Current Medicinal Chemistry - Online First

The coronavirus 3C-like protease (3CLpro) is essential for SARS-CoV-2 replication, making it a key target for antiviral drug development. Natural products represent a valuable source of bioactive compounds. This study aimed to identify novel 3CLpro inhibitors from natural compounds through a combination of virtual screening and experimental validation.

Recombinant 3CLpro was expressed, purified, and evaluated for enzymatic activity using Fluorescence Resonance Energy Transfer (FRET) assays under optimized conditions. Out of 583 virtually screened compounds, 30 were selected for experimental validation. Epitheaflagallin 3-O-gallate (ETFGg) was further analyzed for binding interactions using Molecular Dynamics (MD) simulations.

ETFGg exhibited strong binding affinity (−66.90 kcal/mol) and inhibitory activity (IC50 = 8.73 ± 2.30 μM) against 3CLpro. MD simulations revealed stable interactions with key residues (HIE163, THR190, GLN192) in the 3CLpro active site.

Our findings demonstrate that ETFGg is a potent and stable inhibitor of SARS-CoV-2 3CLpro, with a binding profile distinct from known inhibitors such as ebselen. The substrate inhibition kinetics observed suggest a novel allosteric mechanism, which may provide a new strategy for targeting 3CLpro. This study supports the value of natural product libraries combined with computational and FRET-based screening for discovering antiviral leads.

ETFGg was identified as a promising 3CLpro inhibitor with high binding stability, highlighting its potential as a lead compound for the development of anti-COVID-19 drugs.

Lung cancer is a leading cause of cancer-related morbidity and mortality. The development and evaluation of effective treatment strategies for lung cancer are of high clinical importance. Everolimus (Eve) has been shown to upregulate the expression of phosphatases and inhibit the migration and proliferation of A549 cancer cells. The present study focuses on the synthesis of biodegradable bovine serum albumin (BSA) nanoparticles for the loading and delivery of Eve.

In the desolvation process, Eve molecules were kept in the BSA system. The physicochemical properties of the Eve drug containing BSA nanoparticles (Eve@BSA) have been exactly characterized. The loading and release assays of Eve were also studied at different glutaraldehyde percentages, times, and solvents.

Field emission scanning electron microscopy (FE-SEM) analysis of BSA nanoparticles revealed a spherical morphology with an average size of 93.7 ± 3.7 nm. The results demonstrated that BSA nanoparticles are highly efficient carriers, achieving an Eve loading efficiency of approximately 54% at 4% glutaraldehyde. The release of Eve from the BSA nanoparticles was dependent on the solvent and duration of incubation. According to the MTT assay, Eve@BSA exhibited low cytotoxicity and high biocompatibility against L929 fibroblast cells. In contrast, the cytotoxicity of Eve@BSA against A549 cells (IC50 ≈ 47 μg/mL) was significantly higher than that of free Eve (IC50 ≈ 283 μg/mL) after 48 hours.

The synergistic effects of Eva@BSA nanoformulation due to functional groups-rich BSA seemed to improve in vitro antiproliferation efficacies compared with the single treatment of Eve.

The findings confirm the synergistic anticancer effect of Eve@BSA, indicating that this nanosystem may serve as a promising candidate for the treatment of lung cancer.

The development and progression of non-small cell lung cancer (NSCLC) are intricately linked to immune cell activation, but its related signature has not been reported.

This study combines in silico and in vitro approaches. TCGA-NSCLC and Gene Expression Omnibus (GEO) datasets were utilized to develop and validate a prognostic signature based on cell activation genes. The signature’s validity was assessed through the identification of genomic, transcriptomic, tumor microenvironment (TME), and single-cell infiltration characteristics. The function of the candidate gene RORA was verified using CCK8, apoptosis, colony formation, wound healing, and transwell assays. The detailed mechanism of RORA was investigated through ChIP-PCR, luciferase assays, Western blot, and ROS detection.

The prognostic signature was constructed from TCGA-NSCLC datasets and validated in six independent datasets (GSE30219, GSE33072, GSE37745, GSE41271, GSE42127, GSE50081). The signature was associated with LRP1B and RYR2 mutations, NSCLC-related pathways, drug response, and immune cell infiltration. The candidate gene RORA significantly inhibits the proliferation and migration abilities of NSCLC cell lines (A549 and NCI-H1299). Furthermore, the transcription factor RORA promotes ZNF490 expression, which subsequently inhibits NUDFs expression and oxidative phosphorylation (oxphos).

The signature highlighted its significance with genomic features that were frequently reported as prognostic indicators (LRP1B and RYR2 mutations, cancer-related infiltration and pathway infiltration), and putative treatment response (IC50 in the TCGA dataset). Its detailed mechanism of candidate gene RORA revealed its role in oxphos, highlighting the crosstalk between metabolism and immune activation.

The model is robust and effectively reflects NSCLC heterogeneity while predicting prognosis. RORA promotes the expression of ZNF490 to inhibit NUDFs and oxidative phosphorylation.

Limited studies have explored how ferroptosis and Epithelial-Mesenchymal Transition (EMT) jointly affect the prognosis of Esophageal Squamous Cell Carcinoma (ESCC). This study aimed to develop a clinical prognostic model based on the combined impact of ESCC.

Gene expression levels and clinical data of ESCC patients were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Using Cox regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, we identified nine prognostic genes to build a predictive model. Immune cell infiltration was evaluated using CIBERSORT and single-sample Gene Set Enrichment Analysis methods. Finally, in vitro experiments were conducted to assess the oncogenic effects of ACSL3 and VIM.

We developed a Ferroptosis-EMT Integrated Score (FEIS) based on nine key genes. High-FEIS patients had worse survival, increased immune infiltration, and higher expression of immune checkpoints. A nomogram was built for prognosis prediction, and in vitro studies confirmed the tumor-promoting roles of ACSL3 and VIM.

The FEIS model robustly predicts ESCC prognosis by integrating ferroptosis and EMT, offering novel biomarkers for personalized immunotherapy, though further validation is warranted.

Our study introduced a novel prognostic tool that integrates ferroptosis and EMT-related biomarkers and offers valuable insights for developing personalized treatment strategies for ESCC patients.

This study explored potential atrial fibrillation (AF) risk genes via nicotinamide adenine dinucleotide (NAD⁺) metabolism using tissue samples and the Gene Expression Omnibus (GEO) database.

A cross-sectional study was conducted on atrial tissues from patients undergoing left atrial appendage resection. Whole transcriptome sequencing was performed on 3 AF and 3 control samples. The GSE115574 and GSE79768 datasets were analyzed, yielding 51 NMRGs. DE-mRNAs were screened and overlapped to obtain DE-NMRGs. LASSO and RFE algorithms identified critical genes, and enrichment and drug-prediction analyses were conducted. Gene expressions were validated in 5 additional patients using qRT-PCR.

Three key genes (SLC6A6, ATP1B4, and BEX2) were identified, associated with energy metabolism pathways and potentially influencing AF progression through immune response modulation.

Previous studies reported the role of NAD⁺ metabolism in AF, but its mechanism is unclear. This study identified SLC6A6, ATP1B4, and BEX2 as gene signatures linking NAD⁺ metabolism to AF. These genes are involved in metabolic or electrophysiological processes that can predispose to arrhythmogenesis. However, their specific mechanisms of action remain unclear, and further research is needed.

The study identified three key genes (SLC6A6, ATP1B4, and BEX2) involved in NAD⁺ metabolism, with diagnostic potential for AF patients and associations with energy metabolism and immune infiltration.

Cancer-associated fibroblasts (CAFs) play vital roles in HCC initiation and progression via multicellular, stromal-dependent processes. Despite their acknowledged significance, the comprehensive role of CAF-related gene signatures in HCC remains underexplored. Given the established role of CAFs in HCC progression and therapy resistance, we aimed to develop a CAF-derived gene signature for prognosis prediction.

This comprehensive analysis used RNA sequencing data from The Cancer Genome Atlas database and a validation cohort from the International Cancer Genome Consortium database. Differential gene expression analysis identified CAF-related genes associated with HCC prognosis. A gene signature was developed using the least absolute shrinkage and selection operator algorithm and Cox regression analysis, and its prognostic value was evaluated through Kaplan-Meier survival analysis and receiver operating characteristic curve (ROC) analysis. The signature’s associations with immune cell infiltration, chemotherapeutic response, and functional enrichment were investigated to further evaluate the prognostic value of CAF-related genes.

In total, 256 differentially expressed CAF-related genes were identified between samples with high and low CAF infiltration. After systematic analysis, a prognostic signature, including 23 genes, was constructed. Kaplan-Meier and ROC analyses demonstrated the robust predictive potential of our risk model for patients with HCC. Univariate/multivariate Cox regression analyses further confirmed that the risk model was an independent prognostic factor for HCC in both the testing and validation cohorts. The signature stratified patients into high- and low-risk groups with distinct survival (log-rank p < 0.001), achieving areas under the curve of 0.848 (1 year), 0.795 (3 years), and 0.781 (5 years). Patients in the high-risk group were more responsive to vinblastine, docetaxel, and navitoclax. Patients in the low-risk group had greater chemosensitivity to olaparib. Moreover, the stromal score was significantly higher in the high-risk group. Finally, the signaling pathways enriched in the high-risk group were mainly associated with HCC progression.

We established a CAF-related gene signature model as an independent prognostic predictor for HCC. This model may also guide adjuvant chemotherapy and targeted therapy, though further validation across diverse cohorts is needed to confirm its clinical utility.

The CAF-related gene signature exhibited good predictive potential concerning the prognosis of patients with HCC.

Esophageal cancer (EC) is a significant clinical challenge due to its aggressiveness and poor prognosis. CD47, a transmembrane protein, inhibits macrophage phagocytosis and is linked to tumor advancement and poor outcomes. The interaction between curcumin (CUR) and CD47 and its effects on EC needs further studies.

This study identified common target genes of CUR and EC through network pharmacology, and then found core genes via protein-protein interaction (PPI) analysis. In vitro experiments were conducted to investigate the effects of CUR on cell proliferation, apoptosis, and migration, and to explore the underlying mechanisms. in vivo xenograft experiments were also carried out to evaluate the effects and mechanisms of CUR on tumor growth.

CD47 was highly expressed in EC, and CUR shared ten common target genes with EC. Enrichment analysis and PPI network supported PTGS2 and BAX as core genes. in vitro, CUR could inhibit the proliferation and migration of CD47-overexpressing EC cells and induce apoptosis. In the xenograft model, CUR could inhibit tumor growth (p = 0.0144). The mechanism of CUR may be related to multiple components of the MAPK signaling pathway, especially ERK1/2 and its phosphorylation. Additionally, CUR treatment reduced the COX-2 expression level. Immunohistochemistry showed that both BAX and Bcl-2 proteins were upregulated, but the upregulation of BAX protein was significantly more pronounced than that of Bcl-2.

Our study has confirmed that CUR inhibits CD47-overexpressing esophageal cancer cells. This mechanism may be achieved by blocking ERK1/2 and its phosphorylation, reducing COX2 levels, and enhancing BAX protein expression.

This study highlights CUR's potential in treating EC, particularly in CD47 overexpression cases. These results clarify the molecular interactions and provide a basis for future research on CUR-based therapies targeting EC progression pathways.

Prostate cancer is the fourth most commonly diagnosed cancer worldwide and the eighth leading cause of cancer-related mortality, primarily affecting elderly males. Conventional therapeutic approaches, while effective in some cases, often come with substantial side effects, posing particular challenges for older patients. As a result, the exploration of natural compounds from traditional Chinese medicine (TCM) as potential anticancer agents has gained increasing attention. Sesamin, a dietary lignan found in sesame seeds and frequently used in TCM, has shown promise in preliminary studies for its antioxidant, anti-inflammatory, and potential anticancer properties. However, its specific effects and underlying mechanisms against prostate cancer cells remain inadequately characterized.

This study investigated the anticancer effects of sesamin on human prostate cancer DU145 cells. Cell viability was evaluated using MTT assays. Apoptosis induction and cell cycle distribution were assessed by flow cytometry. Protein expression levels of PPAR-γ, p21, and p53 were measured using Western blotting. Additionally, in silico molecular docking was performed using the LibDock algorithm to evaluate sesamin’s binding affinity with the target proteins PPAR-γ and p21.

Sesamin treatment significantly reduced the viability of DU145 cells in a dose-dependent manner. Flow cytometry revealed increased apoptosis and cell cycle arrest at the G1 phase. Western blot analysis showed upregulated expression of PPAR-γ and p21, while p53 expression remained largely unchanged. Molecular docking analysis demonstrated strong binding affinity of sesamin to PPAR-γ (LibDock score: 125.03) and p21 (LibDock score: 105.45), supporting its involvement in a p53-independent apoptotic mechanism.

The study demonstrates that sesamin exerts significant anticancer effects on prostate cancer DU145 cells by inhibiting cell viability, inducing apoptosis, and causing G1 phase cell cycle arrest. The upregulation of PPAR-γ and p21, coupled with unchanged p53 expression, suggests that sesamin may activate a p53-independent pathway, a valuable feature in treating prostate cancers with defective p53 signaling. Molecular docking results corroborate these findings, indicating direct interactions between sesamin and its molecular targets.

Sesamin exhibits promising antiproliferative and pro-apoptotic activities against DU145 prostate cancer cells. Its potential to act as a G1-phase-specific chemotherapeutic agent via a p53-independent mechanism warrants further investigation and development as a natural candidate for prostate cancer therapy.

Observational studies have suggested associations between circulating metabolites and breast cancer (BC) risk, but the direction and causality of these relationships remain unclear due to confounding and reverse causation. Therefore, we aimed to evaluate the potential causal effects of 1,400 circulating metabolites on BC subtypes using Mendelian randomization (MR) based on GWAS data from European-ancestry populations.

Two-sample and reverse MR analyses were performed to explore potential causal links between metabolites and BC from the FinnGen and Breast Cancer Association Consortium (BCAC) cohorts. The inverse-variance weighted (IVW) approach served as the main analytical method to evaluate these associations. To further ensure the robustness and credibility of the MR findings, sensitivity analyses were conducted, incorporating leave-one-out procedures, the Cochran's Q test, and the MR-Egger intercept test.

Following correction using the False Discovery Rate (FDR) method at a significance level of 0.10, we identified 5alpha-pregnan-3beta,20alpha-diol monosulfate levels (p = 6.7714*10-5, PFDR = 0.0798) and Myristoleate (14:1n5) levels (p =0.0002, PFDR = 0.0798) were associated with an increased risk of ER+ BC. Conversely, the Caffeine to paraxanthine ratio (p =0.0001, PFDR = 0.0798) was associated with a reduced risk. In the reverse MR analysis, interactions were observed between Eicosanedioate (C20-DC) levels, Piperine levels, Caffeine to theobromine ratio, Indolepropionate levels, 1-oleoyl-GPC (18:1) levels, and Oleoylcarnitine levels with BC. Notably, the p-values of intercept terms in MR-Egger regression all exceeded 0.05, suggesting an absence of potential horizontal pleiotropy.

These findings suggested that hormone-related, lipid-related, and diet-derived metabolites might play subtype-specific roles in breast cancer development. The identified metabolites provided mechanistic insights and highlighted potential biological pathways that warrant further functional validation. They may also serve as preliminary biomarkers for future metabolomic and translational research.

Our MR study identified several metabolites that may be causally associated with BC risk. These findings offer potential candidates for further mechanistic investigation and highlight the importance of subtype-specific approaches in metabolomics research.

Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis and a high fatality rate. To predict the prognosis of HNSCC, this study developed a prognostic model based on nitrogen metabolism (NM)-related genes.

This study utilized transcriptomic data and clinical information from HNSCC obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify differentially expressed NM-related genes. Subsequently, an NM-related prognostic risk model was established by integrating univariate Cox regression, LASSO regression, and multivariate Cox regression. Its predictive value was validated using Kaplan-Meier and ROC curves. Further analysis using GSVA and CIBERSORT examined the relationship between the risk model and the tumor microenvironment immune status, while also evaluating chemotherapy drug sensitivity across different risk groups. Finally, protein-protein interaction (PPI) networks and key gene screening were employed, and the functional validation of the core genes was conducted through in vitro experiments.

We identified 10 key NM-related genes (GLS, ASNS, EXT2, HPRT1, SLC7A5, SMS, B3GNT8, GATM, NAGK, and SULT1B1) to construct a prognostic risk model. The GSVA analysis revealed that the low-risk group was enriched in immune-related pathways, while the high-risk group favored metabolic pathways. Additionally, the low-risk group exhibited higher levels of immune cell infiltration. We discovered that gefitinib, belinostat, erlotinib, and phenformin were more effective against cancer cells with lower risk scores. The PPI network screening identified key hub genes, including LORICRIN. Experimental validation demonstrated that LORICRIN overexpression significantly suppressed migration and invasion in HNSCC cells, suggesting its potential tumor-suppressive role in carcinogenesis and progression.

This study emphasizes the links between NM signatures, immune regulation, and signaling pathways, underscoring their potential in the HNSCC mechanism research.

Our study established a NM-related gene signature closely linked to immune microenvironment and drug sensitivity, highlighting potential biomarkers and therapeutic targets for prognosis and personalized therapy in HNSCC.

Osteosarcoma is a highly aggressive cancer with a notably low five-year survival rate. Although aspirin has demonstrated potential in inhibiting the malignant progression of osteosarcoma, the underlying mechanisms remain unclear.

In this study, RNA sequencing (RNA-seq) was employed to identify the downstream targets of aspirin in osteosarcoma cells. Then, we examined the expression and clinical significance of PDE4D using osteosarcoma patient samples, tissue microarrays, and data from the TARGET and GTEx databases. The effects of PDE4D on cell growth and mobility were assessed by CCK-8, colony formation, transwell, and wound-healing assays. To explore how aspirin influenced the NF-κB/p65/PDE4D axis, we performed qRT-PCR, Western blotting, luciferase reporter assays, etc. Additionally, mouse models with subcutaneous tumors were used to confirm the roles of aspirin and PDE4D.

Our results showed that aspirin significantly impeded the proliferation, migration, and invasion of osteosarcoma cells by various functional assays. RNA-seq identified PDE4D as a key target modulated by aspirin treatment in osteosarcoma. Clinically, PDE4D was highly expressed in osteosarcoma cells and tissues, and higher levels of PDE4D were linked to poorer patient outcomes. Functionally, PDE4D served as an oncogene that promoted the malignant traits of osteosarcoma both in vitro and in vivo. Mechanistically, our findings revealed that NF-κB/p65 directly interacted with the core region of the PDE4D promoter, increasing its expression.

The findings of this study reveal a novel mechanism whereby aspirin exerts its anti-tumor effects by inhibiting the NF-κB/p65/PDE4D axis, providing a mechanistic basis for its therapeutic potential. Further validation in different animal models of osteosarcoma is warranted.

Aspirin suppressed the malignant progression of osteosarcoma by targeting the NF-κB/p65/PDE4D axis, positioning PDE4D as a potential therapeutic target for aspirin-based treatment strategies.

Radiotherapy remains a cornerstone of treatment for non-small cell lung cancer (NSCLC). Despite its critical role, the emergence of radiation resistance remains a significant hurdle, often leading to therapeutic failure and disease progression. This research aimed to investigate the expression of Pellino E3 ubiquitin protein ligase family member 3 (PELI3) in NSCLC and examine its involvement in modulating the tumor's response to radiation.

To quantify PELI3 levels in NSCLC tissues, real-time PCR and Western blotting techniques were employed. The effects of silencing PELI3 on cancer cell proliferation were evaluated using CCK-8 and colony formation assays. Furthermore, an in vivo mouse xenograft model was used to corroborate the in vitro results.

PELI3 expression was markedly elevated in NSCLC tumor samples relative to normal tissues and showed a strong association with clinical features, such as tumor volume, lymph node involvement, and radiotherapy responsiveness. Further analysis revealed that PELI3 promoted epithelial-to-mesenchymal transition (EMT) following radiation exposure. Suppressing PELI3 expression mitigated radiation-induced EMT in both cellular and animal models.

Elevated PELI3 promotes radiation-induced EMT and radioresistance in NSCLC. Suppressing PELI3 reverses EMT features and enhances radiosensitivity in vitro and in vivo, highlighting PELI3 as a potential biomarker and therapeutic target to improve radiotherapy outcomes.

These findings suggest that PELI3 could serve as a valuable prognostic marker in NSCLC and may represent a promising target to improve tumor sensitivity to radiotherapy.

This study investigates the therapeutic effects of Osthole and elucidates its mechanisms in oral squamous cell carcinoma (OSCC).

Differential expression analysis was performed, followed by nomogram construction, gene set enrichment analysis, and immune infiltration analysis. Molecular docking was conducted to evaluate binding interactions, and single-cell analysis was performed.

PTGS2 was identified as a key candidate capable of binding with Osthole. Immune infiltration analysis revealed elevated levels of activated inflammatory cells in OSCC. Single-cell analysis further showed high PTGS2 expression in macrophages and mast cells.

This study demonstrates PTGS2’s involvement in OSCC, highlighting its potential as both a biomarker and a therapeutic target.

Osthole can modulate OSCC by targeting PTGS2, providing a theoretical basis for OSCC management.

Centrosome Amplification (CA) is a state where malignant cells contain excessive centrosomes due to cell cycle dysregulation. Altered CA has been observed in Glioblastoma (GBM). This study developed a CA-related gene model to assess the Tumor Immune Microenvironment (TIME) and prognostic outcomes for patients with GBM.

TCGA-GBM and mRNAseq_325 cohorts were obtained from the Chinese Glioma Genome Atlas (CGGA) database. CA-relevant gene modules and feature genes were identified via WGCNA analysis. Key genes were selected to develop a risk model, followed by validation of the model’s performance. We further compared the gene mutation landscape, TIME characteristics, drug sensitivity, and enriched pathways between high- and low-risk patient groups.

The brown module, which showed the highest correlation with CA, was selected to identify CA-related key genes to develop a Riskscore model. The model can accurately categorize patients into high- and low-risk groups and predict their clinical outcomes with precision. Notably, high-risk GBM patients exhibited higher StromalScore and dendritic score, and the Riskscore was positively correlated with fibroblast infiltration. Moreover, patients with different risk levels displayed distinct enriched pathways and gene mutation landscapes. Further, the high-risk group showed an evidently higher CAF score, and the differential relation between drug sensitivity and the Riskscore was detected.

Though CA was altered in GBM, its prognostic utility remained to be explored. The current study addressed this gap by developing a 6-gene risk model capable of predicting the prognosis and TIME of GBM patients.

A CA-related model was constructed to assess the prognosis and TIME of GBM patients, contributing to the management of GBM in clinical practice.

Tic disorders are neuropsychiatric conditions characterized by involuntary motor or vocal tics; however, the mechanisms underlying these disorders and potential therapeutic targets remain unknown. Therefore, this study investigated the mechanisms underlying tic disorders, particularly focusing on the role of mitochondrial energy metabolism, and identified potential targets of traditional Chinese medicine for these disorders.

Mitochondrial energy metabolism-related genes were retrieved from GeneCards and relevant literature. Additionally, Wangwei powder components and their potential targets were obtained from the TCMSP, HERB, and PubChem databases. Bioinformatic analysis was employed to identify key genes and mechanisms involved in tic disorders.

Notably, 210 target genes of Wangwei powder, 365 mitochondrial energy metabolism-related genes, and 2020 differentially expressed genes in the tic disorder vs. control groups were identified. Based on the intersections of the differentially expressed genes, mitochondrial energy metabolism-related genes, and target genes, aldehyde dehydrogenase 2 (Aldh2), acetyl-CoA acetyltransferase 1 (Acat1), aldehyde dehydrogenase 1a1 (Aldh1a1), and adenylate kinase 2 (Ak2) were identified as key genes in tic disorder pathophysiology. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the key genes were mainly involved in liver development, cellular detoxification of aldehydes, pyruvate metabolism, and fatty acid degradation pathways. Additionally, immune infiltration analysis highlighted notable discrepancies in immune cell populations between the tic disorder and control groups.

Aldh2, Acat1, Aldh1a1, and Ak2 demonstrate potential as therapeutic targets for TD in WWS. The role of Acat1 in immune modulation and disease progression highlights its promise for immunotherapy. However, further experimental validation is needed to address study limitations.

The results indicate that the key genes (Aldh2, Acat1, Aldh1a1, and Ak2) play a crucial role in the pathogenesis of tic disorders through metabolic pathways and immune cell regulation.

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.

FL-related microarray datasets were downloaded from the Gene Expression Omnibus database. Differential expression analysis and weighted gene co-expression network analysis (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.

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, N-myc downstream-regulated gene 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.

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.

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

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.

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).

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.

In a 24-week study, significant reductions in weight, BMI, body fat percentage, HbA1c, FPG, and diastolic blood pressure with SGLT2i have been reported in those patients. Furthermore, we also observed that cyclophilin A, an oxidative marker of atherosclerosis, plays a destructive role in cardiomyocyte levels, which are decreased during the SGLT2i therapy.

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.

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.

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.

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.

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.

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

Clostridium difficile infection (CDI) is a serious global health concern characterized by toxin-induced colonic damage, ranging from diarrhea to life-threatening conditions. Despite improved diagnostics and treatments, recurrence rates of up to 30% underscore persistent gaps in effective disease management.

CDI pathogenesis is driven by the disruption of the gut microbiota, often due to broad-spectrum antibiotic use. Risk factors such as advanced age, hospitalization, IBD, and immunosuppression increase the severity and recurrence of the infection. The hypervirulent ribotype 027 strain has been associated with increased mortality and treatment resistance, necessitating targeted therapies.

Emerging treatments such as FMT and monoclonal antibodies show promise for CDI management, with FDA approvals marking progress in microbiome restoration. However, hurdles remain in safety, regulation, and donor screening. Advances in diagnostic and scoring tools have aided in the detection and treatment, but differentiating between colonization and infection remains a challenge. Preventive measures and novel agents such as bacteriocins and bacteriophages offer targeted, microbiome-sparing strategies.

Despite recent advances, CDI management remains challenging because of diagnostic uncertainty and frequent recurrences. Innovative treatments such as FMT and monoclonal antibodies are promising but face limitations in safety, access, and cost. Preventive strategies and decision tools help, yet distinguishing colonization from infection remains difficult, underscoring the need for ongoing and multidisciplinary innovation.

This review highlights current approaches to CDI diagnosis, treatment, and prevention, stressing the urgent need for innovative strategies to reduce recurrence. Targeted research and policy efforts are vital to improving outcomes and quality of life for those affected.

Neuroinflammation, primarily mediated by activated microglia, is a significant contributor to neurodegenerative diseases, such as Alzheimer's and Parkinson's disease. Quercetin (QCT), a dietary flavonoid, has demonstrated anti-inflammatory and neuroprotective properties; however, the detailed molecular mechanisms behind these effects remain unclear. This study aimed to investigate the anti-inflammatory actions of QCT, particularly focusing on its potential to suppress the activation of microglia and subsequent neuroinflammation.

BV2 microglial cells were stimulated with lipopolysaccharide (LPS) to induce an inflammatory response and were subsequently treated with various concentrations of QCT. Cell viability was assessed using the MTT assay. Levels of pro-inflammatory cytokines (IL-6, TNF-α) and nitric oxide (NO) were quantified through ELISA and Griess reaction methods, respectively. Western blot analysis was conducted to examine inducible nitric oxide synthase (iNOS), NF-κB, IκBα, and phosphorylated IκBα protein expressions. In silico approaches, including protein-protein interaction (PPI) network analysis and molecular docking, were employed to explore potential molecular mechanisms involving NF-κB signaling pathways.

Treatment with QCT significantly reduced the secretion of IL-6 (96%) and TNF-α (87%), as well as NO production (42%), in a dose-dependent manner. Western blot results demonstrated a marked reduction in iNOS expression and inhibition of NF-κB activation through reduced phosphorylation of IκBα following QCT treatment. Molecular docking indicated a strong binding affinity between QCT and IKKβ, suggesting inhibition of the NF-κB pathway.

The findings indicated QCT to exert potent anti-inflammatory effects in LPS-stimulated BV2 cells by modulating key proteins involved in the NF-κB signaling pathway. Specifically, the docking results implied QCT’s direct interaction with the catalytic subunit IKKβ, inhibiting IκBα phosphorylation and subsequent NF-κB activation. The results have been found to be consistent with previous literature, reinforcing QCT's role in reducing neuroinflammation through specific molecular targets and pathways. Further in vivo studies are necessary to validate the findings.

Quercetin effectively suppressed neuroinflammation in microglial cells through inhibition of the NF-κB signaling pathway, reducing levels of critical pro-inflammatory mediators. The outcomes have highlighted the potential of quercetin as a preventive nutraceutical for neurodegenerative diseases, necessitating future in vivo investigations to confirm its therapeutic efficacy.

The causality between thyroid disorders and Gastroesophageal Reflux Disease (GERD) remains to be deciphered. This two-sample Mendelian Randomization (MR) study was performed to elucidate the causal association between GERD and thyroid diseases and functions.

Summary statistics for GERD were retrieved from a published GWAS dataset deposited in the Integrative Epidemiology Unit OpenGWAS database. Thyroid hormone level data were obtained from the ThyroidOmics Consortium, and genetic variants associated with thyroid disorders were sourced from the FinnGen Project. MR statistical analyses used the Inverse Variance Weighted (IVW) algorithm, followed by various sensitivity and reliability analyses. Odds Ratio (OR) and beta coefficient (β) with 95% Confidence Interval (CI) were estimated for categorical and continuous outcomes, respectively. The significant causal association was determined based on a Bonferroni-corrected threshold of p-value < 0.0021 (calculated as 0.05/24 trait pairs).

The findings of MR analysis tend to favor the causality of GERD for hyperthyroidism (IVW: OR = 1.517, 95% CI: 1.164 to 1.978, p = 2.04E-03) but not the other thyroid disorders. The reverse MR estimates suggested that thyroid disorders may not affect the susceptibility of GERD. Moreover, genetic proxied GERD was significantly negatively associated with circulating Thyroid Stimulating Hormone (TSH) level (IVW: β = -0.048, 95% CI: -0.078 to -0.019, p = 1.17E-03), whereas the causality of this enteropathy on Free Triiodothyronine (FT3), Free Thyroxine (FT4), Total Triiodothyronine (TT3), FT3/FT4 ratio, and TT3/FT4 ratio (and vice versa) is unfounded.

This MR study indicates that the genetic liability to GERD is significantly detrimental to hyperthyroidism risk and the homeostasis of TSH.

The findings suggest that effective GERD management could mitigate hyperthyroidism risk.

“Penumbra freezing” aims to extend vascular recanalization treatment to acute ischemic stroke (AIS) patients beyond the standard time window by preserving the ischemic penumbra. Efficient biomarkers are crucial for identifying patients eligible for AIS treatment.

This study enrolled 141 AIS patients who exceeded the conventional treatment window. Using CT perfusion imaging, patients were categorized into “penumbra freezing” and “non-penumbra freezing” groups based on the EXTEND criteria. Multiple regression analysis assessed the association of nine baseline factors and five blood lipid indicators with “penumbra freezing.” Diagnostic accuracy was evaluated using ROC curves. Mendelian randomization (MR) analysis validated these findings using blood lipid indicators as exposures and penumbra biomarkers as outcomes.

Among AIS patients beyond the treatment window, males exhibited better penumbra preservation (OR=0.243, 95% CI=0.072-0.813, p=0.022), while those with hyperlipidemia showed poorer preservation (OR=2.429, 95% CI=1.027-7.747, p=0.043). In the “penumbra freezing” group, ApoA1 levels were significantly lower (1.29 ± 0.03 g/L) compared to the “non-penumbra freezing” group (1.42 ± 0.06 g/L, p=0.034). Conversely, Lp(a) levels were significantly higher in the “penumbra freezing” group (304.63 ± 52.44 mg/L) than in the “non-penumbra freezing” group (110.26 ± 40.71 mg/L, p=0.034). Higher ApoA1 levels increased the likelihood of “non-penumbra freezing” beyond the time window (OR=3.206, 95% CI=1.034-9.938, p=0.044), while elevated Lp(a) levels reduced this likelihood (OR=0.075, 95% CI=0.007-0.848, p=0.036). MR analysis confirmed genetic associations of ApoA1 and Lp(a) with penumbra biomarkers.

ApoA1 and Lp(a) may be linked to ischemic penumbra status, but further validation is needed due to limitations in sample size and study methodology.

ApoA1 and Lp(a) are promising biomarkers for identifying AIS patients eligible for “penumbra freezing,” suggesting the potential to extend the treatment window.

Coronary atherosclerotic disease (CAD), clinically manifesting as progressive coronary atherosclerosis (As), involves endothelial cell (EC) dysfunction. HYMAI may contribute to atherogenesis by acting on ECs, but its regulation of endothelial injury and role in As pathogenesis remain unclear.

HYMAI expression was assessed via PCR array in blood samples from healthy individuals, patients with premature coronary atherosclerotic disease (PCAD), and patients with mature coronary atherosclerotic disease (MCAD) (each group consisting of 4 males and 2 females). Using male ApoE^−/− and LDLR^−/− mice fed with a high-fat diet (HFD) to model As, we evaluated the effects of endothelial-specific HYMAI overexpression on aortic lesions. Autophagy and apoptosis were analyzed in ox-LDL-treated human coronary artery endothelial cells (HCAECs).

HYMAI levels increased sequentially in healthy individuals, PCAD, and MCAD patients. In HFD-fed ApoE^−/− and LDLR^−/− mice, aortic atherosclerosis progressed with age, while HYMAI expression in aortic tissue declined. HYMAI overexpression in ECs promoted autophagy and attenuated atherosclerosis. In vitro, ox-LDL suppressed HYMAI, triggering autophagic inhibition and apoptotic activation in HCAECs. HYMAI overexpression rescued ox-LDL-impaired autophagy and suppressed apoptosis through the miR-19a-3p/ATG14 pathway. MiR-19a-3p overexpression reversed autophagic rescue and promoted apoptosis by repressing ATG14.

HYMAI upregulation counteracts ox-LDL-treated endothelial autophagic inhibition via the miR-19a-3p/ATG14 pathway, rescuing apoptosis and attenuating As in both in vivo and in vitro settings.

Our results demonstrated that HYMAI attenuated As progression in As mice and ox-LDL-treated HCAECs by enhancing endothelial autophagy through the miR-19a-3p/ATG14 axis. These findings establish HYMAI as a novel regulatory mechanism and provide a potential druggable target for As and CAD.

Klotho is a multifunctional protein with anti-aging properties that plays a role in regulating vitamin D and phosphate metabolism. Sarcopenia is characterized by the loss of muscle mass and strength and is an important public health concern due to its negative effects on health. The aim of this study was to investigate the association between α-Klotho levels and the frequency of sarcopenia in a diverse population.

This study analyzed data from 1,250 participants in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. Participants were divided into four subgroups based on serum α-Klotho levels. Sarcopenia was assessed using skeletal muscle index and handgrip strength measurements. Multivariable logistic regression analysis was used to determine the association between serum α-Klotho levels and sarcopenia.

There was a significant difference in serum α-Klotho levels between patients with sarcopenia and patients without sarcopenia. In an unadjusted multivariable logistic regression model, higher α-Klotho serum levels were associated with a lower risk of sarcopenia (p < 0.05). This trend was maintained in the partially adjusted model, indicating that higher levels of α-Klotho were associated with a lower risk of sarcopenia. However, the fully adjusted model did not show significance.

Several factors significantly influence the relationship between serum α-Klotho levels and sarcopenia, including sex, ethnicity, alcohol consumption, body mass index (BMI), vitamin D levels, and disease status. Our findings indicate that the risk of sarcopenia is elevated in individuals within the lowest quartile of serum α-Klotho levels. Furthermore, a negative correlation exists between α-Klotho levels and grip strength, observed in both the overall sample and the aging-related subgroup. These results highlight the necessity for further investigation into the complex interplay between α-Klotho and grip strength, particularly in the context of sarcopenia associated with renal disease.

Serum α-Klotho levels in different populations are negatively correlated with the risk of sarcopenia, suggesting that α-Klotho may be involved in the occurrence and development of sarcopenia. Therefore, measuring α-Klotho levels in clinical practice may be a valuable diagnostic tool to identify individuals at high risk of developing sarcopenia.

Hepatocellular Carcinoma (HCC) exhibits high recurrence rates, particularly when accompanied by Microvascular Invasion (MVI). We identified MVI-related biomarkers and established a prognostic model for personalized HCC treatment.

Data were downloaded from The Cancer Genome Atlas (TCGA) and HCCDB databases. Key radiomics features were identified using the support vector machine-recursive feature elimination (SVM-RFE) algorithm, and differential expression analysis was performed with DESeq2. This was followed by functional enrichment analysis using the clusterProfiler package. Through univariate and Lasso regression analyses, we constructed a robust RiskScore model to effectively stratify HCC patients into distinct risk groups based on the median RiskScore value. The model prediction performance was evaluated using ROC curves and Kaplan-Meier (KM) analysis. We used the CIBERSORT algorithm to characterize immune cell infiltration patterns and conducted GSEA to identify differentially activated pathways between the risk groups.

Radiomic analysis revealed four significant features strongly associated with MVI, enabling the construction of a nomogram model with robust classification performance (AUC = 0.742). Subsequent analysis identified 241 overlapping MVI-related Differentially Expressed Genes (DEGs) enriched in critical tumor proliferation and invasion pathways. A 10-gene RiskScore model was developed, demonstrating excellent prognostic discrimination in training and validation cohorts. CIBERSORT analysis revealed significant correlations between specific immune cell infiltration and the 10 genes. GSEA analysis showed significant enrichment of cell cycle regulation pathways in the high-risk group, suggesting their important role in MVI.

The RiskScore was established using MVI-related features for prognosis assessment in HCC.

Our findings provided novel biomarkers and a theoretical basis for the early diagnosis and personalized treatment of HCC.

To identify the critical genes, biological mechanisms, and signaling pathways involved in the therapeutic effects of quercetin on diabetic foot ulcers using network pharmacology and molecular docking approaches.

We identified pathological targets of diabetic foot ulcers (DFU) from GeneCards, OMIM, and TTD, and pharmacological targets of quercetin from STP, TCMSP, and PharmMapper. Intersection analysis revealed potential therapeutic targets. Core targets were determined via GO/KEGG enrichment, PPI network construction, and Cytoscape screening algorithms (Degree, Closeness, Betweenness). Molecular docking and dynamics simulations assessed quercetin-core target interactions and binding affinity.

After screening and intersecting the targets of quercetin and diabetic foot ulcers, 236 genes related to quercetin's anti-diabetic foot ulcer effects were identified, with six key genes emerging as critical: SRC, TP53, MAPK1, JUN, HSP90AA1, and AKT1. Enrichment analysis suggested that quercetin may modulate inflammatory imbalance(HSP90AA1), immunosuppression(JUN), and oxidative stress(SRC, TP53, MAPK1, and AKT1) during diabetic foot ulcer progression.

The relationship between these core targets and biological pathways in diabetic foot ulcers requires further experimental validation. Notably, molecular docking and dynamics simulation results confirmed strong binding affinity between quercetin and the core targets, supporting their potential therapeutic relevance.

Quercetin exerts anti-diabetic foot ulcer effects by regulating SRC, TP53, MAPK1, JUN, HSP90AA1, and AKT1. These hub genes may serve as promising candidates for future therapeutic interventions in diabetic foot ulcers.

The receptor for pyroglutamylated RF amide peptide (QRFPR) is a G protein-coupled receptor that plays a role in various physiological and pathological processes. However, a gap remains in our understanding of QRFPR's pan-cancer properties.

This study performs an extensive pan-cancer analysis of QRFPR utilizing large-scale genomic datasets, including The Cancer Genome Atlas (TCGA). We evaluated QRFPR expression levels in multiple malignancies and examined their correlations with clinical outcomes. Additionally, we investigated associations between QRFPR expression and immune cell infiltration using bioinformatics tools.

Our results reveal significant alterations in QRFPR expression across several cancer types, particularly breast, colorectal, and prostate cancers. Elevated levels of QRFPR are linked to poor prognosis in certain malignancies, such as uterine corpus endometrial carcinoma (UCEC) and mesothelioma (MESO), and correlate with increased infiltration of immune cells, especially T cells and macrophages. Pathway enrichment analyses suggest that QRFPR may impact critical signaling pathways associated with cell growth, apoptosis, and immune regulation.

The observed variations in QRFPR expression across cancer types suggest its diverse roles in tumor biology. Its association with unfavorable clinical outcomes in specific cancers, as well as its link to immune cell infiltration, highlights its multifaceted impact on tumor progression and microenvironment modulation.

Our findings underscore the potential of QRFPR as a prognostic biomarker and therapeutic target in cancer biology. Further investigations into its functional mechanisms could pave the way for precision medicine approaches in oncology.

Cholesterol plays a key role in maintaining tumor cell homeostasis. Reduced IGFBP6 expression is associated with an increased risk of breast cancer recurrence. Previous studies showed that IGFBP6 knockdown decreases cholesterol levels in the MDA-MB-231 cell line. This study aimed to investigate how IGFBP6 influences genes involved in cholesterol metabolism.

We used MDA-MB-231 breast cancer cells with IGFBP6 knockdown. Transcriptomic and proteomic analyses were performed, with selected gene expression validated by RT-PCR. Correlations between IGFBP6 and cholesterol-related genes were evaluated using public RNA-seq datasets.

IGFBP6 knockdown in MDA-MB-231 cells resulted in a threefold decrease in low-density lipoprotein receptor (LDLR) expression and a twofold reduction in LDLR adaptor protein (LDLRAP1) mRNA levels, both responsible for exogenous cholesterol uptake. Meanwhile, PCSK9 expression increased 11-fold (p-adj = 1.4E-93), further limiting uptake. Despite the upregulation of genes involved in endogenous cholesterol synthesis (HMGCS1, HMGCR, FDFT1, SQLE, DHCR24), total cholesterol content in knockdown cells decreased, leading to activation of the sterol-dependent transcription factor SREBF1 (OR = 6.44; p-adj = 0.036). Correlation analysis revealed a significant association between IGFBP6 expression and cholesterol synthesis genes in basal-like breast cancer.

The altered expression profile of multiple cholesterol metabolism-related genes with known prognostic value aligns with a transcriptional program typical of poor-outcome basal-like tumors. These findings support the role of IGFBP6 as a regulator of lipid metabolism and a potential biomarker for therapeutic stratification.

The results of this study indicate that the reduction in cholesterol levels observed in breast cancer cells following IGFBP6 knockdown is primarily due to decreased exogenous uptake. These findings highlight the role of IGFBP6 in regulating cholesterol metabolism and further explain its clinical significance in predicting breast cancer recurrence and progression.

Breast cancer has become the most commonly diagnosed cancer in women worldwide, with advanced cases often leading to bone metastases that significantly affect prognosis and quality of life. This meta-analysis and systematic review aims to evaluate and compare the diagnostic performance of [¹⁸F]FDG PET/CT and bone scintigraphy for detecting bone metastases in breast cancer patients.

A systematic search was conducted across PubMed, Embase, Web of Science, and Scopus for studies published up to February 2025. Relevant articles were identified using a combination of subject-specific and free-text keywords, including “breast cancer,” “positron emission tomography,” “bone scintigraphy,” and “bone metastasis.” Studies assessing the diagnostic utility of [¹⁸F]FDG PET/CT and bone scintigraphy in detecting bone metastases were included. A bivariate random-effects model was used to calculate pooled estimates of sensitivity, specificity, and diagnostic accuracy with 95% confidence intervals (CIs). Potential sources of heterogeneity were explored using meta-regression analysis. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied to evaluate the methodological quality of the included studies.

A total of 1407 publications were initially retrieved, and 13 studies involving 892 patients met the inclusion criteria. The pooled diagnostic performance for [¹⁸F]FDG PET/CT demonstrated a sensitivity of 0.91 (95% CI: 0.81-0.96) and a specificity of 0.98 (95% CI: 0.93-1.00), with an area under the curve (AUC) of 0.99 (95% CI: 0.97-0.99). In comparison, bone scintigraphy showed a sensitivity of 0.82 (95% CI: 0.72-0.89), specificity of 0.81 (95% CI: 0.73-0.87), and an AUC of 0.88 (95% CI: 0.85-0.91). Despite its higher diagnostic accuracy, PET/CT exhibited notable heterogeneity across studies, potentially influenced by differences in patient populations and imaging interpretation criteria.

Our meta-analysis demonstrated the superior diagnostic performance of [¹⁸F]FDG PET/CT over bone scintigraphy, likely attributable to its enhanced sensitivity for osteolytic lesions and integrated anatomical-functional imaging. Nevertheless, considerable inter-study heterogeneity and incomplete clinical data reporting limit the generalizability and robustness, warranting further standardized prospective investigations.

The findings suggest that [¹⁸F]FDG PET/CT offers superior diagnostic accuracy compared to bone scintigraphy for detecting bone metastases in breast cancer patients. However, its clinical application requires further validation through large-scale, prospective studies. Additionally, considerations such as cost-effectiveness and accessibility must be addressed before widespread clinical adoption.

This paper provides a comprehensive review examining the application of copper radionuclides, particularly ⁶⁴Cu, in the diagnosis and potential therapy of various brain diseases.

Two researchers conducted an independent search of the PubMed and Web of Science databases for original research articles published in English. Following a screening process based on titles and abstracts, 42 publications reporting the use of copper radionuclides for diagnosing or treating brain diseases were selected for this review.

The analysis revealed that several copper isotopes, namely 60 Cu, 61 Cu, 62 Cu, ⁶⁴Cu, and ⁶⁷Cu, have been explored for diagnostic or therapeutic purposes in conditions including Alzheimer’s disease, Wilson’s disease, brain tumors, and traumatic brain injury. The isotopes 60 Cu, 61 Cu, and 62 Cu were primarily associated with diagnostic uses. In contrast, ⁶⁴Cu and ⁶⁷Cu were identified as having potential for both diagnosis and therapy (theranostic). Furthermore, the availability of ⁶⁴Cu was noted to be better compared to ⁶⁷Cu.

⁶⁴Cu radionuclides are frequently employed in imaging techniques for brain pathologies. While their role in radiographic applications is prominent, the therapeutic potential of ⁶⁴Cu is currently underdeveloped, and current evidence is primarily derived from preclinical studies, highlighting the critical need for clinical trials to validate ⁶⁴Cu’s efficacy and safety as a theranostic agent in neurological conditions.

⁶⁴Cu holds significant potential for both diagnosis and therapy of various brain diseases. Continued research and development in this area are crucial to unlock its full therapeutic potential and improve patient outcomes.

Idiopathic pulmonary fibrosis (IPF) is a kind of interstitial lung disease with a poor prognosis. Even though genome-wide association studies (GWAS) have identified numerous loci linked to IPF risk, the underlying causal genes and biological processes are still mostly unknown.

The IPF GWAS summary data included 4,125 cases, 20,464 controls from five cohorts. The weight file and related files for transcriptome association studies (TWAS) of plasma protein, multi-tissues, cross-tissue, and single-cell were obtained from Zhang’s study, Mancuso lab, GTExV8 database, and Thompson’s study, respectively. We conducted TWAS employing functional Summary-based Imputation (FUSION) from four levels, which were plasma protein, multiple tissues, cross-tissue, and single cell. Conditional and joint (COJO) analysis and multi-marker analysis of genomic annotation (MAGMA) analysis were used to validate the above results. Summary-data-based Mendelian randomization (SMR) and Bayesian co-localization analysis were utilized to explain the causal association between selected genes and the risk of IPF.

A total of 12, 361, 1187, and 72 genes were calculated from the four dimensions of TWAS. TOLLIP, GCHFR, ZNF318 TALDO1, CD151, and AP4M1 were selected by intersecting the results of the four sets of genes. GCHFR, TALDO1, CD151, and AP4M1 were verified by COJO analysis and MAGMA analysis. SMR and colocalization analyses identified GCHFR as the most significant gene for IPF.

We have applied the TWAS approach to identify novel therapeutic targets for IPF in multiple dimensions. Further biological testing will be required in future studies to validate our findings.

In summary, we carried out an extensive TWAS that integrated four dimensions: plasma protein, multiple tissues, cross-tissue, and single cell. GCHFR was identified as the most significant gene for IPF in this study.

Centromere protein M (CENPM), a member of the CENP family, is correlated with several malignancies, but its role in colon adenocarcinoma (COAD) is unclear. This study aims to explore the expression, prognostic significance, and biological role of CENPM in COAD.

The association of CENPM with the occurrence and progression of COAD was thoroughly analyzed via several bioinformatics databases. Furthermore, the correlation between CENPM expression and clinicopathological features and prognostic value was validated via immunohistochemistry (IHC) of tissue microarrays (TMAs) from 80 patients.

CENPM mRNA expression was significantly elevated in COAD samples compared with healthy tissues. As COAD progressed, CENPM expression decreased, and patients with lower CENPM transcript levels had a worse prognosis. IHC results further confirmed the overexpression of CENPM in COAD patients, identifying this gene as an independent prognostic factor. Additionally, high CENPM expression was linked to methylation in COAD patients, and the primary function of CENPM and its neighboring genes was determined to be cell cycle regulation. Immunological analysis demonstrated that CENPM expression was positively correlated with activated CD8+ T cells, CD4+ T cells, and dendritic cells (DCs) but negatively correlated with regulatory T cells (Tregs). CENPM expression was positively correlated with that of the immune checkpoint genes LAG3, CD244, LGALS9, PDCD1 (PD1), and PVRL2 but negatively correlated with the expression of BTLA, CSF1R, KDR, IL10RB, PDCD1LG2, and TGFBR1.

These findings collectively highlight a multifaceted role of CENPM in COAD, linking its overexpression to improved patient outcomes through mechanisms involving cell cycle control and immunomodulation. Its significant correlation with key immune infiltrates and checkpoint markers implies potential utility as a novel predictor for immunotherapy responsiveness.

CENPM is an independent prognostic factor for COAD, with its overexpression associated with improved survival. It regulates the cell cycle and tumor microenvironment, making it a promising potential predictive biomarker for immune therapy response.

Sodium Selenite (NaSe) is a molecule with various biological activities. Bone fractures and osteoporotic diseases are increasingly common health issues, prompting the search for alternative treatments. Therefore, the purpose of this study was to examine the antioxidant and osteogenic properties of NaSe.

The experiments were conducted using the hFOB1.19 osteoblast cell line. The MTT assay was used to assess the effects of NaSe on cell viability, while cytotoxicity was evaluated with Lactate Dehydrogenase (LDH) assays. Osteogenic differentiation was assessed by alizarin red staining, and Alkaline Phosphatase (ALP) activity and intracellular Reactive Oxygen Species (ROS) levels were also analyzed.

The results showed that NaSe significantly enhanced cell viability in a dose-dependent manner at low doses (0.01-1μM), with the most effective dose being 1μM (p<0.05). LDH activity remained similar to the control within the 0.01-1μM range but increased significantly at higher concentrations (5-50 μM) in both 24- and 48-hour experiments (p<0.05). NaSe reduced intracellular ROS levels significantly between 0.01-1 μM, with 1 μM being the most effective concentration (p<0.05). The highest ALP activity was observed at 0.1 μM NaSe (p < 0.05), and calcium deposition increased in a concentration-dependent manner (p<0.05). The most effective dose for enhancing mineralization was 0.1 μM (p<0.05).

This study demonstrates that NaSe has antioxidant and osteogenic effects at low doses in hFOB cells. These positive effects suggest that NaSe could be a promising candidate for in-vitro, in-vivo, and clinical trials, providing hope for new treatments for bone diseases.

One of the most effective osteoanabolic drugs for treating osteoporosis is romosozumab, which was developed as a consequence of growing knowledge of the Wnt signaling system. This review explored how romosozumab affects the bone mineral density (BMD) in osteoporotic patients.

Up until January 2024, PubMed, Web of Science, and Scopus were reviewed for any randomized controlled trials (RCTs) evaluating the impact of osteoporotic treatment with romosozumab on BMD changes and bone metabolism markers in primary osteoporosis patients. Pooled Hedges’ g indices, which were consistently used across all included studies to measure standardized mean differences, were computed along with their corresponding 95% confidence intervals using either a random-effects or fixed-effects model.

Out of the 1855 papers, 24 RCTs met the inclusion criteria. Patients with osteoporosis who received romosozumab for a period of time demonstrated an augmentation in their lumbar spine BMD. The study findings indicated that the total hip and femoral neck BMD demonstrated significant enhancement in 22 (out of 23) and 19 (out of 21) studies, respectively.

In patients with osteoporosis, romosozumab could markedly increase the total hip, lumbar spine, and femoral neck BMD. This finding could be verified by measuring bone turnover indicators such as PINP, TRACP-5b, and CTX.

Low back pain (LBP) and sciatica are among the most prevalent musculoskeletal disorders, leading to significant disability and an economic burden. Neurotrophic factors, including nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), and glial cell-derived neurotrophic factor (GDNF), play critical roles in pain modulation and neuronal function. While NGF-targeting monoclonal antibodies have shown potential in treating chronic pain, their efficacy and safety remain under debate. This study employs Mendelian Randomization (MR) to assess the causal relationships between NGF, BDNF, GDNF, and the risk of LBP and sciatica.

We conducted a two-sample MR analysis using genetic instruments for NGF, BDNF, and GDNF. LBP and sciatica data were obtained from FinnGen. The inverse variance weighted (IVW) method was applied as the primary causal estimation, with the weighted median (WM) and MR-Egger regression used for sensitivity analyses. Reverse MR was performed to evaluate bidirectional causality. Furthermore, we used expression quantitative trait loci (eQTLs) within 50 kb of each gene locus as genetic instruments for NGF regulation, ensuring that the genetic variants used directly influence neurotrophic factor expression.

MR analysis revealed a significant causal association between NGF and an increased risk of LBP (OR = 1.121, 95% CI 1.021-1.230, p = 0.016) and sciatica (OR = 1.158, 95% CI 1.034-1.296, p = 0.010), while BDNF and GDNF showed no significant associations with pain outcomes. Sensitivity analyses confirmed the robustness of the NGF findings, with no evidence of horizontal pleiotropy or heterogeneity. Reverse MR analysis showed no significant causal effect of LBP or sciatica on NGF levels (p > 0.05), ruling out reverse causality. Additionally, we investigated the NGF-eQTL, which captures genetically regulated NGF expression, and found a significant association between the NGF-eQTL and LBP (OR = 1.040, 95% CI 1.010-1.070, p = 0.007). Unlike external NGF measurements, the NGF-eQTL minimizes environmental confounding and reverse causation, providing stronger genetic evidence supporting NGF as a therapeutic target for LBP.

Our findings provide strong genetic evidence that nerve growth factor (NGF) plays a causal role in the development of low back pain and sciatica, supporting NGF inhibition as a promising therapeutic strategy. These results align with clinical observations where anti-NGF monoclonal antibodies demonstrated pain-relieving effects, though safety concerns remain. In contrast, no causal associations were observed for BDNF or GDNF, underscoring the specificity of NGF in peripheral pain sensitization. The study demonstrates the value of Mendelian Randomization in minimizing confounding and reverse causation, thereby strengthening causal inference. Future work should focus on pharmacogenomic predictors to identify patients most likely to benefit from NGF-targeted interventions while minimizing adverse effects.

This study provides genetic evidence that NGF plays a causal role in LBP and sciatica, reinforcing its potential as a therapeutic target. However, BDNF and GDNF were not significantly associated with pain outcomes, suggesting distinct mechanisms of pain modulation. While clinical trials of anti-NGF monoclonal antibodies have demonstrated efficacy in pain reduction, concerns about adverse effects, such as joint degeneration, habe limited their widespread clinical use. Future research should explore genetic predictors of anti-NGF therapy response to optimize treatment strategies for LBP and related musculoskeletal pain disorders.