Increasing evidence demonstrated that the ketogenic diet (KD) played a positive effect on cancer treatment. However, no systematic review and bibliometric analysis were conducted in this field. This study aimed to explore the current status, and reveal the potential trends and hotspots to provide a reference for future research. Publications were extracted from the Web of Science Core Collection. CiteSpace (5.6.R3) software and the website of bibliometrics were used for visual analysis. A total of 500 publications with 334 articles and 166 reviews were included, with the timespan of 2012 to 2021. The United States was the most productive country. Majority of the top 10 institutions were from the United States, and Harvard University was the top-contributing institution. The most prolific author and the co-cited author was Thomas N Seyfried from Boston College. The highest cited reference was published in PLoS ONE, authored by Abdelwahab Mohammed G, with 161 citations. Glioma and breast cancer were the most common types of cancer in this field, while hepatocellular carcinoma and pancreatic cancer were the new hotspots. The anti-tumor mechanism of KD mainly focused on regulating metabolism, decanoic acid, oxidative stress, fatty acid oxidation, and cell apoptosis. Additionally, the presence of “chemotherapy” and “radiotherapy” in the keywords indicated that KD combined with anti-tumor research was a topic, while “immunotherapy” has became a recent frontiers. Notably, as a metabolic therapy, KD was deserved more attention in the treatment of hepatocellular carcinoma and pancreatic cancer, and KD combined with immunotherapy was the new hotspot and frontier. Additionally, more molecular studies and high-quality uniformly, randomized, controlled clinical trials are urgently warranted to evaluate the effect of KD in multiple cancers.
Thyroid cancer is the most common form of endocrine cancer around the world, and among which papillary thyroid carcinoma (PTC) is the most ubiquitous pathological sub-kind. Sushi repeat-containing protein X-linked 2 (SRPX2) was reported to be an independent prognostic factor and significantly overexpressed in advanced PTC patients. However, the biological functions of SRPX2 remain ambiguous in PTC. Here, we explored SRPX2 expression profiles and functions in PTC, finding that SRPX2 expression was remarkably upregulated in PTC tissues and cell lines. Further colony formation, CCK-8, as well as transwell assay, suggested that SRPX2 silencing remarkably dampened PTC growth and migration. Mouse xenograft models were established to find that SRPX2 silence remarkably suppressed PTC proliferation and migration in vivo. Following mechanism studies revealed that SRPX2 realized its functions in the PTC process partially through activating the Focal adhesion kinase (FAK) phosphorylation. In conclusion, this study investigated the functions and mechanisms of the SRPX2/FAK pathway in PTC progression. SRPX2 could act as a prospective biologic signature and therapeutic target molecule for PTC.
ObjectiveThis study aims to analyze the efficacy and mechanism of action of the Shunaoxin pill in preventing cognitive impairment in diabetic patients using network pharmacology.MethodsThe main active compounds of the Shunaoxin pills and their action targets were identified via the TCMSP and Batman-TCM databases. The GEO database was used to identify the genes in type 2 diabetic individuals associated with cognitive impairment. Subsequently, a common target protein-protein interaction (PPI) network was constructed using the STRING database, and targets associated with diabetes and cognitive impairment were screened by performing a topological analysis of the PPI network. The AutoDock Vina software was used for molecular docking to evaluate the reliability of the bioinformatic analysis predictions and validate the interactions between the active ingredients of the Shunaoxin pill and proteins associated with diabetes and cognitive impairment.ResultsBased on the TCMSP and Batman-Tcm platform, 48 active ingredients of the Shunaoxin pill were identified, corresponding to 222 potential action targets. Further analysis revealed that 18 active components of the Shunaoxin pill might contribute to cognitive impairment in type 2 diabetic patients. Molecular docking simulations demonstrated that the active ingredients of the Shunaoxin pill (hexadecanoic acid, stigmasterol, beta-sitosterol, and angelicin) targeted four core proteins: OPRK1, GABRA5, GABRP, and SCN3B.ConclusionActive ingredients of the Shunaoxin pill may alleviate cognitive impairment in diabetic patients by targeting the proteins OPRK1, GABRA5, GABRP, and SCN3B.
ObjectiveThrough transcriptomic and metabolomic analyses, this study examined the role of high-fiber diet in obesity complicated by diabetes and neurodegenerative symptoms.MethodThe expression matrix of high-fiber-diet-related metabolites, blood methylation profile associated with pre-symptomatic dementia in elderly patients with type 2 diabetes mellitus (T2DM), and high-throughput single-cell sequencing data of hippocampal samples from patients with Alzheimer's disease (AD) were retrieved from the Gene Expression Omnibus (GEO) database and through a literature search. Data were analyzed using principal component analysis (PCA) after quality control and data filtering to identify different cell clusters and candidate markers. A protein–protein interaction network was mapped using the STRING database. To further investigate the interaction among high-fiber-diet-related metabolites, methylation-related DEGs related to T2DM, and single-cell marker genes related to AD, AutoDock was used for semi-flexible molecular docking.ResultBased on GEO database data and previous studies, 24 marker genes associated with high-fiber diet, T2DM, and AD were identified. Top 10 core genes include SYNE1, ANK2, SPEG, PDZD2, KALRN, PTPRM, PTPRK, BIN1, DOCK9, and NPNT, and their functions are primarily related to autophagy. According to molecular docking analysis, acetamidobenzoic acid, the most substantially altered metabolic marker associated with a high-fiber diet, had the strongest binding affinity for SPEG.ConclusionBy targeting the SPEG protein in the hippocampus, acetamidobenzoic acid, a metabolite associated with high-fiber diet, may improve diabetic and neurodegenerative diseases in obese people.
Background Unstable intracranial aneurysms (UIAs) are more likely to rupture and cause serious consequences. Evaluating the stability of unruptured aneurysms facilitates clinical management stratification. Purpose To compare and evaluate the predictive performance of qualitative and quantitative wall enhancement (aneurysmal wall enhancement [AWE], circumferential aneurysmal wall enhancement [CAWE], wall enhancement ratio [WER]) on high-resolution magnetic resonance imaging (MRI) of the vessel wall to predict the presence of UIA. Material and Methods Original articles describing the depiction of aneurysmal wall enhancement on 3.0-T or 1.5-T high-resolution vessel wall imaging were retrieved from the Web of Science, Medline/PubMed, the Cochrane Library, and EMBASE databases up to 15 February 2022. The combined sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated, and meta-regression analysis was performed. Results In total, 12 original articles involving 1619 intracranial aneurysms (IAs) were included. The combined sensitivity and specificity of AWE, CAWE, and WER were 91% and 67%, 59% and 83%, and 86% and 75%, respectively, in the diagnosis of UIA. The summary AUC values of these items were, in order from high to low, 0.88 (WER), 0.84 (AWE), and 0.77 (CAWE), and the differences among them were significant ( z = 2.976, P = 0.003 and z = 2.950, P = 0.003). The meta-regression analysis identified average size and 2D/3D magnetic imaging technology as possible sources of heterogeneity. Conclusion Qualitative and quantitative wall enhancement showed moderate accuracy in predicting UIA, and WER had the highest accuracy among them in this meta-analysis. Two covariates were found to explain the heterogeneity.
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