Search Results (228)

Healthcare cleaning services are essential for infection prevention and control, but they also contribute to the carbon footprint of healthcare facilities through recurrent consumption of detergents, disinfectants, textiles, water, energy, and transport-related resources. This sequential, non-randomized, single-facility evaluation compared a traditional cleaning protocol with a Green protocol oriented to the Italian Minimum Environmental Criteria (Criteri Ambientali Minimi, CAM) for cleaning services at Domus Nova Hospital, a private accredited healthcare facility in Ravenna, Italy. A risk-based microbiological monitoring plan was applied to low-, medium-, and medium-high-risk areas, prioritizing high-touch surfaces and using RODAC contact plates and sterile swabs. In parallel, a comparative Life Cycle Assessment was conducted in accordance with ISO 14040, ISO 14044, and ISO 14067 principles, using Global Warming Potential over 100 years as the main impact indicator and the functional unit of one square meter of cleaned hospital surface maintained for one year. The two protocols were assessed during different monitoring periods of unequal duration; therefore, the study was interpreted as a whole-system operational comparison rather than as a randomized trial or formal equivalence/non-inferiority assessment. After cleaning, all 64 observations obtained under the Green protocol met the adopted surface-hygiene acceptability criteria, compared with 55 of 64 observations under the Traditional protocol. No predefined target pathogenic indicators were recovered from post-cleaning samples under the applied culture conditions. From a climate-impact perspective, the Green protocol reduced the carbon footprint by 39.0%, corresponding to an avoided impact of 450 g CO2e m⁻² year⁻¹ and 2663.5 kg CO2e year⁻¹ at the facility scale. The main climate-related benefits were associated with the combined effect of textile-system redesign, lower energy consumption, optimized product use, and reduced operator transport. These findings support the use of integrated surface-hygiene indicators and life-cycle metrics to inform healthcare cleaning procurement, while highlighting that the results concern culture-based surface contamination indicators from a single facility and do not directly assess infection transmission or patient outcomes. Full article

Hemodialysis (HD) remains the most widely adopted renal replacement therapy for patients with end-stage kidney disease; however, its delivery entails a substantial environmental burden due to high water and energy consumption and extensive reliance on single-use synthetic polymeric membranes. As the global prevalence of chronic kidney disease increases, the ecological footprint of dialysis systems has become a critical challenge for sustainable healthcare. Conventional HD membranes, based on petroleum-derived polymers, provide controlled permeability but are inherently non-renewable, non-biodegradable, and susceptible to fouling and bio-incompatibility, underscoring the need for alternative, more sustainable materials. Chitosan has emerged as a promising biopolymer owing to its biodegradability, intrinsic antimicrobial activity, chemical versatility, and favorable hemocompatibility. This review presents a comprehensive analysis of chitosan-based hybrid membranes for HD, with emphasis on sustainability-driven material innovation. The structural chemistry and functional properties of chitosan are discussed in relation to molecular weight, degree of deacetylation, and supramolecular organization, followed by a comparative assessment of chitosan derived from crustacean, insect, fungal, and cephalopod sources. Attention is given to fungal chitosan as a naturally deacetylated, high-purity, and reproducible biomaterial aligned with circular bioeconomy principles. Eco-innovative extraction and purification strategies, including enzymatic and low-energy processes, are critically examined alongside membrane fabrication approaches such as polymer blending, electrospinning of hollow fibers, and functionalization strategies aimed at improving hemocompatibility, antimicrobial performance, and fouling resistance. Key challenges related to membrane reuse, scale-up, regulatory compliance, and clinical translation are also addressed. Overall, this review highlights fungal-derived chitosan as a sustainable platform for next-generation HD membranes. Full article

Climate change has been identified by the World Health Organization (WHO) as “the single greatest health threat to humanity”. To investigate this subject, we conducted a narrative review of the literature about sustainability in the OR, with the aim of exploring the existing knowledge and identifying prevailing challenges in the field. A combined automated and manual database search of the literature was performed using Medline (PubMed), Scopus, Ovid, and the Cochrane Library, covering publications available up to and including 21 May 2025. The significance of environmental sustainability is recognized across all healthcare systems. To fulfil the United Nations Sustainable Development Goals, the healthcare sector must undergo a transformation towards more eco-friendly practices, which will also affect clinical decision-making. Net-zero is an internationally agreed goal for avoiding worsening global heating in the second half of the 21st century, as it aims to balance the quantities of greenhouse gases released into and removed from the atmosphere, achieving carbon neutrality. Nevertheless, the operating room (OR) is among the most significant contributors to environmental pollution, with the major carbon hotspots determined by the use of energy, procurement and disposal of consumables and the waste of water. In response to this challenge, leading medical societies, surgical teams, government bodies, and industry stakeholders endorse Green Surgery (GS) by taking steps to address healthcare sustainability and its impact on climate change. Therefore, a movement toward “greening” healthcare, or improving the environmental footprint of healthcare has been built. Full article

The rapid expansion of artificial intelligence (AI) is accelerating data center construction and creating downstream implications for households. This study examines how AI-era data center costs (comprising construction, energy, water, grid upgrades, cooling, and lifecycle management) move through service supply chains and affect household prices in healthcare, transportation, education, banking, and commerce. It also considers the productivity and welfare benefits that AI may transmit. This study identifies four pass-through channels: utility-rate socialization of energy costs, cloud-platform pricing, sectoral pass-through from AI-adopting industries, and indirect effects through supply chains and labor markets. It introduces the AI-inflated net good basket, defined as transmitted cost minus transmitted benefit, to show how AI reshapes the overall net cost of household consumption rather than simply inflating individual prices. The study develops the AI Infrastructure Net Cost Pass-Through Model (AI-NCPM), a four-layer conceptual framework tracing net cost flows from data center investment to sectoral allocation and household outcomes. The model’s parameters are analytically specified but not empirically calibrated; numerical examples are illustrative rather than representing estimated effects. Its main contribution is an integrative framework linking cost pass-through, infrastructure cost socialization, two-sided platform allocation, environmental externalities, and household expenditure incidence within a single net-cost account. Because these effects originate in the design, construction, energy and cooling systems, and lifecycle operation of data centers, the analysis connects AI infrastructure economics to the built environment. The framework suggests that low-income, minority, rural, older adult, and disability-affected households may face disproportionate net burdens, as costs fall heavily on essential services while benefits accrue more readily to affluent and digitally connected households. Full article

Background: Climate change is increasingly recognised not only as an environmental emergency but also as a structural determinant of health and health-system performance. Its clinical consequences will not be distributed evenly: high-income countries face rising heat mortality, infrastructure fragility, ageing-related vulnerability, and the need to decarbonise technologically intensive care; middle- and low-income countries face heterogeneous but often more compressed combinations of heat, infectious disease, food insecurity, water stress, displacement, conflict-related fragility, and limited fiscal capacity. Objective: This structured narrative review proposes a comparative framework for understanding how climate change will transform health care across high-, middle-, and low-income settings and identifies adaptation priorities that are resilient, equitable, and low-carbon. Methods: We synthesised major climate-health assessments, peer-reviewed epidemiological studies, modelling papers, systematic and scoping reviews, and health-system decarbonisation literature identified through targeted searches and reference chaining. Five climate-health pathways, specified a priori from established direct, indirect, and socially mediated pathway frameworks, were used to organise the review. Findings: Climate change will reshape health care through five interacting pathways: direct thermal injury and extreme-weather mortality; altered infectious disease ecology; food, water, and nutritional insecurity; mental, maternal-child, and occupational impacts; and damage to the infrastructure, workforce, supply chains, finances, and emissions profile of health systems. In high-income countries, climate stress exposes the limits of hospital-centred, carbon-intensive, just-in-time care. In middle-income countries, expanding coverage and technology coexist with uneven insurance, large informal workforces, and rapidly growing emissions. In low-income and fragile settings, the same hazards interact with undernutrition, weak surveillance, under-resourced primary care, and constrained finance to produce larger marginal health losses. Conclusions: The central contribution is the concept of the climate-health divide: the unequal conversion of shared climate hazards into clinical demand, service disruption, financial stress, and emissions-intensive responses. Climate resilience and healthcare decarbonisation should therefore be designed together rather than treated as separate agendas. Full article

Non-aeruginosa Pseudomonas (NAP) species represent a diverse and ubiquitous group of Gram-negative bacteria inhabiting a wide range of environmental niches, from soil and water to plant rhizospheres and clinical settings. While Pseudomonas aeruginosa has historically dominated clinical and research focus, the significance of NAP species, such as Pseudomonas fluorescens, Pseudomonas putida, and Pseudomonas stutzeri, as both opportunistic human pathogens and versatile biotechnological agents is increasingly recognized. Their remarkable genomic plasticity, driven by large accessory genomes and mobile genetic elements, underpins their metabolic versatility and adaptability but also facilitates the acquisition of virulence determinants and antibiotic resistance genes, contributing to their emergence in healthcare settings, particularly among immunocompromised individuals. This review provides a comprehensive analysis of NAP species, focusing on recent advances in their taxonomy facilitated by genomic tools like Whole-Genome Sequencing (WGS) and Multilocus Sequence Typing (MLST), which reveal complex species groups and challenge traditional classifications. We delve into the genomic landscape, exploring pangenome dynamics, horizontal gene transfer (HGT), and the genomic signatures that may differentiate clinical from environmental isolates. The clinical relevance of NAPs is examined, detailing the spectrum of infections, epidemiological trends, risk factors, and insights into virulence mechanisms, including secretion systems (T3SS, T6SS) and pathogenicity islands. Addressing a critical need, this review incorporates detailed sections on the diagnostic challenges posed by NAPs, including common misidentifications and the role of modern techniques like MALDI-TOF MS and WGS, and outlines current and novel therapeutic strategies, considering the growing problem of antimicrobial resistance (AMR) within this group. Furthermore, the biotechnological applications of NAPs in bioremediation and biocatalysis are discussed alongside evolving biosafety considerations, reflecting the shift from strict containment to integrated monitoring approaches for genetically engineered strains. By synthesizing current knowledge and highlighting research gaps, this review underscores the necessity of integrated, One Health approaches to understand and manage the dual nature of non-aeruginosa Pseudomonas species as both environmental inhabitants and clinically relevant pathogens. Full article

Background and Objectives: Dengue is emerging as a multifaceted public health challenge that extends beyond traditional vector-borne disease frameworks. Climate change, rapid urbanisation, environmental transformation, global mobility, and digital ecosystems are progressively reshaping transmission dynamics, outbreak patterns, and preparedness needs worldwide. This narrative review aimed to examine dengue from an integrated public health perspective, focusing on climate-sensitive transmission, urban health, surveillance and preparedness, digital epidemiology, artificial intelligence (AI), and health communication. Materials and Methods: A structured narrative review was conducted through targeted literature searches in PubMed, Scopus, and Web of Science between April and May 2026. To this end, a series of separate thematic search strategies were developed to explore the principal conceptual domains addressed in the review. The synthesis was organised around five interconnected preparedness domains: climate change and environmental transformation; urbanisation and urban health; surveillance, vaccination, and integrated preparedness; digital health, artificial intelligence, and mathematical modelling; and health communication and community engagement. The retrieved literature was analysed using a thematic narrative synthesis approach. Results: The retrieved evidence indicated the progressive expansion and redefinition of dengue risk across both endemic and historically non-endemic regions. Climate variability, environmental transformation, rapid urbanisation, and increasing human mobility have emerged as interconnected drivers capable of influencing vector ecology, transmission dynamics, outbreak frequency, and healthcare system vulnerability. Urbanisation has been frequently associated with infrastructural inequalities, environmental degradation, inadequate water and waste management, and territorial conditions favourable to vector proliferation. The extant literature has also placed significant emphasis on the growing importance of integrated surveillance systems and early warning approaches combining epidemiological, environmental, climatic, entomological, and mobility-related data. Digital epidemiology, AI-based predictive models, and digital surveillance tools may contribute to strengthening outbreak forecasting and preparedness capacity, although important limitations related to data quality, interoperability, interpretability, and implementation remain. In parallel, misinformation, risk communication challenges, and digital communication ecosystems emerged as relevant factors influencing public perception, preventive behaviours, institutional trust, and adherence to public health interventions. Conclusions: Dengue is a systems-level public health challenge shaped by climate change, urbanisation, environmental disruption, human mobility, health-system preparedness, and digital ecosystems. Conventional vector-control strategies alone are unlikely to adequately address this growing complexity. Strengthening dengue preparedness should therefore be considered a broader indicator of public health resilience and long-term health-system adaptation. Full article

Plastic pollution has emerged as a major environmental concern due to its persistence and widespread accumulation in terrestrial ecosystems. The extensive utilization of plastics across a diverse range of products, from packaging to healthcare, construction, and transportation, poses a significant risk due to their enduring and non-biodegradable nature. Micro/nanoplastics (MNPs) derived either from the fragmentation of larger plastics or direct release are increasingly detected in agricultural soils, where they interact with plant systems. In addition, chronic exposure of MNPs alters soil structure, microbial diversity, and nutrient cycling, further impacting agroecosystem functioning. Plants have been shown to absorb MNPs mostly from contaminated soil and irrigated water through their root systems, allowing their subsequent translocation to aerial tissues. MNPs can enter plants through the aquaporins, apoplast pathways, crack entry modes, and leaf stomata, disrupting nutrient uptake, photosynthesis, and growth processes, ultimately affecting crop productivity and quality, while their accumulation in edible tissues raises concerns regarding food safety and trophic transfer. To address these challenges, it is crucial to have standard detection methods for identifying MNPs and to bridge the gap for further mitigation. This review further discussed effective mitigation strategies, including nanomaterial and phytohormone-based interventions under increasing plastic contamination. Full article

Objectives: Inadequate access to safe water, sanitation, and hygiene (WASH) continues to drive infectious diseases, malnutrition, and educational disparities, particularly among vulnerable populations. This systematic review examined WASH intervention strategies implemented in Malaysia between 2014 and 2025, focusing on shifts in hygiene-related knowledge, attitudes and practices (KAP), health outcomes, infrastructure improvements, and implementation challenges. Methods: A comprehensive search across five databases (Science Direct, PubMed, Scopus, Web of Science, and Google Scholar) identified twelve eligible studies targeting schools, healthcare settings, and rural or Indigenous communities. Results: Education-based interventions predominated (n = 10), often employing participatory and theory-driven approaches grounded in the Health Belief Model or Information–Motivation–Behavioural Skills framework. Evidence revealed significant improvements in KAP, particularly when digital, gamified, or storytelling elements were integrated. Community-led and caregiver-inclusive models demonstrated greater behavioural adoption and retention. Thematic analysis identified several implementation challenges, which include (i) sole reliance on self-reported outcomes with limited use of objective indicators, (ii) short intervention durations (<2 months) that limit long-term impact, and (iii) lack of policy and curriculum integration. Conclusions: Findings underscore the need for culturally tailored, longitudinal, and system-embedded interventions that combine behavioural theory with infrastructure investment. Integrating WASH initiatives into Malaysia’s health and education frameworks could advance Sustainable Development Goal 6, ensuring scalable and equitable improvements in hygiene literacy, community resilience, and public health outcomes. Full article

This study presents a technical assessment of solar energy systems for integrated agricultural use and rural electrification. A model village comprising 30 households was considered, and high-resolution hourly load profiles were developed to characterize consumption dynamics, including peak demand and sectoral distribution across residential, agricultural, public, healthcare, and commercial users. A 60 kW photovoltaic (PV) system was designed in conjunction with an independent solar thermal installation for hot water supply. The system configuration was established through component sizing and numerical modeling, incorporating heat transfer mechanisms and operational constraints. Time-dependent simulations performed in MATLAB (R2022b) evaluated PV power output, battery storage cycling, and thermal system performance over a 24-h horizon. A comparative analysis of standalone PV, hybrid PV/T, and decoupled PV–thermal configurations was conducted based on performance and operational criteria. The results indicate that separated electrical and thermal subsystems achieve improved cost-effectiveness, enhanced reliability, and reduced maintenance requirements. The proposed approach demonstrates the technical viability of solar-based energy systems for rural applications, supporting energy autonomy, reduced fossil fuel dependence, and sustainable agricultural development. Full article

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy performance helps save energy, boost energy independence and security, lower energy costs, and reduce the need for grid investments. Standardizing energy performance assessments enables benchmarking and comparison of building efficiency, encouraging informed decision-making. In this context, the paper presents a knowledge discovery-driven intelligent decision-making system, designed, developed, and tested to identify the best strategies for prioritizing buildings in the envelope process. The system combines data mining techniques with statistical analysis to precisely rank and thoroughly evaluate low-energy-performance buildings and to develop scenario-based strategies for enveloping the buildings to achieve high energy efficiency (associated with nearly zero-energy buildings) under real-world conditions. Testing of the proposed intelligent decision-making system was conducted using a real building database of approximately 3900 records, uploaded from the Romanian central administration website. Under the highest-performance scenario of the envelope-priority strategy, which includes nearly zero-energy building standards, energy savings exceeded 50% across all categories: 51.70% for healthcare, 53.40% for residential, 60.11% for administrative and office buildings, and 69.92% for educational institutions. Overall, the average savings across all building types were 59.81% (644.86 GWh/year). Full article

Gelatin is a valuable hydrocolloid produced by partial hydrolysis of collagen from mainly mammalian and fish sources. The rheological properties of fish gelatin differ from those of mammalian species in terms of gel strength, viscosity, and other rheological characteristics, even from different fish species and parts of the fish with different properties. Fish gelatin is sustainable for the environment and easy for people to accept for cultural reasons. Owing to these properties, gelatin is used across food, biomedical, pharmaceutical, and health sectors, where 3D printing enables customization and functional performance. Key determinants of print fidelity include gelatin concentration, rheological properties, temperature, gelling behavior, water content, and printing parameters. Suitability for 3D printing is typically assessed via physicochemical characterization, particularly rheology and gelling mechanisms/kinetics. Gelatin-based 3D printing systems offer various advantages due to their biocompatibility, low cost, and controllable rheological properties, and they have potential applications in the food, healthcare, biomedical, tissue engineering, and drug delivery system areas. Using gelatin in combination with other additives can improve printing accuracy and mechanical strength parameters, overcome the limitations of gelatin’s inherent mechanical strength, and develop higher printing accuracy and performance systems. This allows for the development of functional, innovative, and high-value-added products while ensuring safe use. Full article

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and $R^2$. The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests. Full article

Aerosol-generating procedures (AGPs) expose healthcare personnel to airborne pathogens and require portable engineering controls that can be integrated into routine clinical workflows. We developed a portable, foldable negative-pressure aerosol-containment system (FNPACS) combining adaptive fan control, an H14 high-efficiency particulate air (HEPA) filter, and a disposable metal-oxide prefilter in a mobile filtration module. Bench performance was evaluated using pressure-flow testing in accordance with National Environmental Balancing Bureau (NEBB) procedures and International Organization for Standardization (ISO) 14644-3, polyalphaolefin aerosol challenge testing, and smoke visualization, while an exploratory clinical study assessed environmental contamination via real-time reverse-transcription PCR (rRT-PCR) in 11 patients (31 assay analyses). Bench testing demonstrated HEPA filtration efficiencies of 99.994–99.997%, stable negative-pressure generation across fan duty cycles, no detectable downstream breakthrough beyond the HEPA filter under the tested conditions, and effective inward airflow on smoke testing. A Lagrangian discrete phase model (DPM) particle-tracking simulation further characterized size-dependent aerosol-surrogate transport. Under HEPA-ON active-extraction conditions, 73.0–86.1% of simulated 0.3–10 µm water-equivalent particles were transported to the HEPA suction pathway, while 13.9–27.0% were deposited on internal wall surfaces. In the clinical evaluation, SARS-CoV-2 RNA detection on environmental swabs was limited and predominantly low level. The clearest reproducible signal occurred on the top interior surface under HEPA-OFF conditions, whereas HEPA-ON detections were isolated or presumptive high-Ct signals without reproducible confirmation. These findings provide preliminary engineering and usability support for FNPACS as a feasible near-source aerosol-control platform for AGPs. The patient swab component should be interpreted as an exploratory, proof-of-concept assessment rather than confirmatory evidence of clinical containment efficiency because several clinical cases had non-supportive patient-related controls and were therefore not used in the primary containment interpretation. Full article

Critical infrastructures are increasingly Internet-connected cyber–physical systems whose recovery after cyber incidents must satisfy safety, timing, regulatory, and interdependency constraints. Yet, the use of large language models (LLMs) for generating recovery plans remains fragmented across cybersecurity, industrial control, digital twins, and AI assurance research. This review synthesizes that emerging field through a structured critical survey of studies on LLMs in incident response, OT/ICS resilience, and cyber–physical recovery, with a focused perspective on grounding, trust, and assurance mechanisms relevant to recovery-plan generation. It develops an architecture-centric taxonomy spanning prompt-only assistants, retrieval-augmented copilots, graph-aware planners, multi-agent systems, and hybrid verification/simulation pipelines; maps realistic applications across energy, water, manufacturing, transportation, healthcare, and telecommunications; and organizes limitations into technical, security, governance, and human-factor categories. Based on this synthesis, the paper proposes the Grounded Recovery Planning Stack as a reference architecture and outlines a staged roadmap from human-in-the-loop copilots to bounded orchestration. The main conclusion is that near-term value lies in grounded, auditable, compliance-aware copilots, whereas autonomous recovery execution remains premature without stronger validation, state-aware grounding, sector-specific benchmarks, and formal safeguards. Full article