Telehealth and digital health technology have been revolutionizing health care delivery for many years, but the rapid use of these technologies greatly increased because of the COVID-19 Pandemic. The purpose of this review is to critically evaluate the role of telehealth, remote patient monitoring (RPM), and artificial intelligence (AI), and how they have been able to improve the overall delivery of health care, particularly in managing chronic diseases. A narrative review of published literature was completed, analysing literature regarding telehealth applications, digital health tools, and the integration of AI among a variety of health care domains. The evidence demonstrates that telehealth offers increased access to care and promotes better patient participation and monitoring of disease (e.g. diabetes and hypertension). There are some differences in the outcomes of telehealth services based on the population being served, the digital literacy of the patient and the overall digital infrastructure of the health care system being used. AI integration to support telehealth has also been shown to support accurate diagnosis and improved clinical decision making for a patient, however, there still exist some concerns pertaining to data privacy, bias and regulatory frameworks governing the use of AI. The use of telehealth and digital health technology have incredible potential to transform health care systems through increased access and efficiency of service delivery and providing patient-centred care; however, it is critical to address necessary infra-structural, ethical, and regulatory issues to make them sustainable and equitably implemented across health care systems everywhere.
Topical drug delivery systems have advanced significantly with the incorporation of polymer-based formulations, providing better patient compliance, controlled drug release, and increased therapeutic efficacy. Lipid-polymer hybrid nanoparticles (LPNPs) are particularly highlighted for site-specific delivery of multiple medications, owing to their structural advantages and controlled-release capabilities. The multifunctional role of polymers in stabilizing therapeutic proteins and enhancing skin penetration is explored, along with innovations such as pH-sensitive, temperature-sensitive, and biodegradable polymer systems. Emerging technologies like 3D printing are also discussed for their potential to revolutionize personalized topical therapies. Applications in dermatology, wound healing, and cosmetics underscore the versatility of polymeric systems. Numerous polymeric systems, including hydrogels, emulgels, nanogels, polymeric nanoparticles, microspheres, and film-forming systems, are highly effective at improving drug localization, enhancing skin retention, and achieving controlled release. The comparative analysis of these systems indicates that nanoparticles or nanogels will provide superior tissue penetration and targeted delivery, while hydrogels or emulgels will provide increased patient compliance and a prolonged duration of action at the site of topical administration. Challenges associated with scaling up manufacturing processes, polymer-related toxicity, regulatory approval, and long-term stability will continue to restrict the translation of these technologies to clinical use. Safety concerns, particularly toxicity and long-term bioaccumulation of certain polymer systems, are critically examined.
Aging is a multifactorial process characterized by systemic physiological decline, during which neural stem cells (NSCs) undergo epigenetic reprogramming, contributing to cognitive impairment. Emerging evidence implicates the gut-brain axis in modulating this decline, yet the mechanistic underpinnings remain elusive. Here, we integrate single-cell transcriptomics and epigenomics (scRNA-seq and scATAC-seq) to dissect how microbiota-derived short-chain fatty acids (SCFAs) influence the chromatin accessibility and gene expression patterns of NSCs across age groups in murine models. SCFA supplementation in aged mice restores youthful epigenetic states in a subset of NSCs, promotes neurogenesis-associated transcriptional programs, and reduces senescence signatures. These findings uncover a novel avenue where microbiota metabolites serve as epigenetic modulators of neural aging, offering targets for therapeutic rejuvenation of the aging brain.
This paper aimed to mix and test a clove oil-loaded niosomal gel to improve topical delivery. Clove oil is also rich in eugenol and is highly antimicrobial, but its active compound is volatile and easily released when used conventionally. To overcome these limitations, niosomes were developed using the thin-film hydration method with Span 60 and cholesterol, which were then embedded in a carbopol gel base. The optimised formulation (F3) exhibited a vesicle size of 182.4 ± 4.2 nm with a polydispersity index (PDI) of 0.241 ± 0.02, characteristic of uniform nanosized vesicles. The entrapment efficiency of 78.54 +/- 3.1% indicated the successful entrapment of clove oil. In vitro release experiments revealed 84.3 ± 2.4% release after 24 hours, compared with 98.7 ± 1.8% from the conventional gel after 12 hours (p < 0.05). The niosomal gel was also better in antimicrobial activity, with a zone of inhibition of 24 mm against Staphylococcus aureus and 21 mm against Candida albicans (p<0.05). These findings indicate that niosomal encapsulation significantly enhances the stability, prolonged release, skin retention, and antimicrobial activity of clove oil, making it a promising alternative for topical use in medicinal therapy.
Human microbiota consists of millions and trillions of micro-organisms like Firmicutes (Bacillota) and Bacteroidota including Faecalibacterium prausnitziithat thrives strictly anaerobically in the colon, regulate inflammation via butyrate-production. Bifidobacterium, produce lactic acid, break down fibers, and support infant gut health via human milk oligosaccharides. Other significant phyla include Actinomycetota, Pseudomonadota, and Verrucomicrobiota. Use of antibiotics and other disease conditions alter this microbiota of gut. Hence probiotics are used to flourish and maintain the microenvironment. This review paper focuses on isolation of various species of lactic acid bacteria including the newer strains developed till now. NGPs (Next Generation Probiotics) including Akkermansia muciniphila and engineered Escherichia coli variants, target precise conditions like metabolic syndrome and inflammation via advanced genomic modifications. Various isolation and identification techniques have also been explained like PAGE (Polyacrylamide Gel Electrophoresis), DGGE (Denaturing Gradient Gel Electrophoresis) and Culturomics. Post-2024 research highlights phage-assisted isolation to enrich rare taxa and machine learning-optimized media formulations for fastidious growers. Studies from 2025 report >90% success in isolating Akkermansia muciniphila variants using mucus-mimicking media, enhancing NGP yields for metabolic disorders. These methods prioritize scalability for clinical translation. Key hurdles include maintaining anaerobiosis, strain stability, and regulatory validation. Future techniques may leverage CRISPR-based tagging and organ-on-chip models for in situ isolation. Overall, NGP isolation has shifted from empirical culturing to precision microbiome engineering, promising personalized biotherapeutics.
This study evaluated the antibacterial activity, acute toxicity, and histological effects of Eucalyptus camaldulensis, Dodonaea viscosa, and Senna siamae, three ethnobotanical plants traditionally used to treat typhoid fever in Kano State, Nigeria. Antibacterial activity against Salmonella typhi was assessed using the agar well diffusion method, followed by determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Acute toxicity was evaluated using a single oral limit dose of 5000 mg/kg in mice, and histological assessment of the liver, kidney, and heart was performed using hematoxylin-eosin staining. At 100 mg/ml, E. camaldulensis exhibited the largest inhibition zone (20.3 ± 2.52 mm), followed by S. siamae (15.0 ± 0.00 mm) and D. viscosa (13.0 ± 0.00 mm) which showed a statistically significant (p < 0.05) with the control. MIC and MBC values confirmed that E. camaldulensis had the highest antibacterial potency (MIC 6.25 mg/ml; MBC 12.5 mg/ml), whereas D. viscosa and S. siamae showed MIC 12.5 mg/ml and MBC 25 mg/ml. Acute toxicity assessment revealed no mortality at 5000 mg/kg for all the extracts (LD50 > 5000 mg/kg). Histological evaluation showed normal heart tissues in all the tested groups, normal liver and kidney tissues in E. camaldulensis and S. siamae-treated mice, but slight tubular necrosis in the kidney and minimal hepatic necrosis in the liver of D. viscosa-treated mice. Lesions were graded as minimal and observed in 1 out of 3 mice per group.
This study compared the condition factor and nutrient composition of two sexes of the African catfish (Clarias gariepinus) from the wild and cultured sources in Zobe Dam and Ni’ima Farm, respectively, in Dutsin-Ma, Katsina State, Nigeria. For this, 20 wild and 20 cultured, with equal sex representation (total n=40). The condition factor (K) of the wild fish was statistically higher (males: 1.71 ± 0.03; females: 1.69 ± 0.04) than the cultured fish (males: 1.52 ± 0.05; females: 1.56 ± 0.02). This shows that the wild fish had better overall well-being and energy reserves than the cultured ones. The proximate analysis was conducted (for dry matter, crude protein, crude fibre, lipid, ash, and nitrogen-free extract), and there were no significant differences in most of the parameters of the sources and sexes except the ash content of the cultured fish, which was higher, and the wild fish possessed higher lipid and nitrogen-free extract. The male fishes showed slightly higher crude protein and lipids than the females. In conclusion, it was observed that the cultured and wild C. gariepinus fish had similar nutritional value, although the cultured fish had better minerals and the wild fish had more lipid from natural foraging. These findings will provide the basis for sustainable development of feed formulation, processing and management to enhance the quality of the cultured fish as well as assist the aquaculture sector of Dutsin-Ma, Katsina State, Nigeria, amid growing protein demand.
Artificial intelligence (AI) has emerged as a transformative force in healthcare, revolutionizing clinical practice, research, and patient care delivery. This review examines the current applications of AI across various healthcare domains, including medical imaging, diagnostics, drug discovery, personalized medicine, and healthcare administration. We discuss the integration of machine learning, deep learning, and natural language processing technologies that enable enhanced diagnostic accuracy, treatment optimization, and operational efficiency. The review highlights significant achievements in AI-powered medical imaging analysis, predictive analytics for disease progression, and clinical decision support systems. We also address critical challenges including data privacy concerns, algorithmic bias, regulatory frameworks, and the need for clinical validation. Despite these challenges, AI demonstrates substantial promise in addressing healthcare disparities, reducing clinician burnout, and improving patient outcomes. The future of AI in healthcare lies in developing explainable AI systems, ensuring equitable access, and fostering human-AI collaboration that augments rather than replaces clinical expertise.
The XEC strain of SARS-CoV-2, a recombinant variant, presents significant challenges due to its mutations that enhance immune escape potential and potentially alter transmission dynamics. As the world continues to confront the evolving nature of COVID-19, biotechnological innovations, including genomic surveillance, CRISPR-based diagnostics, and mRNA vaccine platforms, have been essential in responding to emerging variants. However, the XEC variant’s ability to evade immunity requires ongoing adaptation of these technologies, including precision diagnostics and updated vaccines. Despite progress, substantial gaps remain in understanding the pathophysiology of new variants like XEC, their impacts on vulnerable populations, and the efficacy of current therapeutics. Future research should prioritize investigating the molecular mechanisms driving XEC’s pathogenicity, long-term vaccine effectiveness, the development of novel therapeutics, and the integration of biotechnology into public health policies. Furthermore, enhanced international collaboration and data sharing are critical for improving global surveillance and preparedness. Addressing these research gaps through multidisciplinary efforts will be crucial in mitigating the impact of future viral threats and safeguarding global health.
This review aims to explore recent advancements in human-based methodologies that are reshaping the landscape of preclinical research. It focuses on evaluating the scientific validity, translational relevance, and regulatory recognition of emerging non-animal platforms. By analyzing these approaches, the article seeks to demonstrate their potential in enhancing predictive accuracy, ethical responsibility, and the overall efficiency of biomedical research and drug development. Most predominantly used methods include Artificial intelligence models, in-vitro models, in-silico models, organ-on-chip systems, and other innovative technologies. Human organoids-on-chips (OrgOCs) combine human organoids (HOs) technology and microfluidic organs-on-chips (OOCs). HOs are related to biological analysis and genetic manipulation while OOCs can simulate external characteristics of organs like living tissue, OrgOCs served as 3D organotypic living models allowing them to recapitulate critical tissue-specific properties and predict human responses. Virtual screening, molecular docking, QSAR modeling, AI/ML based clinical computational models are some of the tools used in building non-animal modelling. Animal testing requirement of FDA will be replaced using above range of approaches in a laboratory setting. Implementation of the regimen shall begin for investigational new drug (IND) applications, where inclusion of NAMs data is encouraged, as outlined in road map guidance document. In the future, computational approaches have the potential to catapult us into the realm of customized treatment, where individual differences are methodically examined leading to transformed drug development. Virtual screening and computer-based trials are emerging as ways to speed up drug development while reducing expenses. is critical to balance innovation with ethical data handling. In essence, the future of drug design is being charted by the dynamic interplay of computational prowess and biological insight, heralding a new era of targeted, efficient, and personalized therapeutics.
The change of injectable semaglutide into verbally administered portion of drug or other consumable forms shows a significant progress in peptide-located diabetes medicines. This study evaluates the feasibility, pharmacokinetics, and temporary balance of oral semaglutide brought through capsule and liquid formulations in Sprague–Dawley rats. Injectable semaglutide (1 mg/mL) was reformulated using SNAC-located next-release sciences. Both oral formulations illustrated agreeable bioavailability (0.8–0.9%) relative to the injectable form. Pharmacokinetic reasoning told deferred Tmax for the tablet distinguished to the liquid, unpaid to formulation excipients. Stability experiment over 30 days designated maintained potency (95–97%) accompanying gentle opalescence in the liquid expression, inciting plans for enhanced expression plannings. These judgments provide basic evidence advocating future long-term ICH-obedient support studies and expression refinement for numbering spoken GLP-1 agonist development.
This review is dedicated to a systematic evaluation of the involvement of Gamma-Aminobutyric Acid (GABA) and the three major receptor subtypes in the pathophysiology of Alzheimer’s disease. The core theme is how changes in GABAergic neurotransmission, receptor expression, synaptic inhibition, and network oscillatory dysfunction lead to cognitive decline, neurodegeneration, and disease progression. The review also outlines the therapeutic interventions designed to target the GABAergic signaling to lessen the Alzheimer's-related neuropathology. This review was conducted using a structured narrative approach to ensure a transparent and comprehensive synthesis of data on GABAergic mechanisms in Alzheimer’s disease. A systematic literature search was performed across PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2000 and 2024. Search keywords included: “GABA AND Alzheimer’s disease,” “GABAergic dysfunction,” “GABA receptor subtypes,” “GABAA_AA receptors and AD,” “GABAB_BB signaling,” “GABAC_CC receptor function,” “inhibitory neurotransmission AND neurodegeneration.” GABA plays an important role in synchronization of neuronal transmission in brain and also functions for storing of memory. It performs physiological functions like production of controlling brain signals, interferon-γ production, and decrease the cell excitability. In this review article, we have shown the role of GABA and its types in Alzheimer’s disease AD.
Salvadora persica (miswak) is traditionally used as a natural oral hygiene tool. This study investigates the antibacterial activity of hot aqueous miswak extract against Staphylococcus aureus isolated from patients with gingivitis. Fifty samples were collected from patients diagnosed with gingivitis at a primary health center in Babylon Governorate between January and June 2025. Bacterial isolates were identified using standard microbiological methods. Miswak extract was prepared in concentrations of 20%, 30%, 40%, and 50%. The antimicrobial activity was assessed using the agar well diffusion method and compared with conventional antibiotics: vancomycin, carbenicillin, and piperacillin. The Staphylococcus aureus isolates were gotten, 4 isolates from males (26.66%) and 11 isolates from females (73.33%). There was no significant difference between the infection rate of bacterial isolates and the use of miswak (P=0.37), the occurrence of bleeding in the gums (P=0.36), and smoking (P=0.37). The miswak extract at a concentration of (50%) showed a greater effect than the other concentrations, as the inhibition zone was (9.86) mm with highly significant differences at the probability level concentrations of extract. (P<0.05), in addition to the presence of significant differences between the effect of Miswak at concentrations (30%, 40%, 50%) and the sensitivity of the isolates to vancomycin, Pipracillin and carbenicillin. The higher the concentration of the aqueous extract of Miswak, the greater the effect on Staphylococcus aureus isolated from gingivitis compared to some types of antibiotics.
This study explores the potential of soil microbiomes as indicators of public health risks, emphasizing the complex interplay between soil microbial communities and human health outcomes. Soil microorganisms are critical components of ecosystems, influencing both beneficial functions, such as nutrient cycling and plant health, and harmful effects, including the presence of pathogens and antimicrobial resistance genes that can pose risks to human populations. The study investigates how anthropogenic factors—such as urbanization, agriculture, and climate change—affect soil microbial diversity, which in turn impacts public health. The integration of advanced biotechnological tools, such as metagenomics, machine learning, and biosensors, is explored as a means of enhancing the detection and monitoring of soil health risks. The study also highlights the current gaps in research linking soil microbial dynamics to human health outcomes and calls for interdisciplinary approaches to bridge these gaps. Findings from this research suggest that soil microbiomes have significant potential to serve as bioindicators of public health risks, offering a new avenue for improving health surveillance and informing policy recommendations. The study concludes with a call to action for further research, improved monitoring strategies, and the incorporation of soil health into public health frameworks to address the global health challenges posed by environmental changes.
This study explores the innovative intersection of artificial intelligence (AI), CRISPR technology, and microbiome insights in microbial drug discovery, with a focus on overcoming the challenges posed by antimicrobial resistance (AMR) and emerging infectious diseases. The global threat of AMR necessitates the development of novel approaches that transcend traditional drug discovery methods. AI-driven platforms, including machine learning and high-throughput screening, are transforming drug design by enabling rapid identification of potential therapeutic targets and optimizing drug repurposing efforts. CRISPR-based gene-editing technologies offer precise tools to combat resistance mechanisms at the genetic level, while microbiome-based therapies hold promise for restoring microbial balance and improving immune responses. Despite significant progress, several challenges remain, including the integration of these technologies, data quality concerns, and the clinical translation of innovative solutions. The future of microbial drug discovery lies in the synergy of these technologies, providing a pathway toward personalized, effective treatments and combating the growing threat of AMR. This study provides a comprehensive overview of the current landscape, identifies research gaps, and outlines potential directions for future advancements.
The soil microbiome represents a valuable and largely untapped resource for drug discovery, containing a diverse array of microorganisms capable of producing bioactive compounds with significant therapeutic potential. This study examines the role of soil-derived microorganisms in the development of novel antimicrobial, anticancer, and other bioactive agents, highlighting the advancements made through high-throughput sequencing, metagenomics, and omics technologies. These approaches have significantly enhanced our ability to identify and characterize bioactive compounds within complex soil ecosystems. However, challenges such as culturing unculturable microorganisms, ensuring compound stability, and translating findings into clinical applications remain significant barriers. The study also explores the integration of computational tools, particularly machine learning and artificial intelligence, which have shown promise in accelerating the identification and optimization of bioactive compounds. Moreso, ethical considerations surrounding soil bioprospecting, including environmental impact and sustainable practices, are discussed as critical factors in ensuring responsible microbial resource exploration. With antimicrobial resistance becoming an increasingly urgent global health crisis, the potential of soil microbiomes as a source of novel therapeutics is more crucial than ever. However, the study emphasizes the need for continued advancements in metagenomics, synthetic biology, and drug delivery systems. It also advocates for greater interdisciplinary collaboration to overcome existing challenges and unlock the full potential of soil microbiomes for drug discovery.
