinal characteristics.A cross-sectional study was conducted in Shenzhen Traditional Chinese Medicine Hospital. Baseline information and retinal photos were collected within 2 weeks of admission. An NIHSS score was measured for each patient by trained doctors. Patients were classified into 0 to 4 score group and 5 to 42 score group for analysis. Three multivariate logistic models, with traditional clinical characteristics alone, with retinal characteristics alone, and with both, were built.For clinical characteristics, hypertension duration is statistically significantly associated with higher NIHSS score (P = .014). Elevated total homocysteine levels had an OR of 0.456 (P = .029). For retinal characteristics, the fractal dimension of the arteriolar network had an OR of 0.245 (P < .001) for the left eyes, and an OR of 0.417 (P = .009) for right eyes. The bifurcation coefficient of the arteriole of the left eyes had an OR of 2.931 (95% CI 1.573-5.46, P = .001), the nipping of the right eyes had an OR of 0.092 (P = .003) showed statistical significance in the model.The area under receiver-operating characteristic curve increased from 0.673, based on the model with clinical characteristics alone, to 0.896 for the model with retinal characteristics alone and increased to 0.931 for the model with both clinical and retinal characteristics combined.Retinal characteristics provided more information than clinical characteristics in estimating NIHSS grading and can provide us with an objective method for stroke severity estimation.

Bioinformatics Analyses of Potential miRNA-mRNA Regulatory Axis in HBV-related Hepatocellular Carcinoma.

Aims: We aimed to explore the crucial miRNA-mRNA axis through bioinformatics analysis and provide evidences for the development of pathophysiological mechanisms and new therapies for HBV-related HCC. Methods: MiRNA (GSE76903) and mRNA (GSE77509) dataset were used to screen differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs) using R software. Overlapping genes between DE-mRNAs and target genes of DE-miRNAs were identified as candidate genes. Hub genes were obtained via cytohubba analysis. The expression at protein and mRNA levels and prognostic value of hub genes were evaluated based on The Cancer Genome Atlas (TCGA) data. Key miRNA-mRNA axes were constructed according to predicted miRNA-mRNA pairs. MiRNA expression and prognostic role were respectively identified using starBase v3.0 and Kaplan-Meier plotter database. Real-time PCR was performed to verify the expression of crucial miRNAs and mRNAs. Coexpression of crucial miRNA and mRNA were analyzed using starBase v3.0. Results: CDK1, CCNB1, CKS2 and CCNE1 were screened as hub genes, which were significantly upregulated at protein and mRNA levels. These up-regulated hub genes were also significantly associated with poor prognosis. Hsa-mir-195-5p/CDK1, hsa-mir-5589-3p/CCNB1 and hsa-let-7c-3p/CKS2 were screened as critical miRNA-mRNA axes. Critical miRNAs were decreased in HCC, which indicates unfavourable prognosis. QPCR results showed that crucial miRNAs were decreased, whereas critical mRNAs were increased in HBV-related HCC. A reverse relationship between miRNA and mRNA in crucial axis was further verified. Conclusion: This study identified several miRNA-mRNA axes in HBV-related HCC. Hsa-mir-195-5p/CDK1, hsa-mir-5589-3p/CCNB1 and hsa-let-7c-3p/CKS2 might serve as potential prognostic biomarkers and therapeutic targets for HBV-related HCC.

Efficacy of verum and sham acupoint catgut embedding for treatment of obesity: Study protocol for a randomized controlled trial.

BACKGROUND: Obesity has become a major public health hazard with epidemic proportions, affecting adults, adolescents, and children of both genders. Previous studies have suggested that acupoint catgut embedding (ACE) might be a potential therapeutic approach for obesity. The purpose of this study is to conduct a rigorous and normative trial to determine the efficacy of ACE for obesity. METHODS/DESIGN: A total of 99 eligible patients diagnosed with obesity will be recruited in this study. They will be randomly allocated to either the verum ACE group, sham ACE group, or waiting list (WL) group, with 33 patients in each group. Each patient in the two ACE-based groups will receive eight sessions of treatment, lasting over 8 weeks. The primary outcome is the reduction of body mass index (BMI) after treatment. Secondary outcomes will include waist circumference (WC), hip circumference (HC), waist:hip ratio, body fat percentage, blood lipid level, subcutaneous fat area, visceral fat area, and World Health Organization Quality of Life (WHOQOL). All the outcomes will be evaluated at baseline, at the end of the 8 weeks of treatments, and at 3 months of follow-up. The evaluators and data analyzers will be blinded to group allocation. DISCUSSION: The findings of this randomized, sham-, and WL-controlled trial will help to investigate the influence of ACE on clinical variables as well as visceral fat area of obesity, which will provide high-quality evidence on the efficacy of ACE for obesity. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1800020248. Registered on December 21, 2018.

Bioinformatics analysis of hepatic gene expression profiles in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is characterized by hyperglycemia. The liver has a critical role in regulating glucose homeostasis. The present study aimed to analyze hepatic gene expression profiles and to identify the key genes and pathways involved in T2DM. Gene expression profiles of 10 patients with T2DM and 7 subjects with normal glucose tolerance were downloaded from the Gene Expression Omnibus database. Subsequently, differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. In addition, a protein-protein interaction network was built and hub genes were identified. In total, 1,320 DEGs were identified, including 698 up- and 622 downregulated genes, and these were mainly enriched in positive regulation of transcription from RNA polymerase II promoter, cell adhesion, inflammatory response, positive regulation of apoptotic process, signal transduction and the Tolllike receptor signaling pathway. A total of 8 hub genes (G-protein subunit gamma transducin 2, ubiquitinconjugating enzyme E2 D1, glutamate metabotropic receptor 1, G-protein signaling modulator 1, C-X-C motif chemokine ligand 9, neurotensin, purinergic receptor P2Y1 and ring finger protein 41) were screened from the network. The present study may contribute to the elucidation of the hepatic pathology of T2DM.

Identification of key pathways and biomarkers in sorafenib-resistant hepatocellular carcinoma using bioinformatics analysis.

Hepatocellular carcinoma (HCC) is one of the most common malignant types of cancer, with a high mortality rate. Sorafenib is the sole approved oral clinical therapy against advanced HCC. However, individual patients exhibit varying responses to sorafenib and the development of sorafenib resistance has been a new challenge for its clinical efficacy. The current study identified gene biomarkers and key pathways in sorafenib-resistant HCC using bioinformatics analysis. Gene dataset GSE73571 was obtained from the Gene Expression Omnibus (GEO) database, including four sorafenib-acquired resistant and three sorafenib-sensitive HCC phenotypes. Differentially expressed genes (DEGs) were identified using the web tool GEO2R. Functional and pathway enrichment of DEGs were analyzed using the Database for Annotation, Visualization and Integrated Discovery and the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. A total of 1,319 DEGs were selected, which included 593 upregulated and 726 downregulated genes. Functional and pathway enrichment analysis revealed DEGs enriched in negative regulation of endopeptidase activity, cholesterol homeostasis, DNA replication and repair, coagulation cascades, insulin resistance, RNA transport, cell cycle and others. Eight hub genes, including kininogen 1, vascular cell adhesion molecule 1, apolipoprotein C3, alpha 2-HS glycoprotein, erb-b2 receptor tyrosine kinase 2, secreted protein acidic and cysteine rich, vitronectin and vimentin were identified from the PPI network. In conclusion, the present study identified DEGs and key genes in sorafenib-resistant HCC, which further the knowledge of potential mechanisms in the development of sorafenib resistance and may provide potential targets for early diagnosis and new treatments for sorafenib-resistant HCC.

Developmental Toxicity of Diethylnitrosamine in Zebrafish Embryos/Juveniles Related to Excessive Oxidative Stress.

Diethylnitrosamine (DEN) is present in food, water, and daily supplies and is regarded as a toxicant of carcinogenicity. The developmental toxicity of DEN has been rarely reported as yet. In this study, zebrafish were exposed to different concentrations of DEN at 6 h post-fertilization (hpf) to access embryonic toxicity of the compound. The results show that DEN resulted in negative effects of hatching rate, heartbeat, body length, and spontaneous movement. Deformities, including notochord malformation, pericardium edema, embryonic membrane turbidity, tail hypoplasia, yolk sac deformity, and growth retardation, happened during exposure period. Moreover, production of reactive oxygen species (ROS) significantly increased after DEN treatment. Then, alterations of the expression level of oxidative stress-related genes were observed in our results. To our knowledge, this is the first study concerning the effect of DEN on zebrafish. And from the information of our research, we speculated that development toxicity of DEN should be related to the excessive oxidative stress.