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Abstract While previous observational studies have suggested a link between leukocyte counts and vascular dementia (VD), the causal relationship between leukocyte counts and various subtypes of VD remains elusive. This study aimed to investigate the causal relationship between five types of leukocyte counts and VD, with the goal of improving prevention and treatment strategies. In this study, leukocyte counts were used as the exposure variable, with genome-wide association study (GWAS) data sourced from both the UK Biobank and the Blood Cell Consortium. Additionally, GWAS data for five subtypes of vascular dementia were obtained from the FinnGen database. We conducted rigorous statistical analysis and visualization using Mendelian randomization (MR) to elucidate the potential causal relationship between leukocyte counts and vascular dementia. This study, utilizing MR analysis with data from the UK Biobank and Blood Cell Consortium, identified significant causal associations between increased lymphocyte counts and VD. Specifically, lymphocyte counts were found to be causally related to multiple and mixed VD subtypes. Sensitivity analyses, including MR-Egger regression and MR-PRESSO tests, confirmed the robustness of these findings, with no evidence of reverse causality or significant horizontal pleiotropy detected. The results underscore a potential inflammatory or immunological mechanism in the pathogenesis of VD, highlighting lymphocytes as a key component in their etiology. This investigation establishes a robust association between elevated lymphocyte and leukocyte counts and an increased risk of VD, emphasizing the roles of inflammation, immune activation, and hematological factors in disease pathogenesis.

Abstract Despite substantial breakthroughs in the treatment of hepatocellular carcinoma (HCC) in recent years, many patients are diagnosed in the middle or late stages, denying them the option for surgical excision. Therefore, it is of great importance to find effective therapeutic targets of HCC. In this study, it is found that Gap junction protein beta‐2 (GJB2) is highly enriched in malignant cells based on single‐cell RNA sequencing and higher expression of GJB2 indicates a worse prognosis. The localization of GJB2 in HCC cancer cells is changed compared with normal liver tissue. In cancer cells, GJB2 tends to be located in the cytoplasm and nucleus, while in normal tissues, GJB2 is mainly located on the cell membrane. GJB2 is related to glycolysis, promoting NF‐κB pathway via inducing the ubiquitination degradation of IκBa, and activating HIF‐1α/GLUT‐1/PD‐L1 pathway. In addition, GJB2 knockdown reshapes tumor immune microenvironment and Salvianolic acid B inhibits the activity of GJB2. In conclusion, GJB2 promotes HCC progression by activating glycolysis through cytoplasmic translocation and generating a suppressive tumor microenvironment. Salvianolic acid B inhibits the expression of GJB2 and enhances the sensitivity of anti‐PD1 therapy, which may provide insights into the development of novel combination therapeutic strategies for HCC.

Abstract Background IPF is a complex lung disease whose aetiology is not fully understood, but diet may have an impact on its development and progression. Therefore, we investigated the potential causal connection between dietary intake and IPF through TSMR to offer insights for early disease prevention recommendations. Methods The study incorporated 29 dietary exposure factors, oily fish intake, bacon intake, processed meat intake, poultry intake, beef intake, pork intake, lamb/mutton intake, non-oily fish intake, fresh fruit intake, cooked vegetable intake, baked bean intake, fresh tomato intake, tinned tomato intake, salad/raw vegetable intake, Fresh fruit intake, coffee intake, tea intake, water intake, red wine intake, average weekly beer plus cider intake, alcoholic drinks per week, cereal intake, bread intake, whole-wheat intake, whole-wheat cereal intake, cheese intake, yogurt intake, salt added to food and whole egg intake. The study explored the causal link between diet and IPF using TSMR analysis, predominantly the IVW method, and performed sensitivity analyses to validate the results. Result The study revealed that consuming oily fish, yogurt, and dried fruits had a protective effect against IPF, whereas the consumption of alcoholic beverages and beef was linked to an increased risk of IPF. Conclusion In this MR study, it was discovered that the consumption of oily fish, yogurt, and dried fruits exhibited a protective effect against IPF, whereas the intake of alcoholic beverages and beef was associated with an elevated risk of IPF. These findings underscore the significance of making informed and timely dietary decisions in IPF prevention.

Mining-induced subsidence poses a serious hazard to the surrounding environment and infrastructure, necessitating the detection of such subsidence for effective disaster mitigation and the safeguarding of local residents. Fucheng 1 is the first high-resolution mini-satellite interferometric Synthetic Aperture Radar (SAR) launched by China in June 2023. In this study, we used Fucheng 1 SAR images to analyze mining-induced subsidence in Karamay by InSAR Stacking and D-InSAR. The findings were compared with Sentinel-1A imagery to evaluate the effectiveness of Fucheng 1 in monitoring subsidence and its interferometric performance. Analysis revealed significant mining-induced subsidence in Karamay, and the results from Fucheng 1 closely corresponded with those from Sentinel-1A, particularly regarding the extent of the subsidence. It is indicated that the precision of Fucheng 1 SAR imagery has reached leading standards. In addition, due to its higher resolution, the maximum detectable deformation gradient (MDDG) of Fucheng 1 is 2.15 times higher than that of Sentinel images. This study provides data support for the monitoring of mining-induced subsidence in the Karamay and give a theoretical basis for the application of Fucheng 1 in the field of Geohazard monitoring.

Diffusion models are a kind of math-based model that were first applied to image generation. Recently, they have drawn wide interest in natural language generation (NLG), a sub-field of natural language processing (NLP), due to their capability to generate varied and high-quality text outputs. In this article, we conduct a comprehensive survey on the application of diffusion models in text generation. We divide text generation into three parts (conditional, unconstrained, and multi-mode text generation, respectively) and provide a detailed introduction. In addition, considering that autoregressive-based pre-training models (PLMs) have recently dominated text generation, we conduct a detailed comparison between diffusion models and PLMs in multiple dimensions, highlighting their respective advantages and limitations. We believe that integrating PLMs into diffusion is a valuable research avenue. We also discuss current challenges faced by diffusion models in text generation and propose potential future research directions, such as improving sampling speed to address scalability issues and exploring multi-modal text generation. By providing a comprehensive analysis and outlook, this survey will serve as a valuable reference for researchers and practitioners interested in utilizing diffusion models for text generation tasks.

Tomato yellow leaf curl virus (TYLCV) is a prominent viral pathogen that adversely affects tomato plants. Effective strategies for mitigating the impact of TYLCV include isolating tomato plants from the whitefly, which is the vector of the virus, and utilizing transgenic lines that are resistant to the virus. In our preliminary investigations, we observed that the use of growth retardants increased the rate of TYLCV infection and intensified the damage to the tomato plants, suggesting a potential involvement of gibberellic acid (GA) in the conferring of resistance to TYLCV. In this study, we employed an infectious clone of TYLCV to inoculate tomato plants, which resulted in leaf curling and growth inhibition. Remarkably, this inoculation also led to the accumulation of GA3 and several other phytohormones. Subsequent treatment with GA3 effectively alleviated the TYLCV-induced leaf curling and growth inhibition, reduced TYLCV abundance in the leaves, enhanced the activity of antioxidant enzymes, and lowered the reactive oxygen species (ROS) levels in the leaves. Conversely, the treatment with PP333 exacerbated TYLCV-induced leaf curling and growth suppression, increased TYLCV abundance, decreased antioxidant enzyme activity, and elevated ROS levels in the leaves. The analysis of the gene expression profiles revealed that GA3 up-regulated the genes associated with disease resistance, such as WRKYs, NACs, MYBs, Cyt P450s, and ERFs, while it down-regulated the DELLA protein, a key agent in GA signaling. In contrast, PP333 induced gene expression changes that were the opposite of those caused by the GA3 treatment. These findings suggest that GA plays an essential role in the tomato’s defense response against TYLCV and acts as a positive regulator of ROS scavenging and the expression of resistance-related genes.

Hainan province which located in the southernmost part of China is an important special economic zone and experimental zone of free trade.However， the studies of underlying surface impact on weather prediction in Hainan is fewer than other places.To understand the impact of underlying surface on numerical weather prediction， the WRF （Weather Research and Forecasting） model is used to simulate the meteorological field over Hainan in 2013.The comparison between default land surface data （land use， vegetation fraction， terrain， and soil type） and new high-resolution land surface data， i.e.Moderate Resolution Imaging Spectroradiometer （MODIS） land use data in 2013 processed based on IGBP （International geosphere biosphere program） classification standard， vegetation fraction data calculated based on MODIS normalized difference vegetation index （NDVI） in 2013， Shuttle Radar Topography Mission 3 （SRTM3） terrain data and Harmonized World Soil Database （HWSD） soil type data is investigated through numerical sensitivity tests to analyze the impact on meteorological field simulations.The study is divided into four parts.The first part is the introduction； The second part mainly introduces the research area， data sources， model design and evaluation methods； The third part compares the simulation results of using new high-resolution land surface data with the WRF default land surface data and evaluates the simulation results； Then the fourth part is about the result and discussion.The result indicates that using default or new high-resolution land surface data can both simulate the temporal-spatial distribution of regional meteorological fields.Using the new high-resolution land surface data can improve the simulated results of 2 m temperature and 2 m relative humidity， with the Root Mean Square Error （RMSE） reduced by 7.2% （6.5%） and 6.1%（7.7%） in spring （summer）， and the Hit Rate （HR） increased by 3.7%（2.8%） and 3.2%（2.9%） in spring （summer）.The impact of high-resolution land surface on 10 m wind speed simulation seems smaller than that on 2 m temperature and 2 m relative humidity.10 m wind speed error reduces slightly after using high-resolution land surface data， with the RMSE reduced by 3.8%（4.5%） and HR increased by 2.1%（2.9%） in spring （summer）.Compared to other underlying surface data， land use data has more significant impact on near-surface meteorological fields simulation.In general， using the high-resolution land surface data in Hainan can improve the accuracy of WRF model and reduce the simulation error.This study can deepen the understanding of numerical forecast products for forecasters， improve the accuracy of weather forecast， and provide theoretical basis for Seismic Prevention and Disaster Mitigation.

Abstract Background Tanshinone I (TI) is a primary component of Salvia miltiorrhiza Bunge (Danshen), which confers a favorable role in a variety of pharmacological activities including cardiovascular protection. However, the exact mechanism of the cardiovascular protection activity of TI remains to be illustrated. In this study, the cardiovascular protective effect and its mechanism of TI were investigated. Methods In this study, tert-butyl hydroperoxide (t-BHP)-stimulated H9c2 cells model was employed to investigate the protective effect in vitro. The cell viability was determined by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT) assay and lactate dehydrogenase (LDH) kit. The reactive-oxygen-species (ROS) level and mitochondrial membrane potential (MMP) were investigated by the flow cytometry and JC-1 assay, respectively. While in vivo experiment, the cardiovascular protective effect of TI was determined by using myocardial ischemia–reperfusion (MI/R) model including hematoxylin–eosin (H&E) staining assay and determination of superoxide dismutase (SOD) and malondialdehyde (MDA). Tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) release were detected by Enzyme-linked immunosorbent assay (ELISA). Receptor interacting protein kinase 1 (RIP1), receptor interacting protein kinase 3 (RIP3), receptor interacting protein kinase 3 (MLKL), protein kinase B (Akt), Nuclear factor erythroid 2 related factor 2 (Nrf2), Heme oxygenase-1 (HO-1) and NAD(P)H: quinone oxidoreductase-1 (NQO-1) were determined by western blotting. Results Our data demonstrated that TI pretreatment attenuated t-BHP and MI/R injury-induced necroptosis by inhibiting the expression of p-RIP1, p-RIP3, and p-MLKL. TI activated the Akt/Nrf2 pathway to promote the expression of antioxidant-related proteins such as phosphorylation of Akt, nuclear factor erythroid 2 related factor 2 (Nrf2), quinone oxidoreductase-1 (NQO-1) and heme oxygenase-1 (HO-1) expression in t-BHP-stimulated H9c2 cells. TI relieved oxidative stress by mitigating ROS generation and reversing MMP loss. In vivo experiment, TI made electrocardiograph (ECG) recovery better and lessened the degree of myocardial tissue damage. The counts of white blood cell (WBC), neutrophil (Neu), lymphocyte (Lym), and the release of TNF-α and IL-6 were reversed by TI treatment. SOD level was increased, while MDA level was decreased by TI treatment. Conclusion Collectively, our findings indicated that TI exerted cardiovascular protective activities in vitro and in vivo through suppressing RIP1/RIP3/MLKL and activating Akt/Nrf2 signaling pathways, which could be developed into a cardiovascular protective agent.

In recent years, the rapid development of artificial intelligence, especially deep learning technology, makes machine learning have application scenarios in the fields of power system stability analysis, coordination along with scheduling and load forecasting. This paper designs an emotional deep learning programming controller (EDLPC) for automatic voltage control of power systems. The designed EDLPC contains an emotional deep neural network (EDNN) structure and an artificial emotional Q-learning algorithm. Besides, a specially defined proportional-integral-derivative (PID) controller is added to the deep neural networks (DNNs) structure as the actuator of an EDNN to realize the automatic tuning of PID controller parameters. In terms of control, the controller combines the advantages of the EDNN and PID controller, meanwhile adopts a reinforcement learning algorithm to optimize the parameters. From the perspective of reinforcement learning, embedding prior knowledge into the output instructions of EDNN is helpful to weaken the fitting problem in the training process. Compared with the outputs of the DNN and Q-learning algorithm under the two cases, the EDLPC could gain the highest control performance with smaller voltage deviations. The simulation results verify the feasibility and effectiveness of the proposed method for automatic voltage control of power systems.

Ilicis Rotundae Cortex (IRC) consists of the bark of Ilex rotunda Thunb, and its chemical constituents mainly include flavonoid glycosides, phenols, and triterpenoid saponins. In this study, a preliminary analysis was performed to identify and obtain the chemical components from IRC to better control the quality of the medicinal materials and provide a chemical basis for the study of the efficacy of the active components. Simple and efficient sample pretreatment and ultrasonic-assisted extraction methods were used to analyze the mass spectrum fragments and fracture modes in the anion mode by UPLC-Q-TOF-MS/MS. Using a two-step strategy, the neutral loss, diagnostic ions, and characteristic fragments were studied to screen diverse skeletons and substitutions, and the possible compounds were identified by comparison with databases. The representative compounds were compared with the standard, and the mass spectrogram was found to match perfectly. Thus, our findings reveal that this method is feasible and reliable and can be used to analyze the chemical components of IRC. We identified 105 compounds, including 22 triterpenoid saponins, 15 chlorogenic acids, 33 phenylpropanoids and phenylpropanosides, 3 iridoids, 1 flavonoid, 10 lignans, 12 glycosides, and 9 other compounds. This method lays the foundation for further elucidating the pharmacodynamics of IRC and provides a practical method for the identification of IRC.

A novel optical frequency-hopping system based on distributed feedback laser integrated with an electroabsorption modulator is proposed and demonstrated. In the proposed system, a user's data are split into segments and modulated onto multiple optical frequency shift keying carries, therefore, a single wavelength of optical carrier only carries partial user's data. By this way, the security of optical communication system is improved. In this paper, we demonstrate an error free transmission through 32-km single mode fiber and 8-km dispersion compensation fiber with 2.5 Gb/s hopping rate and 10 Gb/s data rate. Meanwhile, we also compare and analyze the performance of the proposed system with different hopping rate and data rate.

Nowadays, people are overwhelmingly exposed to various kinds of information from different information networks. In order to recommend users with the information entities that match their interests, many recommendation methods have been proposed so far. And some of these methods have explored different ways to utilize different kinds of auxiliary information to deal with the information sparsity problem of user feedbacks. However, as a special kind of information sparsity problem, the “cold start” problem is still a big challenge not well-solved yet in the recommendation problem. In order to tackle the “cold start” challenge, in this paper, we propose a novel recommendation model, which integrates the auxiliary information in multiple heterogeneous information networks (HINs), namely the Cross-HIN Recommendation System (CHRS). By utilizing the rich heterogeneous information from meta-paths, the CHRS is able to calculate the similarities of information entities and apply the calculated similarity scores in the recommendation process. For the information entities shared among multiple information networks, CHRS transfers item latent information from other networks to help the recommendation task in a given network. During the information transfer process, CHRS applies a domain adaptation matrix to tackle the domain difference problem. We conduct experiments to compare our CHRS method with several widely employed or the state-of-art recommendation models, and the experimental results demonstrate that our method outperforms the baseline methods in addressing the “cold start” recommendation problem.

At present, few studies have focused on the impact of circulation patterns on aerosol pollution in the Pearl River delta region (PRD) region based on the objective circulation classification method. Based on PM2.5 observation data, meteorological observation data, Aerosol Robotic Network (AERONET) aerosol observation data and European Center for Medium-Range Weather Forecasting (ECMWF) ERA (European Reanalysis)-Interim data in the PRD during 2013 to 2017, the air pollution level, meteorological conditions, and aerosol optical and radiation characteristics in different circulation patterns are studied in this paper. Using ECMWF ERA-Interim sea level pressure, nine circulation patterns were determined based on the T-mode principal component analysis (PCA) combined with the k-means clustering method. There were significant differences in PM2.5 values under different circulation patterns, indicating that the change of atmospheric circulation is an important factor driving the change of air quality. The prevailing wind in winter (northerly wind) facilitates the transport of pollutants from the north of the PRD and forms severe air pollution, while the prevailing wind in summer (southerly wind) brings clean air from the South China Sea; additionally, a high frequency of precipitation benefits the wet scavenging of pollutants, resulting in improved air quality in the PRD region. The impact of circulation patterns on the AOD (aerosol optical depth) is basically similar to that of the PM2.5 concentration. The study also found that the annual average total radiation was negatively correlated with the annual average PM2.5 concentration. In future, we plan to identify which methods and data are suitable for circulation classification in the PRD region.

Zhenjiang aromatic vinegar (ZAV) is a kind of traditional fermented food worldwide. In this study, the changes of physicochemical properties, total phenolic content (TPC), total flavonoid content (TFC), and total antioxidant activity (TAA) were evaluated during the brewing process of ZAV. In addition, the correlation between phenolic compound contents and antioxidant activities was investigated during the aging process (AP) of ZAV. The results showed that total acids, non-volatile acids, and amino nitrogen increased gradually during the brewing process. Reducing sugar decreased sharply at the early fermentation stage and then increased during the AP. Meanwhile, TPC, TFC, and TAA kept a very low level at the stage of alcohol fermentation (AF), and increased to the highest level at the sixth year of the AP. TAA has a high positive correlation with TPC and TFC during the brewing process of ZAV. In addition, the contents of p-hydroxybenzoic acid, vanillic acid, and catechin were higher than other phenolic compounds and reached the highest level at the sixth year of the AP, and were the main composition of phenolic compounds during the AP. Moreover, gallic acid, ferulic acid, and sinapic acid had the higher contribution at the early stage of the AP, and then declined to a lower level. Catechin, vanillic acid, and syringic acid had a higher contribution during the AP. These findings would be helpful in controlling the quality of vinegar and improving its functional properties.