Data System Research Articles (Page 1)

Shear wave elastography (SWE) has been investigated as a complement to B-mode ultrasound for breast cancer diagnosis. Although multicenter trials suggest benefits for patients with Breast Imaging Reporting and Data System (BI-RADS) 4(a) breast masses, widespread adoption remains limited because of the absence of validated velocity thresholds. This study aims to develop and validate a deep learning (DL) model using SWE images (artificial intelligence [AI]-SWE) for BI-RADS 3 and 4 breast masses and compare its performance with human experts using B-mode ultrasound. We used data from an international, multicenter trial (ClinicalTrials.gov identifier: NCT02638935) evaluating SWE in women with BI-RADS 3 or 4 breast masses across 12 institutions in seven countries. Images from 11 sites were used to develop an EfficientNetB1-based DL model. An external validation was conducted using data from the 12th site. Another validation was performed using the latest SWE software from a separate institutional cohort. Performance metrics included sensitivity, specificity, false-positive reduction, and area under the receiver operator curve (AUROC). The development set included 924 patients (4,026 images); the external validation sets included 194 patients (562 images) and 176 patients (188 images, latest SWE software). AI-SWE achieved an AUROC of 0.94 (95% CI, 0.91 to 0.96) and 0.93 (95% CI, 0.88 to 0.98) in the two external validation sets. Compared with B-mode ultrasound, AI-SWE significantly reduced false-positive rates by 62.1% (20.4% [30/147] v 53.8% [431/801]; P < .001) and 38.1% (33.3% [14/42] v 53.8% [431/801]; P < .001), with comparable sensitivity (97.9% [46/47] and 97.8% [131/134] v 98.1% [311/317]; P = .912 and P = .810). AI-SWE demonstrated accuracy comparable with human experts in malignancy detection while significantly reducing false-positive imaging findings (ie, unnecessary biopsies). Future studies should explore its integration into multimodal breast cancer diagnostics.

Five-year Outcomes for Men after Negative Magnetic Resonance Imaging (MRI) or Negative Biopsy in the RAPID MRI-directed Prostate Cancer Diagnostic Pathway.

This study explores the differential diagnostic value of conventional dimensional ultrasound (US) and automated breast volume scanner (ABVS) for breast ductal carcinoma in situ (DCIS) patients. A total of 986 female patients who underwent breast tumor surgery in our hospital from December 2019 to December 2022 were included. Clinical, US, ABVS, and pathological information were collected from all of the patients. Pathological results were used to separate patients into 3 groups: benign, DCIS, and invasive ductal carcinoma (IDC). Single-factor and multivariate analyses were conducted to evaluate the characteristics of DCIS. Of the 986 patients with breast tumors included in this study, 498, 193, and 295 were diagnosed with benign, DCIS, and IDC tumors, respectively. Compared with benign tumors, DCIS tumors were characterized by higher age at onset and breast imaging-reporting and data system (BI-RADS) grades, together with high rates of extension to the nipple, microcalcification, convergence sign, abundant blood supply, and nipple discharge proportion. Relative to IDC patients, DCIS tumors exhibited lower BI-RADS grades, aspect ratio values, and Ki-67 index values together with lower rates of irregular morphology, unclear boundaries, posterior echo attenuation, convergence sign, enhanced peripheral echo, nipple discharge, and palpable masses, and higher rates of extension to the nipple. Higher microcalcification rates in DCIS tumors were observed than the proportion of non-calcification in IDC cases. Conventional US and ABVS images of DCIS tumors exhibit certain distinctive characteristics that can aid in the differential diagnosis of DCIS.

Abstract Introduction Pharmaceuticals are vital to healthcare and considered a human right, yet equitable access remains difficult in small markets like Malta. Despite a fully tax-funded NHS offering full reimbursement, rising pharmaceutical costs and reliance on imports heighten vulnerability to global disruptions including the phenomenon of Brexit and COVID-19. Limited national data further emphasizes the need for targeted research to address Malta’s distinct pharmaceutical access and policy challenges [1]. Aim The study aimed to capture the collaboration and understanding of the perspective of both the internal and external stakeholders within the National Health Service, and hence provide a platform for elucidating real-time experiences within a small country context, as perceived by the diverse stakeholders. Thereafter establish the connection with existing policies, and the prevailing challenges perceived. Methodology A qualitative, inductive research design was employed to explore these complex issues. Semi-structured interviews were conducted with purposefully selected internal and external stakeholders, enabling the collection of detailed and context-rich data. Thematic Analysis, as outlined by Clarke and Braun (2006), was used to identify and develop key themes from the raw data, allowing for an emergent understanding of stakeholder concerns [2]. A conceptual model was subsequently developed to interpret findings within a structured framework [3]. Ethical approval was obtained from both IDEA College (Malta) and the Ministry for Health and Active Ageing (Malta), with strict adherence to ethical standards concerning participant consent, confidentiality, and data protection Results Findings reveal that Malta’s pharmaceutical sector faces considerable challenges related to affordability, accessibility, and supply continuity. Stakeholders identified geopolitical disruptions, including Brexit, and Malta’s inherent small-market limitations as primary drivers of elevated medicine prices and procurement difficulties. Participants also criticized outdated pricing mechanisms, procedural delays, and the limitations of ERP systems and relevant data in HTAs, which often fail to reflect actual market prices [4]. While the NHS’s full reimbursement model ensures equitable access, it may reduce cost sensitivity among both prescribers and patients. There were widespread calls for sustainable funding strategies, enhanced interdepartmental coordination, and improved data systems. Stakeholders strongly advocated for EU-level collaboration, joint procurement models, and better stock management frameworks especially further to procurement shift from UK to EU market [5]. Discussion This study provides critical insights into Malta’s pharmaceutical pricing landscape, contributing to a limited body of national literature on access and affordability issues. It demonstrates how global market disruptions, combined with national policy limitations, impact equitable access. Limitations of the study included challenges in participant recruitment due to the sensitive nature of the topic and a constrained diversity of perspectives owing to time restrictions. Nonetheless, the study underscores the importance of stakeholder collaboration, updated procurement strategies, and robust data infrastructure. Future research should explore the effects of cost-awareness programs on prescribing behaviours and investigate procurement innovations in other small EU markets to inform sustainable reform efforts.

Background/aim Hashimoto’s thyroiditis (HT) is a highly prevalent autoimmune disorder. Its coexistence with benign and malignant thyroid nodules is well-documented; however, data from non-Western countries remain limited. Our objectives were to determine the demographics, clinical presentation, biochemical parameters, and thyroid ultrasonographic findings in an Egyptian cohort with HT; estimate nodule prevalence; and identify potential risk factors for nodular presentation. Patients and methods A cross-sectional study was conducted on 408 newly diagnosed patients with HT at Alexandria University Hospital. Sociodemographic, clinical presentation, biochemical (thyroid function and autoantibodies thyroperoxidase and thyroglobulin Abs), and ultrasonographic data were collected. Thyroid nodules were classified according to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). Fine-needle aspiration cytology (FNAC) was classified by the Bethesda system (BSRTC). Multiple logistic regression identified predictors of nodularity. Results Among our cohort of 408 participants (female-to-male ratio of 15:1; mean age 38.6 years), 23.5% had thyroid nodules on ultrasound. Nodules were more frequent in those ≥35 years and with a family history of thyroid disease. Compressive symptoms were more common in the nodular group (33.0% vs. 18.6%). Hypothyroidism was observed in 80.9%, predominantly subclinical, and was more frequent in the non-nodular group (80.4% vs. 71.1%). Autoantibodies tested positive in 87.5%. One-third had diffuse enlargement; most nodules were classified as TIRADS 3 or 4. FNAC ( n = 49) showed 63.2% benign, 32.7% indeterminate, and 4.1% non-diagnostic. Histopathology ( n = 18) identified papillary thyroid cancer in 44.4%. In multiple logistic regression, age 35–50 (OR = 7.023, 95% CI: 1.447–334.090), age ≥50 (OR = 8.589, 95% CI: 1.740–42.402), family history of goiter/thyroid cancer (OR = 5.177, 95% CI: 1.055–25.403), lower TSH (OR = 0.981, 95% CI: 0.966–0.997), TPOAb (OR = 0.998, 95% CI: 0.997–0.999), and larger thyroid volume (OR = 1.036, 95% CI: 1.012–1.060) were independent predictors of nodularity. Conclusion HT shows heterogeneous clinical presentations, with subclinical hypothyroidism predominating. Compressive symptoms are more common in patients with nodules. Ultrasound and FNAC are essential for the management of nodules with HT and can help prevent unnecessary surgery. Older age, larger thyroid volume, and a positive familial history of goiter and/or thyroid cancer are major predictors for nodularity. The malignancy rate is ~2%, with microcalcifications strongly associated with malignancy.

Hip fractures cause major morbidity, mortality and long-term disability among older persons worldwide. The World Health Organization has defined two key indicatorswithin the framework of the UN Decade of Healthy Ageing to measure health system performance in providing care for older adults with hip fractures: the proportion who receive surgery within 48 h of fracture; and the proportion who receive pharmacological treatment for osteoporosis post-fracture. This Perspective article, which describes the clinical importance of these indicators, their amenability for adoption and implications for health equity, is based on findings from audits, guidelines and key literature. Numerous evidence-based solutions- for example, fracture liaison services, orhtogeriatric care models and digital tools support hip-fracture management, yet major barriers remain, such as data gaps, system preparedness and pathway variability. New or modified policies developed by national governments, ministries of health and other relevant authorities and tailored to specific geopolitical contexts are urgently needed to enable the implementation of timely surgical care and secondary fracture prevention strategies aligned with theWHO indicators. Improved health information systems to measure performance and to ensure translation to real-world changes in the lives of older people worldwide are of paramount importance.

Abstract—The Internet of Medical Things (IoMT) is rapidly transforming healthcare by enabling real-time monitoring, re- mote diagnosis, and intelligent decision-making. While these technologies improve patient care and efficiency, they also in- troduce new vulnerabilities in terms of data security, patient privacy, and system reliability. The growing reliance on inter- connected medical devices makes IoMT systems an attractive target for adversaries, with risks ranging from data breaches and adversarial manipulation to system-wide intrusions. Traditional security frameworks, such as centralized intrusion detection systems or rule-based approaches, struggle to keep up with the evolving nature of threats and the unique constraints of IoMT environments, including limited device resources, latency sensitivity, and the need for privacy preservation. To overcome these limitations, we present an integrated framework that combines federated learning, blockchain, and advanced deep learning models to provide a holistic solution for secure data processing and intrusion detection in IoMT ecosystems. The pro- posed architecture introduces quantum-based authentication for stronger device-level security, privacy-preserving collaborative training to enable distributed model learning without exposing raw patient data, and noise-driven feature masking to minimize the risks of adversarial attacks and poisoning attempts. In ad- dition, the framework reduces communication overhead through prototype-driven representation learning and optimization-aware aggregation, ensuring efficiency even in bandwidth-constrained medical networks. Index Terms—IoMT, Federated Learning, Blockchain, Deep Learning, Privacy Preservation, Intrusion Detection

Gender mainstreaming has been institutionalized in the Philippines through policies such as the Magna Carta of Women (RA 9710), the GAD Budget Policy, and the Harmonized Gender and Development Guidelines (HGDG). Yet, its implementation at the regional and local levels remains uneven, particularly in areas with complex development challenges like the Caraga Region. This study provides an evidence-based assessment of the relevance and effectiveness of gender mainstreaming policies and programs in Caraga, using a predominantly quantitative approach through a structured survey administered both online (Google Forms) and face-to-face. A total of 133 stakeholders participated, representing Regional Line Agencies (RLAs), Local Government Units (LGUs), State Universities and Colleges (SUCs), and Civil Society Organizations (CSOs). Descriptive statistics were used to analyze respondent profiles, knowledge, attitudes, and practices (KAP), while thematic analysis enriched the interpretation of open-ended responses. Findings revealed high levels of awareness of GAD principles and gender-related laws, strong attitudinal support for gender equality and GBV prevention, but moderate familiarity with technical tools such as HGDG, GMEF, and gender-responsive budgeting. Respondents reported regular compliance with GAD planning and budgeting requirements, yet flagged gaps in fund utilization, outcome-based monitoring, and inclusivity of marginalized sectors. Key barriers identified include limited budgets, absence of full-time GAD staff, socio-cultural resistance, and weak inter-agency coordination. This study concludes that while the enabling environment for gender mainstreaming in Caraga is strong, systemic reforms and capacity enhancement are necessary to translate policy mandates into transformative outcomes. It recommends sustained technical training, increased and better-targeted GAD resource allocation, robust sex- and age-disaggregated data systems, year-round advocacy campaigns, and institutionalized coordination mechanisms to ensure that gender equality becomes a measurable and sustainable driver of regional development.

This study presents the perceived implementability of the digital Hospital-Based Cancer Registry (HBCR) and the Adapted-Resource Implementation Application (ARIA) to enhance data systems and treatment standards at Pediatric Oncology unit (POU). A 2-year (2023-2025) implementation study on the integrated application of ARIA and HBCRs is being conducted at Jimma University Medical Center (JUMC) and St. Paul Hospital Millennium Medical College (SPHMMC). This article reports the formative assessment results, guided by the Consolidated Framework for Implementation Research (CFIR), involved eight focus group discussions, four in-depth interviews, and two co-design workshops with diverse healthcare providers and hospital management/leadership personnel. The integrated implementation of HBCR-ARIA was viewed as innovative and adaptable. Digital HBCR was perceived as more effective than manual methods for managing pediatric oncology data. Similarly, ARIA was perceived as effective and feasible for providing patient-specific standardized care. Workflows and responsibilities were co-defined separately for the respective POUs. The co-designed implementation strategy includes residents filling demographic and diagnostic information of patients' on HBCR interim document and then cross-checked by the pediatric Hematology and Oncology (PHO) fellows. The Medical Monitor (PHO senior) approves the validity of the document before entry into REDCap by the data clerk. ARIA is filled by PHO fellows and approved by second PHO fellow or PHO seniors based on the availability. Facilitators in both the inner (hospital) and outer (external) settings outweighed the barriers. Facilities and motivated human resources are in place to implement the digital HBCR and ARIA strategies at the respective POU. However, challenges such as inconsistent electric power, unreliable internet services, and logistic-supply issues. The implementation strategies for digitized HBCR and ARIA, co-designed to fit the specific contexts of two POU, appear promising but require further evaluation.

To assess the impact of 5α-reductase inhibitors (5-ARIs) on multiparametric magnetic resonance imaging (mpMRI) features of Prostate Imaging-Reporting and Data System (PI-RADS) lesions and their influence on the detection of clinically significant prostate cancer (csPCa), with a focus on differences between prostate zones. We retrospectively reviewed data from 1108 PI-RADS version 2 score 3-5 lesions in 718 patients across a multi-institutional cohort, all of whom underwent magnetic resonance imaging (MRI)-targeted biopsy. A subset of 66 lesions from patients receiving 5-ARI therapy was matched to lesions from untreated patients and independently reviewed by an experienced radiologist in a blinded fashion. Apparent diffusion coefficient (ADC) values were quantified for each lesion and for peripheral and transition zones. Among the 1108 lesions, 90 (8%) were in patients on 5-ARI therapy for ≥3 months prior to mpMRI. Multivariable analysis demonstrated that 5-ARI use was associated with significantly reduced odds of detecting csPCa on targeted biopsy (odds ratio [OR] 0.32, 95% confidence interval [CI] 0.18-0.57). Stratified analysis revealed a pronounced reduction in csPCa detection in peripheral zone lesions (OR 0.20, 95% CI 0.05-0.68), but not in transition zone lesions (OR 0.38, 95% CI 0.11-1.18). Blinded radiological review showed higher mean ADC values in peripheral zone lesions among 5-ARI users (869 vs 765 mm2/s; P = 0.04) and lower lesion conspicuity (P = 0.027). There were no significant imaging differences in the transition zone. Treatment with 5-ARIs is associated with decreased detection of csPCa on MRI-targeted biopsy, especially for peripheral zone lesions. These effects may be attributable to increased ADC values and reduced lesion conspicuity, suggesting a potential increase in false-positive mpMRI findings in patients receiving 5-ARIs.

Purpose To develop a multimodality deep learning model (Ovarian Cancer Network, OCNet) using dynamic contrast-enhanced US (CEUS) images for classifying adnexal lesions. Materials and Methods This retrospective study included patients with pathologically confirmed adnexal lesions detected on US across 14 hospitals in China between January 2018 and July 2023. Data were divided into the training set (n = 275), internal testing set (n = 57), and external testing set (n = 63). Two deep learning models (OCNetmanual and OCNetautomated) were developed and compared with Ovarian-Adnexal Reporting and Data System (O-RADS) US and Assessment of Different NEoplasia's in the adnexa (ADNEX) model. Diagnostic performances of radiologists with and without assistance of OCNet were also assessed. Results A total of 395 female patients (median age, 43 years [IQR, 31-55]) were included (252 benign and 143 malignant). OCNetmanual and OCNetautomated achieved an area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI: 0.89, >0.99) and 0.91 (95% CI: 0.83, 0.99), respectively, outperforming O-RADS US (AUC: 0.79; 95% CI: 0.68, 0.89; P = .002 and P = .03) and ADNEX model (AUC: 0.86; 95% CI: 0.77, 0.95; P = .04 and P = .36). Additionally, the assistance of OCNet enhanced diagnostic performance for junior radiologists, improving the average of AUC from 0.86 to 0.94 and the average specificity from 52 to 73%. Conclusion The OCNet model achieved higher performance than O-RADS US and the ADNEX model for classifying adnexal lesions and improved diagnostic performance of junior radiologists. ©RSNA, 2025.

In the digital era, algorithms and data systems have profoundly reshaped social relations in China, transforming traditional structures into fluid, dynamic networks. Drawing on Fei Xiaotong's "differential mode of association," which views Chinese society as ego-centered with graded ties, and Zygmunt Bauman's "liquid modernity," emphasizing transient and unbound interactions, this study introduces the concept of a "reversible liquid differential order." This framework captures how social ties form, dissolve, and reconfigure rapidly in digital contexts, particularly on platforms like Xiaohongshu, a social e-commerce app targeting young women. The research explores modular and elastic social relations on Xiaohongshu through a qualitative case study. Data were collected from 20 public notes and approximately 50 related comments under the #LifeSharing tag in 2025, selected for high interaction levels and relevance to relational dynamics. Thematic analysis was employed to code patterns, identifying themes such as temporary connections, algorithm-driven intimacy gradients, and guanxi culture. Findings revealed that Xiaohongshu's algorithms curate personalized content, fostering ephemeral ties through notes, comments, and recommendations, while users adapt with resilience. The study concluded that this reversible order integrates cultural specificity with algorithmic elasticity, enhancing user well-being but also amplifying social anxiety. Theoretically, it advances network analysis for quantifying cultural patterns; practically, it informs platform designs to mitigate relational uncertainties in digital China.

Clinical trial (CT) safety surveillance is critical to protecting participants and ensuring reliable evidence on the safety and efficacy of new medical products. This is especially relevant in Africa, where CT activity remains limited, regulatory maturity varies, and drug safety surveillance systems are under-resourced despite considerable demographic advantages and genetic and cultural diversity. Pre-licensure safety monitoring is a vital yet underdeveloped element of the research ecosystem, and the absence of a regional repository for safety data constrains early detection of risks, particularly in multi-country trials. To assess the current state of CT safety surveillance in Africa, a landscape analysis of the systems for clinical trial safety data reporting, collation, and analysis was conducted. Expert perspectives were synthesized to describe existing practices, identify key gaps, and propose opportunities for strengthening systems. Findings revealed limited regulatory capacity, limited drug safety monitoring expertise, and inadequate resources for causality assessment and aggregate data analysis. Despite these challenges, opportunities exist to strengthen CT safety surveillance through digitization of reporting systems, harmonization of serious adverse event forms, regional collaboration, and capacity building for strengthening the ecosystem. Experts emphasized the need for collaboration among regulators of member states, availability of electronic CT management platform in member states and a regional pre-licensure safety data repository to enable timely evidence generation, support member states, and ensure appropriate linkages between pre-licensure and post-market surveillance. Strengthening CT safety surveillance is critical for safeguarding participants, promoting ethical research, and enhancing Africa’s role in global clinical research. The results of this landscape analysis provide a roadmap for building a coordinated model for pre-licensure safety monitoring across the continent.

This paper presents a novel Markov Chain Monte Carlo (MCMC) simulation model for analyzing multi-sensor data to enhance cattle farm management. As Precision Livestock Farming (PLF) systems become more widespread, leveraging data from technologies like 3D acceleration, pneumatic, and proximity sensors is crucial for deriving actionable insights into animal behavior. Our research addresses this need by demonstrating how MCMC can be used to accurately model and predict complex cattle activity patterns. We investigate the direct impact of these insights on optimizing key farm management areas, including feed allocation, early disease detection, and labor scheduling. Using a combination of controlled monthly experiments and the analysis of uncontrolled, real-world data, we validate our proposed approach. The results confirm that our MCMC simulation effectively processes diverse sensor inputs to generate reliable and detailed behavioral patterns. We find that this data-driven methodology provides significant advantages for developing informed management strategies, leading to improvements in the overall efficiency, productivity, and profitability of cattle operations. This work underscores the potential of using advanced statistical models like MCMC to transform multi-sensor data into tangible improvements for modern agriculture.

The mounting prevalence of chronic diseases poses a substantial public health and economic burden, particularly in aging societies such as the United States. Focusing on both direct healthcare expenditure and indirect costs such as productivity loss, this study examines the economic burden of chronic non-communicable diseases (NCDs) from 1996 to 2040. A multidisciplinary approach is employed, integrating panel data models to identify determinants of real healthcare spending across ten chronic conditions and an Autoregressive Integrated Moving Average (ARIMA) forecasting model to estimate future expenditure as a share of national Gross Domestic Product (GDP). The estimations are based on data available for the period 1996–2015, which serve as the foundation for projections up to 2040. The results show that chronic diseases—especially cardiovascular conditions, diabetes, and respiratory illnesses—are associated with persistent increases in public and private healthcare costs and substantial reductions in labor productivity. Disparities by age, income, and race further intensify this burden. Projections suggest that the financial impact of chronic diseases will escalate significantly through 2040, exceeding the rate of GDP growth. Our study concludes that indirect costs are often underestimated in many models, which limits accurate fiscal planning. We thus underscore the need for integrated economic health forecasting tools to support sustainable, equity-focused health policies. These findings support calls for increased investment in prevention, coordinated chronic care, and more robust data systems to anticipate long-term health and economic outcomes.

Catastrophic health expenditure has emerged as one of the most persistent barriers to achieving universal health coverage in developing nations since 2005. In Cameroon, particularly within the Southwest Region, high out-of-pocket spending on healthcare has intensified household poverty levels and restricted access to essential maternal and child health services. This study investigates the relationship between catastrophic health expenditure and the infant mortality rate in the Southwest Region of Cameroon using secondary data covering the period from 2005 to 2016. The analysis explores how rising healthcare costs and financial shocks at the household level contribute to preventable infant deaths and poor health outcomes. Data were obtained from reliable international and national sources, including the World Bank, World Health Organization, Demographic and Health Surveys, and the National Institute of Statistics. Using a descriptive and correlational approach, the study examines both the trend and magnitude of catastrophic health expenditure alongside infant mortality patterns over the last two decades. The findings reveal a strong positive association between the financial burden of healthcare and the level of infant mortality, particularly among low-income and uninsured households. Regions where healthcare costs consume a large share of family income consistently show higher rates of infant deaths, reflecting the vulnerability of poor families to financial hardship. The study underscores the urgent need for policy action aimed at reducing out-of-pocket health spending and improving the affordability of quality care. Recommended interventions include expanding community-based and national health insurance schemes, providing targeted subsidies for maternal and child healthcare, and investing in accessible primary healthcare infrastructure. Moreover, strengthening monitoring and data systems to track catastrophic health expenditure and infant mortality indicators is crucial for informed decision-making. The findings reaffirm that effective financial protection policies are central to improving infant survival and achieving sustainable health outcomes in the Southwest Region of Cameroon.

The agricultural sector is transforming through digital technologies and data-driven tools, creating both opportunities and ethical challenges. This perspective paper explores the ethical dilemmas that arise where agricultural data intersect with trust, equity and sustainability. Farmers’ trust issues with data-driven technologies are closely linked to how data are collected, processed and used. We emphasise the importance of data governance, highlighting the need for trust, transparency, accountability and participatory governance within agricultural data systems. The paper also discusses equity concerns, such as the disparity between smallholder farmers and large-scale agribusinesses, ambiguities surrounding data ownership and the risk of marginalising certain communities within the digital agriculture paradigm. Environmental sustainability is another key focus. While data analytics can support more efficient and climate-smart farming, they also raise questions about long-term resource management and environmental impacts. Incorporating multiple disciplinary perspectives, the paper underscores ongoing issues related to power dynamics, governance, the innovation gap and the importance of embracing diversity. Drawing from these perspectives, we offer conclusions and explore how these approaches might be integrated to address the outlined ethical challenges. Finally, we highlight key ethical issues framed as vital to shaping the future of agricultural data. This paper aims to provide ethical frameworks and recommendations for the responsible use of agricultural data.

Resilience through urban planning has gained prominence since the adoption of the Sendai Framework for Disaster Risk Reduction (2015–2030), particularly in regions exposed to multiple natural hazards. This study examines how six Western Mediterranean countries—Spain, France, Italy, Tunisia, Algeria, and Morocco—address disaster risk prevention through urban and spatial planning. Although these countries share a similar geodynamic and climatic context, their approaches to integrating hazard prevention into planning frameworks vary significantly due to institutional, technical, and legal factors. Special attention is given to the case of Morocco, where delays in hazard integration are evident, particularly in the Maghreb region. Limited access to historical data, weak inter-agency coordination, and insufficient scientific capacity hinder effective planning. In response, Morocco has developed the Urbanization Suitability Map (USM) program, a non-binding planning tool inspired by the French Natural Risk Prevention Plan (PPRN). The USM tool overlays hazard information to guide land use decisions and mitigate risks such as floods, landslides, and seismic activity. Using a qualitative comparative analysis of regulatory texts, national planning strategies, and mapping instruments, this study identifies contrasting levels of disaster risk reduction integration across the six countries. The Moroccan USM initiative stands out as a pragmatic response to governance gaps and offers a transferable model for other countries with similar constraints. The findings underscore the need for clearer legislation, improved data systems, and multi-level coordination to enhance urban resilience. Recommendations are provided to strengthen hazard-informed planning practices and support more adaptive and sustainable land management in risk-prone areas.

Firefighters display increased risk of colorectal cancer (CRC). The distribution for CRC stage at diagnosis among firefighters compared to other occupational groups is unknown. CRC cases from the Florida Cancer Data System cancer registry (2001-2014) for males ≥20 years were ascertained. Firefighters were identified through either direct linkage with Florida Fire Marshal's Office employment and certification records or Standard Occupation Code annotations ascertained at diagnosis. White-collar, blue-collar, and service workers were also identified according to these codes. Stage of diagnosis was classified as localized, regional or distant. Bivariate tabulations of occupational groups and clinico-demographic covariates were conducted using contingency tables. The association between occupational class and stage at diagnosis was assessed by multivariable multinomial logistic regression adjusting for year of diagnosis, age, race and ethnicity, tobacco use and cancer diagnosis sequence and adjusted odds ratios (aORs) reported. 13,813 CRC cases, including 346 cases among firefighters, were analyzed. Firefighters were more likely to be non-Hispanic white and be diagnosed with a single primary cancer. 140 (40.5%) firefighter CRC cases were localized. Using firefighters as the referent group, only blue-collar workers approached 50% increased odds of later-stage diagnoses (aORRegional: 1.44; 95% CI: 1.12 to 1.84; p = .004; aORDistant: 1.49; 95% CI: 1.11 to 2.01; p = .008). Individuals ≥50 years and the first among multiple primary cancers were more likely to have localized CRC (p < .001). Although firefighters have increased CRC risk, they tend to be diagnosed more localized. Improved screening across worker groups can increase the percentage of localized CRCs.

The lack of data integration between the Syariah Court and other departments in Malaysia is one of the challenges in the administration of Islamic families in the Syariah Court, Malaysia. The credibility of Malaysia's Islamic judicial institutions will erode if this predicament remains. The Malaysian Syariah Justice Department (JKSM), the Malaysian Islamic Development Department (JAKIM), the Royal Malaysian Police (PDRM), and Bank Negara are among the various organizations involved in the cases in the Malaysian Syariah Court. Therefore, this study aims to identify the improvement of the data system in the management of Muslim families in the Malaysian Syariah Court. This study interviewed three respondents consisting of 1 JKSM Officer (Respondent 2), and 2 academics (Respondent 1&amp;3). Interview data has been processed using thematic analysis using Nvivo.The results of the study show that there are four themes which is Claims still being done manually in courts, Different jurisdictions in between states, The lack of integration between Syariah Court and other institutions and the lack of information in system e-Syariah and e-Nafkah. From the theme, it is important to empower the data system in the Syariah Court to be more advanced and organized to facilitate the affairs of all parties. This improvement is important because it is significant with the development of Malaysia Madani initiated by the Prime Minister of Malaysia, where emphasis is placed on the development of socially prosperous Malaysian families and communities. In addition, this improvement is important to be an example for family management in other countries.