Search Results (521)

Among the existing challenges in the field of hyperspectral imaging, the need to optimize memory usage and computational capacity in material detection methods stands out, given the vast amount of data associated with the hundreds of reflectance bands. In line with this, this article proposes a comparative study on the effectiveness and efficiency of five computational methods for detecting composite material asbestos cement (AC) in hyperspectral images: correlation, spectral differential similarity (SDS), Fourier phase similarity (FPS), area under the curve (AUC), and decision trees (DT). The novelty lies in the comparison between the first four methods, which represent the spectral proximity method and a machine learning method, such as DT. Furthermore, SDS and FPS are novel methods proposed in the present document. Given the accuracy that detection methods based on supervised learning have demonstrated in material identification, the results obtained from the DT model were compared with the percentage of AC detected in a hyperspectral image of the Manga neighborhood in the city of Cartagena by the other four methods. Similarly, in terms of computational efficiency, a 20 × 20 pixel region with 380 bands was selected for the execution of multiple repetitions of each of the five computational methods considered, in order to obtain the average processing time of each method and the relative efficiency of the methods with respect to the method with the best effectiveness. The decision tree (DT) model achieved the highest classification accuracy at 99.4%, identifying 11.44% of asbestos cement (AC) pixels in the reference image. However, the correlation method, while detecting a lower percentage of AC pixels (9.72%), showed the most accurate visual performance and had no spectral overlap, with a 1.4% separation between AC and non-AC pixels. The SDS method was the most computationally efficient, running 23.85 times faster than the DT model. The proposed methods and results can be applied to other hyperspectral imaging tasks involving material identification in urban environments, especially when balancing accuracy and computational efficiency is essential. Full article

(1) Background: Occupational exposure to asbestos remains a significant public health concern due to its association with pleural cancer and other cancers. This cohort study examines the incidence of asbestos-related diseases among railway carriage maintenance workers exposed to asbestos between 1960 and 1979 in Bologna, Italy. (2) Methods: A cohort of 2197 male workers was followed from 1960 onwards, with data collected on asbestos exposure, smoking habits, and mortality outcomes. The association of asbestos exposure and smoking with the risk of pleural cancer and lung cancer was assessed using Cox proportional hazards regression models. (3) Results: This study identified a substantial burden of asbestos-related pleural cancer, with an exponential increase in risk over time since the beginning of exposure. Our results suggest the lack of a multiplicative effect of asbestos exposure and smoking on lung cancer risk. The Cox models showed a significant association between smoking and lung cancer risk, with a hazard ratio of 3.26 (95% CI: 1.10–9.64, p = 0.03), less significant for asbestos exposure, with a hazard ratio of 1.42 (95% CI: 0.66–3.06). (4) Conclusions: This study provides valuable insights into the long-term health effects of occupational asbestos exposure and underscores the complex interaction between asbestos exposure and smoking in the development of lung cancer. Full article

We report the first case of pleural mesothelioma (PM) occurring in a child affected by NF2-related schwannomatosis (NF2-SWN) and without any history of environmental exposure to asbestos. Mesothelioma is a rare secondary tumor in brain cancer patients and the association with NF2-SWN has been described only in a few anecdotal cases and never in the pediatric field. NF2-SWN is an autosomal dominant disease caused by inactivating germline mutations of the NF2 tumor suppressor gene, one of the most common mutations associated with human primary mesothelioma too. By MLPA assay, array-CGH analysis, and NGS on blood and tumor DNA, we determined the mutation profile of this rare NF2-driven PM and we identified several atypical chromosomal aberrations in tumor cells, suggesting a different genomic signature between pediatric and adult mesothelioma. Full article

Rainwater harvesting (abbreviation: RWH) presents a valuable alternative water source for agriculture, particularly in regions facing water scarcity. However, contaminants leaching from roofing materials, such as asbestos cement (abbreviation: AC), may compromise water quality and affect plant physiological responses. This paper aimed to assess how simulated rainwater, reflecting the different levels of contamination (1, 2, 5, 10, and 20 mg/L), influences leaf temperature in tomato plants (Solanum lycopersicum), a known non-invasive indicator of plant water stress. The treatments were applied over a four-week period under controlled greenhouse conditions. Leaf temperature was monitored using infrared thermography. Results showed that higher treatment concentrations led to a significant increase in leaf temperature, indicating elevated water stress. These findings suggest that even low levels of contaminants originating from roofing materials can induce detectable physiological stress in plants. Monitoring leaf temperature offers a rapid and non-destructive method for assessing environmental water quality impacts on crops. The outcomes of this research have direct applicability in the safer design of RWH systems and in evaluating the suitability of collected rainwater for irrigation use. Full article

Fire events can impact physical and mental health through smoke exposure, evacuation, property loss, and/or other environmental stressors. In this study, we developed community-driven, cross-sectional online surveys to assess public attitudes, health impacts, and protective actions of residents affected by the Tustin hangar fire that burned for 24 days in southern California. Results showed the most frequently reported fire-related exposure concerns (93%) to be asbestos and general air pollution and the most commonly reported mental health impacts to be anxiety (41%), physical fatigue (37%), headaches (33%), and stress (26%). Nose/sinus irritation was the most commonly reported (26.0%) respiratory symptom, while skin- and eye-related conditions were reported by 63.0% and 72.2% of the survey population, respectively. The most commonly reported health-protective actions taken by residents included staying indoors and/or closing doors and windows (67%), followed by wearing face masks (37%) and the indoor use of air purifiers (35%). A higher proportion of low-income residents had to spend money on remediation or other health-protective actions compared to high-income residents. Participants overwhelmingly reported disapproval of their city’s and/or government’s response to the fire disaster. Findings from this study underscore the potential impacts of major pollution events on neighboring communities and offer critical insights to better position government agencies to respond during future disasters while effectively communicating with the public and addressing community needs. Full article

This study proposes a practical integration of an existing deep learning model (YOLOv9-E) and social participation GIS using multi-source remote sensing data to identify asbestos-containing materials located on the side of a building affected by light occlusions. These objects are often undetectable by traditional vertical or oblique photogrammetry, yet their precise localization is essential for effective removal planning. By leveraging the mobility and responsiveness of citizen investigators, we conducted fine-grained surveys in community spaces that were often inaccessible using conventional methods. The YOLOv9-E model demonstrated robustness on mobile-captured images, enriched with geolocation and orientation metadata, which improved the association between detections and specific buildings. By comparing results from Google Street View and field-based social imagery, we highlight the complementary strengths of both sources. Rather than introducing new algorithms, this study focuses on an applied integration framework to improve detection coverage, spatial precision, and participatory monitoring for environmental risk management. The dataset comprised 20,889 images, with 98% being used for training and validation and 2% being used for independent testing. The YOLOv9-E model achieved an mAP50 of 0.81 and an F1-score of 0.85 on the test set. Full article

Background/Objectives: Artificial intelligence (AI) has evolved from early diagnostic expert systems to advanced generative models, such as GPT-4, which are increasingly being used in healthcare. Concerns persist regarding inaccuracies and input dependency. This study aimed to deliver initial insights into whether gender influences the interaction of medical professionals with generative AI. Methods: This analysis investigated gender differences in medical students’ and physicians’ interactions with ChatGPT-4 while researching occupational medicine cases in a randomized controlled study. Participants assessed cases involving asbestos-related disease, metal sulfate allergy, and berylliosis using ChatGPT. Inputs and outputs were evaluated for accuracy, confabulations, communication styles, and user satisfaction. Demographic data and self-assessments of occupational medicine knowledge before and after the tasks were also collected. Results: Among 27 participants (63% women, 37% men), women showed greater knowledge improvement after using ChatGPT, particularly in asbestos-related cancer identification. No significant gender differences emerged in diagnostic accuracy, reporting procedures, or satisfaction with ChatGPT. Women exhibited significantly higher self-rated competence after using the ChatGPT application, while men only showed minimal change. Input from the female participants led to more confabulations, although response accuracy remained comparable. Conclusions: This study offers the first real-world insights into the use of generative AI in occupational medicine, highlighting the importance of understanding user-dependent variability in AI-supported clinical practice and decision-making. These findings underscore the need for gender-sensitive AI literacy training in medical education, accommodating diverse interaction styles and strategies to mitigate AI-generated misinformation. Future research with larger and more diverse cohorts could provide deeper insights into the influence of gender, age, and experience on AI utilization in healthcare. Integrating gender-based interaction differences into AI training and applications may improve clinical performance and promote more equitable healthcare practices. Full article

Growing requirements in the field of environmental protection and waste management result in the need to search for new and effective methods of recycling various types of waste. From the perspective of technical and natural sciences, the disposal of hazardous waste, which can lead to environmental degradation, is of utmost importance. A particularly hazardous waste is asbestos, used until recently in many branches of the economy and industry. Despite the ban on the production and use of asbestos introduced in many countries, products containing it are still present in the environment and pose a real threat. This paper presents the results of research related to the process of asbestos neutralization, especially the chrysotile variety, by the thermal decomposition method. Changes in the mineralogical characteristics of asbestos waste were studied using the following methods: TG-DTA-EGA, XRD, SEM-EDS and XRF. The characteristics of the chrysotile asbestos sample were determined before and after thermal treatment at selected temperatures. The second part of the study focuses on the kinetic aspect of this process, where the chrysotile thermal decomposition process was measured by two techniques: ex situ and in situ. This study showed that the chrysotile structure collapsed at approximately 600–800 °C through dehydroxylation, and then the fibrous chrysotile asbestos was transformed into new mineral phases, such as forsterite and enstatite. The formation of forsterite was observed at temperatures below 1000 °C, while enstatite was created above this temperature. From the kinetic point of view, the chrysotile thermal decomposition process could be described by the Avrami–Erofeev model, and the calculated activation energy values were ~180 kJ mol⁻¹ and ~220 kJ mol⁻¹ for ex situ and in situ processes, respectively. The obtained results indicate that the thermal method can be successfully used to detoxify hazardous chrysotile asbestos fibers. Full article

Malignant mesothelioma (MM) is a highly aggressive cancer strongly associated with asbestos exposure, and accumulating evidence suggests that high mobility group box 1 (HMGB1) plays a central role in its pathogenesis. Our in vitro and in vivo experiments revealed that HMGB1 was highly expressed in MM. Both genetic and pharmacological inhibition of HMGB1 markedly suppressed MM cell viability, migration, and invasion, while inducing G1-phase cell cycle arrest and enhancing apoptosis. Interestingly, the inhibition of Toll-like receptor 4 (TLR4), achieved through both siRNA and TAK-242 treatment, not only suppressed tumor-promoting signals but also reduced HMGB1 expression, suggesting a self-amplifying HMGB1-TLR4 loop. Mechanistically, in vitro experiments indicated that suppression of HMGB1 and TLR4 was associated with decreased activation of NF-κB, AKT, and ERK pathways, which are involved in regulating MM cell survival and motility. In xenograft models, treatment with ethyl pyruvate (EP) and TAK-242 significantly suppressed tumor growth and HMGB1 expression, reinforcing their therapeutic potential. Given HMGB1’s influence on both tumor cell behavior and the immune microenvironment, targeting the HMGB1-TLR4 axis may not only provide a novel therapeutic strategy for MM but also offer insights into the mechanisms underlying asbestos-induced tumorigenesis, potentially guiding future prevention and intervention strategies in asbestos-exposed populations. Full article

The development of standardised, reproducible preclinical models is essential for advancing pleural mesothelioma (PM) research. Here, we present a simple and reliable minimally invasive transthoracic intrapleural injection technique that could improve the efficiency of orthotopic PM model generation. By incorporating a simple needle sleeve to control the injection depth, this method eliminates the need for surgery or general anaesthesia, reducing technical complexity and animal stress while ensuring precise delivery into the pleural cavity. We demonstrate the effectiveness of this approach by achieving a 100% tumour engraftment rate following the injection of AE17 tumour cells. Additionally, this technique has been successfully used for asbestos fibre injection in mesothelioma models, highlighting its versatility. By providing a more accessible, standardised alternative to existing methods, this protocol improves the reliability of PM models and facilitates broader adoption by researchers, including those with limited experience in invasive procedures. Full article

Asbestos cement materials represent a persistent source of environmental contamination, particularly in urban areas where weathering facilitates the release of hazardous chrysotile fibres. Despite extensive research on the human health impacts of asbestos, ecological interactions remain poorly understood. This paper explores the dual role of bryophytes colonising asbestos cement roofing as passive filters that trap airborne fibres and as vulnerable organisms subjected to asbestos-induced stress. Using a synthesis of recent findings, we assess the capacity of mosses to immobilise chrysotile fibres through their dense, mat-like structures, potentially reducing local dispersion. Simultaneously, we examine physiological and biochemical responses to prolonged fibre exposure, including reduced photosynthetic activity and signs of oxidative stress. The findings highlight a paradoxical function of bryophytes: while they contribute to pollution mitigation, they also accumulate contaminants and suffer from sublethal damage. These interactions may have broader implications for contaminant redistribution, particularly through decomposition and trophic transfer. Understanding these dynamics is essential for advancing ecological risk assessments and developing sustainable remediation strategies in asbestos-contaminated habitats. Full article

Pleural mesothelioma (PM) is a rare disease, which is going to be a global medical concern in the 21st century, because of its aggressiveness, late diagnosis, and insufficient therapies. This review seeks to enhance the comprehension of medical professionals regarding the risk factors and environmental influences that contribute to the development of the disease, as well as its underlying mechanisms. In addition, we aim to provide a schematic yet thorough overview of diagnostic techniques in PM, emphasizing the significance of the immunohistochemical markers BAP1 and MTAP, with the latter serving as an almost ideal surrogate for the gold-standard diagnostic approach, FISH p16/CDKN2A deletion. The scientific world is grappling with BAP1, MTAP, and the tumour inflammatory microenvironment, because they are the key for personalized treatments and palliative care in this disease. Considering that the survival rate for patients with PM seldom surpasses five years, every moment is significant. Therefore, our article also highlights recent advancements in clinical assessments related to prognostic scoring and treatment options. PM is a complex disease, with gradual progression over decades, which requires further investigation covering the prevention, mutations, diagnosis and treatment. Full article

This study addresses the need for thermomechanically robust materials for high-temperature environments by investigating fabric-reinforced composites produced through polymer infiltration and thermal pressing using phenol-formaldehyde (PF) and epoxy (ER) resins. Experimental validation was required due to the lack of comparative data across different textile reinforcements under identical conditions. Seven technical fabrics—carbon, aramid, basalt, silica, fiberglass, asbestos, and a carbon/aramid hybrid—were used as reinforcements. Mechanical testing revealed that carbon- and hybrid fiber composites exhibited the highest tensile (up to 465 MPa) and compressive strengths (up to 301 MPa), particularly when combined with ER. Conversely, the use of PF generally resulted in a 30–50% reduction in mechanical strength. However, PF-based composites demonstrated superior thermal resistance, with the silica/PF combination showing the lowest back-face temperature (401 °C), up to 37% lower than other pairings. Thermal conductivity ranged from 0.041 to 0.51 W/m·K, with PF-based systems offering 6–12% lower values on average compared to ER-based analogs. Morphological analysis confirmed better interfacial bonding in ER composites, while PF systems showed higher structural integrity under thermal loading. Overall, the results emphasize the trade-offs between mechanical strength and thermal protection depending on the fabric–resin combination. Among all variants, the silica fabric with PF demonstrated the most balanced performance, making it a promising candidate for thermomechanical applications. Full article

Background: Mesothelioma is a rare and aggressive cancer primarily caused by asbestos exposure. In Colombia, asbestos use began in 1942, but mortality surveillance remains limited. Long latency periods and poor documentation hinder public health action. Materials and Methods: A retrospective descriptive study was conducted using mortality data from 1997 to 2022 obtained from the National Administrative Department of Statistics (DANE), including all mesothelioma cases recorded under the five ICD-10 diagnostic categories (C45.0 to C45.9), covering all anatomical sites of first occurrence. Variables analyzed included sex, age, occupation, and place of residence. Mortality rates and trends were estimated using R, Excel, JoinPoint, and Minitab. Results: A total of 1539 mesothelioma deaths were recorded. Most occurred in men (65.1%) and in individuals over 60 years old (62.6%). Urban areas accounted for 92% of deaths. The most frequent diagnosis was unspecified mesothelioma (61.3%). Cities with the highest adjusted mortality rates per 100,000 inhabitants were Sibaté (38.36), Soacha (8.41), and Bogotá (1.89), aligning with historical exposure zones. Conclusions: Mesothelioma is still a preventable public health issue in Colombia, with sustained mortality affecting even working-age populations. The high rate of unspecified diagnoses and weak linkage between morbidity and mortality data underscore the need to strengthen diagnostic capacity, improve surveillance, and implement a national asbestos-related disease elimination strategy. Full article