Health Sciences Journal
https://mdripublishing.com/index.php/HSJ
<p style="text-align: justify;">Health Sciences Journal is an open access journal of Management Development & Research Innovation (MDRI) under terms of Creative common attribution Non Commercial 4.0 International License. It is published bi-annually, blind peer review. Original and review articles are published in this journal which are in line with aims and scope of HSJ. <strong><em> </em></strong> HSJ covers all areas of health and medical sciences from basic, applied to clinical and experimental work. Areas included are medicine, dentistry and applied medical sciences, public health, pharmaceutical, health economics, health informatics, and bioinformatics, contributed to medical knowledge. Manuscripts may add new method of experiments, importance and significance of medical, clinical issues and epidemiological work of significant scientific implication. All authors must ensure while submitting paper to HSJ that “Recommendation for the conduct editing, reporting and publication of scholarly work in Medical journal” as described by (<a href="https://www.icmje.org/">https://www.icmje.org/</a>). In processing and publication of research work, the Journal currently follows the Higher Education Commision (HEC) criteria.</p>Management Development and Research Innovationen-USHealth Sciences Journal2959-2240GREEN-SYNTHESIZED AZADIRACHTA INDICA–MEDIATED AGNPS WITH PHYSICOCHEMICAL CHARACTERIZATION AND ANTIBACTERIAL ACTIVITY AGAINST DENTAL PSEUDOMONAS AERUGINOSA
https://mdripublishing.com/index.php/HSJ/article/view/186
<p>The growing prevalence of antimicrobial resistance (AMR) in opportunistic bacteria, especially Pseudomonas aeruginosa, poses a serious challenge in both dental and broader clinical environments. Objectives: In response to this issue, green nanotechnology—particularly plant-mediated silver nanoparticles (AgNPs)—has gained attention as an eco-friendly and biocompatible antimicrobial strategy. This study aimed to synthesize silver nanoparticles using Azadirachta indica (neem) leaf extract and to assess their antibacterial efficacy against dental isolates of P. aeruginosa. Methodology: Silver nanoparticles were fabricated through a modified reduction approach in which A. indica leaf extract served simultaneously as a reducing and capping agent. The synthesized nanoparticles were extensively characterized using UV–visible spectroscopy, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and dynamic light scattering (DLS) to determine their structural, morphological, and physicochemical properties. Antibacterial activity was evaluated by agar well diffusion, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) assays at concentrations of 10, 20, and 30 μg/mL. A 0.2% chlorhexidine solution was employed as a positive control. Results: XRD patterns confirmed the crystalline structure of the AgNPs, with an estimated average crystallite size of 16.07 nm. FTIR analysis identified bio functional groups from neem extract involved in nanoparticle stabilization, while SEM imaging revealed predominantly hexagonal-shaped particles. UV–visible spectroscopy showed a distinct surface plasmon resonance peak at 238 nm, and DLS analysis indicated a hydrodynamic diameter of 144.22 nm. The neem-mediated AgNPs exhibited dose-dependent antibacterial activity against P. aeruginosa, with mean inhibition zones of 12 ± 1.13 mm, 14 ± 2.05 mm, and 17 ± 1.15 mm at 10, 20, and 30 μg/mL, respectively. Notably, the antibacterial effect at 30 μg/mL was comparable to that of chlorhexidine (18 ± 1.46 mm). Conclusion: This study demonstrates that A. indica–derived silver nanoparticles possess significant antibacterial potential against P. aeruginosa. Their strong activity, coupled with a green and sustainable synthesis approach, suggests that these nanoparticles could serve as a promising alternative to conventional antimicrobials however, further in vivo studies and comprehensive toxicity evaluations are necessary before clinical or dental applications can be considered.</p>Aitezaz Hassan NasirGhulam MurtazaShakeeb UllahAli ZamanM. Inam Ullah MalikSher MuhammadRehmat Ullah KhanMuhammad Zubair
Copyright (c) 2026 Health Sciences Journal
2026-02-202026-02-2042526010.59365/hsj.4(2).2026.186ARTIFICIAL INTELLIGENCE IN COMMUNITY BASED REHABILITATION: A SYSTEMATIC REVIEW
https://mdripublishing.com/index.php/HSJ/article/view/176
<p>Background: Community-Based Rehabilitation (CBR) is a strategy to promote inclusion, independence, and participation for people with disabilities, particularly in low-resource settings. In recent years, artificial intelligence (AI) has been increasingly used in clinical rehabilitation; however, its integration into community contexts remains limited. Objective: This systematic review aimed to identify and synthesize recent evidence on the use of AI technologies within CBR. Methods: A systematic search was conducted in PubMed, Scopus, and ScienceDirect for articles published from January 2020 to July 2025. Eligible studies included empirical research applying AI in CBR contexts. Two reviewers independently screened, extracted data, and assessed risk of bias using RoB2, ROBINS-I, PROBAST, and QUADAS-2. Results: From 842 identified records, 10 studies met inclusion criteria. Applications of AI in CBR were grouped into prediction and screening, home-based or remote rehabilitation, patient empowerment, and social support. Reported benefits included improved cognition, sarcopenia reversal, frailty and depression screening, diabetes self-management, and smoking cessation. Socially assistive robots were found acceptable and useful in supporting daily activities and emotional well-being. Limitations across studies included small samples, short follow-up, limited external validation, and a focus on technologically literate populations. Conclusion: AI shows considerable potential to strengthen the accessibility, personalization, and effectiveness of CBR. Future research should focus on large-scale, long-term studies with diverse populations and explore strategies for equitable, sustainable integration of AI into community rehabilitation services.</p>Jesselyn TanotoDenny FerdiansyahYoshe Jesslyn
Copyright (c) 2026 Health Sciences Journal
2026-02-202026-02-2042617410.59365/hsj.4(2).2026.176