Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.

This study focuses on developing machine learning models to detect subtle alterations in hepatocyte chromatin organization due to Iron (II, III) oxide nanoparticle exposure, hypothesizing that exposure will significantly alter chromatin texture. A total of 2000 hepatocyte nuclear regions of interest (ROIs) from mouse liver tissue were analyzed, and for each ROI, 5 different parameters were calculated: Long Run Emphasis, Short Run Emphasis, Run Length Nonuniformity, and 2 wavelet coefficient energies obtained after the discrete wavelet transform. These parameters served as input for supervised machine learning models, specifically random forest and gradient boosting classifiers. The models demonstrated relatively robust performance in distinguishing hepatocyte chromatin structures belonging to the group exposed to IONPs from the controls. The study's findings suggest that iron oxide nanoparticles induce substantial changes in hepatocyte chromatin distribution and underscore the potential of AI techniques in advancing hepatocyte evaluation in physiological and pathological conditions.

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.

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.

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.