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The proliferation of social media has transformed the fulfillment of corporate social responsibility (CSR) from traditional offline activities to emerging online methods, ushering in the era of Virtual CSR activities. This study focuses on the crucial issue of enhancing consumer engagement in Virtual CSR initiatives. Drawing upon the Theory of Planned Behavior and Perceived Risk Theory, this study empirically analyzes the factors influencing consumers’ willingness and behavior to participate in Virtual CSR activities through questionnaire surveys. Our findings reveal that behavioral attitudes, perceived behavioral control, and external scenarios positively impact consumer willingness to participate, which in turn significantly promotes participation behavior. Furthermore, willingness to participate serves as a mediator between these factors and actual participation behavior. Based on these insights, we propose practical recommendations for enterprises to optimize their Virtual CSR strategies.

This study aimed to understand green finance’s impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root and cointegration test), the latest causal test, impulse response, and variance decomposition analysis. Examined the long-term equilibrium relationship between green finance, fertilizer use, and agricultural carbon emissions. The results show: fertilizer consumption and agricultural carbon emissions have a positive correlation. However, green finance can significantly reduce agricultural carbon emissions. The causal test confirmed the bidirectional causal relationship between agricultural carbon emissions and fertilizer use. At the same time, verified one-way causality from green finance to both of them. Interpret the results of impulse response and variance decomposition analysis: among the changes in agricultural carbon emissions, chemical fertilizers contributed 2.45%, green finance contributed 4.34%. In addition, the contribution rate of green finance to chemical fertilizer changes reached 11.37%. Green finance will make a huge contribution to reducing fertilizer use and agricultural carbon emissions within a decade. The research conclusions provide an important scientific basis for China’s provinces (cities) to formulate carbon emission reduction policies. China has initially formed a policy system and market environment to support the development of green finance, in 2020, the “dual carbon” goal was formally proposed. In 2021, the national “14th Five-Year Plan” and the 2035 Vision Goals emphasized the importance of green finance. It plays an important supporting role in carbon emission reduction goals, and green finance has become an important pillar of national strategic goals.

Emerging evidence suggests that astrocyte loss is one of the most important pathological features in the hippocampus of patients with major depressive disorder (MDD) and depressive mice. Pyroptosis is a recently discovered form of programmed cell death depending on Caspase–gasdermin D (Casp-GSDMD), which is involved in multiple neuropsychiatric diseases. However, the involvement of pyroptosis in the onset of MDD and glial pathological injury remains obscure. Here, we observed that depressive mice showed astrocytic pyroptosis, which was responsible for astrocyte loss, and selective serotonin reuptake inhibitor (SSRI) treatment could attenuate the pyroptosis induced by the chronic mild stress (CMS) model. Genetic KO of GSDMD, Casp-1, and astrocytic NOD-like receptor protein 3 (NLRP3) inflammasome in mice alleviated depression-like behaviors and inhibited the pyroptosis-associated protein expression. In contrast, overexpression of astrocytic GSDMD–N-terminal domain (GSDMD-N) in the hippocampus could abolish the improvement of behavioral alterations in GSDMD-deficient mice. This work illustrates that targeting the NLRP3/Casp-1/GSDMD–mediated pyroptosis may provide potential therapeutic benefits to stress-related astrocyte loss in the pathogenesis of depression.

Background Household solid fuel use is associated with a higher risk of a wide spectrum of health disorders. However, the sex-specific relationship between solid fuel use and incident stroke in older Chinese adults, as well as the potential mediating role of depressive symptoms, remains insufficiently explored. Methods This longitudinal study used data from the China Health and Retirement Longitudinal Study (CHARLS), including 13,928 Chinese participants aged 45 years or older who were free of stroke at baseline. Logistic regression models were used to assess the relationship between solid fuel use, depressive symptoms, and the risk of incident stroke. Mediation analyses were performed to quantify the potential mediation role of depressive symptoms in the association. All analyses were stratified by sex to assess sex-specific susceptibility. Results Of the 13,928 adults (mean age of 58, 47.26% male), 917 (6.58%) participants documented the incident stroke. Solid fuel use was significantly associated with a higher risk of incident stroke in the total population (OR = 1.26, 95% CI: 1.06–1.49) and female populations (OR = 1.39, 95% 1.09–1.77) in the fully adjusted model. In addition, depressive symptoms may partially mediate up to15.7% of the association between solid fuel use and incident stroke, and this finding was consistent whether depressive symptoms were defined as general depression or severe depression. The results of the stratified analysis also indicate that this mediating effect is present only among the female group. Conclusion Household solid fuel use was significantly associated with a higher risk of incident stroke, and depressive symptoms played a mediating role in the relationship. These findings highlight the need for integrated public health interventions in the areas of environmental pollution and mental health, with particular attention to women.

To address the lack of physical interpretability and weak model generalization in purely data-driven methods for estimating the State of Health (SOH) of LIBs, this study proposes a lithium battery SOH estimation method based on Differential Temperature- Voltammetry (DTV) characteristics and Particle Swarm Optimization-Gated Recurrent Unit (PSO-GRU). To capture thermodynamic characteristics during battery aging, First, this paper computes DTV curves based on thermo-electrical coupling responses during charge-discharge cycles and extracts a 6-dimensional physical feature vector to quantify Multiphysics evolution patterns in battery aging. Second, a PSO-GRU prediction model is established, employing the particle swarm optimization (PSO) algorithm to adaptively optimize the hyperparameters of the gated recurrent unit (GRU). Additionally, to address the issue of significant data fluctuations in the early stages of battery aging that interfere with long-term trend prediction, a training set optimization method based on aging stage segmentation is proposed. Simulation experiments demonstrate that this method achieves significantly higher SOH estimation accuracy on the NASA battery dataset compared to standard GRU and long short-term memory (LSTM) models. After applying the optimization strategy, the model’s mean absolute error (MAE) on the test set decreased from 1.45% to 0.75%, and the root mean square error (RMSE) decreased from 1.86% to 0.97%, demonstrating enhanced generalization capability and robustness. The experimental results validate the necessity of excluding non-stationary data from the formation period for constructing high-accuracy, long-term prediction models, providing new insights for the engineering application of data-driven methods.

Soil texture is one of the important physical and natural properties of soil. Much of the current research focuses on soil texture monitoring using non-imaging geophysical spectrometers. However there are fewer studies utilizing unmanned aerial vehicle (UAV) hyperspectral data for soil texture monitoring. UAV mounted hyperspectral cameras can be used for quickly and accurately obtaining high-resolution spatial information of soil texture. A foundation has been laid for the realization of rapid soil texture surveys using unmanned airborne hyperspectral data without field sampling. This study selected three typical farmland areas in Huangshui Basin of Qinghai as the study area, and a total of 296 soil samples were collected. Data calibration of UAV spectra using laboratory spectra and field in situ spectra to explore the feasibility of applying laboratory soil texture models directly to field conditions. This results show that UAV hyperspectral imagery combined with machine learning can obtain a set of ideal processing methods. The pre-processing of the spectral data can obtain high accuracy of soil texture estimation and good mapping effect. The results of this study can provide effective technical support and decision-making assistance for future agricultural land planning on the Tibetan Plateau. The main innovation of this study is to establish a set of processing procedures and methods applicable to UAV hyperspectral imagery to provide data reference for monitoring soil texture in agricultural fields on the Tibetan Plateau.

Understanding the health literacy status of patients with gout diagnosis is essential for improving the health of this population. Our study aimed to investigate the latent profiles of health literacy in patients with gout and to analyze differences in characteristics across potential profiles. This was a cross-sectional study. Eligible participants attended the Shandong Gout Medical Center, from March 2023 to May 2023 and self-reported gout diagnosis. We used the Health Literacy Scale for Patients with Gout designed and validated by our team. The scale had good reliability and validity among patients with gout. 243 patients completed the Demographic Information Questionnaire and the Health Literacy Scale for Patients with Gout. We used latent profile analysis to identify the latent profiles of gout patients' health literacy. We used Chi-square tests with Bonferroni correction to analyze differences in demographics and illness characteristics across identified profiles. Three profiles of patients with gout emerged (prevalence): the low literacy-low critical group (21.81%), the moderate literacy group (42.79%), and the high literacy-stable group (35.39%). The three groups differed in age, education level, monthly income, disease duration, and place of residence (P<0.01). The health literacy of patients with gout was heterogeneous. Healthcare professionals should adopt targeted interventions based on the characteristics of each latent health literacy profile to improve the health literacy level of patients with gout.

Background Accurate diagnosis of adrenal incidentalomas is crucial in patients with extra-adrenal malignant tumors. This study aims to develop a nomogram integrating clinical features, deep learning-derived imaging features, and ultrasound radiomics characteristics to distinguish adrenal metastases from adrenal adenomas. Methods A retrospective analysis was conducted on 449 cases, including 228 cases of adrenal metastases and 221 cases of adrenal adenomas, divided into training and testing cohorts at a 7:3 ratio. Patient clinical data and ultrasonographic images were collected, with regions of interest (ROIs) delineated on ultrasound images. Feature extraction, selection, and radiomics model (Rad) construction were performed, followed by model evaluation. Multiple deep learning models were employed to identify the optimal architecture for deep feature extraction. These deep features were combined with radiomics features to establish a deep learning radiomics model (DLR) for the differentiation between adrenal metastases and adenomas. Results The study demonstrates that the Rad, DLR, and combined models exhibit superior diagnostic performance in differentiating adrenal metastases from adrenal adenomas. In the testing cohort, the combined model outperforms the Rad and DLR models. The area under the curve (AUC) in the testing set for Rad, DLR, and combined models were 0.839, 0.839, and 0.850, respectively. Conclusion The nomogram integrating clinical features, deep learning features, and ultrasound radiomics features demonstrates robust performance in differentiating adrenal metastases from adrenal adenomas and can assist in preliminary diagnostic stratification of indeterminate adrenal nodules in patients with extrarenal tumors.

Background Population aging is the predominant global demographic trend of the contemporary era. However, the mental health of many older adults is not as good as it could be. Ensuring the rights and well-being of older adults is crucial for achieving sustainable and healthy aging. Numerous countries have implemented healthcare integration services tailored to their unique contexts. In 2016, China initiated community health care services for older adults. Methods We used panel data derived from the China Health and Retirement Longitudinal Study from 2015 to 2018 and analyses were performed using STATA, version 17. Our study employed a difference-in-differences model to assess the association of community health care services with mental health of older adults and conducted a placebo test to assess the reliability of the difference-in-differences model estimations. Additionally, subgroup regression analyses were conducted to investigate whether community health care services exert differing effects on the mental well-being of older adults across subgroups by sex, age groups, and education level. Results Community health care services significantly improved depression levels and cognitive function in older adults. Notably, these services exerted a more pronounced effect on alleviating depression symptoms among male older adults and more positively affected cognitive function among female older adults. Additionally, the services demonstrated greater effectiveness in improving both depression levels and cognitive function among older adults with lower educational attainment, while maintaining positive impacts on younger older adults. Conclusions Community health care services played a crucial role in enhancing the mental health of older adults, with varying degrees of impact across demographic groups. Our study underscores the importance of such services in promoting healthy aging and provides a foundation for the further development of hierarchical community health care services. This development is conducive to advancing community health care services, enhancing the mental well-being, and fostering healthy aging for Chinese older adults.

Alpha-fetoprotein (AFP)-secreting hepatocellular carcinoma (HCC), which accounts for ~75% of HCCs, is more aggressive with a worse prognosis than those without AFP production. The mechanism through which the interaction between tumors and the microenvironment leads to distinct phenotypes is not yet clear. Therefore, our study aims to identify the characteristic features and potential treatment targets of AFP-negative HCC (ANHC) and AFP-positive HCC (APHC). We utilized single-cell RNA sequencing to analyze 6 ANHC, 6 APHC, and 4 adjacent normal tissues. Integrated multi-omics analysis together with survival analysis were also performed. Further validation was conducted via cytometry time-of-flight on 30 HCCs and multiplex immunohistochemistry on additional 59 HCCs. Our data showed that the genes related to antigen processing and interferon-γ response were abundant in tumor cells of APHC. Meanwhile, APHC was associated with multifaceted immune distortion, including exhaustion of diverse T cell subpopulations, and the accumulation of tumor-associated macrophages (TAMs). Notably, TAM-SPP1 + was highly enriched in APHC, as was its receptor CD44 on T cells and tumor cells. Targeting the Spp1-Cd44 axis restored T cell function in vitro and significantly reduced tumor burden when treated with either anti-Spp1 or anti-Cd44 antibody alone or in combination with anti-Pd-1 antibody in the mouse model. Furthermore, elevated IL6 and TGF-β1 signaling contributed to the enrichment of TAM-SPP1 + in APHC. In conclusion, this study uncovered a highly suppressive microenvironment in APHC and highlighted the role of TAM-SPP1 + in regulating the immune microenvironment, thereby revealing the SPP1-CD44 axis as a promising target for achieving a more favorable immune response in APHC treatment.