Obesity-linked insulin resistance greatly increases the risk for type 2 diabetes, hypertension, dyslipidemia, and non-alcoholic fatty liver disease, together known as the metabolic or insulin resistance syndrome. How obesity promotes insulin resistance remains incompletely understood. Plasma concentrations of free fatty acids and proinflammatory cytokines, endoplasmic reticulum (ER) stress, and oxidative stress are all elevated in obesity and have been shown to induce insulin resistance. However, they may be late events that only develop after chronic excessive nutrient intake. The nature of the initial event that produces insulin resistance at the beginning of excess caloric intake and weight gain remains unknown. We show that feeding healthy men with ~6000 kcal/day of the common U.S. diet [~50% carbohydrate (CHO), ~ 35% fat, and ~15% protein] for 1 week produced a rapid weight gain of 3.5 kg and the rapid onset (after 2 to 3 days) of systemic and adipose tissue insulin resistance and oxidative stress but no inflammatory or ER stress. In adipose tissue, the oxidative stress resulted in extensive oxidation and carbonylation of numerous proteins, including carbonylation of GLUT4 near the glucose transport channel, which likely resulted in loss of GLUT4 activity. These results suggest that the initial event caused by overnutrition may be oxidative stress, which produces insulin resistance, at least in part, via carbonylation and oxidation-induced inactivation of GLUT4.
The use of MBP alone before elective colorectal resection to prevent SSI is ineffective and should be abandoned. In contrast, OA and MBP + OA are associated with decreased risks of SSI and are not associated with increased risks of other adverse outcomes compared with no preparation. Prospective studies to determine the efficacy of OA are warranted; in the interim, MBP + OA should be used routinely before elective colorectal resection to prevent SSI.
Determination of fundamental mechanisms of disease often hinges on histopathology visualization and quantitative image analysis. Currently, the analysis of multi-channel fluorescence tissue images is primarily achieved by manual measurements of tissue cellular content and sub-cellular compartments. Since the current manual methodology for image analysis is a tedious and subjective approach, there is clearly a need for an automated analytical technique to process large-scale image datasets. Here, we introduce Nuquantus (Nuclei quantification utility software) - a novel machine learning-based analytical method, which identifies, quantifies and classifies nuclei based on cells of interest in composite fluorescent tissue images, in which cell borders are not visible. Nuquantus is an adaptive framework that learns the morphological attributes of intact tissue in the presence of anatomical variability and pathological processes. Nuquantus allowed us to robustly perform quantitative image analysis on remodeling cardiac tissue after myocardial infarction. Nuquantus reliably classifies cardiomyocyte versus non-cardiomyocyte nuclei and detects cell proliferation, as well as cell death in different cell classes. Broadly, Nuquantus provides innovative computerized methodology to analyze complex tissue images that significantly facilitates image analysis and minimizes human bias.
Background All elective surgeries have been postponed at our institution starting 3/16/20 due to the COVID-19 pandemic. We assessed changes in hospital resource utilization and estimated the future backlog of cases in the colorectal surgery division of a large safety-net hospital. Methods Patients undergoing colorectal procedures from 3/16/20 to 4/23/20 (COVID) were compared with those from January through June 2018 (historical). Resource utilization rates were calculated by weekly case volumes and hospital stay in each group. A future catch up timeframe and new wait times from scheduling to surgery dates were calculated. Results The COVID and historical groups included 13 and 239 patients, respectively. The COVID group showed a 74% relative decrease in weekly surgical case rates (9.2 to 2.4 patients per week) . Both groups had similar lengths of stay. The COVID group had a longer average ICU stay (1.4 ± 2.5 days vs. 0.4 ± 1.2 days, P = 0.016) and a 132% increase in ICU resource utilization. Overall, the COVID group had a 48% relative decrease in hospital resource utilization, owing to reduced volume but higher acuity. If the surgery numbers returns to pre-COVID volumes, the calculated “catch up” times range from 4.6 weeks to 9.2 weeks. Wait times for new cases may increase by 70% compared with pre-COVID levels. Conclusion Cancelling elective colorectal surgeries results in a decrease in overall but increase in ICU-specific resource utilization. Though necessary, cancellations result in an increasing backlog of cases that poses significant future logistical and clinical challenges in an already overburdened safety-net hospital. Effective triage systems will be critical to prioritize this backlog.
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