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.

Most cancers are currently incurable, partly due to abnormal post-translational modifications (PTMs). In this study, we initially used multiple myeloma (MM) as a working model and found that SUMOylation activating enzyme subunit 1 (SAE1) promotes the malignancy of MM. Through proteome microarray analysis, SAE1 was identified as a potential target for bioactive colcemid or its derivative colchicine. Elevated levels of SAE1 were associated with poor clinical survival and increased MM proliferation in vitro and in vivo. Additionally, SAE1 directly SUMOylated and upregulated the total protein expression of p27, leading to LLPS-mediated nuclear export of p27. Our study also demonstrated the involvement of SAE1 in other types of cancer cells, and provided the first monomer crystal structure of SAE1 and its key binding model with colchicine. Colchicine also showed promising results in the Patient-Derived Tumor Xenograft (PDX) model. Furthermore, a controlled clinical trial with 56 MM patients demonstrated the clinical efficacy of colchicine. Our findings reveal a novel mechanism by which tumor cells evade p27-induced cellular growth arrest through p27 SUMOylation-mediated nuclear export. SAE1 may serve as a promising therapeutic target, and colchicine may be a potential treatment option for multiple types of cancer in clinical settings.

Tumors exhibit abnormal glucose metabolism, consuming excessive glucose and excreting lactate, which constructs a tumor microenvironment that facilitates cancer progression and disrupts immunotherapeutic efficacy. Currently, tumor glucose metabolic dysregulation to reshape the immunosuppressive microenvironment and enhance immunotherapy efficacy is emerging as an innovative therapeutic strategy. However, glucose metabolism modulators lack specificity and still face significant challenges in overcoming tumor delivery barriers, microenvironmental complexity, and metabolic heterogeneity, resulting in poor clinical benefit. Nanomedicines, with their ability to selectively target tumors or immune cells, respond to the tumor microenvironment, co-deliver multiple drugs, and facilitate combinatorial therapies, hold significant promise for enhancing immunotherapy through tumor glucose metabolic reprogramming. This review explores the complex interactions between tumor glucose metabolism-specifically metabolite transport, glycolysis processes, and lactate-and the immune microenvironment. We summarize how nanomedicine-mediated reprogramming of tumor glucose metabolism can enhance immunotherapy efficacy and outline the prospects and challenges in this field.

Notum, a negative feedback regulator of the Wnt signaling, has emerged as a promising target for treating glucocorticoid-induced osteoporosis (GIOP). This study showcases an efficient strategy for discovering the anti-Notum constituents from herbal medicines (HMs) as novel anti-GIOP agents. Firstly, a rapid-responding near-infrared fluorogenic substrate for Notum was rationally engineered for high-throughput identifying the anti-Notum HMs. The results showed that Bu-Gu-Zhi (BGZ), a known anti-osteoporosis herb, potently inhibited Notum in a competitive-inhibition manner. To uncover the key anti-Notum constituents in BGZ, an efficient strategy was adapted via integrating biochemical, phytochemical, computational, and pharmacological assays. Among all identified BGZ constituents, three furanocoumarins were validated as strong Notum inhibitors, while 5-methoxypsoralen (5-MP) showed the most potent anti-Notum activity and favorable safety profiles. Mechanistically, 5-MP acted as a competitive inhibitor of Notum via creating strong hydrophobic interactions with Trp128 and Phe268 in the catalytic cavity of Notum. Cellular assays showed that 5-MP remarkably promoted osteoblast differentiation and activated Wnt signaling in dexamethasone (DXMS)-challenged MC3T3-E1 osteoblasts. In dexamethasone-induced osteoporotic mice, 5-MP strongly elevated bone mineral density (BMD) and improved cancellous and cortical bone thickness. Collectively, this study constructs a high-efficient platform for discovering key anti-Notum constituents from HMs, while 5-MP emerges as a promising anti-GIOP agent.

OBJECTIVE: To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors. METHODS: From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact. RESULTS: Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution. CONCLUSION The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female ; Humans ; Male ; China/epidemiology* ; Cities/epidemiology* ; Hand, Foot and Mouth Disease/transmission* ; Incidence ; Risk Factors ; Temperature

Decoction is the most commonly used dosage form in the clinical treatment of traditional Chinese medicine (TCM). During boiling, the violent movement of various active ingredients in TCM creates molecular forces such as hydrogen bonding, π-π stacking, hydrophobic interactions and electrostatic interactions, which results in the formation of self-assembled aggregates in decoction (SADs), including particles, gels, fibers, etc. It was found that SADs widely existed in decoction with biological activities superior to both effective monomers and their physical mixtures, providing a new idea to reveal the pharmacodynamic material basis of Chinese herbal medicine from the perspective of component interactions-phase structure. Recently, SADs have become a novel focus of research in TCM. This paper reviewed their relevant studies in recent years and found some issues to be concerned in the research, such as the polydispersity of decoction system, instability of active ingredient interactions during boiling, uncertainty of the aggregates self-assembly rules, and stability, purity, yield of the products. In this regard, some solutions and new ideas were presented for the integrated development and clinical application of SADs.

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1 250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAXGv).The videos were divided into development set(245 A4C,155 PLAX,225 PSAXGV),semi-automated training set(98 A4C,62 PLAX,90 PSAXGV)and test set(147 A4C,93 PLAX,135 PSAXGV)at the ratio of 5:2:3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33％,97.26％,97.26％and 97.26％to 99.73％,99.65％,99.77％and 99.71％,respectively,while the overall accuracy for assessing A4C,PLAX and PSAXGV TTE as standard views in test set improved from 89.12％,83.87％and 90.37％to 93.20％,90.32％and 93.33％,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.