Dry eye is a chronic ocular surface disease caused by multiple factors. It is caused by the instability of tear film and the imbalance of the microenvironment of ocular surface, and may be accompanied by ocular surface inflammation, damage, and abnormal nerve sensation. The instability of tear film is its core characteristic. Mucin is an important component of the tear film and plays a role in stabilizing the tear film. The reduction of its secretion and the change of its structure lead to the occurrence and development of dry eye. The intracellular Ca2+ signal is the key to controlling the secretion of water and enzymes by exocrine glands. A decrease in the Ca2+ signal can cause dry eye. Conjunctival goblet cells are the main cells that secrete mucin. By activating the intracellular PLC-IP3-Ca2+ pathway, RyRs pathway, cAMP signaling pathway, P2X receptor, BLT1 and ChemR23 receptors, cholinergic receptor, and ALX signaling pathway, the content of Ca2+ can be increased, and the replenishment of mucin granules can be accelerated, thereby relieving the symptoms of dry eye. The Ca2+ signaling pathway may be an important target for the treatment of dry eye. This article reviews the role of mucin in dry eye and the influence of the Ca2+ signal on the secretion of mucin by conjunctival goblet cells.

Viral infection has always been a significant challenge to human health. Transplant recipients, including those who have undergone solid organ transplantation and allogeneic hematopoietic stem cell transplantation, are at high risk of viral infection due to their weak immune function under immunosuppressive therapy. Unlike the general population, transplant recipients are prone to pneumonia and even severe pneumonia after respiratory viral infection, which requires close attention from clinicians. Therefore, this article reviews the clinical characteristics and special management of viral infection in this population, focusing on the epidemiological features of common respiratory viral infection in transplant recipients, early diagnosis and intervention after infection, severe warning signs and drug treatment strategies, for the reference of clinical colleagues.

Cardiovascular disease (CVD) remains one of the leading causes of mortality among adults globally, with continuously rising morbidity and mortality rates. Metabolic disorders are closely linked to various cardiovascular diseases and play a critical role in their pathogenesis and progression, involving multifaceted mechanisms such as altered substrate utilization, mitochondrial structural and functional dysfunction, and impaired ATP synthesis and transport. In recent years, the potential role of peroxisome proliferator-activated receptors (PPARs) in cardiovascular diseases has garnered significant attention, particularly peroxisome proliferator-activated receptor alpha (PPARα), which is recognized as a highly promising therapeutic target for CVD. PPARα regulates cardiovascular physiological and pathological processes through fatty acid metabolism. As a ligand-activated receptor within the nuclear hormone receptor family, PPARα is highly expressed in multiple organs, including skeletal muscle, liver, intestine, kidney, and heart, where it governs the metabolism of diverse substrates. Functioning as a key transcription factor in maintaining metabolic homeostasis and catalyzing or regulating biochemical reactions, PPARα exerts its cardioprotective effects through multiple pathways: modulating lipid metabolism, participating in cardiac energy metabolism, enhancing insulin sensitivity, suppressing inflammatory responses, improving vascular endothelial function, and inhibiting smooth muscle cell proliferation and migration. These mechanisms collectively reduce the risk of cardiovascular disease development. Thus, PPARα plays a pivotal role in various pathological processes via mechanisms such as lipid metabolism regulation, anti-inflammatory actions, and anti-apoptotic effects. PPARα is activated by binding to natural or synthetic lipophilic ligands, including endogenous fatty acids and their derivatives (e.g., linoleic acid, oleic acid, and arachidonic acid) as well as synthetic peroxisome proliferators. Upon ligand binding, PPARα activates the nuclear receptor retinoid X receptor (RXR), forming a PPARα-RXR heterodimer. This heterodimer, in conjunction with coactivators, undergoes further activation and subsequently binds to peroxisome proliferator response elements (PPREs), thereby regulating the transcription of target genes critical for lipid and glucose homeostasis. Key genes include fatty acid translocase (FAT/CD36), diacylglycerol acyltransferase (DGAT), carnitine palmitoyltransferase I (CPT1), and glucose transporter (GLUT), which are primarily involved in fatty acid uptake, storage, oxidation, and glucose utilization processes. Advancing research on PPARα as a therapeutic target for cardiovascular diseases has underscored its growing clinical significance. Currently, PPARα activators/agonists, such as fibrates (e.g., fenofibrate and bezafibrate) and thiazolidinediones, have been extensively studied in clinical trials for CVD prevention. Traditional PPARα agonists, including fenofibrate and bezafibrate, are widely used in clinical practice to treat hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) levels. These fibrates enhance fatty acid metabolism in the liver and skeletal muscle by activating PPARα, and their cardioprotective effects have been validated in numerous clinical studies. Recent research highlights that fibrates improve insulin resistance, regulate lipid metabolism, correct energy metabolism imbalances, and inhibit the proliferation and migration of vascular smooth muscle and endothelial cells, thereby ameliorating pathological remodeling of the cardiovascular system and reducing blood pressure. Given the substantial attention to PPARα-targeted interventions in both basic research and clinical applications, activating PPARα may serve as a key therapeutic strategy for managing cardiovascular conditions such as myocardial hypertrophy, atherosclerosis, ischemic cardiomyopathy, myocardial infarction, diabetic cardiomyopathy, and heart failure. This review comprehensively examines the regulatory roles of PPARα in cardiovascular diseases and evaluates its clinical application value, aiming to provide a theoretical foundation for further development and utilization of PPARα-related therapies in CVD treatment.

Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

Aim To investigate the mechanisms of Ke-chuanting granules(KCT)inhibiting the IL-33/ILC2s pathway and pathogenic T cells to intervene in allergic airway inflammation.Methods Network pharmacolo-gy was utilized to analyze the potential targets and mechanisms of KCT-treated asthma.Allergic asthma models were induced in mice using OVA.Lung histo-pathology was conducted to observe injury changes.ELISA and quantitative PCR were utilized to measure key inflammatory factors and their mRNA expression levels in Th2-type asthma.Western blot was used to detect the phosphorylation levels of relevant proteins in the MAPK pathway.Flow cytometry was performed to evaluate the proportions of ILC2s,Th1,Th 17,Th2 and Treg cells.Results Network pharmacology iden-tified 227 main active components and 143 key targets of KCT in treating asthma,primarily enriched in signa-ling pathways such as MAPK and IL-17.Further vali-dation experiments demonstrated that KCT significantly alleviated lung inflammatory injury in asthmatic mice,reduced the number of B cells,production of I L-4,TNF-α and TGF-β,downregulated JNK phosphoryla-tion levels in lung tissue,as well as mRNA levels of Il-33,Bcl11b,Rorα,Tcf-7,Jun,Mapk3 and Mapk14.KCT intervention reduced the numbers of ILC2s and Th 17 cells in lungs and spleens of mice,and inhibited Th2 cell infiltration in lungs.Conclusions KCT ex-hibits therapeutic effects on allergic airway inflamma-tion in asthma,closely associated with the inhibition of the IL-33/ILC2s pathway,pathogenic T cell subsets,and JNK-MAPK signaling pathway.

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

Objective To establish an ideal model of the mitral valve,including the left heart and blood,and study the motion characteristics of the mitral valve in blood flow using the fluid-structure interaction(FSI)simulation.Methods Based on anatomical parameters,models of the mitral valve,left heart,and blood were established.The finite-elements combined immersed boundary method was used for FSI to simulate the motion of the mitral valve using the LS-DYNA software.Morphological,mechanical,and hemodynamic parameters were compared with those obtained from structural simulations.Results The morphological results of the mitral valve from the two simulations differed significantly,and the FSI results matched the ultrasound images.The stress distributions of the leaflets in the FSI and structural simulations were consistent.The maximum first principal stresses calculated by FSI and structural simulations were 1.48 MPa and 1.53 MPa,respectively,with a relative error of 3.27％.The fluid field in the left heart was complex with vortex structures,and the maximum mitral flow velocity was 1.02 m/s during diastole,consistent with the physiological data of healthy humans(0.89±0.15 m/s).Conclusions The morphological results of the mitral valve obtained from the FSI simulation were closer to those in the physiological state.FSI simulations can provide flow patterns that are indispensable for clinical diagnosis.Structural simulations are more efficient for studying leaflet stress distribution.

Aim To investigate the therapeutic effect of the MW-9 on ulcerative colitis(UC)and reveal the underlying mechanism, so as to provide a scientific guidance for the MW-9 treatment of UC. Methods The model of lipopolysaccharide(LPS)-stimulated RAW264.7 macrophage cells was established. The effect of MW-9 on RAW264.7 cells viability was detected by MTT assay. The levels of nitric oxide(NO)in RAW264.7 macrophages were measured by Griess assay. Cell supernatants and serum levels of inflammatory cytokines containing IL-6, TNF-α and IL-1β were determined by ELISA kits. Dextran sulfate sodium(DSS)-induced UC model in mice was established and body weight of mice in each group was measured. The histopathological damage degree of colonic tissue was assessed by HE staining. The protein expression of p-p38, p-ERK1/2 and p-JNK was detected by Western blot. Results MW-9 intervention significantly inhibited NO release in RAW264.7 macrophages with IC50 of 20.47 mg·L-1 and decreased the overproduction of inflammatory factors IL-6, IL-1β and TNF-α(P<0.05). MW-9 had no cytotoxicity at the concentrations below 6 mg·L-1. After MW-9 treatment, mouse body weight was gradually reduced, and the serum IL-6, IL-1β and TNF-α levels were significantly down-regulated. Compared with the model group, MW-9 significantly decreased the expression of p-p38 and p-ERK1/2 protein. Conclusions MW-9 has significant anti-inflammatory activities both in vitro and in vivo, and its underlying mechanism for the treatment of UC may be associated with the inhibition of MAPK signaling pathway.

OBJECTIVE To optimize ethanol extraction process of Yihuang powder. METHODS An orthogonal experiment was designed by reflux extraction with ethanol volume fraction， liquid-to-material ratio， and extraction time as investigation factors. The parameters used were the contents of hesperidin， nobiletin， tangeretin， gallic acid， chebulagic acid， chebulinic acid， liquiritin， glycyrrhizin， eugenol， and the paste-forming rate. The analytic hierarchy process （AHP） was used to calculate the comprehensive score. The optimal ethanol extraction process parameters of Yihuang powder were determined by verifying the results predicted by orthogonal experiment and genetic algorithm （GA）-back propagation neural network （BP neural network）. RESULTS The optimal ethanol extraction process parameters， as optimized by orthogonal experiment， were as follows: ethanol volume fraction of 60%， liquid-solid ratio of 14∶1 （mL/g)， extraction time of 90 min， and extraction for 2 times. The comprehensive score obtained by verification was 79.19. Meanwhile， the optimal ethanol extraction process parameters， optimized by GA-BP neural network， were ethanol volume fraction of 65%， liquid-solid ratio of 14∶1 （mL/g )， extraction time of 60 min， and extraction for 2 times. The comprehensive score obtained by verification was 85.30， higher than the results obtained from orthogonal experiment. CONCLUSIONS The optimization method of orthogonal experiment combined with GA-BP neural network is superior to the traditional orthogonal experiment optimization method. The optimized ethanol extraction process of Yihuang powder is stable and reliable.

Objective To analyze the clinical characteristics of stiff left atrial syndrome (SLAS) after Mei mini maze procedure for atrial fibrillation (AF), and to explore its risk factors and treatments. Methods We retrospectively analyzed the clinical data of the patients who underwent Mei mini maze procedure in Xinhua Hospital between 2010 and 2020. According to whether SLAS occurred in the early postoperative period, patients were divided into a SLAS group and a non-SLAS group. The basic data, perioperative echocardiogram and laboratory test indexes of the two groups were compared. Results A total of 1 056 patients were collected. There were 672 (63.6%) males with an average age of 63.6±9.3 years, including 489 patients with persistent AF and 567 patients with paroxysmal AF. Fourteen (14/1 056, 1.3%) patients developed SLAS, with an average occurrence time of 2.1±1.1 days after the surgery. The average follow-up time of the whole group was 21.4±7.8 months. Two patients in the SLAS group developed SLAS again after discharge, and the occurrence time was 3 weeks and 4 weeks after the operation, respectively; while no SLAS occurred after discharge in the non-SLAS group. Diabetes and small preoperative left atrial diameter were risk factors for SLAS after surgery. Patients with SLAS had a good prognosis after adequate diuretic therapy. Conclusion The incidence of SLAS after Mei mini maze procedure for AF is low, and it mostly occurs in the early postoperative period. After adequate diuretic treatment, the prognosis is good.