lncRNA LENGA sponges miR-378 to promote myocardial fibrosis in atrial fibrillation.

miR-378 is known to suppress myocardial fibrosis, while its upstream regulators have not been identified. lncRNA LENGA is a recently identified lncRNA in cancer biology. We observed the altered expression of LENGA in atrial fibrillation (AF) patients and predicted its interaction with miR-378. We then explored the interaction between LENGA and miR-378 in AF. Angiotensin-II (Ang-II)-induced human atrial cardiac fibroblasts and human atrial muscle tissues were collected and the expression of LENGA and miR-378 was determined by RT-qPCR. The interaction between LENGA and miR-378 was analyzed through bioinformatics analysis and confirmed by RNA pulldown assay. Cell proliferation and collagen production were analyzed through in vitro assay to analyze the role of LENGA and miR-378 in MF. AF patients showed increased expression of LENGA and deceased expression of miR-378 compared to the sinus rhythm group. LENGA and miR-378 interacted with each other, while they are not closely correlated with each other. Overexpression assay showed that LENGA and miR-378 overexpression failed to affect each other's expression. LENGA promoted collagen production and proliferation of Ang-II-induced atrial fibroblasts, while miR-378 played opposite roles. Moreover, LENGA suppressed the function of miR-378. Therefore, LENGA may sponge miR-378 to promote MF in AF.

Transcriptomic Heterogeneity of Human Mesenchymal Stem Cells Derived from Bone Marrow, Dental Pulp, Adipose Tissue, and Umbilical Cord.

Compared with mesenchymal stem cells (MSCs) obtained from other tissue sources, those derived from umbilical cord (UC) tissue exhibit numerous advantages and vast potential for therapeutic applications. However, MSCs from different tissue sources are heterogeneous, and therefore, the therapeutic efficacy of UC-derived MSCs as a replacement for other tissue-derived MSCs needs to be studied. To better understand the distinctions between UC-derived MSCs and MSCs derived from other tissues, we conducted a transcriptome analysis of MSCs obtained from UC and three other tissues. Correlation analysis revealed the strongest correlation between UC-MSCs (UC-MSCs) and bone marrow-MSCs (BM-MSCs). Compared with UC-MSCs, the lower differentially expressed genes of BM-MSCs, dental pulp-MSCs (DP-MSCs), and adipose tissue-MSCs (AP-MSCs) were predominantly enriched in actin-related terms, while higher differentially expressed genes were predominantly enriched in immunological processes. We also analyzed the distribution of 34 frequently or highly expressed cell characterization molecules in BM-MSCs, DP-MSCs, AP-MSCs, and UC-MSCs. CD200 (FPKM >10) was only detected in UC-MSCs, while CD106 was detected in AD-MSCs and DP-MSCs (FPKM >10). The reliability of transcriptomic data analysis was verified by quantitative real-time PCR. Finally, we recommend the use of CD200, CD106, and other similar markers with unstable expression as benchmark molecules to monitor the proliferation and differentiation potential of MSCs. This study provides comprehensive insights into the heterogeneity between UC-MSCs and MSCs derived from other tissues, which can guide the therapeutic application of UC-MSCs.

Correlation between Genes of the ceRNA Network and Tumor-Infiltrating Immune Cells and Their Biomarker Screening in Kidney Renal Clear Cell Carcinoma.

This study aimed to using bioinformatics tools, qPCR, and the immunohistochemical analysis to find out factors related to the early diagnosis and prognosis of kidney renal clear cell carcinoma (KIRC). The expression profiles of lncRNA, miRNA, and mRNA of KIRC were downloaded from The Cancer Genome Atlas database. A ceRNA regulatory network was constructed based on the interaction between these three differentially expressed genes. The CIBERSORT deconvolution algorithm was used to analyze the differential distribution of 22 types of immune cells. The Kaplan-Meier survival and Cox analyses were used to screen genes of the ceRNA network and also immune cell subtypes related to the clinical and prognostic prediction of KIRC. Co-expression regulatory relationships were found among LINC01426, LINC00894, CCNA2, L1 cell adhesion molecule (L1CAM), and T follicular helper cells, which served as potential biomarkers. The results of quantitative reverse transcriptase-polymerase chain reaction showed that LINC01426 was upregulated while L1CAM was downregulated in KIRC, but no difference was found in the expression levels of LINC00894 and CCNA2 in cancer and adjacent samples. The immunohistochemical analysis showed that T follicular helper cells were more concentrated in core tissues and metastases of KIRC. In a word, co-expression relationships were found among LINC01426, L1CAM, and T follicular helper cells, and they may serve as biomarkers for early diagnosis and prognostic evaluation of KIRC.

A Correlation Between Pericarpium Citri Reticulatae Volatile Components and the Change of the Coexisting Microbial Population Structure Caused by Environmental Factors During Aging.

Pericarpium Citri Reticulatae (PCR) is a natural citrus by-product with beneficial health and nutritive properties that is used widely in food and is an ingredient in traditional Chinese medicine. PCR improves gradually with aging. However, the present research has not yet revealed the reasons for this. Some data prove the important role of microorganisms in the quality of tobacco and fermented tea with the time of the aging of these foods. Our studies further proved that the coexisting Aspergillus niger plays an important role in the change of flavonoids and volatile oil in PCR during this process. Therefore, we put forward that longer storage is better for PCR and is highly correlated with the change of the coexisting microbial population structure caused by environmental factors. Samples of PCR aged in Beijing, Sichuan, Guangdong, and Yunnan were collected at different time points. Using GC/MS and high throughput 16S rDNA and ITS sequencing techniques, massive changes in volatile profile and microbial communities were observed during aging. Spearman correlation analysis indicated that Exobasidium, Xeromyces, Pseudocercospora, Russula, Aspergillus, Herbaspirillum, Sphingomonas, and Streptococcus, which are the dominant microbial genera in Sichuan and Guangdong showed strong connections with volatile components of chemical markers. It was preliminarily verified that the changes of volatile components for PCR are highly correlated with the change of the coexisting microbial population structure caused by environmental factors, providing a new idea for the research on the aging mechanism of PCR and key influencing factors of aging quality.

Understanding and predicting the functional consequences of missense mutations in BRCA1 and BRCA2.

BRCA1 and BRCA2 are tumour suppressor genes that play a critical role in maintaining genomic stability via the DNA repair mechanism. DNA repair defects caused by BRCA1 and BRCA2 missense variants increase the risk of developing breast and ovarian cancers. Accurate identification of these variants becomes clinically relevant, as means to guide personalized patient management and early detection. Next-generation sequencing efforts have significantly increased data availability but also the discovery of variants of uncertain significance that need interpretation. Experimental approaches used to measure the molecular consequences of these variants, however, are usually costly and time-consuming. Therefore, computational tools have emerged as faster alternatives for assisting in the interpretation of the clinical significance of newly discovered variants. To better understand and predict variant pathogenicity in BRCA1 and BRCA2, various machine learning algorithms have been proposed, however presented limited performance. Here we present BRCA1 and BRCA2 gene-specific models and a generic model for quantifying the functional impacts of single-point missense variants in these genes. Across tenfold cross-validation, our final models achieved a Matthew's Correlation Coefficient (MCC) of up to 0.98 and comparable performance of up to 0.89 across independent, non-redundant blind tests, outperforming alternative approaches. We believe our predictive tool will be a valuable resource for providing insights into understanding and interpreting the functional consequences of missense variants in these genes and as a tool for guiding the interpretation of newly discovered variants and prioritizing mutations for experimental validation.

[Determination and confirmation of cyanuric acid in infant formula using mixed-mode solid-phase extraction cartridge clean up-gas chromatography-mass spectrometry].

A method is presented for the quantitative determination and confirmation of cyanuric acid in infant formula by mixed-mode solid-phase extraction cartridge clean up-gas chromatography-mass spectrometry (GC-MS). Cyanuric acid was extracted from infant formula with an acetic acid solution at 84 degrees C. An aliquot of the supernatant was cleaned up using mixed-mode solid-phase extraction cartridge containing C18 and graphitized carbon black (GCB), and evaporated to dryness under nitrogen. The residues were converted to trimethylsilyl derivatives, then determined by GC-MS in selected ion monitoring (SIM) mode. The linear range was from 0.01 -2 mg/L. The recoveries were 80% - 103% and the relative standard deviations were 7.7% - 14.5% in the spiked range of 0.25 -2.5 mg/kg. The limit of detection was 0.10 mg/kg and the limit of quantification was 0.25 mg/kg. The method is rapid, sensitive, accurate, specific, and rugged. It is suitable for the quantitative determination and confirmation of cyanuric acid in infant formula.