N-acetylcysteine counteracts oxidative stress and protects alveolar epithelial cells from lung contusion-induced apoptosis in rats with blunt chest trauma

The aim of this study was to investigate the protective effects of N-acetylcysteine (NAC) on peroxidative and apoptotic changes in the contused lungs of rats following blunt chest trauma. The rats were randomly divided into three groups: control, contusion, and contusion + NAC. All the rats, apart from those in the control group, performed moderate lung contusion. A daily intramuscular NAC injection (150 mg/kg) was given immediately following the blunt chest trauma and was continued for two additional days following cessation of the trauma. Samples of lung tissue were taken in order to evaluate the tissue malondialdehyde (MDA) level, histopathology, and epithelial cell apoptosis using terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) assay and active caspase-3 immunostaining. In addition, we immunohistochemically evaluated the expression of surfactant protein D (SP-D) in the lung tissue. The blunt chest trauma-induced lung contusion resulted in severe histopathological injury, as well as an increase in the MDA level and in the number of cells identified on TUNEL assay together with active caspase-3 positive epithelial cells, but a decrease in the number of SP-D positive alveolar type 2 (AT-2) cells. NAC treatment effectively attenuated histopathologic, peroxidative, and apoptotic changes, as well as reducing alterations in SP-D expression in the lung tissue. These findings indicate that the beneficial effects of NAC administrated following blunt chest trauma is related to the regulation of oxidative stress and apoptosis.     

High throughput single cell bioinformatics

Advances in systems biology and bioinformatics have highlighted that no cell population is truly uniform and that stochastic behavior is an inherent property of many biological systems. As a result, bulk measurements can be misleading even when particular care has been taken to isolate a single cell type, and measurements averaged over multiple cell populations in a tissue can be as misleading as the average height at an elementary school. There is a growing need for experimental techniques that can provide a combination of single cell resolution, large cell populations, and the ability to track cells over multiple time points. In this article, a microwell array cytometry platform was developed to meet this need and investigate the heterogeneity and stochasticity of cell behavior on a single cell basis. The platform consisted of a microfabricated device with high‐density arrays of cell‐sized microwells and custom software for automated image processing and data analysis. As a model experimental system, we used primary hepatocytes labeled with fluorescent probes sensitive to mitochondrial membrane potential and free radical generation. The cells were exposed to oxidative stress and the responses were dynamically monitored for each cell. The resulting data was then analyzed using bioinformatics techniques such as hierarchical and k‐means clustering to visualize the data and identify interesting features. The results showed that clustering of the dynamic data not only enhanced comparisons between the treatment groups but also revealed a number of distinct response patterns within each treatment group. Heatmaps with hierarchical clustering also provided a data‐rich complement to survival curves in a dose response experiment. The microwell array cytometry platform was shown to be powerful, easy to use, and able to provide a detailed picture of the heterogeneity present in cell responses to oxidative stress. We believe that our microwell array cytometry platform will have general utility for a wide range of questions related to cell population heterogeneity, biological stochasticity, and cell behavior under stress conditions. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Use of a Continuous Glucose Monitoring System in High-Risk Hospitalized Noncritically Ill Patients With Diabetes After Cardiac Surgery and During Their Transition of Care From the Intensive Care Unit During COVID-19: A Pilot Study

ObjectiveContinuous glucose monitoring (CGM) has demonstrated benefits in managing inpatient diabetes. We initiated this single-arm pilot feasibility study during the COVID-19 pandemic in 11 patients with diabetes to determine the feasibility and accuracy of real-time CGM in patients who underwent cardiac surgery and whose care was being transitioned from the intensive care unit.MethodsA Clarke error grid analysis was used to compare CGM and point-of-care measurements. The mean absolute relative difference (MARD) of the paired measurements was calculated to assess the accuracy of CGM for glucose measurements during the first 24 hours on CGM, the remaining time on CGM, and for different chronic kidney disease (CKD) strata.ResultsOverall MARD between point-of-care and CGM measurements was 14.80%. MARD for patients without CKD IV and V with an estimated glomerular filtration rate (eGFR) of ≥20 mL/min/1.73 m² was 12.13%. Overall, 97% of the CGM values were within the no-risk zone of the Clarke error grid analysis. For the first 24 hours, a sensitivity analysis of the overall MARD for all patients and those with an eGFR of ≥20 mL/min/1.73 m² was 15.42% ± 14.44% and 12.80% ± 7.85%, respectively. Beyond the first 24 hours, overall MARD for all patients and those with an eGFR of ≥20 mL/min/1.73 m² was 14.54% ± 13.21% and 11.86% ± 7.64%, respectively.ConclusionCGM has shown great promise in optimizing inpatient diabetes management in the noncritical care setting and after the transition of care from the intensive care unit with high clinical reliability and accuracy. More studies are needed to further assess CGM in patients with advanced CKD.