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The accurate state-of-charge (SOC) estimation of sodium-ion batteries is the basis for their efficient application. In this paper, a new SOC estimation method suitable for sodium-ion batteries and their application conditions is proposed, which considers the combination of open circuit voltage (OCV) and internal resistance correction. First, the optimal order of equivalent circuit model is analyzed and selected, and the monotonic and stable mapping relationships between OCV and SOC, as well as between ohmic internal resistance and SOC are determined. Then, a joint estimation algorithm for battery model parameters and SOC is established, and a joint SOC correction strategy based on OCV and ohmic internal resistance is established. The test results show that OCV correction is reliable when polarization is small, that the ohmic internal resistance correction is reliable when the current fluctuation is large, and that the maximum absolute error of SOC estimation of the proposed method is not more than 2.6%.

Electric vehicles and battery energy storage are effective technical paths to achieve carbon neutrality, and lithium-ion batteries (LiBs) are very critical energy storage devices, which is of great significance to the goal. However, the battery’s characteristics of instant degradation seriously affect its long life and high safety applications. The aging mechanisms of LiBs are complex and multifaceted, strongly influenced by numerous interacting factors. Currently, the degree of capacity fading is commonly used to describe the aging of the battery, and the ratio of the maximum available capacity to the rated capacity of the battery is defined as the state of health (SOH). However, the aging or health of the battery should be multifaceted. To realize the multi-dimensional comprehensive evaluation of battery health status, a novel SOH estimation method driven by multidimensional aging characteristics is proposed through the improved single-particle model. The parameter identification and sensitivity analysis of the model were carried out during the whole cycle of life in a wide temperature environment. Nine aging characteristic parameters were obtained to describe the SOH. Combined with aging mechanisms, the current health status was evaluated from four aspects: capacity level, lithium-ion diffusion, electrochemical reaction, and power capacity. The proposed method can more comprehensively evaluate the aging characteristics of batteries, and the SOH estimation error is within 2%.

Summary: Efficient health indicators (HI) and prediction methods are crucial for assessing the remaining useful life (RUL) of fuel cells. However, obtaining HI under dynamic conditions with frequently changing loads is highly challenging. Therefore, this study proposes a prediction framework based on dynamic conditions. A method combining complete ensemble empirical mode decomposition with adaptive noise, power spectral density, and energy analysis (CPE) is proposed to extract HI under dynamic conditions from the perspectives of frequency and energy. Furthermore, the time convolution network with adaptive Bayesian optimization (AB-TCN) is introduced to address parameter optimization and prediction challenges. Effective feature parameters of the data are identified using random forest and used to train the AB-TCN. Results show that the extracted HI can effectively determine the end-of-life. The AB-TCN achieves accurate RUL estimation with a prediction error of only 6.825% and shows strong adaptability to various prediction tasks.

Abstract Systemic therapy is typically the primary treatment choice for hepatocellular carcinoma (HCC) patients with extrahepatic metastases. Some patients may achieve partial response (PR) or complete response (CR) with systemic treatment, leading to the possibility of their primary tumor becoming resectable. This study aimed to investigate whether these patients could achieve longer survival through surgical resection of their primary tumor. We retrospectively collected data from 150 HCC patients with extrahepatic metastases treated at 15 different centers from January 1st, 2015, to November 30th, 2022. We evaluated their overall survival (OS) and progress-free survival (PFS) and analyzed risk factors impacting both OS and PFS were analyzed. Patients who received surgical treatment had longer OS compared to those who did not (median OS 16.5 months vs. 11.3 months). However, there was no significant difference in progression-free survival between the two groups. Portal vein invasion (P = 0.025) was identified as a risk factor for poor prognosis in patients, while effective first-line treatment (P = 0.039) and surgical treatment (P = 0.005) were protective factors. No factors showed statistical significance in the analysis of PFS. Effective first-line treatment (P = 0.027) and surgical treatment (P = 0.006) were both independent protective factors for prolonging patient prognosis, while portal vein invasion was an independent risk factor (P = 0.044). HCC patients with extrahepatic metastases who achieve PR/CR with conversion therapy may experience longer OS through surgical treatment. This study is the first to analyze the clinical outcomes of patients receiving surgical treatment for HCC with extrahepatic metastases.

Abstract Battery remaining charging time (RCT) prediction can facilitate charging management and alleviate mileage anxiety for electric vehicles (EVs). Also, it is of great significance to improve EV users' experience. However, the RCT for a lithium-ion battery pack in EVs changes with temperature and other battery parameters. This study proposes an electrothermal model-based method to accurately predict battery RCT. Firstly, a characteristic battery cell is adopted to represent the battery pack, thus an equivalent circuit model (ECM) of the characteristic battery cell is established to describe the electrical behaviors of a battery pack. Secondly, an equivalent thermal model (ETM) of the battery pack is developed by considering the influence of ambient temperature, thermal management, and battery connectors in the battery pack to calculate the temperature which is then fed back to the ECM to realize electrothermal coupling. Finally, the RCT prediction method is proposed based on the electrothermal model and validated in the wide temperature range from − 20 ℃ to 45 ℃. The experimental results show that the prediction error of the RCT in the whole temperature range is less than 1.5%.

Abstract Inflammation and immune processes underlie pulmonary hypertension progression. Two main different activated phenotypes of macrophages, classically activated M1 macrophages and alternatively activated M2 macrophages, are both involved in inflammatory processes related to pulmonary hypertension. Recent advances suggest that macrophages coordinate interactions among different proinflammatory and anti-inflammatory mediators, and other cellular components such as smooth muscle cells and fibroblasts. In this review, we summarize the current literature on the role of macrophages in the pathogenesis of pulmonary hypertension, including the origin of pulmonary macrophages and their response to triggers of pulmonary hypertension. We then discuss the interactions among macrophages, cytokines, and vascular adventitial fibroblasts in pulmonary hypertension, as well as the potential therapeutic benefits of macrophages in this disease. Identifying the critical role of macrophages in pulmonary hypertension will contribute to a comprehensive understanding of this pathophysiological abnormality, and may provide new perspectives for pulmonary hypertension management.

Abstract Background Episodic memory loss is a prominent clinical manifestation of Alzheimer’s disease (AD), which is closely related to tau pathology and hippocampal impairment. Due to the heterogeneity of brain neurons, the specific roles of different brain neurons in terms of their sensitivity to tau accumulation and their contribution to AD-like social memory loss remain unclear. Therefore, further investigation is necessary. Methods We investigated the effects of AD-like tau pathology by Tandem mass tag proteomic and phosphoproteomic analysis, social behavioural tests, hippocampal electrophysiology, immunofluorescence staining and in vivo optical fibre recording of GCaMP6f and iGABASnFR. Additionally, we utilized optogenetics and administered ursolic acid (UA) via oral gavage to examine the effects of these agents on social memory in mice. Results The results of proteomic and phosphoproteomic analyses revealed the characteristics of ventral hippocampal CA1 (vCA1) under both physiological conditions and AD-like tau pathology. As tau progressively accumulated, vCA1, especially its excitatory and parvalbumin (PV) neurons, were fully filled with mislocated and phosphorylated tau (p-Tau). This finding was not observed for dorsal hippocampal CA1 (dCA1). The overexpression of human tau (hTau) in excitatory and PV neurons mimicked AD-like tau accumulation, significantly inhibited neuronal excitability and suppressed distinct discrimination-associated firings of these neurons within vCA1. Photoactivating excitatory and PV neurons in vCA1 at specific rhythms and time windows efficiently ameliorated tau-impaired social memory. Notably, 1 month of UA administration efficiently decreased tau accumulation via autophagy in a transcription factor EB (TFEB)-dependent manner and restored the vCA1 microcircuit to ameliorate tau-impaired social memory. Conclusion This study elucidated distinct protein and phosphoprotein networks between dCA1 and vCA1 and highlighted the susceptibility of the vCA1 microcircuit to AD-like tau accumulation. Notably, our novel findings regarding the efficacy of UA in reducing tau load and targeting the vCA1 microcircuit may provide a promising strategy for treating AD in the future.

The inefficient combustion of traditional biomass fuels in the Tibetan Plateau, the world’s highest region, impacts both local ecosystems and global climate change despite the substantial renewable energy potential and ongoing economic growth of the area. However, the utilization of clean household energy sources and the enablers supporting their sustained use in this region remain underexplored. Through the regional household survey and fuel-weighing campaign, we observed that clean modern energy sources, such as gas and electricity, were used for over 85% of the year in urban areas but only 25% in rural areas. Approximately 3.98 million residents still predominantly rely on traditional solid fuels for daily cooking and/or heating. A substantial energy inequality was identified, with Gini coefficients of 0.65 and 0.55 for cooking and heating, respectively. Despite the disparity in clean energy adoption across income groups being relatively small, the regional utilization of clean energy is severely constrained by limited accessibility and affordability. This has minimized the impact of household characteristics, such as gender, age, and education level, and diminished the effect of rising incomes on accelerating clean cooking practices. The findings highlight the urgent need for targeted residential energy interventions and incentives to promote a clean energy transition in the Tibetan Plateau, as achieving universal clean energy access by 2030 is unlikely without significant efforts.

ABSTRACT The Changle goose (CLG), a Chinese indigenous breed, is celebrated for its adaptability, rapid growth, and premium meat quality. Despite its agricultural value, the exploration of its genomic attributes has been scant. Our study entailed whole‐genome resequencing of 303 geese across CLG and five other Chinese breeds, revealing distinct genetic diversity metrics. We discovered significant migration events from Xingguo gray goose to CLG and minor gene flow between them. We identified genomic regions through selective sweep analysis, correlating with CLG's unique traits. An elevated inbreeding coefficient in CLG, alongside reduced heterozygosity and rare single nucleotide polymorphisms (RSNPs), suggests a narrowed genetic diversity. Genomic regions related to reproduction, meat quality, and growth were identified, with the GATA3 gene showing strong selection signals for meat quality. A non‐synonymous mutation in the Sloc2a1 gene, which is associated with reproductive traits in the CLG, exhibited significant differences in allelic frequency. The roles of CD82, CDH8, and PRKAB1 in growth and development, alongside FABP4, FAF1, ESR1, and AKAP12 in reproduction, were highlighted. Additionally, Cdkal1 and Mfsd14a may influence meat quality. This comprehensive genetic analysis underpins the unique genetic makeup of CLG, providing a basis for its conservation and informed breeding strategies.

ObjectiveTo integrate pharmacovigilance and network toxicology methods to explore the potential adverse drug events (ADEs) and toxic mechanisms of selumetinib, and to provide a reference for quickly understanding the safety and toxicological mechanisms of newly marketed drugs.MethodsTaking selumetinib as an example, this study integrated pharmacovigilance methods based on real-world data and network toxicology methods to analyze its ADE and its potential toxicological mechanism. First, the ADE reports of selumetinib were extracted from the US Food and Drug Administration (FDA) adverse event reporting system (FAERS), and the ADE signals were detected by reporting odds ratio (ROR) and UK medicines and healthcare products regulatory agency (MHRA) methods. The ADE signals were classified and described according to the preferred terms (PTs) and system organ class (SOC) derived from the Medical Dictionary for Regulatory Activities (MedDRA). The network toxicology method was used to analyze the toxicological mechanism of the interested SOCs. The specific steps included predicting the potential targets of selumetinib using TOXRIC, STITCH, ChEMBL, CTD, SwissTargetPreditcion, and Super-PRED databases, collecting the targets of SOC using GeneCards database, conducting protein-protein interaction (PPI) analysis through STRING database, conducting gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis through DAVID database, and testing the molecular affinity using AutoDock software.ResultsA total of 1388 ADE reports related to selumetinib were extracted, and 53 positive signals were detected by ROR and MHRA methods, of which 20 signals were not mentioned in the package insert, including ingrowing nail, hyperphosphatemia, cardiac valve disease, hematuria, neutropenia, etc. Analysis of the toxicological mechanism of six SOCs involved in positive ADE signals revealed that the key targets included EGFR, STAT3, AKT1, IL6, BCL2, etc., and the key pathways included PI3K/Akt pathway, apoptosis, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor resistance, etc. Molecular docking assays showed spontaneous binding of selumetinib to key targets in these pathways.ConclusionThe pharmacovigilance analysis identified some new potential ADEs of selumetinib, and the network toxicology analysis showed that the toxic effects of selumetinib may be related to PI3K/Akt pathway, apoptosis, ErbB signaling pathway, EGFR tyrosine kinase inhibitor resistance and other pathways.

Background: To investigate the long-term corneal stromal remodeling and central stromal thickness (CST) reduction accuracy after small-incision lenticule extraction (SMILE) for high myopia correction. Methods: This prospective study included 30 patients (50 eyes) who had undergone SMILE. Measurements of CST reduction using optical coherence tomography were performed at 1 month, 6 months, 1 year, and 3 years after surgery. Correlations were performed between planned and achieved CST reductions. Results: The study enrolled 50 eyes of 30 patients. The mean spherical equivalent was -9.25±1.52 D(diopters). The postoperative CST increased in the first month after surgery and remained stable for a year. Thereafter, it remained stable during follow-up from 1 to 3 years postoperatively. The predicted CST reduction was 146.4 ± 10.3 μm. The achieved CST reductions at 1 month, 6 months, 1 year, and 3 years after surgery were 135.3 ± 12.1 μm, 130.8 ± 10.6 μm, 125.9 ± 9.4 μm, and 122.2 ± 10.6 μm, respectively. An overestimation of CST reduction was observed three years after surgery. Correlation analysis revealed a strong correlation between planned and achieved CST reductions; however, no correlation was found between CST reductions predicted error and the planned CST reductions. Conclusion: During long-term follow-up, our findings revealed a significant stromal remodeling following SMILE in patients with high myopia. Therefore, clinicians should consider it when screening patients with high myopia for SMILE.

BackgroundThe causality between frailty and gestational diabetes mellitus (GDM) has not yet been fully explored. A potential bidirectional causality was also needed to be confirmed.MethodsA bidirectional two-sample Mendelian randomization (MR) was conducted, with frailty-related data was collected from UK Biobank and TwinGen and GDM-related data was collected from the FinnGen consortium. We performed univariable and multivariable-adjusted MR with adjustments for body mass index (BMI). Several methodologies of MR were conducted to confirm the robustness of results.ResultsFrailty was significantly associated with elevated risks of GDM (OR, 3.563; 95% CI, 1.737 to 7.309; P< 0.001) and GDM was also significantly associated with elevated risks of frailty (β, 0.087; 95% CI, 0.040 to 0.133; P< 0.001). There is no evidence demonstrating the existence of horizontal pleiotropy and heterogeneity. This association was robust after adjustments for BMI. The sensitivity analyses with Weighted median, Maximum likelihood, Penalised weighted median, MR Egger and MR PRESSO methods indicated consistent results.ConclusionOur study provides evidence of the bidirectional causal association between frailty and GDM from genetic perspectives, signaling that the identification and assessment of frailty should become a standard strategy during the early stages and care of gestational diabetes.

Abstract Covalent organic frameworks (COFs), which are constructed by linking organic building blocks via dynamic covalent bonds, are newly emerged and burgeoning crystalline porous copolymers with features including programmable topological architecture, pre‐designable periodic skeleton, well‐defined micro‐/meso‐pore, large specific surface area, and customizable electroactive functionality. Those benefits make COFs as promising candidates for advanced electrochemical energy storage. Especially, for now, structure engineering of COFs from multi‐scale aspects has been conducted to enable optimal overall electrochemical performance in terms of structure durability, electrical conductivity, redox activity, and charge storage. In this review, we give a fundamental and insightful study on the correlations between multi‐scale structure engineering and eventual electrochemical properties of COFs, started with introducing their basic chemistries and charge storage principles. The careful discussion on the significant achievements in structure engineering of COFs from linkages, redox sites, polygon skeleton, crystal nanostructures, and composite microstructures, and further their effects on the electrochemical behavior of COFs are presented. Finally, the timely cutting‐edge perspectives and in‐depth insights into COF‐based electrode materials to rationally screen their electrochemical behaviors for addressing future challenges and implementing electrochemical energy storage applications are proposed.

To address the issues of low coordination in low-carbon operation between Carbon Capture and Storage (CCS) devices and Power to Gas (P2G) devices in integrated energy systems (IES), as well as the inaccurate characterization of carbon emissions from energy storage devices, this paper proposes an extended carbon emission flow model that integrates the collaborative operation mode of CCS-P2G and the low-carbon characteristics of energy storage. The model establishes a coupling relationship between CCS and P2G on the energy supply side to achieve low-carbon economic operation of P2G. On the energy storage side, the concept of “electricity-carbon ratio (ECR)” is introduced to characterize the carbon emission characteristics of energy storage devices, exploring the potential for coordinated low-carbon dispatch on both the energy supply and energy storage sides. Based on this, a low-carbon economic dispatch model for integrated energy systems is constructed, considering multiple uncertainties such as wind power, electricity prices, and electric-heat-gas loads. To achieve fast and efficient solving of the model, a parallel multi-dimensional approximate dynamic programming algorithm is adopted, which significantly improves solving efficiency by constructing a multi-layer parallel loop nested framework without losing solving accuracy. The effectiveness of the proposed model and algorithm is validated using an improved E14-H6-G6 system, consisting of a 14-node power grid, a 6-node heating network, and a 6-node gas network. The CCS-P2G (Carbon Capture, Storage, and Power-to-Gas) collaborative operation mode discussed in this article significantly enhances the economic and low-carbon performance of the Integrated Energy System (IES) by fully reutilizing CO2. Compared to unmodified coal-fired power units, the total cost is reduced by 137,900 yuan, thereby validating the effectiveness of the CCS-P2G collaborative operation mode in low-carbon scheduling.

Battery capacity assessment is a crucial research direction in the field of lithium-ion battery applications. In the previous research, a novel data-driven state of health (SOH) estimation method based on the voltage relaxation curve at full charging is developed. The experimental results have shown the evidence of the superiority of accurate battery SOH estimation based on physical features derived from equivalent circuit models (ECMs). However, the earlier research has limitations in estimating battery capacity with a diversity of battery charging states of charge. This study represents an extension of the previous work, aiming to investigate the feasibility of this technology for battery degradation evaluation under various charging states so that the application capability in practice is enhanced. In this study, six ECM features are extracted from 10-min voltage relaxation data across varying charging states to characterize the battery degradation evolution. Gaussian process regression (GPR) is employed to learn the relationship between the physical features and battery SOH. Experimental results under 10 different state of charge (SOC) ranges show that the developed methodology predicts accurate battery SOH, with a root mean square error being 0.9%.

Career crafting offers a new approach for individuals to cope with changing career situations. However, few studies have focused on personality-related antecedents that stably predict career proactivity. Additionally, as individuals’ careers are embedded in various social relationships, career crafting involves significant social interaction. Our study focuses on gratitude, which is related to social interaction, suggesting that gratitude fosters an appreciation for interpersonal relationships, providing a beneficial impetus for career crafting. A quantitative approach was adopted with a three-wave survey with 825 responses, and SPSS 26 and Mplus 8.3 were used as the analytical software for confirmatory factor analysis, hierarchical regression analysis, and path analysis. We conducted an empirical examination employing a moderated mediation model grounded in the framework of proactive motivation. The results revealed a positive correlation between gratitude and career crafting, with prosocial motivation mediating this relationship. Simultaneously, intrinsic motivation moderated the relationship between prosocial motivation and career crafting. Our study emphasizes gratitude’s role in career crafting and explores how it, along with prosocial motivations, drives proactive behaviors, responding to calls for relational work redesign and examining interactions between intrinsic and prosocial motivations in careers. It has important practical implications for individuals, organizations, and career counselors.

Abstract The utilization of novel noncollinear antiferromagnetic materials holds great promise for the development of energy‐efficient spintronic devices. However, only a few studies have reported on the all‐electrical control of perpendicular magnetization switching using noncollinear antiferromagnets as the spin source, and the underlying mechanism behind the unconventional spin‐orbit torque (SOT) is still a topic of debate. In this work, deterministic perpendicular magnetization switching in Mn3Sn/CoTb bilayers is successfully achieved. Compared to the control samples with heavy metal as the spin source, the critical switching current density is over one order of magnitude reduced, indicating an enhanced efficiency of the out‐of‐plane charge‐to‐spin conversion in the textured Mn3Sn films. The influence of film thickness and growth temperature on the efficiency of different spin polarizations suggests potential roles of crystal quality and spin texture in spin diffusion with different spin polarization directions. These findings provide valuable insights into the crystal structure, spin‐orbit torque effects, and charge‐to‐spin conversion in Mn3Sn films, highlighting the importance of understanding interface and bulk contributions in antiferromagnetic spin transport phenomena.

Universal access to clean fuels in household use is one explicit indicator of sustainable development while currently still billions of people rely on solid fuels for daily cooking. Despite of the recognized clean transition trend in general, disparities in household energy mix in different activities (e.g. cooking and heating) and historical trends remain to be elucidated. In this study, we revealed the historical changing trend of the disparity in household cooking and heating activities and associated carbon emissions in rural China. The study found that the poor had higher total direct energy consumption but used less modern energy, especially in cooking activities, in which the poor consumed 60 % more energy than the rich. The disparity in modern household energy use decreased over time, but conversely the disparity in total residential energy consumption increased due to the different energy elasticities as income increases. Though per-capita household CO2 and Black Carbon (BC) emissions were decreasing under switching to modern energies, the disparity in household CO2 and BC deepened over time, and the low-income groups emitted ∼ 10 kg CO2 more compared to the high-income population. Relying solely on spontaneous clean cooking transition had limited impacts in reducing disparities in household energy and carbon emissions, whereas improving access to modern energy had substantial potential to reduce energy consumption and carbon emissions and its disparity. Differentiated energy-related policies to promote high-efficiency modern heating energies affordable for the low-income population should be developed to reduce the disparity, and consequently benefit human health and climate change equally.

Abstract Background Epithelial mesenchymal transformation (EMT) in alveolar type 2 epithelial cells (AT2) is closely associated with pulmonary fibrosis (PF). Histone deacetylase 3 (HDAC3) is an important enzyme that regulates protein stability by modulating the acetylation level of non-histones. Here, we aimed to explore the potential role and regulatory mechanisms associated with HDAC3 in PF. Methods We quantified HDAC3 expression both in lung tissues from patients with PF and from bleomycin (BLM)-treated mice. HDAC3 was also detected in TGF-β1-treated AT2. The mechanistic activity of HDAC3 in pulmonary fibrosis and EMT was also explored. Results HDAC3 was highly expressed in lung tissues from patients with PF and bleomycin (BLM)-treated mice, especially in AT2. Lung tissues from AT2-specific HDAC3-deficient mice stimulated with BLM showed alleviative fibrosis and EMT. Upstream of HDAC3, TGF-β1/SMAD3 directly promoted HDAC3 transcription. Downstream of HDAC3, we also found that genetic or pharmacologic inhibition of HDAC3 inhibited GATA3 expression at the protein level rather than mRNA. Finally, we found that intraperitoneal administration of RGFP966, a selective inhibitor of HDAC3, could prevent mice from BLM-induced pulmonary fibrosis and EMT. Conclusion TGF-β1/SMAD3 directly promoted the transcription of HDAC3, which aggravated EMT in AT2 and pulmonary fibrosis in mice via deacetylation of GATA3 and inhibition of its degradation. Our results suggest that targeting HDAC3 in AT2 may provide a new therapeutic target for the prevention of PF.

To improve the safety of electric vehicles and battery energy storage systems, early prediction of thermal runaway (TR) is of great significance. This work proposes a novel method for early warning and short-term prediction of the TR. To give warning of TR long time in advance, a variety of battery models are established to extract key features, such as Pauta feature and Shannon entropy of voltage deviation, and then local outlier factor algorithm is used for feature fusion to detect abnormal cells. For the short-term prediction, the predefined threshold and variation rates are used. By measuring the real-time signals, such as voltage and temperature, their variation rates are calculated, based on which TR can be predicted exactly. The real data including TR from an electric vehicle are used to verify the method that it can give a warning on TR long time before it happens up to 74 days. This is remarkable for providing replacement recommendations for abnormal cells. It can also predict the occurrence of TR 33 seconds in advance to ensure the safe use of batteries.

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

Cooperative Technology Transfer (CTT) is a technology transfer model where universities and enterprises jointly participate throughout the entire process of technology transfer activities. Most discussions focus on its mechanisms and influencing factors, yet a framework to guide CTT projects in practice is still lacking. This study proposes an assessment model based on the life-cycle of CTT projects, covering the initial cooperation relationship, project management during the mid-term, and technological achievements at the end. The model was evaluated by 14 experts first and then validated through two CTT projects in China. Gray Relation Analysis was employed to calculate the weights of different factors based on their relative importance, while the Dempster–Shafer theory was utilized to combine evidence from various sources and address the uncertainty in the assessment. The results of the case analysis indicate that the attitudes of universities and enterprises are considered critical in influencing the success of CTT projects, while management issues that arise during the projects can pose potential risks. This research serves as an applied exploration and has three functions. Firstly, the model can be used as a feasibility study before the project commences. Secondly, it can be utilized to analyze and improve potential issues during the project. Finally, it can be used for a post-project experience summary.

Abstract Background The APETALA 2/ ethylene-responsive element binding factors (AP2/ERF), are thought to be associated with plant abiotic stress response, and involved in some plant hormone signaling pathways. Trichosanthes kirilowii is an important edible and medicinal crop, so far no research has been conducted on the TkAP2/ERF genes. Result In this study, a total of 135 TkERFs were identified, these genes were divided into 4 subfamilies and clustered into 13 groups. Moreover, 37 paralogous pairs were identified, with only two having Ka/Ks values greater than 1, proving that most TkERF genes underwent purifying selection during evolution. Co-expression networks constructed using transcriptome data at various flowering stages revealed that 50, 64, and 67 AP2/ERF genes correlated with members of the ethylene, gibberellin, and abscisic acid signaling pathways, respectively. When tissue cultured seedlings were treated with ETH, GA3 and ABA, 11, 12 and 17 genes were found to be up-regulated, respectively, suggesting that some members of the TkERF gene family may be involved in plant hormone signaling pathways. And under 4 ℃, PEG and NaCl treatment, 15, 20 and 19 genes were up-regulated, respectively, this suggested that these selected genes might be involved in plant abiotic stresses. Conclusions Overall, we identified 135 AP2/ERF family members, a comprehensive analysis of AP2/ERF gene expression patterns by RNA-seq and qRT-PCR showed that they played important roles in flower development and abiotic stress. This study provided a theoretical basis for the functional study of TkAP2/ERF genes and the genetic improvement of T. kirilowii.

Half-metallic chromium dioxide (CrO2) is a promising candidate in magnetic random-access memory (MRAM) devices due to its nearly full spin polarization and ultralow Gilbert damping at room temperature. In this study, we succeeded in fabricating (110) and (100)-oriented RuO2/CrO2 bilayers with different thicknesses of CrO2 film using two-step method. The CrO2 film epitaxially grown on a RuO2 layer exhibits a perfect in-plane magnetic uniaxial anisotropy. The magnetic relaxation of CrO2 films can be strongly modulated via the proximity to RuO2 layer, which may relate to the enhancement of the two-magnon scattering due to effects of antiferromagnetic order in RuO2 film. In addition, electronic transport measurements indicate that the electronic characteristic is strongly related to the film growth orientation, and a linear magnetoresistance is observed stemming from intergrain tunneling magnetoresistance and double-exchange mechanism. Angle-dependent ferromagnetic resonance measurements indicates that the uniaxial anisotropy in CrO2 film is strongly related to the strain effect, which is consistent with reciprocal space mapping results. This work lays a foundation for current-drive MRAM based on RuO2/CrO2 bilayer and provides a feasible damping modulation method for CrO2 film.

Arrhythmia is one of the most common cardiovascular diseases. The search for new drugs to suppress various types of cardiac arrhythmias has always been the focus of attention. In the past decade, the screening of antiarrhythmic active substances from plants has received extensive attention. These natural compounds have obvious antiarrhythmic effects, and chemical modifications based on natural compounds have greatly increased their pharmacological properties. The chemical modification of botanical antiarrhythmic drugs is closely related to the development of new and promising drugs. Therefore, the structural characteristics and action targets of natural compounds with antiarrhythmic effects are reviewed in this paper, so that pharmacologists can select antiarrhythmic lead compounds from natural compounds based on the disease target - chemical structural characteristics.

To enhance the quality of life and ensure sustainability in crowded cities, safe management of drinking water using cutting-edge technologies is a priority. This study developed an intelligent early warning system (EWS) for alarming and controlling risks from bacteria and disinfection byproducts in a drinking water distribution system (DWDS), named BARCS (Bacterial Risk Controlling System). BARCS adopts an artificial intelligence (AI) approach to data-driven prediction and considers total chlorine (TCl) concentration as the pivot indicator for risk identification and control. First, the machine learning-based AI model in BARCS can provide a reliable prediction of TCl concentration in a DWDS, with an average R2 of 0.64 for the validation set, while offering great flexibility for BARCS to adapt to various conditions. Second, TCl concentration was proven to be a good indicator of bacterial risk in a DWDS, as well as a cost-effective surrogate variable to assess disinfection byproduct risk. Third, the robustness analysis demonstrates that with state-of-the-art water quality monitoring technologies, online implementation of BARCS in real-world settings is feasible. Overall, BARCS represents a promising solution to the safe management of drinking water in future smart cities. HIGHLIGHTS BARCS predicts and regulates bacterial risk in pipelines.; TCl prediction module harvests an average R2 of 0.64 for the validation set.; The relationship between TCl and CFU is quantified.; Online implementation of BARCS in real-world settings is feasible.;

Abstract State of health is a critical state which evaluates the degradation level of batteries. However, it cannot be measured directly but requires estimation. While accurate state of health estimation has progressed markedly, the time- and resource-consuming degradation experiments to generate target battery labels hinder the development of state of health estimation methods. In this article, we design a deep-learning framework to enable the estimation of battery state of health in the absence of target battery labels. This framework integrates a swarm of deep neural networks equipped with domain adaptation to produce accurate estimation. We employ 65 commercial batteries from 5 different manufacturers to generate 71,588 samples for cross-validation. The validation results indicate that the proposed framework can ensure absolute errors of less than 3% for 89.4% of samples (less than 5% for 98.9% of samples), with a maximum absolute error of less than 8.87% in the absence of target labels. This work emphasizes the power of deep learning in precluding degradation experiments and highlights the promise of rapid development of battery management algorithms for new-generation batteries using only previous experimental data.

Abstract The development of a battery management algorithm is highly dependent on high-quality battery operation data, especially the data in extreme conditions such as low temperatures. The data in faults are also essential for failure and safety management research. This study developed a battery big data platform to realize vehicle operation, energy interaction and data management. First, we developed an electric vehicle with vehicle navigation and position detection and designed an environmental cabin that allows the vehicle to operate autonomously. Second, charging and heating systems based on wireless energy transfer were developed and equipped on the vehicle to investigate optimal charging and heating methods of the batteries in the vehicle. Third, the data transmission network was designed, a real-time monitoring interface was developed, and the self-developed battery management system was used to measure, collect, upload, and store battery operation data in real time. Finally, experimental validation was performed on the platform. Results demonstrate the efficiency and reliability of the platform. Battery state of charge estimation is used as an example to illustrate the availability of battery operation data.

Abstract Paddy fields are a major emission source of greenhouse gases (GHGs) [for instance, methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)] among agricultural fields. Biochar has been deemed a potential candidate for the reduction of GHGs in paddy fields. However, there is no consistent conclusion that biochar can simultaneously reduce emissions of CH4, N2O, and CO2. Herein, we proposed the FeN3-doped biochar (FG) as an excellent material for GHGs restriction in paddy fields via the first-principles calculation. The computation results indicated that the FG exhibited satisfactory adsorption ability for CH4, CO2, and N2O, which improved the adsorption energies to −1.37 , −1.54, and −2.91 eV, respectively. Moreover, the density of state (DOS) analyses revealed that the factor responsible for FeN3-doped biochar to exhibit excellent adsorption ability was the occurrence of drastic energy up- or down-shift of the electron for Fe d, C p, O p, or N p orbital upon adsorption of CH4, CO2, or N2O. Our study suggested an advanced modified biochar material for reducing the GHGs emissions in paddy fields, in addition to exploring the adsorption properties and mechanisms of FeN3-doped biochar for GHGs mitigation, which provided a strategy to explore biochar modification and efficient emission reduction materials. Graphical Abstract

Abstract Background Abnormal tau accumulation and cholinergic degeneration are hallmark pathologies in the brains of patients with Alzheimer’s disease (AD). However, the sensitivity of cholinergic neurons to AD-like tau accumulation and strategies to ameliorate tau-disrupted spatial memory in terms of neural circuits still remain elusive. Methods To investigate the effect and mechanism of the cholinergic circuit in Alzheimer's disease-related hippocampal memory, overexpression of human wild-type Tau (hTau) in medial septum (MS)-hippocampus (HP) cholinergic was achieved by specifically injecting pAAV-EF1α-DIO-hTau-eGFP virus into the MS of ChAT-Cre mice. Immunostaining, behavioral analysis and optogenetic activation experiments were used to detect the effect of hTau accumulation on cholinergic neurons and the MS-CA1 cholinergic circuit. Patch-clamp recordings and in vivo local field potential recordings were used to analyze the influence of hTau on the electrical signals of cholinergic neurons and the activity of cholinergic neural circuit networks. Optogenetic activation combined with cholinergic receptor blocker was used to detect the role of cholinergic receptors in spatial memory. Results In the present study, we found that cholinergic neurons with an asymmetric discharge characteristic in the MS-hippocampal CA1 pathway are vulnerable to tau accumulation. In addition to an inhibitory effect on neuronal excitability, theta synchronization between the MS and CA1 subsets was significantly disrupted during memory consolidation after overexpressing hTau in the MS. Photoactivating MS-CA1 cholinergic inputs within a critical 3 h time window during memory consolidation efficiently improved tau-induced spatial memory deficits in a theta rhythm-dependent manner. Conclusions Our study not only reveals the vulnerability of a novel MS-CA1 cholinergic circuit to AD-like tau accumulation but also provides a rhythm- and time window-dependent strategy to target the MS-CA1 cholinergic circuit, thereby rescuing tau-induced spatial cognitive functions. Graphical Abstract

AIM:To investigate the efficacy of domestic cyclosporine A(CsA)in dry eye and its effect on sub-basal nerves(SBN)by observing quantitative and morphological changes in corneal SBN of patients with moderate to severe dry eye before and after the treatment with 0.05% CsA eye drops(Ⅱ).METHODS: In this prospective study, a total of 20 patients(20 eyes)with moderate to severe dry eye who admitted to the ophthalmology department of the Affiliated Eye Hospital of Nanchang University from December 2020 to January 2022 were selected. They were treated with domestic CsA and followed up for 3mo. Clinical evaluation was carried out at baseline and at 3mo after treatment. The changes in clinical symptoms, signs and morphology and quantity of SBN were observed.RESULTS: The ocular surface disease index(OSDI)score, the tear break-up time(TBUT), Schirmer Ⅰ, corneal fluorescein staining(CFS)score were significantly improved at 3mo after treatment. Confocal microscopy data analysis showed that SBN density increased from 13.49±5.43 mm/mm2 to 14.93±5.34 mm/mm2(P

Attapulgite-hydroxyethyl cellulose-poly (acrylic acid-co-2-acrylamide-2-methylpropanesulfonic acid) (ATP-HEC-P(AA-co-AMPS)) in-concrete curing material was synthesized by aqueous solution polymerization using attapulgite (ATP) as an inorganic filler and hydroxyethyl cellulose (HEC) as a backbone. The effects of relevant factors such as ATP dosage, HEC dosage, degree of neutralization, initiator quality, and cross-linking agent quality on the water absorption characteristics of ATP-HEC-P (AA-co-AMPS) were investigated through expansion tests. The micro-morphology of ATP-HEC-P (AA-co-AMPS) was also comprehensively characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, a thermal analysis, and other applicable means. The results showed that the prepared ATP-HEC-P (AA-co-AMPS) had a strong water absorption and water retention capacity, with a water absorption multiplicity of 382 g/g in deionized water and 21.55% water retention capacity after being placed at room temperature for 7 d in a bare environment. Additionally, ATP-HEC-P (AA-co-AMPS) showed good performance for absorbing liquids within the pH range of 7–12. The material’s thermal stability and mechanical properties were also significantly improved after the addition of ATP. The preparation cost is low, the process is simple, and the material meets the requirements for concrete curing materials.

The ATP-BF-P(HEC-AA-AMPS) composite highly absorbent polymer was copolymerized with acrylic acid (AA) and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) using an aqueous solution method with attapulgite (ATP) and attapulgite (ATP) as a matrix. The prepared ATP-BF-P(HEC-AA-AMPS) was characterized in terms of microstructure and tested for its water absorption capacity, water retention properties, and pH dynamic sensing ability. The results showed that the synthesized ATP-BF-P(HEC-AA-AMPS) had a rough and porous surface and a high water absorption capacity and rate, almost reaching the maximum water absorption around 20 min, and demonstrated excellent water retention performance at low and medium temperatures. ATP-BF-P(HEC-AA-AMPS) has a sensitive dynamic sensing ability in different pH solutions, with a high swelling capacity between pH 6.0 and 10.0. When the pH value exceeded 10.0, the swelling rate decreased rapidly. Additionally, the thermal stability and mechanical strength of the highly absorbent polymers were significantly improved after blending with ATP and BF.

Thermal conductive coating materials with combination of mechanical robustness, good adhesion and electrical insulation are in high demand in the electronics industry. However, very few progresses have been achieved in constructing a highly thermal conductive composites coating that can conformably coat on desired subjects for efficient thermal dissipation, due to their lack of materials design and structure control. Herein, we report a bioinspired thermal conductive coating material from cellulose nanofibers (CNFs), boron nitride (BN), and polydopamine (PDA) by mimicking the layered structure of nacre. Owing to the strong interfacial strength, mechanical robustness, and high thermal conductivity of CNFs, they do not only enhance the exfoliation and dispersion of BN nanoplates, but also bridge BN nanoplates to achieve superior thermal and mechanical performance. The resulting composites coating exhibits a high thermal conductivity of 13.8 W/(m·K) that surpasses most of the reported thermal conductive composites coating owing to the formation of an efficient thermal conductive pathway in the layered structure. Additionally, the coating material has good interface adhesion to conformably wrap around various substrates by scalable spray coating, combined with good mechanical robustness, sustainability, electrical insulation, low-cost, and easy processability, which makes our materials attractive for electronic packaging applications.

As an important virulence phenotype of Escherichia coli, the regulation mechanism of biofilm by non-coding RNA and quorum sensing system has not been clarified. Here, by transcriptome sequencing and RT-PCR analysis, we found CsrB, a non-coding RNA of the carbon storage regulation system, was positively regulated by the LuxR protein SdiA. Furthermore, β-galactosidase reporter assays showed that SdiA enhanced promoter transcriptional activity of csrB. The consistent dynamic expression levels of SdiA and CsrB during Escherichia coli growth were also detected. Moreover, curli assays and biofilm assays showed sdiA deficiency in Escherichia coli SM10λπ or BW25113 led to a decreased formation of biofilm, and was significantly restored by over-expression of CsrB. Interestingly, the regulations of SdiA on CsrB in biofilm formation were enhanced by quorum sensing signal molecules AHLs. In conclusion, SdiA plays a crucial role in Escherichia coli biofilm formation by regulating the expression of non-coding RNA CsrB. Our study provides new insights into SdiA-non-coding RNA regulatory network involved in Escherichia coli biofilm formation.

Drip irrigation is deemed as a solution to the water conflict between agricultural and ecological needs in arid regions, but assessing hydrological impacts of drip irrigation remains challenging. This study developed a new approach to simulating drip irrigation at a basin scale, with the configuration of irrigation system explicitly represented and the emitter-scale wetted soil volume directly modeled, and incorporated the approach into HEIFLOW, a fully distributed and physically based ecohydrological model. The improved model, named HEIFLOW-drip, was used to study the potential implementation of drip irrigation in the Zhangye basin in Northwest China. Due to the recycling effect of irrigation return flow, the basin-scale water-saving efficiency (WSE) of drip irrigation fully implemented in the irrigated farmlands is 16.8%, less than half of its field-scale WSE (36.5%). This discrepancy indicates that accounting the water saved in fields may lead to notable overestimation of the basin-wide water saving by drip irrigation in basins with strong surface water-groundwater interactions. If fully implemented, drip irrigation would significantly alter the regional water balance, increasing the stream outflow by approximately 30%, while causing a decline in groundwater level. This tradeoff can be alleviated by tuning the management parameters of drip irrigation, which can achieve a synergistic effect of increasing the streamflow while preventing dramatic groundwater depletion. Another effective strategy is to implement drip irrigation in part of the basin. Given the intricate impacts of drip irrigation on hydrological processes, the determination of the scale and location of drip irrigation should be thought through at the basin level. Further analyses indicate the importance of proper management of the water saved by drip irrigation, which is crucial to prevent the paradox of irrigation efficiency. The findings of this study have great implications for addressing the complex water-food-ecosystem nexus in arid endorheic river basins.

BackgroundThe prognosis of hepatocellular carcinoma combined with portal vein tumor thrombus is poor, with a median survival of only 3-6 months. PD-1 combined with targeted therapy may provide an opportunity for patients with BCLC C stage hepatocellular carcinoma combined with portal vein tumor thrombus to undergo radical surgery, significantly prolonging their survival time.Case presentationA middle-aged 51-year-old male who was diagnosed with hepatocellular carcinoma combined with portal vein main stem tumor thrombus at our center in May 2020, with a BCLC stage of C, liver cirrhosis, HBV infection, and preoperative evaluation as unresectable. The liver function was Child-Pugh A. The initial treatment was lenvatinib combined with PD-1 therapy, followed by one cycle of TACE treatment. The tumor and thrombus volume significantly reduced, followed by continuous TACE combined with immunotherapy and targeted therapy, leading to the appearance of portal vein main stem emboli. After multidisciplinary discussion, surgical resection was performed, and the embolus was removed, achieving a cure. The patient has been tumor-free for over 34 months.ConclusionPD-1 combined with lenvatinib and local TACE create conditions for radical surgery, and it is hoped that more real-world research data can provide better evidence for the transformational treatment of hepatocellular carcinoma combined with portal vein tumor thrombus.

Objective: To investigate and analyze the post-marketing adverse event (AE) data of multiple sclerosis (MS) therapeutic drug dalfampridine using the US Food and Drug Administration Adverse Event Reporting System (FAERS) for its clinical safety application.Methods: Use OpenVigil2.1 platform to obtain AE data of dalfampridine from FAERS from February 2010 to September 2022. Match “adverse drug reaction” with preferred term (PT) and system organ class (SOC) according to the Medical Dictionary for Regulatory Activities (MedDRA), then merge the same PT and delete non-AE PT. Positive signals were identified by the reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) methods. When AE signals met the criteria of those three methods, they were identified as positive signals.Results: A total of 44,092 dalfampridine-related AE reports were obtained, and 335 AE signals were identified, including 11,889 AE reports. AEs were more common in females and in the 45–65 age group, which is consistent with the epidemiological characteristics of MS. The 335 AE signals involved 21 SOCs, including investigations, infections and infestations, eye disorders, etc. Among the top 20 PTs in signal strength, 10 were associated with abnormal lymphocyte percentage and count, and 5 were associated with abnormal urine tests, some of which were not described in the instruction, such as spinal cord injury cauda equina, haemoglobin urine present, urinary sediment abnormal and so on. The most frequently reported AE signals were urinary tract infection, dizziness, condition aggravated. In addition, 23 AE signals with death outcomes were identified, with an incidence of less than 0.1%.Conclusion: Data mining of FAERS was conducted to analyze the AEs of dalfampridine, and new AE signals were found. This study provides a reference for the safe use of dalfampridine in the treatment of MS.

Lithium-ion batteries have become the best choice for battery energy storage systems and electric vehicles due to their excellent electrical performances and important contributions to achieving the carbon-neutral goal. With the large-scale application, safety accidents are increasingly caused by lithium-ion batteries. As the core component for battery energy storage systems and electric vehicles, lithium-ion batteries account for about 60% of vehicular failures and have the characteristics of the rapid spread of failure, short escape time, and easy initiation of fires, so the safety improvement of lithium-ion batteries is urgent. This study analyses the causes and mechanisms of lithium-ion batteries failures from design, production, and application, investigates its failure features and warning algorithms for thermal runaway, and the concept of long-medium-short graded warning is proposed based on the battery failure mechanism and its evolution to provide a basis for failure warning. As lithium-ion batteries fires are difficult to completely avoid, the characteristics of lithium-ion batteries fires are explored to improve battery structure and develop fire extinguishing agents and methods for fire prevention and suppression. Improving the safety of batteries is a systematic project, and at a time when there has been no breakthrough in the chemical system, improvements, such as build a practical graded warning system, are needed in all aspects of design, production, use and disposal to improve battery safety and minimize the risk of failure.

Abstract The production of traditional Peking opera facial masks often relies on hand painting by experienced painters, which restricts the inheritance and development of this intangible cultural heritage. Current research mainly focuses on the digital reconstruction and storage of existing Peking opera facial masks, while high-quality facial mask generation technology is still in an infancy stage. In this paper, different deep learning frameworks are improved for learning features of Peking opera facial masks and generating new masks, which can effectively promote the creative application of Peking opera facial masks. First, using different data enhancement methods, an improved Style Generative Adversarial Network-2 (StyleGAN2) can learn implicit and explicit features of Peking opera facial masks and automatically generate new facial masks. In addition, an image translation framework for joint cross-domain communication under weak supervision is used to translate face sketches and color reference maps to an intermediate feature domain, and then synthesize new facial masks through an image generation network. The experimental results show that the generated Peking opera facial masks have good local randomness and excellent visual quality.

Highlights Covalent organic framework (COF) superlattices were assembled by free-standing COF nanofilms based on the van der Waals force for the first time. Geometry-induced “nano-hourglass” steric configuration in COF superlattice can provide rapid charge transfer/accumulation at heterojunction interface for in-Plane Micro-supercapacitors. The prepared MSC exhibited a high energy density of 63.2 mWh cm−3 even after high-angle and repeat arbitrary bending from 0 to 180°.

Naturally derived biopolymers attracted great interest to construct photonic materials but traditional processing commonly results in non-uniform organization across largescale areas. Here, the authors report a uniform biophotonic organization of cellulose nanocrystals decorated with superparamagnetic nanoparticles enabling transformation from helicoidal cholesteric to uniaxial nematic phase with near-perfect orientation.

The neural mechanisms for reward generalization are not fully understood. Here the authors investigate the role of posterior basolateral amygdala calbindin-expressing cells in modulating behavioural responses related to reward and aversion.

BackgroundChinese people experienced a nationwide coronavirus disease 2019 (COVID-19) pandemic after the adjustment of epidemic response policies from December 2022 to January 2023. This study aims to explore the prevalence of mental and cognitive symptoms and their associated factors among medical students after the COVID-19 pandemic.MethodsA cross-sectional study was conducted between February 27th and March 8th, 2023. The symptoms of anxiety, depression, insomnia, post-traumatic stress disorder (PTSD), and cognitive function among medical students were examined using the Generalized Anxiety Disorder-7 (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), the Athens Insomnia Scale (AIS), the Impact of Event Scale-6 (IES-6), and the Perceived Deficits Questionnaire-Depression-5 (PDQ-D-5). Data on demographic information was also collected. Statistical analyses were conducted to describe the prevalence and explore the associated factors of mental and cognitive symptoms.ResultsAmong 947 participants, the proportion of students experiencing anxiety, depression, insomnia, and PTSD symptoms was 37.8, 39.3, 28.3, and 29.5%, respectively. The self-reported COVID-19 infection rate was 72.2%. Higher grades, childhood, and current rural residence were identified as potential risk factors for mental and cognitive symptoms. Gender, age, average monthly household income, and COVID-19 diagnosis were not associated with mental and cognitive symptoms among medical students.ConclusionOur findings revealed a high prevalence of mental and cognitive symptoms among Chinese medical students after the COVID-19 pandemic. Special attention should be paid to the mental health of higher-grade students and those residing in rural areas.

Summary: Activated inflammation and pyroptosis in macrophage are closely associated with acute lung injury (ALI). Histone deacetylase 3 (HDAC3) serves as an important enzyme that could repress gene expression by mediating chromatin remodeling. In this study, we found that HDAC3 was highly expressed in lung tissues of lipopolysaccharide (LPS)-treated mice. Lung tissues from macrophage HDAC3-deficient mice stimulated with LPS showed alleviative lung pathological injury and inflammatory response. HDAC3 silencing significantly blocked the activation of cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway in LPS-induced macrophage. LPS could recruit HDAC3 and H3K9Ac to the miR-4767 gene promoter, which repressed the expression of miR-4767 to promote the expression of cGAS. Taken together, our findings demonstrated that HDAC3 played a pivotal role in mediating pyroptosis in macrophage and ALI by activating cGAS/STING pathway through its histone deacetylation function. Targeting HDAC3 in macrophage may provide a new therapeutic target for the prevention of LPS-induced ALI.

Sepsis is one common cause of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), which is closely associated with high mortality in intensive care units (ICU). Histone deacetylase 3 (HDAC3) serves as an important epigenetic modifying enzyme which could affect chromatin structure and transcriptional regulation. Here, we explored the effects of HDAC3 in type II alveolar epithelial cells (AT2) on lipopolysaccharide (LPS)-induced ALI and shed light on potential molecular mechanisms. We generated ALI mouse model with HDAC3 conditional knockout mice (Sftpc-cre; Hdac3f/f) in AT2 and the roles of HDAC3 in ALI and epithelial barrier integrity were investigated in LPS-treated AT2. The levels of HDAC3 were significantly upregulated in lung tissues from mice with sepsis and in LPS-treated AT2. HDAC3 deficiency in AT2 not only decreased inflammation, apoptosis, and oxidative stress, but also maintained epithelial barrier integrity. Meanwhile, HDAC3 deficiency in LPS-treated AT2 preserved mitochondrial quality control (MQC), evidenced by the shift of mitochondria from fission into fusion, decreased mitophagy, and improved fatty acid oxidation (FAO). Mechanically, HDAC3 promoted the transcription of Rho-associated protein kinase 1 (ROCK1) in AT2. In the context of LPS stimulation, the upregulated ROCK1 elicited by HDAC3 could be phosphorylated by Rho-associated (RhoA), thus disturbing MQC and triggering ALI. Furthermore, we found that forkhead box O1 (FOXO1) was one of transcription factors of ROCK1. HDAC3 directly decreased the acetylation of FOXO1 and promoted its nuclear translocation in LPS-treated AT2. Finally, HDAC3 inhibitor RGFP966 alleviated epithelial damage and improved MQC in LPS-treated AT2. Altogether, HDAC3 deficiency in AT2 alleviated sepsis-induced ALI by preserving mitochondrial quality control via FOXO1-ROCK1 axis, which provided a potential strategy for the treatment of sepsis and ALI.

In the above article [1], the authors want to update the definition of fresh water provided in Sections II and VI based on discussions with the IEC.

Abstract Background The blue-crowned laughingthrush (Garrulax courtoisi) is a critically endangered songbird endemic to Wuyuan, China, with population of ~323 individuals. It has attracted widespread attention, but the lack of a published genome has limited research and species protection. Results We report two laughingthrush genome assemblies and reveal the taxonomic status of laughingthrush species among 25 common avian species according to the comparative genomic analysis. The blue-crowned laughingthrush, black-throated laughingthrush, masked laughingthrush, white-browed laughingthrush, and rusty laughingthrush showed a close genetic relationship, and they diverged from a common ancestor between ~2.81 and 12.31 million years ago estimated by the population structure and divergence analysis using 66 whole-genome sequencing birds from eight laughingthrush species and one out group (Cyanopica cyanus). Population inference revealed that the laughingthrush species experienced a rapid population decline during the last ice age and a serious bottleneck caused by a cold wave during the Chinese Song Dynasty (960–1279 AD). The blue-crowned laughingthrush is still in a bottleneck, which may be the result of a cold wave together with human exploitation. Interestingly, the existing blue-crowned laughingthrush exhibits extremely rich genetic diversity compared to other laughingthrushes. These genetic characteristics and demographic inference patterns suggest a genetic heritage of population abundance in the blue-crowned laughingthrush. The results also suggest that fewer deleterious mutations in the blue-crowned laughingthrush genomes have allowed them to thrive even with a small population size. We believe that cooperative breeding behavior and a long reproduction period may enable the blue-crowned laughingthrush to maintain genetic diversity and avoid inbreeding depression. We identified 43 short tandem repeats that can be used as markers to identify the sex of the blue-crowned laughingthrush and aid in its genetic conservation. Conclusions This study supplies the missing reference genome of laughingthrush, provides insight into the genetic variability, evolutionary potential, and molecular ecology of laughingthrush and provides a genomic resource for future research and conservation.

Abstract Tropical cyclone (TC) stalling has been widely perceived to yield a greater threat of flooding. Understanding the effect of stalling and its long‐term trends will enhance adaptation strategies to cyclone‐associated disasters. We show that stalling prolongs western North Pacific TCs to live 24 hr longer and produces 23% greater 24‐hr rainfall accumulations in a more concentrated area, which is more prominent over a 72‐hr rolling period. More importantly, we discover a northward migration of TC stalling (∼0.7°N decade−1) over 1979–2020, bringing increasingly higher flood risks to the highly‐populated East Asian coast. Further diagnoses suggest the role of binary cyclone interactions in TC stalling, whereby the second larger TC slows down the smaller one by weakening the northwestward steering flows. The northward shift of TC stalling can be explained by a similar trend in binary TC cases and environmental fields. Our findings are robust across various best track and precipitation products.