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Background: Heavy metal pollution has emerged as a significant concern for human health, prompting increased awareness of its potential adverse effects. While previous research has established a connection between heavy metals and liver function biomarkers, the specific relationship between heavy metals and HBV infection remains unexplored. This cross-sectional study aims to investigate the potential correlations between five blood heavy metals - lead, cadmium, mercury, manganese, and selenium - and the presence of HBsAg, HBsAb, and HBcAb in adults. Methods: The study utilized data from NHANES 2007–2018. Participants were classified into four groups based on their infectious status, and the association between heavy metals and HBV infection was analyzed using multiple logistic regression and stratification analysis. Results: A total of 8431 participants were included, with 5 436 classified as Susceptible, 1 765 as Vaccinated, 865 as Natural Infection, and 103 as Acute/Chronic HBV Infection. The Vaccinated group exhibited a lower mean age (34.52 ± 14.16 years) compared to the other groups. Statistically significant differences in heavy metal concentrations (except selenium) were observed among the groups (P < 0.001). After adjusting for covariates, lead was significantly associated with HBV infection (Q2: OR 2.37, 95%CI 1.04–5.39; Q3: OR 2.34, 95%CI 1.01–5.40), and positive trends were observed for high blood concentrations of mercury (Q4: OR 3.03, 95%CI 1.31–7.04) and manganese (Q4: OR 2.52, 95%CI 1.20–5.28). Furtherly, the presence of lead reduced the protection of HBsAb (Q2: OR 0.84, 95%CI 0.73–0.97; Q3: OR 0.77, 95%CI 0.66–0.90; Q4: OR 0.83, 95%CI 0.70–0.98). Subgroup analysis indicated that cadmium was associated with an increased risk of HBV infection in Asians (OR 1.36, 95%CI 1.03–1.78) and individuals with a BMI range of 25 to 30 (OR 1.60, 95%CI 1.17–2.18). Conclusions: The study's findings suggest a correlation between elevated blood Pb concentrations and reduced immunization rates against hepatitis B. Individuals with a positive HBsAg exhibit lower blood Se concentrations and higher blood Hg and Mn concentrations. [ABSTRACT FROM AUTHOR]

Background: Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported. Methods: We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein–protein interaction analyses. Results: We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9. Conclusions: The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML. [ABSTRACT FROM AUTHOR]

Protein tyrosine kinase (PTK) is one of the major signaling enzymes in the process of cell signal transduction, which catalyzes the transfer of ATP-γ-phosphate to the tyrosine residues of the substrate protein, making it phosphorylation, regulating cell growth, differentiation, death and a series of physiological and biochemical processes. Abnormal expression of PTK usually leads to cell proliferation disorders, and is closely related to tumor invasion, metastasis and tumor angiogenesis. At present, a variety of PTKs have been used as targets in the screening of anti-tumor drugs. Tyrosine kinase inhibitors (TKIs) compete with ATP for the ATP binding site of PTK and reduce tyrosine kinase phosphorylation, thereby inhibiting cancer cell proliferation. TKI has made great progress in the treatment of cancer, but the attendant acquired acquired resistance is still inevitable, restricting the treatment of cancer. In this paper, we summarize the role of PTK in cancer, TKI treatment of tumor pathways and TKI acquired resistance mechanisms, which provide some reference for further research on TKI treatment of tumors. [ABSTRACT FROM AUTHOR]

Background: Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management.Methods: We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF).Results: A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in 'cell cycle' and 'oocyte meiosis' related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients.Conclusions: The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients' prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes. [ABSTRACT FROM AUTHOR]