Insulin-like growth factor 1 promotes the gonadal development of Pampus argenteus by regulating energy metabolism†.

Insulin-like growth factor 1 (Igf1) is known to promote ovarian maturation by interacting with other hormones. However, the limited research on the role of Igf1 in the energy metabolism supply of gonads has hindered further exploration. To explore the role of Igf1 in gonadal development of silver pomfret, we analyzed the expression levels and the localization of igf1 mRNA and protein during testicular and ovarian development of silver pomfret. The results of the study showed upregulation of Igf1 in the critical period of vitellogenesis and sperm meiosis, which was found to be mainly expressed in the somatic cells of the gonads. Upon adding E2 and Igf1 to cultured gonadal tissues, the expression of energy-related genes was significantly increased, along with the E2-enhanced effect of Igf1 in the testis. Importantly, stimulation of both ovaries and testes with E2 and Igf1 led to a remarkable increase in the expression of vitellogenesis and meiosis-related genes. Therefore, we conclude that Igf1 promotes vitellogenesis and sperm meiosis by regulating gonadal energy production. Moreover, the expression of Igf1 in gonads is significantly regulated by E2. These findings provide new insights for the research of Igf1 in fish breeding, thus allowing the regulation of energy metabolism between growth and reproduction for successful reproductive outcomes.

N6-methylandenosine-related immune genes correlate with prognosis and immune landscapes in gastric cancer.

Objectives: This study aimed to probe into the significance of N6-methyladenosine (m6A)-related immune genes (m6AIGs) in predicting prognoses and immune landscapes of patients with gastric cancer (GC). Methods: The clinical data and transcriptomic matrix of GC patients were acquired from The Cancer Genome Atlas database. The clinically meaningful m6AIGs were acquired by univariate Cox regression analysis. GC patients were stratified into different clusters via consensus clustering analysis and different risk subgroups via m6AIGs prognostic signature. The clinicopathological features and tumor microenvironment (TME) in the different clusters and different risk subgroups were explored. The predictive performance was evaluated using the KM method, ROC curves, and univariate and multivariate regression analyses. Moreover, we fabricated a nomogram based on risk scores and clinical risk characteristics. Biological functional analysis was performed based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The connectivity map was used to screen out potential small molecule drugs for GC patients. Results: A total of 14 prognostic m6AIGs and two clusters based on 14 prognostic m6AIGs were identified. A prognostic signature based on 4 m6AIGs and a nomogram based on independent prognostic factors was constructed and validated. Different clusters and different risk subgroups were significantly correlated with TME scores, the distribution of immune cells, and the expression of immune checkpoint genes. Some malignant and immune biological processes and pathways were correlated with the patients with poor prognosis. Ten small molecular drugs with potential therapeutic effect were screened out. Conclusions: This study revealed the prognostic role and significant values of m6AIGs in GC, which enhanced the understanding of m6AIGs and paved the way for developing predictive biomarkers and therapeutic targets for GC.

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer.

BACKGROUND: Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. METHODS: The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the "limma" R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. RESULTS: An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. CONCLUSION: In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

Scalable fabrication of bimetal modified polyacrylonitrile (PAN) nanofibrous membranes for photocatalytic degradation of dyes.

Fabricating nanostructured fibrous membranes as photocatalyst would facilitate the effective treatment of dyeing effluents. However, creating such photocatalytic nanofibrous membranes has proven tremendously challenging. In this work, we report a scalable strategy to prepare copper-iron bimetal modified polyacrylonitrile (PAN) nanofibrous membranes by electrospinning technology. The resultant PAN membranes exhibit an ultra-fine fiber diameter (600 nm), large surface area (5.34 m2 g-1) and excellent photocatalytic capacity for reactive blue 19, reactive red 195 and acid orange 7 (＞99.99%) within 60 min. The successful synthesis of such intriguing materials could provide a versatile platform for further exploring nano-sized photocatalyst fibrous membranes for degradation of dyes.