ROS-responsive charge reversal mesoporous silica nanoparticles as promising drug delivery system for neovascular retinal diseases.

Intravitreal injection of biodegradable implant drug carriers shows promise in reducing the injection frequency for neovascular retinal diseases. However, current intravitreal ocular devices have limitations in adjusting drug release rates for individual patients, thereby affecting treatment effectiveness. Accordingly, we developed mesoporous silica nanoparticles (MSNs) featuring a surface that reverse its charge in response to reactive oxygen species (ROS) for efficient delivery of humanin peptide (HN) to retinal epithelial cells (ARPE-19). The MSN core, designed with a pore size of 2.8 nm, ensures a high HN loading capacity 64.4% (w/w). We fine-tuned the external surface of the MSNs by incorporating 20% Acetyl-L-arginine (Ar) to create a partial positive charge, while 80% conjugated thioketal (TK) methoxy polyethylene glycol (mPEG) act as ROS gatekeeper. Ex vivo experiments using bovine eyes revealed the immobilization of Ar-MSNs-TK-PEG (mean zeta potential: 2 mV) in the negatively charged vitreous. However, oxidative stress reversed the surface charge to -25 mV by mPEG loss, facilitating the diffusion of the nanoparticles impeded with HN. In vitro studies showed that ARPE-19 cells effectively internalize HN-loaded Ar-MSNs-TK, subsequently releasing the peptide, which offered protection against oxidative stress-induced apoptosis, as evidenced by reduced TUNEL and caspase3 activation. The inhibition of retinal neovascularization was further validated in an in vivo oxygen-induced retinopathy (OIR) mouse model.

Determination of percentage elongation at break and histopathology of skin from yankasa sheep experimentally infested with Amblyomma variegatum.

Bites of haematophagous ectoparasites cause mechanical injuries and histopathological changes in their hosts' hides and skins whose resultant leathers become unsuitable for certain leather products. The effects of tick bites on the wellbeing of their hosts are known, however, knowledge of their effects on the quality of leathers is scarce. This work investigated the effects of tick bites on the histopathology of skin and the percentage elongation at break (PEB) of shoe upper leathers produced from the skins of Amblyomma variegatum infested Yankasa sheep. A total of nine apparently healthy Yankasa sheep were selectively purchased from the open market and acclimatized for four weeks in the laboratory. Three animals in each of group 1 and 2 were infested with 40 nymphs and 20 adults of Am. variegatum respectively. Group three animals served as uninfested control. All animals were euthanized after the ticks were fully engorged and detached. Skin biopsies at tick attachment points and the uninfested control were taken from flayed skins and processed for histopathological examination. All skins were processed into finished leathers and their PEB determined. Histopathological studies revealed keratinization in all Am. variegatum infested sheep skins, while the un-infested control skins were normal. Mean PEB (%) of leathers were 21.41±3.33SE (nymphs), 36.73±4.44SE (adults) and 47.83±2.78SE (control). Bites of Am. variegatum cause histopathological changes in Yankasa sheep skins that significantly (p = 0.006) reduce the PEB of resultant leathers to less than the acceptable minimum standard of 40 % whose leathers are classified as rejects. In this study, skin of Yankasa sheep infested by nymphs and adults of Am. variegatum ticks resulted in low quality leathers that are unsuitable for standard leather products production and are also of low market value due to keratinization. Sustained efforts need to be undertaken to increase the awareness on the negative impact of tick bites on leather products by encouraging livestock farmers to engage in early treatment of animals infested with ticks.

Photo-Cross-linked Gelatin Methacryloyl Hydrogels Enable the Growth of Primary Human Endometrial Stromal Cells and Epithelial Gland Organoids.

In vitro three-dimensional (3D) models are better able to replicate the complexity of real organs and tissues than 2D monolayer models. The human endometrium, the inner lining of the uterus, undergoes complex changes during the menstrual cycle and pregnancy. These changes occur in response to steroid hormone fluctuations and elicit crosstalk between the epithelial and stromal cell compartments, and dysregulations are associated with a variety of pregnancy disorders. Despite the importance of the endometrium in embryo implantation and pregnancy establishment, there is a lack of in vitro models that recapitulate tissue structure and function and as such a growing demand for extracellular matrix hydrogels that can support 3D cell culture. To be physiologically relevant, an in vitro model requires mechanical and biochemical cues that mimic those of the ECM found in the native tissue. We report a semisynthetic gelatin methacryloyl (GelMA) hydrogel that combines the bioactive properties of natural hydrogels with the tunability and reproducibility of synthetic materials. We then describe a simple protocol whereby cells can quickly be encapsulated in GelMA hydrogels. We investigate the suitability of GelMA hydrogel to support the development of an endometrial model by culturing the main endometrial cell types: stromal cells and epithelial cells. We also demonstrate how the mechanical and biochemical properties of GelMA hydrogels can be tailored to support the growth and maintenance of epithelial gland organoids that emerge upon 3D culturing of primary endometrial epithelial progenitor cells in a defined chemical medium. We furthermore demonstrate the ability of GelMA hydrogels to support the viability of stromal cells and their function measured by monitoring decidualization in response to steroid hormones. This study describes the first steps toward the development of a hydrogel matrix-based model that recapitulates the structure and function of the native endometrium and could support applications in understanding reproductive failure.

Efficacy, tolerability, and bone density outcomes of elagolix with add-back therapy for endometriosis-associated pain: 12 months of an ongoing randomized phase 3 trial.

BACKGROUND: Elagolix, an approved oral treatment for endometriosis-associated pain, has been associated with hypoestrogenic effects when used as monotherapy. Hormonal add-back therapy has the potential to mitigate these effects. OBJECTIVE: To evaluate efficacy, tolerability, and bone density outcomes of elagolix 200 mg twice daily with 1 mg estradiol /0.5 mg norethindrone acetate (add-back) therapy once daily compared with placebo in premenopausal women with moderate-to-severe endometriosis-associated pain. STUDY DESIGN: This ongoing, 48-month, phase 3 study consists of a 12-month, double-blind period, with randomization 4:1:2 to elagolix 200 mg twice daily with add-back therapy, elagolix 200 mg twice daily monotherapy for 6 months followed by elagolix with add-back therapy, or placebo. The co-primary endpoints were proportion of patients with clinical improvement (termed "responders") in dysmenorrhea and nonmenstrual pelvic pain at month 6. We report 12-month results on efficacy of elagolix with add-back therapy versus placebo in reducing dysmenorrhea, nonmenstrual pelvic pain, dyspareunia, and fatigue. Tolerability assessments include adverse events and change from baseline in bone mineral density. RESULTS: A total of 679 patients were randomized to elagolix with add-back therapy (n=389), elagolix monotherapy (n=97), or placebo (n=193). Compared with patients randomized to placebo, a significantly greater proportion of patients randomized to elagolix with add-back therapy responded with clinical improvement in dysmenorrhea (62.8% versus 23.7%; P≤.001) and nonmenstrual pelvic pain (51.3% versus 36.8%; P≤.001) at 6 months. Compared with placebo, elagolix with add-back therapy produced significantly greater improvement from baseline in 7 hierarchically ranked secondary endpoints including dysmenorrhea (months 12, 6, 3), nonmenstrual pelvic pain (months 12, 6, 3), and fatigue (months 6) (all P<.01). Overall, the incidence of adverse events was 73.8% with elagolix plus add-back therapy and 66.8% with placebo. The rate of severe and serious adverse events did not meaningfully differ between treatment groups. Study drug discontinuations associated with adverse events were low in patients receiving elagolix with add-back therapy (12.6%) and those receiving placebo (9.8%). Patients randomized to elagolix monotherapy exhibited decreases from baseline in bone mineral density of -2.43% (lumbar spine), -1.54% (total hip), and -1.78% (femoral neck) at month 6. When add-back therapy was added to elagolix at month 6, the change from baseline in bone mineral density remained in a similar range of -1.58% to -1.83% at month 12. However, patients who received elagolix plus add-back therapy from baseline exhibited little change from baseline in bone mineral density (<1% change) at months 6 and 12. CONCLUSION: Compared with placebo, elagolix with add-back therapy resulted in significant, clinically meaningful improvement in dysmenorrhea, nonmenstrual pelvic pain, and fatigue at 6 months that continued until month 12 for both dysmenorrhea and nonmenstrual pelvic pain. Elagolix with add-back therapy was generally well tolerated. Loss of bone mineral density at 12 months was greater in patients who received elagolix with add-back therapy than those who received placebo. However, the change in bone mineral density with elagolix plus add-back therapy was < 1% and was attenuated compared with bone loss observed with elagolix monotherapy.

ALLOPURINOL TREATMENT IMPROVES INSULIN RESISTANCE IN NON-DIABETIC PATIENTS WITH RENAL STONE.

Hyperuricemia is an objective risk factor of derangement of fasting serum glucose and type 2 diabetes (T2D), yet whether hyperuricemia has a causative influence on insulin resistance is still debatable. In this study, we tested the hypothesis that lowering uric acid in hyperuricemic nondiabetic subjects might improve insulin resistance. Patients with renal stone and hyperuricemia (n=15) were recruited from the private clinic of Ib-Sina Local Teaching Hospital in Mosul city and prospectively placed on allopurinol (300mg/day) for 6 months. Serum uric acid (SUA), fasting serum glucose (FSG), fasting insulin, and C-peptide were measured using commercial kits. Results confirmed that allopurinol has significantly (P<0.05) reduced c-peptide and insulin together with a non-significant (p>0.05) reduction of serum glucose levels. In conclusion, allopurinol has improved insulin level and glycemic control in a healthy individual, these findings could be used as a template for using allopurinol in diabetic patients to improve glycemic control or future studies could be directed toward structural modification of allopurinol which hopefully might lead to innovation of new antidiabetic drugs.

Side-specific factors for intraoperative hemodynamic instability in laparoscopic adrenalectomy for pheochromocytoma: a comparative study.

BACKGROUND: Adrenalectomy for pheochromocytoma (PHEO) is challenging because of the high risk of intraoperative hemodynamic instability (HDI). This study aimed to compare the incidence and risk factors of intraoperative HDI between laparoscopic left adrenalectomy (LLA) and laparoscopic right adrenalectomy (LRA). METHODS: We retrospectively analyzed two hundred and seventy-one patients aged > 18 years with unilateral benign PHEO of any size who underwent transperitoneal laparoscopic adrenalectomy at our hospitals between September 2016 and September 2023. Patients were divided into LRA (N = 122) and LLA (N = 149) groups. Univariate and multivariate logistic regression analyses were used to predict intraoperative HDI. In multivariate analysis for the prediction of HDI, right-sided PHEO, PHEO size, preoperative comorbidities, and preoperative systolic blood pressure were included. RESULTS: Intraoperative HDI was significantly higher in the LRA group than in the LLA (27% vs. 9.4%, p < 0.001). In the multivariate regression analysis, right-sided tumours showed a higher risk of intraoperative HDI (odds ratio [OR] 5.625, 95% confidence interval [CI], 1.147-27.577, p = 0.033). The tumor size (OR 11.019, 95% CI 3.996-30.38, p < 0.001), presence of preoperative comorbidities [diabetes mellitus, hypertension, and coronary heart disease] (OR 7.918, 95% CI 1.323-47.412, p = 0.023), and preoperative systolic blood pressure (OR 1.265, 95% CI 1.07-1.495, p = 0.006) were associated with a higher risk of HDI in both LRA and LLA, with no superiority of one side over the other. CONCLUSION: LRA was associated with a significantly higher intraoperative HDI than LLA. Right-sided PHEO was a risk factor for intraoperative HDI.

Employing students' evaluations and tutors' perceptions to evaluate a faculty development program on problem-based learning at the Faculty of Medicine, King Abdulaziz University.

BACKGROUND: Faculty development programs are crucial for promoting continuous learning, enhancing teaching effectiveness, and encouraging professional growth among medical educators. Problem-based learning was introduced as a teaching strategy in our Faculty of Medicine in 2007. Thereafter, several rounds of a faculty development program were conducted to help teachers recognize their role as facilitators and assess areas for improvement. METHODS: We conducted a mixed-methods study with a sample of 284 third-year medical students answering a questionnaire and 21 faculty members participating in focus groups. A validated 13-item questionnaire was used to investigate the students' evaluation of their tutors' performance in problem-based learning. Three sessions were then conducted with faculty members involved in problem-based learning to gain in-depth insights into their experiences and perspectives. RESULTS: The mean performance ranking for tutors awarded by the students was above halfway. There was a significant positive correlation between tutors' performance ranking and all five of the learning approaches examined herein: constructive/active learning, self-directed learning, contextual learning, collaborative learning, and intra-personal behavior (p < 0.05). The data from the focus groups were analyzed under five broad themes: tutors' insights into their strengths and weaknesses, challenges in conducting problem-based learning, tutors' ways of preparing for problem-based learning, feedback, and suggestions for improving problem-based learning workshops. CONCLUSIONS: This study recommends improvements and future directions for advanced program evaluation. Faculty development programs can be tailored to effectively address students and faculty members' goals and needs, which can benefit the teaching and learning process and foster a culture of continuous improvement and professional growth.

Patient Outcomes and Management Strategies for Intensive Care Unit (ICU)-Associated Delirium: A Literature Review.

Delirium is a significant public health concern, with tremendous implications for patient outcomes. Intensive care unit (ICU)-related delirium is gaining attention due to the higher prevalence of delirium in ICU-admitted patients. The most common negative outcomes of ICU delirium include cognitive impairments, functional dependence, high incidence of mortality, extended stay in the ICU, and high costs. So far, no single etiological factor has been identified as the sole cause of delirium. Several functional, neurotransmitter, or injury-causing hypotheses have been proposed for ICU delirium. Several risk factors contribute to the development of delirium in patients admitted to the ICU. These are age, gender, types of sedation, physical restraints, medical and surgical interventions, pain, and extended stay in the ICU. The most commonly used assessment modules for ICU delirium are the PREdiction of DELIRium in ICu patients (PRE-DELIRIC), Early PREdiction model for DELIRium in ICu patients (E-PRE-DELERIC), and Lanzhou Model, Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), Intensive Care Delirium Screening Checklist (ICDSC), and Delirium Rating Scale (DRS). There is no proper treatment for ICU delirium; however, it can be managed through various pharmacological and non-pharmacological interventions. Healthcare providers should receive constant education and training on delirium recognition, prevention, and management to enhance patient care and outcomes in the ICU. Further research is needed on the effective prevention and management of ICU delirium.

A hybrid model for the detection of retinal disorders using artificial intelligence techniques.

The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularization, diabetic macular edema, drusen, and normal cases. This study proposed a new framework that combines machine learning and deep learning-based techniques. The utilized classifiers were support vector machine (SVM), K-nearest neighbor (K-NN), decision tree (DT), and ensemble model (EM). A feature extractor, the InceptionV3 convolutional neural network, was also employed. The performance of the models was evaluated against nine criteria using a dataset of 18000 OCT images. For the SVM, K-NN, DT, and EM classifiers, the analysis exhibited state-of-the-art performance, with classification accuracies of 99.43%, 99.54%, 97.98%, and 99.31%, respectively. A promising methodology has been introduced for the automatic identification and classification of retinal disorders, leading to reduced human error and saved time.

Repurposing ezetimibe as a neuroprotective agent in a rotenone-induced Parkinson's disease model in rats: Role of AMPK/SIRT-1/PGC-1α signaling and autophagy.

As a severe neurological disorder, Parkinson's disease (PD) is distinguished by dopaminergic neuronal degeneration in the substantia nigra (SN), culminating in motor impairments. Several studies have shown that activation of the AMPK/SIRT1/PGC1α pathway contributes to an increase in mitochondrial biogenesis and is a promising candidate for the management of PD. Furthermore, turning on the AMPK/SIRT1/PGC1α pathway causes autophagy activation, which is fundamental for maintaining neuronal homeostasis. Interestingly, ezetimibe is an antihyperlipidemic agent that was recently reported to possess pleiotropic properties in neurology by triggering the phosphorylation and activation of AMPK. Thus, our study aimed to investigate the neuroprotective potential of ezetimibe in rats with rotenone-induced PD by activating AMPK. Adult male Wistar rats received rotenone (1.5 mg/kg, s.c.) every other day for 21 days to induce experimental PD. Rats were treated with ezetimibe (5 mg/kg/day, i.p.) 1 h before rotenone. Ezetimibe ameliorated the motor impairments in open field, rotarod and grip strength tests, restored striatal dopamine and tyrosine hydroxylase in the SN, up-regulated p-AMPK, SIRT1, and PGC1α striatal expression, upsurged the expression of ULK1, beclin1, and LC3II/I, reduced Bax/Bcl2 ratio, and alleviated rotenone-induced histopathological changes in striatum and SN. Our findings also verified the contribution of AMPK activation to the neuroprotective effect of ezetimibe by using the AMPK inhibitor dorsomorphin. Together, this work revealed that ezetimibe exerts a neuroprotective impact in rotenone-induced PD by activating AMPK/SIRT-1/PGC-1α signaling, enhancing autophagy, and attenuating apoptosis. Thus, ezetimibe's activation of AMPK could hold significant therapeutic promise for PD management.

Tailoring neo/adjuvant systemic therapy in breast cancer: "The advent of a personalized approach"-The Breast-Gynecological and Immuno-Oncology International Cancer Conference (BGICC) consensus and recommendations.

BACKGROUND: The management of early breast cancer (BC) has witnessed an uprise in the use of neoadjuvant therapy and a remarkable reshaping of the systemic therapy postneoadjuvant treatment in the last few years, with the evolution of many controversial clinical situations that require consensus. METHODS: During the 14th Breast-Gynecological and Immuno-Oncology International Cancer Conference held in Egypt in 2022, a panel of 44 BC experts from 13 countries voted on statements concerning debatable challenges in the neo/adjuvant treatment setting. The recommendations were subsequently updated based on the most recent data emerging. A modified Delphi approach was used to develop this consensus. A consensus was achieved when ≥75% of voters selected an answer. RESULTS AND CONCLUSIONS: The consensus recommendations addressed different escalation and de-escalation strategies in the setting of neoadjuvant therapy for early BC. The recommendations recapitulate the available clinical evidence and expert opinion to individualize patient management and optimize therapy outcomes. Consensus was reached in 63% of the statements (52/83), and the rationale behind each statement was clarified.

Flipped classroom orthodontic education for undergraduate dental students: A factor analysis study.

INTRODUCTION: Dental schools have a primary responsibility to devise a curriculum that enhances students' confidence and knowledge in orthodontic case analysis. This study aims to compare the confidence levels and performance of undergraduate students in orthodontic case screening, moderated by faculty in a lecture-based format against their self-analysis of the same cases 1 year later, using a case-based and flipped learning approach. MATERIALS AND METHODS: This study involved 100 fifth-year students. The same group received predoctoral orthodontics training through an instructor-centered, didactic approach in their fifth year and a case-based, student-centered, flipped classroom approach in their sixth year. At the end of each semester, the students completed an orthodontic case analysis and a self-reflection survey. RESULTS: This study found no significant differences in diagnostic capabilities for orthodontic findings between the two methods studied. However, the self-evaluation survey data revealed an increase in students' confidence levels. This was specifically in terms of carrying out independent orthodontic case diagnosis, effectively communicating with orthodontic specialists, and their comfort in approaching orthodontic cases following the flipped classroom approach. Despite increased confidence in case diagnosis, the results showed that final-year students are uncertain about creating initial treatment plans and referring cases at an early stage. CONCLUSION: Despite no observed improvement in students' orthodontic diagnostic abilities after another semester of student-centered learning, their confidence in diagnosing orthodontic cases was notably enhanced.

Boosting the Anti-Helicobacter Efficacy of Azithromycin through Natural Compounds: Insights From In Vitro, In Vivo, Histopathological, and Molecular Docking Investigations.

BACKGROUND: Antimicrobial-resistant Helicobacter pylori (H. pylori) poses a significant public health concern, especially given the limited therapeutic options for azithromycin-resistant strains. Hence, there is a necessity for new studies to reconsider the use of azithromycin, which has diminished in effectiveness against numerous strains. Thus, we aimed to augment azithromycin's anti-Helicobacter properties by combining it with curcumin in different formulations, including curcumin in clove oil, curcumin nano-gold emulsion, and curcumin nanoemulsion. METHODS: The antimicrobial activities of the investigated compounds, both individually and in combination with other anti-Helicobacter drugs, were evaluated. Their antibiofilm and anti-virulence properties were assessed using both phenotypic and genotypic methods, alongside molecular docking studies. Our findings were further validated through mouse protection assays and histopathological analysis. RESULTS: We observed high anti-Helicobacter activities of curcumin, especially curcumin nanoemulsion. A synergistic effect was detected between curcumin nanoemulsion and azithromycin with fraction inhibitory concentration index (FICI) values <0.5. The curcumin nanoemulsion was the most active anti-biofilm and anti-virulence compound among the examined substances. The biofilm-correlated virulence genes (babA and hopQ) and ureA genes were downregulated (fold change <1) post-treatment with curcumin nanoemulsion. On the protein level, the anti-virulence activities of curcumin nanoemulsion were documented based on molecular docking studies. These findings aligned with histopathological scoring of challenge mice, affirming the superior efficacy of curcumin nanoemulsion/azithromycin combination. CONCLUSION: The anti-Helicobacter activities of all curcumin physical forms pose significant challenges due to their higher  minimum inhibitory concentration (MIC) values exceeding the maximum permissible level. However, using curcumin nanoemulsion at sub-MIC levels could enhance the anti-Helicobacter activity of azithromycin and exhibit anti-virulence properties, thereby improving patient outcomes and addressing resistant pathogens. Therefore, more extensive studies are necessary to assess the safety of incorporating curcumin nanoemulsion into H. pylori treatment.

Experimental investigation of multi-step airfoils in low Reynolds numbers applications.

This study provides a detailed analysis of the aerodynamic performance of various airfoil configurations, focusing on lift coefficient, stall characteristics, and maximum lift-to-drag ratio. The investigation includes the NACA23012C profile and configurations with different step geometries, ranging from one-step to five-step designs. Experimental measurements were conducted using a well-equipped aerodynamic laboratory, Institute of Aviation Engineering and Technology (IAET), Giza, Egypt. The lab features a wind tunnel, propeller test rig, and data acquisition system. The experiments were conducted meticulously to ensure accuracy and reproducibility, with a standardized method employed for uncertainty analysis. The results reveal distinct aerodynamic behaviors among the different configurations, highlighting the significant impact of design variations on aerodynamic performance. Notably, the three-step configuration consistently exhibited high performance, with a competitive or superior lift coefficient across a range of Reynolds numbers, showing an improvement of up to 35.1 %. Similarly, the four-step configuration demonstrated substantial increases in lift-to-drag ratios, reaching up to 53.2 %, while the five-step configuration exhibited varying trends with a minimum drag coefficient. The study also investigated stall characteristics and sensitivity to Reynolds numbers, revealing the complex trade-offs inherent in airfoil design. The findings provide valuable insights into optimizing airfoil performance under different operational conditions. Additionally, the adoption of two and three stepped airfoils resulted in significant reductions in blade material and associated costs for turbine blades.

Development of low-cost micro-fabrication procedures for planar micro-thermoelectric generators based on thin-film technology for energy harvesting applications.

With the rapid proliferation of portable and wearable electronics, energy autonomy through efficient energy harvesting has become paramount. Thermoelectric generators (TEGs) stand out as promising candidates due to their silent operation, high reliability, and maintenance-free nature. This paper presents the design, fabrication, and analysis of a micro-scale TEG for powering such devices. A planar configuration was employed for its inherent miniaturization advantages. Finite element analysis using ANSYS reveals that a double-layer device under a 50 K temperature gradient generates an impressive open-circuit voltage of 1417 mV and a power output of 2.4 µW, significantly exceeding its single-layer counterpart (226 mV, 0.12 µW). Validation against the analytical model results yields errors within 2.44% and 2.03% for voltage and power, respectively. Furthermore, a single-layer prototype fabricated using paper shadow masks and sputtering deposition exhibits a voltage of 131 mV for a 50 K temperature difference, thus confirming the feasibility of the proposed design. This work establishes a foundation for developing highly efficient micro-TEGs for powering next-generation portable and wearable electronics.

RETRACTED: External pop-out versus classic technique for delivery of the fetal head during elective cesarean section: A randomized clinical trial.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief and the Journal's Ethics Committee. After post-publication investigation, issues related to the following were identified in the article: To facilitate a thorough examination and ensure the accuracy of the information reported in the article, the authors were asked for the raw data of the article. In the absence of an answer from the authors, a decision to retract the article was made in accordance with the journal's commitment to upholding the highest standards of scientific integrity and accuracy in published research.

Performance Evaluation of Sinusoidal Power Supplies for Ozone Generation in Water Purification Applications.

Ozone generation is a water disinfection method, superior to chlorine in terms of fewer byproducts and no residual taste. However, its high production cost limits its widespread adoption. This paper designs an ozone generation sinusoidal power supply for water treatment. Ozone generation requires a high-frequency and high-voltage power supply to produce ozone from oxygen molecules. The study evaluates two power supply topologies, one with a parallel LC filter and the other with an LCL filter, assessing their feasibility, effectiveness, and reliability. Theoretically, the LCL filter achieves higher gains than the parallel LC filter. The larger inductance in the parallel LC filter reduces gain, while the larger inductance in the LCL filter increases gain. Simulation and practical results validate these findings, achieving gains of 40 for the parallel LC filter and 150 for the LCL filter.

Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G smart cities' IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework.

The growing importance of edge and fog computing in the modern IT infrastructure is driven by the rise of decentralized applications. However, resource allocation within these frameworks is challenging due to varying device capabilities and dynamic network conditions. Conventional approaches often result in poor resource use and slowed advancements. This study presents a novel strategy for enhancing resource allocation in edge and fog computing by integrating machine learning with the blockchain for reliable trust management. Our proposed framework, called CyberGuard, leverages the blockchain's inherent immutability and decentralization to establish a trustworthy and transparent network for monitoring and verifying edge and fog computing transactions. CyberGuard combines the Trust2Vec model with conventional machine-learning models like SVM, KNN, and random forests, creating a robust mechanism for assessing trust and security risks. Through detailed optimization and case studies, CyberGuard demonstrates significant improvements in resource allocation efficiency and overall system performance in real-world scenarios. Our results highlight CyberGuard's effectiveness, evidenced by a remarkable accuracy, precision, recall, and F1-score of 98.18%, showcasing the transformative potential of our comprehensive approach in edge and fog computing environments.

Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs.

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients' chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model's input requirements, we enhanced them through data augmentation techniques for training purposes. We evaluated the model's performance by analyzing the precision, recall, and F1 scores across training, validation, and testing datasets. The results show that the ResNet50 model outperformed VGG16 with accuracy and resilience. It displayed superior ROC AUC values in both validation and test scenarios. Particularly impressive were ResNet50's precision and recall rates, nearing 0.99 for all conditions in the test set. On the hand, VGG16 also performed well during testing-detecting tuberculosis with a precision of 0.99 and a recall of 0.93. Our study highlights the performance of our deep learning method by showcasing the effectiveness of ResNet50 over traditional approaches like VGG16. This progress utilizes methods to enhance classification accuracy by augmenting data and balancing them. This positions our approach as an advancement in using state-of-the-art deep learning applications in imaging. By enhancing the accuracy and reliability of diagnosing ailments such as COVID-19 and tuberculosis, our models have the potential to transform care and treatment strategies, highlighting their role in clinical diagnostics.