Identification of the OA-related metabolism-related genes, corresponding transcription factors, relevant pathways, and specific bioactive small molecules.

Metabolic alteration of articular cartilage is associated with the pathogenesis of Osteoarthritis (OA). This study aims to identify the metabolism-related genes, corresponding transcription factors (TFs), and relevant pathways. Overall, RNA sequencing profiles of articular cartilage were collected from the GEO database. Metabolism-related genes and OA-related hallmarks were collected from the MSigDB v7.1. Differential expression analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Gene Set Variation Analysis (GSVA) were conducted to identify pathways or hallmarks that were related to the pathogenesis of OA. The Pearson correlation analysis was used to establish the regulatory network among transcription factors, metabolism-related genes, and hallmarks. To further confirm the regulation of the identified transcription factors, Chromatin Immunoprecipitation-sequencing (ChIP-seq) was conducted, and single-cell sequencing was used to locate the cell clusters. Connectivity Map (CM) analysis were also conducted to identify the potential specific bioactive small molecules targeting the metabolic alteration of osteoarthritis. scTPA database was used to detect activated signaling pathways. Collectively, a total of 74 and 38 differentially expressed metabolism-related genes and TFs were retrieved. Skeletal system development, extracellular matrix, and cell adhesion molecule binding were important pathways in GO analysis. Human papillomavirus infection, PI3K-Akt signaling pathway, and Human T-cell leukemia virus 1 infection were the top 3 pathways in KEGG. 7 and 12 hallmarks were down- and up-regulated in GSVA, respectively. Ten bioactive small molecules may be potential treatments of OA by regulating the metabolism of articular cartilage. ChIP-seq analysis showed high relativity between transcription factors and their target genes. Furthermore, single-cell sequencing confirms the high expression of identified transcription factors in chondrocytes. To conclude, we established a comprehensive network integrated with transcription factors, metabolism-related genes, and hallmarks.

Establishment of a predictive model for purulent meningitis in preterm infants.

Background: Purulent meningitis (PM) is an important cause of mortality and morbidity in the newborn population throughout the world. The subtle of specific clinical signs and low success rates of lumbar puncture make diagnosis of PM more difficult in preterm than in older children. The objective of this study was to establish a predict model for preterm PM in hopes of helping clinicians develop new diagnostic and treatment strategies. Methods: Premature infants who were admitted to The First Affiliated Hospital of Zhengzhou University from September 2017 to March 2020 were enrolled in this study. All the patients underwent lumbar puncture. We collected data encompassing maternal diseases and neonatal clinical features. Cerebrospinal fluid (CSF) culture is the gold standard for diagnosing meningitis. The PM was diagnosed according to the diagnostic criteria. All statistical analyses were performed using R 3.63 (https://www.r-project.org/). Logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model of PM. The Brier score, calibration slope, and concordance (C)-index were used to verify the accuracy of prediction model. Results: A total of 168 preterm infants were enrolled in this study, 80 boys and 88 girls, the gestational age (GA) was 26.43-36.86 weeks (32.45±2.79 weeks), the birth weight (BW) was 700-3,400 g (1,814.05±568.84 g). There were 77 preterm infants with PM while 91 without. We identified seven variables as independent risk factors for PM in preterm infants by LASSO analysis [the optimal λ was 0.080960, and log(λ) = -2.5138], including procalcitonin (PCT) on the 1st day after birth, prenatal glucocorticoid use, albumin, the 1-minute Apgar score, the use of non-invasive biphasic positive airway pressure, hemoglobin, and sex. These were used to construct a risk prediction nomogram and verified its accuracy. The Brier score was 0.17, the calibration slope was 0.966, and the concordance index was 0.82018. Conclusions: Our prediction model could predict the risk of PM in preterm infants. Using this prediction model, it may be able to provide reference to determine whether lumbar puncture is performed and whether antibiotics are applied as soon as possible.

Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network.

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

Development of a Nomogram for Moderate-to-Severe Bronchopulmonary Dysplasia or Death: Role of N-Terminal Pro-brain Natriuretic Peptide as a Biomarker.

Objectives: This study aimed to explore the clinical value of N-terminal pro-brain natriuretic peptide (NT-proBNP) in predicting moderate-to-severe bronchopulmonary dysplasia (BPD)/death, and to establish an effective clinical predictive nomogram. Methods: We retrospectively analyzed very low birth weight infants (VLBWs) with gestational age ≤ 32 weeks. The NT-proBNP values were determined on the 1st, 3rd, 7th, 14th, 21st, and 28th days after birth. The correlation between NT-proBNP level and moderate-to-severe BPD/death was evaluated. Receiver operating characteristic (ROC) curve analysis was used to evaluate the prediction ability. Then, we used multivariable logistic regression to build the prediction model and nomogram, and calibration of the model was assessed by calibration curve. Results: In total, 556 VLBWs were involved, among whom 229 developed BPD (mild: n = 109; moderate: n = 68; severe: n = 52) and 18 died. The NT-proBNP level in the moderate-to-severe BPD/death group was significantly higher than that in the no-to-mild BPD group from the 3rd to 28th day (P < 0.001). When the natural logarithm of the serum NT-ProBNP level increased by 1 unit at day 7 (±2 days) of life, the risk of moderate and severe BPD/death was the highest (OR = 3.753; 95% CI: 2.984~4.720), and ROC analysis identified an optimal cutoff point of 3360 ng/L (sensitivity: 80.0%; specificity: 86.2%; AUC: 0.861). After adjusting for confounding factors, the level of NT-proBNP at day 7 (±2 days) of life still had important predictive value for the development of moderate-to-severe BPD/death, significantly improving the predictive ability of the model. Conclusion: The level of NT-proBNP at day 7 (±2 days) of life can be used as an early promising biomarker for VLBWs to develop moderate-to-severe BPD/death. We constructed an early predictive nomogram to help clinicians identify high-risk populations.

COL3A1 and MMP9 Serve as Potential Diagnostic Biomarkers of Osteoarthritis and Are Associated With Immune Cell Infiltration.

BACKGROUND: Osteoarthritis (OA) is one of the most common age-related degenerative diseases. In recent years, some studies have shown that pathological changes in the synovial membrane occur earlier than those in the cartilage in OA. However, the molecular mechanism of synovitis in the pathological process of OA has not been elucidated. This study aimed to identify novel biomarkers associated with OA and to emphasize the role of immune cells in the pathogenesis of OA. METHODS: Microarray datasets were obtained from the Gene Expression Omnibus (GEO) and ArrayExpress databases and were then analyzed using R software. To determine differential immune cell subtype infiltration, the CIBERSORT deconvolution algorithm was used. Quantitative reverse transcription PCR (qRT-PCR) was used to determine the relative expressions of selected genes. Besides, Western blotting was used to assess the protein expression levels in osteoarthritic chondrocytes. RESULTS: After analyzing the database profiles, two potential biomarkers, collagen type 3 alpha 1 chain (COL3A1), and matrix metalloproteinase 9 (MMP9), associated with OA were discovered, which were confirmed by qRT-PCR and Western blotting. Specifically, the results revealed that, as the concentration of IL-1ß increased, so did the gene and protein expression levels of COL3A1 and MMP9. CONCLUSION: The findings provide valuable information and direction for future research into novel targets for OA immunotherapy and diagnosis and aids in the discovery of the underlying biological mechanisms of OA pathogenesis.

A Good Way to Reduce Screening for Retinopathy of Prematurity: Development of the ROP Model in a China Preterm Population.

Importance: Retinopathy of prematurity (ROP) is a preventable cause of blindness in children. Without treatment, more than 45% of eyes may suffer permanent vision loss. Current ROP screening guidelines, which include a range of birth weights (BWs) and gestational ages (GAs), may require screening many low-risk preemies who might develop severe ROP. Method: All high-risk infants in the neonatal intensive care unit (NICU) of the First Affiliated Hospital of Zhengzhou University from 2017 to 2021 were included in this retrospective cohort study. Each of the 27 candidate risk factors was evaluated in univariate analysis and adjusted for known risk factors (i.e., GA and BW). The significant results were analyzed in a backward selection multivariate logistic regression model. Receiver operating characteristic (ROC) curves and a nomogram were drawn. Results: The study included 2,040 infants who underwent ROP screening. The weight gain rate [OR, 2.65; 95% confidence interval (CI), 1.49-1.21 ≤ 12 g/d vs. > 18 g/d; P = 0.001], blood transfusion (OR, 2.03; 95% CI, 1.14-3.64; P = 0.017), invasive mechanical ventilation (OR, 1.74; 95% CI, 1.15-2.66; P = 0.009) and N-terminal segment of pro-B-type natriuretic peptide (NT-proBNP) ≥ 25,000 ng/L (OR, 1.51; 95% CI, 1.00-2.28; P = 0.048) were four new statistically independent risk factors in addition to GA and BW. The area under the curve (AUC) of the final multivariate model was 0.90 (95% CI, 0.88-0.92; P < 0.001). Conclusions and Relevance: These findings add to our understanding of ROP screening because they include all eligible infants rather than only high-risk infants, as in previous studies. Under the control of BW and GA, low weight gain rate, increased number of blood transfusion, invasive mechanical ventilation and NT-proBNP ≥ 25,000 ng/L were "new" statistically independent risk factors for ROP. The ROP risk can be calculated manually or represented by a nomogram for clinical use.

Increased risk of intracranial hemorrhage in preterm infants with OPRM1 gene A118G polymorphism.

BACKGROUND: To investigate the relationship between the OPRM1 gene A118G polymorphism and intracranial hemorrhage (ICH) in premature infants and identify the relevant genes in disease occurrence. METHODS: In the present case study analysis, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to detect the genotype and allele frequencies of the OPRM1 gene All8G single nucleotide polymorphism (SNP) in a case group of premature infants with ICH (n=167) and a control group of premature infants (n=163) without ICH. RESULTS: In the case group, 73 (43.7%) wild type A118 homozygous (A/A), 82 (49.1%) mutant heterozygous (A/G), and 12 (7.2%) mutant G118 homozygous (G/G) individuals were observed. The frequencies of A and G alleles were 68.3% and 31.7% respectively. In the control group, 89 (54.6%) wild type A118 homozygous (A/A), 68 (41.7%) mutant heterozygous (A/G), and 6 (3.7%) mutant G118 homozygous (G/G) individuals were observed. The frequencies of A and G alleles were 75.5% and 24.5% respectively. There was no significant difference in the frequency distribution of the OPRM1 gene A118G polymorphism between the two groups (χ2=4.839, P=0.089). There was a significant difference in the positive rate of wild-type AA and mutant-type (A/G + G/G) between the two groups (χ2=3.913, P=0.048). Carrying the G allele of the individual was 1.5 times more frequent suffering from the risk of ICH than carrying the A allele [odds ratio (OR): 1.549; 95% confidence interval (CI): 1.003-2.391], indicating that the OPRM1 118G allele was positively correlated with ICH and can increase the risk of ICH occurrence. CONCLUSIONS: The OPRM1 gene A118G polymorphism is associated with ICH in premature infants. The OPRM1 gene A118G may play a critical role in the occurrence of ICH.

Anthropometric indices as surrogates for estimating abdominal visceral and subcutaneous adipose tissue: A meta-analysis with 16,129 participants.

AIM: To seek anthropometric indices that estimate visceral and subcutaneous adipose tissue (VAT and SAT) by meta-analysis and comparing the predictive efficacy based on different characteristics of participants. METHODS: PubMed, PubMed Central, Web of Science, China National Knowledge Infrastructure and Wanfang databases were searched for publications containing correlation coefficients of VAT and/or SAT with waist circumference (WC) and/or body mass index (BMI). The overall or subgroup pooled results were analyzed by meta and metafor packages of R with random effects model. MedCalc software was used to compare the correlation coefficients between groups. RESULTS: Twenty-nine publications were included in this meta-analysis. The correlation coefficients of VAT-WC, VAT-BMI, SAT-WC and SAT-BMI for total studies were between 0.640 and 0.785. The correlation of VAT with WC was larger than that with BMI (Z = 11.664, P < 0.001). Meanwhile, the correlation coefficients of VAT-WC were statistically different among different age groups, areas, ethnicities, body shapes, scanning levels, units and instruments of measuring VAT (P < 0.05). The overall correlation of SAT with BMI was larger than that with WC (Z = 3.805, P < 0.001). The subgroups' correlation coefficients of SAT-BMI showed statistical differences between genders, age groups, areas, ethnicities, body shapes, scanning levels, units (cm2 and cm3) and instruments of measuring SAT (P < 0.05). CONCLUSIONS: WC may be a common and simple surrogate for estimating VAT, and BMI for SAT, especially in Europeans, but not in the aged people.