Association between Glutathione S-Transferases Gene Variants and COVID-19 Severity in Previously Vaccinated and Unvaccinated Polish Patients with Confirmed SARS-CoV-2 Infection.

As the outcome of COVID-19 is associated with oxidative stress, it is highly probable that polymorphisms of genes related to oxidative stress were associated with susceptibility and severity of COVID-19. The aim of the study was to assess the association of glutathione S-transferases (GSTs) gene polymorphisms with COVID-19 severity in previously vaccinated and unvaccinated Polish patients with confirmed SARS-CoV-2 infection. A total of 92 not vaccinated and 84 vaccinated patients hospitalized due to COVID-19 were included. The WHO COVID-19 Clinical Progression Scale was used to assess COVID-19 severity. GSTs genetic polymorphisms were assessed by appropriate PCR methods. Univariable and multivariable analyses were performed, including logistic regression analysis. GSTP1 Ile/Val genotype was found to be associated with a higher risk of developing a severe form of the disease in the population of vaccinated patients with COVID-19 (OR: 2.75; p = 0.0398). No significant association was observed for any of the assessed GST genotypes with COVID-19 disease severity in unvaccinated patients with COVID-19. In this group of patients, BMI > 25 and serum glucose level > 99 mg% statistically significantly increased the odds towards more severe COVID-19. Our results may contribute to further understanding of risk factors of severe COVID-19 and selecting patients in need of strategies focusing on oxidative stress.

Near-Infrared Spectroscopy with Supervised Machine Learning as a Screening Tool for Neutropenia.

The use of non-invasive tools in conjunction with artificial intelligence (AI) to detect diseases has the potential to revolutionize healthcare. Near-infrared spectroscopy (NIR) is a technology that can be used to analyze biological samples in a non-invasive manner. This study evaluated the use of NIR spectroscopy in the fingertip to detect neutropenia in solid-tumor oncologic patients. A total of 75 patients were enrolled in the study. Fingertip NIR spectra and complete blood counts were collected from each patient. The NIR spectra were pre-processed using Savitzky-Golay smoothing and outlier detection. The pre-processed data were split into training/validation and test sets using the Kennard-Stone method. A toolbox of supervised machine learning classification algorithms was applied to the training/validation set using a stratified 5-fold cross-validation regimen. The algorithms included linear discriminant analysis (LDA), logistic regression (LR), random forest (RF), multilayer perceptron (MLP), and support vector machines (SVMs). The SVM model performed best in the validation step, with 85% sensitivity, 89% negative predictive value (NPV), and 64% accuracy. The SVM model showed 67% sensitivity, 82% NPV, and 57% accuracy on the test set. These results suggest that NIR spectroscopy in the fingertip, combined with machine learning methods, can be used to detect neutropenia in solid-tumor oncology patients in a non-invasive and timely manner. This approach could help reduce exposure to invasive tests and prevent neutropenic patients from inadvertently undergoing chemotherapy.

Heat Shock Protein 27 Is an Emerging Predictor of Contrast-Induced Acute Kidney Injury on Patients Subjected to Percutaneous Coronary Interventions.

Contrast-induced acute kidney injury (CI-AKI) is a serious complication associated with considerable morbidity and mortality. Heat-shock protein 27 (HSP27) plays a role in the defense of the kidney tissue against various forms of cellular stress, including hypoxia and oxydative stress, both features associated with CI-AKI. The aim of our study was to evaluate a potential predictive value of HSP27 for CI-AKI in patients subjected to percutaneous coronary interventions (PCI). Included were 343 selected patients subjected to PCI. Exclusion criteria were conditions that potentially might influence HSP27 levels. HSP27 serum levels were evaluated prior to PCI, together with serum creatinine, the concentration of which was also evaluated twice at 48 and 72 h post PCI. CI-AKI was diagnosed in 9.3% of patients. Patients in whom CI-AKI was diagnosed were older (p < 0.001), were more often females (p = 0.021), had higher prevalence of diabetes (p = 0.011), hypotension during PCI (p < 0.001), albuminuria (p = 0.004) as well as multivessel disease (p = 0.002), received higher contrast volume (p = 0.006), more often received contrast volume (CV) above the maximum allowed contrast dose (MACD) (p < 0.001), and had lower HSP27 level (p < 0.001). On multivariate analysis, CV > MACD (OR 1.23, p = 0.001), number of diseased vessels (OR 1.27, p = 0.006), and HSP27 (OR 0.81, p = 0.001) remained independent predictors of CI-AKI. Low concentration of HSP27 is an emerging, strong and independent predictor of CI-AKI in patients subjected to PCI.

Analysis of the Nutritional Status in Homeless People in Poland Based on the Selected Biochemical Parameters.

The aim of the study was to assess the nutritional status of adult homeless people using both anthropometric and biochemical measurements. The analysis comprised anthropometric indicators, i.e., body mass index and waist circumference, and the following biomarkers: red blood cells, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, white blood cells, complete lymphocyte count, neutrophils-to-lymphocytes ratio, platelets-to-lymphocytes ratio, platelets-to-leukocytes ratio, C reactive protein level, serum iron concentration, serum albumin concentration, total serum protein, fasting lipids and blood glucose level. There were representative Polish homeless people enrolled (n = 580). The analysis of the conducted studies proved that there is a greater frequency of overweight and obesity than underweight in the target population. The major problem was abdominal obesity that was present statistically more frequently in women than men (p < 0.001). In the majority of cases, homeless people were found to have normal complete blood count parameters. In obese people, there were statistically significant both elevated and decreased hematocrit levels, a significant decrease in red blood cells, elevated serum glucose, triglycerides and total protein level (p < 0.05). The presence of abdominal obesity, elevated glucose concentration, low-density lipoprotein cholesterol, and triglycerides, and decreased high-density lipoprotein cholesterol in serum together with smoking increase the risk of cardiovascular disease.

Tree growth influenced by warming winter climate and summer moisture availability in northern temperate forests.

The role of future forests in global biogeochemical cycles will depend on how different tree species respond to climate. Interpreting the response of forest growth to climate change requires an understanding of the temporal and spatial patterns of seasonal climatic influences on the growth of common tree species. We constructed a new network of 310 tree-ring width chronologies from three common tree species (Quercus robur, Pinus sylvestris and Fagus sylvatica) collected for different ecological, management and climate purposes in the south Baltic Sea region at the border of three bioclimatic zones (temperate continental, oceanic, southern boreal). The major climate factors (temperature, precipitation, drought) affecting tree growth at monthly and seasonal scales were identified. Our analysis documents that 20th century Scots pine and deciduous species growth is generally controlled by different climate parameters, and that summer moisture availability is increasingly important for the growth of deciduous species examined. We report changes in the influence of winter climate variables over the last decades, where a decreasing influence of late winter temperature on deciduous tree growth and an increasing influence of winter temperature on Scots pine growth was found. By comparing climate-growth responses for the 1943-1972 and 1973-2002 periods and characterizing site-level growth response stability, a descriptive application of spatial segregation analysis distinguished sites with stable responses to dominant climate parameters (northeast of the study region), and sites that collectively showed unstable responses to winter climate (southeast of the study region). The findings presented here highlight the temporally unstable and nonuniform responses of tree growth to climate variability, and that there are geographical coherent regions where these changes are similar. Considering continued climate change in the future, our results provide important regional perspectives on recent broad-scale climate-growth relationships for trees across the temperate to boreal forest transition around the south Baltic Sea.