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BackgroundCancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment. The objective of this study was to pinpoint the essential regulatory genes associated with CSCs in prostate adenocarcinoma (PRAD) and assess their potential significance in the diagnosis, prognosis, and immunotherapy of patients with PRAD.MethodThe study utilized single-cell analysis techniques to identify stem cell-related genes and evaluate their significance in relation to patient prognosis and immunotherapy in PRAD through cluster analysis. By utilizing diverse datasets and employing various machine learning methods for clustering, diagnostic models for PRAD were developed and validated. The random forest algorithm pinpointed HSPE1 as the most crucial prognostic gene among the stem cell-related genes. Furthermore, the study delved into the association between HSPE1 and immune infiltration, and employed molecular docking to investigate the relationship between HSPE1 and its associated compounds. Immunofluorescence staining analysis of 60 PRAD tissue samples confirmed the expression of HSPE1 and its correlation with patient prognosis in PRAD.ResultThis study identified 15 crucial stem cell-related genes through single-cell analysis, highlighting their importance in diagnosing, prognosticating, and potentially treating PRAD patients. HSPE1 was specifically linked to PRAD prognosis and response to immunotherapy, with experimental data supporting its upregulation in PRAD and association with poorer prognosis.ConclusionOverall, our findings underscore the significant role of stem cell-related genes in PRAD and unveil HSPE1 as a novel target related to stem cell.

Gastric cancer is a deadly human malignancy and the molecular mechanisms underlying gastric cancer pathophysiology are very complicated. Thus, further investigations are warranted to decipher the underlying molecular mechanisms. With the development of high-throughput screening and bioinformatics, gene expression profiles with large scale have been performed in gastric cancer. In the present study, we mined The Cancer Genome Atlas (TCGA) database and analyzed the gene expression profiles between gastric cancer tissues and normal gastric tissues. A series of differentially expressed lncRNAs, miRNAs and mRNAs between gastric cancer tissues and normal gastric tissues were identified. Based on the differentially expressed genes, we constructed miRNA-mRNA network, lncRNA-mRNA network and transcriptional factors-mRNA-miRNA-lncRNA network. Furthermore, the Kaplan survival analysis showed that high expression levels of EVX1, GBX2, GCM1, HOXC8, HOXC9, HOXC10, HOXC11, HOXC12 and HOXC13 were all significantly correlated with shorter overall survival of the patients with gastric cancer. On the other hand, low expression level of HOXA13 was associated with shorter overall survival of patients with gastric cancer. Among these hub genes, we performed the in vitro functional studies of HOXC8 in the gastric cancer cells. Knockdown of HOXC8 and overexpression of miR-4256 both significantly repressed the gastric cancer cell proliferation and migration, and miR-4256 repressed the expression of HOXC8 via targeting its 3’ untranslated region in gastric cancer cells. Collectively, our results revealed that a complex interaction networks of differentially expressed genes in gastric cancer, and further functional studies indicated that miR-4256/HOXC8 may be an important axis in regulating gastric cancer progression.

Summary: The phenotype-first approach (PFA) and data-driven approach (DDA) have both greatly facilitated anthropological studies and the mapping of trait-associated genes. However, the pros and cons of the two approaches are poorly understood. Here, we systematically evaluated the two approaches and analyzed 14,838 facial traits in 2,379 Han Chinese individuals. Interestingly, the PFA explained more facial variation than the DDA in the top 100 and 1,000 except in the top 10 phenotypes. Accordingly, the ratio of heterogeneous traits extracted from the PFA was much greater, while more homogenous traits were found using the DDA for different sex, age, and BMI groups. Notably, our results demonstrated that the sex factor accounted for 30% of phenotypic variation in all traits extracted. Furthermore, we linked DDA phenotypes to PFA phenotypes with explicit biological explanations. These findings provide new insights into the analysis of multidimensional phenotypes and expand the understanding of phenotyping approaches.

The high consumption and emission of sulfonamide antibiotics (SAs) have a considerable threat to humans and ecosystems, so there is a need to develop safer and more effective methods than conventional strategies for the optimal removal of these compounds. In this study, four SAs with different substituents, sulfadiazine (SDZ), sulfamerazine (SMR), sulfamethoxazole (SMX), and sulfamethazine (SMZ) were removed by a pure culture of Paenarthrobacter ureafaciens YL1. The effect of the initial SAs concentration on the growth rate of strain YL1 was investigated. The results showed that the strain YL1 effectively removed various SAs in the concentration range of 0.05–2.4 mmol·L−1. The Haldane model was used to perform simulations of the experimental data, and the regression coefficient of the model indicated that the model had a good predictive ability. During SAs degradation, the maximum specific growth rate of strain YL1 was ranked as SMX > SDZ > SMR > SMZ with constants of 0.311, 0.304, 0.302, and 0.285 h−1, respectively. In addition, the biodegradation of sulfamethoxazole (SMX) with a five-membered substituent was the fastest, while the six-membered substituent of SMZ was the slowest based on the parameters of the kinetic equation. Also, density functional theory (DFT) calculations such as frontier molecular orbitals (FMOs), and molecular electrostatic potential map analysis were performed. It was evidenced that different substituents in SAs can affect the molecular orbital distribution and their stability, which led to the differences in the growth rate of strain YL1 and the degradation rate of SAs. Furthermore, the toxicity of P. ureafaciens is one of the crucial factors affecting the biodegradation rate: the more toxic the substrate and the degradation product are, the slower the microorganism grows. This study provides a theoretical basis for effective bioremediation using microorganisms in SAs-contaminated environments.

Sulfamethoxazole (SMX) is a widespread and persistent pollutant in the environment. Although the screening and analysis of SMX-degrading bacteria have been documented, the interaction mechanisms of functional microorganisms are still poorly understood. This study constructed a consortium with strain YL1 and YL2 supplied with SMX as the sole carbon and energy source. The coexisting mechanism and the removal of SMX of the consortium were investigated. The total oxidizable carbon (TOC) removal rate of the combined bacterial system was 38.94% compared to 29.45% for the single bacterial system at the same biomass. The mixed bacterial consortium was able to resist SMX at concentrations up to 400 mg/L and maintained a stable microbial structure at different culture conditions. The optimum conditions found for SMX degradation were 30 °C, pH 7.0, a shaking speed of 160 r·min−1, and an initial SMX concentration of 200 mg·L−1. The degradation of SMX was accelerated by the addition of YL2 for its ability to metabolize the key intermediate, 4-aminophenol. The removal rate of 4-aminophenol by strain YL2 reached 19.54% after 5 days. Genome analysis revealed that adding riboflavin and enhancing the reducing capacity might contribute to the degradation of SMX. These results indicated that it is important for the bioremediation of antibiotic-contaminated aquatic systems to understand the metabolism of bacterial communities.

A social health insurance (SHI) program has been established in China to ensure that people can obtain health care economically and equitably. Our analysis indicates that in 2005-06, 66.5 percent of Chinese citizens were non-SHI inpatients. We also found that drug spending for SHI inpatients was significantly higher than that for non-SHI inpatients. After adjusting for other variables, we found that the SHI coverage was also associated positively with higher drug costs. We present evidence to show that drug spending differences are attributable at least in part to differences in insurance courage. [ABSTRACT FROM AUTHOR]