This study explored the prescription pattern of traditional Chinese medicine(TCM) in the treatment of hypertensive left ventricular hypertrophy(LVH), so as to provide a relevant theoretical basis for the clinical diagnosis and treatment of hypertensive LVH. The study systematically searched the databases of CNKI, Wanfang, VIP, and SinoMed to screen out the qualified literature on TCM treatment of hypertensive LVH and used Microsoft Excel 2021 to establish the relevant prescription database. It also counted the frequency, property, flavor, and meridian affiliation of TCM in the prescriptions and classified their efficacy. The study used Lantern 5.0 and Rstudio software to analyze the hidden structural models and association rules of the high-frequency TCM with a frequency of >3.50% and adopted Origin 2024 software to visualize the data, so as to explore the prescription pattern of TCM in treating hypertensive LVH. The results showed that a total of 128 TCM prescriptions were included, involving 163 TCM with a total frequency of 1 242. The high-frequency TCM included Salviae Miltiorrhizae Radix et Rhizoma, Uncariae Ramulus Cum Uncis, Gastrodiae Rhizoma, Poria, and Chuanxiong Rhizoma, with the main efficacy from blood-activating and stasis-resolving herbs, tonic herbs, and liver-calming and wind-extinguishing herbs. The latent structure analysis(LSA) identified 10 latent variables, 20 latent classes, 7 comprehensive clustering models, and 23 core prescriptions. It was speculated that the common syndromes of hypertensive LVH included blood stasis obstructing the collaterals, ascending hyperactivity of liver Yang, Yin deficiency with Yang hyperactivity, and intermingled phlegm and blood stasis. The association rule analysis yielded 33 strong association rules, with the highest comprehensive association rule being Gastrodiae Rhizoma→Uncariae Ramulus Cum Uncis. Hypertensive LVH is characterized by asthenia in origin and asthenia in superficiality, with Yin deficiency and Qi deficiency as the origin and blood stasis and phlegm as the superficiality. Clinical treatment focuses on activating blood circulation, resolving stasis, tonifying Qi, and nourishing Yin, combined with syndrome-specific therapies such as calming wind and stopping convulsions, clearing heat, eliminating dampness and resolving phlegm, and promoting diuresis and reducing swelling.
Drugs, Chinese Herbal/therapeutic use* ; Data Mining ; Humans ; Hypertension/complications* ; Hypertrophy, Left Ventricular/physiopathology* ; Medicine, Chinese Traditional ; Drug Prescriptions

OBJECTIVE: To investigate the effect of moxibustion on central insulin resistance related proteins of the rats suffering from diabetic cognitive decline, and analyze the underlying mechanism of moxibustion for cognition improvement. METHODS: Using the intraperitoneal injection of STZ combined with a high-fat diet, the rat model of diabetic cognitive decline were prepared. Twenty successfully-modeled rats were assigned randomly into a model group and a moxibustion group, 10 rats in each one. Besides, a blank group was set up with 10 rats collected. In the moxibustion group, suspending moxibustion was applied to "Baihui" (GV20), "Shenting" (GV24) and "Dazhui" (GV14) at the same time, 20 min in each intervention, once a day, and 6 interventions were delivered weekly and the duration of treatment was consecutive 4 weeks. The random blood glucose was measured using glucometer, and the learning-memory ability was detected by water maze test. HE staining was used to observe the morphology of neurons in the hippocampal tissue, real-time PCR assay was to detect mRNA expression of insulin receptor substrate 1 (IRS1), phosphatidylinositol 3-kinase (PI3K) and protein kinase B (AKT) in the hippocampal tissue. The Western blot method was employed to detect the protein expression of IRS1, PI3K, AKT, phosphorylated IRS1 (p-IRS1), phosphorylated PI3K (p-PI3K) and phosphorylated AKT (p-AKT) in the hippocampal tissue, and the ratio of p-IRS1/IRS1, p-PI3K/PI3K and p-AKT/AKT was calculated separately. The immunofluorescence intensity of p-IRS1, p-PI3K, and p-AKT was measured using immunofluorescence. RESULTS: Compared with the blank group, the rats of the model group exhibited higher random blood glucose (P<0.001), longer escape latency (P<0.001), severe pathological damage in the hippocampus, lower mRNA expression of IRS1, PI3K, and AKT (P<0.001), reduced ratio of p-IRS1/IRS1, p-PI3K/PI3K and p-AKT/AKT (P<0.001), and declined immunofluorescence intensity of p-IRS1, p-PI3K, and p-AKT in the hippocampal tissue (P<0.001). In comparison with the model group, for the rats of the moxibustion group, the random blood glucose decreased (P<0.05), the escape latency was shortened (P<0.01), the hippocampal pathological damage was attenuated, the mRNA expression of IRS1, PI3K and AKT increased (P<0.01), the ratio of p-IRS1/IRS1, p-PI3K/PI3K and p-AKT/AKT was elevated (P<0.01, P<0.05), and the immunofluorescence intensity of p-IRS1, p-PI3K, and p-AKT in the hippocampal tissue was strengthened (P<0.01, P<0.05). CONCLUSION In diabetic rats experiencing cognitive decline, moxibustion can enhance the learning-memory ability, which may be attributed to modulating the protein expression of IRS1, PI3K, and AKT, and their phosphorylation, activating insulin signal transduction, and reducing central insulin resistance.
Animals ; Moxibustion ; Insulin Resistance ; Rats ; Male ; Insulin Receptor Substrate Proteins/genetics* ; Rats, Sprague-Dawley ; Humans ; Proto-Oncogene Proteins c-akt/genetics* ; Cognitive Dysfunction/genetics* ; Diabetes Mellitus, Experimental/therapy* ; Hippocampus/metabolism* ; Acupuncture Points ; Phosphatidylinositol 3-Kinases/genetics*

OBJECTIVE: To investigate the effects of Huayu Tongluo (transforming stasis and unblocking collaterals) moxibustion on cognitive function and insulin resistance in patients with type 2 diabetes mellitus (T2DM) and cognitive decline. METHODS: Ninety patients with T2DM and cognitive decline were randomly divided into a moxibustion group (n=45, 3 cases dropped out, 2 cases were eliminated) and a waiting moxibustion group (n=45, 2 cases dropped out). Both groups received routine hypoglycemic treatment for 12 weeks. The moxibustion group additionally received Huayu Tongluo moxibustion at Baihui (GV20), Shenting (GV24), and Dazhui (GV14). Pressing moxibustion was applied to Baihui (GV20) for 20 min, while suspended moxibustion was applied to Shenting (GV24) and Dazhui (GV14) for 20 min each. Treatments of moxibustion were administered every other day (three times per week) for 12 weeks. All patients were followed up for 12 weeks, during which their original hypoglycemic medication regimen was maintained. Before treatment, after 12 weeks of treatment, and at the 12-week follow-up, the scores of Montreal cognitive assessment (MoCA), mini-mental state examination (MMSE), Addenbrooke's cognitive examination Ⅲ (ACE-Ⅲ), symbol digit modalities test (SDMT), and Athens insomnia scale (AIS) and the insulin resistance index (HOMA-IR) were observed in the two groups. RESULTS: Compared with before treatment, the MoCA scores, MMSE scores, ACE-Ⅲ subscale scores (attention, memory, language fluency, language, visuospatial ability) and total scores, and SDMT scores were increased (P<0.01), while the AIS scores were decreased (P<0.05) in the moxibustion group after treatment and at follow-up. Compared with before treatment, the MMSE score, ACE-Ⅲ subscale scores (memory, attention) and total score after treatment, as well as the ACE-Ⅲ subscale scores (language, memory, attention) and total score, and SDMT score at follow-up were increased (P<0.05, P<0.01) in the waiting moxibustion group. Compared with before treatment, HOMA-IR was decreased in both groups after treatment and at follow-up (P<0.01). At follow-up, ACE-Ⅲ subscale scores (attention, memory), and the total score in the moxibustion group were lower than those after treatment (P<0.05, P<0.01), and the ACE-Ⅲ language subscale score, total ACE-Ⅲ score, and SDMT score in the waiting moxibustion group were higher than those after treatment (P<0.01, P<0.05). After treatment and at follow-up, compared with the waiting moxibustion group, the moxibustion group had higher MoCA scores, MMSE scores, SDMT scores, ACE-Ⅲ subscale scores (attention, memory, language fluency) and total scores (P<0.05, P<0.01), and lower HOMA-IR (P<0.05). CONCLUSION Huayu Tongluo moxibustion can effectively improve cognitive function in patients with T2DM and cognitive decline. This improvement may be associated with the reduction in insulin resistance.
Humans ; Insulin Resistance ; Diabetes Mellitus, Type 2/complications* ; Male ; Female ; Moxibustion ; Middle Aged ; Aged ; Cognition ; Acupuncture Points ; Adult ; Cognitive Dysfunction/therapy*

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

AIM To explore the effects of Hofmeister series ions on encapsulation efficiencies of cinnamaldehyde,paeonol,and ligustilide in inclusion complex of volatile oils from Wenjing Decoction.METHODS The volatile oils were extracted,after which the β-cyclodextrin inclusion complex was prepared,the thermal stability was evaluated,and encapsulation efficiencies and inclusion complex constants of various volatile components in Na2SO4,NaH2PO4,NaCl,NaI,NaSCN solutions were determined.RESULTS The β-cyclodextrin inclusion complex demonstrated good thermal stability within 10 d.After the addtion of Hofmeister series ions,various volatile components displayed increased encapsulation efficiencies and inclusion complex constants,and concentration-dependent manner was observable in the latter.CONCLUSION Hofmeister series ions can affect the binding affinities of volatile components and β-cyclodextrin in volatile oils from Wenjing Decoction,thus regulate their encapsulation efficiencies.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective: To explore the bidirectional causal relationship between 731 immune cell phenotypes and recurrent aphthous ulcers (RAU) using Mendelian randomization (MR). Methods: A two-sample bidirectional MR study was conducted using publicly available genome-wide association study (GWAS) summary statistics for 731 immune cell phenotypes and the RAU GWAS summary data from the FinnGen consortium. The inverse-variance weighted (IVW) method was used as the primary analysis tool, with supplementary analyses including the weighted median (WM) method, MR-Egger regression, weighted mode, and simple mode. Sensitivity analyses were conducted using Cochran’s Q test, the mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method for detecting pleiotropy and outliers, and leave-one-out cross-validation. Furthermore, differential analysis was performed using a clinical cohort dataset from the Gene Expression Omnibus (GEO) to further validate the MR results. Results: In the forward MR analysis, 731 immune cell phenotypes were considered as exposures and RAU as the outcome. Among them, 52 immune cell phenotypes showed a significant causal effect on RAU (P<0.05). After false discovery rate (FDR) correction, two immune phenotypes remained significantly associated with RAU risk: with increased monocyte-derived myeloid suppressor cells (M-MDSC) (OR = 1.06; 95% CI: 1.03-1.09) and CD33 on granulocytic myeloid-derived suppressor cells (G-MDSC) (OR = 1.06; 95% CI: 1.03-1.09), the risk of RAU also increased. In reverse MR, RAU was found to have a significant causal effect on two immune cell phenotypes (P<0.05), but no significant effects were found after FDR correction. Sensitivity analysis showed no significant heterogeneity between SNPs (P>0.05). Differential analysis of the GEO dataset revealed that the characteristic genes of myeloid-derived suppressor cells (MDSC) (CTBS, IPMK, and UBA3) were significantly upregulated in RAU (P<0.05). Conclusion The MR results of 731 immune cell phenotypes suggest that M-MDSC and CD33 molecules on G-MDSC may be risk factors for RAU development. The clinical GEO dataset further validated that MDSC may play a role in RAU, while RAU did not show a significant causal association with the 731 immune cell phenotypes.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Computer-assisted methods for pathological image analysis can improve doctor's efficiency of image reading and diagnostic accuracy, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning technology has spurred a wealth of research in the field of histopathology. This article reviews the various applications of deep learning in digital pathological image analysis, such as pathological image segmentation, cancer auxiliary diagnosis, and cancer prognosis prediction, and discusses the challenges and solutions in its application. Furthermore, it predicts future trends in deep learning for pathological image analysis and proposes potential research directions.
Deep Learning ; Humans ; Image Processing, Computer-Assisted/methods* ; Artificial Intelligence ; Neoplasms