beta-Lactoglobulin (beta-LG) is one of the cow's major milk proteins and the most abundant whey protein. This globular protein of about 18 kDa is folded, forming a beta-barrel (or calyx) structure. This structure is stabilized by two disulfide bonds and can be altered by heating above 65 degrees C. beta-LG is also one of the major allergens in milk. Heating is one of the most common technologic treatments applied during many milk transformations. During heating in the presence of reducing sugars, beta-LG is also submitted to the Maillard reaction, which at the first stage consists of the covalent fixation of sugars on the epsilon-amino groups of lysyl residues. The following steps are condensation and polymerization reactions leading to the formation of melanoidins (brown pigments). Despite the frequency of use of heating during milk transformation, the effects of heat-induced denaturation and of glycation of beta-LG on its recognition by IgE from cow's milk allergy (CMA) patients are not fully understood. The objectives of our work were to evaluate the effect of heat-induced denaturation of bovine beta-LG on binding of IgE from CMA patients and to determine the effect of moderate glycation on the degree of recognition by IgE. We showed that heat-induced denaturation (loss of tertiary and secondary structures) of beta-LG is associated with weaker binding of IgE from CMA patients. It was also shown that moderate glycation of beta-LG in early stages of Maillard reaction has only a small effect on its recognition by IgE, whereas a high degree of glycation has a clear "masking" effect on the recognition of epitopes. This demonstrates the importance of epsilon-amino groups of lysines in the definition of epitopes recognized by IgE.

The combined treatment concept of cytoreductive surgery (CRS) and Hyperthermic intraperitoneal chemotherapy (HIPEC) has shown to be an efficient therapeutic option for selected patients with primary and secondary peritoneal carcinomatosis (PC). This strategy represents the standard of care for diseases like pseudomyxoma peritonei and peritoneal mesothelioma, and offers the best long-term results for PC from colorectal cancer. Despite these results, skepticism exists regarding this therapeutic approach partly because of its perceived high toxicity. In this article, we review the current evidence on complications that can occur after CRS and HIPEC and the risk factors associated with increased incidence of morbidity and mortality.

Dextrocardia with situs inversus is a rare clinical entity with an estimated incidence ranges from 1 in 8000 to 1 in10,000. Percutaneous intervention in patient with dextrocardia and situs inversus is clinically challenging due to abnormal orientation of coronary geometry and the intervention requires appropriate use of guiding catheters, engagement technique, appropriate radiological angles as well as views. In this case-report, we describe percutaneous intervention with stenting in 48-year-old male patient with dextrocardia and situs inversus. We successfully deployed drug-eluting stents in right coronary artery and left circumflex artery.

Background: A strong association between abnormal lipid variables and development of atherosclerosis is widely established. However, few data exist on the association between lipid levels and the extent or severity of coronary lesions in patients with coronary artery disease. Objective: We aimed to determine the link between lipid levels and the extent or severity of coronary lesions in patients with suspected coronary artery disease using Friesinger index (FR). Methodology: In this prospective and singe-center study, consecutive patients who underwent coronary angiography for diagnostic purposes were analyzed. Each participant was evaluated for lipid levels i.e. total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, very-low-density lipoprotein (VLDL) cholesterol, non-HDL cholesterol, triglycerides/ HDL cholesterol, and triglycerides/non-HDL cholesterol. The extent of coronary disease was evaluated using FR index. Results: A total of 566 patients (mean age: 56.17 ± 9.99 years) were included in the study. The mean FR index was 5.40 ± 3.78. A significantly positive correlation was observed between FR index and total cholesterol (P = 0.002), triglycerides (P < 0.001), VLDL cholesterol (P < 0.001), non-HDL cholesterol (P = 0.006), triglycerides/HDL cholesterol ratio (P = 0.008), and triglycerides/non-HDL cholesterol ratio (P = 0.002). On the contrary, an inverse correlation was observed between FR index and HDL cholesterol (P < 0.001). Age or gender played no role in governing the FR index severity, while body-mass index, hypertension, diabetes, and smoking showed significant association with FR index (P < 0.001 for all). Conclusion: The present study demonstrates a significant link between the extent of coronary artery disease and levels of certain lipid variables.

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Graph Neural Networks (GNN) provide a powerful framework that elegantly integrates Graph theory with Machine learning for modeling and analysis of networked data. We consider the problem of quantifying the uncertainty in predictions of GNN stemming from modeling errors and measurement uncertainty. We consider aleatoric uncertainty in the form of probabilistic links and noise in feature vector of nodes, while epistemic uncertainty is incorporated via a probability distribution over the model parameters. We propose a unified approach to treat both sources of uncertainty in a Bayesian framework, where Assumed Density Filtering is used to quantify aleatoric uncertainty and Monte Carlo dropout captures uncertainty in model parameters. Finally, the two sources of uncertainty are aggregated to estimate the total uncertainty in predictions of a GNN. Results in the real-world datasets demonstrate that the Bayesian model performs at par with a frequentist model and provides additional information about predictions uncertainty that are sensitive to uncertainties in the data and model.