Structural characterization and therapeutic effect of Alhagi honey oligosaccharide on liver fibrosis in mice.

Alhagi honey is derived from the secretory granules of Alhagi pseudoalhagi Desv., a leguminous plant commonly known as camelthorn. Modern medical research has demonstrated that the extract of Alhagi honey possesses regulatory properties for the gastrointestinal tract and immune system, as well as exerts anti-tumor, anti-oxidative, anti-inflammatory, anti-bacterial, and hepatoprotective effects. The aim of this study was to isolate and purify oligosaccharide monomers (referred to as Mel) from camelthorn and elucidate their structural characteristics. Subsequently, the impact of Mel on liver injury induced by carbon tetrachloride (CCl4) in mice was investigated. The analysis identified the isolated oligosaccharide monomer (α-D-Glcp-(1 â†’ 3)-ß-D-Fruf-(2 â†’ 1)-α-D-Glcp), with the molecular formula C18H32O16. In a mouse model of CCl4-induced liver fibrosis, Mel demonstrated significant therapeutic effects by attenuating the development of fibrosis. Moreover, it enhanced anti-oxidant enzyme activity (glutathione peroxidase and superoxide dismutase) in liver tissues, thereby reducing oxidative stress markers (malondialdehyde and reactive oxygen species). Mel also improved serum albumin levels, lowered liver enzyme activities (aspartate aminotransferase and alanine aminotransferase), and decreased inflammatory factors (tumor necrosis factor-alpha, interleukin-1 beta, and interleukin-6). Immunohistochemistry, immunofluorescence, and western blotting analyses confirmed the ability of Mel to downregulate hepatic stellate cell-specific markers (collagen type I alpha 1 chain, alpha-smooth muscle actin, transforming growth factor-beta 1. Non-targeted metabolomics analysis revealed the influence of Mel on metabolic pathways related to glutathione, niacin, pyrimidine, butyric acid, and amino acids. In conclusion, the results of our study highlight the promising potential of Mel, derived from Alhagi honey, as a viable candidate drug for treating liver fibrosis. This discovery offers a potentially advantageous option for individuals seeking natural and effective means to promote liver health.

Genomic profiles and their relationships with clinical characteristics and immune features in cervical cancer.

OBJECTIVE: This study aimed to investigate the genomic alteration profiles of cervical cancer patients, examine the correlation between mutation patterns and clinical and immune attributes, and discover novel targets for treatment of individuals with cervical cancer. METHODS: We performed targeted next-generation sequencing of tumor tissues and blood samples obtained from 45 cervical cancer patients to analyze somatic alterations, mutation patterns, and HLA alleles comprehensively. Additionally, we used flow cytometry to assess expression levels of immune checkpoint genes. RESULTS: Notably, genes such as AR (78%), KMT2D (76%), and NOTCH1 (62%) exhibited higher mutation frequencies. Moreover, the tumor mutation burden (TMB) was significantly greater in HPV-positive cervical cancer patients than in HPV-negative patients (P=0.029). BMI (P=0.047) and mutations in BARD1 (P=0.034), CEP290 (P=4E-04), and SLX4 (P=0.0128) were identified as predictors of shorter overall survival in cervical cancer patients. Furthermore, the present study revealed significant upregulation of PD-1 (P=0.027) and Tim-3 (P=0.048) in the high mutant-allele tumor heterogeneity (MATH) cohort. In the elderly cervical cancer patient population, HLA-A03:01 emerged as a high-risk allele (OR=3.2, P<0.0001); HLA-C07:02 (OR=0.073, P=0.02) and HLA-B*07:02 (OR=0.257, P=0.037) were associated with a reduced risk among patients with low TMB. CONCLUSIONS: This study offers insights into the mutation characteristics of cervical cancer patients and identifies potential therapeutic.

Predicting survival and prognosis of postoperative breast cancer brain metastasis: a population-based retrospective analysis.

BACKGROUND: Breast cancer is one of the most common cancer in women and a proportion of patients experiences brain metastases with poor prognosis. The study aimed to construct a novel predictive clinical model to evaluate the overall survival (OS) of patients with postoperative brain metastasis of breast cancer (BCBM) and validate its effectiveness. METHODS: From 2010 to 2020, a total of 310 female patients with BCBM were diagnosed in The Affiliated Cancer Hospital of Xinjiang Medical University, and they were randomly assigned to the training cohort and the validation cohort. Data of another 173 BCBM patients were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database as an external validation cohort. In the training cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression model was used to determine the fundamental clinical predictive indicators and the nomogram was constructed to predict OS. The model capability was assessed using receiver operating characteristic, C-index, and calibration curves. Kaplan-Meier survival analysis was performed to evaluate clinical effectiveness of the risk stratification system in the model. The accuracy and prediction capability of the model were verified using the validation and SEER cohorts. RESULTS: LASSO Cox regression analysis revealed that lymph node metastasis, molecular subtype, tumor size, chemotherapy, radiotherapy, and lung metastasis were statistically significantly correlated with BCBM. The C-indexes of the survival nomogram in the training, validation, and SEER cohorts were 0.714, 0.710, and 0.670, respectively, which showed good prediction capability. The calibration curves demonstrated that the nomogram had great forecast precision, and a dynamic diagram was drawn to increase the maneuverability of the results. The Risk Stratification System showed that the OS of low-risk patients was considerably better than that of high-risk patients ( P < 0.001). CONCLUSION: The nomogram prediction model constructed in this study has a good predictive value, which can effectively evaluate the survival rate of patients with postoperative BCBM.

Meta-Analysis of the Diagnostic Value of Tracer Staining Technology Based on Nanocarbon Suspension in Sentinel Lymph Node Biopsy of Breast Cancer.

Objective: To evaluate the diagnostic value of the nanometer carbon suspension tracer staining technique in sentinel lymph node biopsy of breast cancer is the objective of this study. Methods: The PubMed, Embase, Cochrane Library (Central), and Web of Science (SCI Expanded), and Chinese databases (CNKI, VIP, Wan Fang, and CBM) were systematically searched for studies on the diagnostic value of nanocarbon suspension in sentinel lymph node biopsy of breast cancer. Two reviewers independently assessed the methodological quality of each study using the QUADAS-2 tool. The extracted valid data were calculated using Meta-Disc1.4 software and tested for heterogeneity. STATA14.0 software was selected for sensitivity analysis of the included studies, and publication bias was assessed using Deeks' forest plot asymmetry test. Results: A total of 10 studies were obtained. The pooled data were as follows: sensitivity, 0.92 (0.88~0.95); specificity, 0.99 (0.98~1.00); positive likelihood ratio, 69.24 (30.34~158.02); negative likelihood ratio, 0.09 (0.06~0.13); and the combined diagnostic odds ratio, 747.40 (285.77~1954.76), AUC = 0.9881. Nanocarbon suspension tracers have an accuracy rate of 98.81% in the diagnosis of sentinel lymph nodes in breast cancer. Conclusion: Tracer staining technology based on nanocarbon suspension can accurately assess the status of lymph nodes in sentinel lymph node biopsy of breast cancer and has good stability and operability, which is worthy of clinical promotion.

UBE2C affects breast cancer proliferation through the AKT/mTOR signaling pathway.

BACKGROUND: Ubiquitin-conjugating enzyme E2C (UBE2C) has been shown to be associated with the occurrence of various cancers and involved in many tumorigenic processes. This study aimed to investigate the specific molecular mechanism through which UBE2C affects breast cancer (BC) proliferation. METHODS: BC-related datasets were screened according to filter criteria in the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. Then differentially expressed genes (DEGs) were identified using Venn diagram analysis. By using DEGs, we conducted the following analyses including Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI), and survival analysis, and then validated the function of the hub gene UBE2C using quantitative reverse transcription-polymerase chain reaction (RT-qPCR), cell counting kit-8 (CCK-8) assay, transwell assay, and Western blot assay. RESULTS: In total, 151 DEGs were identified from the GEO and TCGA databases. The results of GO analysis demonstrated that the DEGs were significantly enriched with mitotic nuclear division, lipid droplet, and organic acid-binding. KEGG analysis showed that the peroxisome proliferators-activated receptor (PPAR) signaling pathway, regulation of lipolysis in adipocytes, and proximal tubule bicarbonate reclamation were significantly enriched in the signal transduction pathway category. The top three hub genes that resulted from the PPI network were FOXM1, UBE2C, and CDKN3. The results of survival analysis showed a close relationship between UBE2C and BC. The results of CCK-8 and transwell assays suggested that the proliferation and invasion of UBE2C knockdown cells were significantly inhibited (P < 0.050). The results of Western blot assay showed that the level of phosphorylated phosphatase and tensin homology deleted on chromosome 10 (p-PTEN) was obviously increased (P < 0.050), whereas the levels of phosphorylated protein kinase B (p-AKT), phosphorylated mammalian target of rapamycin (p-mTOR), and hypoxia-inducible factor-1 alpha (HIF-1α) were dramatically decreased (P < 0.050) in the UBE2C knockdown cell. CONCLUSION: UBE2C can promote BC proliferation by activating the AKT/mTOR signaling pathway.