Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

BACKGROUND:Previous studies have found that neohesperidin can delay bone loss in ovariectomized mice and has the potential to treat osteoporosis,but its specific mechanism of action remains to be explored. OBJECTIVE:To explore the key targets and possible mechanisms of neohesperidin in the treatment of osteoporosis based on bioinformatics and cell experiments in vitro. METHODS:The gene expression dataset related to osteoporosis was obtained from GEO database,and the differentially expressed genes were screened and analyzed in R language.The osteoporosis-related targets were screened from GeneCards and DisGeNET databases,and the neohesperidin-related targets were screened from ChEMBL and PubChem databases,and the common targets were obtained by intersection of the three.The String database was used to construct the PPI network of intersection genes,and the key targets were screened.The DAVID database was used for GO and KEGG enrichment analysis.The AutoDock software was used to verify the molecular docking between the neohesperidin and the target protein.The effect of neohesperidin on osteogenic differentiation of C57 mouse bone marrow mesenchymal stem cells was detected.Complete medium was used as blank control group;osteogenic induction medium was used as the control group;and osteogenic induction medium containing different concentrations of neohesperidin(25,50 μmol/L)was used as experimental group.The expression of alkaline phosphatase,the degree of mineralization,the expression of osteogenic-related genes and target genes during osteogenic differentiation of cells were measured at corresponding time points. RESULTS AND CONCLUSION:(1)9 253 differentially expressed genes,2 161 osteoporosis-related targets,and 326 neohesperidin-related targets were screened.There were 53 common targets among the three.All 53 genes were up-regulated in osteoporosis samples.The PPI network screened the target gene PRKACA of research significance.GO function and KEGG pathway enrichment analysis showed that neohesperidin's treatment of osteoporosis through PRKACA target mainly depended on biological processes such as protein phosphorylation and protein autophosphorylation,acting on endocrine resistance,proteoglycan in cancer,and estrogen signaling pathway to play a therapeutic role.Molecular docking results showed that neohesperidin had a certain binding ability to the protein corresponding to the target PRKACA.(2)The results of alkaline phosphatase staining showed that neohesperidin could promote the expression of alkaline phosphatase in the early stage of osteogenic differentiation of mesenchymal stem cells.Alizarin red staining showed that neohesperidin could promote the mineralization of osteogenic differentiation of mesenchymal stem cells.RT-qPCR results showed that neohesperidin could increase the mRNA expression of alkaline phosphatase,PRKACA,and osteocalcin.(3)These results indicate that neohesperidin may promote osteogenic differentiation through PRKACA target on the estrogen signaling pathway to prevent and treat osteoporosis.

Objective To analyze the clinical significance of subjective visual vertical (SVV) tests at different head deflection angles in assessing utricle function in patients with benign paroxysmal positional vertigo (BPPV). Methods A total of 61 BPPV patients who were treated at the Hearing Impairment and Vertigo Diagnosis and Treatment Center of Otolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine from August 2022 to May 2023 were retrospectively included, and 29 healthy adults were selected as controls. SVV tests were performed on all research subjects at different head deflection angles: upright head (0°), left head 45° (L45°), right head 45° (R45°). The test results between the two groups were compared. Results SVV absolute value at R45° in BPPV group was lower than that in the control group (P＝0.003); there was no significant difference in SVV values at 0° and L45° between the two groups. There was no statistical difference in SVV values at different head deflection angles between the control group and the left BPPV group. SVV absolute value at R45° in right BPPV group was lower than that in the control group (P＜0.001); there was no statistical difference in SVV values at 0° and L45° between the two groups. Conclusions SVV test can provide subjective information about the utricle, and SVV tests at different head deflection angles can fine-tune evaluate the function of the utricle in BPPV patients.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

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.