Current medicinal chemistry最新文献

Introduction: Follicular lymphoma (FL) is the most prevalent form of indolent lymphoma, characterized by intermittent relapse and remission periods. This study aims to identify potential biomarker genes for FL and elucidate their roles in the disease.

Methods: FL-related microarray datasets were downloaded from the Gene Expression Omnibus database. Differential expression and weighted gene co-expression network analyses (WGCNA) were conducted to identify potential hub genes. Various machine learning algorithms were applied to improve gene selection accuracy and predictive performance. Mendelian randomization (MR) analysis was carried out to identify genes with causal relationships to FL. Functional enrichment analysis was performed to explore the underlying mechanisms. Finally, the identified biomarker gene was validated in clinical samples using quantitative real-time PCR.

Results: A total of 60 hub genes were identified through differential expression analysis and WGCNA. Subsequently, 11 characteristic genes were identified using machine learning algorithms. MR analysis revealed 173 genes with causal effects on FL, leading to the identification of one key co-expressed gene, NDRG family member 2 (NDRG2), as a potential biomarker for FL. NDRG2 demonstrated strong predictive performance. Functional enrichment analysis revealed significant associations between NDRG2 and immune-related pathways in FL. Validation in clinical samples confirmed the relevance of NDRG2 as a biomarker.

Discussion: The integration of machine learning and MR successfully identified NDRG2 as a promising biomarker with a causal relationship to FL. Validation in clinical samples reinforced the reliability of these findings in clinical practice.

Conclusion: By combining machine learning, MR, and experimental validation, NDRG2 was identified and validated as a promising biomarker for FL.

Introduction: This study aimed to explore potential causal relationships between mitochondria- related genes and irritable bowel syndrome (IBS) using integrative multi-omics analysis.

Methods: Genome-wide association study data for IBS (1,480 cases and 454,868 controls) were integrated with mitochondrial gene data from DNA methylation quantitative trait loci, blood expression quantitative trait loci, and protein quantitative trait loci. Molecular trait associations with IBS were assessed through summary-based Mendelian randomization and co-localization analyses. Steiger filtering analysis was applied to identify causal directions, and candidate genes were independently replicated by two-sample MR in the FinnGen R11 cohort.

Results: Three primary genes supported by multi-omics evidence-CASP3, GATM, and PDK1-were identified. Increased CASP3 methylation, expression, and protein were positively associated with IBS risk, indicating pro-apoptotic and pro-inflammatory mechanisms, whereas elevated GATM expression and protein were negatively associated, consistent with a protective role via creatine-mediated energy homeostasis.

Discussion: Additionally, 19 genes were classified as secondary evidence genes and 5 as tertiary evidence genes. Among these, genes such as ACAD10 and MSRA were validated using FinnGen data.

Conclusion: This study represents the first application of multi-omics techniques to elucidate the relationship between mitochondrial genes and IBS. The findings indicate multiple candidate pathogenic genes and highlight the role of mitochondrial dysfunction in IBS pathogenesis. These findings offer new opportunities for the discovery of IBS biomarkers and the development of therapeutic strategies.

Objective: This study aimed to evaluate cyclophilin (CypA) levels in patients with diabetes mellitus (DM) before and after treatment. Metabolic variables, such as weight, blood pressure, and plasma glucose, were assessed in these patients.

Method: This prospective cross-sectional study was conducted over 24 weeks. We included 38 patients with DM. After confirming the diagnosis of type 2 diabetes, SGLT2i (empagliflozin vs dapagliflozin) therapy was prescribed to the patients. Weight, body mass index (BMI), waist circumference, body fat ratio, fasting plasma glucose, glycated hemoglobin (HbA1c, %), and CypA levels were measured at 0, 12, and 24 weeks. Patients in the drug subgroup were divided into 2 groups: Empagliflozin (Empa, n=16) and Dapagliflozin (Dapa, n=22).

Results: Weight (p<0.001), body mass index (p<0.001), percentage of body fat (p<0.001), diastolic blood pressure (p=0.006), fasting plasma glucose (p<0.001), HbA1c (p<0.001), serum creatinine (p<0.001), and CypA (p<0.001) levels after the SGLT2i therapy were statistically decreased compared to pre-treatment values in all patients. When comparing drug subgroups, significant decreases in weight (p=0.013) and percentage body fat (p=0.01) were observed in the Empa group compared with the Dapa group at 24 weeks. Changes in FPG (p=0.399), HbA1c (p=0.102), and CypA (p=0.329) between the two groups seemed to be similar.

Conclusion: Beyond the improvement of metabolic parameters, SGLT2 treatment reduced CypA levels in patients with DM regardless of drug subgroups. These drugs may further prevent the presence of cardiovascular diseases.

Introduction: Diabetes mellitus affects the body's ability to regulate glucose and maintain insulin homeostasis. It has been linked to complications in the heart, kidneys, eyes, and other organs. Recent studies have reported that triazole derivatives can act as antidiabetic drugs. Therefore, this study aimed to evaluate the effects of two newly synthesized triazole derivatives (MMTN and MPTN) of nalidixic acid on streptozotocin (STZ)-induced diabetes in mice.

Method: Nalidixic acid was transformed into 1-ethyl-3-[5-mercapto-4-methyl-(4H)-1,2,4- triazol- 3-yl]-7-methyl-1,8-naphthyridin4(1H)-one (MMTN) and 1-ethyl-3-[5-mercapto- 4-phenyl-(4H)-1,2,4-triazol-3-yl]-7-methyl-1,8-naphthyridin-4(1H)-one (MPTN), through a multistep synthesis process. Forty adult male mice were divided into four groups (n=10): a control group, a diabetic group, a diabetic group treated with MMTN (100 mg/kg i.p), and a diabetic group treated with MPTN (50 mg/kg i.p). Diabetes was induced by intraperitoneal injection of STZ (50 mg/kg) for five consecutive days.

Results: After 18 days, serum and pancreas samples were collected for analysis. Serum glucose levels were increased, pancreatic total antioxidant capacity (TAC) was decreased, and pancreatic malondialdehyde (MDA) levels were increased in the diabetic group.

Discussion: However, the treatment of diabetic mice with the two compounds caused a notable reduction in blood glucose levels, a rise in serum insulin levels, a decrease in pancreatic MDA, and an increase in TAC levels. Furthermore, pancreatic and duodenal homeobox 1 gene (PDX-1) and insulin 1(INS-1) mRNA expression levels in the pancreas were upregulated in the diabetic + MMTN or MPTN-treated groups.

Conclusion: The synthetic compounds exhibited significant anti-hyperglycemic and antioxidant activity, protected and enhanced the function of pancreatic β-cells, and stimulated insulin secretion.

Background: Papillary thyroid carcinoma (PTC), the most common thyroid malignancy, presents with multiple variants. This study aimed to identify potential biomarkers and therapeutic candidates for PTC through computational analyses and molecular docking.

Methods: Gene expression data related to PTC were obtained from the TCGA-THCA and GEO datasets (GSE35570 and GSE33630) to identify differentially expressed genes (DEGs). Functional enrichment analysis was performed on the DEGs, followed by construction of a protein-protein interaction (PPI) network. Hub genes were identified using recursive feature elimination (RFE) and LASSO regression analyses. A nomogram incorporating these hub genes was developed, and its diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Furthermore, the relationship between hub genes and immune cell infiltration was investigated. Potential drug candidates targeting the hub genes were predicted and validated through molecular docking.

Results: Common DEGs across the three datasets were enriched in pathways such as ECM-receptor interaction, proteoglycans in cancer, and cell adhesion molecules. Significantly enriched GO terms included 'binding,' 'receptor activity,' 'integral component of membrane,' 'cytoplasm,' 'cell adhesion,' and 'immune response.' A PPI network was constructed by intersecting the common DEGs with PTC-related targets. Machine learning algorithms identified three hub genes: SRY-box transcription factor 4 (SOX4), cyclin D1 (CCND1), and lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1). These hub genes exhibited differential expression in PTC and were used to construct a reliable diagnostic model. Furthermore, molecular docking revealed stable binding between CCND1 and Tipifarnib, suggesting potential therapeutic relevance.

Discussion: While previous studies have applied bioinformatics and molecular docking in PTC research, this study uniquely integrates both approaches to identify the hub gene CCND1 and its potential targeting drug, Tipifarnib, as promising molecular markers and therapeutic candidates for PTC.

Conclusion: The hub gene CCND1 and its targeting drug candidate Tipifarnib may contribute to PTC treatment.

Gene therapy involves the modification of genetic material to correct or compensate for defective genes, thereby aiming to treat or prevent various diseases, including hepatic disorders. Recent advancements in non-viral nanocarrier systems, such as polymeric nanoparticles, lipid-based nanocarriers, and metal-organic frameworks, have emerged as promising alternatives for liver-targeted gene delivery. These systems offer several advantages over viral vectors, including improved safety profiles, greater payload capacity, enhanced specificity, and reduced immunogenicity. This review highlights recent developments in nanocarriers for hepatic gene delivery. We discuss commonly used non-viral approaches, emphasizing their respective strengths and limitations. Furthermore, the review examines studies on gene delivery to the liver, exploring the design of various platforms, their mechanisms of action, and the associated challenges.

Licochalcone A (Lic A) is a natural chalcone compound extracted from Glycyrrhiza inflata Batal, which exhibits a broad spectrum of pharmacological activities, including anti-inflammatory, antioxidant, anti-tumor, analgesic, hepatoprotective and antibacterial properties. Regarding its pharmacological effects, Lic A demonstrates inhibitory effects on various tumors, such as hepatocellular carcinoma, colorectal carcinoma, and leukemia. These effects are achieved by modulating key signaling pathways, including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), mitogen- activated protein kinase (MAPK), and phosphatidylinositol 3-Kinase (PI3K)/Protein Kinase B (Akt). However, the therapeutic potential of Lic A is remarkably hampered by its poor aqueous solubility and low permeation efficiency, which lead to inadequate absorption and poor bioavailability, posing formidable challenges for both oral and transdermal delivery. To address these limitations, advanced technologies such as micelles, mesoporous silica nanoparticles, cell-penetrating peptides, self-microemulsifying drug delivery systems, and eutectogels have been employed to enhance the solubility, permeability, and bioavailability of Lic A, thereby expanding its potential applications. This review aims to summarize the pharmacological effects, signal pathways, and mechanisms of action of Lic A. Moreover, it discusses recent research progress in improving its oral and transdermal delivery efficiency, further summarizing its clinical application and development prospects. Collectively, the work provides a comprehensive reference and methodological guidance for in-depth investigations of Lic A, as well as the exploration and formulation optimization of other flavonoid ingredients.

Introduction: Curcuma longa, commonly known as turmeric, contains curcumin, which is its main compound and has been reported to possess a wide variety of pharmacological activities, such as anti-carcinogenic, anti-malarial, antioxidant, antibacterial, anti-mutagenic, anti-inflammatory, and immunomodulatory effects. Even though it has many strong biological properties, curcumin lacks solubility, which affects its clinical efficacy. DK1 is a curcumin analogue that has been found to possess selective cytotoxicity on breast cancer cells compared to normal breast cells; however, its effectiveness in colon cancer has yet to be validated. This study was performed to investigate the effects of DK1 on colon cancer using an in vivo model in terms of its anti-apoptotic, immunoregulatory, and antioxidant potential. The pathways affected by the DK1 treatment were also evaluated.

Methods: In this study, male BALB/c mice induced with colon cancer were utilized, and the resulting tumours and spleen were subjected to TUNEL, immunophenotyping, and several antioxidant assays, such as nitric oxide, malondialdehyde, and superoxide dismutase, as well as gene and protein expression analyses.

Results: K1 treatment led to tumor shrinkage, an increase in apoptotic tumor cells, and elevated populations of helper and cytotoxic T cells by 5% and 3%, respectively. Besides that, the NO and MDA levels were also significantly reduced. This study also observed dysregulations in several oncogenes in the VEGF pathway, such as CMYC, iNOS, and IL-1β genes, which are involved in angiogenesis and inflammation.

Discussion: The effects of DK1 treatment included antitumor and anti-inflammatory properties against the inoculated CT26 tumour. DK1 showed potential in regulating the inflammation via the VEGF pathway by the significant downregulation of TNF-α and IL-1β pro-inflammatory genes, as well as PTX3, OPN, and serpin-E1 pro-angiogenic proteins.

Conclusion: The results suggested that DK1 may potentially function as an immunoregulator and anti-cancer agent for colon cancer therapy.

Introduction: Ischemic stroke (IS) is a major cause of death and disability worldwide. The transcriptional mechanism of neutrophil extracellular trap-related genes (NRGs) and their diagnostic potential remain unknown. This study aims to explore the mechanism of NRGs in IS through machine learning and Single-cell RNA sequencing (scRNA-seq).

Methods: We conducted differential analysis and functional enrichment analysis on the GEO dataset. Machine learning algorithms were used to identify NRGs related to IS. ScRNA-seq analysis was employed to verify the expression of NRGs in different cell types, and cellchat was used to explore the interactions between cell types in the IS. The expression of Eno1 was also verified in the mouse model of middle cerebral artery occlusion (MCAO).

Results: We identified 26 differentially expressed NRGs (DE-NRGs). The diagnostic models constructed from five DE-NRGs (ENO1, HMGB1, ILK, ORAI1, SUCNR1) demonstrated high predictive ability. Single-cell analysis revealed that NRGs were highly expressed in the IS group. The experiment verified the significant upregulation of Eno1.

Discussion: This study employed machine learning and scRNA-seq to identify the DENRGs- related diagnostic model, providing a certain theoretical basis for IS risk stratification. More experiments are needed to verify the role of DE-NRGs in IS in the future.

Conclusion: This study identified DE-NRGs with diagnostic capabilities in IS and verified their high expression through scRNA and experimental methods. DE-NRGs may be potential therapeutic targets for IS.