Aquaporin CmPIP2; 3 links H2O2 signal and antioxidation to modulate trehalose-induced cold tolerance in melon seedlings.

Cold stress severely restricts the growth and development of cold-sensitive crops. Trehalose (Tre), known as the 'sugar of life', plays key roles in regulating plant cold tolerance by triggering antioxidation. However, the relevant regulatory mechanism remains unclear. Here, we confirmed that Tre triggers apoplastic hydrogen peroxide (H2O2) production and thus plays key roles in improving the cold tolerance of melon (Cucumis melo var. makuwa Makino) seedlings. Moreover, Tre treatment can promote the transport of apoplastic H2O2 to the cytoplasm. This physiological process may depend on aquaporins. Further studies showed that a Tre-responsive plasma membrane intrinsic protein 2; 3 (CmPIP2; 3) had strong H2O2 transport function and that silencing CmPIP2; 3 significantly weakened apoplastic H2O2 transport and reduced the cold tolerance of melon seedlings. Yeast library and protein-DNA interaction technology were then used to screen two Tre-responsive transcription factors, abscisic acid responsive element (ABRE)-binding factor 2 (CmABF2) and abscisic acid responsive element (ABRE)-binding factor 3 (CmABF3), which can bind to the ABRE motif of the CmPIP2; 3 promoter and activate its expression. Silencing of CmABF2 and CmABF3 further dramatically increased the ratio of apoplastic H2O2/cytoplasm H2O2 and reduced the cold tolerance of melon seedlings. This study uncovered that Tre treatment induces CmABF2/3 to positively regulate CmPIP2; 3 expression. CmPIP2; 3 subsequently enhances the cold tolerance of melon seedlings by promoting the transport of apoplastic H2O2 into the cytoplasm for conducting redox signals and stimulating downstream antioxidation.

PM2.5 induces developmental neurotoxicity in cortical organoids.

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 µg/mL and 50 µg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Optimal conditions for cryopreservation by vitrification of largemouth bass (Micropterus salmoides) embryos.

The largemouth bass (Micropterus salmoides) is one of the important freshwater aquaculture species in the world. However, due to limitations on introduction scale, high-density farming, inbreeding, and species hybridization, the germplasm resources of largemouth bass face threats such as degradation and susceptibility to diseases. Therefore, it is urgent to conduct research on the conservation of its original and good germplasm resources. We optimized the conditions of cryopreservation to vitrify and revive largemouth bass embryos, including the mixing ratio of cryoprotectants, embryo stage, equilibration step and temperature, and washing regent. The results showed that the least toxic single, binary, and ternary mixed permeating cryoprotectants were PG, PM (PG: MeOH = 2:1), and PMD (PM: DMSO = 3:1), respectively. The least toxic non-permeating cryoprotectant was 5 % glucose. The optimal vitrification solution selected was PMDG (30 % PMD + 5 % glucose) with an 80.67 % survival rate of embryos. Embryos at the heartbeat stage exhibited strong tolerance to the PMDG solution, which is the optimal embryo stage for cryopreservation. During the equilibration process, either the five-step equilibration method or pre-cooling the cryoprotectant to 4°C could reduce its toxicity. During the washing process, a 0.125 mol·L-1 sucrose solution yielded the best results. Based on the optimized conditions, 650 embryos at the heartbeat stage were subjected to cryopreservation by vitrification, resulting in a total of 350 intact transparent eggs, two of which hatched successfully. The results provide a reference for further improving the efficiency of cryopreservation by vitrification of largemouth bass and other fish species.

Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.

Objective.Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring its quality, insufficient training data often leads to overfitting and inadequate generalization capabilities of deep learning-based classification networks. Therefore, we propose a novel data augmentation method and deep learning classification model to enhance the decoding performance of MI-EEG further.Approach.The raw EEG signals were transformed into the time-frequency maps as the input to the model by continuous wavelet transform. An improved Wasserstein generative adversarial network with gradient penalty data augmentation method was proposed, effectively expanding the dataset used for model training. Additionally, a concise and efficient deep learning model was designed to improve decoding performance further.Main results.It has been demonstrated through validation by multiple data evaluation methods that the proposed generative network can generate more realistic data. Experimental results on the BCI Competition IV 2a and 2b datasets and the actual collected dataset show that classification accuracies are 83.4%, 89.1% and 73.3%, and Kappa values are 0.779, 0.782 and 0.644, respectively. The results indicate that the proposed model outperforms state-of-the-art methods.Significance.Experimental results demonstrate that this method effectively enhances MI-EEG data, mitigates overfitting in classification networks, improves MI classification accuracy, and holds positive implications for MI tasks.

Ecological drivers of nesting behavior in a subtropical city: An observational study on spotted doves.

Due to rapid homogenization in habitat types as a result of urbanization, some urban birds adapt their nesting strategies to changes in local habitat characteristics. Bird nesting decisions might have been mainly linked to resource constraints and ensuring reproductive success. In this study, we examined patterns of nesting behavior by spotted doves (Spilopelia chinensis) in a rapidly urbanizing area of Nanchang, China using ArcGIS 10.8, satellite tracking, camera traps, and field survey. To explore the mechanisms underlying nesting behavior in urban habitats, we assessed the correlations between nest reuse and reproductive success, and between nest reuse and nest predation. From December 2018 to December 2021, a total of 302 breeding nests were surveyed. The results revealed that the nest reuse rate was 38.08% (n = 115). Nests closer to trunk, with lower nest position and higher large-scale urbanization score tended to have higher reuse rate. In addition, nests with the higher the nest height and percent of canopy cover, and the lower small-scale urbanization score were more likely to reproduce successfully, and the reused nests also reproduce more successfully. The reproductive success associated with nest reuse was significantly higher than that associated with new nests (χ 2 = 8.461, p = .004). High degree of urbanization promoted nest reuse of spotted doves (large-scale urbanization score, z = 2.094, p = .036), which apparently enhanced their reproductive success (nest reuse, z = 2.737, p = .006). In conclusion, a nest structure with good permeability is the material basis for the nest reuse in spotted dove, while the relatively low risk of predation in urban habitat and the scarcity of nest site resources due to urbanization increase the tendency of birds to reuse old nests, which is associated with their reproductive success and evolutionary fitness.

Sustainable biosynthesis of squalene from waste cooking oil by the yeast Yarrowia lipolytica.

Squalene is a highly sought-after triterpene compound in growing demand, and its production offers a promising avenue for circular economy practices. In this study, we applied metabolic engineering principles to enhance squalene production in the nonconventional yeast Yarrowia lipolytica, using waste cooking oil as a substrate. By overexpressing key enzymes in the mevalonate pathway - specifically ERG9 encoding squalene synthase, ERG20 encoding farnesyl diphosphate synthase, and HMGR encoding hydroxy-methyl-glutaryl-CoA reductase - we achieved a yield of 779.9 mg/L of squalene. Further co-overexpression of DGA1, encoding diacylglycerol acyltransferase, and CAT2, encoding carnitine acetyltransferase, in combination with prior metabolic enhancements, boosted squalene production to 1381.4 mg/L in the engineered strain Po1g17. To enhance the supply of the precursor acetyl-CoA and inhibit downstream squalene conversion, we supplemented with 6 g/L pyruvic acid and 0.7 mg/L terbinafine, resulting in an overall squalene titer of 2594.1 mg/L. These advancements underscore the potential for sustainable, large-scale squalene production using Y. lipolytica cell factories, contributing to circular economy initiatives by valorizing waste materials.

Industrialization Mitigates Greenhouse Gas Intensity in China's Dairy Sector yet May Prove Insufficient to Offset Emissions from Future Production Expansion.

China's dairy farming is undergoing a critical transition from extensive to industrial systems. To achieve sustainable milk production within China's dual-carbon goals, understanding the multidimensional impacts of industrialization on greenhouse gas (GHG) emissions is imperative. This study comprehensively analyzed the implications of China's dairy industrialization on GHG emissions and explored future mitigation potential. Results indicated that industrial systems exhibited lower methane but higher carbon dioxide intensities, with net GHG intensity lower than other systems. During 2002-2020, China's milk production increased by 165%, while GHG emissions increased by 105% to 50.27 Tg CO2eq, accompanying an industrialization rate increased from 16% to 75%. The industrialization progress played a mitigating effect on GHG primarily through intensification within individual production systems before 2008 and transformation between systems post-2008. However, the industrialization's effect was relatively modest compared to other socio-economic factors. By 2030, 11.8 Tg CO2eq will be triggered by predicted milk production growth, but only 0.6 Tg can be offset by system transformation. Integrating measures to improve feed, herd, and manure management on industrial farms could decouple GHG emissions from milk production and achieve a carbon peak before 2030. We suggest transforming to improved industrial systems as a necessary step toward sustainable livestock production.

Efficient Alcoholysis of Poly(ethylene terephthalate) by Using Supercritical Carbon Dioxide as a Green Solvent.

In order to reduce the environmental impact of poly(ethylene terephthalate) (PET) plastic waste, supercritical fluids were used to facilitate effective recovery via improved solvent effects. This work focuses on the mechanisms of supercritical CO2 (ScCO2) during the alcoholysis processing of PET using systematic experiments and molecular dynamics (MD) simulations. The results of the alcoholysis experiment indicated that PET chips can be completely depolymerized within only an hour at 473 K assisted with ScCO2 at an optimal molar ratio of CO2/ethanol of 0.2. Random scission of PET dominates the early stage of the depolymerization reaction process, while specific scission dominates the following stage. Correspondingly, molecular dynamics (MD) simulations revealed that the solubilization and self-diffusion properties of ScCO2 facilitate the transportation of alcohol molecules into the bulk phase of PET, which leads to an accelerated diffusion of both oligomers and small molecules in the system. However, the presence of excessive CO2 has a negative impact on depolymerization by weakening the hydrogen bonding between polyester chain segments and ethanol, as well as decreasing the swelling degree of PET. These data provide a deep understanding of PET degradation by alcohols and the enhancement of ScCO2. It should be expected to achieve an efficient and high-yield depolymerization process of wasted polyesters assisted with ScCO2 at a relatively low temperature.

Prediction model for asymptomatic carotid atherosclerosis using retinal microvascular intelligent analysis: A retrospective study.

IMPORTANCE: Early detection and timely diagnosis of asymptomatic carotid atherosclerosis significantly assist in the prevention of ischemic stroke for them. OBJECTIVE: This observational study aimed to develop and validate a novel prediction model to assist in the early diagnosis of carotid atherosclerosis based on new characteristic variables screened by retinal microvascular intelligence analysis. MAIN OUTCOME(S) AND METHOD (S): The least absolute shrinkage and selection operator (LASSO) combined with 10-fold cross-validation were screened for characteristic variables, and nomograms were plotted to demonstrate the prediction model. Receiver operating characteristic (ROC) curves and area under the curve (AUC), calibration plots and brier score (BS), and decision curve analysis (DCA) were used to evaluate the risk model's discrimination, calibration, and clinical applicability. RESULTS: Age, gender, diabetes mellitus (DM), drinking history, vascular branching angle, mean vascular diameter within 0.5-1.0 papillary diameter (PD), curvature tortuosity arteriole in the inferior region of the optic disc, and vascular density in the nasal region of the optic disc were identified as characteristic variables for carotid atherosclerosis with retinal microvascular intelligence analysis. The predictive nomogram model presented good discrimination with AUCs of 0.790 (0.774-0.806), and the calibration curve displayed high consistency between predicted and actual probability. The DCA demonstrated that this nomogram model led to net benefits in a threshold probability range of 20 %-94 % and could be adapted for clinical decision-making. The results of the 100-bootstrap resampling strategy for internal validation also show that the risk model is well discriminated with an AUC of 0.789 and excellent calibration. External validation showed good discrimination with AUCs of 0.703 (0.627 - 0.779) and good calibration, the risk threshold is 10 %-92 % in terms of DCA. CONCLUSIONS AND RELEVANCE: The novel prediction model based on retinal microvascular intelligence analysis constructed in this study could be effective prognoses for predicting the risk of asymptomatic carotid atherosclerosis in a Chinese screening population.

Association Between Triglyceride Glucose Index with Cognitive Impairment and Dementia in Adult Population: A Meta-Analysis.

The current understanding of the correlation between insulin resistance (IR) and cognitive dysfunction is limited. Therefore, the objective of this systematic review and meta-analysis was to assess the association between the triglyceride glucose (TyG) index, a recently suggested indicator of IR, and cognitive impairment and dementia in the adult population. Observational studies pertinent to our research were identified through comprehensive searches of the PubMed, Embase, and Web of Science databases. To account for potential heterogeneity, the random-effects models were employed to aggregate the findings. This meta-analysis included ten observational studies involving 5602409 participants. Compared to those with the low TyG index, subjects with the high TyG index were significantly associated with the risk of cognitive impairment [risk ratio (RR): 1.39, 95% confidence interval (CI): 1.22 to 1.59, p<0.001; I2=45%) and dementia (RR: 1.30, 95% CI: 1.06 to 1.60, p=0.01; I2=50%). The association was consistent for Alzheimer's disease (RR: 1.35, 95% CI: 1.04 to 1.76, p=0.03; I2=54%) and vascular dementia (RR: 1.18, 95% CI: 1.13 to 1.24, p<0.001; I2=0%). Subgroup analyses showed that the association between TyG index with cognitive impairment and dementia were stronger in cross-sectional studies than that in cohort studies (p for subgroup difference=0.02), but not significantly modified by age, sex, or diabetic status of the participants. In conclusion, a high TyG index may be associated with higher risk of cognitive impartment and dementia in adult population.