Health and Economic Benefits of Complying With the World Health Organization Air Quality Guidelines for Particulate Matter in Nine Major Latin American Cities.

Objectives: This study aims to estimate the short-term preventable mortality and associated economic costs of complying with the World Health Organization (WHO) air quality guidelines (AQGs) limit values for PM10 and PM2.5 in nine major Latin American cities. Methods: We estimated city-specific PM-mortality associations using time-series regression models and calculated the attributable mortality fraction. Next, we used the value of statistical life to calculate the economic benefits of complying with the WHO AQGs limit values. Results: In most cities, PM concentrations exceeded the WHO AQGs limit values more than 90% of the days. PM10 was found to be associated with an average excess mortality of 1.88% with concentrations above WHO AQGs limit values, while for PM2.5 it was 1.05%. The associated annual economic costs varied widely, between US$ 19.5 million to 3,386.9 million for PM10, and US$ 196.3 million to 2,209.6 million for PM2.5. Conclusion: Our findings suggest that there is an urgent need for policymakers to develop interventions to achieve sustainable air quality improvements in Latin America. Complying with the WHO AQGs limit values for PM10 and PM2.5 in Latin American cities would substantially benefits for urban populations.

Review of formation mechanisms and quality regulation of chewiness in staple foods: Rice, noodles, potatoes and bread.

Staple foods serve as vital nutrient sources for the human body, and chewiness is an essential aspect of food texture. Age, specific preferences, and diminished eating functions have broadened the chewiness requirements for staple foods. Therefore, comprehending the formation mechanism of chewiness in staple foods and exploring approaches to modulate it becomes imperative. This article reviewed the formation mechanisms and quality control methods for chewiness in several of the most common staple foods (rice, noodles, potatoes and bread). It initially summarized the chewiness formation mechanisms under three distinct thermal processing methods: water medium, oil medium, and air medium processing. Subsequently, proposed some effective approaches for regulating chewiness based on mechanistic changes. Optimizing raw material composition, controlling processing conditions, and adopting innovative processing techniques can be utilized. Nonetheless, the precise adjustment of staple foods' chewiness remains a challenge due to their diversity and technical study limitations. Hence, further in-depth exploration of chewiness across different staple foods is warranted.

Interpretable prediction, classification and regulation of water quality: A case study of Poyang Lake, China.

Effective identification and regulation of water quality impact factors is essential for water resource management and environmental protection. However, the complex coupling of water quality systems poses a significant challenge to this task. This study proposes coherent model for water quality prediction, classification and regulation based on interpretable machine learning. The decomposition-reconstruction module is used to transform non-stationary water quality series into stationary series while effectively reducing the feature dimensions. Spatiotemporal multi-source data is introduced by using the Maximum Information Coefficient (MIC) for feature selection. The Temporal Convolutional Network (TCN) is used to extract the temporal features of different variables, followed by the introduction of External Attention mechanism (EA) to construct the relationship between these features. Finally, the target water quality sequence is simulated using Gated Recurrent Unit (GRU). The proposed model was applied to Poyang Lake in China to predict six water quality indicators: ammonia nitrogen (NH3-N), dissolved oxygen (DO), pH, total nitrogen (TN), total phosphorus (TP), water temperature (WT). The water quality was then classified based on the prediction results using the XGBoost algorithm. The findings indicate that the proposed model's Nash-Sutcliff Efficiency (NSE) value ranges from 0.88 to 0.99, surpassing that of the benchmark model, and demonstrates strong interval prediction performance. The results highlight the superior performance of the XGBoost algorithm (with an accuracy of 0.89) in addressing water quality classification issues, particularly in cases of category imbalance. Subsequently, interpretability analysis using the SHapley Additive exPlanation (SHAP) method revealed that the model is capable of learning relationships between different variables and there exists a possibility of learning the physical laws. Ultimately, this study proposes a water quality regulation mechanism that improves TN and DO levels by stepwise changing the magnitude of water temperature, which significantly improves in the case of data limitations. In conclusion, this study presents an overall framework for integrating water quality prediction, classification and improvement for the first time, forming a complete set of water quality early warning and improvement management strategies. This framework provides new ideas and ways for lake water quality management.

Metabolomic and Transcriptomic Changes Underlying the Effects of L-Citrulline Supplementation on Ram Semen Quality.

This study examined the effects of L-Cit supplementation on ram semen quality through metabolomics and transcriptomics. A total of 16 rams were randomly categorized into two groups. The control group was fed a basic diet, whereas the experimental group received feed supplemented with 12 g/d of L-Cit. Semen and blood were collected from the rams on days 0 and 72 to measure sugar, pyruvate, amino acid, and nontargeted metabolite contents. Additionally, hypothalamic and testicular tissues were collected for a transcriptomic analysis. We found 27 differential metabolites between the control and experimental groups, of which 21 were downregulated (p < 0.05) and 6 were upregulated (p < 0.05). Compared with the control group, xylose and pyruvate contents in seminal plasma increased by 43.86% and 162.71%, respectively (p < 0.01). Additionally, the levels of 11 amino acids showed a significant increase in seminal plasma (p < 0.01). Furthermore, 961 and 715 differentially expressed genes were detected in the hypothalamic and testicular tissues, respectively. The pathways of significant enrichment in the hypothalamus and testes were protein digestion, absorption, glycolysis/gluconeogenesis, and amino as well as nucleotide sugar metabolisms. In the present study, L-Cit improved protein synthesis and blood metabolism, consequently increasing the contents of most amino acids in ram seminal plasma. Specifically, the hypothalamus controlled the expression of glycolysis/gluconeogenesis-related genes in the testes through its metabolites released into the serum, thereby providing energy for sperm production, which led to a decrease in the sugar content of seminal plasma.

Testing ecosystem accounting in the United States: A case study for the Southeast.

Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S. We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a ten-state region in the Southeast. The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015. Results illustrate how information from ecosystem accounts can contribute to policy and decision-making. Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area's environmental-economic trends. The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries. Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.

Can Air Quality Management Drive Sustainable Fuels Management at the Temperate Wildland-Urban Interface?

Sustainable fire management has eluded all industrial societies. Given the growing number and magnitude of wildfire events, prescribed fire is being increasingly promoted as the key to reducing wildfire risk. However, smoke from prescribed fires can adversely affect public health and breach air quality standards. Here we propose that air quality standards can lead to the development and adoption of sustainable fire management approaches that lower the risk of economically and ecologically damaging wildfires while improving air quality and reducing climate-forcing emissions. For example, green fire breaks at the wildland-urban interface (WUI) can resist the spread of wildfires into urban areas. These could be created through mechanical thinning of trees, and then maintained by targeted prescribed fire to create biodiverse and aesthetically pleasing landscapes. The harvested woody debris could be used for pellets and other forms of bioenergy in residential space heating and electricity generation. Collectively, such an approach would reduce the negative health impacts of smoke pollution from wildfires, prescribed fires, and combustion of wood for domestic heating. We illustrate such possibilities by comparing current and potential fire management approaches in the environmentally similar landscapes of Vancouver Island in British Columbia, Canada and the island state of Tasmania in Australia.

Elucidating the Mechanisms of the Tomato ovate Mutation in Regulating Fruit Quality Using Proteomics Analysis.

The ovate mutation has frequently been used to study changes in fruit shape but not fruit quality. A deterioration in fruit quality associated with the ovate mutation was discovered in this study. To elucidate how ovate influences the quality of fruit, we performed a proteomics analysis of the fruits of the ovate mutant (LA3543) and wild-type ("Ailsa Craig", LA2838A) using tandem mass tag analysis. The results indicated that the ovate mutation significantly influences fruit quality in a number of ways, including by reducing the expression of 1-aminocyclopropane-1-carboxylic acid oxidase 3 (ACO3) in ethylene biosynthesis, improving firmness by reducing the amount of pectinesterase and polygalacturonase, reducing sugar accumulation by downregulating the abundance of mannan endo-1,4-ß-mannosidase 4, ß-galactosidase, and ß-amylase, and reducing the malic acid content by downregulating the accumulation of malic enzymes and malate synthase. These findings could inform future improvements in fruit quality.

[Effects of light quality on cell growth and psbA promoter of engineered Synechococcus sp. PCC7002].

Light quality can regulate both psbA genes and vector promoter psbA of the engineered Synechococcus. Through light regulation, we tried to improve yield of the recombinant protein for vp28 gene-expressed Synechococcus sp. PCC7002. To drive photon-capturing efficiently, three limiting factors (irradiance, temperature and pH) were optimized by measuring net photosynthesis. High cell density cultures were performed with variant ratios of white, red and blue light in a 5-L photo-bioreactor. Yields of biomass, expressions of vp28 and transcription levels of psbA were compared. High ratio blue light-induced vp28 transcription had tripled and the relative accumulation of VP28 protein was doubled. The relative expressions of psbAII and psbAIII had positive correlations with higher ratio of blue light, not the red light. With high ratio red light inducing, dry biomass reached 1.5 g/L in three days. Therefore, we speculated that red light accelerated biomass accumulation of the transgenic strain and blue light promoted transcription for PpsbA and psbA. These results provided useful information for mass production of cyanobacteria and its secondary metabolites.

Distributional benefit analysis of a national air quality rule.

Under Executive Order 12898, the U.S. Environmental Protection Agency (EPA) must perform environmental justice (EJ) reviews of its rules and regulations. EJ analyses address the hypothesis that environmental disamenities are experienced disproportionately by poor and/or minority subgroups. Such analyses typically use communities as the unit of analysis. While community-based approaches make sense when considering where polluting sources locate, they are less appropriate for national air quality rules affecting many sources and pollutants that can travel thousands of miles. We compare exposures and health risks of EJ-identified individuals rather than communities to analyze EPA's Heavy Duty Diesel (HDD) rule as an example national air quality rule. Air pollutant exposures are estimated within grid cells by air quality models; all individuals in the same grid cell are assigned the same exposure. Using an inequality index, we find that inequality within racial/ethnic subgroups far outweighs inequality between them. We find, moreover, that the HDD rule leaves between-subgroup inequality essentially unchanged. Changes in health risks depend also on subgroups' baseline incidence rates, which differ across subgroups. Thus, health risk reductions may not follow the same pattern as reductions in exposure. These results are likely representative of other national air quality rules as well.