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This study presents a compact and high-efficiency microstrip antenna integrated with a square electromagnetic band-gap (EBG) structure for radio frequency energy harvesting to power battery-less Internet of Things (IoT) sensors and medical devices in the 5.8 GHz Industrial, Scientific, and Medical (ISM) band. The proposed antenna features a compact design with reduced physical dimensions of 36 × 40 mm2 (0.69λo × 0.76λo) while providing high-performance parameters such as a reflection coefficient of −27.9 dB, a voltage standing wave ratio (VSWR) of 1.08, a gain of 7.91 dBi, directivity of 8.1 dBi, a bandwidth of 188 MHz, and radiation efficiency of 95.5%. Incorporating EBG cells suppresses surface waves, enhances gain, and optimizes impedance matching through 50 Ω inset feeding. The simulated and measured results of the designed antenna show a high correlation. This study demonstrates a robust and promising solution for high-performance wireless systems requiring a compact size and energy-efficient operation.

This paper presents PCB design solutions for implementing a radiative-field RF energy harvester with an ASK-PWM decoding communication scheme using available commercial components. The paper provides the design approach and tackles key challenges such as the impact of inductive parasitic effects at the output of the harvester, how to maintain the PCE at a constant value regardless of the time constant at the output of the communication path’s rectifier, and the difficulty of changing the aspect ratio of the discrete inverter used for PWM decoding. These challenges are addressed by using multiple capacitors connected in parallel at the output of the rectifier to reduce inductive parasitic effects, adding a series resistor in the communication path’s rectifier to isolate its loading from impacting the PCE, and utilizing a potentiometer in the inverter to realize PWM decoding on PCB. The system was manufactured using FR-4 substrate material with a size of 5 cm × 4 cm × 0.6 cm, harvesting energy at the ISM frequency of 924 MHz with a PCE of 42.12% at a bit rate of 15 Kbps. Moreover, the system consumes only 355 μW of power and maintains correct harvesting and decoding operation in the antenna separation range of 6–12 cm. This work aims to provide an alternative to IC realization by implementing the system entirely using commercial discrete components, reducing costs, adding flexibility, reducing development time, and allowing for simple debugging.

After demonstrating, in previous works, the proof of concept of adaptive rectifiers with active load modulation to operate simultaneously for short/long range RF Wireless Power Transfer (WPT) while maintaining a high Power Conversion Efficiency (PCE), the authors introduced in this paper a power link budget of the proposed adaptive rectifier with a compromise between distance and efficiency. Then, to further exhibit its capabilities and enhance its performance, this paper first introduced a discussion about the parameters preventing the rectifier from operating over a wide range of input powers was performed. Furthermore, active load modulation was implemented and its co-simulation results presented. Finally, an adaptive rectifier was fabricated and its results successfully compared to measured data. It exhibits 40% of PCE over a wide dynamic input range of incident RF power levels from −6 to 25 dBm at the 900 MHz in the Industrial Scientific Medical band (ISM band), with a maximum PCE of 66% for an input power of 15 dBm. The proposed devices are therefore suitable for WPT applications to harvest energy from a controlled source.

Wireless Power Transfer (WPT) has become a pivotal technology, enabling the battery-free operation of Internet of Things (IoT) and biomedical devices while supporting environmental sustainability. This review provides a comprehensive analysis of microstrip patch antennas (MPAs) operating at the 5.8 GHz Industrial, Scientific, and Medical (ISM) band, emphasizing their advantages over the more commonly used 2.4 GHz band. A detailed and systematic classification framework for MPA architectures is introduced, covering single-element, multi-band, ultra-wideband, array, MIMO, wearable, and rectenna systems. The review examines advanced optimization methodologies, including Defected Ground Structures (DGS), Electromagnetic Bandgap (EBG) structures, Metamaterials (MTM), Machine Learning (ML), and nanomaterials, each contributing to improvements in gain, bandwidth, efficiency, and device miniaturization. Unlike previous surveys, this work offers a performance-benchmarked classification specifically for 5.8 GHz MPAs and provides a quantitative assessment of key trade-offs, such as efficiency versus substrate cost. The review also advocates for a shift toward Power Conversion Efficiency (PCE)-centric co-design strategies. The analysis identifies critical research gaps, particularly the ongoing disparity between simulated and experimental performance. The review concludes by recommending multi-objective optimization, integrated antenna-rectifier co-design to maximize PCE, and the use of advanced materials and computational intelligence to advance next-generation, high-efficiency 5.8 GHz WPT systems.

The use of simulation-based methods for teaching and learning in the education of health professions is increasing, but its prevalence in Saudi Arabia among respiratory therapy programs has yet to be investigated. The purpose of this study is to identify the use of simulation-based learning (SBL) in respiratory therapy programs in Saudi Arabia. A cross-sectional study was performed by sending Google forms survey via Email to directors of respiratory therapy programs in Saudi Arabia (N=16) to evaluate how each one used simulations as an educational tool. The survey was returned with a total response of 12 out of all 16 program that were initially contacted (75% response rate). Among the respondents, approximately 75% of the programs are using SBL, while high-fidelity simulation is used by all programs. The present data show that 67% of the respiratory therapy programs has a space for simulation within the department, while 33% utilizes institutional simulation centers. For short simulation scenarios, debriefing is not conducted in 67% of the programs. There is acceptance by program directors that simulation hours should be counted towards clinical hours. About 67% of respondent programs have mandatory simulation learning activities, and 100% agree that simulations should be used more. However, lack of training and shortage of staff are among barriers to increase the use of SBL. SBL is commonly used and relatively varied among respiratory therapy programs. However, it requires some improvements in several aspects, including the use of debriefing and increasing the number of properly trained staff.

Severe COVID‐19 cases are often characterised by a hyperinflammatory cytokine storm, which leads to immune dysregulation and increased mortality. Simultaneously, opportunistic fungal infections such as mucormycosis have been increasingly reported, especially in immunocompromised individuals. Triazole antifungals are widely used to treat such infections, but their potential immunomodulatory effects remain underexplored. This study aimed to investigate the off‐target potential of commonly used antifungal triazoles itraconazole, ketoconazole, posaconazole and voriconazole against human phosphodiesterase‐4 (PDE‐4), a key enzyme involved in the regulation of pro‐inflammatory cytokine expression. To our knowledge, this is the first study to explicitly propose and computationally validate the dual role of triazole antifungals as both antifungal and immunomodulatory agents. A computational approach comprising molecular docking, molecular dynamics (MD) simulations and quantum chemical analysis was employed to evaluate the interaction of the selected triazoles with PDE‐4. Binding affinity and interaction stability were compared with roflumilast, a known PDE‐4 inhibitor. Among the tested triazoles, posaconazole exhibited the most favourable binding energy (−44.60 kcal/mol via MM‐GBSA), forming stable interactions with key residues in the catalytic site of PDE‐4, similar to those observed with roflumilast. MD simulations further confirmed the binding stability of posaconazole, as evidenced by favourable RMSD and hydrogen bonding patterns. Quantum chemical analysis indicated strong electrophilicity and reactivity of posaconazole, supporting its potential PDE‐4 inhibitory activity. The findings suggest that certain triazole antifungals, especially posaconazole, may both fight fungal infections and reduce the cytokine storm in severe COVID‐19, offering a promising rapid‐response therapeutic strategy.

Taurine, an amino acid abundantly found in the brain and other tissues, has potential neuroprotective properties. Alzheimer's disease (AD) is a commonly occurring type of dementia, which becomes more prevalent as people age. This experiment aimed to assess the neuroprotective effects of taurine on SH-SY5Y cells by examining its impact on Dihydrotestosterone (DHT), Dihydroprogesterone (DHP), as well as the expression of miRNA-21 and miRNA-181. The effects of various taurine concentrations (0.25, and 0.75 mg/mL), and LPS (0.1, and 12 mg/mL) on the SH-SY5Y cell line were assessed using the MTT assay. The levels of DHT and DHP were quantified using an ELISA kit. Additionally, the expression levels of miRNA-181 and miRNA-21 genes were examined through Real-Time PCR analysis. The results of the MTT assay showed that treatment with taurine at concentrations of 0.25, and 0.75 mg/mL reduces the toxicity of LPS in SH-SY5Y cells. ELISA results indicated that taurine at a concentration of 0.25, and 0.75 mg/mL significantly elevated DHT and DHP hormones in the SH-SY5Y cell line compared to the untreated group (  < 0.01). The expression levels of IL-1β and IL-6 were decreased under the influence of LPS in SH-SY5Y cells after taurine treatment (p < 0.01). Gene expression analysis revealed that increasing taurine concentration resulted in heightened expression of miRNA-181 and miRNA-21, with the most significant increase observed at a concentration of 0.75 mg/mL (  < 0.001). Our study findings revealed that the expression of miRNA-181 and miRNA-21 can be enhanced by taurine. Consequently, exploring the targeting of taurine, miRNA-181, and miRNA-21 or considering hormone therapy may offer potential therapeutic approaches for treating AD or alleviating severe symptoms. Nonetheless, in order to fully comprehend the precise mechanisms involved, additional research is required.

Objective Diabetes is a chronic disease resulting from insufficient insulin secretion or impaired insulin function. Diabetic nephropathy (DN) is one of the most common complications of diabetes and a leading cause of end‐stage renal disease. Early diagnosis of DN is crucial for timely intervention and effective disease management. Methods Gene expression profiles GSE142025 and GSE220226 were retrieved from the GEO database and combined into a metadata cohort, while GSE189007 was obtained as an independent validation dataset. Differentially expressed genes (DEGs) were identified in 46 glomerular samples from DN patients and 31 control samples. Gene Ontology (GO) and Disease Ontology (DO) enrichment analyses, gene set enrichment analysis (GSEA), least absolute shrinkage and selection operator (LASSO) regression, support vector machine‐recursive feature elimination (SVM‐RFE) analysis, and area under the curve (AUC) calculations were performed. Results A total of 109 DEGs were identified. Among them, DUSP1, EGR1, FPR1, G6PC, GDF15, LOX, LPL, PRKAR2B, PTGDS, and TPPP3 were selected as potential diagnostic biomarkers for DN. These biomarkers exhibited a positive correlation with immune cell infiltration. Experimental validation identified LOX as the most promising novel diagnostic biomarker for DN. This study provides new insights into the early diagnosis, pathogenesis, and molecular mechanisms of DN. Diabetic nephropathy (DN) is a major complication of diabetes, leading to end‐stage renal disease. This study identified 109 differentially expressed genes (DEGs) and validated LOX as a novel diagnostic biomarker through integrated bioinformatics and experimental analysis. The findings highlight key molecular mechanisms and immune cell interactions, offering new insights for early DN diagnosis and treatment.

The coronavirus disease 2019 (COVID-19) was first found in Wuhan, China, in December 2019. Because the virus spreads quickly, it quickly became a global worry. Coronaviridae is the family that contains both SARS-CoV-2 and the viruses that came before (i.e., MERS-CoV and SARS-CoV). Recent sources portray that the COVID-19 virus has affected 344,710,576 people worldwide and killed about 5,598,511 people in the last 2 years. The B.1.1.529 strain, later called “Omicron,” was named a Variant of Concern on November 24, 2021. The SARS-CoV-2 virus has gone through a never-ending chain of changes that have never happened before. As a result, it has many different traits. Most of these changes have occurred in the spike protein, where antibodies bind. Because of these changes, the Omicron type is very contagious and easy to pass on. There have been a lot of studies done to try to figure out this new challenge in the COVID-19 strains race, but there is still a lot that needs to be explained. This study focuses on virtual screening, docking, and molecular dynamic analysis; we aimed to identify therapeutic candidates for the SARS-CoV-2 variant Omicron based on their ability to inhibit non-structural proteins. We investigate the prediction of the properties of a substantial database of drug molecules obtained from the OliveNet™ database. Compounds that did not exhibit adequate gastrointestinal absorption and failed the Lipinski test are not considered for further research. The filtered compounds were coupled with our primary target, SARS-CoV-2 Omicron spike protein. We focused on SARS-CoV-2 Omicron spike protein and filtering potent olive compounds. Pinoresinol, the most likely candidate, is bound best (− 8.5 kcal/mol). Pinoresinol’s strong interaction with the active site made the complex’s dynamic structure more resilient. MD simulations explain the protein–ligand complex’s stability and function. Pinoresinol may be a promising SARS-CoV-2 Omicron spike protein receptor lead drug, and additional research may assist the scientific community. Graphical Abstract

Neuro-oncological and neurodegenerative disorders, represented paradigmatically by glioblastoma and Alzheimer's disease, respectively, persist as formidable challenges in the biomedical realm. The interconnected molecular underpinnings of these conditions necessitate rigorous and novel therapeutic examinations. This comprehensive research was anchored on the premise of unveiling the therapeutic potential and specificity of Lupenone, a potent phytoconstituent, in targeting the molecular pathways underpinning both glioblastoma and Alzheimer's amyloid beta pathology. This was gauged through its interactions with key protein structures, 5H08 and 2ZHV. An integrative approach was adopted, marrying advanced proteomics and modern computer-aided drug design techniques. Molecular docking of Lupenone with 5H08 and 2ZHV was meticulously executed, with subsequent molecular dynamics simulations providing insights into the stability, viability, and intricacies of these interactions. Lupenone demonstrated profound binding affinities, evidenced by robust docking scores of -9.54 kcal/mol for 5H08 and -10.59 kcal/mol for 2ZHV. These interactions underscored Lupenone's eminent therapeutic potential in mitigating glioblastoma and modulating the amyloid beta pathology inherent to Alzheimer's. The introduction of Proteolysis Targeting Chimeras (PROTACs) further magnified the therapeutic prospects, accentuating Lupenone's efficacy. The findings of this study not only underscore the therapeutic acumen of Lupenone in addressing the challenges posed by glioblastoma and Alzheimer's but also lay a strong foundation for its consideration as a leading candidate in future neuro-oncological and neurodegenerative research endeavors. Given the compelling in-silico data, a clarion call is made for its empirical validation in holistic in-vivo settings, potentially pioneering a new therapeutic epoch in both glioblastoma and Alzheimer's interventions.