Oxygen-derived free radicals and hemolysis during open heart surgery

Reperfusion injury occurs during open-heart surgery after prolonged cardioplegic arrest. Cardiopulmonary bypass also is known to cause hemolysis. Since reperfusion of ischemic myocardium is associated with the generation of oxygen free radicals, and since free radicals can attack a protein molecule, it seems reasonable to assume that hemolysis might be the consequence of free radical attack on hemoglobin protein. The results of this study demonstrated that reperfusion following ischemic arrest caused an increase in free hemoglobin and free heme concentrations, simultaneously releasing free iron and generating hydroxyl radicals. In vitro studies using pure hemoglobin indicated that superoxide anion generated by the action of xanthine oxidase on xanthine could release iron from the heme ring and cause deoxygenation of oxyhemoglobin into ferrihemoglobin. This study further demonstrated that before the release of iron from the heme nucleus, oxyhemoglobin underwent deoxygenation to ferrihemoglobin. The released iron can catalyze the Fenton reaction, leading to the formation of cytotoxic hydroxyl radical (OH·). In fact, the formation of OH. in conjunction with hemolysis occurs during cardiac surgery, and when viewed in the light of the in vitro results, it seems likely that oxygen-derived free radicals may cause hemolysis during cardiopulmonary bypass and simultaneously release iron from the heme ring, which can catalyze the formation of OH·.     

Variable selection in nonlinear function-on-scalar regression

We develop a new method for variable selection in a nonlinear additive function-on-scalar regression (FOSR) model. Existing methods for variable selection in FOSR have focused on the linear effects of scalar predictors, which can be a restrictive assumption in the presence of multiple continuously measured covariates. We propose a computationally efficient approach for variable selection in existing linear FOSR using functional principal component scores of the functional response and extend this framework to a nonlinear additive function-on-scalar model. The proposed method provides a unified and flexible framework for variable selection in FOSR, allowing nonlinear effects of the covariates. Numerical analysis using simulation study illustrates the advantages of the proposed method over existing variable selection methods in FOSR even when the underlying covariate effects are all linear. The proposed procedure is demonstrated on accelerometer data from the 2003–2004 cohorts of the National Health and Nutrition Examination Survey (NHANES) in understanding the association between diurnal patterns of physical activity and demographic, lifestyle, and health characteristics of the participants.     

Protection from nonfreezing cold injury by quinacrine, a phospholipase inhibitor

A recent study from our laboratory indicated additional tissue injury during rewarming of a cooled rabbit leg. Oxygen-derived free radicals were believed to play a role in such "rewarming injury." Since free radicals may attack membrane phospholipids, we analyzed the phospholipid composition in the leg tissue during cooling and rewarming. Our results indicated significant breakdown of membrane phospholipids, particularly phosphatidylcholine and phosphatidylethanolamine, with a corresponding accumulation of lysophosphatidylcholine and nonesterified fatty acids. Quinacrine, a phospholipase inhibitor, was able to preserve membrane phospholipids during rewarming of the cooled leg. Rewarming of cooled tissue was also accompanied by additional tissue injury, as evidenced by the increased release of lactic acid dehydrogenase and creatine kinase, as well as enhanced lipid peroxidation, as evidenced by increased malonaldehyde formation. Quinacrine reduced the release of these intracellular enzymes and decreased lipid peroxidation, suggesting its efficacy as a therapeutic agent against hypothermic injury.     

Changes in lipid profiles of brain of albino rats following envenomation

Effect of high doses of cobra venom (150 micrograms/120 +/- 20 g body weight) and viper venom (300 micrograms/120 +/- 20 g body weight) on total lipid, triglyceride, phospholipid, cholesterol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) of brain of albino rats was studied. Total lipid (TL) triglyceride (TG) and phospholipid (PL) are decreased in both viper and cobra venom treated groups while cholesterol (C), and LDL-C are increased in both the groups in relation to controlled ones. HDL-C content was almost unaltered. Decrease in triglyceride and phospholipid may be due to effect of lipases and phospholipases whereas increased cholesterol and LDL-C may be attributed to lysis of cell membrane.     

Purification and characterization of myo-inositol hexaphosphate-adenosine diphosphate phosphotransferase from Phaseolus aureus

myo-Inositol hexaphosphate adenosine diphosphate phosphotransferase transfers phosphate from myo-inositol hexaphosphate to adenosine diphosphate to synthesize adenosine triphosphate. This enzyme has been isolated and purified from ungerminated mungbean seeds and found to be different from guanosine diphosphate phosphotransferase. A purification of about 200-fold with 15% recovery has been obtained. The optimal pH of the reaction is 7.0 and is dependent on the presence of a divalent cation, i.e., Mg²⁺ and Mn²⁺. The K_m value for myo-inositol hexaphosphate has been found to be 0.41 × 10^?4m and V is 90.0 nmol of P_i transferred per milligram of protein per 20 min. K_m for ADP is 0.88 × 10^-4m and V is 83.3 nmol of phosphorus transferred to ADP per milligram of protein per 20 min. The ADP phosphotransferase reaction is reversible to the extent of about 50% of the forward reaction. dADP is partly effective as an acceptor but other ribonucleoside mono- and diphosphates cannot substitute for ADP. The products ATP and myo-inositol pentaphosphate have been confirmed by several criteria. It has also been shown that this enzyme transfers phosphate only from a specific phosphoryl group (C-2 position) of myo-inositol hexaphosphate for the synthesis of ATP and 1,3,4,5,6-myo-inositol pentaphosphate or pentakis (dihydrogen phosphate).     

Prediction of stenosis behaviour in artery by neural network and multiple linear regressions

Biomechanics and Modeling in Mechanobiology - Blood flow analysis in the artery is a paramount study in the field of arterial stenosis evaluation. Studies conducted so far have reported the...     

Bacopasaponins with cytotoxic activity against human breast cancer cells in vitro

Molecular Biology Reports - Globally, breast cancer is a serious concern that exhibits a persistent rise in its incidence and related mortality even after significant advancement in the field of...     

Environmental variables responsible for Zebu cattle thermal comfort acquisition

International Journal of Biometeorology - The aim of this study was to estimate, using data mining, which microclimate and behavioral variables affect the behavior of animals to seek shaded or...     

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse-phase protein arrays–based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.