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Background: Ovarian cancer (OV) is regarded as one of the most lethal malignancies affecting the female reproductive system, with individuals diagnosed with OV often facing a dismal prognosis due to resistance to chemotherapy and the presence of an immunosuppressive environment. T cells serve as a crucial mediator for immune surveillance and cancer elimination. This study aims to analyze the mechanism of T cell-associated markers in OV and create a prognostic model for clinical use in enhancing outcomes for OV patients. Methods: Based on the single-cell dataset GSE184880, this study used single-cell data analysis to identify characteristic T cell subsets. Analysis of high dimensional weighted gene co-expression network analysis (hdWGCNA) is utilized to identify crucial gene modules along with their corresponding hub genes. A grand total of 113 predictive models were formed utilizing ten distinct machine learning algorithms along with the combination of the cancer genome atlas (TCGA)-OV dataset and the GSE140082 dataset. The most dependable clinical prognostic model was created utilizing the leave one out cross validation (LOOCV) framework. The validation process for the models was achieved by conducting survival curve analysis and receiver operating characteristic (ROC) analysis. The relationship between risk scores and immune cells was explored through the utilization of the Cibersort algorithm. Additionally, an analysis of drug sensitivity was carried out to anticipate chemotherapy responses across various risk groups. The genes implicated in the model were authenticated utilizing qRT-PCR, cell viability experiments, and EdU assay. Results: This study developed a clinical prognostic model that includes ten risk genes. The results obtained from the training set of the study indicate that patients classified in the low-risk group experience a significant survival advantage compared to those in the high-risk group. The ROC analysis demonstrates that the model holds significant clinical utility. These results were verified using an independent dataset, strengthening the model's precision and dependability. The risk assessment provided by the model also serves as an independent prognostic factor for OV patients. The study also unveiled a noteworthy relationship between the risk scores calculated by the model and various immune cells, suggesting that the model may potentially serve as a valuable tool in forecasting responses to both immune therapy and chemotherapy in ovarian cancer patients. Notably, experimental evidence suggests that PFN1, one of the genes included in the model, is upregulated in human OV cell lines and has the capacity to promote cancer progression in in vitro models. Conclusion: We have created an accurate and dependable clinical prognostic model for OV capable of predicting clinical outcomes and categorizing patients. This model effectively forecasts responses to both immune therapy and chemotherapy. By regulating the immune microenvironment and targeting the key gene PFN1, it may improve the prognosis for high-risk patients.

Abstract L-glutamate is an important component of protein. It can prevent gastrointestinal damage caused by NSAIDs. We constructed two-phase enteric-coated granules of aspirin and L-glutamate compound by extrusion spheronization method and fluidized bed coating. The subliminal effective dose of L-glutamate is 100 mg/kg tested by model of gastric ulcer of rats induced by aspirin and drug administration. HPLC-UV and UV–Vis methods were adopted to determine content and cumulative release of aspirin and L-glutamate as quality analysis method indexes. The prescription and process optimization were carried out with yield, sphericity and dissolution. The two-phase compound granules have good sphericity of 0.93 ± 0.05 (aspirin pellets) and 0.94 ± 0.02 (L-glutamate pellets), content of salicylic acid (0.24 ± 0.03)%, dissolution of aspirin (2.36 ± 0.11)%. Quality evaluation and preliminary stability meet the commercial requirements. The stored environment of compound preparation should be sealed in a cool and dark place.

Chronic myeloid leukemia (CML) is induced by the BCR/ABL1 oncogene, which encodes a protein tyrosine kinase. We examined the effect of direct overexpression of the human p210BCR/ABL1 oncoprotein in zebrafish. Humanized p210BCR/ABL1 protein was detectable in Tg(hsp70: p210BCR/ABL1) transgenic zebrafish embryos and adult kidney marrow. Transgenic zebrafish developed CML, which could be induced via cells transplanted into recipients. The expression of human BCR/ABL1 promoted myeloid lineages in Tg(hsp70:p210BCR/ABL1) transgenic embryos. A total of 77 of 101 (76.24%) Tg(hsp70:p210BCR/ABL1) adult transgenic zebrafish (age 6 months-1 year) developed CML. CML in zebrafish showed a triphasic phenotype, similar to that in humans, involving a chronic phase predominantly characterized by neutrophils in various degrees of maturation, an accelerated phase with an increase in blasts and immature myeloid elements, and a blast phase with >90% blasts in both the peripheral blood and kidney marrow. Tyrosine kinase inhibitors, as the standard drug treatment for human CML, effectively reduced the expanded myeloid population in Tg(hsp70:p210BCR/ABL1) transgenic embryos. Moreover, we screened a library of 171 compounds and identified ten new drugs against BCR/ABL1 kinase-dependent or -independent pathways that could also reduce lcp1+ myeloid cell numbers in Tg(hsp70:p210BCR/ABL1) transgenic embryos. In summary, we generated the first humanized zebrafish CML model that recapitulates many characteristics of human CML. This novel in vivo model will help to elucidate the mechanisms of CML disease progression and allow high-throughput drug screening of possible treatments for this disease.

Benzene exposure is associated with various hematological disorders, in particular leukemia. The reactive metabolite of benzene, 1,4-benzoquinone (BQ), generated in bone marrow, is suggested to be a key molecule in mediating benzene-induced hematotoxicity and carcinogenicity. However, its pathogenic role remains largely unknown due to a lack of suitable vertebrate whole-organism models. Here, we present an in vivo study to reveal the effect of BQ exposure on hematotoxicity in zebrafish. From embryonic stages to adulthood, BQ exposure suppressed erythroid and lymphoid hematopoiesis but led to abnormal accumulation of myeloid cells and precursors, which resembles benzene-induced cytopenia and myeloid dysplasia in humans. This myeloid expansion is caused by granulocyte, but not macrophage, lineage, emphasizing the significant role of lineage specificity in BQ-mediated hematopoietic toxicity. Analysis of the c-myb (also known as myb)-deficient mutant cmybhkz3 revealed that BQ induced neutrophilia in a c-myb-dependent manner, demonstrating that c-myb is a key intrinsic mediator of BQ hematotoxicity. Our study reveals that BQ causes lineage-specific hematotoxicity in zebrafish from embryonic stages to adulthood. Since c-myb is indispensable for BQ to induce neutrophilia, c-myb could serve as a potential drug target for reversing BQ hematotoxicity.