The activation of HAMP promotes colorectal cancer cell proliferation through zinc-mediated upregulation of SMAD4 expression.

Background: Colorectal cancer (CRC) poses a significant challenge in digestive system diseases, and emerging evidence underscores the critical role of zinc metabolism in its progression. This study aimed to investigate the clinical implications of genes at the intersection of zinc metabolism and CRC. Methods: We downloaded CRC prognosis-related genes and zinc metabolism-related genes from public databases. Then, the overlapping genes were screened out, and bioinformatics analysis was performed to obtain the hub gene associated with CRC prognosis. Subsequently, in vitro assays were carried out to investigate the expression of this hub gene and its exact mechanism between zinc metabolism and CRC. Results: HAMP was identified as the hub CRC prognostic gene from overlapping zinc metabolism-related and CRC prognostic genes. In vitro analysis showed HAMP was over-expressed in CRC, and its knockdown inhibited RKO and HCT-116 cell invasion and migration significantly. ZnSO4 induced HAMP up-regulation to promote cell proliferation, while TPEN decreased HAMP expression to inhibit cell proliferation. Importantly, we further found that ZnSO4 enhanced SMAD4 expression to augment HAMP promoter activity and promote cell proliferation in CRC. Conclusions: HAMP stands out as an independent prognostic factor in CRC, representing a potential therapeutic target. Its intricate regulation by zinc, particularly through the modulation of SMAD4, unveils a novel avenue for understanding CRC biology. This study provides valuable insights into the interplay between zinc metabolism, HAMP, and CRC, offering promising clinical indicators for CRC patients. The findings present a compelling case for further exploration and development of targeted therapeutic strategies in CRC management.

IL1A regulates the inflammation in gout through the Toll-like receptors pathway.

Objective: Gout is a dangerous metabolic condition related to monosodium urate (MSU). Our aim is to study the molecular mechanisms underlying gout and to identify potential clinical biomarkers by bioinformatics analysis and experimental validation. Methods: In this study, we retrieved the overlapping genes between GSE199950-Differential Expressed Genes (DEGs) dataset and key module in Weighted Gene Co-Expression Network Analysis (WGCNA) on GSE199950. These genes were then analyzed by protein-protein interaction (PPI) network, expression and Gene Set Enrichment Analysis to identify the hub gene related to gout. Then, the gene was investigated by peripheral blood mononuclear cells (PBMCs), immunoassay and cell experiments like western blotting to uncover its underlying mechanism in gout cells. Results: From the turquoise module and 83 DEGs, we identified 62 overlapping genes, only 11 genes had mutual interactions in PPI network and these genes were highly expressed in MSU-treated samples. Then, it was found that the IL1A (interleukin 1 alpha) was the only one gene related to Toll-like receptor signaling pathway that was associated with the occurrence of gout. Thus, IL1A was determined as the hub gene in this study. In immunoassay, IL1A was significantly positively correlated with B cells and negatively correlated with macrophages. Moreover, IL1A is highly expressed in gout patients,it has a good clinical diagnostic value. Finally, the results of in vitro experiments showed that after knocking down IL1A, the expressions of pro-inflammatory cytokines and Toll-like receptor signaling pathway-related proteins (TLR2, TLR4, MyD88) were all reduced. Conclusion: It is confirmed that IL1A is a promoting gene in gout with a good diagnostic value, and specifically it affects the inflammation in gout through Toll-like receptor pathway. Our research offers fresh perspectives on the pathophysiology of gout and valuable directions for future diagnosis and treatment.

Bioinformatics-based study to detect chemical compounds that show potential as treatments for pulmonary thromboembolism.

The objectives of the present study comprised the recognition of major genes related to pulmonary thromboembolism (PTE) and the evaluation of their functional enrichment levels, in addition to the identification of small chemical molecules that may offer potential for use in PTE treatment. The RNA expression profiling of GSE84738 was obtained from the Gene Expression Omnibus database. Following data preprocessing, the differently expressed genes (DEGs) between the PTE group and the control group were identified using the Linear Models for Microarray package. Subsequently, the protein­protein interaction (PPI) network of these DEGs was examined using the Search Tool for the Retrieval of Interacting Genes/Proteins database, visualized via Cytoscape. The most significantly clustered modules in the network were identified using Multi Contrast Delayed Enhancement, a plugin of Cytoscape. Subsequently, functional enrichment analysis of the DEGs was performed, using the Database for Annotation Visualization and Integrated Discovery tool. Furthermore, the chemical­target interaction networks were investigated using the Comparative Toxicogenomics Database as visualized via Cytoscape. A total of 548 DEGs (262 upregulated and 286 downregulated) were identified in the PTE group, compared with the control group. The upregulated and downregulated genes were enriched in Gene Ontology terms related to inflammation and eye sarcolemma, respectively. Tumor necrosis factor (TNF) and erb­b2 receptor tyrosine kinase 2 (ERBB2) were upregulated genes that ranked higher in the PPI network (47 and 40 degrees, respectively) whereas C­JUN was the most downregulated gene (46). Small chemical molecules ethinyl (135), cyclosporine (126), thrombomodulin precursor (113) and tretinoin (111) had >100 degrees in the DEG­chemical interaction network. In addition, ethinyl targeted to TNF, whereas TNF and ERBB2 were targeted by cyclosporine, and tretinoin was a targeted chemical of ERBB2. Therefore, cyclosporine, ethinyl, and tretinoin may be potential targets for PTE treatment.

Prediction of neurologic deterioration based on support vector machine algorithms and serum osmolarity equations.

OBJECTIVE: Dehydration on admission is correlated with neurological deterioration (ND). The primary objective of our study was to use support vector machine (SVM) algorithms to identify an ND prognostic model, based on dehydration equations. METHODS: This study included a total of 382 patients hospitalized with acute ischemic stroke. The following parameters were recorded: age, sex, laboratory values (serum sodium, potassium, chlorinum, glucose, and urea), and vascular risk factor data. Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of the BUN/Cr ratio as well as each of 38 equations for predicting ND. We used the Boruta algorithm for feature selection. After optimizing the SVM kernel parameters, we built an SVM model to predict ND and used the test set to obtain predictive values for assessing model accuracy. RESULTS: In total, 102 of 382 patients (26.7%) with acute ischemic stroke developed ND. In all patients, the BUN/Cr ratio and each of 38 equations were significant predictors of ND. Equation 20 [1.86 × Na+ + glucose + urea + 9] yielded the maximum area under the ROC curve, and faired best in terms of prognostic performance (a cutoff value of 284.49 mM yielded a sensitivity of 94.12% and specificity of 61.43%). Equation 32 predicted ND poststroke across population groups, and worked well in older as well as young adults; (a cutoff value of 297.08 mM yielded a sensitivity of 93.14% and specificity of 60.00%). Feature selection by the Boruta algorithm was used to decrease the number of variables from 18 to 5 in the condition. The specificity of test samples for the SVM prediction model increased from 44.1% to 89.4%, and the AUC increased from 0.700 to 0.927. CONCLUSIONS: SVM algorithms can be used to establish a prediction model for dehydration-associated ND, with good classification results.

NPC-26 kills human colorectal cancer cells via activating AMPK signaling.

NPC-26 is novel mitochondrion-interfering compound. The current study tested its potential effect against colorectal cancer (CRC) cells. We demonstrated that NPC-26 induced potent anti-proliferative and cytotoxic activities against CRC cell lines (HCT-116, DLD-1 and HT-29). Activation of AMP-activated protein kinase (AMPK) signaling mediated NPC-26-induced CRC cell death. AMPKα1 shRNA knockdown or dominant negative mutation abolished NPC-26-induced AMPK activation and subsequent CRC cell death. NPC-26 disrupted mitochondrial function, causing mitochondrial permeability transition pore (mPTP) opening and reactive oxygen species (ROS) production. ROS scavengers (NAC or MnTBAP) and mPTP blockers (cyclosporin A or sanglifehrin A) blocked NPC-26-induced AMPK activation and attenuated CRC cell death. Significantly, intraperitoneal injection of NPC-26 potently inhibited HCT-116 tumor growth in severe combined immuno-deficient (SCID) mice. Yet, its anti-tumor activity was significantly weakened against AMPKα1-silenced HCT-116 tumors. Together, we conclude that NPC-26 kills CRC cells possibly via activating AMPK signaling.

Inhibition of mTORC1 renders cardiac protection against lipopolysaccharide.

Sepsis-induced cardiac dysfunction is a severe clinical problem. It is evident that rapamycin can protect heart from pathological injuries. However, there are no data demonstrating rapamycin reverse cardiac dysfunction induced by sepsis. In this study, Lipopolysaccharide (LPS) was administrated to mice and H9c2 cells. After treatment, we further determined cardiac function by echocardiography, ANP, BNP and inflammatory markers by qPCR and apoptosis by TUNEL staining. Moreover, mTORC1 signaling pathway and Akt activity were measured by Western blots. We found that rapamycin attenuated cardiac dysfunction, increase in ANP and BNP as well as apoptosis induced by LPS both in mice and in H9c2 cells. Unexpectedly, LPS did not significantly affect the mRNA levels of TNF-α and IL-6. Furthermore, rapamycin further reduced the decrease in mTORC1 signaling and Akt activity induced by LPS. In conclusion, rapamycin can protect heart from LPS induced damages by inhibition mTORC1 signaling and elevation of Akt activity.