Liver cancer (LC) remains one of the most prevalent tumors globally. Despite considerable advancements in its clinical treatment in recent years, the global burden of this disease is projected to increase. According to World Health Organization statistics, the number of LC deaths worldwide in 2022 was 760,000, ranking third among all cancers. Therefore, there is an urgent need to delve deeper into the realms of LC diagnosis, prognosis, and treatment. Proteomics, as an emerging technology leveraging mass spectrometry (MS)-based protein identification, liquid chromatography separation, and bioinformatics-driven data integration, enables the systematic characterization of proteome dynamics to address critical challenges in LC research. These challenges include the discovery of diagnostic and prognostic biomarkers as well as therapeutic targets. By scrutinizing the expression of specific proteins in both normal and cancerous tissues through high-throughput protein microarrays, researchers can uncover novel biomarkers. The use of these biomarkers alone or in combination with established ones holds the potential to significantly advance the fields of LC diagnosis, prognosis, and treatment. In general, the application of proteomics has significantly promoted the development of LC research. In this review, we summarized the latest advancements in the application of proteomics in LC, with a particular focus on diagnosis, prognosis, and treatment. We also concluded selected protein markers, aiming to offer guidance for further applications and present additional therapeutic targets for LC.

Objective To explore the valve regurgitation status of left heart after the implantation of left ventricular assist device (LVAD) and its effect on prognosis of patients with LVAD implantation. Methods A total of 35 patients with cardiomyopathy who underwent magnetic levitation LVAD implantation at Zhongshan Hospital, Fudan University from February 2021 to July 2024 were retrospectively selected. Clinical data during hospitalization were collected, including preoperative basic data and postoperative valve regurgitation status. Telephone follow-ups were conducted to monitor patients’ survival status and transthoracic echocardiography was used to assess left valve function. Kaplan-Meier survival curves and log-rank test were employed to compare the survival rate of patients with different levels of valve regurgitation. Results The 35 patients had a mean age of (53.9±11.1) years, with 85.7% male, and 3 patients (8.6%) died during hospitalization. Preoperatively, 17 patients (48.6%) had moderate or greater mitral regurgitation, while all 35 patients had less than moderate aortic regurgitation. One month postoperatively, thirty patients were followed up, among which 24 patients (80%) had less than moderate mitral regurgitation, including 11 cases with alleviated regurgitation compared to pre-surgery; 6 patients (20%) had moderate or greater mitral regurgitation, including 4 cases with stable regurgitation and 2 cases with progression of regurgitation compared to pre-surgery; 2 patients (6.7%) had progression of aortic regurgitation to moderate or greater. The follow-up time was 1.2 (1.0, 2.1) years, with 1-year survival rate of 91.4% and 3-year survival rate of 71.1%. Survival analysis showed that the 3-year survival rate of patients with moderate or greater mitral regurgitation one month postoperatively was significantly lower than that of patients with less than moderate regurgitation (66.7% vs 83.3%, P＝0.046). Conclusions After the implantation of magnetic levitation LVAD, most patients showed improvement in mitral regurgitation, while aortic regurgitation remained unchanged. The degree of mitral regurgitation one month postoperatively is associated with prognosis.

Alcoholic liver disease(ALD), a major cause of chronic liver disease worldwide, poses a serious threat to human health. Despite the availability of various drugs for treating ALD, their efficacy is often uncertain, necessitating the search for new therapeutic approaches. Traditional Chinese medicine polysaccharides have garnered increasing attention in recent years due to their versatility, high efficiency, and low side effects, and they have demonstrated significant potential in preventing and treating ALD. Emerging studies have suggested that these polysaccharides exert their therapeutic effects through multiple mechanisms, including the inhibition of oxidative stress and the regulation of lipid metabolism, gut microbiota, and programmed cell death. This review summarizes the recent research progress in the pharmacological effects and regulatory mechanisms of traditional Chinese medicine polysaccharides in treating ALD, aiming to provide a scientific basis and theoretical support for their application in the prevention and treatment of ALD.
Humans ; Liver Diseases, Alcoholic/metabolism* ; Polysaccharides/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Oxidative Stress/drug effects* ; Medicine, Chinese Traditional ; Gastrointestinal Microbiome/drug effects* ; Lipid Metabolism/drug effects*

The present study delves into the cellular mechanisms underlying the antiviral effects of dehydrodiisoeugenol(DEH) by focusing on the transcription factor EB(TFEB)/autophagy-lysosome pathway. The cell counting kit-8(CCK-8) was utilized to assess the impact of DEH on the viability of human non-small cell lung cancer cells(A549). The inhibitory effect of DEH on the replication of influenza A virus(H1N1) was determined by real-time quantitative polymerase chain reaction(RT-qPCR). Western blot was employed to evaluate the influence of DEH on the expression level of the H1N1 virus nucleoprotein(NP). The effect of DEH on the fluorescence intensity of NP was examined by the immunofluorescence assay. A mouse model of H1N1 virus infection was established via nasal inhalation to evaluate the therapeutic efficacy of 30 mg·kg~(-1) DEH on H1N1 virus infection. RNA sequencing(RNA-seq) was performed for the transcriptional profiling of mouse embryonic fibroblasts(MEFs) in response to DEH. The fluorescent protein-tagged microtubule-associated protein 1 light chain 3(LC3) was used to assess the autophagy induced by DEH. Western blot was employed to determine the effect of DEH on the autophagy flux of LC3Ⅱ/LC3Ⅰ under viral infection conditions. Lastly, the role of TFEB expression in the inhibition of DEH against H1N1 infection was evaluated in immortalized bone marrow-derived macrophage(iBMDM), both wild-type and TFEB knockout. The results revealed that the half-maximal inhibitory concentration(IC_(50)) of DEH for A549 cells was(87.17±0.247)μmol·L~(-1), and DEH inhibited H1N1 virus replication in a dose-dependent manner in vitro. Compared with the H1N1 virus-infected mouse model, the treatment with DEH significantly improved the body weights and survival time of mice. DEH induced LC3 aggregation, and the absence of TFEB expression in iBMDM markedly limited the ability of DEH to counteract H1N1 virus replication. In conclusion, DEH exerts its inhibitory activity against H1N1 infection by activating the TFEB/autophagy-lysosome pathway.
Influenza A Virus, H1N1 Subtype/genetics* ; Animals ; Autophagy/drug effects* ; Humans ; Mice ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Influenza, Human/metabolism* ; Lysosomes/metabolism* ; Orthomyxoviridae Infections/genetics* ; Eugenol/pharmacology* ; Antiviral Agents/pharmacology* ; Virus Replication/drug effects* ; A549 Cells ; Male

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.

AIM To investigate the effects of Shuyu Pills combined with evolimus on the epithelial mesenchymal transformation of triple negative breast cancer cells 4T1 and MDA-MB-231 induced by TGF-β1.METHODS The 4T1 and MDA-MB-231 cells were divided into the blank group and the induction group to induce the epithelial mesenchymal transformation with TGF-β1 cytokine treatment,followed by the assignment into the model group,the Shuyu Pills group,the everolimus group and the Shuyu Pills combined with everolimus group.CCK8 method,plate cloning method,cell scratch test and Transewll test were used to detect the proliferation,cloning formation,migration and invasion ability of the cells whose expressions of E-cadherin,N-cadherin,Vimentin,MMP9,MMP2 and pathway proteins PTEN,PI3K,Akt and mTOR were detected by Western blot.RESULTS Compared with the blank group,the induction group displayed a cell morphological change from epithelioid to stromal,decreased expression of E-cadherin protein(P＜0.01);and increased protein expressions of N-cadherin and Vimentin(P＜0.05).Compared with the model group,each group intervened with the medicine displayed decreased proliferation,clone formation,migration and invasion ability of both kinds of cells(P＜0.01);increased protein expressions of PTEN and E-cadherin(P＜0.05,P＜0.01);and decreased protein expressions of PI3K,Akt,mTOR,N-cadherin,Vimentin,MMP9 and MMP2(P＜0.05,P＜0.01);and more significantly in the Shuyu Pills combined with evolimus group(P＜0.05,P＜0.01).CONCLUSION With a more ideal effect than the single uses in inhibiting the TGF-β1-induced epithelial mesenchymal transformation of triple-negative breast cancer cells,the combination use of Shuyu Pills and everolimus may work through the regulation of PI3K/Akt/mTOR signaling pathway.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the char-acteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Structural optimization of lead compounds is a crucial step in drug discovery.One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties.One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules,thereby accelerating the molecular optimization process.Deep molecular diffusion generative models simulate a gradual process that creates novel,chemically feasible molecules from noise.However,the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules,leading to challenges in modifying the scaffold-based molecular structures,and creates limitations in the stability and diversity of the generated molecules.To address these challenges,we propose a deep molecular diffusion generative model,the three-dimensional(3D)equivariant diffusion-driven molecular generation(3D-EDiffMG)model.The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder(dual-SWLEE)is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions.Addi-tionally,a gate multilayer perceptron(gMLP)block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies.The experimental results show that 3D-EDiffMG effectively generates unique,novel,stable,and diverse drug-like molecules,highlighting its potential for lead optimization and accelerating drug discovery.

Objective: To investigate the distribution characteristics and related factors of weight loss behavior among middle school students in Shanghai, so as to provide a reference for guiding scientific weight loss among middle school students. Methods: From May to June 2021, a stratified cluster random sampling method was used to select 16 758 junior and high school students in 16 districts of Shanghai. Youth Risk Behavior Surveillance System was administered to assess the basic condition and weight loss behaviors of the students. An unordered multinomial Logistic regression model was employed to analyze the factors associated with weight loss behaviors. Results: A total of 5 881 (35.09%) reported engaging in exercise for weight loss, 6 344 (37.86%) reported dieting for weight loss, and 461 (2.75%) engaged in unhealthy weight loss behaviors. The unordered multinomial Logistic regression analysis indicated that compared with the no weight loss behavior group, students from urban areas( OR =1.35,95% CI =1.10-1.66), those with Internet addiction ( OR =1.71,95% CI =1.23-2.38), those with victims of bullying ( OR =2.09, 95% CI =1.68-2.61), those experiencing insomnia ( OR =2.33,95% CI = 1.74-3.11), those feelings of sadness or despair ( OR =3.10, 95% CI =2.42- 3.97 ), and those who perceived their body weight as slightly heavy ( OR =2.77, 95% CI = 2.17-3.55) or very heavy ( OR =3.41, 95% CI =2.44-4.75) were more likely to engage in unhealthy weight loss behaviors ( P <0.05). Conclusions There are significant differences in weight loss behaviors among middle school students with varying characteristics in Shanghai. Negative emotions such as insomnia and feelings of sadness or despair, Internet addiction, cognitive bias in weight and experiences of bullying are identified as related factors for unhealthy weight loss behaviors. Targeted intervention measures should be implemented to guide students towards scientific approaches to weight management.