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This study focuses on the association between seminal concentration of prosaposin and ambient air pollutants and whether the association affects the normal fertilization rate in vitro fertilization (IVF) treatment. The cohort of 323 couple participants aged 22–46 was recruited from Jan. 2013 to Jun. 2018. At enrollment, resident address information was obtained and semen parameters of male counterparts were evaluated according to WHO criteria. We used inverse distance weighting interpolation to estimate the levels of ambient pollutants (SO 2 , O 3 , CO, NO 2 , PM 2.5, and PM 10) in the surrounding area. The exposure of each participant was estimated based on the data gathered from air quality monitoring stations and their home address over various periods (0–9, 10–14, and 0–90 days) before semen sampling. The generalized linear regression model (GLM) and the Bayesian kernel machine regression (BKMR) were used to analyze the associations between pollutants, semen parameters, prosaposin, and normal fertilization. Additionally, the mediating effect of prosaposin and semen parameters on the link between pollutants and normal fertilization was investigated. GLM and BKMR showed exposure to ambient air pollutants was all associated with the concentration of seminal prosaposin, among them, O 3 and CO were also associated with normal fertilization (-0.10, 95 %CI: −0.13, −0.06; −26.43, 95 %CI: −33.79, −19.07). Among the semen parameters, only the concentration of prosaposin and total motile sperm count (TMC) was associated with normal fertilization (0.059, 95 %CI: 0.047, 0.071; 0.016, 95 %CI: 0.012, 0.020). Mediation analysis showed that prosaposin played a stronger mediating role than TMC in the relationship between short-term exposure to O 3 and fertilization (66.83 %, P<0.001 versus 3.05 %, P>0.05). Seminal plasma prosaposin showed a stronger meditating effect reflect the correlation between ambient air pollutants and normal fertilization rate than conventional semen parameters, which may be used as one of the indicators between pollution and fertilization in IVF. [Display omitted] • Air pollution decreases seminal prosaposin concentration. • O 3 and CO exposure leads to decreased normal fertilization. • Over 60 % of the effects of O 3 on fertilization are mediated by prosaposin. [ABSTRACT FROM AUTHOR]

This paper proposes an interpretable deep learning method based on generative data augmentation for forecasting carbon allowance prices in the EU Emissions Trading System (ETS) Phase 4. Utilizing TimeGAN, we generate near-real expanded data to enhance the training sets. Temporal Fusion Transformer (TFT) is used to quantify the contribution of impact factors. The results show that the augmentation effectively improved the prediction accuracy. Interpretability analysis reveals that Brent crude oil, NBP natural gas, and Rotterdam coal are the top three contributors. Our findings offer a strong approach for the new phase price forecasting, helping market participants and policymakers in informed decision-making. • Proposes a capable EU ETS Phase 4 forecasting framework. • Generative data augmentation improves the prediction accuracy of allowance prices. • Interpretable forecasting can help the EU ETS participants make informed decisions. [ABSTRACT FROM AUTHOR]

• A new upper variance risk spillover model based on G-expectation is proposed. • Developed countries contribute more to the upper variance of the system. • The total spillover index rises from 24.81% to 66.01% during the crisis. • The dynamic upper variance proves to be sensitive to crisis events. This study proposes a combination model to assess upper variance spillover effects in 14 stock markets. By integrating G-normal distribution model and the connectedness approach, we measure spillover effects and compute upper variance. Empirical findings reveal that developed countries (e.g., Britain, France, Germany) contribute more to upper variance risk, while developing countries (e.g., Philippines, Brazil, Indonesia) receive it. During the crisis, the total spillover index increases from 24.81% to 66.01%. French and German stock markets' spillover rises by 144.21% and 44.94% respectively, while China's spillover is relatively smaller. Dynamic upper variance exhibits an upward trend, sensitive to major economic shocks. [ABSTRACT FROM AUTHOR]

Rapid urbanization and industrialization in the eastern seaboard region of China enhance the widespread use of organophosphorus flame retardants (OPFRs). The present study set up a coupled WRF-CMAQ-SMOKE and multi-compartment exchange modeling framework to assess the environmental fate and cycling of OPFRs and their contamination in the Bohai and Yellow Seas' marine food web. The framework predicts meteorological conditions, optimized air emissions, and concentrations of OPFRs in air, seawaters, marine sediment, and the food web. The model was implemented to simulate the temporal and spatial fluctuations of Tris (2-chloroisopropyl) phosphate (TCPP), the most dominant congener of OPFRs in China, in the Bohai and the Yellow Sea ecosystems on a spatial resolution of 10 km. Results revealed the effects of source proximity, atmospheric transport and deposition, and the changes in meteorology on TCPP's temporal-spatial distribution across different areas of coastal waters. The model also captures TCPP levels in commercial fish species in the Bohai Sea. The detailed temporal-spatial characteristics of TCPP with the mesoscale resolution provide useful information and a new tool for the environmental and health consequences of mariculture, urban and industrial emission mitigation in coastal regions for emerging chemicals, and fishery industry development. [Display omitted] • Mesoscale cycling of OPFR across China's marine environment was quantitatively assessed. • Diurnal and monthly variation of OPFR with high spatial resolution are identified. • Source proximity and lipid contents determine OPFR contamination in commercial fish. • The model provides a useful tool to foresee the risk of toxic chemicals in fish. [ABSTRACT FROM AUTHOR]

Glutamine is a major energy source for rapidly dividing cells, such as hematopoietic stem cells and cancer cells. Reliance on glutamine is therefore regarded as a metabolic hallmark of proliferating cells. Moreover, reprogramming glutamine metabolism by various factors, including tissue type, microenvironment, pro-oncogenes, and tumor suppressor genes, can facilitate stem cell fate decisions, tumor recurrence, and drug resistance. However, the significance of glutamine metabolism in cardiomyocytes, an end-differentiated cell type, is not fully understood. Existing evidence suggests important roles of glutamine metabolism in the development of cardiovascular diseases. In this review, we have focused on glutaminolysis and its regulatory network in proliferating cells. We have summarized current findings about the role of glutamine utilization in cardiomyocytes and have discussed possibilities of targeting glutamine metabolism for the treatment of cardiovascular diseases. • Glutamine metabolism and its most updated regulatory mechanisms. • Biological significance of glutamine and its metabolites in proliferating cells. • Current studies on glutamine metabolism of cardiomyocytes. • Targeting glutamine metabolism in cardiovascular diseases therapy. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are formed by the incomplete combustion of fossil fuels and forest or biomass burning. PAHs undergo long-range atmospheric transport, as evidenced by in situ observations across the Arctic. However, monitored atmospheric concentrations of PAHs indicate that ambient PAH levels in the Arctic do not follow the declining trend of worldwide anthropogenic PAH emissions since the 2000s, suggesting missing sources of PAHs in the Arctic or other places across the Northern Hemisphere. To trace origins and causes for the increasing trend of PAHs in the Arctic, the present study reconstructed PAH emissions from forest fires in the northern boreal forest derived by combining forest carbon stocks and MODIS burned area. We examined the statistical relationships of forest biomass, MODIS burned area, emission factors, and combustion efficiency with different PAH congeners. These relationships were then employed to construct PAH emission inventories from forest biomass burning. We show that for some PAH congeners, for example, benzo[a]pyrene (BaP)—the forest-fire-induced air emissions are almost one order of magnitude higher than previous emission inventories in the Arctic. A global-scale atmospheric chemistry model, GEOS-Chem, was used to simulate air concentrations of BaP, a representative PAH congener primarily emitted from biomass burning, and to quantify the response of BaP to wildfires in the northern boreal forest. The results showed that BaP emissions from wildfires across the northern boreal forest region played a significant role in the contamination and interannual fluctuations of BaP in Arctic air. A source-tagging technique was applied in tracking the origins of BaP pollution from different northern boreal forest regions. We also show that the response of BaP pollution at different Arctic monitoring sites depends on the intensity of human activities. Image 1 • PAH emissions from wildfire were developed using carbon stock and MODIS burned area. • New inventory improved PAH emissions from wildfire biomass burning. • Wildfires in northern Russia were major contributors to BaP pollution in the Arctic. • Increasing PAHs from wildfires offset their declining trend arising from global control. PAH emissions from boreal forest biomass burning based on carbon stock data were established to identify the contributions of northern boreal forest fires to BaP pollution from 2002 to 2014 in the Arctic. [ABSTRACT FROM AUTHOR]