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Background: Curcumin originates from the natural herb turmeric, and its antitumor effects have been known about for a long time. However, the mechanism by which curcumin affects gastric cancer (GC) has not been elucidated ., Aim: To elucidate the potential mechanisms of curcumin in the treatment of GC., Methods: Network pharmacological approaches were used to perform network analysis of Curcumin. We first analyzed Lipinski's Rule of Five for the use of Curcumin. Curcumin latent targets were predicted using the PharmMapper, SwissTargetPrediction and DrugBank network databases. GC disease targets were mined through the GeneCard, OMIM, DrugBank and TTD network databases. Then, GO enrichment, KEGG enrichment, protein-protein interaction (PPI), and overall survival analyses were performed. The results were further verified through molecular docking, differential expression analysis and cell experiments., Results: We identified a total of 48 curcumin-related genes with 31 overlapping GC-related targets. The intersection targets between curcumin and GC have been enriched in 81 GO biological processes and 22 significant pathways. Following PPI analysis, 6 hub targets were identified, namely, estrogen receptor 1 ( ESR1 ), epidermal growth factor receptor ( EGFR ), cytochrome P450 family 3 subfamily A member 4 ( CYP3A4 ), mitogen-activated protein kinase 14 ( MAPK14 ), cytochrome P450 family 1 subfamily A member 2 ( CYP1A2 ), and cytochrome p450 family 2 subfamily B member 6 ( CYP2B6 ). These factors are correlated with decreased survival rates among patients diagnosed with GC. Molecular docking analysis further substantiated the strong binding interactions between Curcumin and the hub target genes. The experimental findings demonstrated that curcumin not only effectively inhibits the growth of BGC-823 cells but also suppresses their proliferation. mRNA levels of hub targets CYP3A4 , MAPK14 , CYP1A2 , and CYP2B6 in BGC-823 cells were significantly increased in each dose group., Conclusion: Curcumin can play an anti-GC role through a variety of targets, pathways and biological processes., Competing Interests: Conflict-of-interest statement: The authors declare that there are no conflicts of interest regarding the publication of this paper. The authors affirm that this research is conducted in an unbiased manner and that the findings and conclusions presented are solely based on scientific merit., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Hepatocellular carcinoma (HCC) is a malignancy found globally. Accumulating studies have shown that long noncoding RNAs (lncRNAs) play critical roles in HCC. However, the function of lncRNA in HCC remains poorly understood., Aim: To understand the effect of lncRNA W42 on HCC and dissect the underlying molecular mechanisms., Methods: We measured the expression of lncRNA W42 in HCC tissues and cells (Huh7 and SMMC-7721) by quantitative reverse transcriptase polymerase chain reaction. Receiver operating characteristic curves were used to assess the sensitivity and specificity of lncRNA W42 expression. HCC cells were transfected with pcDNA3.1-lncRNA W42 or shRNA-lncRNA W42. Cell functions were detected by cell counting Kit-8 (CCK-8), colony formation, flow cytometry and Transwell assays. The interaction of lncRNA W42 and DBN1 was confirmed by RNA immunoprecipitation and RNA pull down assays. An HCC xenograft model was used to assess the role of lncRNA W42 on tumor growth in vivo . The Kaplan-Meier curve was used to evaluate the overall survival and recurrence-free survival after surgery in patients with HCC., Results: In this study, we identified a novel lncRNA (lncRNA W42), and investigated its biological functions and clinical significance in HCC. LncRNA W42 expression was upregulated in HCC tissues and cells. Overexpression of lncRNA W42 notably promoted the proliferative and invasion of HCC, and inhibited cell apoptosis. LncRNA W42 directly bound to DBN1 and activated the downstream pathway. LncRNA W42 knockdown suppressed HCC xenograft tumor growth in vivo . The clinical investigation revealed that HCC patients with high lncRNA W42 expression exhibited shorter survival times., Conclusion: In vitro and in vivo results suggested that the novel lncRNA W42, which is upregulated in HCC, may serve as a potential candidate prognostic biomarker and therapeutic target in HCC patients., Competing Interests: Conflict-of-interest statement: All authors have nothing to disclose., (©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Accumulating evidence has revealed that several long non-coding ribonucleic acids (lncRNAs) are crucial in the progress of hepatocellular carcinoma (HCC)., Aim: To classify a long non-coding RNA, i.e ., lncRNA W5, and to determine the clinical significance and potential roles of lncRNA W5 in HCC., Methods: The results showed that lncRNA W5 expression was significantly downregulated in HCC cell lines and tissues. Analysis of the association between lncRNA W5 expression levels and clinicopathological features suggested that low lncRNA W5 expression was related to large tumor size ( P < 0.01), poor histological grade ( P < 0.05) and serious portal vein tumor thrombosis ( P < 0.05). Furthermore, Kaplan-Meier survival analysis showed that low expression of lncRNA W5 predicts poor overall survival ( P = 0.016)., Results: Gain-of-loss function experiments, including cell counting kit8 assays, colony formation assays, and transwell assays, were performed in vitro to investigate the biological roles of lncRNA W5. In vitro experiments showed that ectopic overexpression of lncRNA W5 suppressed HCC cell proliferation, migration and invasion; conversely, silencing of lncRNA W5 promoted cell proliferation, migration and invasion. In addition, acting as a tumor suppressor gene in HCC, lncRNA W5 inhibited the growth of HCC xenograft tumors in vivo ., Conclusion: These results showed that lncRNA W5 is down-regulated in HCC, and it may suppress HCC progression and predict poor clinical outcomes in patients with HCC. LncRNA W5 may serve as a potential HCC prognostic biomarker in addition to a therapeutic target., (©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.)

Aim: To examine the accuracy of machine learning to relate particulate matter (PM) 2.5 and PM10 concentrations to upper respiratory tract infections (URIs)., Methods: Daily nationwide and regional outdoor PM2.5 and PM10 concentrations collected over 30 consecutive days obtained from the Taiwan Environment Protection Administration were the inputs for machine learning, using multilayer perceptron (MLP), to relate to the subsequent one-week outpatient visits for URIs. The URI data were obtained from the Centers for Disease Control datasets in Taiwan between 2009 and 2016. The testing used the middle month dataset of each season (January, April, July and October), and the training used the other months' datasets. The weekly URI cases were classified by tertile as high, moderate, and low volumes., Results: Both PM concentrations and URI cases peak in winter and spring. In the nationwide data analysis, MLP machine learning can accurately relate the URI volumes of the elderly (89.05% and 88.32%, respectively) and the overall population (81.75% and 83.21%, respectively) with the PM2.5 and PM10 concentrations. In the regional data analyses, greater accuracy is found for PM2.5 than for PM10 for the elderly, particularly in the Central region (78.10% and 74.45%, respectively), whereas greater accuracy is found for PM10 than for PM2.5 for the overall population, particularly in the Northern region (73.19% and 63.04%, respectively)., Conclusion: Short-term PM2.5 and PM10 concentrations were accurately related to the subsequent occurrence of URIs by using machine learning. Our findings suggested that the effects of PM2.5 and PM10 on URI may differ by age, and the mechanism needs further evaluation., Competing Interests: Conflict-of-interest statement: The authors declare that they have no conflicts of interest.

Aim: To compare the gene expression profile in a pair of HBV-infected twins., Methods: The gene expression profile was compared in a pair of HBV-infected twins., Results: The twins displayed different disease outcomes. One acquired natural immunity against HBV, whereas the other became a chronic HBV carrier. Eighty-eight and forty-six genes were found to be up- or down-regulated in their PBMCs, respectively. Tumor necrosis factor-alpha-induced protein 1 (TNF-alphaIP1) that expressed at a higher level in the HBV-immune twins was identified and four pairs of siblings with HBV immunity by RT-PCR. However, upon HBV core antigen stimulation, TNF-alphaIP1 was downregulated in PBMCs from subjects with immunity, whereas it was slightly upregulated in HBV carriers. Bioinformatics analysis revealed a K+ channel tetramerization domain in TNF-alphaIP1 that shares a significant homology with some human, mouse, and C elegan proteins., Conclusion: TNF-alphaIP1 may play a role in the innate immunity against HBV.