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At least 397 records · Page 22Linked to original sources
PubMed2005

Data mining of the transcriptome of Plasmodium falciparum: the pentose phosphate pathway and ancillary processes.

The general paradigm that emerges from the analysis of the transcriptome of the malaria parasite Plasmodium falciparum is that the expression clusters of genes that code for enzymes engaged in the same cellular function is coordinated. Here the consistency of this perception is examined by analysing specific pathways that metabolically-linked. The pentose phosphate pathway (PPP) is a fundamental element of cell biochemistry since it is the major pathway for the recycling of NADP+ to NADPH and for the production of ribose-5-phosphate that is needed for the synthesis of nucleotides. The function of PPP depends on the synthesis of NADP+ and thiamine pyrophosphate, a co-enzyme of the PPP enzyme transketolase. In this essay, the transcription of gene coding for enzymes involved in the PPP, thiamine and NAD(P)+ syntheses are analysed. The genes coding for two essential enzymes in these pathways, transaldolase and NAD+ kinase could not be found in the genome of P. falciparum. It is found that the transcription of the genes of each pathway is not always coordinated and there is usually a gene whose transcription sets the latest time for the full deployment of the pathway's activity. The activity of PPP seems to involve only the oxidative arm of PPP that is geared for maximal NADP+ reduction and ribose-5-phosphate production during the early stages of parasite development. The synthesis of thiamine diphosphate is predicted to occur much later than the expression of transketolase. Later in the parasite cycle, the non-oxidative arm of PPP that can use fructose-6-phosphate and glyceraldehyde-3-phosphate supplied by glycolysis, becomes fully deployed allowing to maximize the production of ribose-5-phosphate. These discrepancies require direct biochemical investigations to test the activities of the various enzymes in the developing parasite. Notably, several transcripts of PPP enzyme-coding genes display biphasic pattern of transcription unlike most transcripts that peak only once during the parasite cycle. The physiological meaning of this pattern requires further investigation.

Animals↗
PubMed2005

DNA microarrays and data mining to study hepatic fibrosis.

The pathogenesis of liver fibrosis has evolved dramatically in recent years. Hepatic stellate cells (HSCs) have been recognized as the main fibrogenic cells in the injured liver, and key fibrogenic cytokines have been identified. We propose the use of DNA microarrays to study changes in gene expression in activated HSCs and in fibrotic livers in order to identify key genes involved in liver fibrosis. For this purpose, RNA can be extracted from both cultured cells and liver tissue. The target RNA is hybridized to probes, which are gene-specific sequences immobilized on chips. The hybridization signal is assessed using a confocal laser scanner. Comparison of hybridization signals and patterns allows the identification of mRNAs that are differentially expressed. Statistical analysis enables classification and clustering of genes according to their up- or downregulation. By using this powerful technique, we have identified genes that are differentially regulated in both HSCs and the fibrotic human liver.

Computational Biology↗
PubMed2026

Acupoint Selection Patterns and Potential Mechanisms of Acupuncture in Knee Osteoarthritis: A Combined Data Mining and Network Pharmacology Study.

OBJECTIVE: To identify the core acupoint prescription and Kellgren-Lawrence (K-L) grade-dependent compatibility patterns of acupuncture for KOA through complex network analysis, and to predict the potential molecular mechanisms underlying the core prescription via network pharmacology. METHODS: Literature was retrieved from PubMed, EMbase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, and SinoMed (inception to September 3, 2025). Frequency, association rule, complex network, and K-L grade subgroup analyses were applied. Potential targets of the core prescription were identified via network pharmacology and intersected with disease targets from OMIM, Therapeutic Target, GeneCards, and DrugBank. A protein-protein interaction (PPI) network was constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the potential molecular mechanisms. RESULTS: We included 522 studies, yielding 582 prescriptions involving 123 acupoints. The core prescription comprised 24 acupoints, including Dubi (ST35), Neixiyan (EX-LE4), Liangqiu (ST34), Xuehai (SP10), Zusanli (ST36), Yanglingquan (GB34), Yinlingquan (SP9), among others. K-L subgroup analysis revealed ST35, GB34, SP9, and SP10 as universal core acupoints. The mild-to-moderate subgroup mainly used local acupoints, while the moderate-to-severe subgroup centered on ST35, with increased distal acupoint usage and higher degree values. Network pharmacology analysis identified 77 overlapping targets. Core targets included tumor necrosis factor (TNF), interleukin 6 (IL6), interleukin 1 beta (IL1B), tumor protein p53 (TP53), matrix metallopeptidase 9 (MMP9), signal transducer and activator of transcription 3 (STAT3), transforming growth factor beta 1 (TGFB1), caspase 3 (CASP3), and B-cell lymphoma 2 (BCL2), which were enriched in inflammation and immunity, cartilage metabolism, and tissue repair pathways. CONCLUSION: The core acupoint prescription for KOA features local acupoints combined with distal ones, exhibiting distinct patterns across K-L grades. Our computational findings suggest that core acupoints may potentially delay knee joint degeneration by synergistically regulating inflammation, cartilage metabolism, apoptosis, and tissue repair, although these predictions require experimental validation. These findings provide preliminary evidence and a theoretical basis for standardized clinical point selection and further mechanistic research.

KOA↗
PubMed2005

Approach to novel functional foods for stress control: 1. Toward structure-activity relationship and data mining of food compounds by chemoinformatics.

Over the past several decades, thousands of natural organic compounds have been isolated from foods, and the information about their structures and biological activities has been accumulated. Despite the long research history of food products and their potential great promise as a medicine and functional food, the systematic research and development have not been carried out extensively. For understanding of the comprehensive structure-activity relationship, we have developed the database system of flavonoids, which are frequently found in vegetables and fruits. We also plan to execute a virtual screening of flavonoids with antidepressant activity by using the database and an advanced chemoinformatic tool. In this section, we will briefly describe (1) flavonoid database and (2) virtual screening of antidepressant compounds.

Antidepressive Agents↗