Inflammatory Marker but Not Adipokine Predicts Mortality among Long-Term Hemodialysis Patients

Aims: chronic inflammation contributes significantly to the morbidity and mortality of chronic hemodialysis patients. A recent research has shown that adipokines were associated with inflammation in these patients. We aim to investigate whether biomarkers of inflammation, adipokines, and clinical features can predict the outcome of hemodialysis patients. Materials and methods: we enrolled 181 hemodialysis patients (men: 97, mean age: 56.3±13.6) and analyzed predictors of long-term outcomes. Results: during the 3-year followup period, 41 patients died; the main causes of death were infection and cardiovascular disease. Elevated serum levels of hsCRP and albumin and advanced age were highly associated with death (all P<.001). Leptin and adiponectin levels were not significantly different between deceased patients and survivors. Cox-regression analysis indicated that age, diabetes, albumin level, and hsCRP were independent factors predicting mortality. Conclusion: the presence of underlying disease, advanced age, and markers of chronic inflammation is strongly related to survival rate in long-term hemodialysis patients

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Measurement of Visceral Fat: Should We Include Retroperitoneal Fat?

<div><p>Objective</p><p>Whether retroperitoneal fat should be included in the measurement of visceral fat remains controversial. We compared the relationships of fat areas in peritoneal, retroperitoneal, and subcutaneous compartments to metabolic syndrome, adipokines, and incident hypertension and diabetes.</p><p>Methods</p><p>We enrolled 432 adult participants (153 men and 279 women) in a community-based cohort study. Computed tomography at the umbilicus level was used to measure the fat areas.</p><p>Results</p><p>Retroperitoneal fat correlated significantly with metabolic syndrome (adjusted odds ratio (OR), 5.651, p<0.05) and the number of metabolic abnormalities (p<0.05). Retroperitoneal fat area was significantly associated with blood pressure, plasma glycemic indices, lipid profile, C-reactive protein, adiponectin (r = −0.244, P<0.05), and leptin (r = 0.323, p<0.05), but not plasma renin or aldosterone concentrations. During the 2.94±0.84 years of follow-up, 32 participants developed incident hypertension. Retroperitoneal fat area (hazard ration (HR) 1.62, p = 0.003) and peritoneal fat area (HR 1.62, p = 0.009), but not subcutaneous fat area (p = 0.14) were associated with incident hypertension. Neither retroperitoneal fat area, peritoneal fat area, nor subcutaneous fat areas was associated with incident diabetes after adjustment.</p><p>Conclusions</p><p>Retroperitoneal fat is similar to peritoneal fat, but differs from subcutaneous fat, in terms of its relationship with metabolic syndrome and incident hypertension. Retroperitoneal fat area should be included in the measurement of visceral fat for cardio-metabolic studies in human.</p></div

The relationship between metabolic syndrome and body fat in logistic regression models, using metabolic syndrome as the dependent variable.

<p>Body fat was logarithmically transformed for statistical analyses. Odds ratios (95% CI) were shown.</p>a<p>p<0.05.</p><p>The relationship between metabolic syndrome and body fat in logistic regression models, using metabolic syndrome as the dependent variable.</p

Hazard ratios (HRs) and 95% confidence interval (95% CI) of different fat components to predict the development of incident hypertension and incident diabetes during follow-up.

<p>Hazard ratios were normalized to show the effect of every 1 standard deviation increase in fat areas.</p>a<p>p<0.05.</p><p>Model 1: adjusted for age, sex, and family history of hypertension.</p><p>Model 2: adjusted for age, sex, and family history of diabetes.</p><p>Hazard ratios (HRs) and 95% confidence interval (95% CI) of different fat components to predict the development of incident hypertension and incident diabetes during follow-up.</p

Different fat compartments to predict the probability of incident hypertension.

<p>Kaplan-Meier failure curves for the probability of developing hypertension in subgroups divided by the median of (A) retroperitoneal fat area, (B) peritoneal fat area, and (C) subcutaneous fat area. P values by log-rank tests are shown.</p