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Background: Previous studies have reported inverse associations between urban greenness and mortality. However, findings regarding contemporaneous and cumulative average greenness exposure are inconsistent. A potential explanation is the weak effects of greenness among the general population. This study assessed the associations between contemporaneous and cumulative average greenness exposure and survival in lung cancer patients. Methods: An open cohort consisting of lung cancer patients enrolled from 1 January 2001 was studied. The cohort was followed up until 31 December 2018. We evaluated contemporaneous and cumulative greenness exposure using the normalized difference vegetation index (NDVI) within a 250 m buffer of each patient’s geocoded residential address. The association between NDVI and mortality was evaluated using both time-fixed and time-varying Cox models. Their difference was compared either. Results: In time-fixed Cox models, a 0.1-unit increment in contemporaneous and cumulative average NDVI was associated with 17% (95% confidence interval [CI], 15–18%) and 7% (95% CI, 5–8%) reductions in mortality rate, respectively. Time-varying Cox models consistently revealed significant associations, but their magnitudes were lower, at 2% (95% CI, 1–3%) for both contemporaneous and cumulative average NDVI. Compared to the time-fixed models, the time-varying ones exhibited better fit for the proportional hazard assumption in Cox regressions with more conservative results. Conclusion: Urban greenness is positively associated with an increased chance of survival in lung cancer patients. Compared to time-fixed Cox models, the results of time-varying Cox models were more conservative. This study confirms the beneficial health effects of urban greenness, which may facilitate the improvement of public health by urban green space planning.

Machine learning (ML) methods have rapidly developed in various theoretical and practical research areas, including predicting genomic breeding values for large livestock animals. However, few studies have investigated the application of ML in broiler breeding. In this study, seven different ML methods—support vector regression (SVR), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), kernel ridge regression (KRR) and multilayer perceptron (MLP) were employed to predict the genomic breeding values of laying traits, growth and carcass traits in a yellow-feathered broiler breeding population. The results indicated that classic methods, such as GBLUP and Bayesian, achieved superior prediction accuracy compared to ML methods in five of the eight traits. For half-eviscerated weight (HEW), ML methods showed an average improvement of 54.4% over GBLUP and Bayesian methods. Among the ML methods, SVR, RF, GBDT, and XGBoost exhibited improvements exceeding 60%, with respective values of 61.3%, 61.0%, 60.4%, and 60.7%; while MLP improved by 54.4% and LightGBM by 53.7%, KRR had the lowest improvement at 29.4%. For eviscerated weight (EW), ML methods still outperformed GBLUP and Bayesian methods. MLP gained the largest improvement at 19.0%, while SVR, RF, GBDT, XGBoost, LightGBM, and KRR improved by 15.0%, 16.5%, 9.5%, 7.0%, 1.6%, and 15.9%, respectively. Compared to default hyperparameters, the average improvement of ML methods with tuned hyperparameters was 34.0%, 32.9%, 27.0%, 19.3%, 26.8%, 13.2%, 18.9%, and 46.3%, respectively. The prediction accuracy of above algorithms could be optimized using genome-wide association study (GWAS) to select subsets of significant SNPs. This work provides valuable insights into genomic prediction, aiding genetic breeding in broilers.

Furandicarboxylic acid is considered one of the most representative biomass matrix platforms and has been widely used to synthesize various novel biomaterials. In this study, a series of copolymerized poly (aryl ether ketone) resins with excellent properties have been prepared by combining the nonlinear structure of furan ketone with the weakly polarized cyclohexane structure. And the relationship between the structure and properties of the resins has been systematically studied. The results showed that the synthesized resins had excellent thermal properties, and the 5% thermal decomposition temperature could reach up to 478 °C. In addition, the resin exhibits good solubility and can be dissolved in the most common solvents. Its water absorption is deficient, at only 0.71%. At 10 GHz, the lowest dielectric constant of the resin is 3.05. Most importantly, using bio-based monomers in this study provides an environmentally friendly strategy for material design and synthesis, providing a green way to develop high-performance low-dielectric materials.

Redox electrolytes are highly attractive to bring conventional carbon-based supercapacitors the additional pseudocapacitance; however, shuttling of redox species remains a severe issue restricting the potential applications of redox electrolytes. Here, we report a new phosphotungstic acid-containing redox electrolyte for carbon-based supercapacitors, which shows the shuttling-free feature by locking the polyoxometalate mediators in the porous carbon electrode. Impressively, the porous carbon electrode affords a remarkable specific capacitance of 885.7 F g−1 at 5 mV s−1 in the phosphotungstic acid-added electrolyte, triple that in the additive-free H2SO4 electrolyte (290.2 F g−1). Profiting from the unique Grotthuss proton conduction of phosphotungstic acid, the porous carbon electrode achieves the dramatic rate capability in our redox electrolyte (i.e., 567.7 F g−1 at 200 mV s−1). Moreover, the assembled supercapacitor device affords a specific energy of 52.3 Wh kg−1 and long-term cycling stability (93.7% over 5000 cycles). This study highlights the superiority of the polyoxometalate additive for redox electrolytes in developing advanced supercapacitors integrating high energy density, excellent rate performance, and electrochemical durability.

The chicken egg yolk, which is abundant with lipids, proteins, and minerals, is the major nutrient resource for the embryonic development. In fact, the magnitude and type of yolk nutrients are dynamically changed during the chicken embryogenesis to meet the developmental and nutritional requests at different stages. The yolk nutrients are metabolized and absorbed by the yolk sac membrane and then used by the embryo or other extraembryonic tissues. Thus, understanding the metabolites in the yolk helps to unveil the developmental nutritional requirements for the chicken embryo. In this study, we performed ultra high performance liquid chromatography/tandem mass spectrometry (UHPLC-MS/MS) analysis to investigate the change of metabolites in the egg yolk at embryonic (E) 07, E09, E11, E15, E17, and E19. The results showed that 1) the egg yolk metabolites at E07 and E09 were approximately similar, but E09, E11, E15, E17, and E19 were different from each other, indicating the developmental and metabolic change of the egg yolk; and 2) most of the metabolites were annotated in amino acid metabolism pathways from E11 to E15 and E17 to E19. Especially, arginine, lysine, cysteine, and histidine were continuously increased during the embryonic development, probably because of their effects on the growth promotion and oxidative stress amelioration of the embryo. Interestingly, the ferroptosis was found as one of major processes occurred from E15 to E17 and E17 to E19. Owing to the upregulated expression of acyl-CoA synthetase long-chain family member 4 detected in the yolk sac, we assumed that the ferroptosis of the yolk sac was perhaps caused by the accumulation of reactive oxygen species, which was induced by the large amount of polyunsaturated fatty acids and influx of iron in the yolk. Our findings might offer a novel understanding of embryonic nutrition of broilers according to the developmental changes of metabolites in the egg yolk and may provide new ideas to improve the health and nutrition for prehatch broiler chickens.

Cyclization reaction of poly(acrylonitrile-co-2-acrylamido-2-methylpropane sulfonic acid) [P(AN-co-AMPS)] copolymer during thermal oxidative stabilization (TOS) process was investigated by FTIR and two dimensional (2D) correlation analysis technique. The results showed the mechanism of cyclization reaction at different temperatures were varying. At 200 °C, the cyclization reactions generated by autocatalytic cyclization mechanism. While at higher temperatures, the cyclization reactions took place through ionic cyclization mechanism and free radical cyclization mechanism. The AMPS comonomer could reduce the heat release of cyclization reactions and improve the stability at 200 and 230 °C. At higher temperatures, the cyclization reactions were facilitated rapidly. However, the oxidation and degradation reactions were also intense, which will cause the molecular chain to break and defects in the final carbon fibers (CFs). This research has theoretical guiding significance for the optimization of heat treatment conditions for PAN copolymers used as CFs.