Structurally diverse zinc(II) complexes containing tripodal tetradentate phenoxido-amines with promising antiproliferative effects.

Structurally diverse zinc(II) complexes with tripodal tetradentate phenolic-amines of variable substituents in the phenol and amine moieties were synthesized and thoroughly characterized. The two dinuclear [Zn2(L1)2](ClO4)2·MeOH (1), [Zn2(L2)2](ClO4)2 (2), and four mononuclear [Zn(L3)(H2O)]·MeOH (3), [Zn(L4)] (4), [Zn(L5)] (5) and [Zn(L6)] (6) complexes revealed distorted octahedral, trigonal-bipyramidal or tetrahedral geometries. The free HL1 and H2L3-6 ligands, and complexes 1-6 were evaluated for in vitro cytotoxicity against human cancer cell lines (A2780, A2780R, PC-3 and 22Rv1) and normal healthy MRC-5 cells. Overall results revealed high-to-moderate cytotoxicity (with the best IC50 values for complex 6 ranging from 2.4 to 4.5 µM), which is however, significantly higher than that of the reference drug cisplatin. The moderately active complexes 1-4 showed considerable selectivity on A2780 cells (IC50 ≈ 16.3-19.5 µM) over MRC-5 ones (with IC50 >50 µM for 1, 2 and 4, and with IC50 >25 µM for 3). The complexes 1, 2, and 6 and the ligand H2L6 were chosen for subsequent deeper biological evaluations. Their time-resolved cellular uptake and other cellular effects in A2780 cells were studied, such as cell cycle profile, intracellular ROS production, induction of apoptosis and activation of caspases 3/7. Complexes 1 and 2 caused significant G0/G1 cell cycle arrest in A2780 cells and antioxidant effects at normal conditions. They showed only limited effects on cellular processes connected with cytotoxicity, i.e. induction of apoptosis, depletion of mitochondrial membrane potential, and autophagy. These findings can be at least partly attributed to the low ability of the complexes to enter the A2780 cells and the depression of metabolic activity of the target cancer cells.

Determinants of Intention to Uptake COVID-19 Vaccination Among Saudi Adults: Application of the Health Belief Model.

Introduction: The pandemic caused by COVID-19 has had a profound effect on global health. Due to its potential impact on the efficacy of pandemic control measures, vaccine hesitancy (VH) in relation to COVID-19 has emerged as a significant concern. The attainment of herd immunity is contingent on the rate of COVID-19 vaccine adoption. Despite this, there have been reports of reluctance toward the COVID-19 vaccine. This study seeks to investigate the effect of constructs that influence adults' intentions to receive COVID-19 vaccination using the Health Belief Model (HBM). Methods: A cross-sectional study was conducted by recruiting Saudi Arabian adults as participants. Using Structural Equation Modeling (SEM), the proposed HBM model was evaluated. A total of 505 individuals replied to the survey. Results: The suggested HBM model explained 68% of the variation in intention to get COVID-19 immunization. I found all HBM variables namely perceived susceptibility, greater levels of perceived behavioral control, severity, benefits, and barriers to be significant predictors of vaccination intentions. Among demographic variables, only married status had a significant relationship with the intention to obtain COVID-19 immunization. Discussion: The findings of this study indicate that the HBM can be utilized effectively to obtain insight into the factors that influence COVID-19 prevention measure adherence. Understanding and recognizing individuals' perceived health beliefs and practices is essential for the development of effective COVID-19 intervention strategies.

Predicting COVID-19 vaccine uptake: Comparing the health belief model and theory of planned behavior.

The COVID-19 outbreak has had a significant impact on the global health landscape, underscoring the crucial role that vaccinations play in achieving herd immunity and reducing the effects of pandemics. Given the importance of this issue, it is imperative to gain a deeper understanding of the various factors that influence individuals' decisions to seek vaccination. This study aimed to compare the prediction level of the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and a combined model in explaining the intention of adults to receive COVID-19 immunization. A cross-sectional online survey was conducted among adults (n = 505) in Saudi Arabia. The survey contained variables related to the HBM and TPB. The prediction level of the two models as well as a combined model were evaluated utilizing Structural Equation Modeling (SEM). Among the recruited 505 participants, 88% fell within the 18 to 30 age range, and 54.5% were male. The proposed HBM model accounted for 68% of the variation in intention, whereas the TPB model explained 78.2% of the variation in COVID-19 vaccination intention. The combined model showed greater explanatory power (82%). The variables of susceptibility (ß = 0.20, p < .001), severity (ß = 0.49, p < .001), advantages (ß = 0.63, p < .001), and obstacles (ß = - 0.24, p < .001), perceptions of behavioral control (ß = 1.58, p < .001) and attitudes (ß = 0.44, p < .001) were found to significantly predict increased vaccination intentions in the combined model. However, the subjective norm construct did not significantly predict vaccination intentions (ß = 0.06, p = .34). The TPB has greater explanatory power than the HBM in predicting the intention to obtain COVID-19 vaccination. However, the combined model showed a greater prediction level. Understanding and identifying people's perceived health beliefs and practices is critical for developing successful COVID-19 intervention methods.

Tumor necrosis factor alpha induced protein 3, interleukin 10, tumor necrosis factor alpha, and interleukin 17 F genes polymorphisms in Algerian patients with rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic autoimmune disease with chronic inflammation. Its pathogenesis involves immunological, genetic, and environmental factors. We investigate the association between Tumor Necrosis Factor α Protein 3 (TNFAIP3), Interleukin 10 (IL10), Tumor Necrosis Factor α (TNF α), and Interleukin 17 F (IL17F) polymorphisms with susceptibility to RA. METHODS AND RESULTS: 191 patients with RA diagnosed according to the American College of Rheumatology (ACR)/ European League Against Rheumatism (EULAR) classification and 190 healthy subjects were recruited. Rheumatoid factor (RF), anti-citrullinated peptide antibodies (ACPA), and C-reactive protein (CRP) were measured. Genotyping of the polymorphisms was performed by real-time PCR. Analysis of the allelic frequencies of TNFAIP3 showed a positive association OR (95% CI) = 1.46 (1.01-2.09); p = 0.04, but failed to meet the criteria of significance after Bonferroni Correction. The genotypic and allelic distribution of the IL10, IL17F, and TNFα showed no significant difference when comparing the RA group with controls. Furthermore, the genotype codominant model shows a moderate positive association in the presence of ACPA (OR (95% CI) = 2.82 (1.22-6.24); p = 0.01. None of the polymorphisms studied was associated with RF and CRP production. CONCLUSION: Our results show that there is a tendency for the AG genotype of IL10-1082 to be associated with the production of ACPA in patients with RA. None of the variants studied were associated with RA susceptibility in Algerians.

The role of online hemodiafiltration with endogenous reinfusion in the treatment of systemic lupus erythematosus activity resistant to conventional therapy.

Introduction: Lupus is a diverse autoimmune disease with autoantibody formation. Lupus nephritis carries a grave prognosis. Complement involvement, namely, C1q deficiency, is linked to activity and renal involvement and could help in their assessment. LN therapies include plasma exchange, immune adsorption, and probably hemodiafiltration with online endogenous reinfusion (HFR), together with traditional immunosuppressive therapies. Aim: The aim of this study was to evaluate the role of HFR in improving signs and symptoms of systemic lupus erythematosus (SLE) activity and laboratory parameters in cases not responding to traditional immunosuppressive therapy. Settings and design: A controlled clinical study was conducted on 60 patients with lupus from Group A that was subdivided into two groups: cases 1 (47 patients), those who received traditional medical treatment, and cases 2 (13 patients), those who underwent HFR in addition to medical treatment. Group B consisted of two subgroups: control 1, composed of 20 healthy age- and sex-matched volunteers, and control 2, consisting of 10 cases with different glomerular diseases other than lupus. Methods and materials: Serum C1q was determined before and after the HFR as well as induction by medical treatment. Disease activity was assessed using SLEDAI-2K with a responder index of 50; quality of life was assessed using SLEQOL v2, and HFR was performed for the non-responder group. Results: C1q was lower in cases. It can efficiently differentiate between SLE patients and healthy controls with a sensitivity of 81.67% and a specificity of 90%. It can also efficiently differentiate between SLE patients and the control 2 group (non-lupus patients with renal glomerular disease) with a sensitivity of 83.33% and a specificity of 100%. C1q was more consumed in proliferative lupus, and correlated with anti-ds DNA, C3, and C4. Conclusions: C1q efficiently discriminates lupus patients and correlates with proliferative forms. HFR might ameliorate lupus activity and restore C1q.

Asymmetric dual-core liquid crystal channel-based tunable mode converter.

In this work, a higher order-to-fundamental mode converter is reported and analyzed based on an asymmetric dual channel waveguide (ADC-WG) on silicon. In the reported structure, one of the two waveguides is infiltrated with nematic liquid crystal (NLC) material to add temperature tunability while the other one is a solid BK7 waveguide. The modal characteristics are obtained using the full vectorial finite difference method (FVFDM). In addition, the structural parameters and optical characteristics of the employed materials are investigated to achieve good wavelength selectivity with a short device length (LD). Thus, a compact mode converter that can work at different wavelengths including the telecommunication wavelength i.e., 1.55 µm with LD ~ 482.31 µm and a low crosstalk of - 19.86 dB is presented. To prove the thermal tunability of the suggested mode converter, its operation is tested through a temperature range between 20 and 35 °C and the results show that the mode conversion process is achieved at each temperature with different phase matching wavelengths (λPMW) but with quite similar coupling length (LC). The proposed device can therefore be effectively utilized in integrated photonic circuits.

Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association.

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

B-scan measurements of intraocular tumor heights intraoperatively, before and after radioactive plaque application: A comparative prospective study.

PURPOSE: To assess the difference in intraocular tumors height measurements intraoperatively before and after radioactive plaque application. METHODOLOGY: Twenty-four eyes of 24 patients with intraocular tumors, candidates for radioactive therapy, were included. Each tumor was measured at the same setting before and after plaque application independently by 3 sonographers, using a 20-MHz B-scan transducer. Mean pre-plaque and post-plaque measurements were calculated and recorded. An A-scan vector aided in identification of the inner and outer tumor surfaces. RESULTS: Each patient was examined independently three times by three experienced ultrasonographers within the same setting to assess interobserver variability. There was no statistically significant difference between the 3 examiners' readings, with P-value 0.99 for pre-plaque height and 0.97 for post-plaque height. Mean pre-plaque height was 5.16±2.11mm, while post-plaque height was 5.51±2.1mm (P-value 0.001). The Spearman correlation test showed that initial tumor height was negatively correlated with the difference between both heights, but with no statistical significance. CONCLUSION: Intraocular tumor height measurement differs significantly before and after plaque application. Use of the pre-plaque height is advised until further studies are performed to assess the effect of this difference on treatment outcomes.

Cytoprotective potency of naringin against di-n-butylphthalate (DBP)-induced oxidative testicular damage in male rats.

The present study aimed to investigate the protective potential of naringin (NG) against di-n-butyl phthalate (DBP)- induced testicular damage and impairment of spermatogenesis in rats. Forty-two male Wistar albino rats were divided into six equal groups, and treated orally, 3 times weekly for 8 successive weeks. Control vehicle group was administrated olive oil, naringin-treated group was administered NG (80 mg/kg), DBP 250- and DBP 500- intoxicated groups received DBP (250 mg/kg) and (500 mg/kg), respectively, NG + DBP 250 and NG + DBP 500 groups received NG, an hour prior to DBP 250 and 500 administration. The results revealed that DBP induced dose-dependent male reproductive dysfunctions, included a significant decrease in the serum testosterone level concomitantly with significant decreases in the sperm count, viability, and total motility. Meanwhile, DBP significantly increased the testicular malondialdehyde level with significant reductions of glutathione content and catalase activity. Histopathologically, DBP provoked absence of spermatozoa, degenerative changes in the cell layers of seminiferous tubules and a significant decrease in the thickness of the seminiferous tubules epithelium. Conversely, the concomitant treatment with NG, one hour before DBP 250 or 500- intoxication mitigated the dose-dependent reproductive dysfunctions induced by DBP, evidenced by significant increases of serum testosterone level, sperm motility, count and viability along with marked improvement of the oxidant/antioxidant status and testicular histoarchitecture. In conclusion, the findings recorded herein proved that NG could mitigate DBP-induced testicular damage and impairment of spermatogenesis, suggesting the perspective of using NG as a natural protective and therapeutic agent for alleviating the reproductive dysfunctions and improving reproductive performance, mainly via its potent antioxidant activity.

Permeation Flux Prediction of Vacuum Membrane Distillation Using Hybrid Machine Learning Techniques.

Vacuum membrane distillation (VMD) has attracted increasing interest for various applications besides seawater desalination. Experimental testing of membrane technologies such as VMD on a pilot or large scale can be laborious and costly. Machine learning techniques can be a valuable tool for predicting membrane performance on such scales. In this work, a novel hybrid model was developed based on incorporating a spotted hyena optimizer (SHO) with support vector machine (SVR) to predict the flux pressure in VMD. The SVR-SHO hybrid model was validated with experimental data and benchmarked against other machine learning tools such as artificial neural networks (ANNs), classical SVR, and multiple linear regression (MLR). The results show that the SVR-SHO predicted flux pressure with high accuracy with a correlation coefficient (R) of 0.94. However, other models showed a lower prediction accuracy than SVR-SHO with R-values ranging from 0.801 to 0.902. Global sensitivity analysis was applied to interpret the obtained result, revealing that feed temperature was the most influential operating parameter on flux, with a relative importance score of 52.71 compared to 17.69, 17.16, and 14.44 for feed flowrate, vacuum pressure intensity, and feed concentration, respectively.

Ventricular tachycardia and in-hospital mortality in the intensive care unit.

Background: Continuous electrocardiographic (ECG) monitoring is used to identify ventricular tachycardia (VT), but false alarms occur frequently. Objective: The purpose of this study was to assess the rate of 30-day in-hospital mortality associated with VT alerts generated from bedside ECG monitors to those from a new algorithm among intensive care unit (ICU) patients. Methods: We conducted a retrospective cohort study in consecutive adult ICU patients at an urban academic medical center and compared current bedside monitor VT alerts, VT alerts from a new-unannotated algorithm, and true-annotated VT. We used survival analysis to explore the association between VT alerts and mortality. Results: We included 5679 ICU admissions (mean age 58 ± 17 years; 48% women), 503 (8.9%) experienced 30-day in-hospital mortality. A total of 30.1% had at least 1 current bedside monitor VT alert, 14.3% had a new-unannotated algorithm VT alert, and 11.6% had true-annotated VT. Bedside monitor VT alert was not associated with increased rate of 30-day mortality (adjusted hazard ratio [aHR] 1.06; 95% confidence interval [CI] 0.88-1.27), but there was an association for VT alerts from our new-unannotated algorithm (aHR 1.38; 95% CI 1.12-1.69) and true-annotated VT(aHR 1.39; 95% CI 1.12-1.73). Conclusion: Unannotated and annotated-true VT were associated with increased rate of 30-day in-hospital mortality, whereas current bedside monitor VT was not. Our new algorithm may accurately identify high-risk VT; however, prospective validation is needed.

Examining health sciences students' intention to uptake COVID-19 vaccination using the theory of planned behavior.

To examine the association between the theory of planned behavior (TPB) constructs and Health Sciences students' intentions to receive COVID-19 vaccination. A cross-sectional study was conducted in Saudi Arabia by recruiting Health Sciences students as participants. Using Structural Equation Modeling (SEM), the proposed TPB model was evaluated. The sample of 505 individuals consisted of more males (n = 275; 54.5%) than females and was relatively young (88% were between the ages of 18 and 30). The suggested TPB model explained 78.2% of the variation in intention to get COVID-19 immunization. We found that greater levels of perceived behavioral control (ß = 1.58, p < .001) and attitude (ß = .44, p < .001) strongly predicted increased vaccination intentions. The subjective norm construct was not a significant predictor of vaccination intentions (ß = 0.06, p = .34). The findings of this study indicate that the TPB can be utilized effectively to obtain insight into the factors associated with COVID-19 adherence and help in the development of effective COVID-19 intervention strategies.

Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction.

Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting electrocardiogram (ECG) are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but, currently, there are no accurate tools to identify them during initial triage. Here we report, to our knowledge, the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI. Using 7,313 consecutive patients from multiple clinical sites, we derived and externally validated an intelligent model that outperformed practicing clinicians and other widely used commercial interpretation systems, substantially boosting both precision and sensitivity. Our derived OMI risk score provided enhanced rule-in and rule-out accuracy relevant to routine care, and, when combined with the clinical judgment of trained emergency personnel, it helped correctly reclassify one in three patients with chest pain. ECG features driving our models were validated by clinical experts, providing plausible mechanistic links to myocardial injury.

Unsupervised machine learning identifies symptoms of indigestion as a predictor of acute decompensation and adverse cardiac events in patients with heart failure presenting to the emergency department.

BACKGROUND: Patients with known heart failure (HF) present to emergency departments (ED) with a plethora of symptoms. Although symptom clusters have been suggested as prognostic features, accurately triaging HF patients is a longstanding challenge. OBJECTIVES: We sought to use machine learning to identify subtle phenotypes of patient symptoms and evaluate their diagnostic and prognostic value among HF patients seeking emergency care. METHODS: This was a secondary analysis of a prospective cohort study of consecutive patients seen in the ED for chest pain or equivalent symptoms. Independent reviewers extracted clinical data from charts, including nine categories of subjective symptoms reported during initial evaluation. The diagnostic outcome was acute HF exacerbation and prognostic outcome was 30-day major adverse cardiac events (MACE). Outcomes were adjudicated by two independent reviewers. K-means clustering was used to derive latent patient symptom clusters, and their associations with outcomes were assessed using multivariate logistic regression. RESULTS: Sample included 438 patients (age 65±14 years; 45% female, 49% Black, 18% HF exacerbation, 32% MACE). K-means clustering identified three presentation phenotypes: patients with dyspnea only (Cluster A, 40%); patients with indigestion, with or without dyspnea (Cluster B, 23%); patients with neither dyspnea nor indigestion (Cluster C, 37%). Compared to Cluster C, indigestion was a significant predictor of acute HF exacerbation (OR=1.8, 95%CI=1.0-3.4) and 30-day MACE (OR=1.8, 95%CI=1.0-3.1), independent of age, sex, race, and other comorbidities. CONCLUSION: Indigestion symptoms in patients with known HF signify excess risk of adverse events, suggesting that these patients should be triaged as high-risk during initial ED evaluation.

Broadband Photon Harvesting in Organic Photovoltaic Devices Induced by Large-Area Nanogrooved Templates.

Thin-film organic photovoltaic (OPV) devices represent an attractive alternative to conventional silicon solar cells due to their lightweight, flexibility, and low cost. However, the relatively low optical absorption of the OPV active layers still represents an open issue in view of efficient devices that cannot be addressed by adopting conventional light coupling strategies derived from thick PV absorbers. The light coupling to thin-film solar cells can be boosted by nanostructuring the device interfaces at the subwavelength scale. Here, we demonstrate broadband and omnidirectional photon harvesting in thin-film OPV devices enabled by highly ordered one-dimensional (1D) arrays of nanogrooves. Laser interference lithography, in combination with reactive ion etching (RIE), provides the controlled tailoring of the height and periodicity of the silica grooves, enabling effective tuning of the anti-reflection properties in the active organic layer (PTB7:PCBM). With this strategy, we demonstrate a strong enhancement of the optical absorption, as high as 19% with respect to a flat device, over a broadband visible and near-infrared spectrum. The OPV device supported on these optimized nanogrooved substrates yields a 14% increase in short-circuit current over the corresponding flat device, highlighting the potential of this large-scale light-harvesting strategy in the broader context of thin-film technologies.

Impact of daily use of emollient 'plus' on corticosteroid consumption in patients with atopic dermatitis: An open, randomized controlled study.

BACKGROUND: Emollients are the baseline treatment for mild or moderate atopic dermatitis (AD) to improve the epidermal barrier and provide anti-irritant and anti-pruritic effects. Emollient 'plus' can influence the skin microbiome of atopic eczema patients. OBJECTIVES: To evaluate the benefits of using Emollient 'plus' to reduce corticosteroid consumption. METHODS: In an open, single-centre, randomized, controlled study, patients with mild to moderate AD (Severity scoring of AD [SCORAD] score 20-30) were randomized 1:1 to apply the Emollient 'plus' twice daily for 28 days or to continue with their usual classical emollient (Control group). In addition, each patient received topical corticosteroids to use when necessary and according to the dermatologist's prescription. Assessments included SCORAD, PO-SCORAD, local SCORAD, quality of life questionnaires, and tolerability. RESULTS: A total of 119 patients were included in the PP population with a mean age of 26.50 ± 17.5 years old (min-max 3-71 years). Between baseline and day 28, the mean amount of corticosteroid used was lower for the Emollient 'plus' versus Control group (6.03 vs. 9.16 g; p = 0.041) and corticosteroid was applied on fewer days (37.5% vs. 46.9% of days; p = 0.0256) with fewer applications per day (0.55 vs. 0.71 applications per day; p = 0.0203). Similar improvements were observed in both groups for SCORAD, PO-SCORAD, local SCORAD, skin sensation score, AD burden scale, patient benefit index >1, as well as subject and investigator efficacy and tolerability questionnaire assessments. CONCLUSIONS: Between baseline and day 28, there was significant corticosteroid-sparing in the Emollient 'plus' group compared to the Control group in quantity, number of applications per day and number of days of use, whilst efficacy was maintained with no significant differences between the two groups for all clinical evaluations, as well as for tolerability.