Artificial Diet Influences Population Growth of the Root Maggot Bradysia impatiens (Diptera: Sciaridae).

In order to investigate the effects of artificial diets on the population growth of root maggot Bradysia impatiens, its population growth parameters were assayed on eight artificial diets (Diet 1, D2, D3, D4, D5, D6, D7, and D8). Results showed that developmental duration from egg to pupa was successfully completed on all eight artificial diets. However, the egg to pupal duration was shortest, while the survival rate of four insect stages was lowest when B. impatiens was reared on D1. When B. impatiens was reared on D7 and D8, the survival rate, female longevity, and female oviposition were higher than those reared on other diets. When B. impatiens was reared on D7, the intrinsic rate of increase (rm = 0.19/d), net reproductive rate (R0 = 39.88 offspring per individual), and finite rate of increase (λ = 1.21/d) were higher for its population growth with shorter generation time (T = 19.49 d) and doubling time (Dt = 3.67 d). The findings indicate that the D7 artificial diet is more appropriate for the biological parameters of B. impatiens and can be used an indoor breeding food for population expansion as well as further research. We propose that vitamin C supplement added to the D7 is critical for the improvement of the B. impatiens growth.

Development and validation of a novel liquid-liquid phase separation gene signature for bladder cancer.

Bladder carcinoma (BLCA) represents a common urinary tract malignancy, characterized by aggressive behavior and high recurrence rates. The biological response regulation during tumor proliferation and metastasis is intimately associated with liquid-liquid phase separation (LLPS). For the purpose of enhancing early detection and treatment, this study employed transcriptomic data to examine the prognostic implications of LLPS-associated genes and formulate a predictive model. Clinical and transcriptomic data of bladder cancer patients were sourced from the GEO and TCGA databases. This study applied a clustering algorithm using non-negative matrix factorization (NMF) to classify samples, which were systematically compared based on their liquid-liquid phase separation characteristics. Prognostic models were developed using multivariate Cox regression and the Least Absolute Shrinkage Selection Operator (LASSO) algorithm to establish risk formulas for nine genes. The gene signature's validity was tested across the entire TCGA cohort (406 cases), the TCGA testing cohort (120 cases), and the external validation dataset GSE13507. The predictive accuracy of the signature system was assessed using receiver operating characteristic (ROC) and Kaplan-Meier curves. Additionally, decision curve analysis incorporating clinicopathological parameters and the genetic signature was employed to predict individual survival. This study identified two distinct molecular subtypes, C1 and C2. Patients with the C1 subtype exhibited significantly better prognoses than those with the C2 subtype. Low-risk group patients consistently showed superior prognoses compared to high-risk groups across the entire TCGA, GEO, and TCGA training cohorts. Furthermore, the LLPS-related gene model demonstrated prognostic value independent of other clinical traits. This study identifies LLPS-associated gene clusters and establishes an independent, accurate prognostic model for BLCA. The model holds potential for clinical application in BLCA prognosis assessment.

A prognostic model for bladder cancer based on cytoskeleton-related genes.

BACKGROUND: A typical cancerous growth in the urinary tract, bladder cancer (BLCA) has a dismal survival rate and a poor chance of being cured. The cytoskeleton has been shown to be tightly related to tumor invasion and metastasis. Nevertheless, the expression of genes associated with the cytoskeleton and their prognostic significance in BLCA remain unknown. METHODS: In our study, we performed differential expression analysis of cytoskeleton-related genes between BLCA versus normal bladder tissues. According to the outcomes of this analysis of differentially expressed genes, all BLCA cases doing nonnegative matrix decomposition clustering analysis be classified into different molecular subtypes and were subjected to Immune cell infiltration analysis. We then constructed a cytoskeleton-associated gene prediction model for BLCA, and performed risk score independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, enrichment analysis, clinical correlation analysis of prognostic models, and immune cell correlation analysis were carried out. RESULTS: We identified 546 differentially expressed genes that are linked to the cytoskeleton, including 314 up-regulated genes and 232 down-regulated genes. All BLCA cases doing nonnegative matrix decomposition clustering analysis could be classified into 2 molecular subtypes, and we observed differences (P < .05) in C1 and C2 immune scores about 9 cell types. Next, we obtained 129 significantly expressed cytoskeleton-related genes. A final optimized model was constructed consisting of 11 cytoskeleton-related genes. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with BLCA. Survival curves and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Significant enrichment pathways for cytoskeleton-associated genes in bladder cancer samples were explored by Gene set enrichment analysis enrichment analysis. After we obtained the risk scores, a clinical correlation analysis was performed to examine which clinical traits were related to the risk scores. Finally, we demonstrated a correlation between different immune cells. CONCLUSION: Cytoskeleton-related genes have an important predictive value for BLCA, and the prognostic model we constructed may enable personalized treatment of BLCA.

RNA interference of trehalose-6-phosphate synthase and trehalase genes regulates chitin metabolism in two color morphs of Acyrthosiphon pisum Harris.

Trehalose-6-phosphate synthase (TPS) and trehalase (TRE) directly regulate trehalose metabolism and indirectly regulate chitin metabolism in insects. Real-time quantitative PCR (RT-qPCR) and RNA interference (RNAi) were used to detect the expressions and functions of the ApTPS and ApTRE genes. Abnormal phenotypes were found after RNAi of ApTRE in the Acyrthosiphon pisum. The molting deformities were observed in two color morphs, while wing deformities were only observed in the red morphs. The RNAi of ApTPS significantly down-regulated the expression of chitin metabolism-related genes, UDP-N-acetyglucosamine pyrophosphorylase (ApUAP), chitin synthase 2 (Apchs-2), Chitinase 2, 5 (ApCht2, 5), endo-beta-N-acetylglucosaminidase (ApENGase) and chitin deacetylase (ApCDA) genes at 24 h and 48 h; The RNAi of ApTRE significantly down-regulated the expression of ApUAP, ApCht1, 2, 8 and ApCDA at 24 h and 48 h, and up-regulated the expression of glucose-6-phosphate isomerase (ApGPI) and Knickkopf protein (ApKNK) genes at 48 h. The RNAi of ApTRE and ApTPS not only altered the expression of chitin metabolism-related genes but also decreased the content of chitin. These results demonstrated that ApTPS and ApTRE can regulate the chitin metabolism, deepen our understanding of the biological functions, and provide a foundation for better understanding the molecular mechanism of insect metamorphosis.