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Magnitude of workplace violence and associated factors among healthcare professionals in East Africa: A systematic review and meta-analysis

Introduction Workplace violence refers to violent acts that occur in the workplace against employees while they are delivering services to consumers. This phenomenon is an invasive and alarming issue affecting employees worldwide, posing both implicit and explicit threats to their health, safety and well-being. According to a World Health Organization report and study findings, 20% to 38% of healthcare workers have experienced physical violence at some point during their careers, compared to employees in other sectors. This study aimed to assess the pooled magnitude of workplace violence and to identify its associated factors among healthcare professionals in East Africa. Method The study protocol was registered with PROSPERO under registration number CRD42024552266. An extensive electronic database search was conducted from August 10–31, 2024, using PubMed, Google Scholar, Web of Science, and manual Google searches. The extracted data were exported into STATA version 17 for analysis. A weighted inverse-variance random-effects model was used to calculate the pooled magnitude of workplace violence and to determine the impact of predictors on the workplace violence. Publication bias was checked by a funnel plot and Egger’s test. Heterogeneity was assessed using I2 statistic and Galbraith plot. Subgroup and sensitivity analyses were conducted to investigate the sources of heterogeneity. Results A total of 25 studies involving 9,648 participants were included in this study. The pooled magnitude of workplace violence was 55.64% (95% CI: 48.32, 62.96; I2 = 97%, p < 0.01). Factors significantly associated with workplace violence included working in the emergency department (AOR = 4.3, 95% CI: 3.22, 5.39), younger age (AOR = 3.01, 95% CI: 1.42, 4.60), less work experience (AOR = 5.14, 95% CI: 2.67, 7.61), being female (AOR = 2.74, 95% CI: 1.54, 3.95), and alcohol consumption (AOR = 3.17, 95% CI: 1.52, 4.83). Conclusion The magnitude of workplace violence in the region was relatively prevalent, with significantly higher odds among emergency department staff, younger healthcare professionals, those with less work experience, female professionals, and individual reporting alcohol consumption.

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IFN-β therapy rescues dysregulated IFN-stimulated proteins, serum cytokines, and neurotrophic factors in multiple sclerosis: Multiplex analysis of short-term and long-term IFN responses

Introduction Dysfunctional regulatory T cells and subnormal responses to interferon-β disrupt the immune system in multiple sclerosis. We probed dysregulated type I IFN pathways in vitro and in vivo IFN-β to induce transcription factors, cytokines, and neurotrophic factors. Methods 36 MS-relevant serum proteins curated to be relevant to MS were detected with multiplex and IFN activity assays plus western blots of mononuclear cells from 15 partial responders (PR) to IFN-β therapy with exacerbations over five years of treatment, and 12 clinical responders (CR) without exacerbations. Response was measured 0, 4, and 24 hours after injection of 16 million units (MU) of IFN-β (double-dose) and 8 MU (standard dose), in clinically stable PR and CR, and 16 MU IFN-β in paired PR during exacerbations, an IFN-resistant state. IFN-β effects after therapy washout were compared to 15 therapy-naïve stable and 13 active RRMS and 18 healthy controls (HC). Results IFN-β injection corrected subnormal levels of p-S-STAT1 transcription factor and induced antiviral MxA and type I IFNs. IFN-β induced anti-inflammatory IL-4, IL-10, IL-12p40, and TNFRII more strongly in stable PR than CR. Th2 cytokines correlated with serum vitamin D levels in CR. During exacerbations, IFN-β injections induced Th1, Th2, and neurotropic proteins. After therapy washout, serum IFN-α/β and pro-inflammatory IL-12p70 levels were lower in stable CR than in PR. In therapy-naïve MS, Th1, Th2, and neurotrophic protein levels were surprisingly subnormal and poorly intercorrelated. Long-term IFN-β therapy elevated serum proteins and brought them to a balanced positively-correlated state, echoing HC. Conclusions IFN-β corrects low serum type I IFN levels, enhances responses to subsequent IFN exposure, induces immunoregulatory and neuroprotective proteins, and balances dysregulated and subnormal serum cytokine levels. Low serum IFN and IFN-β-induced proteins link to better long-term response to IFN-β therapy. Correction of immune disruption suggests new mechanisms for immunopathology and therapy.

Comparing efficacy and adherence of smartphone-guided exercises to conventional self-directed exercises for neck pain in office workers: A randomized controlled trial protocol

Background Self-exercises focusing on strength and endurance training, as well as self-mobilization, are effective in neck pain (NP). This study aims to investigate the differences in self-management using two workplace-based interventions: a smartphone application consisting of personalized neck exercises compared to conventional approach (self-exercises program on paper) in chronic NP office workers. Methods The project is a prospective, superiority, randomized controlled trial. Fifty participants with chronic NP will be randomly assigned into the interventional group (IG, n = 25), utilizing the smartphone application, or the control group (CG, n = 25). The CG includes the use of a paper sheet with exercises and recommendations, and the IG includes the use of a smartphone application, which provides individualized exercise programs. Both protocols will last three months and will be preceded by an educational session at baseline for all participants. The main outcome measure comprises pain intensity evaluated according to the pain intensity number rating scale. Secondary outcomes are function evaluated according to the neck disability index, quality of life according to the short form 12, and participants’ adherence to self-exercises. Outcome measures will be collected at baseline, and one and three months of follow-up. Discussion The current project will evaluate the effectiveness of a smartphone application consisting of personalized neck exercises, when compared with a conventional approach for self-rehabilitation. The smartphone application will allow to monitor the participants’ status and to help resolving the problem of adherence to self-exercises in chronic NP. Despite some limitations may be related to the short follow-up duration, the study findings could help to develop evidence-based knowledge about the impact of workplace interventions using new technologies in mitigating discomfort and promoting well-being among affected workers. Trial Registration ClinicalTrials.gov. NCT06485804 Registered on July 1, 2024.

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End user experiences of an electronic health records platform in a tertiary hospital system in Kenya

Background Electronic Health Record (EHR) systems allow health care facilities to provide better care to patients and improve overall provider efficiency. They are vital for low-and middle-income countries in achieving the United Nations Sustainable Development Goal of ensuring healthy lives and promoting the well-being of all their citizens. This study aimed to evaluate perceptions and usage of a comprehensive EHR by end-users after its deployment into a tertiary hospital system and its outpatient centers in Kenya and also aimed to understand the effectiveness of various implementation strategies deployed by the institution during their implementation process. Methods We conducted a cross-sectional study between October 2023 and January 2024 at the Aga Khan University Hospital, Nairobi with staff involved in using the EHR system. A standardized electronic questionnaire was shared with the users and responses were captured on REDCap after obtaining written consent electronically. Results Of the 548 participants who agreed to join the study, 471 responded to the survey in full. Most respondents (420, 89.9%) stated that the EHR made their work better or much better, compared to a paper-based system. Majority of end-users stated that the EHR benefited their practice (378, 87.1%), provided autonomy to healthcare workers (382, 86.2%), the quality of healthcare (424, 95.5%), interactions within the healthcare team (353, 79.1%) and enjoyment of their clinical practice (360, 80.7%). Conclusion The majority of end users believed the EHR to be effective and appropriate to use within this specific and unique healthcare system. The specific strategies deployed by institution were also successful in ensuring high rates of EHR usage and can be looked at as a blueprint for future EHR deployments in other sub-Saharan African healthcare systems.

Patient demographics, medical factors, treatment modalities and satisfaction at five traditional Chinese medicine practices in Switzerland: A cross-sectional study

Background Traditional Chinese Medicine (TCM) is increasingly integrated into healthcare and insurance systems, therefore, it is essential to understand its current status and patients’ perspectives. Methods This cross-sectional study was conducted from January 1st to December 31st, 2023, across five TCM practices in Switzerland. All patients attending their sixth therapy session were invited to complete an electronically anonymized questionnaire covering patient demographics, treatment experiences, and satisfaction. Results A total of 461 patients participated in the survey, with the majority being female (60.1%) and aged 50 years or older (57.4%). Among them, 54.0% reported multiple health conditions, with 32.9% having musculoskeletal disorders and 31.8% suffering from chronic pain as the main reasons for seeking therapy. Most patients received weekly TCM treatments (91.3%), with 50.7% also undergoing conventional therapies. Of the respondents, 50.0% reported full coverage for their TCM therapy costs. Access to TCM was primarily through personal recommendations (44.5%), and 92.2% of patients reported waiting less than 10 minutes before each therapy session. Acupuncture was the predominant treatment (95.7%), with 35.8% receiving additional dietary advice. The overall patient satisfaction rate stood at 96.5%, with 99.5% indicating their intention to continue receiving TCM treatments. Notably, patients with full insurance coverage for TCM treatment costs demonstrated significantly higher treatment satisfaction compared to those with no coverage (odds ratio = 2.42, 95% confidence interval [1.10 to 5.31], p = 0.028). By contrast, other evaluated medical factors did not show statistically significant associations with treatment satisfaction. Conclusion This study revealed that women, patients aged over 50, and individuals with multiple health conditions, particularly musculoskeletal disorders and chronic pain, are more likely to seek regular integrated TCM treatment. Patients reported high levels of satisfaction with TCM, with treatment satisfaction significantly higher among those with full insurance coverage for TCM treatment costs compared to those without coverage. Future research should enroll a broader range of TCM practices and patient populations to enhance the generalizability of these findings and accurately evaluate how insurance coverage influences TCM satisfaction, thereby better addressing patient needs.

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Performance of large language models ChatGPT and Gemini in child and adolescent psychiatry knowledge assessment

Objective This study evaluates the performance of four large language models—ChatGPT 4o, ChatGPT o1-mini, Gemini 2.0 Flash, and Gemini 1.5 Flash—in answering multiple-choice questions in child and adolescent psychiatry to assess their level of factual knowledge in the field. Methods A total of 150 standardized multiple-choice questions from a specialty board review study guide were selected, ensuring a representative distribution across different topics. Each question had five possible answers, with only one correct option. To account for the stochastic nature of large language models, each question was asked 10 times with randomized answer orders to minimize known biases. Accuracy for each question was assessed as the percentage of correct answers across 10 requests. We calculated the mean accuracy for each model and performed statistical comparisons using paired t-tests to evaluate differences between Gemini 2.0 Flash and Gemini 1.5 Flash, as well as between Gemini 2.0 Flash and both ChatGPT 4o and ChatGPT o1-mini. As a post-hoc exploration, we identified questions with an accuracy below 10% across all models to highlight areas of particularly low performance. Results The accuracy of the tested models ranged from 68.3% to 78.9%. Both ChatGPT and Gemini demonstrated generally solid performance in the assessment of in child and adolescent psychiatry knowledge, with variations between models and topics. The superior performance of Gemini 2.0 Flash compared with its predecessor, Gemini 1.5 Flash, may reflect advancements in artificial intelligence capabilities. Certain topics, such as psychopharmacology, posed greater challenges compared to disorders with well-defined diagnostic criteria, such as schizophrenia or eating disorders. Conclusion While the results indicate that language models can support knowledge acquisition in child and adolescent psychiatry, limitations remain. Variability in accuracy across different topics, potential biases, and risks of misinterpretation must be carefully considered before implementing these models in clinical decision-making.

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A move in the right direction: Tracking the traceability of British Thoroughbreds outside of racing

Horse welfare within/after racing is often questioned by the public. British Racing’s Horse Welfare Board’s “A life well-lived” strategy provides a blueprint for Thoroughbred welfare, advocating accurate lifetime traceability of horses as essential to achieve this. The Census aimed to establish a population density model for British Thoroughbreds, not actively engaged in racing. Equestrians who owned/kept a Thoroughbred were asked to complete the Census between May and December 2023. Frequency analysis identified patterns in passport compliance, knowledge and understanding of current systems, and profiled Thoroughbred demographics: age, use, and history. Records for 8,256 horses were analysed (margin of error: ± 1%, 99% CI); 98% of horses had a passport, but only 64% were in their current owner’s name despite 90% being aware that they should have changed the horse’s registration details. Horses were predominately owned (91%), were geldings (74%), and aged between 5–14 years (63%); Leisure riding, hacking, and unaffiliated competition were the most common activities participated in; no significant differences in registration compliance occurred between activities. The Census provides an accurate representation of British Thoroughbreds not actively involved in racing totalling 33,600 horses, with 80% traceable. The results offer an insight into owner/keeper decision-making with respect to horse registration and Thoroughbred usage after racing. A need to improve current equine traceability systems through digitalisation and simplification was voiced, alongside enhanced communication strategies to showcase why compliance is important. Ongoing accurate records are essential to support education, research, and strategy to safeguard Thoroughbred welfare across their racing and second careers.

Health effects of occupational noise exposure on heavy-duty equipment operators and exposed workers in a mining firm in Ghana

Background The mining industry is one of the sectors that uses heavy-duty equipment in its daily operations. This exposes miners to undesirable noise levels, increasing their risks of health-related problems. However, published data on the health effects of occupational noise exposure on miners in Ghana are limited, and this can affect potential interventions to promote miners’ health and safety. This study, therefore, assessed noise-exposure levels and associated health-related problems among heavy-duty equipment operators and other exposed workers in a mining firm in Ghana. Methods A cross-sectional study involving 316 randomly selected heavy-duty equipment operators and exposed workers was conducted from 29th March 2023–31st May 2023. Data on socio-demographic and work-related characteristics, including age, mining experience, knowledge of noise-induced hearing loss (NIHL), noise exposure levels and health-related problems, were collected using a pretested questionnaire. Logistic regression models were used to identify significant predictors of health-related problems. Results The mean age of study participants was 33.8 (±7.5) years with a range of 21–60 years. The prevalence of health-related problems in the twelve months before the study was 55.7%. The commonly reported health-related problems included hearing difficulties (84.1%), hearing loss (49.4%), and sleeping difficulties (36.9%). Approximately 68.6% of the workers were exposed to noise levels that were unacceptable. After adjusting for significant covariates, factors such as working experience of 5–9 years (AOR: 4.25, 95%CI: 1.92–9.40), inadequate knowledge of NIHL (AOR:1.78, 95%CI: 1.03–3.09) and exposure to unacceptable noise levels (AOR = 5.52, 95%CI = 2.91–10.48) were independently associated with health-related problems. Conclusion The prevalence of health-related problems among the workers was high. Potential strategies, including a hearing conservation program to promote health and safety among these workers at the workplace, should target reducing the exposure to high noise levels and increasing awareness of NIHL.

Detection and score grading for prostate adenocarcinoma using semantic segmentation

Prostate cancer is a major global health challenge. In this study, we present an approach for the detection and grading of prostate cancer through the semantic segmentation of adenocarcinoma tissues, specifically focusing on distinguishing between Gleason patterns 3 and 4. Our method leverages deep learning techniques to improve diagnostic accuracy and enhance patient treatment strategies. We developed a new dataset comprising 100 digitized whole-slide images of prostate needle core biopsy specimens, which are publicly available for research purposes. Our proposed model integrates dilated attention mechanisms and a residual convolutional U-Net architecture to enhance the richness of feature representations. Class imbalance is addressed using pixel expansion and class weights, and a five-fold cross-validation method ensures robust training and validation. In model ensemble evaluation, the model achieves an average Dice of 0.87 and accuracy of 0.92 on the cross-validation held-out folds. When applied to completely unseen, external test data, the model demonstrates an average Dice of 0.64 and accuracy of 0.81. Segmentation and grading results were validated by a team of expert pathologists. Based on experimental results, this study demonstrates the potential of our proposed method and model as a valuable tool for the detection and grading of prostate cancer in clinical settings.

Measurement properties of instruments used to measure health-related quality of life in pediatric and adults patients with inherited epidermolysis bullosa: A systematic review and meta-analysis protocol

Inherited Epidermolysis Bullosa (EB) is a group of rare, genetic skin diseases characterized by extreme fragility of the skin and mucous membranes, leading to blistering and wounds in response to minimal trauma or friction. These clinical manifestations significantly reduce health-related quality of life (HRQoL). The objective of this protocol article is to provide information about the methods planned to be used to assess the measurement properties of HRQoL instruments specifically developed for EB patients of all age groups through a systematic review and meta-analysis. The protocol followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols (PRISMA-P) guideline. The literature search will be conducted in PubMed, Web of Science (WOS) and EMBASE, including terminology that aligns with the four key elements of the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) research question (construct, target population, measurement properties and type of PROM), as well as the terminology proposed by COSMIN for measurement properties. Studies that include information on measurement properties (specifically, validity and/or reliability) with a sample of patients with inherited EB will be selected. Both title and abstract screening and full text review, will be conducted by two independent reviewers using the Rayyan tool. In addition, the risk of bias will be assessed using the COSMIN-Risk of Bias checklist. The data from each study and each measurement property will be summarized in accordance with the COSMIN guidelines. The evidence gathered will strive to adjudicate data on measurements properties of HRQoL instruments used in EB patients, and the limitations of the future systematic review will be discussed. Ultimately, results of the future systematic review will help develop more personalized guidelines for the assessment of HRQoL in EB patients of all age groups. The protocol is registered in OSF with registration number vrm87: https://osf.io/vrm87/

Investigating the use of physics informed neural networks for dam-break scenarios

The real-time forecasting of flood dynamics is a long-standing challenge traditionally addressed through numerical solutions of the Shallow Water Equations (SWEs). Numerical solutions of realistic flow problems using numerical schemes are often hindered by high computational costs, particularly due to the need for fine spatial and temporal discretization, complex boundary conditions, and the resolution of non-linearities inherent in the governing equations. In this study, we investigate the use of Physics-Informed Neural Networks (PINNs) to solve 1D and 2D SWEs in dam-break scenarios. The proposed PINN framework incorporates the governing partial differential equations along with the initial and boundary conditions directly within the training process of the network, ensuring physically consistent solutions. We conduct a systematic comparison of the solutions of SWE using the classical numerical scheme (Lax-Wendroff) with estimates of physics informed neural networks. For 1D SWE, a neural network is trained and validated on a dam-break problem, revealing that physics-informed models produce smoother but still acceptable estimates of wave propagation compared to standard numerical results. For 2D SWE, we consider various configurations of dam geometries along with varying initial profiles for water heights. Across all scenarios, reproduce the numerical baselines, albeit with limited accuracy, while avoiding spurious oscillations and numerical artifacts. Further tuning, achieved by incorporating numerical solutions into the PINN training, improved accuracy. This proof of concept demonstrates the potential of hybridized PINNs as a mesh-free, scalable, and generalizable framework for approximating solutions to nonlinear hyperbolic systems. Our results indicate that pre-trained, physics-informed models could serve as a viable alternative for real-time flood forecasting in complex domains.

Experimental exploration of artificial intelligence and ADAMS simulation technology in the teaching of vertical hoop upward throw in rhythmic gymnastics

Currently, rhythmic gymnastics teaching mainly focuses on traditional techniques and cannot break through issues such as blind spots in the coordination training between apparatus and body. In the academic field, research results are still dominated by single aspects such as new rules and event analysis. ADAMS technology can provide an innovative path to solve the above problems in rhythmic gymnastics teaching and scientific research. Based on the analysis of the advantages of ADAMS simulation technology and the theoretical basis for artificial intelligence technology to adapt to educational paradigms, this paper first uses ADAMS software to model the rhythmic gymnastics hoop through steps including model import, material definition, constraint relationship establishment, driving and force application, and simulation setting. It then conducts simulation of the vertical hoop thrown upward at two different angles (30 degrees and 45 degrees) and makes a comparative analysis of the counterclockwise and clockwise rotations of the vertical hoop thrown upward at the same angle. Furthermore, it carries out teaching experiments to explore the practical application of artificial intelligence technology in the teaching of upward throwing of the vertical hoop in rhythmic gymnastics, and draws the following conclusions: (1) The choice of projection angle has a differential impact on movement efficiency: a 30° projection angle is more suitable for basic standardized training due to its stable trajectory and moderate displacement, while a 45° projection angle is more conducive to enhancing artistic expression by virtue of its advantage in air retention. (2) Rotation direction has a significant impact on technical efficiency: clockwise rotation strengthens the spatiotemporal consistency of apparatus throwing and catching, while counterclockwise rotation optimizes the fluency of movement connection. Combined training can meet the requirements for innovative scoring. (3) ADAMS technology significantly improves teaching effectiveness through accurate trajectory prediction and mechanical analysis. Experimental data confirm that it is superior to traditional teaching methods in terms of skill mastery, interest stimulation, and satisfaction. It is suggested that efforts should be made to construct an intelligent teaching closed-loop system based on ADAMS technology and promote a dual-track model of “scientific quantification-artistic expression”, which is conducive to the scientific and intelligent development of physical education and art courses in colleges and universities.

Significant increase in eco-efficiency of China’s grain production from 2000 to 2022: Trend changes, typological evolution, and driving factors

Enhancing the eco-efficiency of grain production is a critical avenue for ensuring food security and ecological sustainability. This study employs a global super-efficiency SBM model incorporating undesirable outputs, combined with the life cycle assessment method, to comprehensively measure the eco-efficiency of grain production in 31 Chinese provinces and municipalities from 2000 to 2022. Furthermore, we conduct a comprehensive analysis of the distributional dynamics and key driving factors of the eco-efficiency of grain production. The findings indicate that: (1) The overall level of eco-efficiency in China’s grain production is relatively low, exhibiting significant regional disparities. The spatial pattern follows the gradient of “major grain-producing regions> production-sales balance regions> the major grain-consuming regions,” with most provinces yet to reach the efficiency frontier. (2) The eco-efficiency of grain production in China generally exhibits an upward trend, although there are indications of spatial polarization, evident “club convergence” characteristics, and a notable “positive spillover” effect. (3) The eco-efficiency of grain production in China is influenced by a complex interplay of factors, including economic, social, technological, demographic, and natural elements. The gross total agricultural output, water resources endowment, and structure of agricultural production emerge as the critical driving factors, manifesting the Matthew effect of “the rich getting richer and the poor getting poorer.” The findings of this study provide a foundation for the refinement of sustainable grain production policies and the promotion of green agricultural transformation.

Work engagement and its association with emotional intelligence and demographic characteristics among nurses in Palestinian neonatal intensive care units

Introduction Work engagement, defined as a positive, fulfilling, work-related state of mind characterized by vigor, dedication, and absorption, is crucial for nurse retention and quality of care in high-stress environments. Neonatal Intensive Care Units (NICUs) present unique emotional and psychological challenges for nurses, necessitating skills like emotional intelligence (EI) to enhance work engagement. This study investigates the association between EI, demographic factors, and work engagement among Palestinian NICU nurses. Methods A cross-sectional, descriptive correlational design was employed during February-April 2025. Of 230 nurses invited, 207 completed the survey (response rate = 90.2%) across 12 Palestinian NICUs using convenience sampling. Data analysis was conducted using descriptive statistics, Pearson’s correlation, and multiple linear regression via SPSS v26. Validated tools, the Schutte Self-Report Emotional Intelligence Test (SSEIT) and Utrecht Work Engagement Scale (UWES), were used. Results Emotional intelligence (EI) demonstrated a strong positive correlation with work engagement (r = 0.693, p < 0.001), accounting for 48.0% of the variance in engagement scores. Age (B = 0.463, β = 0.535, p = 0.002), female gender (B = −2.250, β = −0.115, p = 0.017), and rotating shifts (B = 1.579, β = 0.105, p = 0.028) were significant predictors. EI was the strongest predictor (B = 0.358, β = 0.593, p < 0.001). The EI subdimension “utilizing emotions” scored highest (M = 47.3 ± 5.8). Discussion The findings demonstrate strong associations between EI and engagement in high-stress NICU environments. Based on these findings, we propose implementing comprehensive EI training programs in nursing curricula, establishing mentorship programs to address age-related disparities, and developing gender-sensitive workplace policies to optimize work engagement and improve patient care quality.

Policy landscape analysis for fruits and vegetables in four low- and middle-income countries through a food systems approach

Low fruit and vegetable intake is a significant nutritional issue in low- and middle-income countries, where resolving all forms of malnutrition remains a pressing challenge. Nutritional status is influenced by many dietary factors, and enhancing fruit and vegetable consumption offers significant health benefits and contributes to overall dietary quality. The study aimed to examine the policy landscape for fruits and vegetables across the food system in four low-middle income countries (Benin, Sri Lanka, Tanzania, the Philippines) and identify opportunities to strengthen food systems policies to enhance fruit and vegetable consumption as part of a comprehensive strategy to improve nutrition outcomes. A comparative qualitative analysis of policy documents (n = 14 [Benin], 18 [Sri Lanka], 30 [Tanzania], 55 [the Philippines] relevant to fruits and vegetables at the national and subnational levels, framed by a food systems framework, was conducted. A modified SWOT analysis was then conducted to formulate strategic policy recommendations to improve consideration of fruits and vegetables in policies tackling food system aspects. The analysis revealed specific opportunities for strengthening policy prioritization of fruits and vegetables across the food system such as multisectoral collaboration, policy integration between the national and subnational level, sustainability and resilience, and inclusion and equity. By addressing factors influencing fruit and vegetable intake within a dynamic food system, these countries and others facing challenges to the consumption of fruits and vegetables can effectively promote diet quality, improve food security, and address all forms of malnutrition through better policy design and particularly implementation.

Sustainable heavy metal immobilization in contaminated soils using plant-derived urease-driven biomineralization

Soil contamination by heavy metals presents substantial ecological and geotechnical risks, thereby demanding sustainable remediation strategies. Conventional approaches, including chemical stabilization and microbial-induced carbonate precipitation (MICP), are limited by high costs, ecological disturbances, and sensitivity to environmental stressors. A plant-derived urease-driven enzyme-induced carbonate precipitation (EICP) system was evaluated for immobilizing cadmium (Cd2⁺), lead (Pb2⁺), and zinc (Zn2⁺) in contaminated soils. Systematic screening revealed that jack bean and watermelon seed ureases are optimal catalysts for heavy metal sequestration, achieving efficiencies of 87.3% for Cd2 ⁺ , 91.5% for Pb2 ⁺ , and 76.4% for Zn2 ⁺ . These high efficiencies are attributed to their catalytic specificity and the retained enzymatic activity under environmental stress. Critical process parameters were fine-tuned through iterative experimentation, maintaining a urea-CaCl₂ reaction stoichiometry of 1.5:1 molar ratio and calibrating the enzyme dosage to 1.2 U/g of soil matrix. This optimized operational range effectively promoted carbonate mineralization while preserving essential soil hydraulic properties, as evidenced by sustained permeability exceeding 10 ⁻ ⁵ cm/s throughout precipitation cycles. Durability assessments under simulated acid rain and freeze-thaw cycles demonstrated 82.5% retention of Cd2⁺ and 92.7% retention of unconfined compressive strength, outperforming conventional lime and MICP treatments. X-ray diffraction analysis confirmed the presence of stable crystalline phases. Field validation confirmed that the EICP protocol can be feasibly scaled to real-world sites with operational costs averaging $52 per cubic meter, representing a 61% reduction compared to microbial-based treatments. This plant-based EICP approach offers a scalable and cost-effective solution for ecological restoration and geotechnical stabilization in contaminated soils, demonstrating significant potential for sustainable environmental management.