Abalone peptide increases stress resilience and cost-free longevity via SKN-1-governed transcriptional metabolic reprogramming in C. elegans.

A major goal of healthy aging is to prevent declining resilience and increasing frailty, which are associated with many chronic diseases and deterioration of stress response. Here, we propose a loss-or-gain survival model, represented by the ratio of cumulative stress span to life span, to quantify stress resilience at organismal level. As a proof of concept, this is demonstrated by reduced survival resilience in Caenorhabditis elegans exposed to exogenous oxidative stress induced by paraquat or with endogenous proteotoxic stress caused by polyglutamine or amyloid-ß aggregation. Based on this, we reveal that a hidden peptide ("cryptide")-AbaPep#07 (SETYELRK)-derived from abalone hemocyanin not only enhances survival resilience against paraquat-induced oxidative stress but also rescues proteotoxicity-mediated behavioral deficits in C. elegans, indicating its capacity against stress and neurodegeneration. Interestingly, AbaPep#07 is also found to increase cost-free longevity and age-related physical fitness in nematodes. We then demonstrate that AbaPep#07 can promote nuclear localization of SKN-1/Nrf, but not DAF-16/FOXO, transcription factor. In contrast to its effects in wild-type nematodes, AbaPep#07 cannot increase oxidative stress survival and physical motility in loss-of-function skn-1 mutant, suggesting an SKN-1/Nrf-dependent fashion of these effects. Further investigation reveals that AbaPep#07 can induce transcriptional activation of immune defense, lipid metabolism, and metabolic detoxification pathways, including many SKN-1/Nrf target genes. Together, our findings demonstrate that AbaPep#07 is able to boost stress resilience and reduce behavioral frailty via SKN-1/Nrf-governed transcriptional reprogramming, and provide an insight into the health-promoting potential of antioxidant cryptides as geroprotectors in aging and associated conditions.

China can be self-sufficient in maize production by 2030 with optimal crop management.

Population growth and economic development in China has increased the demand for food and animal feed, raising questions regarding China's future maize production self-sufficiency. Here, we address this challenge by combining data-driven projections with a machine learning method on data from 402 stations, with data from 87 field experiments across China. Current maize yield would be roughly doubled with the implementation of optimal planting density and management. In the 2030 s, we estimate a 52% yield improvement through dense planting and soil improvement under a high-end climate forcing Shared Socio-Economic Pathway (SSP585), compared with a historical climate trend. Based on our results, yield gains from soil improvement outweigh the adverse effects of climate change. This implies that China can be self-sufficient in maize by using current cropping areas. Our results challenge the view of yield stagnation in most global areas and provide an example of how food security can be achieved with optimal crop-soil management under future climate change scenarios.

Resource Allocation Strategy of the Educational Resource Base for MEC Multiserver Heuristic Joint Task.

This paper analyzes the application of MEC multiserver heuristic joint task in resource allocation of the educational resource database. After constructing the scenario of educational resource database, a mathematical model is constructed from the dimensions of local execution strategy, unloading execution, and given educational resource allocation, in order to optimize the optimal allocation of educational resources through MEC. The results show that the DOOA scheme has good performance in terms of calculation cost and timeout rate. Compared with other benchmark schemes, the DQN-based unloading scheme has better performance, can effectively balance the load, and is better than the random unloading scheme and the SNR-based unloading scheme in terms of delay and calculation cost. The results show that the total hits of all category 1 users' content requests account for the proportion of the total content requests. The images have a small downward trend at the 15000 and 30000 time slots and then continue to rise. This shows that the proposed scheme can automatically adjust the caching strategy to adapt to the changes of content popularity, which proves that the agent can correctly perceive the changing trend of content popularity when the popularity of network content is unknown and improve the caching strategy accordingly to improve the cache hit rate. Therefore, the allocation of educational resources based on the MEC multiserver heuristic joint task is more reasonable and can achieve the optimal solution.

A reachable probability approach for the analysis of spatio-temporal dynamics in the human functional network.

The dynamic architecture of the human brain has been consistently observed. However, there is still limited modeling work to elucidate how neuronal circuits are hierarchically and flexibly organized in functional systems. Here we proposed a reachable probability approach based on non-homogeneous Markov chains, to characterize all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level. We proved at the theoretical level the convergence of the functional brain network system, and demonstrated that this approach is able to detect network steady states across connectivity structure, particularly in areas of the default mode network. We further explored the dynamically hierarchical functional organization centered at the primary sensory cortices. We observed smaller optimal reachable steps to their local functional regions, and differentiated patterns in larger optimal reachable steps for primary perceptual modalities. The reachable paths with the largest and second largest transition probabilities between primary sensory seeds via multisensory integration regions were also tracked to explore the flexibility and plasticity of the multisensory integration. The present work provides a novel approach to depict both the stable and flexible hierarchical connectivity organization of the human brain.

Mitigating global warming potential while coordinating economic benefits by optimizing irrigation managements in maize production.

China is the second largest irrigated country in the world. Increasing irrigation intensity costs more water and energy, and produces more greenhouse gas (GHG). In the present study, the responses of maize economic and environmental benefits to different irrigation managements were analyzed in a 2-year field study. A purposely designed tube-study was conducted to explore mechanism underlying effects of irrigation managements in detail. Three treatments, rainfed (RF), flood irrigation (FI), and drip irrigation (DI) were included in the field. Five treatments, no irrigation, flood irrigation, irrigation in 0-30, 30-60, and 0-90 cm depth were conducted in the tube study. Compared to RF, grain yields of FI and DI significantly increased by 22.1 % and 35.7 %, respectively, the net ecosystem economic budget significantly increased by 34.2 % and 35.6 %, and carbon footprint decreased by 7.0 % and 12.7 % in the field study. The irrigation treatments in the tube study increased the global warming potential by 12.0-32.8 % and grain yield by 44.5-203.9 %, and reduced GHG intensity by 24.3-57.4 %, compared with no irrigation treatment. Water content at the top soil layer had the greatest impact on GHG emissions. In conclusion, the differences in grain yield and GHG emissions among irrigation managements are mainly due to the soil water content in space and time. Drip irrigation decreases GHG intensity by producing more grain yield due to the optimized soil water distribution in the root zone. Irrigation management with appropriate amount and frequency can increase economic benefit and reduce environmental cost in maize production.

Prevalence and burden of headache disorders in two neighboring provinces of China.

To our knowledge, studies concerning the prevalence and burden of primary headache in China are limited to specific regions without comparison of different districts. A survey in a different area with similar climate and culture may enhance our knowledge of the factors causing primary headache and the burden of headache. We conducted a 1 year survey on the prevalence and burden of primary headache in the Chinese provinces of Guangdong and Guangxi. Our study also evaluated the factors behind similarities and differences affecting prevalence in the two regions of study. The survey methodology, which was used in an Expanded Program on Immunization by the World Health Organization, was adopted to investigate the prevalence and burden of headache patients. Random samples of 372 local residents in Guangdong and 182 local residents in Guangxi aged 18-65 years were invited to a face-to-face interview. The education level and mean household income were higher in Guangdong (p<0.05). The 1 year prevalence of primary headache was 22.6% (84/372) in Guangdong and 41.2% (75/182) in Guangxi (p<0.001). The average financial burden of primary headache is 2.1% and 3.7% of the mean household income in Guangdong and Guangxi, respectively (p=0.001). The district with lower economic status had a higher prevalence of primary headache, and inevitably bears a heavier burden even with the same disease cost.