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OBJECTIVE The island sign of non-contrast computed tomography (NCCT) is a risk factor for hematoma expansion (HE) after spontaneous intracerebral hemorrhage (sICH), but has inconsistent conclusions. A meta-analysis was performed to investigate the predictive accuracy of island sign for HE. METHODS A systematic review of published literature on island sign and hematoma expansion was conducted. The pooled sensitivity, specificity and summary receiver operating characteristics curve (SROC) were generated. The publication bias was assessed by Deeks’ funnel plot asymmetry test. RESULTS Nine studies with a total of 2,939 patients were included in the present study. The pooled sensitivity and specificity of island sign for predicting hematoma expansion was 0.50 and 0.89, respectively. The area under the curve (AUC) was 0.73 in the SROC curve. There was no significant publication bias. CONCLUSION This meta-analysis suggests that island sign of non-contrast CT has a good predictive accuracy for hematoma enlargement in intracerebral hemorrhage.

Background and Aims: It has recently emerged the concept of “obesity paradox,” a term used to describe an inverse association between obesity and clinical outcomes in cardiovascular diseases and stroke. The purpose of this study was to investigate the association between body mass index (BMI) and the risk of intracranial aneurysm rupture.Methods: In this study, we conducted a retrospective analysis of a prospectively maintained database of patients with intracranial aneurysms from 21 medical centers in China. A total of 3,965 patients with 4,632 saccular intracranial aneurysms were enrolled. Patients were separated into unruptured (n = 1,977) and ruptured groups (n = 1,988). Univariable and multivariable logistic regression analyses were performed to determine the association between BMI and intracranial aneurysm rupture.Results: Compared to the patients with normal BMI (18.5 to < 24.0 kg/m2), the odds of intracranial aneurysm rupture were significantly lower in patients with BMI 24.0 to < 28.0 kg/m2 (OR = 0.745, 95% CI = 0.638–0.868, P = 0.000) and patients with BMI ≥ 28.0 kg/m2 (OR = 0.628, 95% CI = 0.443–0.890, P = 0.009). Low BMI (2) was not associated with intracranial aneurysm rupture (OR = 0.894, 95% CI = 0.483–1.657, P = 0.505). For males, both the BMI 24.0 to < 28.0 kg/m2 (OR = 0.606, 95% CI = 0.469–0.784, P = 0.000) and the BMI ≥ 28.0 kg/m2 (OR = 0.384, 95% CI = 0.224–0.658, P = 0.001) were associated with a lower rupture risk, whereas the inverse association was not observed in females. Both the BMI 24.0 to < 28.0 kg/m2 (OR = 0.722 for aged 50–60y, 95% CI = 0.554–0.938, P = 0.015; OR = 0.737 for aged >60y, 95% CI = 0.586–0.928, P = 0.009) and the BMI ≥ 28.0 kg/m2 (OR = 0.517 for aged 50–60y, 95% CI = 0.281–0.950, P = 0.0034; OR = 0.535 for aged >60y, 95% CI = 0.318–0.899, P = 0.0018) was associated with a lower rupture risk in patients aged ≥50 years, whereas the association was not significant in patients aged Conclusions: Increased BMI is significantly and inversely associated with saccular intracranial aneurysm rupture in males and patients aged ≥50 years.

Background: Ferroptosis plays an important role in glioma and significantly affects the prognosis, but the specific mechanism has not yet been elucidated. Recent studies suggest that autophagy regulates the process of ferroptosis. This study aimed to find potential autophagy-ferroptosis genes and explore the prognostic significance in glioma.Methods: Ferroptosis and autophagy genes were obtained from two online databases (zhounan.org/ferrdb and autophagy.lu/). The RNAseq data and clinical information were obtained from the Chinese Glioma Genome Atlas (CGGA) database (http://www.cgga.org.cn/). Univariate, multivariate, lasso and Cox regression analysis screened out prognosis-related genes, and a risk model was constructed. Receiver operating characteristic (ROC) curve analysis evaluated the predictive efficiency of the model. Finally, a nomogram was constructed to more accurately predict the prognosis of glioma.Results: We developed a Venn diagram showing 23 autophagy-ferroptosis genes. A total of 660 cases (including RNA sequences and complete clinical information) from two different cohorts (training group n = 413, verification group n = 247) of the CGGA database was acquired. Cohorts were screened to include five prognosis-related genes (MTOR, BID, HSPA5, CDKN2A, GABARAPLA2). Kaplan-Meier curves showed that the risk model was a good prognostic indicator (p < 0.001). ROC analysis showed good efficacy of the risk model. Multivariate Cox analysis also revealed that the risk model was suitable for clinical factors related to prognosis, including type of disease (primary, recurrence), grade (III-IV), age, temozolomide treatment, and 1p19q state. Using the five prognosis-related genes and the risk score, we constructed a nomogram assessed by C-index (0.7205) and a calibration plot that could more accurately predict glioma prognosis.Conclusion: Using a current database of autophagy and ferroptosis genes, we confirmed the prognostic significance of autophagy-ferroptosis genes in glioma, and we constructed a prognostic model to help guide treatment for high grade glioma in the future.

Although obstructive sleep apnea (OSA) has been clinically reported to be associated with acute coronary syndrome (ACS), the pathogenesis between the two is unclear. Herein, we analyzed and screened out the prospective molecular marker. To explore the candidate genes, as well as signaling cascades involved in ACS related to OSA, we extracted the integrated differentially expressed genes (DEGs) from the intersection of genes from the Gene Expression Omnibus (GEO) cohorts and text mining, followed by enrichment of the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein–protein interaction (PPI) network and the matching hub gene. A total of 17 and 56 integrated human DEGs in unstable angina (UA) and myocardial infarction (MI) group associated with OSAs that met the criteria of |log2 fold change (FC)|≥ 1, adjusted P

Background Although chronic periodontitis has previously been reported to be linked with Alzheimer's disease (AD), the pathogenesis between the two is unclear. The purpose of this study is to analyze and screen the relevant and promising molecular markers between chronic periodontitis and Alzheimer's disease (AD). Methods In this paper, we analyzed three AD expression datasets and extracted differentially expressed genes (DEGs), then intersected them with chronic periodontitis genes obtained from text mining, and finally obtained integrated DEGs. We followed that by enriching the matching the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein–protein interaction (PPI) network and the matching hub gene. Finally, we verified our data using a different independent AD cohort. Results The chronic periodontitis gene set acquired from text abstracting was intersected with the previously obtained three AD groups, and 12 common genes were obtained. Functional enrichment assessment uncovered 12 cross-genes, which were mainly linked to cell morphogenesis involved in neuron differentiation, leading edge membrane, and receptor ligand activity. After PPI network creation, the ten hub genes linked to AD were retrieved, consisting of SPP1, THY1, CD44, ITGB1, HSPB3, CREB1, SST, UCHL1, CCL5 and BMP7. Finally, the function terms in the new independent dataset were used to verify the previous dataset, and we found 22 GO terms and one pathway, "ECM-receptor interaction pathways", in the overlapping functional terms. Conclusions The establishment of the above-mentioned candidate key genes, as well as the enriched signaling cascades, provides promising molecular markers for chronic periodontitis-related AD, which may help the diagnosis and treatment of AD patients in the future.

Background: Although chronic periodontitis has been confirmed to be related to Alzheimer’s disease, the pathogenesis between the two is unclear. Herein, we analyzed and screened out the prospective molecular marker.Methods: To explore the candidate genes, as well as signaling cascades involved in Alzheimer’s disease and mild cognitive impairment (MCI) related to chronic periodontitis, we extracted the integrated differentially expressed genes (DEGs) from the intersection of genes from the Gene Expression Omnibus (GEO) cohorts and text mining, followed by enrichment of the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein-protein interaction (PPI) network and the matching hub gene.Results: A total of 305 and 100 integrated human DEGs in AD and MCI group associated with chronic periodontitis were uncovered, respectively, that met the criteria of |log2 changes| ≥2, adjusted P Conclusions: The establishment of the above-mentioned candidate key genes, as well as the enriched signaling cascades provides promising molecular marker for chronic periodontitis-related cognitive decline, especially AD, which may help the diagnosis and treatment of AD patients in the future.

Background Considering the high invasiveness and mortality of glioma as well as the unclear key genes and signaling pathways involved in the development of gliomas, there is a strong need to find potential gene biomarkers and available drugs. Methods Eight glioma samples and twelve control samples were analyzed on the GSE31095 datasets, and differentially expressed genes (DEGs) were obtained via the R software. The related glioma genes were further acquired from the text mining. Additionally, Venny program was used to screen out the common genes of the two gene sets and DAVID analysis was used to conduct the corresponding gene ontology analysis and cell signal pathway enrichment. We also constructed the protein interaction network of common genes through STRING, and selected the important modules for further drug-gene analysis. The existing antitumor drugs that targeted these module genes were screened to explore their efficacy in glioma treatment. Results The gene set obtained from text mining was intersected with the previously obtained DEGs, and 128 common genes were obtained. Through the functional enrichment analysis of the identified 128 DEGs, a hub gene module containing 25 genes was obtained. Combined with the functional terms in GSE109857 dataset, some overlap of the enriched function terms are both in GSE31095 and GSE109857. Finally, 4 antitumor drugs were identified through drug-gene interaction analysis. Conclusions In this study, we identified that two potential genes and their corresponding four antitumor agents could be used as targets and drugs for glioma exploration.

Background: Alzheimer disease (AD) is a progressive neurodegenerative disease caused by many factors. The essential genes and signaling pathways involved in the pathogenesis of AD are still unknown. The purpose of our research is to analyze and screen out potential molecular biomarkers and related signaling pathways.Methods: We obtained the gene expression profile of GSE18309 from the gene expression Omnibus website. Then, we used the Limma package in Rstudio to screen out differentially expressed genes (DEGs), followed by the corresponding cell signal pathway enrichment using DAVID analysis. Finally, STRING used to obtain the protein-protein interaction (PPI) network and the corresponding hub gene obtained through MCODE of Cytoscape software.Results: The results showed that a total of 119 upregulated genes and 160 downregulated genes were identified, which met the criteria of |log2 changes| ≥2, adjusted P value Conclusions: In summary, the above-obtained hub gene and the identified signaling pathway will help explore the pathogenesis of AD; and provide new therapeutic targets and prognostic assessment for AD.

The technology of the shaft furnace section in the pellet production has its special technical characteristics, this paper presents an intelligent control system for integrated optimization of production targets in the shaft furnace section. Then we proposed the hardware configuration, network configuration and control functions of the shaft furnace roasting process based on the Siemens Profibus-DP Fieldbus and industrial Ethernet. The WINCC monitor screen is given to reflect the centralized management and decentralized control in the shaft furnace of a steel company.