Two Ferulic Acid Derivatives Inhibit Neuroinflammatory Response in Human HMC3 Microglial Cells via NF-κB Signaling Pathway.

Various physiological and pathological changes are related to the occurrence and development of neurodegenerative diseases. Neuroinflammation is a major trigger and exacerbation of neurodegenerative diseases. One of the main symptoms of neuritis is the activation of microglia. Thus, to alleviate the occurrence of neuroinflammatory diseases, an important method is to inhibit the abnormal activation of microglia. This research evaluated the inhibitory effect of trans-ferulic acid (TJZ-1) and methyl ferulate (TJZ-2), isolated from Zanthoxylum armatum, on neuroinflammation, by establishing the human HMC3 microglial cell neuroinflammation model induced by lipopolysaccharide (LPS). The results showed both compounds significantly inhibited the production and expression of nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-1ß (IL-1ß) contents, and increased the level of anti-inflammatory factor ß-endorphin (ß-EP). Furthermore, TJZ-1 and TJZ-2 can inhibit LPS-induced activation of nuclear factor kappa B (NF-κB). It was found that of two ferulic acid derivatives, both had anti-neuroinflammatory effects by inhibiting the NF-κB signaling pathway and regulating the release of inflammatory mediators, such as NO, TNF-α, IL-1ß, and ß-EP. This is the first report that demonstrates that TJZ-1 and TJZ-2 had inhibitory effects on LPS-induced neuroinflammation in human HMC3 microglial cells, which indicates that two ferulic acid derivates from Z. armatum could be used as potential anti-neuroinflammatory agents.

Adipocytes impact on gastric cancer progression: Prognostic insights and molecular features.

BACKGROUND: Adipocytes, especially adipocytes within tumor tissue known as cancer-associated adipocytes, have been increasingly recognized for their pivotal role in the tumor microenvironment of gastric cancer (GC). Their influence on tumor progression and patient prognosis has sparked significant interest in recent research. The main objectives of this study were to investigate adipocyte infiltration, assess its correlation with clinical pathological features, develop a prognostic prediction model based on independent prognostic factors, evaluate the impact of adipocytes on immune cell infiltration and tumor invasiveness in GC, and identify and validate genes associated with high adipocyte expression, exploring their potential diagnostic and prognostic value. AIM: To explore the relationship between increased adipocytes within tumor tissue and prognosis in GC patients as well as the associated mechanisms and potential biomarkers, using public databases and clinical data. METHODS: Using mRNA microarray datasets from the Gene Expression Omnibus database and clinical samples from Jiangsu Provincial Hospital, survival and regression analyses were conducted to determine the relevant prognostic factors in GC. Feature gene selection was performed using least absolute shrinkage and selection operator and support vector machine recursive feature elimination algorithms, followed by differential gene expression analysis, gene ontology, pathway analysis, and Gene Set Enrichment Analysis. Immune cell infiltration was analyzed using the CIBERSORT algorithm. RESULTS: Tumor adipocyte infiltration correlated with poor prognosis in GC, leading to the development of a highly accurate and discriminative prognostic prediction model. Key genes, ADH1B, SFRP1, PLAC9, and FABP4, were identified as associated with high adipocyte expression in GC. The diagnostic and prognostic potential of these identified genes was validated using independent datasets. Downregulation of immune cells was observed in GC with high adipocyte expression. CONCLUSION: GC with high intratumoral adipocyte expression demonstrated aggressive tumor biology and a poorer prognosis. The genes ADH1B, SFRP1, PLAC9, and FABP4 have been identified as holding diagnostic and prognostic significance in GC. These findings strongly support the use of adipocyte expression as a valuable indicator of tumor invasiveness and anticipated patient outcomes in GC.

Risk factors, prognostic factors, and nomograms for distant metastasis in patients with diagnosed duodenal cancer: A population-based study.

BACKGROUND: Duodenal cancer is one of the most common subtypes of small intestinal cancer, and distant metastasis (DM) in this type of cancer still leads to poor prognosis. Although nomograms have recently been used in tumor areas, no studies have focused on the diagnostic and prognostic evaluation of DM in patients with primary duodenal cancer. AIM: To develop and evaluate nomograms for predicting the risk of DM and personalized prognosis in patients with duodenal cancer. METHODS: Data on duodenal cancer patients diagnosed between 2010 and 2019 were extracted from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for DM in patients with duodenal cancer, and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors in duodenal cancer patients with DM. Two novel nomograms were established, and the results were evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: A total of 2603 patients with duodenal cancer were included, of whom 457 cases (17.56%) had DM at the time of diagnosis. Logistic analysis revealed independent risk factors for DM in duodenal cancer patients, including gender, grade, tumor size, T stage, and N stage (P < 0.05). Univariate and multivariate COX analyses further identified independent prognostic factors for duodenal cancer patients with DM, including age, histological type, T stage, tumor grade, tumor size, bone metastasis, chemotherapy, and surgery (P < 0.05). The accuracy of the nomograms was validated in the training set, validation set, and expanded testing set using ROC curves, calibration curves, and DCA curves. The results of Kaplan-Meier survival curves (P < 0.001) indicated that both nomograms accurately predicted the occurrence and prognosis of DM in patients with duodenal cancer. CONCLUSION: The two nomograms are expected as effective tools for predicting DM risk in duodenal cancer patients and offering personalized prognosis predictions for those with DM, potentially enhancing clinical decision-making.

Chemical constituents from the roots of Zanthoxylum bungeanum Maxim. and their neuroprotective activities.

Twenty-two isolates, including two previously undescribed compounds identified as benzoyltembamide (1) and P-benzoyphenethyl anisate (21), were isolated and identified from a methanol extract of the roots of Zanthoxylum bungeanum Maxim. (Rutaceae) using diverse chromatographic materials and pre-HPLC. Their structures were elucidated on the basis of spectroscopic and spectrometric data analysis such as HR-ESI-MS, 1D and 2D NMR, IR and UV, as well as single-crystal X-ray diffraction for crystalline compounds. All the compounds (except for compound 16) were isolated from the roots of Z. bungeanum for the first time. Selected compounds were evaluated for their antioxidant activities. Compound 18 attenuated the H2O2-induced cytotoxicity and blocked the accumulation of ROS in SH-SY5Y cells, and exhibited potent neuroprotective activity.