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.

OBJECTIVE To evaluate the quality of evidence in the systematic evaluation/meta-analysis of traditional Chinese medicine （TCM） for diabetes retinopathy （DR） based on the GRADE system. METHODS Chinese and English databases were searched to obtain the relevant studies of systematic evaluation/meta-analysis of traditional Chinese medicine in the treatment of DR. The search time was from the establishment of each database to January 13th， 2024. According to the inclusion and exclusion criteria， literature screening was conducted. After extracting relevant information from the included literature， the GRADE system was used to evaluate the quality level of the evidence body in the included studies， and the evidence of the outcome indicators was integrated and summarized. RESULTS A total of 51 studies were ultimately included， encompassing 135 outcome indexes. Among these， 19 indicators （14.1%） were of high quality， 87 （64.4%） were of medium quality， 26 （19.3%） were of low quality， and 3 （2.2%） were of very low quality. Overall， the evidence quality of the outcome indicators in the included studies was medium to low quality. The integrated results of evidence on the efficacy of outcome indexes showed that compared with conventional Western medicine， calcium dobesilate or placebo， TCM had significant advantages in improving overall efficacy， reducing bleeding spot area， reducing macular foveal thickness， and increasing visual improvement rate. In addition，the combination of TCM and conventional Western medicine or calcium dobesilate was significantly more effective than using conventional Western medicine or calcium dobesilate alone. CONCLUSIONS The overall quality of the evidence in the systematic evaluation/meta-analysis study on the treatment of DR with TCM is medium to low quality. Based on existing research findings， TCM demonstrates good clinical efficacy in the treatment of DR.

The traditional Chinese medicine （TCM） myocardial infarction （MI） unit is a standardized， regulated， and continuous integrated care unit guided by TCM theory and built upon existing chest pain centers or emergency care units. This unit emphasizes multidisciplinary collaboration and forms a restructured clinical entity without altering current departmental settings， offering comprehensive diagnostic and therapeutic services with full participation of TCM in the treatment of MI. Its core medical model is patient-centered and disease-focused， providing horizontally integrated TCM-based care across multiple specialties and vertically constructing a full-cycle treatment unit for MI， delivering prevention， treatment， and rehabilitation during the acute， stable， and recovery phases. Additionally， the unit establishes a TCM-featured education and prevention mechanism for MI to guide patients in proactive health management， reduce the incidence of myocardial infarction， and improve quality of life.

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.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective: To evaluate the performance of platelet efficacy score (PEscore) in predicting platelet transfusion efficacy in hematological patients. Methods: A total of 485 patients with hematological diseases, including 298 males (62.09±15.45 years) and 187 females (59.17±16.52 years) who received platelet transfusion from January 1, 2021 to December 31, 2024 were enrolled in this study. Clinical data of the patients such as diagnosis, gender, age, number of platelet transfusion, and platelet antibody data were analyzed to investigate the incidence and influencing factors of platelet transfusion refractoriness in hematological patients at our hospital. ROC curve was used to evaluate the performance of PEscore model in predicting platelet transfusion efficacy. The predictive performance of PEscore model was validated by calculating its sensitivity, specificity, and accuracy in 115 clinical cases. Results: The incidence of platelet transfusion refractoriness in 485 cases was 29.90% (145/485). Significant differences (P<0.05) were observed between the effective and ineffective platelet transfusion groups regarding the following factors: diagnosis: lymphoma [55.32% (26/47) vs 44.68% (21/47)], the number of previous platelet transfusions [≥25: 60.78% (31/51) vs 39.22% (20/51)], platelet antibody screening result [positive: 33.76% (53/157) vs 66.24% (104/157)], and platelet transfusion volume (×10 /L) [>6: 62.71% (74/118) vs 37.29% (44/118)]. The area under the ROC curve of PEscore was 0.876. The cut-off points and corresponding sensitivity and specificity were 19.90.59% and 69.44%, respectively. The results of clinical application showed that the sensitivity, specificity and accuracy of the PEscore model for predicting platelet transfusion were 87.50%, 93.41% and 92.17%, respectively. Conclusion: The incidence of platelet transfusion refractoriness in hematological patients is relatively high. PEscore prediction model has a good performance in predicting the effect of platelet transfusion, which can provide a reliable basis for predicting the effect of platelet transfusion in hematological patients before blood transfusion.

Objective To explore the changing trend in the disease burden of gout in China from 1990 to 2021, and analyze the incidence, prevalence, and disability-adjusted life years (DALYs) by age and gender, with comparisons to global patterns, and to predict the disease burden of gout in China in 2030. Methods Data from the Global Burden of Disease (GBD) database were used to analyze changes in gout burden. Joinpoint regression was used to estimate the average annual percentage change (AAPC) with 95% confidence intervals (CIs). Comparative analyses were conducted on data from China and the world, and an ARIMA model was used to project China's gout burden in 2030. Results From 1990 to 2021, China's age-standardized incidence rate (ASIR) rose from 122.52 to 151.61/100,000, exceeding the global rise from 93.09 to 109.07/100,000. The age-standardized prevalence rate (ASPR) in China increased from 640.67/100,000 to 810.35/100,000, compared to a global rise from 536.54/100,000 to 653.81/100,000. The age-standardized DALYs rate (ASDR) in China increased from 20.2/100,000 to 25.43/100,000, surpassing the global increase from 16.67/100,000 to 20.21/100,000. AAPCs for ASIR, ASPR, and ASDR in China were 0.70%, 0.77%, and 0.75%, respectively, all higher than global rates. Middle-aged and elderly men faced the highest burden. It was predicted that there will be a decline in China's ASIR and ASPR by 2030, while ASDR will remain stable. Conclusion The disease burden of gout in China has increased significantly, outpacing global trends. Targeted interventions for hyperuricemia, particularly in elderly men, are crucial to reduce the future disease burden.

Elemene, derived from Curcuma wenyujin, one of the "8 famous genuine medicinal materials of Zhejiang province," exhibits remarkable antitumor activity. It has gained wide recognition in clinical practice for effectiveness on tumors. Dr. XIE Tian, introduced the innovative concept of "molecular compatibility theory" by combining Chinese medicine principles, specifically the "monarch, minister, assistant, and envoy" theory, with modern biomedical technology. This groundbreaking approach, along with a systematic analysis of Chinese medicine and modern biomedical knowledge, led to the development of elemene nanoliposome formulations. These novel formulations offer numerous advantages, including low toxicity, well-defined composition, synergistic effects on multiple targets, and excellent biocompatibility. Following the principles of the "molecular compatibility theory", further exploration of cancer treatment strategies and methods based on elemene was undertaken. This comprehensive review consolidates the current understanding of elemene's potential antitumor mechanisms, recent clinical investigations, advancements in drug delivery systems, and structural modifications. The ultimate goal of this review is to establish a solid theoretical foundation for researchers, empowering them to develop more effective antitumor drugs based on the principles of "molecular compatibility theory".
Humans ; Retrospective Studies ; Antineoplastic Agents/therapeutic use* ; Neoplasms/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Sesquiterpenes/therapeutic use*