Polycystic ovary syndrome (PCOS) is an endocrine disorder with a variety of etiopathogensis and clinic manifestations. Hitherto its pathogenesy is still uncleared. However, there have been increasing supports for the contribution of the hyperinsulinism and hyperandrogenaemia in the pathological process of the PCOS. Recent years, some literatures reported that hyperleptinaemia is also an important factor. This review seeks to bring together the pothogenesy of the PCOS with these factors.

ObjectiveTo explore the relationship between sleep quality and glucose level,diabetic complications in elderly type 2 diabetes mellitus.Methods A total of 130 hospitalized elderly type 2 diabetes in our hospital were included in the study. Questionnaires and other related clinical data were collected within one week after admission.Patients were divided into two groups:poor-sleeper group and good-sleeper group according to Pittsburgh Sleep Quality Index(PSQI).ResultsSixty percent (78/130) of these patients were poor sleepers. The following parameters differed in the two groups:the duration of diabetes [ (7.9 ± 1.8 ) years vs ( 7.2 ± 1.5 ) years,t =2.318 ],systolic blood pressure [ ( 148 ± 30 ) mm Hg ( 1 mm Hg =0.133 kPa) vs ( 138 ± 23 ) mm Hg,t =2.037 ],fasting plasma glucose (FPG) [ ( 10.7 ± 2.2) mmol/Lvs ( 9.8±1.9)mmol/L,t =2.410],hemoglobin A1c (HbA1c) [(8.6 ±2.2)％ vs (7.8±2.1 ) ％,t =2.068],high-sensitive C-reactive protein (hs-CRP) [ (5.27 ± 2.34) mg/L vs (4.44 ± 1.76)mg/L,t =2.179 ],ratio of diabetic complications ( 61％ vs 32％,x2 ＝ 4.257 ),percentage of depression ( 20％ vs 8％,x2 =3.722 ),score of life quality [ ( 98 ± 19 ) scores vs ( 89 ± 13 ) scores,t ＝ 2.980 ],and proportion of patients treated with insulin (32％ vs 12％,x2 =4.489). All the above parameters were significantly higher in poor-sleeper group than the good-sleeper group (all P value＜ 0.05 ). Multiple correlation analysis showed that the factors affecting sleep quality were FPG,HbA1c,duration of diabetes,diabetic complications,depression,life quality and insulin application (r =0.213,0.257,0.223,0.335,0.422,0.3451,0.231,respectively ; all P value ＜ 0.05 ).By multivariate logistic regression analysis,the followings were found:FPG (β =1.29,P ＜ 0.05 ) and PSQI (β =1.07,P ＜ 0.05 ) were found to be correlated with HbA1c.With increasing of PSQI,FPG,HbA1c,diabetic complications and life quality were changed significantly( all P value ＜ 0.05 ).The indcpcndcnt risk factors of diabetic complications were duration of diabetes ( OR ＝ 1.32,95％ CI 1.01-2.01 ),HbA1c ( OR =2.01,95％ CI 1.63-2.67 ),hs-CRP( OR =1.12,95％ CI 1.08-1.21 ) and PSQI ( OR =1.71,95％ CI 1.58-2.02).ConclusionsElderly type 2 diabetes mellitus are usually poor sleepers. Sleep quality probably affects blood glucoseregulation, and is closely correlated with the occurrence of complications.In addition,poor sleep quality results in poor life quality.

Objective To investigate the activation, distribution, origin, and expression of hepatic stem cells(HSC)in different histological types of primary liver carcinomas. Methods The histological and immunohistochemical features of 94 cases of hepatocellular carcinoma (HCC), 12 cases of intrahepatic cholangiocarcinoma (ICC) and 10 cases of mixed hepatocarcinoma were examined by HE staining and immunohistochemistry SP method, with 5 cases of sclerotic liver and 4 cases of normal liver tissues as control. Results HSC expression was observed and the transfor mation from HSC to carcinoma cell was also noted in the liver. CK7, CK19, c-kit, Thy-1, and AFP were found expressed in different types of hepatic carcinomas and the greatest intensive expression was found in the mixed hepatocarcinoma (P

To investigate the mechanism of rapamycin in promoting asthmatic regulatory T cell differentiation . Asthma model was prepared by sensitization and challenge of ovalbumin in mice. Spleen CD4CD25 T cells were sorted from the asthmatic mice and normal mice by ultrahigh speed flow cytometer, and divided into three groups. Transforming growth factor-β and interleukin-2, or combined with rapamycin (final concentration of 500 nmol/L) were given in the model group or the rapamycin group. The levels of Treg cells and CD4CD25 T cells were detected by flow cytometry. The phosphorylation level of downstream proteins of S6 and Akt in the mTORC1/2 signaling pathway were examined by Western blotting. Compared with the model group, the differentiation level of Treg cells in the rapamycin group was significantly increased, the proliferation level of CD4CD25 T cells was decreased, and the phosphorylations of the mTORC1/2 substrates, S6 protein and Akt were decreased （all <0.05）. Rapamycin can promote the differentiation and function of Treg cells via inhibition of the mTORC1/2 signaling pathway.
Animals ; Asthma ; Cell Differentiation ; Mice ; Phosphorylation ; Signal Transduction ; Sirolimus/pharmacology* ; T-Lymphocytes, Regulatory

The global COVID-19 coronavirus pandemic has infected over 109 million people, leading to over 2 million deaths up to date and still lacking of effective drugs for patient treatment. Here, we screened about 1.8 million small molecules against the main protease (M^pro) and papain like protease (PL^pro), two major proteases in severe acute respiratory syndrome-coronavirus 2 genome, and identified 1851M^pro inhibitors and 205 PL^pro inhibitors with low nmol/l activity of the best hits. Among these inhibitors, eight small molecules showed dual inhibition effects on both M^pro and PL^pro, exhibiting potential as better candidates for COVID-19 treatment. The best inhibitors of each protease were tested in antiviral assay, with over 40% of M^pro inhibitors and over 20% of PL^pro inhibitors showing high potency in viral inhibition with low cytotoxicity. The X-ray crystal structure of SARS-CoV-2 M^pro in complex with its potent inhibitor 4a was determined at 1.8 Å resolution. Together with docking assays, our results provide a comprehensive resource for future research on anti-SARS-CoV-2 drug development.
Humans ; Antiviral Agents/chemistry* ; COVID-19 ; COVID-19 Drug Treatment ; High-Throughput Screening Assays ; Molecular Docking Simulation ; Protease Inhibitors/chemistry* ; SARS-CoV-2/enzymology* ; Viral Nonstructural Proteins