Cloud computing practice activities and mental capacity on developing reproductive health and cognitive absorption.

The current study aims to determine how the interactions between practice (distributed/focused) and mental capacity (high/low) in the cloud-computing environment (CCE) affect the development of reproductive health skills and cognitive absorption. The study employed an experimental design, and it included a categorical variable for mental capacity (low/high) and an independent variable with two types of activities (distributed/focused). The research sample consisted of 240 students from the College of Science and College of Applied Medical Sciences at the University of Hail's.

Assessment of awareness, knowledge, and usage of folic acid among females in Jazan Region, Saudi Arabia.

Folic acid (FA) plays a crucial role in various biological processes. Insufficient intake of FA during pregnancy can lead to serious clinical complications, including neural tube defect. The current study sought to assess the awareness, knowledge, and usage of FA among young females in Jazan region of Saudi Arabia.

Correction: Almadhor et al. AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery. 2021, , 3830.

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Evaluating Communication Performance in Rotating Electrical Machines Using RSSI Measurements and Artificial Intelligence.

This paper introduces a novel methodology for evaluating communication performance in rotating electric machines using Received Signal Strength Indication (RSSI) measurements coupled with artificial intelligence. The proposed approach focuses on assessing the quality of wireless signals in the complex, dynamic environment inside these machines, where factors like reflections, metallic surfaces, and rotational movements can significantly impact communication. RSSI is used as a key parameter to monitor real-time signal behavior, enabling a detailed analysis of communication reliability.

Systematic Review of EEG-Based Imagined Speech Classification Methods.

This systematic review examines EEG-based imagined speech classification, emphasizing directional words essential for development in the brain-computer interface (BCI). This study employed a structured methodology to analyze approaches using public datasets, ensuring systematic evaluation and validation of results. This review highlights the feature extraction techniques that are pivotal to classification performance.

Towards an Accurate Real-Time Digital Elevation Model Using Various GNSS Techniques.

The objective of our research is to produce a digital elevation model (DEM) in a real-time domain. For this purpose, GNSS measurements are obtained from a kinematic trajectory in a clear location in New Aswan City, Egypt. Different real-time processing solutions are employed, including real-time precise point positioning (RT-PPP) and real-time kinematics (RTK); additionally, the widely used post-processed precise point positioning (PPP) processing scenario is used.

Enhancing Deep-Learning Classification for Remote Motor Imagery Rehabilitation Using Multi-Subject Transfer Learning in IoT Environment.

One of the most promising applications for electroencephalogram (EEG)-based brain-computer interfaces (BCIs) is motor rehabilitation through motor imagery (MI) tasks. However, current MI training requires physical attendance, while remote MI training can be applied anywhere, facilitating flexible rehabilitation. Providing remote MI training raises challenges to ensuring an accurate recognition of MI tasks by healthcare providers, in addition to managing computation and communication costs.

Dynamic Road Anomaly Detection: Harnessing Smartphone Accelerometer Data with Incremental Concept Drift Detection and Classification.

Effective monitoring of road conditions is crucial for ensuring safe and efficient transportation systems. By leveraging the power of crowd-sourced smartphone sensor data, road condition monitoring can be conducted in real-time, providing valuable insights for transportation planners, policymakers, and the general public. Previous studies have primarily focused on the use of pre-trained machine learning models and threshold-based methods for anomaly classification, which may not be suitable for real-world scenarios that require incremental detection and classification.

Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework.

Sensor networks generate vast amounts of data in real-time, which challenges existing predictive maintenance frameworks due to high latency, energy consumption, and bandwidth requirements. This research addresses these limitations by proposing an edge-cloud hybrid framework, leveraging edge devices for immediate anomaly detection and cloud servers for in-depth failure prediction. A K-Nearest Neighbors (KNNs) model is deployed on edge devices to detect anomalies in real-time, reducing the need for continuous data transfer to the cloud.

Molecular Docking and Antihypertensive Activity of Isolated from Linn.

Angiotensin-converting enzyme (ACE) is a key regulator of blood pressure, and ACE inhibition is an essential part of the treatment of hypertension. We used a molecular docking approach to find the interaction of ACE with an active flavonoid isolated from Linn, , which leads to potential antihypertensive effects in methyl predenisolone-induced hypertensive rats. Additionally, the pharmacokinetic parameters of this compound are assessed.

Clinical Pharmacokinetics of Fexofenadine: A Systematic Review.

Fexofenadine hydrochloride is a widely prescribed drug for treating histamine-mediated allergic reactions. This review systematically collates existing research on the clinical pharmacokinetics (PK) of fexofenadine, with a copious emphasis on examining the impact of stereoisomerism, disease states, and drug interactions. The search engines PubMed, Science Direct, Google Scholar, and Cochrane were scanned systematically for articles concerning the clinical PK of fexofenadine in humans.

Discovery of Non-Peptide GLP-1 Positive Allosteric Modulators from Natural Products: Virtual Screening, Molecular Dynamics, ADMET Profiling, Repurposing, and Chemical Scaffolds Identification.

Glucagon-like peptide-1 (GLP-1) receptor is currently one of the most explored targets exploited for the management of diabetes and obesity, with many aspects of its mechanisms behind cardiovascular protection yet to be fully elucidated. Research dedicated towards the development of oral GLP-1 therapy and non-peptide ligands with broader clinical applications is crucial towards unveiling the full therapeutic capacity of this potent class of medicines. This study describes the virtual screening of a natural product database consisting of 695,133 compounds for positive GLP-1 allosteric modulation.

Concomitant Inhibition and Collaring of Dual-Species Biofilms Formed by and by Triazole Based Small Molecule Inhibitors.

Background/objectives: Biofilm-associated infections, particularly those involving Candida auris and Staphylococcus aureus, pose significant challenges in clinical settings due to their resilience and resistance to conventional treatments. This study aimed to synthesize novel triazole derivatives containing a piperazine ring via click chemistry and evaluate their efficacy in disrupting biofilms formed by these pathogens.

Methods: Triazole derivatives were synthesized using click chemistry techniques.

Nanocrystals in Dermal Drug Delivery: A Breakthrough for Enhanced Skin Penetration and Targeted Skin Disorder Treatments.

One of the major challenges in dermal drug delivery is the adequate penetration of the active compound into the skin without causing any skin irritation and inflammation. Nanocrystals (NCs) are nanoscale particles, and their sizes are below 1000 nm. NCs are made up of drug particles only, which are used to improve the aqueous solubility and bioavailability of poorly water-soluble drugs.

Integration of Ontogeny-Based Changes for Predicting the Exposure of Diphenhydramine in the Pediatric Population: A PBPK Modeling Approach.

Background: Diphenhydramine is an anti-tussive used periodically to treat seasonal colds, contact dermatitis, and anaphylactic reactions. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of diphenhydramine in predicting its systemic exposure among healthy pediatrics (children and adolescents) by leveraging data files from adults (young and elderly).

Methods: The data profiles comprising serum/plasma concentration over time and parameters related to diphenhydramine were scrutinized via exhaustive literature analysis and consolidated in the PK-Sim software version 11.

Antimicrobial Peptides: A Promising Solution to the Rising Threat of Antibiotic Resistance.

The demand for developing novel antimicrobial drugs has increased due to the rapid appearance and global spread of antibiotic resistance. Antimicrobial peptides (AMPs) offer distinct advantages over traditional antibiotics, such as broad-range efficacy, a delayed evolution of resistance, and the capacity to enhance human immunity. AMPs are being developed as potential medicines, and current computational and experimental tools aim to facilitate their preclinical and clinical development.

Model-Based Dose Selection of a Sphingosine-1-Phosphate Modulator, Etrasimod, in Patients with Various Degrees of Hepatic Impairment.

Etrasimod is a newly FDA-approved Sphingosine-1-Phosphate modulator indicated for moderate and severe ulcerative colitis. It is extensively metabolized in the liver via the cytochrome P450 system and may accumulate markedly in patients with hepatic dysfunction, exposing them to toxicity. The aim of the current study is to utilize a physiologically-based pharmacokinetic modeling approach to evaluate the impact of hepatic impairment on the pharmacokinetic behavior of etrasimod and to appropriately select dosage regimens for patients with chronic liver disease; Methods: PK-Sim was used to develop the etrasimod PBPK model, which was verified using clinical data from healthy subjects and subsequently adapted to reflect the physiological changes associated with varying degrees of hepatic dysfunction; Results: Simulations indicated that hepatic clearance of etrasimod is clearly reduced in patients with Child-Pugh B and C liver impairment.

Nanocarriers for Delivery of Anticancer Drugs: Current Developments, Challenges, and Perspectives.

Cancer, the most common condition worldwide, ranks second in terms of the number of human deaths, surpassing cardiovascular diseases. Uncontrolled cell multiplication and resistance to cell death are the traditional features of cancer. The myriad of treatment options include surgery, chemotherapy, radiotherapy, and immunotherapy to treat this disease.

Formulation and Characterization of β-Cyclodextrins-Nitazoxanide Inclusion Complexes: Enhanced Solubility, In Vitro Drug Release, and Antiviral Activity in Vero Cells.

Nitazoxanide (NTX) exhibits promising therapeutic potential; its effectiveness is constrained by its low oral bioavailability due to its poor water solubility and limited permeability. This study focused on developing a complex of NTX with β-cyclodextrins (β-CDs), specifically β-CD and hydroxypropyl-β-cyclodextrin (Hβ-CD), to enhance the solubility and antiviral activity of NTX. The formation of the β-CD:NTX in an aqueous solution was verified using UV-visible spectroscopy, confirming a 1:1 inclusion complex.

RETRACTED: Ahmed et al. Thermal Analysis of a Metal-Organic Framework ZnxCo-ZIF-8 for Recent Applications. 2021, , 4051.

The journal retracts the article "Thermal Analysis of a Metal-Organic Framework ZnxCo1-X-ZIF-8 for Recent Applications" [...

The Integration of Microwave-Synthesized Silver Colloidal Nanoparticles into Poly (Lactic Acid)-Based Textiles as Antimicrobial Agents via Pre- and Post-Electrospinning Processes.

This study introduces a novel method to enhance the antibacterial functionality of electrospun nanofibrous textiles by integrating silver nanoparticles (AgNPs) into poly (lactic acid) (PLA) fabrics through pre- and post-electrospinning techniques. AgNPs were incorporated into hydrophobic and modified hydrophilic PLA textiles via pre-solution blending and post-solution casting. A PEG-PPG-PEG tri-block copolymer was utilized to enhance hydrophilicity and water stability, while AgNPs served as antibacterial agents.

In Situ Preparation of Silver Nanoparticles/Organophilic-Clay/Polyethylene Glycol Nanocomposites for the Reduction of Organic Pollutants.

This work focuses on the preparation and application of silver nanoparticles/organophilic clay/polyethylene glycol for the catalytic reduction of the contaminants methylene blue (MB) and 4-nitrophenol (4-NP) in a simple and binary system. Algerian clay was subjected to a series of treatments including acid treatment, ion exchange with the surfactant hexadecyltrimethylammonium bromide (HTABr), immobilization of polyethylene glycol polymer, and finally dispersion of AgNPs. The molecular weight of polyethylene glycol was varied (100, 200, and 4000) to study its effect on the stabilization of silver nanoparticles (AgNPs) and the catalytic activity of the resulting samples.

Electrospun Carbon Nanofibers Derived from Polyvinyl Alcohol Embedded with Bimetallic Nickle-Chromium Nanoparticles for Sodium Borohydride Dehydrogenation.

Bimetallic NiCr nanoparticles decorated on carbon nanofibers (NiCr@CNFs) were synthesized through electrospinning and investigated as catalysts for hydrogen generation from the dehydrogenation of sodium borohydride (SBH). Four distinct compositions were prepared, with chromium content in the catalysts ranging from 5 to 25 weight percentage (wt%). Comprehensive characterization confirmed the successful formation of bimetallic NiCr@CNFs.

In Vitro Hydroxyapatite Nucleation in Cationically Cured Epoxy Composites with Pulverized Date Seed.

Recently, driven by a growing focus on environmental sustainability and cost-effectiveness, researchers have shown a keen interest in creating useful materials from bio-wastes, particularly for their potential applications in the biomedical field. Current research has been conducted on the impact of date seed powder (DSP) on hydroxyapatite (HA) formation, specifically in relation to the promotion of bone health and regeneration. HA is an essential component of bone tissue and plays a crucial role in maintaining bone strength and structure.

Revitalizing Soybean Plants in Saline, Cd-Polluted Soil Using Si-NPs, Biochar, and PGPR.

Excessive irrigation of saline-alkaline soils with Cd-contaminated wastewater has resulted in deterioration of both soil and plant quality. To an investigate this, a study was conducted to explore the effects of biochar (applied at 10 t ha), PGPRs ( (USDA 110) + at 1:1 ratio), and Si-NPs (25 mg L) on soybean plants grown in saline-alkali soil irrigated with wastewater. The results showed that the trio-combination of biochar with PGPRs, (as soil amendments) and Si-NPs (as foliar spraying), was more effective than individual or coupled applications in reducing Cd bioavailability in the soil, minimizing its absorption, translocation and bioconcentration in soybean tissues.