Heavy metal contamination of foods remains a persistent global challenge for food safety and public health, driven by industrialization, mining activities, intensive agriculture, and ongoing environmental degradation. This scoping review synthesizes peer-reviewed literature on the occurrence of priority toxic metals—arsenic, cadmium, lead, mercury, and nickel—in food matrices, with emphasis on contamination pathways, analytical detection strategies, and documented human health effects. The reviewed studies reveal widespread accumulation of heavy metals in staple foods, including cereals, vegetables, seafood, and processed products, with concentrations frequently approaching or exceeding international regulatory limits, particularly in regions exposed to strong anthropogenic pressure. Conventional laboratory-based techniques, such as atomic absorption spectrometry and inductively coupled plasma methods, remain the reference standards for quantitative determination and regulatory compliance; however, their application to large-scale or continuous monitoring is often constrained by cost, infrastructure, and operational complexity. Consequently, increasing attention has been directed toward emerging detection approaches, including portable X-Ray fluorescence, Raman/SERS spectroscopy, electrochemical biosensors, electronic tongues, and in situ magnetic measurements, as complementary tools for rapid screening and field-based surveillance. Among these, environmental magnetism and in situ magnetic techniques stand out as non-destructive, low-cost proxies capable of identifying metal-associated particulate contamination linked to food production systems. Chronic dietary exposure to heavy metals is consistently associated with neurotoxicity, nephrotoxicity, carcinogenicity, and oxidative stress, underscoring the need for integrated, multi-tiered monitoring frameworks to support early detection, risk assessment, and prevention.

Mining activities are conducted to extract valuable minerals from the Earth, which are used to manufacture many objects. However, these operations generate landform alterations, such as deep excavations, artificial embankments, and landscape reshaping. In this study, landform changes were monitored in a mining area in Mazapil, Zacatecas, Mexico, using geomatic techniques. Multitemporal Landsat satellite images and digital elevation models (DEMs) from different years were used to detect and quantify landform alterations and estimate the volumes of removed material. The results show ground depressions greater than −333 m and waste material accumulations greater than +152 m, with an average standard deviation of ±3.6 m. A total excavation volume of 413.524 million m³ and a total fill volume of 431.194 million m³ were quantified, with an estimated standard deviation of ±810 m³. The proposed methodology proved effective for the remote quantification of large-scale relief disturbances in open-pit mining areas. It can also be used for environmental monitoring and hydrological risk assessment in active and inactive mining areas.

This study assessed the spatial distribution and composition of airborne particulate matter within a 10 km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stops), revealing mass-specific magnetic susceptibility χ values ranging from −6.71 to 61.1 × 10⁻⁸ m³ kg⁻¹. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW–NNE transport, correlating with hotspots in central and northeastern park areas. Overall, vegetated zones exhibited markedly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³ kg⁻¹) than traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³ kg⁻¹), representing an approximate 50% reduction in magnetic particle accumulation, which highlights the effective role of continuous vegetation cover as a functional green barrier that attenuates the lateral transport and deposition of airborne particulate matter within the park. This research highlights the applicability of combined magnetic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use for identifying both pollution hotspots and mitigation zones, reinforcing the role of urban green spaces as biofunctional filters in cities facing vehicular air pollution.

Acute respiratory distress syndrome (ARDS) remains a leading cause of morbidity and mortality in critically ill patients despite advances in supportive care and lung-protective ventilation. The syndrome is characterized by biological heterogeneity involving epithelial and endothelial injury, dysregulated inflammation, surfactant dysfunction, and impaired alveolar–capillary barrier integrity. This review integrates experimental, translational, and clinical evidence to examine the biological and molecular basis underlying ARDS, with particular emphasis on alveolar–capillary architecture, immune dysregulation, pulmonary mechanics, and the temporal evolution of diffuse alveolar damage. We further discuss emerging concepts in ARDS phenotyping and biomarker-based stratification as tools to address therapeutic heterogeneity and improve prognostic precision. Collectively, the evidence supports a shift from syndromic management toward biologically informed, precision-based approaches that may enable targeted interventions and improved clinical outcomes in ARDS.

Mining activities are conducted to extract valuable minerals from the Earth, used in the manufacture of many objects. However, these operations have been associated with significant landform alterations, such as deep excavations, artificial embankments, and landscape reshaping. In this study, remote sensing (RS) and geographic information systems (GIS) techniques were applied to verify landform changes induced by open-pit mining in Mazapil, Zacatecas, Mexico. Multi-temporal Landsat 5 and 8 satellite images, along with digital elevation models (DEMs) from 1998 and 2014, were used to detect variations in land cover and terrain shape. Analyses revealed ground depressions greater than −333 m and waste accumulations greater than +152 m, with an average standard deviation of ±3.6 m. A total excavation volume of 413,524,124 m³ and an embankment volume of 431,194,785 m³ were quantified, with an estimated standard deviation of ±810 m³. Despite limitations related to DEM resolution, data availability, and restricted mine access, the proposed method proved effective for the remote quantification of large-scale topographic alterations in open-pit mining areas. The integration of satellite imagery, multi-temporal DEMs, and geospatial analysis constitutes a cost-effective and replicable methodology for environmental monitoring, landscape modeling, and hydrological risk assessment in both active and post-mining environments.