Abstractp53‐Transcriptional‐regulated proteins interact with a large number of other signal transduction pathways in the cell, and a number of positive and negative autoregulatory feedback loops act upon the p53 response. P53 directly controls the POMC/α‐MSH productions induced by ultraviolet (UV) and is associated with UV‐independent pathological pigmentation. When identifying the causative gene of dyschromatosis universalis hereditaria (DUH), we found three mutations encoding amino acid substitutions in the gene SAM and SH3 domain containing 1 (SASH1), and SASH1 was associated with guanine nucleotide‐binding protein subunit‐alpha isoforms short (Gαs). However, the pathological gene and pathological mechanism of DUH remain unknown for about 90 years. We demonstrate that SASH1 is physiologically induced by p53 upon UV stimulation and SASH and p53 is reciprocally induced at physiological and pathophysiological conditions. SASH1 is regulated by a novel p53/POMC/α‐MSH/Gαs/SASH1 cascade to mediate melanogenesis. A novel p53/POMC/Gαs/SASH1 autoregulatory positive feedback loop is regulated by SASH1 mutations to induce pathological hyperpigmentation phenotype. Our study demonstrates that a novel p53/POMC/Gαs/SASH1 autoregulatory positive feedback loop is regulated by SASH1 mutations to induce pathological hyperpigmentation phenotype.
With the objective of investigating the characteristics influencing high-risk sexual behaviours in elderly men (60–74 years of age) in Chongqing, China, a total of 1433 healthy elderly men with sexual intercourse frequencies of one to six times/month who were willing to participate in the questionnaires were studied at four hospitals. We measured serum testosterone levels and performed follow-ups every six months, with a total of 1128 elderly men followed up after two years. We also investigated socio-economic and demographic characteristics (age, education, income, location, marital status and number of marriages), types of sexual partners, age differences with fixed sexual partners, frequency of sexual intercourse, combined basic age-related diseases, sexually transmitted infections (STIs) education, elderly self-care ability and high-risk sexual behaviours (frequency of sexual intercourse and number of sexual partners) using questionnaires. We analysed the influencing factors of high-risk sexual behaviours in elderly men using a univariate analysis, multivariate logistic regression analysis, BP neural network prediction and cluster analysis. Finally, we found that serum total testosterone, age, types of sexual partners, age differences with fixed partners and frequency of sexual intercourse are five factors that influence high-risk sexual behaviours in elderly men.
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