Optimizing Crystal Orientation and Defect Mitigation in Antimony Selenide Thin-Film Solar Cells through Buffer Layer Energy Band Adjustment.

Antimony selenide (Sb2Se3) has sparked significant interest in high-efficiency photovoltaic applications due to its advantageous material and optoelectronic properties. In recent years, there has been considerable development in this area. Nonetheless, defects and suboptimal [hk0] crystal orientation expressively limit further device efficiency enhancement. This study used Zinc (Zn) to adjust the interfacial energy band and strengthen carrier transport. For the first time, it is discovered that the diffusion of Zn in the cadmium sulfide (CdS) buffer layer can affect the crystalline orientation of the Sb2Se3 thin films in the superstrate structure. The effect of Zn diffusion on the morphology of Sb2Se3 thin films with CdxZn1-xS buffer layer has been investigated in detail. Additionally, Zn doping promotes forming Sb2Se3 thin films with the desired [hk1] orientation, resulting in denser and larger grain sizes which will eventually regulate the defect density. Finally, based on the energy band structure and high-quality Sb2Se3 thin films, this study achieves a champion power conversion efficiency (PCE) of 8.76%, with a VOC of 458 mV, a JSC of 28.13 mA cm-2, and an FF of 67.85%. Overall, this study explores the growth mechanism of Sb2Se3 thin films, which can lead to further improvements in the efficiency of Sb2Se3 solar cells.

Efficacy of botulinum toxin A combined with extracorporeal shockwave therapy in post-stroke spasticity: a systematic review.

Objectives: In recent years, there has been an increase in the number of randomized clinical trials of BTX-A combined with ESWT for the treatment of post-stroke spasticity. This has made it possible to observe the benefits of combination therapy in clinical practice. Therefore, this paper reviews the effectiveness of BTX-A in combination with ESWT for the treatment of post-stroke spasticity. Methods: By October 2023, a systematic review was conducted in the databases PubMed, Cochrane, Embase, Medline, Web of Science, China National Knowledge Infrastructure, Wan Fang Database, China Biology Medicine disc and China Science and Technology Journal Database were systematically searched. We included randomized controlled trials that reported outcome metrics such as MAS, FMA, and MBI score. Studies were excluded if MAS was not reported. The quality of the included studies was assessed by the Cochrane Collaboration's tool for assessing risk of bias, and the AMSTAR quality rating scale was selected for self-assessment. Results: A total of 70 articles were included in the initial search, and six were ultimately included. The results of the included studies showed that the combination therapy was effective in reducing MAS scores and improving FMA and MBI scores in patients with spasticity compared to the control group. Combination therapy has also been shown to improve joint mobility and reduce pain in spastic limbs. Conclusion: Cumulative evidence from clinical randomized controlled trial studies suggests that the combination therapy is effective in reducing lower limb spasticity and improving mobility after stroke. However, more clinical trials are still needed to corroborate the evidence regarding the efficacy of BTX-A combined with shockwave therapy. Systematic Review Registration: The system review can be searched in the PROSPERO database (CRD42023476654).

Construction of an Immunogenic Cell Death-Related Gene Signature and Genetic Subtypes for Predicting Prognosis, Immune Microenvironments, and Drug Sensitivity in Hepatocellular Carcinoma.

Purpose: Immunogenic cell death (ICD) is a type of regulated cell death that modifies the immune response by releasing DAMPs or danger signals. Herein, we aimed to develop an ICD-related predictive model for patients with hepatocellular carcinoma (HCC) and investigate its applicability for predicting prognostic outcomes and immunotherapeutic responses. Methods: Differentially expressed genes of ICD were identified in the HCC and normal liver samples. A prognostic risk model and a nomogram containing clinicopathological features were created. To validate the effectiveness of the model, an external dataset was used. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, biological function and chemotherapeutic drug sensitivity were evaluated for different genetic subtypes and risk groups. Results: A total of 35 ICD-related genes (ICDRGs) were identified between HCC and normal samples, 11 of which were significantly associated with overall survival (OS) in HCC patients. Four different genetic subtypes were formed and eight ICDRGs were selected to develop a risk prognostic model. The risk scores were shown to be an independent prognostic factor for HCC and positively correlated with pathological severity. Patients in the high-risk group had a higher frequency of TP53 mutations, increased expression of immune checkpoints and human leukocyte antigen genes. The inhibitory concentrations of chemotherapeutic drugs differed in different populations. Conclusion: In this study, we developed an ICDRG risk model and demonstrated its applicability in predicting survival outcomes, immune and chemotherapeutic responses in HCC patients. ICDRGs are expected to be used as novel biomarkers in the medical decision-making of HCC.

Convolutional Neural Network-Based Pattern Recognition of Partial Discharge in High-Speed Electric-Multiple-Unit Cable Termination.

Partial discharge detection is considered a crucial technique for evaluating insulation performance and identifying defect types in cable terminals of high-speed electric multiple units (EMUs). In this study, terminal samples exhibiting four typical defects were prepared from high-speed EMUs. A cable discharge testing system, utilizing high-frequency current sensing, was developed to collect discharge signals, and datasets corresponding to these defects were established. This study proposes the use of the convolutional neural network (CNN) for the classification of discharge signals associated with specific defects, comparing this method with two existing neural network (NN)-based classification models that employ the back-propagation NN and the radial basis function NN, respectively. The comparative results demonstrate that the CNN-based model excels in accurately identifying signals from various defect types in the cable terminals of high-speed EMUs, surpassing the two existing NN-based classification models.

Predictive value of peripheral blood leukocytes-based methylation of Long non-coding RNA MALAT1 and H19 in the chemotherapy effect and prognosis of gastric cancer.

BACKGROUND: The predictive value of the methylation of Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and H19 promoters in peripheral blood leukocytes as a non-invasive biomarker for the chemotherapy effect and prognosis gastric cancer (GC) is unclear. METHODS: The DNA methylation of H19 and MALAT1 between chemotherapy-sensitive and non-sensitive groups and between groups with better and worse survival of GC was compared using regression analyses. Several predictive nomograms were constructed. The genetic alteration of MALAT1 and H19 and the association between gene expression and immune status in GC were also investigated using bioinformatics analysis. RESULTS: Higher genetic methylations in peripheral blood were noticed in GC groups with poorer survival. The constructed nomograms presented strong predictive values for the chemotherapy effect and 3-year survival of disease-free survival, progression-free survival, and overall survival, with the area under the curve as 0.838, 0.838, 0.912, and 0.925, respectively. Significant correlations between MALAT1 or H19 expression and marker genes of immune checkpoints and immune pathways were noticed. The high infiltration of macrophages in H19-high and low infiltration of CD8+ T cells in MALAT1-high groups were associated with worse survival of GC. CONCLUSIONS: MALAT1 and H19 have the potential to predict the chemotherapy response and clinical outcomes of GC.

Joint superpixel and Transformer for high resolution remote sensing image classification.

Deep neural networks combined with superpixel segmentation have proven to be superior to high-resolution remote sensing image (HRI) classification. Currently, most HRI classification methods that combine deep learning and superpixel segmentation use stacking on multiple scales to extract contextual information from segmented objects. However, this approach does not take into account the contextual dependencies between each segmented object. To solve this problem, a joint superpixel and Transformer (JST) framework is proposed for HRI classification. In JST, HRI is first segmented into superpixel objects as input, and Transformer is used to model the long-range dependencies. The contextual relationship between each input superpixel object is obtained and the class of analyzed objects is output by designing an encoding and decoding Transformer. Additionally, we explore the effect of semantic range on classification accuracy. JST is also tested by using two HRI datasets with overall classification accuracy, average accuracy and Kappa coefficients of 0.79, 0.70, 0.78 and 0.91, 0.85, 0.89, respectively. The effectiveness of the proposed method is compared qualitatively and quantitatively, and the results achieve competitive and consistently better than the benchmark comparison method.

GIS-based non-grain cultivated land susceptibility prediction using data mining methods.

The purpose of the present study is to predict and draw up non-grain cultivated land (NCL) susceptibility map based on optimized Extreme Gradient Boosting (XGBoost) model using the Particle Swarm Optimization (PSO) metaheuristic algorithm. In order to, a total of 184 NCL areas were identified based on historical records, and a total of 16 NCL susceptibility conditioning factors (NCLSCFs) were considered, based on both a systematic literature survey and local environmental conditions. The results showed that the XGBoost model optimized by PSO performed well in comparison to other machine learning algorithms; the values of sensitivity, specificity, PPV, NPV, and AUC are 0.93, 0.89, 0.88, 0.93, and 0.96, respectively. Slope, rainfall, fault density, distance from fault and drainage density are most important variables. According to the results of this study, the use of meta-innovative algorithms such as PSO can greatly enhance the ability of machine learning models.

Photoinduced Cuproptosis with Tumor-Specific for Metastasis-Inhibited Cancer Therapy.

Cuproptosis is a novel form of regulated cell death which guarantees to increase the efficacy of existing anticancer treatments that employ traditional apoptotic therapeutics. However, reducing the amount of undesirable Cu ions released in normal tissue and maximizing Cu-induced cuproptosis therapeutic effects at tumor sites are the major challenges. In this study, exploiting the chemical properties of copper ionophores and the tumor microenvironment, a novel method is developed for controlling the valence of copper ions that cause photoinduced cuproptosis in tumor cells. CJS-Cu nanoparticles (NPs) can selectively induce cuproptosis after cascade reactions through H2 O2 -triggered Cu2+ release, photoirradiation-induced superoxide radical (∙O2 - ) generation, and reduction of Cu2+ to Cu+ by ∙O2 - . The generated reactive oxygen species can result in glutathione depletion and iron-sulfur cluster protein damage and further augmented cuproptosis. CJS-Cu NPs effectively suppressed tumor growth and downregulated the expression of metastasis-related proteins, contributing to the complete inhibition of lung metastasis. Ultimately, this study suggests novel avenues for the manipulation of cellular cuproptosis through photochemical reactions.

Health-related quality of life in Chinese SLE patients: evidence from 1568 SLE patients and 2610 healthy controls.

OBJECTIVE: To investigate the effects of systemic lupus erythematosus (SLE) on health-related quality of life (HRQOL), the relationship between disease activity and HRQOL, and potential factors affecting HRQOL in Chinese SLE patients. METHODS: This study recruited 1568 patients and 2610 controls to explore the effects of SLE on HRQOL. The association between disease activity and HRQOL, and the influencing factors of HRQOL were determined in 1568 patients. Then, we prospectively followed 1096 patients to explore the association between reduced disease activity and improved HRQOL, and the influencing factors of improved HRQOL. The Short-Form 36 (SF-36) and SLE disease activity index (SLEDAI) were used to evaluate HRQOL and disease activity. RESULTS: Chinese SLE patients had lower HRQOL than controls in all domains (P < 0.001), especially in role-physical (RP) and role-emotional (RE). Compared with SLE patients from outside China, the HRQOL of Chinese patients appeared to be higher in mental component summary (MCS) but lower in RP and RE. SLEDAI was negatively correlated with HRQOL, which was validated using the results of a follow-up study, where SLEDAI reduction was positively associated with HRQOL improvements (P < 0.05). Furthermore, personality, life nervous and experiences of adverse life events may influence HRQOL and HRQOL improvements. CONCLUSION: SLE significantly affected the HRQOL of Chinese patients, especially in RP and RE. Disease activity was negatively correlated with HRQOL. We also found for the first time some factors affecting HRQOL, which can be regarded as the basis for improving the HRQOL of SLE patients.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer.

OBJECTIVE: The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment. PATIENTS AND METHODS: Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis. RESULTS: The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC. CONCLUSION: The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

Botrytis cinerea-induced F-box protein 1 enhances disease resistance by inhibiting JAO/JOX-mediated jasmonic acid catabolism in Arabidopsis.

Jasmonic acid (JA) is a crucial phytohormone that regulates plant immunity. The endogenous JA level is determined by the rates of its biosynthesis and catabolism in plants. The activation of JA biosynthesis has been well documented; however, how plants repress JA catabolism upon pathogen infection remains elusive. In this study, we identified and characterized Botrytis cinerea-induced F-box protein 1 (BFP1) in Arabidopsis. The expression of BFP1 was induced by B. cinerea in a JA signaling-dependent manner, and BFP1 protein was critical for plant defense against B. cinerea and plant response to JA. In addition, BFP1 overexpression increased plant defenses against broad-spectrum pathogens without fitness costs. Further experiments demonstrated that BFP1 interacts with and mediates the ubiquitination and degradation of jasmonic acid oxidases (JAOs, also known as jasmonate-induced oxygenases, JOXs), the enzymes that hydroxylate JA to 12OH-JA. Consistent with this, BFP1 affects the accumulation of JA and 12OH-JA during B. cinerea infection. Moreover, mutation of JAO2 complemented the phenotypes of the bfp1 mutant. Collectively, our results unveil a new mechanism used by plants to activate immune responses upon pathogen infection: suppressing JA catabolism.

Preparation and application of UPLC silica microsphere stationary phase:A review.

In this review, microspheres for ultra-performance liquid chromatography (UPLC) were reviewed in accordance with the literature in recent years. As people's demands for chromatography are becoming more and more sophisticated, the preparation and application of UPLC stationary phases have become the focus of researchers in this field. This new analytical separation science not only maintains the practicality and principle of high-performance liquid chromatography (HPLC), but also improves the step function of chromatographic performance. The review presents the morphology of four types of sub-2 µm silica microspheres that have been used in UPLC, including non-porous silica microspheres (NPSMs), mesoporous silica microspheres (MPSMs), hollow silica microspheres (HSMs) and core-shell silica microspheres (CSSMs). The preparation, pore control and modification methods of different microspheres are introduced in the review, and then the applications of UPLC in drug analysis and separation, environmental monitoring, and separation of macromolecular proteins was presented. Finally, a brief overview of the existing challenges in the preparation of sub-2 µm microspheres, which required further research and development, was given.

Analysis of spatial and temporal changes and driving forces of arable land in the Weibei dry plateau region in China.

Arable land is the lifeblood of food production, it is of great significance to promote the protection of arable land and ensure national food security by accurately understanding the change law of cultivated land and its driving mechanism. This study takes the Weibei dry plateau region of China as an example, explores its spatial and temporal change characteristics through the center of gravity shift and land use shift matrix, and couples the geographic probe model to reveal the driving mechanisms affecting arable land change. The results show that in the past 25 years, the total arable land area in the Weibei Dry Plateau Region of China has decreased by 5.58%, and the stability of arable land resources in the whole region has weakened. The center of gravity of arable land shifts to the northeast, and the standard deviation ellipse of arable land mainly undergoes the change process of "increase (1995-2015)-decrease (2015-2020)", and the spatial distribution of arable land tends to be dispersed. In the LISA frequency mapping, the proportion of stable constant and low-frequency areas is as high as 89.58%, and the spatial pattern of cultivated land is relatively stable. Medium and high frequency areas. The transformation mode is mainly "low-low" aggregation, "low-high" aggregation is not significant, and the decline of cultivated land in the study area is more obvious. In the past 25 years, a total of 1017.26 km2 of arable land was converted to construction land. The explanatory power of the influencing factors varies in each period (0.299 to 0.731), with total agricultural machinery power has the strongest explanatory power of 0.694, 0.592, and 0.731, respectively. The interaction between slope and annual average temperature and other factors being the highest, both greater than 0.8. Through the construction of LISA frequency mapping, combined with the center of gravity model and standard deviation ellipse, the spatial evolution trend of regional arable land is more comprehensively and dynamically grasped. By using the geodetector model, the driving mechanism of the changes of arable land is revealed comprehensively, which provides a theoretical basis for the scientific management and effective protection of arable land resources and a basis for decision-making.

Global disease burden attributed to high sugar-sweetened beverages in 204 countries and territories from 1990 to 2019.

High sugar-sweetened beverages (SSBs) are a controllable risk factor for chronic non-communicable diseases (NCDs), but their effect on the global disease burden is uncertain. The study aims to assess the global burden of high SSBs from 1990 to 2019. Global Burden of Disease (GBD) 2019 provides data on deaths, disability-adjusted life years (DALYs), years of life with disabilities (YLDs) and years of life lost (YLLs) ascribe to high SSBs by ages, genders, regions and countries. For the past 30 years, overall exposure to high SSBs decreased for males and increased for females. The number of deaths from chronic NCDs ascribed to high SSBs increased from 149,988 (110,278-182,947) to 242,218 (172,045-302,250), DALYs increased from 3,698,578 (2,693,476-4,559,740) to 6,307,562 (4,300,765-8,079,556), especially the males. Age-standardized YLDs rate (ASYLDs) increased from 11.58 to 17.03. The number of ischemic heart disease (IHD) and diabetes mellitus (DM) deaths and DALYs ascribed to high SSBs has been increasing. Age-standardized death rate (ASDR) for DM risen from 0.56 to 0.62, age-standardized DALYs rate (ASDALYs) risen from 21.41 to 28.21. The burden of disease ascribed to high SSBs was in the elderly significantly higher than in the young and middle-aged, mainly concentrated in Central Asia and Oceania. The disease burden was highest in regions with moderate sociodemographic index (SDI). More extraordinary efforts should be made to raise awareness among the general public about interventions aimed at limiting the use of high SSBs, to reduce disease burden ascribed to high SSBs.

Voluntary wheel-running improved pulmonary fibrosis by reducing epithelial mesenchymal transformation.

AIMS: Pulmonary fibrosis seriously affects the health and life quality of patients. Exercise has been shown to have anti-inflammatory and antioxidant effects, but its effect on pulmonary fibrosis is unclear. In this study, the effect and mechanism of exercise on pulmonary fibrosis induced by paraquat were detected. MAIN METHODS: Three data sets were retrieved from GEO data. The biological significance of DEGs generation was determined by GO, KEGG, GSEA, and PPI. Thirty male BALB/C mice were randomly divided into control group, model group and exercise group. H&E staining, Masson staining, Immunohistochemistry and Western blot were used to explore the results. The levels of SOD, CAT, MDA, and GSH in lung tissue were analyzed with detection kits. The levels of inflammatory factors in serum and BALF were measured by ELISA. KEY FINDINGS: Compared with the control group, the infiltration of inflammatory cells and fibrotic lesions were increased in the model group. Compared with the model group, voluntary wheel-running reducing the EMT of alveolar epithelial cells, the activation of the Wnt/ß-catenin signaling pathway and the level of oxidative distress. Moreover, compared to model group, the serum IL-4, IL-10 and IFN-γ were increased, while the serum CXCL1 were decreased, while the levels of CXCL1, IL-6, IL-10, TNF-α and IFN-γ in the bronchoalveolar lavage fluid were decreased in exercise group. SIGNIFICANCE: Voluntary wheel-running reduced inflammatory infiltration and upregulated the expression of antioxidative distress proteins, further to improve the degree of EMT, and ultimately alleviated paraquat induced pulmonary fibrosis.

Enhancement in the Efficiency of Sb2 Se3 Solar Cells by Triple Function of Lithium Hydroxide Modified at the Back Contact Interface.

The efficiency of antimony selenide (Sb2 Se3 ) solar cells is still limited by significant interface and deep-level defects, in addition to carrier recombination at the back contact surface. This paper investigates the use of lithium (Li) ions as dopant for Sb2 Se3 films, using lithium hydroxide (LiOH) as a dopant medium. Surprisingly, the LiOH solution not only reacts at the back surface of the Sb2 Se3 film but also penetrate inside the film along the (Sb4 Se6 )n molecular chain. First, the Li ions modify the grain boundary's carrier type and create an electric field between p-type grain interiors and n-type grain boundary. Second, a gradient band structure is formed along the vertical direction with the diffusion of Li ions. Third, carrier collection and transport are improved at the surface between Sb2 Se3 and the Au layer due to the reaction between the film and alkaline solution. Additionally, the diffusion of Li ions increases the crystallinity, orientation, surface evenness, and optical electricity. Ultimately, the efficiency of Sb2 Se3 solar cells is improved to 7.57% due to the enhanced carrier extraction, transport, and collection, as well as the reduction of carrier recombination and deep defect density. This efficiency is also a record for CdS/Sb2 Se3 solar cells fabricated by rapid thermal evaporation.

Global, regional, and national burden of digestive diseases: findings from the global burden of disease study 2019.

Background: The global burden of digestive diseases has been rising in the last 30 years. The rates and trends of incidence, deaths, and disability-adjusted life-years (DALYs) for digestive diseases need to be investigated. Methods: We extracted the data on overall digestive diseases and by cause between 1990-2019 from the Global Burden of Diseases 2019 website, including the absolute number and the corresponding age-standardized rates of incidence (ASIR), deaths (ASDR), and DALYs (ASDALYs). Results: Globally, the incident cases, deaths, and DALYs of digestive diseases in 2019 increased by 74.44, 37.85, and 23.46%, respectively, compared with that in 1990, with an increasing ASIR of 0.09%, as well as decreasing ASDR and ASDALYs of 1.38 and 1.32% annually. The sociodemographic index (SDI) of overall digestive diseases showed a slight increase in ASIR from low to middle-low regions. The downtrend in ASDR and ASDALYs was found in all SDI regions. The burden of incidence was higher in females, while the burden of deaths and DALYs was higher in males for the overall digestive diseases and most causes. The estimated annual percentage changes were significantly associated with the baseline ASIR, ASDR, and ASDALYs for the overall digestive diseases, and the negative correlations between ASDR, ASDALYs, and human development index both in 1990 (R = -0.68, R = -0.69) and 2019 (R = -0.71, R = -0.73) were noticed. Conclusion: The findings indicate that digestive diseases remain a significant public health burden, with substantial variation across countries, sexes, and age groups. Therefore, implementing age, gender, and country-specific policies for early screening and targeted interventions could significantly reduce the global burden of digestive diseases.

Boosting 3D Object Detection with Density-Aware Semantics-Augmented Set Abstraction.

In recent years, point cloud-based 3D object detection has seen tremendous success. Previous point-based methods use Set Abstraction (SA) to sample the key points and abstract their features, which did not fully take density variation into consideration in point sampling and feature extraction. The SA module can be split into three parts: point sampling, grouping and feature extraction. Previous sampling methods focus more on distances among points in Euclidean space or feature space, ignoring the point density, thus making it more likely to sample points in Ground Truth (GT) containing dense points. Furthermore, the feature extraction module takes the relative coordinates and point features as input, while raw point coordinates can represent more informative attributes, i.e., point density and direction angle. So, this paper proposes Density-aware Semantics-Augmented Set Abstraction (DSASA) for solving the above two issues, which takes a deep look at the point density in the sampling process and enhances point features using onefold raw point coordinates. We conduct the experiments on the KITTI dataset and verify the superiority of DSASA.

Uncovering the mechanisms of Yi Qi Tong Qiao Pill in the treatment of allergic rhinitis based on Network target analysis.

OBJECTIVE: The purpose of this study is to reveal the mechanism of action of Yi Qi Tong Qiao Pill (YQTQP) in the treatment of allergic rhinitis (AR), as well as establish a paradigm for the researches on traditional Chinese medicine (TCM) from systematic perspective. METHODS: Based on the data collected from TCM-related and disease-related databases, target profiles of compounds in YQTQP were calculated through network-based algorithms and holistic targets of TQTQP was constructed. Network target analysis was performed to explore the potential mechanisms of YQTQP in the treatment of AR and the mechanisms were classified into different modules according to their biological functions. Besides, animal and clinical experiments were conducted to validate our findings inferred from Network target analysis. RESULTS: Network target analysis showed that YQTQP targeted 12 main pathways or biological processes related to AR, represented by those related to IL-4, IFN-γ, TNF-α and IL-13. These results could be classified into 3 biological modules, including regulation of immune and inflammation, epithelial barrier disorder and cell adhesion. Finally, a series of experiments composed of animal and clinical experiments, proved our findings and confirmed that YQTQP could improve related symptoms of AR, like permeability of nasal mucosa epithelium. CONCLUSION: A combination of Network target analysis and the experimental validation indicated that YQTQP was effective in the treatment of AR and might provide a new insight on revealing the mechanism of TCM against diseases. Trial registration Name of the registry: Chinese Clinical Trial Registry: Trial registration number: ChiCTR-TRC-13,003,137: Date of registration: Registered 29 March 2013 - Retrospectively registered: URL of trial registry record: https://www.chictr.org.cn/showproj.html?proj=6422 .

Impact of climate factors and climate-gene interaction on systemic lupus erythematosus patients' response to glucocorticoids therapy.

BACKGROUND: Glucocorticoids (GCs) were the essential drugs for systemic lupus erythematosus (SLE). However, different patients differ substantially in their response to GCs treatment. Our current study aims at investigating whether climate variability and climate-gene interaction influence SLE patients' response to the therapy of GCs. METHODS: In total, 778 SLE patients received therapy of GCs for a study of 12-week follow-up. The efficacy of GCs treatment was evaluated using the Systemic Lupus Erythematosus Disease Activity Index. The climatic data were provided by China Meteorological Data Service Center. Additive and multiplicative interactions were examined. RESULTS: Compared with patients with autumn onset, the efficacy of GCs in patients with winter onset is relatively poor (ORadj = 1.805, 95%CIadj : 1.181-3.014, padj = 0.020). High mean relative humidity during treatment decreased the efficacy of GCs (ORadj = 1.033, 95%CIadj : 1.008-1.058, padj = 0.011), especially in female (ORadj = 1.039, 95%CIadj : 1.012-1.067, padj = 0.004). There was a significant interaction between sunshine during treatment and TRAP1 gene rs12597773 on GCs efficacy (Recessive model: AP = 0.770). No evidence of significant interaction was found between climate factors and the GR gene polymorphism on the improved GCs efficacy in the additive model. Multiplicative interaction was found between humidity in the month prior to treatment and GR gene rs4912905 on GCs efficacy (Dominant model: OR = 0.470, 95%CI: 0.244-0.905, p = 0.024). CONCLUSIONS: Our findings suggest that climate variability influences SLE patients' response to the therapy of GCs. Interactions between climate and TRAP1/GR gene polymorphisms were related to GCs efficacy. The results guide the individualized treatment of SLE patients.