A rechargeable molecular solar thermal system below 0 °C

An optimal temperature is crucial for a broad range of applications, from chemical transformations, electronics, and human comfort, to energy production and our whole planet. Photochemical molecular thermal energy storage systems coupled with phase change behavior (MOST-PCMs) offer unique opportunities to capture energy and regulate temperature. Here, we demonstrate how a series of visible-light-responsive azopyrazoles couple MOST and PCMs to provide energy capture and release below 0 °C. The system is charged by blue light at -1 °C, and discharges energy in the form of heat under green light irradiation. High energy density (0.25 MJ kg-1) is realized through co-harvesting visible-light energy and thermal energy from the environment through phase transitions. Coatings on glass with photo-controlled transparency are prepared as a demonstration of thermal regulation. The temperature difference between the coatings and the ice cold surroundings is up to 22.7 °C during the discharging process. This study illustrates molecular design principles that pave the way for MOST-PCMs that can store natural sunlight energy and ambient heat over a wide temperature range.This work was supported by the National Key Research and Development Program of China (2017YFA0207500), National Natural Science Foundation of China (22022507 and 51973111), Beijing National Laboratory for Molecular Sciences (BNLMS202004), China Postdoctoral Science Foundation (2020M681279) and European Research Council (ERC) through CoG 101002131 “PHOTHERM”.With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000917-S).Peer reviewe

Understanding the Functional Activity of Polyphenols Using Omics-Based Approaches

Plant polyphenols are the main category of natural active substances, and are distributed widely in vegetables, fruits, and plant-based processed foods. Polyphenols have a beneficial performance in preventing diseases and maintaining body health. However, its action mechanism has not been well understood. Foodomics is a novel method to sequence and widely used in nutrition, combining genomics, proteomics, transcriptomics, microbiome, and metabolomics. Based on multi-omics technologies, foodomics provides abundant data to study functional activities of polyphenols. In this paper, physiological functions of various polyphenols based on foodomics and microbiome was discussed, especially the anti-inflammatory and anti-tumor activities and gut microbe regulation. In conclusion, omics (including microbiomics) is a useful approach to explore the bioactive activities of polyphenols in the nutrition and health of human and animals

Salidroside Attenuates High-Fat Diet-Induced Nonalcoholic Fatty Liver Disease via AMPK-Dependent TXNIP/NLRP3 Pathway

Our previous studies suggested that salidroside could alleviate hepatic steatosis in type 2 diabetic C57BLKS/Leprdb (db/db) mice. The aim of the present study was to evaluate the therapeutic effect of salidroside on high-fat diet- (HFD-) induced nonalcoholic fatty liver disease (NAFLD) by investigating underlying mechanisms. Mice were fed with HFD or regular diet, randomly divided into two groups, and treated with salidroside or vehicle for 8 weeks. Then, biochemical analyses and histopathological examinations were conducted in vivo and in vitro. Salidroside administration attenuated HFD-induced obesity, blood glucose variability, and hepatic lipid deposition, markedly increasing insulin sensitivity in HFD mice. In addition, salidroside suppressed oxidative stress, thioredoxin-interacting protein (TXNIP) expression, and NLRP3 inflammasome activation in the liver. In cultured hepatocytes, salidroside dose dependently regulated lipid accumulation, reactive oxygen species (ROS) generation, and NLRP3 inflammasome activation as well as improved AMP-activated protein kinase (AMPK) activity and insulin sensitivity. The inhibition of AMPK activation by inhibitor or short interfering RNA (siRNA) resulted in the suppression of the beneficial effects of salidroside in hepatocytes. Our findings demonstrated that salidroside protects against NAFLD by improving hepatic lipid metabolism and NLRP3 inflammasome activation, and these actions are related to the regulation of the oxidative stress and AMPK-dependent TXNIP/NLRP3 pathways

Co-harvesting Solar Energy with Ambient Heat and On-Demand Release of Thermal Energy Below 0 oC Through Visible-Light-Controlled Photochemical Phase Transitions of Azopyrazoles

Photochemical crystal-to-liquid transition generally needs UV light as a stimulus and it is even more challenging to carry out below 0 oC. Here, we design a series of 4-alkylthioarylazopyrazoles as molecular solar thermal batteries, which show bidirectional visible-light-triggered photochemical trans-crystal ↔ cis-liquid transitions below ice point (-1 oC). Through co-harvesting visible-light energy and low-temperature ambient heat, high energy density (0.25 MJ kg-1) is achieved. Further, the rechargeable solar thermal batteries devices are fabricated, which can be charged by blue light (400 nm) at -1 oC. Then, the charged devices can release energy on demand in the form of high-temperature heat. Under green light (532 nm) irradiation, the temperature difference between the charged devices and the ice-cold surrounding is up to 13.5 oC. This study paves the way for the design of advanced molecular solar thermal batteries that store both natural sunlight and ambient heat over a wide temperature range

Time-sensitive clinical concept embeddings learned from large electronic health records

Abstract Background Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do not consider temporal dependencies along the longitudinal sequence of a patient’s records, which may lead to incorrect selection of contexts. Methods To address this issue, we extended three popular concept embedding learning methods: word2vec, positive pointwise mutual information (PPMI) and FastText, to consider time-sensitive information. We then trained them on a large electronic health records (EHR) database containing about 50 million patients to generate concept embeddings and evaluated them for both intrinsic evaluations focusing on concept similarity measure and an extrinsic evaluation to assess the use of generated concept embeddings in the task of predicting disease onset. Results Our experiments show that embeddings learned from information within one visit (time window zero) improve performance on the concept similarity measure and the FastText algorithm usually had better performance than the other two algorithms. For the predictive modeling task, the optimal result was achieved by word2vec embeddings with a 30-day sliding window. Conclusions Considering time constraints are important in training clinical concept embeddings. We expect they can benefit a series of downstream applications

Evaluation and Prediction of Water Quality of Typical Wetlands in the Source Region of the Yangtze River

Wetlands play an important role in water storage and water conservation, but with global climate change, the degradation of wetland ecosystems is accelerating. In this study, we conducted research on the current situation and future prediction of water quality in typical wetlands in the source region of the Yangtze River to provide a scientific basis for the protection and restoration of wetlands in the source region of the Yangtze River. The Bayesian water quality assessment method and Yao Zhiqi evaluation method were used to evaluate the water quality of typical wetlands in the source region of the Yangtze River from 2016 to 2021 and based on the climate change scenarios of three RCPs (Representative Concentration Pathways) under the CMIP5 (Coupled Model Intercomparison Project Phase 5) global climate model and SWAT (soil and water assessment tool) hydrological model, the wetland water quality in the source region of the Yangtze River from 2022 to 2100 was predicted. The results show that the inter-annual changes in CODMn, NH3-N, and TN in a typical wetland show a downward trend, while the temperature and DO concentration show an upward trend from 2016–2021. The changes in CODMn, temperature, and conductivity within the year are abundant season > flat season > dry season; and DO, NH3-A, TN, and TP concentrations within the year are opposite. The water quality of typical wetlands in the source region of the Yangtze River has reached Class II and above. From 2022 to 2100, under climate change in the future, TN, TP, CODMn, NH3-N, and temperature in the wetland water in the source region of the Yangtze River will continue to rise, and the concentration of DO will continue to decline. Therefore, the pressure on water resources in the source region of the Yangtze River is further aggravated, so it is urgent to strengthen water resources protection