Endothelin (ET) is a peptide released by vascular endothelial cells. Except for the potent vasoconstrictor function it plays an important physiological role in tissue differentiation and development, cell proliferation and hormone production. Investigation of the role of ET axis in a variety of tumors such as prostatic, cervical, breast carcinoma has provided evidences of its importance in cancer, recently. Data suggest that multiple functions of the ET axis have associations with mitogenesis, apoptosis inhibition, angiogenesis, and activation of proto-oncogene. The ET axis relates to invasiveness, osteoblast function, and metastatic cancer pain in advanced prostate cancer.
Animals ; Apoptosis ; Endothelins ; physiology ; Humans ; Male ; Mice ; Prostatic Neoplasms ; pathology ; physiopathology ; Receptors, Endothelin ; physiology

To investigate the value of renal resistive index (RRI) in early predictor and discriminator of severe acute pancreatitis (SAP)-related acute kidney injury (AKI). Methods A retrospective observational study was conducted. SAP patients complicated with AKI (within 1 week of onset) and admitted to intensive care unit (ICU) of Ruijin Hospital Shanghai Jiaotong University School of Medicine from January 2016 to June 2019 were enrolled. The RRI within 24 hours admission was measured. Clinical data such as acute physiology and chronic health evaluation Ⅱ(APACHEⅡ), heart rate (HR), mean arterial pressure (MAP), central venous pressure (CVP), intra-abdominal pressure (IAP), arterial blood lactate (Lac), oxygenation index (PaO2/FiO2), base excess (BE), serum creatinine (SCr), urine output, norepinephrine (NE) and RRI were collected. Within 24 hours and 7 days after ICU admission, patients were grouped according to AKI classification criteria of Kidney Disease: Improving Global Outcomes (KDIGO), and the differences of relevant parameters were statistically analyzed. Influence factors of AKI grading were screened by Logistic regression analysis. Pearson correlation analysis was used to analyze the correlation between RRI and other parameters. The predictive value of RRI for AKI classification was analyzed by receiver operating characteristic (ROC) curve. Results A total 57 patients were included, with an average age of (54.6±13.5) years old, and APACHEⅡscore of 21.8±5.6. Within 24 hours, the number of patients suffered from stage 1-3 AKI were 19 (33.3%), 18 (31.6%) and 20 (35.1%), respectively. On day 7, the number of patients suffered from stage 0-3 AKI were 21 (36.9%), 8 (14.0%), 9 (15.8%) and 19 (33.3%), respectively. The higher APACHEⅡ score, CVP, IAP, Lac, NE dosage and RRI were found in the group with higher AKI grades, especially in the group with stage 3 AKI on day 7. RRI of patients with stage 3 AKI was significantly higher than that of patients with stage 1 and 2 AKI within 24 hours (0.74±0.04 vs. 0.65±0.05, 0.68±0.05, both P < 0.05). Similarly, RRI of patients with stage 2 and 3 AKI were significantly higher than that of patients with stage 0 and 1 AKI on day 7 (0.70±0.04, 0.74±0.04 vs. 0.65±0.05, 0.66±0.05, all P < 0.05). Multivariate Logistic regression analysis showed that RRI was an independent factor of AKI classification [odds ratio (OR) = 3.15, 95% confidence interval (95%CI) = 1.09-9.04, P < 0.05], and IAP and CVP also had significant impacts on AKI grading [OR value was 2.11 (95%CI = 1.16-4.22), 3.78 (95%CI = 1.21-12.90), both P < 0.05]. ROC curve analysis showed that the area under curve (AUC) of RRI for predicting AKI ≥2 stage was 0.87 (P < 0.05); the cut-off ﹥ 0.71, sensitivity was 71% and specificity was 83%. The correlation analysis showed that RRI was positively correlated to a certain extent with IAP and lactic acid (r1 = 0.49, r2 = 0.39, both P < 0.05). Conclusion High RRI on ICU admission was a significant predictor for development of severe AKI during the first week, and RRI can help predict the tendency of AKI in SAP.

OBJECTIVESTo investigate the pollutant levels of regulated disinfection by-products trihalomethanes (THMs) and haloacetic acids (HAAs) in raw water from the Huangpu River, the Yangtze River and different treatment processes and finished water, and to explore the changes tendency in transmission and distribution pipeline network.

METHODSA total of 65 ml water samples with two replicates were collected from different raw water, corresponding treatment processes, finished water and six national surveillance points in main network of transmission and distribution, water source for A water plant and B, C water plant was the Huangpu River and the Yangtze River, respectively. Regulated THMs and HAAs above water samples were detected by gas chromatography.

RESULTSThe total trihalomethanes (THM(4)) concentration in different treatment processes of A water plant was ND-9.64 µg/L, dichlorobromomethane was the highest (6.43 µg/L). The THM(4) concentration in B and C water plant was ND to 38.06 µg/L, dibromochloromethane (12.24 µg/L) and bromoform (14.07 µg/L) were the highest in the B and the C water plant respectively. In addition to trichloroacetic acid in A water plant from the raw water, the other HAAs came from different treatment processes. The total haloacetic acids (HAA(6)) concentration of different treated processes in A water plant was 3.21 - 22.97 µg/L, mobromoacetic acid (10.40 µg/L) was the highest. Dibromoacetic acid was the highest both in B (8.25 µg/L) and C (8.84 µg/L) water plant, HAA(6) concentration was ND to 27.18 µg/L. The highest and the lowest concentration of THM(4) were found from the main distribution network of C and A water plant respectively, but the concentration of HAA(6) in the main water pipes network of A water plant was the highest, and the lowest in C water plant. The THMs concentration was 21.11 - 31.18 µg/L in C water plant and 6.72 - 8.51 µg/L in A water plant. The concentration of HAA(6) was 25.02 - 37.31 µg/L in A water plant and 18.69 - 23.32 µg/L in C water plant. The highest concentrations of brominated disinfection by-products in B and C water plant were 54.57 µg/L and 45.38 µg/L respectively, those were higher than A water plant (18.98 µg/L), and higher than the chlorinated disinfection by-products in B and C water plants (30.23 µg/L and 30.60 µg/L).

CONCLUSIONSThe THM(4) concentrations of finished water treated from Huangpu River was lower than finished water from the Yangtze River, while the HAAs concentrations in finish water from Huangpu River was higher than the two water plants of Yangtze River. The fluctuations of THMs and HAAs concentration in distribution network were low during transmission and distribution process.

Chromatography, Gas ; Environmental Monitoring ; methods ; Rivers ; chemistry ; Trihalomethanes ; analysis ; chemistry ; Water Pollutants, Chemical ; analysis ; Water Purification ; methods

OBJECTIVETo investigate the function of dendritic cells (DC) of patients with immune related pancytopenia (IRP) and explore the role of DC in IRP.

METHODSThe expression of CD80 and CD86 on myeloid DC (mDC, Lin-HLA-DR(+) CD11c(+) cells) and plasmacytoid DC (pDC, Lin-HLA-DR(+) CD123(+) cells) of 65 IRP (37 untreated and 28 remitted) patients and 17 healthy controls were analyzed by flow cytometry.

RESULTSThe expression of CD86 on pDC was (82.47 ± 13.17)% in untreated group and (60.08 ± 14.29)% in remission group, which were significantly higher than that of controls (47.95 ± 18.59)% (P < 0.05), while the expression in untreated group was higher than that of remission group (P < 0.05). The expression of CD80 on pDC was (6.31 ± 4.49)% in untreated group, which was significantly higher than that of remitted patients (3.09 ± 2.93)% and controls (2.33 ± 2.25)% (P < 0.05). The expression of CD86 on mDC was (97.06 ± 4.82)% in untreated group and (91.35 ± 12.20)% in control group, while the expression in untreated group was higher than that of control group (P < 0.05). The expression of CD80 on mDC was (6.20 ± 5.44)% in untreated group and (3.97 ± 3.24)% in remission group, which were significantly higher than that of controls (1.86 ± 1.73)% (P < 0.05). The expression of CD86 on pDC was negatively correlated to Th1/Th2 (r = -0.733, P < 0.05), it was positively correlated to the antibody on membrane of BMMNC (r = 0.283, P < 0.05) and the quantity of CD5(+)B cells (r = 0.436, P < 0.05), while it was negatively correlated to the level of hemoglobin, platelets and white blood cells (r = -0.539, P < 0.05; r = -0.519, P < 0.05; r = -0.567, P < 0.05, respectively). The expression of CD80 on pDC was negatively correlated to the level of hemoglobin and platelets (r = -0.431, P < 0.05; r = -0.464, P < 0.05).

CONCLUSIONThe function of pDC in PB of IRP were strengthened, which was relevant to the immunopathogenesis of IRP.

Adolescent ; Adult ; Autoimmune Diseases ; complications ; B7-1 Antigen ; metabolism ; B7-2 Antigen ; metabolism ; Case-Control Studies ; Child ; Child, Preschool ; Dendritic Cells ; metabolism ; Female ; Flow Cytometry ; Humans ; Male ; Middle Aged ; Pancytopenia ; blood ; etiology ; pathology ; Young Adult

Autopsy ; Betacoronavirus ; COVID-19 ; Coronavirus Infections ; Humans ; Pandemics ; Pneumonia, Viral ; SARS-CoV-2

Humans ; RNA, Long Noncoding/genetics* ; MicroRNAs/genetics* ; Cell Line, Tumor ; Inflammation/genetics* ; Apolipoproteins E ; Apoptosis

Humans ; Mechanistic Target of Rapamycin Complex 2/metabolism* ; Multiprotein Complexes/metabolism* ; Neural Stem Cells/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; Rapamycin-Insensitive Companion of mTOR Protein/metabolism* ; TOR Serine-Threonine Kinases/metabolism*