Large Language Models at Work in China's Labor Market

This paper explores the potential impacts of large language models (LLMs) on the Chinese labor market. We analyze occupational exposure to LLM capabilities by incorporating human expertise and LLM classifications, following Eloundou et al. (2023)'s methodology. We then aggregate occupation exposure to the industry level to obtain industry exposure scores. The results indicate a positive correlation between occupation exposure and wage levels/experience premiums, suggesting higher-paying and experience-intensive jobs may face greater displacement risks from LLM-powered software. The industry exposure scores align with expert assessments and economic intuitions. We also develop an economic growth model incorporating industry exposure to quantify the productivity-employment trade-off from AI adoption. Overall, this study provides an analytical basis for understanding the labor market impacts of increasingly capable AI systems in China. Key innovations include the occupation-level exposure analysis, industry aggregation approach, and economic modeling incorporating AI adoption and labor market effects. The findings will inform policymakers and businesses on strategies for maximizing the benefits of AI while mitigating adverse disruption risks

A Galactomannoglucan Derived from Agaricus brasiliensis: Purification, Characterization and Macrophage Activation via MAPK and IkappaB/NFkappaB Pathways

In this study, a novel galactomannoglucan named as TJ2 was isolated from Agaricus brasiliensis with microwave extraction, macroporous resin, ion exchange resin and high resolution gel chromatography. TJ2 is composed of glucose, mannose and galactose in the ratio 99.2:0.2:0.6. Infrared spectra (IR), methylation analysis and nuclear magnetic resonance spectra indicated that TJ2 mainly contained a b-(1?3) – linked glucopyranosyl backbone. Interestingly, TJ2 significantly promoted RAW264.7 cell proliferation, and was able to activate the cells to engulf E. coli. In addition, TJ2 induced the expression of Interleukin 1b (IL-1b), Interleukin 6 (IL-6), tumor necrosis factor a (TNF-a) and cyclooxygenase-2 (Cox-2) in the cells. TJ2 also promoted the production of nitric oxide (NO) by inducing the expression of inducible nitric oxide synthase (iNOS). Moreover, TJ2 is a potent inducer in activating the mitogen-activated protein kinase (MAPK) and inhibitor of nuclear factor-kappa B (IkappaB)/nuclear factor-kappa B (NFkappaB) pathways

Sevoflurane Pre-conditioning Ameliorates Diabetic Myocardial Ischemia/Reperfusion Injury Via Differential Regulation of p38 and ERK.

Diabetes mellitus (DM) significantly increases myocardial ischemia/reperfusion (MI/R) injury. During DM, cardioprotection induced by conventional pre-conditioning (PreCon) is decreased due to impaired AMP-activated protein kinase (AMPK) signaling. The current study investigated whether PreCon with inhaled anesthetic sevoflurane (SF-PreCon) remains cardioprotective during DM, and identified the involved mechanisms. Normal diet (ND) and high-fat diet (HFD)-induced DM mice were randomized into control and SF-PreCon (3 cycles of 15-minute period exposures to 2% sevoflurane) groups before MI/R. SF-PreCon markedly reduced MI/R injury in DM mice, as evidenced by improved cardiac function (increased LVEF and ±Dp/dt), decreased infarct size, and decreased apoptosis. To determine the relevant role of AMPK, the effect of SF-PreCon was determined in cardiac-specific AMPKα2 dominant negative expressing mice (AMPK-DN). SF-PreCon decreased MI/R injury in AMPK-DN mice. To explore the molecular mechanisms responsible for SF-PreCon mediated cardioprotection in DM mice, cell survival molecules were screened. Interestingly, in ND mice, SF-PreCon significantly reduced MI/R-induced activation of p38, a pro-death MAPK, without altering ERK and JNK. In DM and AMPK-DN mice, the inhibitory effect of SF-PreCon upon p38 activation was significantly blunted. However, SF-PreCon significantly increased phosphorylation of ERK1/2, a pro-survival MAPK in DM and AMPK-DN mice. We demonstrate that SF-PreCon protects the heart via AMPK-dependent inhibition of pro-death MAPK in ND mice. However, SF-PreCon exerts cardioprotective action via AMPK-independent activation of a pro-survival MAPK member in DM mice. SF-PreCon may be beneficial compared to conventional PreCon in diabetes or clinical scenarios in which AMPK signaling is impaired

Food-Derived Natural Products Prevent Neurodegenerative Diseases by Regulating Mitophagy: A Review of Research Progress

Neurodegenerative diseases are often characterized by progressive dysfunction and loss of neuronal structure and function, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease. Mitochondria, the center of energy metabolism in the body, are often damaged and accumulated in neurodegenerative diseases. As an efficient way of removing these damaged mitochondria, mitophagy usually shows an abnormal state in the development of these diseases, which aggravates the cognitive and motor dysfunction of the body, and finally speeds up the process of related diseases. In recent years, it has been found that food-derived natural products, such as quercetin, curcumin, resveratrol and silymarin, play significant roles in regulating mitophagy to improve neurodegenerative diseases, which have unique advantages, such as lower toxicity than chemical synthetic drugs and cost-effectiveness. Here, we summarize recent studies on the regulation of mitophagy by food-derived natural products to slow down neurodegenerative disorders in order to provide new ideas for researchers to develop and utilize food-derived natural products

Indirect influence in social networks as an induced percolation phenomenon

Significance Increasing empirical evidence in diverse social and ecological systems has shown that indirect interactions play a pivotal role in shaping systems’ dynamical behavior. Our empirical study on collaboration networks of scientists further reveals that an indirect effect can dominate over direct influence in behavioral spreading. However, almost all models in existence focus on direct interactions, and the general impact of indirect interactions has not been studied. We propose a new percolation process, termed induced percolation, to characterize indirect interactions and find that indirect interactions raise a plethora of new phenomena, including the wide range of possible phase transitions. Such an indirect mechanism leads to very different spreading outcomes from that of direct influences

Research Progress on Intervention of Natural Products from Plants in Neurotoxicity of Acrylamide

Acrylamide (ACR) is a common toxic substance in foods, which can cause serious damage to human organs and systems, especially the nervous system. At present, there are no appropriate measures to prevent and treat ACR neurotoxicity. In recent years, it has been reported that some natural plant products with high safety for consumption, strong antioxidant activity and low cost can intervene in ACR-induced neurotoxicity. This paper mainly introduces the neurotoxicity of ACR, natural plant products that can intervene in ACR neurotoxicity, and the underlying mechanism of action in order to provide a theoretical reference and research ideas for the treatment of ACR neurotoxicity in multiple ways and though multiple targets, as well as the development and application of natural products against ACR neurotoxicity

Dust detection and intensity estimation using Himawari-8/AHI observation.

In this study, simple dust detection and intensity estimation methods using Himawari-8 Advanced Himawari Imager (AHI) data are developed. Based on the differences of thermal radiation characteristics between dust and other typical objects, brightness temperature difference (BTD) among four channels (BT11–BT12, BT8–BT11, and BT3–BT11) are used together for dust detection. When considering the thermal radiation variation of dust particles over different land cover types, a dynamic threshold scheme for dust detection is adopted. An enhanced dust intensity index (EDII) is developed based on the reflectance of visible/near-infrared bands, BT of thermal-infrared bands, and aerosol optical depth (AOD), and is applied to the detected dust area. The AOD is retrieved using multiple temporal AHI observations by assuming little surface change in a short time period (i.e., 1–2 days) and proved with high accuracy using the Aerosol Robotic Network (AERONET) and cross-compared with MODIS AOD products. The dust detection results agree qualitatively with the dust locations that were revealed by AHI true color images. The results were also compared quantitatively with dust identification results from the AERONET AOD and Ångström exponent, achieving a total dust detection accuracy of 84%. A good agreement is obtained between EDII and the visibility data from National Climatic Data Center ground measurements, with a correlation coefficient of 0.81, indicating the effectiveness of EDII in dust monitoring.N/