Evaluation of CYP2C19 Genetic Variant and Its Lack of Association with Valproic Acid Plasma Concentrations Among Zhuang and Han Schizophrenia Patients in Guangxi.

Purpose: To investigate the CYP2C19 genotype distribution and allelic frequency among the Zhuang and Han schizophrenic populations in Guangxi, examine the correlation between CYP2C19 genetic variants and standardized blood levels of Valproic Acid (VPA) in schizophrenic patients, and evaluate the effects of age, gender, and Body Mass Index (BMI) on standardized VPA blood concentrations. Patients and Methods: Between February and December 2022, 192 Zhuang and Han schizophrenia patients treated with VPA were studied. Steady-state VPA concentrations were determined using homogeneous enzyme immunoassays, and CYP2C19 *1, *2, and *3 loci via q-PCR. CYP2C19 genotype distributions between Zhuang and Han groups in Nanning were compared using chi-square tests and contrasted with other ethnicities. Non-parametric tests analyzed VPA variations, identifying critical factors through multivariate stepwise regression. Results: The study identified five CYP2C19 genotypes at the *2 and *3 loci, with the *3/*3 genotype absent in both cohorts. The CYP2C19 distribution in Guangxi Zhuang and Han mirrors, yet diverges significantly from Hui and Kazakh groups. Among 192 subjects, VPA blood levels remained consistent across metabolic types and ages 18-60 but varied significantly by gender. Multivariate analysis revealed gender and BMI as significant factors, overshadowing CYP2C19 genotype and age. Conclusion: In Guangxi, CYP2C19 genetic variants in Zhuang and Han schizophrenia patients demonstrate statistically indistinguishable allelic and metabolic distributions. Gender and BMI can influence standardized VPA blood concentrations in schizophrenia patients. However, in our study cohort, the CYP2C19 genotype and age are not the primary determinants of standardized VPA blood levels.

Near telomere-to-telomere genome of the model plant Physcomitrium patens.

The model plant Physcomitrium patens has played a pivotal role in enhancing our comprehension of plant evolution and development. However, the current genome harbours numerous regions that remain unfinished and erroneous. To address these issues, we generated an assembly using Oxford Nanopore reads and Hi-C mapping. The assembly incorporates telomeric and centromeric regions, thereby establishing it as a near telomere-to-telomere genome except a region in chromosome 1 that is not fully assembled due to its highly repetitive nature. This near telomere-to-telomere genome resolves the chromosome number at 26 and provides a gap-free genome assembly as well as updated gene models to aid future studies using this model organism.

Bacterial Colonization in the Airways and Intestines of Twin and Singleton Preterm Neonates: A Single-Center Study.

Limited studies have investigated the microbial colonization of the airways and intestines in preterm neonates. We studied the composition of intestinal and airway bacterial colonies in several preterm twin pairs and singletons to explore the dominant bacteria, assess their variability, and predict their phenotypic and metabolic functions. In this descriptive study, we collected sputum and fetal stool specimens from 10 twin pairs (20 cases) and 20 singleton preterm neonates. These specimens were analyzed using 16S rRNA deep sequencing to study the alpha and beta diversities and community structures of airway and intestinal bacteria and predict their metabolic functions. Specimens from twins and singleton neonates had distinct aggregations of intestinal and airway bacteria but showed similarities and high microbial diversities during initial colonization. The top five phyla were Proteobacteria, Firmicutes, Actinobacteriota, Bacteroidota, and Cyanobacteria. The top ten genera were Streptococcus, Acinetobacter, Ralstonia, Staphylococcus, Comamonas, Enterococcus, Stenotrophomonas, Dechlorosoma, Sphingopyxis, and Rothia. Potentially pathogenic and highly stress-tolerant Gram-negative bacteria were predominant in the intestinal flora. A considerable proportion of colonies recovered from the airway and intestines of preterm neonates were functional bacteria. The richness of the intestinal and airway flora was not significantly different between twins and singletons, and the flora clustered together. Both intestinal and airway bacteria of twins and singletons were similar. The species involved in initial colonization were similar but different in proportions; therefore, changes in microbial structure and richness may not be attributed to these species.

The heterogeneous driving forces behind carbon emissions change in 30 selective emerging economies.

Emerging economies are predicted to be future emission hotspots due to expected levels of urbanization and industrialization, and their CO2 emissions are receiving more scrutiny. However, the driving forces underlying dynamic change in emissions are poorly understood, despite their crucial role in developing targeted mitigating pathways. We firstly compile energy-related emissions of 30 selective emerging economies from 2010 to 2018. Then, three growth patterns of emissions in these economies have been identified through emission data, which imply different low-carbon pathways. Most emerging economies saw an increase of varying degrees in emissions, driven by economic growth and partly offset by better energy efficiency and improvements in energy mixes. Furthermore, the industrial structure was another factor that slowed emissions, especially in Latin America and the Caribbean. Our research contributes to the heterogeneous exploration of CO2 emissions produced by energy among sectors and the creation of low-carbon development pathways in emerging economies.

A pilot study exploring the association of bronchial bacterial microbiota and recurrent wheezing in infants with atopy.

Background: Differences in bronchial microbiota composition have been found to be associated with asthma; however, it is still unclear whether these findings can be applied to recurrent wheezing in infants especially with aeroallergen sensitization. Objectives: To determine the pathogenesis of atopic wheezing in infants and to identify diagnostic biomarkers, we analyzed the bronchial bacterial microbiota of infants with recurrent wheezing and with or without atopic diseases using a systems biology approach. Methods: Bacterial communities in bronchoalveolar lavage samples from 15 atopic wheezing infants, 15 non-atopic wheezing infants, and 18 foreign body aspiration control infants were characterized using 16S rRNA gene sequencing. The bacterial composition and community-level functions inferred from between-group differences from sequence profiles were analyzed. Results: Both α- and ß-diversity differed significantly between the groups. Compared to non-atopic wheezing infants, atopic wheezing infants showed a significantly higher abundance in two phyla (Deinococcota and unidentified bacteria) and one genus (Haemophilus) and a significantly lower abundance in one phylum (Actinobacteria). The random forest predictive model of 10 genera based on OTU-based features suggested that airway microbiota has diagnostic value for distinguishing atopic wheezing infants from non-atopic wheezing infants. PICRUSt2 based on KEGG hierarchy (level 3) revealed that atopic wheezing-associated differences in predicted bacterial functions included cytoskeleton proteins, glutamatergic synapses, and porphyrin and chlorophyll metabolism pathways. Conclusion: The differential candidate biomarkers identified by microbiome analysis in our work may have reference value for the diagnosis of wheezing in infants with atopy. To confirm that, airway microbiome combined with metabolomics analysis should be further investigated in the future.

Challenges of carbon emission reduction by the workshop education pattern.

The COVID-19 pandemic has forced many conferences and educational events to shift from in-person to online, significantly reducing the carbon footprint associated with these activities. Workshops are a common pattern of thematic learning at the university level, usually involving a series of activities, such as gathering, learning, and dining, for participants from different regions. However, unlike a three-day conference, workshops usually last for seven days or more, resulting in a non-negligible carbon footprint. To resolve this challenge, we have developed a model that provides recommendations for minimizing the carbon footprint of workshops. Using data from the DigitalFUTURES International Workshop on architecture education at Tongji University in China, we calculated the carbon footprint of scenarios with varying workshop durations, participation modes, and transportation methods. Our results show that online workshops can reduce the carbon footprint by up to 88% compared to in-person workshops. Hybrid workshops, which combine online and in-person participation, can also lead to significant carbon reductions, with a 46% online participation rate resulting in an 82% reduction in carbon footprint. However, we recommend that in-person participation be maintained to ensure efficient learning and effective communication. Our work provides a sustainable solution for organizing future workshops with a reduced carbon footprint.

Identification of potential biomarkers for papillary thyroid carcinoma by comprehensive bioinformatics analysis.

To perform bioinformatics analysis on the papillary thyroid carcinoma (PTC) gene chip dataset to explore new biological markers for PTC. The gene expression profiles of GSE3467 and GSE6004 chip data were collected by GEO2R, and the differentially expressed genes (DEGs) were selected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein-protein interaction (PPI) relationship analysis was achieved using STRING, and the hub genes were obtained using the Cytoscape software. GEPIA was used to validate the expressions of the hub genes in the normal and tumor tissues and to conduct survival analyses. Pertinent genetic pathology results were fetched using the HPA database. Finally, the key genes were clinically verified by reverse transcription-polymerase chain reaction. 97 genes were jointly up-regulated and 107 genes were jointly down-regulated in GSE3467 and GSE6004. GO function enrichment analysis revealed that the DEGs were involved in the regulation of calcium ion transport into cytosol, integrin binding, and cell adhesion molecule binding. KEGG pathway enrichment analysis indicated that the DEGs were chiefly associated with thyroid cancer and non-small cell lung cancer. According to the PPI network, 30 key target genes were identified. Only the expressions of ANK2, TLE1, and TCF4 matched between the normal and tumor tissues, and were associated with disease prognosis. When compared with the normal thyroid tissues, the protein and mRNA expressions of ANK2, TLE1, and TCF4 were down-regulated in PTC. Significant differences exist in overall gene expression between the thyroid tissues of patients with PTC and those of healthy people. Furthermore, the differential genes ANK2, TLE1, and TCF4 are expected to be reliable molecular markers for the mechanism study and diagnosis of PTC.

Vision transformer-based weakly supervised histopathological image analysis of primary brain tumors.

Diagnosis of primary brain tumors relies heavily on histopathology. Although various computational pathology methods have been developed for automated diagnosis of primary brain tumors, they usually require neuropathologists' annotation of region of interests or selection of image patches on whole-slide images (WSI). We developed an end-to-end Vision Transformer (ViT) - based deep learning architecture for brain tumor WSI analysis, yielding a highly interpretable deep-learning model, ViT-WSI. Based on the principle of weakly supervised machine learning, ViT-WSI accomplishes the task of major primary brain tumor type and subtype classification. Using a systematic gradient-based attribution analysis procedure, ViT-WSI can discover diagnostic histopathological features for primary brain tumors. Furthermore, we demonstrated that ViT-WSI has high predictive power of inferring the status of three diagnostic glioma molecular markers, IDH1 mutation, p53 mutation, and MGMT methylation, directly from H&E-stained histopathological images, with patient level AUC scores of 0.960, 0.874, and 0.845, respectively.

Sensitivity enhancement of far-detuned RF field sensing based on Rydberg atoms dressed by a near-resonant RF field.

Rydberg-atom electrometers promise traceable standards for RF electrometry by enabling stable and uniform measurement. In this Letter, we propose an approach to increase the sensitivity of the Rydberg-atom electrometer for far-detuned RF field sensing. The key physical mechanism is the addition of a new ingredient-a local RF field near-resonant with a Rydberg transition-so that the far-detuned field can be detected by the shift of an Autler-Townes (AT) splitting peak, which can be dozens of times larger than the AC Stark shift of the electromagnetic induced transparency (EIT) signal without the near-resonant field. The method enables us to measure far-detuned fields with higher sensitivities, including sub-GHz RF fields (even DC electric fields) which are rarely involved in the existing sensitivity enhancement methods.

Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients.

Glioma is the most common and fatal primary brain tumor in humans. A significant role for long non-coding RNA (lncRNA) in glioma is the regulation of gene expression and chromatin recombination, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify necroptosis-related lncRNAs in glioma. In this study, we collected and evaluated the RNA-sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA, https://www.ncbi.nlm.nih.gov/, Data Release 32.0, March 29, 2022) glioma patients, and necroptosis-related lncRNAs were screened. Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were performed to construct a risk score formula to explore the different overall survival between high- and low-risk groups in TCGA. Gene Ontology (GO) and pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG)) were performed to identify the function of screened genes. The immune correlation analysis showed that various immune cells and pathways positively associated with a patient's risk score. Furthermore, the analysis of the tumor microenvironment indicated many immune cells and stromal cells in the tumor microenvironment of glioma patients. Six necroptosis-related lncRNAs were concerned to be involved in survival and adopted to construct the risk score formula. The results showed that patients with high-risk scores held poor survival in TCGA. Compared with current clinical data, the area under the curve (AUC) of different years suggested that the formula had better predictive power. We verified that necroptosis-related lncRNAs play a significant role in the occurrence and development of glioma, and the constructed risk model can reasonably predict the prognosis of glioma. The results of these studies added some valuable guidance to understanding glioma pathogenesis and treatment, and these necroptosis-related lncRNAs may be used as biomarkers and therapeutic targets for glioma prevention.

Pulmonary lymphomatoid granulomatosis in a 4-year-old girl: A case report.

BACKGROUND: Pulmonary lymphomatoid granulomatosis (PLG) is a lymphoproliferative disease associated with Epstein-Barr viral infection occurring mainly in adults and rarely in children. It is characterized by multiple pulmonary nodules. Its diagnosis depends on lung biopsy findings. Most patients are immunodeficient, and it commonly presents in children undergoing chemotherapy for leukemia. We report the case of a child with PLG caused by a mutation in the macrophage-expressed gene 1 (MPEG1), suggesting possible PLG occurrence in children undergoing treatment for pulmonary nodular lesions. CASE SUMMARY: This study reports a case of PLG without apparent immunodeficiency, suggesting the possibility of this disease occurrence during the treatment of pulmonary nodular lesions in children. Initially, the cause was assumed to be an atypical pathogen. Following conventional anti-infective treatment, chest computed tomography findings revealed that there were still multiple nodules in the lungs. Additionally, the patient was found to be infected with the Epstein-Barr virus. Histopathological examination of the resected lung revealed lymphoproliferative lesions with necrosis. Small lymphocytes, plasma cells, and histiocytes were observed in the background, although Reed-Sternberg cells were absent. Immunohistochemical staining [CD20(+), CD30(+), and CD3(+)] and EBV-encoded small RNA1/2 in situ hybridization of small lymphocytes revealed approximately 200 cells/high-power field. Whole exon sequencing of the patient revealed a mutation in the MPEG1. The patient was eventually diagnosed with PLG and transferred to the Department of Pediatric Oncology for bone marrow transplantation. CONCLUSION: As PLG is rare and fatal, it should be suspected in clinical settings when treatment of initial diagnosis is ineffective.

Bacterial composition and colony structure of the lower respiratory tract in infants and children with recurrent wheezing: a case-control study.

BACKGROUND: The bacterial load of the human lower respiratory tract is at least several times lower than that of the other parts of the body. This study aimed to identify the bacterial composition and colony structure of the lower respiratory tract in infants and children with recurrent wheezing compared with those of children with a bronchial foreign body and clarify whether the length of wheezing in infants can contribute to differences in the lower respiratory tract's bacterial colony structure. METHODS: We collected specimens of alveolar lavage fluid from 48 infants and children who underwent fiberoptic bronchoscopy and were divided into groups: A1 (multiple wheezing: wheezing more than three times in < 1 month), A2 (persistent wheezing: > 1 month), and B (bronchial foreign body; control group). We analyzed the bacterial community structure of alveolar lavage fluid using high-throughput sequencing. The richness and diversity of the microbial communities were assessed by α and ß diversity analyses. RESULTS: A total of 6,644 operational taxonomic units (OTUs) were obtained based on the Illumina Nova sequencing platform and clustered according to those that met the 97% identity threshold, followed by species annotation of the OTU sequences. In the annotation results, 2,608 (39.25%) OTUs were annotated at the genus level. At the genus level, Sphingomonas and Phyllobacterium were significantly higher in group A1 than in group B. There were significantly more Phyllobacterium in group A2 than in group B. Prevotella, Neisseria, and Haemophilus were higher in group B than in groups A1 and A2. The differences in the between-group α and ß diversity analyses were statistically significant. The microbial diversity in groups A1 and A2 was significantly less than that in group B, but there was no statistical difference in bacterial community diversity between groups A1 and A2. CONCLUSION: Recurrent wheezing in infants and children is more likely due to alterations in the overall bacterial microecology and disruption of host respiration and immune homeostasis than the effects of a single bacterium.

New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis.

BACKGROUND: Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG. METHODS: Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG. RESULTS: A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells. CONCLUSIONS: HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG.

Effect of Different Adjuvants on Immune Responses Elicited by Protein-Based Subunit Vaccines against SARS-CoV-2 and Its Delta Variant.

The global pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become more serious because of the continuous emergence of variants of concern (VOC), thus calling for the development of broad-spectrum vaccines with greater efficacy. Adjuvants play important roles in enhancing the immunogenicity of protein-based subunit vaccines. In this study, we compared the effect of three adjuvants, including aluminum, nanoparticle manganese and MF59, on the immunogenicity of three protein-based COVID-19 vaccine candidates, including RBD-Fc, RBD and S-trimer. We found that the nanoparticle manganese adjuvant elicited the highest titers of SARS-CoV-2 RBD-specific IgG, IgG1 and IgG2a, as well as neutralizing antibodies against infection by pseudotyped SARS-CoV-2 and its Delta variant. What is more, the nanoparticle manganese adjuvant effectively reduced the viral load of the authentic SARS-CoV-2 and Delta variant in the cell culture supernatants. These results suggest that nanoparticle manganese, known to facilitate cGAS-STING activation, is an optimal adjuvant for protein-based COVID-19 subunit vaccines.

Study on Collision Detection Techniques for the Informed Design of Natural Views in Healthcare Environments.

BACKGROUND: Natural views are an important design strategy for the application of ecological resources in built environments. Numerous clinical studies have indicated that views of nature-for example, plants-can effectively promote patient recovery by relieving their postoperative pains and negative emotions during hospitalization. AIMS: This study demonstrates an intelligent method that develops algorithms of using collision detection techniques in Building Information Modeling to evaluate outdoor plant visibility for patients. METHODS: These algorithms are digitized into a Revit plug-in program, which can be viewed as a design-aided tool for architects with the purpose of informing healthcare environment design in the decision-making process. RESULTS: Its acceptability and effectiveness are evaluated based on the consultations in beta tests. CONCLUSIONS: It is believed that this method can improve the work efficiency of evaluating natural views in wards and help architects implement an informed design of built environments for better health performance. All findings in this study can contribute to the development of computational intelligence and social sustainability in the near future.

Protegrin-1 inhibits porcine ovarian granulosa cell apoptosis from H2O2-induced oxidative stress via the PERK/eIF2α/CHOP signaling pathway in vitro.

In mammals, oxidative stress-induced apoptosis of granulosa cells is one of the major causes of follicular atresia, affecting ovarian physiological function. Protegrin-1 (PG-1) is an antimicrobial peptide with effective antimicrobial activity, immunomodulatory function, and porcine growth-promoting effects. PG-1 has been detected in porcine ovaries follicles. This study aimed to investigate the effect of PG-1 on oxidative stress-induced apoptosis of porcine ovarian granulosa cells and the underlying molecular mechanism. Granulosa cells were obtained from porcine follicles and treated with H2O2 to establish the oxidative stress model, and then treated with or without PG-1 (10 µg/mL). PG-1 significantly suppressed H2O2-induced apoptosis in granulosa cells after 24 h of treatment. Furthermore, these results revealed that PG-1 increased the mRNA and protein expression of anti-apoptotic B cell lymphoma/leukemia 2 (BCL2) and the BCL2/Bcl-2-associated X protein (BAX) ratio while decreasing the expression of pro-apoptotic BAX and active caspase-3. Using Western blot analysis, it was found that PG-1 decreased the phosphorylation of RNA-like endoplasmic reticulum kinase (PERK) and the α-subunit of eukaryotic initiation factor 2 (eIF2α) as well as the protein expression level of CCAAT enhancer-binding protein homologous protein (CHOP), all of which were increased by H2O2. Moreover, inhibitors against PERK and phospho-eIF2ɑ both suppressed the H2O2-induced granulosa cells apoptosis and enhanced the anti-apoptosis effect of PG-1. Taken together, our findings demonstrated that PG-1 inhibited porcine ovarian granulosa cell apoptosis from oxidative stress via the PERK/eIF2α/CHOP signaling pathway in vitro, which suggests the novel regulatory function of the antimicrobial peptide in the ovary.

Hypoxia related long non-coding RNAs in ischemic stroke.

With high rates of mortality and disability, stroke has caused huge social burden, and 85% of which is ischemic stroke. In recent years, it is a progressive discovery of long non-coding RNA (lncRNA) playing an important regulatory role throughout ischemic stroke. Hypoxia, generated from reduction or interruption of cerebral blood flow, leads to changes in lncRNA expression, which then influence disease progression. Therefore, we reviewed studies on expression of hypoxia-related lncRNAs and relevant molecular mechanism in ischemic stroke. Considering that hypoxia-inducible factor (HIF) is a crucial regulator in hypoxic progress, we mainly focus on the HIF-related lncRNA which regulates the expression of HIF or is regulated by HIF, further reveal their pathogenesis and adaption after brain ischemia and hypoxia, so as to find effective biomarker and therapeutic targets.

Three epitope-distinct human antibodies from RenMab mice neutralize SARS-CoV-2 and cooperatively minimize the escape of mutants.

Coronavirus disease 2019 (COVID-19), a pandemic disease caused by the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 3.8 million deaths to date. Neutralizing antibodies are effective therapeutic measures. However, many naturally occurring mutations at the receptor-binding domain (RBD) have emerged, and some of them can evade existing neutralizing antibodies. Here, we utilized RenMab, a novel mouse carrying the entire human antibody variable region, for neutralizing antibody discovery. We obtained several potent RBD-blocking antibodies and categorized them into four distinct groups by epitope mapping. We determined the involved residues of the epitope of three representative antibodies by cryo-electron microscopy (Cryo-EM) studies. Moreover, we performed neutralizing experiments with 50 variant strains with single or combined mutations and found that the mixing of three epitope-distinct antibodies almost eliminated the mutant escape. Our study provides a sound basis for the rational design of fully human antibody cocktails against SARS-CoV-2 and pre-emergent coronaviral threats.

Role of RHOC in evaluating an adverse prognosis in patients with glioma and its potential prognostic value.

In recent years, major discoveries have indicated that Ras homology family member C (RHOC) is involved in the occurrence and pathological progression of a number of malignant tumours; nevertheless, the role served by RHOC in glioma remains unclear. The present study aimed to gain further insight into the biological function and expression of RHOC in human glioma based on the Chinese Glioma Genome Atlas (CGGA). The current study analysed ~1,000 glioma samples from the CGGA. First, RHOC expression was analysed according to the clinical features associated with the prognosis of glioma, such as clinical stage, histological type and age. Second, the Kaplan-Meier method was used, revealing that the survival rate of patients with glioma with high RHOC expression was significantly lower than that of patients with low RHOC expression. Receiver operating characteristic curve analysis indicated that RHOC had moderate diagnostic value for patients with glioma. Gene set enrichment analysis indirectly indicated that RHOC mainly participated in the pathological mechanism of glioma through p53, extracellular matrix receptor interaction and focal adhesion. Finally, the aforementioned results were further verified using The Cancer Genome Atlas data and reverse transcription-quantitative PCR technology. To the best of our knowledge, the present study was the first comprehensive in-depth analysis of RHOC, revealing the potential value of RHOC as a novel oncogene in glioma. The current study provided a novel potential biomarker for the diagnosis and prognosis of glioma, and re-examined the pathological mechanism of glioma from a new perspective.

Effect of DNA methylation on gene transcription is associated with the distribution of methylation sites across the genome in osteoarthritis.

Genetics and epigenetics are important subjects in the field of osteoarthritis (OA) research. DNA methylation may affect gene transcription, but the specific mechanisms have remained to be fully elucidated. In the present study, the ChAMP methylation analysis package was used to identify differentially methylated genes (DMGs) from the dataset GSE63695 from the Gene Expression Omnibus (GEO) database. The distribution of differentially methylated sites (DMS) and the total array sites across the genome were analyzed by enrichment analysis. Subsequently, two mRNA expression profiling datasets, GSE114007 and GSE113825, were obtained from the GEO database and common differentially expressed genes (DEGs) were identified using the Limma package. Key genes were screened by analyzing the distribution of DMS across the genome consisting of DEGs and DMGs. A total of 1,662 and 1,986 DEGs were identified between OA and normal human cartilage from the GSE113825 and GSE114007 dataset, respectively. A further screening revealed 292 genes with common differences between the two datasets. A total of 574 DMS containing 394 DMGs were observed between OA and normal cartilage. Integrative analysis revealed a corresponding subset of 15 genes. Of these, 6 genes were verified by reverse transcription-quantitative PCR, confirming that the mRNA expression of 5 genes (MAP1B, FNDC1, ANLN, SCNN1A and STC2) in OA cartilage was consistent with the mRNA expression from the analysis of the datasets. Upon treatment with the DNA methylation inhibitor 5-aza-2'-deoxycytidine, the mRNA levels of FNDC1 and SCNN1A were decreased, and no significant alteration in the mRNA levels of MAP1B, ANLN, KCNN4 and STC2 was observed. The incidence of differential methylation varied in subregions of the genome and the effects on transcription were associated with the distribution of DEGs across the genome. The regulation of this appears more complex than initially postulated. Combining the data on epigenetic differences of OA with the genome or transcriptome data for analysis may improve the understanding of the pathophysiological processes of OA. FNDC1 and SCNN1A may potentially be valuable biomarkers for OA.