Objective To investigate the semen variation of the uremia patients after renal transplantation. Methods The semen samples from 10 uremia patients before (group A) and after (group B) renal transplantation and 12 normal volunteers(group C) were analyzed,and the main semen parameters of the 3 groups were compared. Results The mean sperm motilities of groups A,B and C were (13.8? 2.8 )%、(48.3?7.2)% and (63.8?3.6)%,respectively,the vitalities were (24.2?4.1)%、(76.3?3.9)% and (80.4?2.2)%,and the normal sperm morphologies were (15.6?2.3)%、(17.7?1.9)% and (33.8?3.7)%.The sperm motility and vitality of group B were significantly improved than group A(both P 0.05). Conclusions The successful renal transplantation can improve the semen parameters of the uremia patients.

OBJECTIVETo evaluate the changes of the semen quality in uremia patients before renal transplantation.

METHODSThe semen of 24 patients with uremia and 12 normal volunteers was analyzed.

RESULTSThe semen volume, sperm motility, survival rate, density and morphological normality percentage were (2.5 +/- 0.4) ml, (13.4 +/- 3.9)%, (25.4 +/- 5.6)%, (20.6 +/- 4.5) x 10(6)/ml and (16.8 +/- 2.1)%, respectively, significantly lower than those of the normal group (P < 0.01).

CONCLUSIONSemen qualities were lowered significantly and spermatogenesis severely affected in patients with uremia.

Adolescent ; Adult ; Case-Control Studies ; Female ; Humans ; Male ; Middle Aged ; Semen ; physiology ; Sperm Count ; Sperm Motility ; Spermatogenesis ; physiology ; Uremia ; physiopathology

Background Phenolic compounds may adversely affect human health, but the current relevant studies are mostly limited to the impact of single phenolic compound exposure on human health, and there is still a lack of studies on the population-based association between combined exposure to multiple common phenolic compounds and dyslipidemia. Objective To explore the association of phenolic compound combined exposure and dyslipidemia based on principal component analysis-random forest (PCA-RF) strategy. Methods The data were from the National Health and Nutrition Examination Survey (2013–2016). A total of 1301 adult residents aged ≥ 20 years with complete information on demographics and lifestyle, urine phenol concentrations (bisphenol A, bisphenol F, bisphenol S, triclocarban, benzophenone, and triclosan), and serum concentrations of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were included in this study. The concentrations of six urinary phenolic compounds were determined by solid phase extraction coupled with high performance liquid chromatography and tandem mass spectrometry, and the lipid indicators were determined by enzymatic methods. Principal component analysis combined with random forest model was used for model construction. First, principal component analysis was performed on 18 original variables including 6 phenolic compounds and 12 basic characteristic indicators, and then random forest model was established with dyslipidemia and its four evaluation indicators as dependent variables and the extracted principal components as independent variables, respectively. Results The PCA-RF analysis showed that bisphenol A, bisphenol F, and benzophenone may be important factors for dyslipidemia in the study subjects; bisphenol A, bisphenol F, and triclosan may be important factors for TC level in the study subjects; bisphenol A, bisphenol F, triclocarban, and benzophenone may be important factors for TG level in the study subjects; bisphenol A may be an important factor for LDL-C level in the study subjects; bisphenol F and benzophenone may be important factors for HDL-C level in the study subjects. Conclusion Phenolic compound exposure may be an important risk factor for the development of dyslipidemia. PCA-RF strategy can be effectively used to explore the association between phenolic compound exposure and dyslipidemia in the population.