Evaluation of the METRA + intervention on mental health and social functioning in Afghan refugee adolescents in Pakistan: a pilot study

Background: Afghan adolescents have been exposed to decades of war, displacement, and limited access to mental health care. Memory Training for Recovery–Adolescent Plus (METRA+) was developed to address posttraumatic stress (PTSD), depression, and social functioning through a brief, culturally adapted, and scalable approach. This pilot study evaluated the feasibility and preliminary efficacy of METRA + among Afghan refugee adolescents in Pakistan. Methods: A single-arm mixed-methods design was used, with 41 Afghan adolescents (27 girls, 14 boys; mean age =  15 .4 years) completing a 13-session METRA + programme integrating compassionate communication, memory specificity, and written exposure. Quantitative measures assessed PTSD symptoms, depression symptoms, anxiety, and social functioning, administered at baseline, after each module, and at two-month follow-up. Data were analyzed using repeated-measures analysis of variance (ANOVA). Post-intervention focus groups explored participants’ experiences and emotional changes, with thematic analysis conducted using MAXQDA 2024, following Braun and Clarke’s ( 2006 ) framework. Results: Significant reductions were observed in symptoms of PTSD, p  < .001, partial η ² = .34, depression, p  = .001, partial η ² = .16, and anxiety, p  = .004, partial η ² = .13, with significant reductions in anxiety observed at follow-up but not immediately post-intervention, and all reductions maintained at follow-up. Improvements in social and communication skills were non-significant, but qualitative analyses indicated that METRA + enhanced emotion regulation, self-efficacy, empathy, academic motivation, and the normalization of traumatic memories. Participants and facilitators reported high satisfaction and strong cultural relevance of the programme. Conclusions: METRA + appears feasible, acceptable, and has potential efficacy for improving mental health and psychosocial outcomes among Afghan refugee adolescents. Findings highlight the promise of memory-focused and compassion-based interventions for youth in humanitarian and low-resource settings. Larger randomized controlled trials are warranted. Trial registration: Australian New Zealand Clinical Trials Registry identifier: ACTRN12624001453572. .

Assessing academic capacity and quality assurance in pharmacy education: a focus on the Eastern Mediterranean region

Pharmacy workforce intelligence (PWI) involves the development, implementation, and evaluation of effective strategies and tools to ensure the availability and quality of pharmacy workforce (PW). Academic capacity (AC) is essential in producing graduates for PW, while quality assurance (QA) in education is crucial in developing competent PW. There is a lack of information about PWI in the Eastern Mediterranean Region (EMR). Based on the available data, there is a notable imbalance in PW distribution in EMR. This study aimed to evaluate the status of AC and QA of pharmacy education in the EMR using the International-Pharmaceutical-Federation (FIP)’s Development-Goals and their associated mechanisms as a framework. An explanatory sequential mixed-methods approach was used. The quantitative phase involved distributing a validated questionnaire among pharmacy leaders of all accessible pharmacy schools in the EMR. The qualitative phase involved the conduct of semi-structured interviews with pharmacy leaders, and the data were thematically analysed. Of 112 identified pharmacy leaders, 61 participated in the survey (response rate, 55%) and 14 participated in the interviews. Most data were consistent among the quantitative and qualitative results. In both phases, most participants reported implementing a student – teacher ratio (70%), periodic accreditation (82%), adoption of global QA standards (67%), and involving key stakeholders in programme development. Enrolment planning based on workforce needs (51%) and capacity-building for teacher-practitioners (47%) were less common and less emphasised in interviews. Although some AC and QA mechanisms are achieved, many require further improvement. Policymakers could establish a national body representing PW, improve workforce data systems for evidence-based enrolment planning, invest in faculty development, and standardised QA frameworks. Standardising stakeholder engagement and enhancing graduate tracking would further ensure that programmes remain aligned with workforce and health system needs.

Acceptance and the willingness to pay for human papilloma virus (HPV) vaccine: A systematic review

Human papillomavirus (HPV) is a major global health concern due to its link to cervical and other cancers. Although HPV vaccination is highly effective, acceptance and willingness to pay (WTP) differ widely across populations. This review summarizes global evidence from 2015–2025. A systematic search of PubMed, Scopus, CENTRAL, Web of Science, and Google Scholar was conducted in 2025 following PRISMA guidelines. Studies reporting data on knowledge, acceptance, attitudes, and WTP across any population were included. Quality assessment used ISPOR checklists, and data were synthesized in Excel 2019. Thirty-five studies met inclusion criteria, with China and Nigeria contributing most. WTP ranged from 52.68% in lower-middle-income countries to 65.38% in low-income countries. Mean WTP was highest in upper-middle-income settings. Knowledge, positive attitudes, socioeconomic status, and trust increased WTP, while cost remained the primary barrier. Improving affordability, awareness, and policy support is essential to enhance global HPV.

Sustainable Development of Aquaculture in Egypt: A Review of Key Challenges and Solutions

The Egyptian aquaculture sector ranks as the seventh largest in the world and the leading producer in Africa, contributing 67% of the total output of the continent and supplying 78% of domestically produced fish. Despite significant growth, the sector has experienced a production decline since 2020. This review aimed to understand the key challenges behind this decline, assess their impact on aquaculture sustainability, and explore potential solutions to enhance resilience and long-term growth. Significant sustainability challenges include temporary farm removal orders, large-scale water projects exacerbating scarcity, and climate change risks such as coastal flooding, each of which could reduce the production capacity of the sector by 50% or more. The sector relies heavily on illegally collected wild seeds (which account for 34% of production), further weakening its resilience, alongside other pressing constraints aggravated by governance shortcomings. Addressing these issues requires integrated solutions, including genetic improvement, the development of sustainable local feed alternatives, adopting best management practices, and enhancements to existing aquaculture systems. Strengthening governance is crucial for equitable resource distribution, effective regulatory enforcement, and fostering stakeholder collaboration. This review provides a foundation to assist stakeholders in developing strategic plans for the aquaculture sector and reinforcing its contribution to food security and economic development.

Real-Time Utility Assessment of Privacy-Anonymized Data: A Cross-Domain Framework for Smart Cities

Smart cities collect lots of data from sources like traffic systems and sensors. This data is vital for improving services such as transport management, public safety, energy saving, and citizen involvement. However, keeping people’s privacy secure by making data anonymous can make the data less useful. Anonymization methods include mix-zones, pseudonymization, and data masking. Existing systems often evaluate the usefulness of data after it’s processed, but usually can not adjust to changes in real-time or work well across different fields. It also does not typically consider fairness for individuals or integrate well with privacy-preserving data methods on devices, which are crucial for city services needing quick responses. This paper presents a new system to assess anonymized data in smart cities in real-time. The system includes four main components: 1. A real-time tool that continuously monitors how anonymization affects data quality across various areas. 2. A utility model that adjusts usefulness scores based on the needs of different smart city services. 3. A module that detects and addresses unfair differences in data usefulness caused by anonymization. 4. A data combination layer that operates well on devices, allowing on-site decision-making while complying with privacy regulations like GDPR. The framework is tested with multiple real-world transportation datasets, anonymized in different ways, and applied to tasks like traffic prediction, anomaly detection, and location-based services. The results demonstrate that the framework provides accurate data usefulness estimation with minimal computing effort, and it offers fair, situation-specific trade-offs in usefulness in real-time. This work connects privacy and usefulness, offering a scalable solution for responsibly using anonymized data in smart city environments. The framework is validated on both transportation and smart energy datasets, demonstrating consistent improvements in privacy–utility–fairness balance and confirming its generality across smart-city domains.

A SHAP-Driven XAI Architecture with Blockchain Support for Cryptocurrency Price Prediction

Predicting cryptocurrency prices remains difficult due to extreme market fluctuations, hidden nonlinear relationships, and the strong influence of public sentiment and unexpected events. Although deep learning models such as LSTMs and attention-based architectures can capture these complex dynamics, their lack of transparency limits their acceptance in financial settings. To address this issue, this work introduces an explainable AI framework that integrates SHapley Additive exPlanations (SHAP) with a blockchain-backed prediction pipeline. The proposed system combines traditional numerical indicators such as historical closing prices, volume-based metrics, and technical analysis features with sentiment signals extracted from social media platform X, enabling the model to respond more effectively to diverse sources of information. Experiments conducted on Bitcoin and Ethereum datasets show that the framework outperforms standard predictive baselines, reaching an RMSE of 188.3, a MAPE of 3.45%, and an R 2 score of 0.953. SHAP-based interpretation reveals that previous-day prices, RSI values, and sentiment intensity are the most influential contributors to prediction outcomes. A user study involving financial analysts indicates that 78% of participants found the explanations clear and expressed greater confidence in the model’s outputs. To ensure integrity and accountability, the system records both predictions and their SHAP explanations on the Ethereum test network, providing an immutable and auditable trace with minimal computational overhead. Overall, this study presents a unified framework that strengthens prediction accuracy while offering interpretable and verifiable insights, helping overcome the traditional black-box limitations of AI methods in cryptocurrency price prediction.

Commentary on “Exploring the Immune Response to COVID ‐19 Vaccines in Dialysis and Transplant Patients”

Coumarin‐Augmented Thiazole Hybrids as Dual Anticancer and Antibacterial Agents

ABSTRACT Coumarins are a privileged scaffold in medicinal chemistry, renowned for diverse therapeutic activities including antiviral, anticancer, and neuroprotective effects. Building on our previous work with 3‐substituted coumarins as inhibitors of tumor‐associated carbonic anhydrases, we report a novel series of thiazol‐hydrazono‐coumarins targeting the ATP‐binding domain of topoisomerase enzymes. Seventeen compounds were synthesized and evaluated for selective cytotoxicity against HeLa cells versus WI‐38 fibroblasts and for antimicrobial activity against four ESKAPE pathogens, Escherichia coli , and Salmonella typhimurium . Several derivatives showed potent antibacterial activity, with MICs as low as 0.12 μg/mL against resistant Staphylococcus aureus strains and inhibition zones up to 33 mm against Gram‐negative bacteria. Compound 13 exhibited strong selectivity, with an IC 50 of 26.8 μg/mL in HeLa cells and 220.7 μg/mL in WI‐38 cells. The five most active compounds were studied via molecular docking and MM/GBSA to elucidate their binding to bacterial DNA gyrase, topoisomerase IV, and human topoisomerase IIα. A molecular dynamics simulation of the S. aureus DNA gyrase B‐compound 13 complex revealed a novel hydrogen bond between the coumarin ring and serine‐129. These findings highlight thiazol‐hydrazono‐coumarins as promising antibacterial leads with ancillary anticancer activity, supporting their potential in treating infections in immunocompromised cancer patients.

Reversing frailty: The transformative effects of structured physical‐activity‐based physiotherapy on physical, cognitive and emotional health in older adults—An evidence‐based systematic review

Abstract Background Elderly frailty is a multifaceted clinical condition with diminished physiological reserves and increased stress susceptibility. It increases disability, hospitalization and mortality rates, requiring multidomain therapy. Structured physical‐activity‐based medical treatment can reduce frailty in physical, mental and emotional areas. This assessment distinguishes outcomes among validated frailty models (phenotype‐based vs. deficit‐accumulation) to highlight model‐specific effects. Objectives The present systematic review assesses the efficacy of structured physical‐activity‐based physiotherapy in reducing frailty and enhancing physical, cognitive and emotional outcomes in persons aged ≥60. It highlights a critical data gap neglected by past studies by distinguishing intervention effects across proven frailty models (phenotype‐based and deficit‐accumulation frameworks). Methodology The review used PRISMA criteria and the PICOS framework to find relevant papers published between January 2002 and December 2025. PubMed, Scopus, Cochrane Library and Embase were searched. RCTs and longitudinal cohort studies on physiotherapy or structured physical‐activity therapies (e.g. resistance training, aerobic conditioning, balance exercises, multimodal programs) for individuals aged ≥60 years were eligible. Frailty, physical performance and quality of life were evaluated. Cochrane Risk of Bias 2.0 was used for randomised studies and ROBINS‐I for non‐randomised designs. Results 36 trials covered varied physiotherapy and structured physical‐activity regimens. Participants, mostly aged ≥60, were mostly women (approximately two‐thirds of the sample). The majority of investigations found that resistance training increased muscle strength and decreased frailty by 20%–35%. Exercises involving balance reduced fall risk by 25%–35%, while aerobic workouts improved gait and cardiovascular fitness. Multimodal interventions reversed frailty in 41%–50% of individuals and improved cognitive and emotional outcomes the highest. Physical performance, quality of life and functional independence improved across frailty models in weighted summaries. Conclusion Structured physical‐activity‐based physiotherapy therapies, especially multimodal programs, reduce frailty and enhance physical, cognitive and emotional resilience in older persons, highlighting their value in comprehensive geriatric care.

Artificial Intelligence in Physiotherapy Education: A Multi‐Country Middle East Survey of AI Acceptance and Barriers Among University Students

ABSTRACT Artificial Intelligence (AI) is reshaping healthcare education, yet structured AI training within physiotherapy programmes remains uneven across the Middle East. We conducted a cross‐sectional, multi‐country online survey of 3195 undergraduate and internship‐level physiotherapy students from nine Middle Eastern countries (Egypt, Jordan, Lebanon, Libya, Palestine, Saudi Arabia, Sudan, Tunisia, and the United Arab Emirates). Using Technology Acceptance Model (TAM) constructs—perceived usefulness (PU) and perceived ease of use (PEOU)—we examined factors associated with AI acceptance and students' perceived barriers to AI integration in physiotherapy education. AI acceptance differed significantly by country (highest in the UAE and lowest in Tunisia), gender (male > female), academic level, GPA, and income ( p  < 0.05). Prior AI workshop participation, use of specific AI tools (e.g., DeepSeek), perceived time‐management benefits, and trust in AI were associated with higher acceptance. In multivariable regression, these sociodemographic and AI‐exposure variables explained 24.4% of the variance in AI acceptance. These findings indicate substantial regional disparities in AI preparedness and access, supporting the need for equitable, competency‐based AI education and governance policies tailored to physiotherapy training across the Middle East.