Priority sources identification and risks assessment of heavy metal(loid)s in agricultural soils of a typical antimony mining watershed.

Heavy metal(loid) (HM) pollution in agricultural soils has become an environmental concern in antimony (Sb) mining areas. However, priority pollution sources identification and deep understanding of environmental risks of HMs face great challenges due to multiple and complex pollution sources coexist. Herein, an integrated approach was conducted to distinguish pollution sources and assess human health risk (HHR) and ecological risk (ER) in a typical Sb mining watershed in Southern China. This approach combines absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models with ER and HHR assessments. Four pollution sources were distinguished for both models, and APCS-MLR model was more accurate and plausible. Predominant HM concentration source was natural source (39.1%), followed by industrial and agricultural activities (23.0%), unknown sources (21.5%) and Sb mining and smelting activities (16.4%). Although natural source contributed the most to HM concentrations, it did not pose a significant ER. Industrial and agricultural activities predominantly contributed to ER, and attention should be paid to Cd and Sb. Sb mining and smelting activities were primary anthropogenic sources of HHR, particularly Sb and As contaminations. Considering ER and HHR assessments, Sb mining and smelting, and industrial and agricultural activities are critical sources, causing serious ecological and health threats. This study showed the advantages of multiple receptor model application in obtaining reliable source identification and providing better source-oriented risk assessments. HM pollution management, such as regulating mining and smelting and implementing soil remediation in polluted agricultural soils, is strongly recommended for protecting ecosystems and humans.

Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China.

With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution.

Standardized framework for assessing soil quality at antimony smelting site by considering microbial-induced resilience and heavy metal contamination.

Antimony smelting activities damage the soil and vegetation surroundings while generating economic value. However, no standardized methods are available to diagnose the extent of soil degradation at antimony smelting sites. This study developed a standardized framework for assessing soil quality by considering microbial-induced resilience and heavy metal contamination at Xikuangshan antimony smelting site. The soil resilience index (SRI) and soil contamination index (SCI) were calculated by Minimum Data Set and geo-accumulation model, respectively. After standardized by a multi-criteria quantitative procedure of modified Nemerow's pollution index (NPI), the integrated assessment of soil quality index (SQI), which is the minimum of SRINPI and SCINPI, was achieved. The results showed that Sb and As were the prominent metal(loid) pollutants, and significant correlations between SQI and SRI indicated that the poor soil quality was mainly caused by the low level of soil resilience. The primary limiting factors of SRI were Fungi in high and middle contaminated areas, and Skermanella in low contaminated area, suggesting that the weak soil resilience was caused by low specific microbial abundances. Microbial regulation and phytoremediation are greatly required to improve the soil quality at antimony smelting sites from the perspectives of pollution control and resilience improvement. This study improves our understanding of ecological effects of antimony smelting sites and provides a theoretical basis for ecological restoration and sustainable development of mining areas.

Musseling through: Mytilus byssal thread production is unaffected by continuous noise.

Anthropogenic low-frequency noise (ALFN) is a rising pollutant in the world oceans. Despite the ubiquity of ALFN, its effect on marine invertebrates is still poorly understood. Here, we tested how continuous low-frequency noise (CLFN), a substantial component of ALFN, affects the byssal thread production of Mytilus, a cosmopolitan genus of mussels with high ecological and economic importance. The effects of acute CLFN exposure and predator cues on byssogenesis by Mytilus spp. were explored in both the presence and absence of predator cues. While predator effluents increased thread production, CLFN had seemingly no effect on thread counts. Further, trends suggested a synergistic effect of CLFN and predator cues. The behavioral indifference of Mytilus spp. toward CLFN could contribute to the observed prevalence of these animals in inherently disturbed habitats. This would partly explain their success in colonizing and persisting on artificial substrata rife with disturbances.

Metal concentrations in fish, crabs, and bivalve molluscs from marine waters adjacent to a multi-metals smelter and refinery.

Metal concentrations were determined in tissues of finfish, crabs, and bivalve molluscs collected from marine waters near Port Pirie, South Australia, the site of a long-standing multi-metals smelter and refinery. A general trend of tissue metal concentrations in order of highest to lowest was observed in bivalves > crabs > finfish. A lead concentration of 158 ± 6.6 mg/kg (wet wt.) was observed in blue mussels (Mytilus galloprovincialis) sampled close to the smelter. Lead concentrations correlated positively with proximity to the smelter in all biota analysed. Similar relationships were observed for cadmium, copper, zinc and selenium in all biota except razorfish (Pinna bicolor; Bivalvia: Pinnidae), which showed no correlation with proximity to the smelter for these metals. Inorganic arsenic concentrations were below the limit of reporting in the majority of the analysed samples, however inorganic arsenic concentrations in blue swimmer crabs (Portunus armatus) and blue mussels correlated with proximity to the smelter. Mercury concentrations in the biota analysed were generally low and showed variable relationships with proximity to the smelter, with no significant correlation observed in finfish and razorfish, a significant positive correlation in blue mussels, and a significant negative correlation in blue swimmer crabs. This is the first major study of metal concentrations in recreationally-targeted marine species near Port Pirie species for more than two decades. Comparison with data from previous studies conducted shows little change in tissue metal concentrations in marine biota near Port Pirie over the past 40 years.

Short-term air pollution and greenness exposures on oxidative stress in urban and peri-urban residents in Beijing: A part of AIRLESS study.

BACKGROUND: Exposure to air pollution has been associated with increased risks of cardiopulmonary diseases, cancer, and mortality, whereas residing near green spaces may reduce the risks. However, limited research explores their combined effect on oxidative stress. METHODS: A total of 251 participants with multi-time measurements were included in the longitudinal-designed study. Personal gaseous air pollutants (CO, NO, NO2, and O3,) and particulate pollution (PM1, PM2.5, and PM10) were measured and followed in two 7-day windows while ambient exposure levels and urine samples were collected simultaneously. Participants' Normalized Difference Vegetation Index (NDVI) was estimated and used to represent greenness exposure. Urinary oxidative stress biomarkers include free malondialdehyde (MDA), total MDA, and 8-hydroxydeoxyguanosine (8-OHdG). Linear mixed-effects models were used to independently and jointly estimate the associations of greenness and air pollution with oxidative stress biomarkers. RESULTS: We found consistent positive associations of personal ozone (O3) exposure with 8-OHdG percent changes, and this association was modified by gender and outdoor activity frequency. Consistent positive associations of personal lag 2-day carbon monoxide (CO) exposure with the percent changes of the three oxidative stress biomarkers were significant. We additionally observed that individuals who lived in greener areas had lower levels of urinary-free and total MDA. Participants in the highest NDVI tertile had 0.38 and 0.46 lower free and total MDA levels, [95 % CI: (-0.70, -0.05) and (-0.78, -0.13)], compared to the lowest NDVI tertile. There was also evidence indicating the modification effects by area, education, and outdoor activity frequency on associations between NDVI exposure and creatinine adjusted free MDA (all Pfor interaction < 0.05). Additional greenness modification effects on personal O3 exposure with urinary 8-OHdG was observed. CONCLUSION: Our study provides biological evidence of the modification effect of the built environment on the impact of air pollution.

Small microplastics have much higher mass concentrations than large microplastics at the surface of nine major European rivers.

Understanding the fates and impacts of microplastics requires information on their sizes, polymer types, concentrations, and spatial and temporal distributions. Here, we focused on large (LMPs, 500 µm to 5 mm) and small (SMPs, 25 to 500 µm) microplastics sampled with the exact same protocol in nine of the major European rivers during the seven months of the Tara Microplastic Expedition. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and pyrolysis coupled with gas chromatography and mass spectrometry (Py-GC-MS) analyses were used to determine the microplastics contents by number and mass. The median LMP concentration was 6.7 particles m-3, which was lower than those in other regions of the world (America and Asia). The SMP mass concentration was much higher to the LMP concentrations, with SMP/LMP ratios up to 1000 in some rivers. We did not observe a systematic positive effect of urban areas for the two size classes or polymers; this could be explained by the fact that the transport of microplastic is highly heterogeneous in rivers. We believe that this study has important implications for predictive models of plastics distribution and fate in aquatic environments.

Untargeted metabolomic insights into plastisphere communities in European rivers.

Every year, rivers introduce a staggering amount of hundred kilotons of plastic into the Oceans. This plastic is inhabited by microorganisms known as the plastisphere, which can be transferred between different ecosystems through the transport of microplastics. Here, we simulated the microbial colonization of polyethylene-based plastic pellets that are classically used to manufacture large-scale plastic products. The pellets were immersed for 1 month in four to five sampling stations along the river-to-sea continuum of nine of the major European rivers. This study presents the first untargeted metabolomics analysis of the plastisphere, by using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). The plastisphere metabolomes were similar in the Rhine and Rhone rivers, while being different from the Tiber and Loire rivers, which showed greater similarity to the Thames and Seine rivers. Interestingly, we found a clear distinction between plastisphere metabolomes from freshwater and marine water in most of the river-to-sea continuum, thus suggesting a complete segregation in plastisphere metabolites that is not consistent with a major transfer of microorganisms between the two contrasted ecosystems. Putative annotations of 189 discriminating metabolites suggested that lipid metabolism was significantly modulated. These results enlightened the relevance of using environmental metabolomic as complementary analysis to the current OMICs analysis.

Microplastic abundance and accumulation patterns in eelgrass (Zostera marina L.) meadows throughout coastal Massachusetts, USA.

Microplastics are fast-emerging as another potential threat to already globally declining seagrass ecosystems, but there is a paucity of in situ surveys showing their accumulations. Here, we surveyed multiple Zostera marina L. meadows in 2020 and 2021 across Massachusetts, USA, for microplastic contamination, as well as identified factors related to patterns of accumulation. We found that microplastics were ubiquitous throughout all sites regardless of proximity to human development, with fibers being the most common microplastic type. In addition, we showed that accumulation of microplastics within seagrass meadows was related to epiphytic cover on leaves, plant morphology, and bulk-density in sediments. The results of this study provide the first in situ baseline microplastic concentrations on Z. marina plants and sediments for the temperate western North Atlantic. Additionally, we identify specific biotic and abiotic factors related to patterns of microplastic accumulation in these ecosystems.

Air Pollution and Rheumatoid Arthritis Risk and Progression: Implications for the Mucosal Origins Hypothesis and Climate Change for RA Pathogenesis.

PURPOSE OF REVIEW: The goal of this review paper is to summarize the main research and findings regarding air pollution and its association with the risk and progression of rheumatoid arthritis (RA). RECENT FINDINGS: The most studied components of air pollution included particulate matter of ≤ 2.5 microns in diameter (PM2.5), PM10, carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NOx), sulfur dioxide (SO2), and ozone (O3). In addition, specific occupations and occupational inhalants have been investigated for RA risk. Several studies showed that increased exposure to air pollutants increased the risk of developing RA, particularly seropositive RA. There was evidence of gene-inhalant interactions for seropositive RA risk. Fewer studies have been conducted on RA disease activity and bone erosions. Some studies suggest that patients with RA-associated interstitial lung disease may have worse outcomes if exposed to air pollution. We summarized associations between air pollution and increased RA risk, including RA-associated interstitial lung disease. Relatively few studies investigated air pollution and RA disease activity or other outcomes. These results suggest an important role of air pollution for seropositive RA development and suggest that climate change could be a driver in increasing RA incidence as air pollution increases.

Decreasing levels of atmospheric pollution and simultaneous reduced number of cardiovascular hospital admissions and operations with improved results. Analysis of the Italian National Registries.

BACKGROUND: The aim of our study was to determine a correlation between decrease of levels of atmospheric pollution (as determined by air levels of Particulate Matters with a diameter equal or less to 2.5 microns) and reduced number of hospital admissions and operations for patients with common cardiovascular diseases in Italy. METHODS: We correlated number of hospital admissions and cardiovascular operations and atmospheric levels of PM.2.5 from 2015 to 2019 in Italy. This time interval was chosen because the possibility to analyze data about other established cardiovascular risk factors as reported by the European Union Eurostat. RESULTS: A statistically significant decrease of hospital admissions for cardiovascular and pulmonary emergencies was registered in Italy from 2015 to 2019 (p<0.01). The number also of cardiovascular operations showed a trend towards reduction with improved 30-days results, without reaching a statistically significant correlation (p =0.10). In the period 2015-2019, there was a steady decrease of atmospheric levels of pM2.5, either in urban or rural areas (p<0.01). The decrease of atmospheric levels of PMs2.5 started in 2010 and continued with a steady trend until the year 2019. In the period 2015-2019 exposure of the Italian population to established risk factors for cardiovascular diseases showed a small increase. The number of admissions and operations for non- cardiovascular and non-pulmonary diseases remained unchanged in the period 2015-2019. CONCLUSIONS: The findings of our study underline the possibility that decrease of atmospheric pollution may determine almost immediate decrease of cardiovascular and pulmonary diseases.

Reflections of stress: Ozone damage in broadleaf saplings can be identified from hyperspectral leaf reflectance.

Tropospheric ozone (O3) causes widespread damage to vegetation; however, monitoring of O3 induced damage is often reliant on manual leaf inspection. Reflectance spectroscopy of vegetation can identify and detect unique spectral signatures of different abiotic and biotic stressors. In this study, we tested the use of hyperspectral leaf reflectance to detect O3 stress in alder, beech, birch, crab apple, and oak saplings exposed to five long-term O3 regimes (ranging from daily target maxima of 30 ppb O3 to 110 ppb). Hyperspectral reflectance varied significantly between O3 treatments, both in whole spectra analysis and when simplified to representative components. O3 damage had a multivariate impact on leaf reflectance, underpinned by changes in pigment balance, water content and structural composition. Vegetation indices derived from reflectance which characterised the visible green peak were able to differentiate between O3 treatments. Iterative normalised difference spectral indices across the hyperspectral wavelength range were correlated to visual damage scores to identify significant wavelengths for O3 damage detection. We propose a new Ozone Damage Index (OzDI), which characterises the reflectance peak in the shortwave infrared region and outperformed existing vegetation indices in terms of correlation to O3 treatment. These results demonstrate the potential application of hyperspectral reflectance as a high throughput method of O3 damage detection in a range of common broadleaf. species.

An equilibrium criterion for plastic debris fate in wave-driven transport.

The nearshore zone turns out to be the area with the higher concentration of plastic debris and, for this reason, it is important to know the processes that affect the transport and the fate of this type of litter. This study focuses on investigating the dynamics of various plastic types under several hydrodynamic conditions primarily induced by waves. 2D tests were carried out at the Hydraulic Laboratory of the University of Messina reproducing the main phenomena that occurred during the wave propagation on a planar beach. More than 200 different conditions were tested changing the wave characteristics, the water depth, the plastic debris characteristics (density and shape), and the roughness of the fixed bottom. In general, it can be observed that the reduction in particle displacement occurs due to: i) a decrease in wave steepness; ii) an increase in depth; iii) an increase in particle size; iv) an increase in plastic density. However, the experimental investigation shows that some plastic characteristics and bed roughness, even when hydraulically smooth, can alter these results. The experimental data analysis identified a criterion for predicting the short-term fate of plastic debris under wave action. This criterion to determine equilibrium conditions, based on an empirical relationship, takes into account the wave characteristics, the bed roughness and slope, and the weight of the debris.

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning.

Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities' contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77-0.91 for COD and 0.47-0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

The screening evaluation of environmental odors: a new dispersion modelling-based tool.

Odor pollution is the biggest source of complaints from citizens concerning environmental issues after noise. Often, the need for corrective actions is evaluated through simulations performed with atmospheric dispersion models. To save resources, air pollution control institutions perform a first-level odor impact assessment, for screening purposes. This is often based on Gaussian dispersion models (GDM), which does not need high computational power. However, their outputs tend to be conservative regarding the analyzed situation, rather than representative of the real in-site conditions. Hence, regulations and guidelines adopted at an institutional level for authorization/control purposes are based on Lagrangian particle dispersion models (LPDM). These models grant a more accurate simulation of the pollutants' dispersion even if they are more demanding regarding both technical skills and computing power. The present study aims to increase the accuracy of screening odor impact assessment by identifying the correlation function of the outputs derived from the two simulation models. The case study is placed in northern Italy, where a single-point source, with various stack heights, was considered. The case study is placed in northern Italy, where a single-point source, with various stack heights, was considered. The obtained correlation functions allow the practitioner to have a more accurate first-level odor impact assessment, to save time for training, and to reduce the site-specific meteorological data before proceeding with the simulation. The identified functions could allow institutions to estimate the results that would have been forecasted with the application of the more complex LPDM, applying, however, the much simpler GDM. This solution grants an accurate tool which can be used to address citizens' concerns while saving workforce and technical resources. Limitations are related to the specificity of the method regarding type sources, orography, and meteorological conditions. Comparison with other screening tools is also presented and discussed.

Prenatal and early-life air pollutant exposure and epigenetic aging acceleration.

BACKGROUND: This study investigated the association of prenatal and early childhood exposure to air pollution with epigenetic age acceleration (EAA) at six years of age using the Environment and Development of Children Cohort (EDC Cohort) MATERIALS & METHODS: Air pollution, including particulate matter [< 2.5 µm (PM2.5) and < 10 µm (PM10) in an aerodynamic diameter], nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and sulfur dioxide (SO2) were estimated based on the residential address for two periods: 1) during the whole pregnancy, and 2) for one year before the follow-up in children at six years of age. The methylation levels in whole blood at six years of age were measured, and the methylation clocks, including Horvath's clock, Horvath's skin and blood clock, PedBE, and Wu's clock, were estimated. Multivariate linear regression models were constructed to analyze the association between EAA and air pollutants. RESULTS: A total of 76 children in EDC cohort were enrolled in this study. During the whole pregnancy, interquartile range (IQR) increases in exposure to PM2.5 (4.56 µg/m3) and CO (0.156 ppm) were associated with 0.406 years and 0.799 years of EAA (Horvath's clock), respectively. An IQR increase in PM2.5 (4.76 µg/m3) for one year before the child was six years of age was associated with 0.509 years of EAA (Horvath's clock) and 0.289 years of EAA (Wu's clock). PM10 (4.30 µg/m3) and O3 (0.003 ppm) exposure in the period were also associated with EAA in Horvath's clock (0.280 years) and EAA in Horvath's skin and blood clock (0.163 years), respectively. CONCLUSION: We found that prenatal and childhood exposure to ambient air pollutants is associated with EAA among children. The results suggest that air pollution could induce excess biological aging even in prenatal and early life.

Artificial light at night alters the locomotor behavior of the Mediterranean sea urchin Paracentrotus lividus.

Artificial light at night (ALAN) is a recognized source of anthropogenic disturbance, although its effects on biological systems have not been fully explored. Within marine ecosystems, coastal areas are the most impacted by ALAN. Here, we focused on the Mediterranean sea urchin Paracentrotus lividus, which has a crucial role in shaping benthic ecosystems. Our objective was to investigate if ALAN affects the nocturnal locomotor behavior of P. lividus. A semi-controlled field study was conducted along a rocky shore near a promenade lit at night. Results suggested a potential impact of ALAN on the locomotor behavior of sea urchins. Individuals of P. lividus tended to move away from the light sources while its directions in dark conditions were uniform. Their locomotor performance, in presence of ALAN, was characterized by shorter latency time, lower sinuosity and higher mean speed at increasing light intensity, with potential cascading effect at the ecosystem level.

Impact of PM2.5 exposure in old age and its interactive effect with smoking on incidence of diabetes.

PURPOSE: To determine the impact of PM2.5 exposure in old age and its interactive effect with smoking on incident diabetes. METHODS: A total of 2766 participants aged ≥60 years in China were interviewed at baseline for disease risk factors in 2001-03 and were then followed up for 10 years to document incident diabetes. They were assessed for daily PM2.5 exposure in 2005. Multivariate Cox regression models were used to examine the association of PM2.5 exposure with incident diabetes and interactive effect between PM2.5 and smoking on incident diabetes. RESULTS: During the cohort follow-up, 176 participants developed diabetes. The incidence of diabetes increased with PM2.5 exposure; the multiple-adjusted hazard ratio (HR) of diabetes was 2.27 (95 % CI 1.36-3.77) in participants with PM2.5 at ≥62.0 µg/m3 compared to those with <62.0 µg/m3. There was a significant interaction effect of PM2.5 with smoking on increased risk of diabetes. The adjusted HR for participants exposed to PM2.5 levels ≥62.0 µg/m3 who smoked was 4.39 (95 % CI 1.72-11.21), while for non-smokers it was 1.65 (95 % CI 0.88-3.09), compared to those with <62.0 µg/m3. CONCLUSIONS: Exposure to PM2.5 in old age was associated with an increased incidence of diabetes and smoking enhanced the impact of PM2.5 on diabetic risk. These findings underscore the urgent need for air quality improvement measures and smoking cessation programs to mitigate the risk of diabetes in aging populations.

Associations between cooking method of food and type 2 diabetes risk: A prospective analysis focusing on cooking method transitioning.

Cooking process for food significantly impacts household air and increase exposure to endocrine disruptors such as acrylamide and, consequently, affecting human health. In the past 30 years, the transformation of cooking methods to high-temperature thermal processing has occurred widely in China. Yet the transition of cooking methods on the onset of type 2 diabetes (T2D) remains unclear, which may hinder health-based Sustainable Development Goals. We aimed to estimate the associations between dietary intake with different cooking methods and T2D risk. We included 14,745 participants (>20 y) from the China Health and Nutrition Survey (1991-2015). Food consumption was calculated using three consecutive 24-h dietary recalls combined with both individual participant level and household food inventory. Cooking methods, including boiled, steamed, baked, griddled, stir-fried, deep-fried, and raw, were also recorded. The consumption of baked/griddle foods and deep-fried foods are positively associated with 39% and 35% higher of T2D risk by comparing the highest with the lowest categories of food consumption, respectively. The overall unhealthy cooking method for processing foods including baked/griddled and deep-fried foods was attributable for 15 million T2D cases of the total T2D burden in 2011, resulting in a medical cost of $2.7 billion and was expected to be attributable for 39 million T2D cases in 2030, producing a medical cost of $223.8 billion. Replacing one serving of deep-fried foods and baked/griddle foods with boiled/steamed foods was related to 50% and 20% lower risk of T2D, respectively. Our findings support healthy driven cooking methods for daily diet are recommended to nourish sustainable T2D prevention in China.

[Translated article] Pharmaceuticals in the environment: A hospital pharmacy perspective.

Drugs do not disappear once they have been excreted. In fact, 992 active principles have already been measured in the different environmental matrices. A recent study led by scientists from the University of York has studied the presence of drugs in the rivers of more than 100 different countries, showing that environmental contamination by pharmaceuticals is a global issue and that, concentrations found are frequently harmful to the environment. In this work, we have tried to briefly expose the problem of environmental contamination with medicines, but above all, we have tried to address the possible solutions, with a perspective from the field of hospital pharmacy. This is a very complex matter (a wicked problem), since it involves multiple stakeholders with different visions and interests regarding medicines. In order to find solutions, we will probably need to act at all steps of the drug's life cycle. Until now, health professionals have been part of the problem. It is time for us to be part of the solution.