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Glycyrrhizic acid (GA) is a triterpene glycoside found in the roots of licorice plants (Glycyrrhiza glabra). GA is the most important active ingredient in the licorice root, and possesses a wide range of pharmacological and biological activities. GA coupled with glycyrrhetinic acid and 18-beta-glycyrrhetic acid was developed in China or Japan as an anti-inflammatory, antiviral, and antiallergic drug for liver disease. This review summarizes the current biological activities of GA and its medical applications in liver diseases. The pharmacological actions of GA include inhibition of hepatic apoptosis and necrosis; anti-inflammatory and immune regulatory actions; antiviral effects; and antitumor effects. This paper will be a useful reference for physicians and biologists researching GA and will open the door to novel agents in drug discovery and development from Chinese herbs. With additional research, GA may be more widely used in the treatment of liver diseases or other conditions.

Background Estrogen receptor-positive (ER+) breast cancers represent approximately two-thirds of all breast cancers and have a sustained risk of late disease recurrence. Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors have shown significant efficacy in ER+ breast cancer. However, their effects are still limited by drug resistance. In this study, we aim to explore the role of long noncoding RNA TROJAN in ER+ breast cancer. Methods The expression level of TROJAN in breast cancer tissue and cell lines was determined by quantitative real-time PCR. In vitro and in vivo assays as well as patient derived organoid were preformed to explore the phenotype of TROJAN in ER+ breast cancer. The TROJAN-NKRF-CDK2 axis were screened and validated by RNA pull-down, mass spectrometry, RNA immunoprecipitation, microarray, dual-luciferase reporter and chromatin immunoprecipitation assays. Results Herein, we showed that TROJAN was highly expressed in ER+ breast cancer. TROJAN promoted cell proliferation and resistance to a CDK4/6 inhibitor and was associated with poor survival in ER+ breast cancer. TROJAN can bind to NKRF and inhibit its interaction with RELA, upregulating the expression of CDK2. The inhibition of TROJAN abolished the activity of CDK2, reversing the resistance to CDK4/6 inhibitor. A TROJAN antisense oligonucleotide sensitized breast cancer cells and organoid to the CDK4/6 inhibitor palbociclib both in vitro and in vivo. Conclusions TROJAN promotes ER+ breast cancer proliferation and is a potential target for reversing CDK4/6 inhibitor resistance.

The remarkable advances in next-generation sequencing technology have enabled the wide usage of sequencing as a clinical tool. To promote the advance of precision oncology for breast cancer in China, here we report a large-scale prospective clinical sequencing program using the Fudan-BC panel, and comprehensively analyze the clinical and genomic characteristics of Chinese breast cancer. The mutational landscape of 1,134 breast cancers reveals that the most significant differences between Chinese and Western patients occurred in the hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer subtype. Mutations in p53 and Hippo signaling pathways are more prevalent, and 2 mutually exclusive and 9 co-occurring patterns exist among 9 oncogenic pathways in our cohort. Further preclinical investigation partially suggests that NF2 loss-of-function mutations can be sensitive to a Hippo-targeted strategy. We establish a public database (Fudan Portal) and a precision medicine knowledge base for data exchange and interpretation. Collectively, our study presents a leading approach to Chinese precision oncology treatment and reveals potentially actionable mutations in breast cancer. Chinese breast cancer patients have not been well represented in clinical sequencing studies. Here the authors analyse the mutational landscape of 1,134 Chinese breast cancer patients, finding actionable targets and a higher prevalence of p53 and Hippo pathway mutations compared to Western cohorts.

Background Triple-negative breast cancer (TNBC) is a highly heterogeneous group of cancers, and molecular subtyping is necessary to better identify molecular-based therapies. While some classifiers have been established, no one has integrated the expression profiles of long noncoding RNAs (lncRNAs) into such subtyping criterions. Considering the emerging important role of lncRNAs in cellular processes, a novel classification integrating transcriptome profiles of both messenger RNA (mRNA) and lncRNA would help us better understand the heterogeneity of TNBC. Methods Using human transcriptome microarrays, we analyzed the transcriptome profiles of 165 TNBC samples. We used k-means clustering and empirical cumulative distribution function to determine optimal number of TNBC subtypes. Gene Ontology (GO) and pathway analyses were applied to determine the main function of the subtype-specific genes and pathways. We conducted co-expression network analyses to identify interactions between mRNAs and lncRNAs. Results All of the 165 TNBC tumors were classified into four distinct clusters, including an immunomodulatory subtype (IM), a luminal androgen receptor subtype (LAR), a mesenchymal-like subtype (MES) and a basal-like and immune suppressed (BLIS) subtype. The IM subtype had high expressions of immune cell signaling and cytokine signaling genes. The LAR subtype was characterized by androgen receptor signaling. The MES subtype was enriched with growth factor signaling pathways. The BLIS subtype was characterized by down-regulation of immune response genes, activation of cell cycle, and DNA repair. Patients in this subtype experienced worse recurrence-free survival than others (log rank test, P  = 0.045). Subtype-specific lncRNAs were identified, and their possible biological functions were predicted using co-expression network analyses. Conclusions We developed a novel TNBC classification system integrating the expression profiles of both mRNAs and lncRNAs and determined subtype-specific lncRNAs that are potential biomarkers and targets. If further validated in a larger population, our novel classification system could facilitate patient counseling and individualize treatment of TNBC.

Progression of triple-negative breast cancer (TNBC) constitutes a major unresolved clinical challenge, and effective targeted therapies are lacking. Because microtubule dynamics play pivotal roles in breast cancer metastasis, we performed RNA sequencing on 245 samples from TNBC patients to characterize the landscape of microtubule-associated proteins (MAPs). Here, our transcriptome analyses revealed that low expression of one MAP, tektin4, indicated poor patient outcomes. Tektin4 loss led to a marked increase in TNBC migration, invasion, and metastasis and a decrease in microtubule stability. Mechanistically, we identified a novel microtubule-associated complex containing tektin4 and histone deacetylase 6 (HDAC6). Tektin4 loss increased the interaction between HDAC6 and α-tubulin, thus decreasing microtubule stability through HDAC6-mediated tubulin deacetylation. Significantly, we found that tektin4 loss sensitized TNBC cells, xenograft models, and patient-derived organoid models to the HDAC6-selective inhibitor ACY1215. Furthermore, tektin4 expression levels were positively correlated with microtubule stability levels in clinical samples. Together, our findings uncover a metastasis suppressor function of tektin4 and support clinical development of HDAC6 inhibition as a new therapeutic strategy for tektin4-deficient TNBC patients.

In view of the problems of lagging and poor predictability for ship assembly and welding quality control, the digital twin technology is applied to realize the quality prediction and control of ship group product. Based on the analysis of internal and external quality factors, a digital twin-based quality prediction and control process was proposed. Furthermore, the digital twin model of quality prediction and control was established, including physical assembly and welding entity, virtual assembly and welding model, the quality prediction and control system, and twin data. Next, the real-time data collection based on the Internet of Things and the twin data organization based on XML were used to create a virtual-real mapping mechanism. Then, the machine learning technology is applied to predict the process quality of ship group products. Finally, a small group is taken as an example to verify the proposed method. The results show that the established prediction model can accurately evaluate the welding angular deformation of group products and also provide a new idea for the quality control of shipbuilding.

Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating the GSE124272 and GSE150408 datasets for differential gene expression profiles associated with CRGs and immune characteristics. Molecular clustering was performed on LDH samples, followed by expression and immune infiltration analyses. Using the WGCNA algorithm, specific genes within CRG clusters were identified. After selecting the most predictive genes from the optimal model, four machine learning models were constructed and validated. This study identified nine CRGs associated with copper-regulated cell death. Two copper-containing molecular clusters linked to death were detected in LDH samples. Elevated expression and immune infiltration levels were found in LDH patients, particularly in CRG cluster C2. Utilizing XGB, five genes were identified for constructing a diagnostic model, achieving an area under the curve values of 0.715. In conclusion, this research provides valuable insights into the association between LDH and copper-regulated cell death, alongside proposing a promising predictive model.

Line heating is highly susceptible to plastic deformation leading to structural changes, which seriously affects shipbuilding efficiency. It is extremely important to obtain the precise line heating deformation law. There is much research on plate deformation prediction, but there is still no mature, accurate and fast prediction method. Based on this, it is necessary to research the line heating deformation prediction method. ELM has the advantages of fast learning speed, good generalization performance and strong function approximation ability. To address the poor stability of the regression model due to the randomly generated weights and thresholds of ELM, a combined prediction model (SSA-ELM) based on a squirrel search algorithm (SSA) optimized limit learning machine is proposed. The results show that the relative errors of transverse shrinkage and angular deformation of SSA-ELM are improved by 4.7% and 3.9%. The SSA-ELM prediction model has good regression accuracy and generalization ability. It gives more accurate prediction results in terms of line heating deformation prediction.

Background To investigate the effectiveness of the GnRH-a ultra-long protocol, GnRH-a long protocol, and GnRH-a short protocol used in in vitro fertilization-embryo transfer (IVF-ET) in infertile women with endometriosis. Methods We searched PubMed, Embase, Web of Science, Cochrane Library, Elsevier Science Direct, OA Library, Google Scholar, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, China Science and Technology Journal database, and the China Biology Medicine disc for randomized controlled trials (RCTs) and observational studies (non-RCTs) to evaluate the efficacy of the GnRH-a ultra-long protocol, GnRH-a long protocol, and GnRH-a short protocol in IVF-ET in infertile patients with endometriosis. Results A total of 21 studies in compliance with the standard literature were included, and RCT and non-RCT studies were analyzed separately. This meta-analysis showed that the GnRH-a ultra-long protocol could improve the clinical pregnancy rate of infertile patients in RCT studies, especially in patients with stages III–IV endometriosis (RR = 2.04, 95% CI: 1.37~3.04, P  < 0.05). However, subgroup analysis found the different down-regulation protocols provided no significant difference in improving clinical outcomes in patients with endometriosis in the non-RCT studies. Conclusion This study suggests that the GnRH-a ultra-long protocol can improve the clinical pregnancy rate of the patients with stages III–IV endometriosis in RCT studies. Although it is generally believed that the results of RCT are more reliable, the conclusions of the non-RCT studies cannot be easily neglect, which let us draw conclusions more cautious.

Background Emerging evidence suggests molecular and phenotypic association between treatment resistance and epithelial–mesenchymal transition (EMT) in cancer. Compared with the well-defined molecular events of miR-200a in EMT, the role of miR-200a in therapy resistance remains to be elucidated. Methods Breast cancer cells transfected with mimic or inhibitor for miR-200a was assayed for chemoresistance in vitro. miR-200a expression was assessed by quantitative real-time PCR (qRT-PCR) in breast cancer patients treated with preoperative chemotherapy. Luciferase assays, cell proliferation assay were performed to identify the targets of miR-200a and the mechanism by which it promotes treatment resistance. Survival analysis was used to evaluate the prognosis value of miR-200a. Results In this study, our results showed ectopic expression of miR-200a promotes chemoresistance in breast cancer cell lines to several chemotherapeutic agents, whereas inhibition of miR-200a enhances gemcitabine chemosensitivity in resistance cancer cells. We found overexpression of miR-200a was closely associated with poor response to preoperative chemotherapy and poor prognosis in breast cancer patients. Furthermore, knockdown of YAP1 and TP53INP1 phenocopied the effects of miR-200a overexpression, and confirmed that TP53INP1 is a novel target of miR-200a. Remarkably, TP53INP1 expression is inversely correlated with miR-200a expression in Breast cancer cell lines. Taken together, these clinical and experimental results demonstrate that miR-200a is a determinant of chemoresistance of breast cancer. Conclusions Upregulated miR-200a enhances treatment resistance via antagonizing TP53INP1 and YAP1 in breast cancer.