The Influence of High-Dose Parenteral Vitamin C on the Incidence and Severity of Postoperative Pulmonary Complications in Cardiac Surgery with Extracorporeal Circulation: A Randomized Controlled Trial.

Cardiac surgery (CS) with extracorporeal circulation (ECC), induces intense oxidative stress (OS) and systemic inflammatory response (SIR), which may seriously affect postoperative lung function. We aimed to test if high parenteral (200 mg/kg/24 h) daily doses of Vitamin C (VitC), given within 48 h after the beginning of the operation, may reduce the incidence and severity of postoperative pulmonary complications (PPCs) in CS patients. This single-center, prospective, randomized, single-blinded, interventional trial included 150 patients, assigned to control Group A (n = 75) and interventional Group B (n = 75). Group B intraoperatively received one-fourth (i.e., 50 mg/kg) of the planned daily Vit C dose, divided into three equal parts and diluted in 10 mL of normal saline, while Group A received an equal volume of normal saline at the same time frames (i.e., the induction of anesthesia, aortic cross-clamp release, and sternal closure). After 6 h from the first intraoperative dose, the following regimen was applied: Group B: 50 mg/kg, 30 min i.v. infusion of VitC in 50 mL of normal saline, every 6 h, for the next 48 h, and Group A: 30 min i.v. infusion of an equal volume of normal saline every 6 h, for the next 48 h. Modified Kroenke's score was used to determine the incidence and severity of PPCs. The overall incidence of PPCs was 36.7% and was significantly lower in Group B (13.3% vs. 60.0%, p < 0.001). The PPCs severity score was also significantly lower in Group B (1 vs. 3, p < 0.001). In addition, patients from Group B had significantly less damaged lungs, better postoperative renal function, shorter ICU stays, fewer ICU re-admissions, and lower hospital mortality. No VitC-related adverse effects were recorded. High parenteral daily VitC doses given within 48 h after the beginning of CS are safe and effective in reducing the incidence and severity of PPCs. A multicenter RCT is needed to confirm these results.

Gray-Level Co-occurrence Matrix Analysis of Nuclear Textural Patterns in Laryngeal Squamous Cell Carcinoma: Focus on Artificial Intelligence Methods.

Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify discrete changes in cell and tissue textural features. Previous research has indicated that these methods may be applicable in the pathology for identification and classification of various types of cancers. In this study, we present findings that squamous epithelial cells in laryngeal carcinoma, which appear morphologically intact during conventional pathohistological evaluation, have distinct nuclear GLCM and DWT features. The average values of nuclear GLCM indicators of these cells, such as angular second moment, inverse difference moment, and textural contrast, substantially differ when compared to those in noncancerous tissue. In this work, we also propose machine learning models based on random forests and support vector machine that can be successfully trained to separate the cells using GLCM and DWT quantifiers as input data. We show that, based on a limited cell sample, these models have relatively good classification accuracy and discriminatory power, which makes them suitable candidates for future development of AI-based sensors potentially applicable in laryngeal carcinoma diagnostic protocols.

Computational approaches for evaluating morphological changes in the corneal stroma associated with decellularization.

Decellularized corneas offer a promising and sustainable source of replacement grafts, mimicking native tissue and reducing the risk of immune rejection post-transplantation. Despite great success in achieving acellular scaffolds, little consensus exists regarding the quality of the decellularized extracellular matrix. Metrics used to evaluate extracellular matrix performance are study-specific, subjective, and semi-quantitative. Thus, this work focused on developing a computational method to examine the effectiveness of corneal decellularization. We combined conventional semi-quantitative histological assessments and automated scaffold evaluations based on textual image analyses to assess decellularization efficiency. Our study highlights that it is possible to develop contemporary machine learning (ML) models based on random forests and support vector machine algorithms, which can identify regions of interest in acellularized corneal stromal tissue with relatively high accuracy. These results provide a platform for developing machine learning biosensing systems for evaluating subtle morphological changes in decellularized scaffolds, which are crucial for assessing their functionality.

Gray level co-occurrence matrix and wavelet analyses reveal discrete changes in proximal tubule cell nuclei after mild acute kidney injury.

Acute kidney injury (AKI) relates to an abrupt reduction in renal function resulting from numerous conditions. Morbidity, mortality, and treatment costs related to AKI are relatively high. This condition is strongly associated with damage to proximal tubule cells (PTCs), generating distinct patterns of transcriptional and epigenetic alterations that result in structural changes in the nuclei of this epithelium. To this date, AKI-related nuclear chromatin redistribution in PTCs is poorly understood, and it is unclear whether changes in PTC chromatin patterns can be detected using conventional microscopy during mild AKI, which can progress to more debilitating forms of injury. In recent years, gray level co-occurrence matrix (GLCM) analysis and discrete wavelet transform (DWT) have emerged as potentially valuable methods for identifying discrete structural changes in nuclear chromatin architecture that are not visible during the conventional histopathological exam. Here we present findings indicating that GLCM and DWT methods can be successfully used in nephrology to detect subtle nuclear morphological alterations associated with mild tissue injury demonstrated in rodents by inducing a mild form of AKI through ischemia-reperfusion injury. Our results show that mild ischemic AKI is associated with the reduction of local textural homogeneity of PTC nuclei quantified by GLCM and the increase of nuclear structural heterogeneity indirectly assessed with DWT energy coefficients. This rodent model allowed us to show that mild ischemic AKI is associated with the significant reduction of textural homogeneity of PTC nuclei, indirectly assessed by GLCM indicators and DWT energy coefficients.

Artificial neural networks in contemporary toxicology research.

Artificial neural networks (ANNs) have a huge potential in toxicology research. They may be used to predict toxicity of various chemical compounds or classify the compounds based on their toxic effects. Today, numerous ANN models have been developed, some of which may be used to detect and possibly explain complex chemico-biological interactions. Fully connected multilayer perceptrons may in some circumstances have high classification accuracy and discriminatory power in separating damaged from intact cells after exposure to a toxic substance. Regularized and not fully connected convolutional neural networks can detect and identify discrete changes in patterns of two-dimensional data associated with toxicity. Bayesian neural networks with weight marginalization sometimes may have better prediction performance when compared to traditional approaches. With the further development of artificial intelligence, it is expected that ANNs will in the future become important parts of various accurate and affordable biosensors for detection of various toxic substances and evaluation of their biochemical properties. In this concise review article, we discuss the recent research focused on the scientific value of ANNs in evaluation and prediction of toxicity of chemical compounds.

Morphogenetic dispositions for variability in acute kidney injury after cardiac surgery: Pilot study.

Background: The aim of our study was to evaluate the degree of genetic homozygosity in cardiac surgical patients with postoperative acute kidney injury (AKI), compared to the subgroup without postoperative AKI, as well as to evaluate antropomorpho-genetic variability in cardiac surgical patients with regard to the presence and severity degree of AKI. Materials and methods: The prospective cohort study included an analysis of 138 eligible coronary artery disease (CAD) surgical patients that were screened consecutively. The tested group was divided into three subgroups according to RIFLE criteria: Subgroup NoAKI (N = 91), risk (N = 31), and injury (N = 16). All individuals were evaluated for the presence of 19 observable recessive human traits (ORHT) as a marker of chromosomal homozygosity and variability. Results: Comparing subgroups NoAKI and risk, four ORHTs were significantly more frequent in the risk subgroup. Comparing subgroups NoAKI and injury, nine ORHTs were significantly more frequent in the injury subgroup; while comparing the injury subgroup and risk, five ORHTs were significantly more frequent in injury than in the risk subgroup. Results also showed a significant increase in the mean value of ORHTs for the injury subgroup compared to NoAKI subgroup (p = 0.039). Variability decreased proportionally to the increase in the severity of AKI (V NoAKI = 32.81%, V Risk = 30.92%, and V Injury = 28.62%). Conclusion: Our findings pointed to the higher degree of recessive homozygosity and decreased variability in AKI patients vs. NoAKI individuals, thus presumably facilitating the development and severity degree expression of AKI in patients after cardiac surgery.

Effect of regional vs general anesthesia on vital functions after cesarean section: a single center experience.

BACKGROUND: The aim was to determine the effect of regional anesthesia (RA) on postoperative vital functions in contrast to general endotracheal anesthesia (GEA) after the cesarean section. METHODS: Prospective cohort study included consecutive term pregnant women delivered by cesarean section (GEA, n = 284; RA, n = 249). RESULTS: Higher levels of blood pressure and heart rate, as well as lower levels of pulse oximetry were found for GEA in contrast to RA (p < 0.001). The application of RA presented less side-effects (p < 0.05). CONCLUSIONS: RA for cesarean section should be preferred when balancing the risks and benefits for the mother and fetus.

Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art.

Artificial intelligence (AI) and machine learning models are today frequently used for classification and prediction of various biochemical processes and phenomena. In recent years, numerous research efforts have been focused on developing such models for assessment, categorization, and prediction of oxidative stress. Supervised machine learning can successfully automate the process of evaluation and quantification of oxidative damage in biological samples, as well as extract useful data from the abundance of experimental results. In this concise review, we cover the possible applications of neural networks, decision trees and regression analysis as three common strategies in machine learning. We also review recent works on the various weaknesses and limitations of artificial intelligence in biochemistry and related scientific areas. Finally, we discuss future innovative approaches on the ways how AI can contribute to the automation of oxidative stress measurement and diagnosis of diseases associated with oxidative damage.

Gray-Level Co-occurrence Matrix Analysis for the Detection of Discrete, Ethanol-Induced, Structural Changes in Cell Nuclei: An Artificial Intelligence Approach.

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy. The aim of our research was to perform the GLCM analysis of cell nuclei in Saccharomyces cerevisiae yeast cells after the induction of sublethal cell damage with ethyl alcohol, and to evaluate the performance of various machine learning (ML) models regarding their ability to separate damaged from intact cells. For each cell nucleus, five GLCM parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, and textural variance. Based on the obtained GLCM data, we applied three ML approaches: neural network, random trees, and binomial logistic regression. Statistically significant differences in GLCM features were observed between treated and untreated cells. The multilayer perceptron neural network had the highest classification accuracy. The model also showed a relatively high level of sensitivity and specificity, as well as an excellent discriminatory power in the separation of treated from untreated cells. To the best of our knowledge, this is the first study to demonstrate that it is possible to create a relatively sensitive GLCM-based ML model for the detection of alcohol-induced damage in Saccharomyces cerevisiae cell nuclei.

Comparison of Post-Cesarean Pain Perception of General Versus Regional Anesthesia, a Single-Center Study.

Background and Objectives: Pain during and after the procedure remains the leading concern among women undergoing cesarean section. Numerous studies have concluded that the type of anesthesia used during a cesarean section undoubtedly affects the intensity and experience of pain after the operation. Materials and Methods: This prospective cohort study was conducted at the Clinic for Gynecology and Obstetrics, Clinical Center "Dragisa Misovic-Dedinje", Belgrade, Serbia. Patients at term pregnancy (37-42 weeks of gestation) with an ASA I score who delivered under general (GEA) or regional anesthesia (RA) by cesarean section were included in the study. Following the procedure, we assessed pain using the Serbian McGill questionnaire (SF-MPQ), Visual Analogue Scale (VAS) and the pain attributes questionnaire at pre-established time intervals of 2, 12, and 24 h after the procedure. Additionally, time to patient's functional recovery was noted. We also recorded the time to the first independent mobilization, first oral intake, and lactation establishment. Results: GEA was performed for 284 deliveries while RA was performed for 249. GEA had significantly higher postoperative sensory and affective pain levels within intervals of 2, 12, and 24 h after cesarean section. GEA had significantly higher postoperative VAS pain levels. On pain attribute scale intensity, GEA had significantly higher postoperative pain levels within all intervals. Patients who received RA had a shorter time to first oral food intake, first independent mobilization, and faster lactation onset in contrast to GEA. Conclusions: The application of RA presented superior postoperative pain relief, resulting in earlier mobilization, shorter time to first oral food intake, and faster lactation onset in contrast to GEA.

Association between Chromatin Structural Organization of Peripheral Blood Neutrophils and Self-Perceived Mental Stress: Gray-Level Co-occurrence Matrix Analysis.

Methods based on the evaluation of textural patterns in microscopy, such as the "gray-level co-occurrence matrix" (GLCM) analysis are modern and innovative computer and mathematical algorithms that can be used to quantify subtle structural changes in cells and their organelles. Potential application of GLCM method in the fields of psychophysiology and psychiatry to this date has not been systematically investigated. The main objective of our study was to test the existence and strength of the association between chromatin structural organization of peripheral blood neutrophils and levels of self-perceived mental stress. The research was done on a sample of 100 healthy student athletes, and the Depression, Anxiety, and Stress Scales (DASS-21) were used for the estimation of psychological distress. Chromatin textural homogeneity and uniformity were negatively correlated (p < 0.01) with mental distress and had relatively good discriminatory power in differentiating participants with normal and elevated stress levels. As an addition, we propose the creation of a machine learning model based on binomial logistic regression that uses these and other GLCM features to predict stress elevation. To the best of our knowledge, these results are one of the first to establish the link between neutrophil chromatin structural organization quantified by the GLCM method and indicators of normal psychological functioning.

Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage.

In recent years, various AI-based methods have been developed in order to uncover chemico-biological interactions associated with DNA damage and oxidative stress. Various decision trees, bayesian networks, random forests, logistic regression models, support vector machines as well as deep learning tools, have great potential in the area of molecular biology and toxicology, and it is estimated that in the future, they will greatly contribute to our understanding of molecular and cellular mechanisms associated with DNA damage and repair. In this concise review, we discuss recent attempts to build machine learning tools for assessment of radiation - induced DNA damage as well as algorithms that can analyze the data from the most frequently used DNA damage assays in molecular biology. We also review recent works on the detection of antioxidant proteins with machine learning, and the use of AI-related methods for prediction and evaluation of noncoding DNA sequences. Finally, we discuss previously published research on the potential application of machine learning tools in aging research.

Oxidopamine and oxidative stress: Recent advances in experimental physiology and pharmacology.

Oxidopamine (6-hydroxydopamine, 6-OHDA) is a toxin commonly used for the creation of experimental animal models of Parkinson's disease, attention-deficit hyperactivity disorder, and Lesch-Nyhan syndrome. Its exact mechanism of action is not completely understood, although there are many indications that it is related to the generation of reactive oxygen species (ROS), primarily in dopaminergic neurons. In certain experimental conditions, oxidopamine may also cause programmed cell death via various signaling pathways. Oxidopamine may also have a significant impact on chromatin structure and nuclear structural organization in some cells. Today, many researchers use oxidopamine-associated oxidative damage to evaluate different antioxidant-based pharmacologically active compounds as drug candidates for various neurological and non-neurological diseases. Additional research is needed to clarify the exact biochemical pathways associated with oxidopamine toxicity, related ROS generation and apoptosis. In this short review, we focus on the recent research in experimental physiology and pharmacology, related to the cellular and animal experimental models of oxidopamine - mediated toxicity.

Quality of Life of Informal Caregivers behind the Scene of the COVID-19 Epidemic in Serbia.

Background and objectives: The COVID-19 pandemic has had an unprecedented reliance on informal caregivers as one of the pillars of healthcare systems. The aim of this study was to assess the quality of life of informal caregivers during the COVID-19 epidemic in Serbia. Materials and Methods: A cross-sectional study was conducted among informal caregivers during the COVID-19 epidemic in Serbia. Physical and mental quality of life was measured by the 36-Item Short-Form Health Survey. Additional data included sociodemographic characteristics, caregiver and care recipient characteristics, and COVID-19 related concerns. The qualitative component was performed using focus groups and individual in-depth interviews. Results: Out of 112 informal caregivers enrolled, most were female (80%), and the average age was 51.1 ± 12.3 years. The majority was delivering care to one person, who was a family member, on a daily basis (86.4%, 92%, and 91.1%, respectively). In multiple regression models, significant predictors of caregivers' physical health were delivering care to a family member and a higher level of care complexity, while significant predictors of caregivers' mental health were a higher level of care complexity and increased concerns about self-health and the health of the person being cared for due to the COVID-19 epidemic. Conclusions: Informal caregivers are experiencing negative physical and mental health outcomes during the COVID-19 epidemic in Serbia.

Nursery teachers in preschool institutions facing burnout: Are personality traits attributing to its development?

INTRODUCTION: The aim of the study was to assess the prevalence of burnout syndrome among nursery teachers in Belgrade's preschool institutions, and to assess the role of personality traits in its development. MATERIALS AND METHODS: A cross-sectional study was conducted in all Belgrade's preschool institutions. A stratified cluster sampling method was used to obtain a representative sample. Burnout was measured using the Maslach Burnout Inventory- General Survey (MBI-GS). The MBI-GS adaptation was based on an internationally accepted methodology for translation and cultural adaptation. Psychometric properties of the Serbian version of the MBI-GS were analyzed through the examination of factorial structure and internal consistency. A shortened version of Big Five Plus Two questionnaire was used to measure Personality traits. RESULTS: Three hundred two health care professionals were enrolled. The mean age was 38±9.2 years and all were female. Confirmatory factor analysis validated the three-factor structure of the questionnaire (exhaustion, cynicism and professional efficacy). Overall, 251 (83.1%) respondents were found to have moderate burnout. In multiple regression analysis, positive valence and conscientiousness were significantly associated with professional efficacy. Aggressiveness, neuroticism, openness, and age, were significantly associated with exhaustion. Aggressiveness, neuroticism and additional jobs showed association with cynicism. CONCLUSION: Present study provided the evidence for the appropriate metric properties of the Serbian version of MBI-GS. Most nurses demonstrated moderate burnout level. Personality traits are characteristics that affect presence of burnout syndrome in healthcare professionals working in preschool institutions.

The Prospects of Secondary Moderate Mitral Regurgitation after Aortic Valve Replacement -Meta-Analysis.

Aortic valve replacement for aortic stenosis represents one of the most frequent surgical procedures on heart valves. These patients often have concomitant mitral regurgitation. To reveal whether the moderate mitral regurgitation will improve after aortic valve replacement alone, we performed a systematic review and meta-analysis. We identified 27 studies with 4452 patients that underwent aortic valve replacement for aortic stenosis and had co-existent mitral regurgitation. Primary end point was the impact of aortic valve replacement on the concomitant mitral regurgitation. Secondary end points were the analysis of the left ventricle reverse remodeling and long-term survival. Our results showed that there was significant improvement in mitral regurgitation postoperatively (RR, 1.65; 95% CI 1.36-2.00; p < 0.00001) with the average decrease of 0.46 (WMD; 95% CI 0.35-0.57; p < 0.00001). The effect is more pronounced in the elderly population. Perioperative mortality was higher (p < 0.0001) and long-term survival significantly worse (p < 0.00001) in patients that had moderate/severe mitral regurgitation preoperatively. We conclude that after aortic valve replacement alone there are fair chances but for only slight improvement in concomitant mitral regurgitation. The secondary moderate mitral regurgitation should be addressed at the time of aortic valve replacement. A more conservative approach should be followed for elderly and high-risk patients.

Surgical Challenges of Heart Mate 3 Pump Implantation in Aneurysmally Changed Heart Ventricles.

We presented surgical treatment of three patients indicated for implantation of a permanent mechanical circulatory support device and with the associated left ventricular aneurysms. In order to evade the left ventricular rupture, adverse thromboembolic events and provide safe implantation of the inflow cannula, LVAD HM3 implantation together with the reconstruction of the left ventricular aneurysmal wall was performed in two patients. Regarding the third patient, LVAD implantation upon the reconstruction of the left ventricular wall was abandoned because there was no safe location for placement of the inflow cannula.

Application of Gray Level co-Occurrence Matrix Algorithm for Detection of Discrete Structural Changes in Cell Nuclei After Exposure to Iron Oxide Nanoparticles and 6-Hydroxydopamine.

The gray level co-occurrence matrix (GLCM) algorithm is a contemporary computational biology method which, today, is frequently used to detect small changes in texture that are not visible using conventional techniques. We demonstrate that the toxic compound 6-hydroxydopamine (6-OHDA) and iron oxide nanoparticles (IONPS) have opposite effects on GLCM features of cell nuclei. Saccharomyces cerevisiae yeast cells were treated with 6-OHDA and IONPs, and imaging with GLCM analysis was performed at three different time points: 30 min, 60 min, and 120 min after the treatment. A total of 200 cell nuclei were analyzed, and for each nucleus, 5 GLCM parameters were calculated: Angular second moment (ASM), Inverse difference moment (IDM), Contrast (CON), Correlation (COR) and Sum Variance (SVAR). Exposure to IONPs was associated with the increase of ASM and IDM while the values of SVAR and COR were reduced. Treatment with 6-OHDA was associated with the increase of SVAR and CON, while the values of nuclear ASM and IDM were reduced. This is the first study to indicate that IONPs and 6-OHDA have opposite effects on nuclear texture. Also, to the best of our knowledge, this is the first study to apply the GLCM algorithm in Saccharomyces cerevisiae yeast cells in this experimental setting.