Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer.

Gastric cancer presents a formidable challenge, marked by its debilitating nature and often dire prognosis. Emerging evidence underscores the pivotal role of tumor stem cells in exacerbating treatment resistance and fueling disease recurrence in gastric cancer. Thus, the identification of genes contributing to tumor stemness assumes paramount importance. Employing a comprehensive approach encompassing ssGSEA, WGCNA, and various machine learning algorithms, this study endeavors to delineate tumor stemness key genes (TSKGs). Subsequently, these genes were harnessed to construct a prognostic model, termed the Tumor Stemness Risk Genes Prognostic Model (TSRGPM). Through PCA, Cox regression analysis and ROC curve analysis, the efficacy of Tumor Stemness Risk Scores (TSRS) in stratifying patient risk profiles was underscored, affirming its ability as an independent prognostic indicator. Notably, the TSRS exhibited a significant correlation with lymph node metastasis in gastric cancer. Furthermore, leveraging algorithms such as CIBERSORT to dissect immune infiltration patterns revealed a notable association between TSRS and monocytes and other cell. Subsequent scrutiny of tumor stemness risk genes (TSRGs) culminated in the identification of CDC25A for detailed investigation. Bioinformatics analyses unveil CDC25A's implication in driving the malignant phenotype of tumors, with a discernible impact on cell proliferation and DNA replication in gastric cancer. Noteworthy validation through in vitro experiments corroborated the bioinformatics findings, elucidating the pivotal role of CDC25A expression in modulating tumor stemness in gastric cancer. In summation, the established and validated TSRGPM holds promise in prognostication and delineation of potential therapeutic targets, thus heralding a pivotal stride towards personalized management of this malignancy.

Construction, Characterization, and Application of an Ammonium Transporter (AmtB) Deletion Mutant of the Nitrogen-Fixing Bacterium Kosakonia radicincitans GXGL-4A in Cucumis sativus L. Seedlings.

Nitrogen is an important factor affecting crop yield, but excessive use of chemical nitrogen fertilizer has caused decline in nitrogen utilization and soil and water pollution. Reducing the utilization of chemical nitrogen fertilizers by biological nitrogen fixation (BNF) is feasible for green production of crops. However, there are few reports on how to have more ammonium produced by nitrogen-fixing bacteria (NFB) flow outside the cell. In the present study, the amtB gene encoding an ammonium transporter (AmtB) in the genome of NFB strain Kosakonia radicincitans GXGL-4A was deleted and the △amtB mutant was characterized. The results showed that deletion of the amtB gene had no influence on the growth of bacterial cells. The extracellular ammonium nitrogen (NH4+) content of the △amtB mutant under nitrogen-free culture conditions was significantly higher than that of the wild-type strain GXGL-4A (WT-GXGL-4A), suggesting disruption of NH4+ transport. Meanwhile, the plant growth-promoting effect in cucumber seedlings was visualized after fertilization using cells of the △amtB mutant. NFB fertilization continuously increased the cucumber rhizosphere soil pH. The nitrate nitrogen (NO3-) content in soil in the △amtB treatment group was significantly higher than that in the WT-GXGL-4A treatment group in the short term but there was no difference in soil NH4+ contents between groups. Soil enzymatic activities varied during a 45-day assessment period, indicating that △amtB fertilization influenced soil nitrogen cycling in the cucumber rhizosphere. The results will provide a solid foundation for developing the NFB GXGL-4A into an efficient biofertilizer agent.

Siderophore Synthesis Ability of the Nitrogen-Fixing Bacterium (NFB) GXGL-4A is Regulated at the Transcriptional Level by a Transcriptional Factor (trX) and an Aminomethyltransferase-Encoding Gene (amt).

Kosakonia radicincitans GXGL-4A, a gram-negative nitrogen-fixing (NF) bacterial strain is coated with a thick capsulatus on the surface of cell wall, which becomes a physical barrier for exogenous DNA to enter the cell, so the operation of genetic transformation is difficult. In this study, an optimized Tn5 transposon mutagenesis system was established by using a high osmotic HO-1 medium combined with the electroporation transformation. Eventually, a mutant library containing a total of 1633 Tn5 insertional mutants were established. Of these mutants, the mutants M81 and M107 were found to have an enhanced capability to synthesize siderophore through the CAS agar plate assay and the spectrophotometric determination. The bacterial cells of two mutants were applied in cucumber growth-promoting experiment. Cucumber seedlings treated with M81 and M107 cells had a significant increase in biomass including seedling height, seedling fresh weight, root fresh weight, and root length. The whole genome sequencing of the mutants M81 and M107 showed that the integration sites of Tn5 transposon element were located in MmyB-like helix-turn-helix transcription regulator (locus tag: A3780_19720, trX) and aminomethyltransferase-encoding genes (locus tag: A3780_01680, amt) in the genome of GXGL-4A, respectively. The ability of siderophore synthesis of the target mutants was improved by Tn5 insertion mutagenesis, and the mutants obtained showed a good plant growth-promoting effect when applied to the cucumber seedlings. The results suggest that the identified functional genes regulates the biosynthesis of siderophore in azotobacter GXGL-4A, and the specific mechanism needs to be further investigated.

Modeling and Predicting Pulmonary Tuberculosis Incidence and Its Association with Air Pollution and Meteorological Factors Using an ARIMAX Model: An Ecological Study in Ningbo of China.

The autoregressive integrated moving average with exogenous regressors (ARIMAX) modeling studies of pulmonary tuberculosis (PTB) are still rare. This study aims to explore whether incorporating air pollution and meteorological factors can improve the performance of a time series model in predicting PTB. We collected the monthly incidence of PTB, records of six air pollutants and six meteorological factors in Ningbo of China from January 2015 to December 2019. Then, we constructed the ARIMA, univariate ARIMAX, and multivariate ARIMAX models. The ARIMAX model incorporated ambient factors, while the ARIMA model did not. After prewhitening, the cross-correlation analysis showed that PTB incidence was related to air pollution and meteorological factors with a lag effect. Air pollution and meteorological factors also had a correlation. We found that the multivariate ARIMAX model incorporating both the ozone with 0-month lag and the atmospheric pressure with 11-month lag had the best performance for predicting the incidence of PTB in 2019, with the lowest fitted mean absolute percentage error (MAPE) of 2.9097% and test MAPE of 9.2643%. However, ARIMAX has limited improvement in prediction accuracy compared with the ARIMA model. Our study also suggests the role of protecting the environment and reducing pollutants in controlling PTB and other infectious diseases.

[New compound NL-608 (a nutlin analog) induces apoptosis in human breast cancer MCF-7 cells].

OBJECTIVE: To observe the effect of NL-608 (a nutlin analog) on apoptosis induction in human breast cancer MCF-7 cells in vitro, and investigate the relevant molecular mechanism. METHODS: The effect of NL-608 on proliferation of MCF-7 cells was determined by MTT assay. The apoptosis in MCF-7 cells was determined by flow cytometry with annexin V-FITC and PI. The activity of caspase 3, caspase 8 and caspase 9 was determined with caspase activity assay kit and Western blot, and the proteins of Fas and FasL were determined by Western blot. RESULTS: NL-608 showed a dose-dependent inhibitory effect on the proliferation of MCF-7 cells. It induced apoptosis in MCF-7 cells in a dose-dependent manner. The activity of caspase 3 and caspase 8 in MCF-7 cells was increased with the increasing concentration of NL-608, but caspase 9 had no changes. The proteins of Fas and FasL were increased in a dose-dependent manner. CONCLUSION: NL-608 induces apoptosis in MCF-7 cells in vitro through inducing caspase 3 activity and death receptor-mediated signal pathway.