Current Medicinal Chemistry - Online First

Ischemic Stroke (IS) represents the most prevalent subtype of cerebrovascular disease, characterized by complex pathophysiological mechanisms that remain inadequately characterized, particularly concerning mitochondrial dysfunctions. These mitochondrial impairments are increasingly recognized as contributory factors in IS pathogenesis, emphasizing the need for further investigation into the underlying molecular mechanisms involved.

In this study, we integrated transcriptomic datasets from the Gene Expression Omnibus (GEO) with the comprehensive MitoCarta3.0 mitochondrial proteome inventory to elucidate the role of dysregulated Mitochondrial-Related Genes (MRGs) in IS. We employed an advanced bioinformatics and machine learning pipeline, incorporating differential expression profiling alongside network-based prioritization using CytoHubba. Rigorous feature selection was conducted through LASSO regression, Support Vector Machine (SVM), and Random Forest (RF) algorithms to derive a robust core MRG signature. Our methodology included training and validation cohorts to construct diagnostic models, which were critically evaluated via Receiver Operating Characteristic (ROC) curves, nomograms, and calibration analyses.

Our analysis identified a seven-gene signature comprising DNAJA3, ACSL1, HSDL2, ECHDC2, ECHDC3, ALDH2, and PDK4, which demonstrated significant correlation with activated CD8⁺ T-cell and natural killer cell infiltration. Furthermore, integrative network analyses revealed intricate regulatory interactions among MRGs, microRNAs, and transcription factors. Notably, drug-target predictions indicated Bezafibrate as a promising therapeutic agent for modulating mitochondrial homeostasis in the context of IS.

These findings offer a novel framework for ischemic stroke diagnosis and therapy, yet their computational derivation underscores the need for thorough experimental validation of MRGs and drug candidates, along with the integration of diverse clinical data to confirm their real-world applicability.

Our findings underscore mitochondrial dysfunction not only as a critical factor in IS pathogenesis but also as a viable therapeutic target. The identified MRG signature presents potential for clinical application in diagnostic and pharmacological strategies aimed at ameliorating ischemic injury. This study highlights the translational significance of systems biology approaches within cerebrovascular medicine, warranting further mechanistic exploration of mitochondrial-immune interactions in stroke pathology.

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.

Several pathological conditions, including glaucoma, malignant brain tumors, and renal, gastric, and pancreatic carcinomas, are commonly associated with carbonic anhydrase type II (CA-II). Additionally, CA-II plays a critical role in regulating bicarbonate concentration in the eyes. The inhibition of CA-II reduces aqueous humor production and thus lowers intraocular pressure associated with glaucoma.

This study aimed to synthesize potent CA-II inhibitors, 5-nitro-1H-benzo[d]imidazole-2(3H)-thione (5NBIT) and acylhydrazone derivatives (1-13).

In this study, a new series of potent CA-II inhibitors, 5-nitro-1H-benzo[d]imidazole-2(3H)-thione (5NBIT) and acylhydrazone derivatives (1-13), were synthesized and characterized by IR, NMR, UV and mass spectroscopy and evaluated against bovine carbonic anhydrase-II (bCA-II).

Interestingly, most of the compounds showed better inhibition than the standard drug, acetazolamide (IC50: 18.2±0.51 µM), such as compounds 1 (IC50: 10.5±0.81 µM), 2 (IC50: 11.3±0.36 µM), 3 (IC50: 16.5±0.53 µM), 4 (IC50: 15.8±1.02 µM), 5 (IC50: 13.7±1.03 µM), and 9 (IC50: 12.2±1.03 µM). Among the synthesized compounds, compound 7 (IC50: 8.2±0.32 µM) exhibited the highest and compound 6 (IC50: 27.6±0.39 µM) showed the lowest inhibition. Structure-activity relationships suggest that the presence of nitro group on the phenyl ring contributed significantly to the overall inhibitory activity. Molecular docking of all the active compounds was performed to predict their binding behavior, which indicated good agreement between docking and experimental findings. Moreover, the MD simulation of compound 7 also showed excellent binding behavior and binding energy within the binding cavity of bCA-II.

These findings suggest that the synthesized 5NBIT and acylhydrazone derivatives exhibited potent CA-II inhibition, with several compounds outperforming the standard drug acetazolamide. These results provide valuable insights for the development of novel CA-II inhibitors with potential therapeutic applications in glaucoma and other related conditions.

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.

Chronic Renal Failure (CRF) is a progressive disease that severely affects patients' quality of life, but its current treatment options remain limited. This study explores the potential mechanism of Eriobotryae Folium (EF) in treating CRF by targeting ferroptosis.

Active compounds and targets of EF were identified through multiple databases (TCMSP, SwissTargetPrediction, UniProt, GeneCards, DrugBank). Using Cytoscape and STRING, both a compound-target network and a PPI network were generated. GO and KEGG analyses were conducted to explore relevant biological functions and pathways. The binding affinity and stability between critical compounds and target proteins were investigated through molecular docking and Molecular Dynamics (MD) simulations.

Eighteen active compounds and 366 targets of EF were identified, along with 1,267 CRF-related and 1,673 ferroptosis-related targets, with 40 overlapping genes. PPI analysis highlighted AKT1, EGFR, HIF1A, SRC, and ESR1 as key targets. The KEGG analysis indicated MAPK and HIF-1 pathways as major regulatory pathways. Molecular docking suggested quercetin, ellagic acid, and oleanolic acid as potential active compounds, with EGFR and SRC as promising targets. MD simulations confirmed strong and stable binding, especially for EGFR-ellagic acid (-21.38 kcal/mol) and EGFR-oleanolic acid (-24.02 kcal/mol).

This study suggests that EF treats CRF by targeting ferroptosis-related pathways and key proteins, such as EGFR and AKT1. MAPK and HIF-1 signaling pathways further substantiate its significant role in disease regulation.

EF may regulate ferroptosis through multiple targets and pathways, offering potential therapeutic benefits for CRF. The findings offer foundational insights for subsequent research and therapeutic development.

Diabetes mellitus, a chronic metabolic disorder characterized by elevated blood glucose levels, has emerged as a significant global health burden. Chronic inflammation and insulin resistance are central to the pathogenesis of non-insulin-dependent (type 2) diabetes mellitus. PTGS2 (prostaglandin-endoperoxide synthase 2) has been implicated in inflammatory pathways associated with diabetic complications, making it a potential therapeutic target.

Advanced computational methodologies were employed to identify potential natural compounds with anti-diabetic activity. Techniques included network pharmacology to establish compound-target-pathway relationships and in silico molecular docking to evaluate binding affinity and interaction profiles of selected phytochemicals with PTGS2.

PTGS2 and its downstream prostaglandin pathways were strongly associated with diabetic inflammation and insulin resistance. Molecular docking identified Corytuberine and Nuciferine as having high binding affinities with PTGS2. Network pharmacology analysis confirmed Nuciferine’s connection to PTGS2, supporting its role as a bioactive agent targeting diabetes-related inflammatory processes.

The findings suggest that PTGS2 contributes to the progression of insulin resistance and chronic inflammation in type 2 diabetes. Targeting this enzyme with bioactive compounds such as Nuciferine may offer therapeutic benefits. However, translational studies and clinical trials are essential to validate these computational predictions and assess safety and efficacy in vivo.

Nuciferine exhibits promising potential in modulating PTGS2 activity and improving insulin sensitivity. Continued research and clinical validation are needed to confirm its efficacy and support the development of novel anti-diabetic therapies targeting inflammatory pathways.

Chemotherapy remains essential despite advances in immunotherapy, radiotherapy, and biological therapy. However, the wide range of chemical drugs is limited by a narrow therapeutic index, low selectivity, and the development of resistance. In this regard, new high-efficiency drugs are in extremely high demand. The indazole moiety, a scaffold found in many biologically active compounds, was selected for use in new drug design.

Six new indazole derivatives were synthesized via Suzuki-Miyaura coupling starting from bromoindazole. Their antiviral (against influenza A and SARS-CoV-2), antibacterial (against M. tuberculosis), and antiproliferative activities (against neuroblastoma, glioma, leukemia cell lines) were evaluated in vitro. Acute toxicity was assessed in mice of both sexes via single intragastric administration, with toxicometric parameters and pathomorphological changes studied.

6-(1H-pyrazol-4-yl)-1H-indazole (8) suppressed the reproduction of the influenza virus at non-toxic doses to the MDCK cells and showed cytotoxicity against cancer cell lines, with an IC50 between 4 and 14 µM. However, it exhibited significant acute toxicity in mice (LD50 40 mg/kg), causing systemic organ damage.

Derivative 8 demonstrated promising antiviral and antiproliferative activities but exhibited considerable acute toxicity in vivo. The antiviral efficacy, although lower than oseltamivir, is meaningful and justifies further optimization and investigation. Its antibacterial activity against M. tuberculosis adds to its potential as a multifunctional agent.

While derivative 8 has shown potential as an antiviral and anticancer agent, its high toxicity highlights the need for further studies to define a safe and effective therapeutic window. Overall, the indazole scaffold remains a valuable platform for the development of new therapeutic compounds.

This study aims to elucidate the mechanisms contributing to the transition from acute to chronic inflammation, particularly in the context of atherosclerosis, by investigating the pro-inflammatory responses of cybrid cell lines derived from patients with coronary heart disease.

Acute inflammatory reactions are essential components of the innate immune response, typically resolving within hours or days. However, disruptions in this process can lead to chronic inflammation, which is linked to significant morbidity and mortality. Atherosclerosis, characterized by chronic vascular inflammation, poses a major health threat, underscoring the need for understanding its underlying mechanisms.

The primary objective is to analyze the pro-inflammatory cytokine responses of 14 cellular lines, including 13 cybrids and one maternal line (THP-1), to identify intolerant and tolerant responses to key cytokines associated with inflammation.

We utilized cybrid cell lines created by fusing THP-1 monocytic cells with platelets from patients diagnosed with atherosclerosis. Cytokine responses were assessed through quantitative analysis of IL-1β, IL-6, MPC-1, IL-8, and TNF-α secretion. Gene expression profiles were analyzed to correlate cytokine secretion with specific gene regulation patterns, focusing on epigenetic mechanisms influencing immune responses.

Distinct intolerant and tolerant responses were observed across the cellular lines for key cytokines. Specifically, TC-HSMAM1 and TCP-521 were intolerant to IL-1β, TC-HSMAM1, TC-LSM2, and TC-522 were intolerant to IL-6, six lines exhibited intolerance to MPC-1, and eight lines were intolerant to IL-8. No intolerant responses were noted for TNF-α. Gene expression analysis revealed that at least ten genes correlated with increased cytokine secretion in intolerant reactions, while 23 genes showed higher expression during these intolerant responses, indicating significant roles for DNA modification and chromatin remodeling. An important finding emerged from the study of agents affecting histone modification. Specifically, unlike other agents, sodium butyrate not only exhibited a stronger suppression of the inflammatory response in cells but also eliminated their intolerance to inflammatory stimulation. Therefore, in the near future, sodium butyrate could be regarded as a fundamentally new anti-inflammatory preventive and therapeutic agent, with its mechanism of action rooted in the prevention and suppression of chronic inflammation.

In chronic non-infectious diseases like atherosclerosis the intolerant response or trained immunity can worsen inflammation. This study shows that both genetic and epigenetic regulation contribute to this intolerant response. It was also found that sodium butyrate can prevent the intolerant response, suggesting it may become a new anti-inflammatory agent that suppresses chronic inflammation.

Our findings have suggested that the interplay between pro-inflammatory cytokine responses and epigenetic regulation mechanisms is critical in determining whether a cell exhibits a normal or intolerant immune response. Understanding these dynamics may provide insights into the chronic inflammatory processes associated with atherosclerosis and other related conditions.

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.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are major gynecological malignancies, causing significant cancer-related deaths in women. Current treatments yield poor outcomes, with a 5-year survival rate of only 17%. Identifying new biomarkers and therapeutic targets is crucial for improving prognosis and guiding personalized treatments.

We analyzed TCEAL2 expression using data from The Cancer Genome Atlas (TCGA) across various cancers, including CESC. We explored its correlation with clinical features, prognosis, immune infiltration, MSI, mRNAsi, and drug sensitivity. TCEAL2 expression was validated in GSE9750 datasets and CESC cell lines using qRT-PCR.

TCEAL2 expression was significantly dysregulated in CESC. Elevated TCEAL2 levels correlated with poor clinical outcomes, including advanced pathological M stage (p = 0.009), initial treatment failure (p = 0.0098), and reduced overall survival (OS) (p = 0.013). TCEAL2 was an independent predictor of unfavorable OS (p = 0.032). It was associated with key pathways such as calcium signaling, oxidative phosphorylation, and Wnt signaling. TCEAL2 also correlated with immune cell infiltration, MSI, and mRNAsi. Notably, TCEAL2 levels inversely correlated with sensitivity to several drugs, including CAY10603 and SB-223133.

The results suggest that TCEAL2 plays a significant role in CESC progression and its tumor microenvironment. Its correlation with immune infiltration and drug sensitivity highlights its potential as a prognostic biomarker and therapeutic target. Future studies should focus on elucidating the molecular mechanisms and validating their clinical utility.

TCEAL2 is a potential prognostic biomarker and therapeutic target in CESC. Further research is needed to explore its role and clinical applications.

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.

Many medications associated with an increased risk of dementia do not have adequate warning labels, leading to a significant underestimation of their potential dangers. This study aims to leverage the FAERS database to identify drugs strongly linked to dementia and to examine the relationship between these drugs using Mendelian randomization techniques. The ultimate goal is to mitigate the risk of developing dementia.

We utilized the FAERS database to identify medications significantly associated with dementia cases. The DrugBank, OpenTargets, and STITCH databases were employed to pinpoint the target genes of these drugs. We then conducted Mendelian randomization analysis to explore the correlation between the expression of drug target genes and the incidence of dementia. Additionally, a time-to-onset analysis assessed the temporal relationships of drug ingestions. Furthermore, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction Network (PPI) analyses were performed to investigate the molecular pathways linked to target genes related to drugs associated with dementia.

A total of 28,139 dementia events were recorded in the FAERS database. Our Mendelian randomization analysis revealed a significant association between the expression of all identified drug target genes and dementia in both blood and brain tissues. Specifically, we identified nine drug target genes with significant correlations, implicating quetiapine, clozapine, valproic acid, alendronate, and digoxin as being strongly associated with dementia, which could provide insight into areas of clinical concern regarding dementia occurrence.

The adverse event data sourced from the FAERS database indicate that certain medications are associated with an increased risk of developing dementia, a finding corroborated by our Mendelian randomization analysis. Establishing a comprehensive monitoring and risk assessment program is crucial for identifying high-risk individuals and facilitating informed medication choices, thereby potentially reducing the incidence of dementia.

Tyrosinase, a copper-containing enzyme, is responsible for melanin production, and its overactivity can lead to hyperpigmentation.

This study aimed to evaluate triazolothiadiazoles (3a-h, 4a-f) and triazolothiadiazines (5a-h) against human and mushroom tyrosinase isozymes.

Several derivatives, such as 3a-3b, 3d, 4c-4f, 5d, and 5e, were identified as potent and selective inhibitors of mushroom tyrosinase, with IC50 values ranging from 1.9 to 15.2 µM. Similarly, compounds 3f, 4b, 5a, and 5b effectively inhibited human tyrosinase, with IC50 values between 12.6 and 18.5 µM. Mechanism-based studies revealed that these active compounds exhibited competitive inhibition against both isozymes without any cytotoxic effects. In-silico analysis further demonstrated that these compounds fit well into the active site of both tyrosinase isozymes.

Additionally, the pharmacokinetic profile of these compounds highlighted promising drug-like properties, making them potential candidates for the development of effective therapeutics for skin disorders.

Gastroesophageal reflux disease (GERD) is a prevalent digestive disorder, yet the causal roles of modifiable risk factors remain unclear. This study aims to investigate the causal relationships between 28 modifiable risk factors (including obesity traits, mental health disorders, sleep traits, metabolic comorbidities, and serum parameters) and GERD using two-sample Mendelian randomization (MR). Gastroesophageal reflux disease (GERD). Our findings aim to inform targeted prevention and treatment strategies for GERD.

This study obtained data from extensive genome-wide association studies (GWAS). Pooled data associated with gastroesophageal reflux associations were obtained from the 23andMe Research team’s research, which included a total of 129,080 cases of gastroesophageal reflux and 473,524 controls of European ancestry. We conducted a univariable Mendelian randomization (MR) analysis to ascertain whether genetic evidence of exposure demonstrated a statistically significant association with the risk of GERD. Subsequently, a multivariable MR analysis was carried out to estimate the independent effects of the exposures on GERD.

Univariable MR analysis utilizing extensive GWAS data suggested that genetic factors such as BMI, Waist circumference, Arm fat mass (left and right), Leg fat mass (left and right), Attention Deficit and Hyperactivity Disorder (ADHD), Major Depressive Disorder (MDD), Schizophrenia, Negative emotions (including nervousness, anxiety, tension, or depression), Insomnia, Sleep apnea syndrome, Sleep duration, and Snoring, as well as Total cholesterol levels and Apolipoprotein B levels, are associated with the development of GERD. Multivariate Mendelian randomization of BMI and Negative emotion as correction factors showed that Waist circumference, Arm fat mass (left and right), Leg fat mass (left and right), ADHD, Insomnia, Sleep apnea syndrome, and Snoring were associated with an increased risk of GERD (p< 0.05). Conversely, longer sleep duration was associated with a reduced risk of GERD (p< 0.05).

This MR study reveals novel causal mechanisms in GERD pathogenesis: (1) Peripheral adiposity (arm/leg fat mass) exerts independent effects beyond central obesity, indicating site-specific fat distribution significance; (2) ADHD emerges as a distinct psychiatric risk factor independent of mental disorders; (3) Sleep apnea operates through BMI-independent pathways. Collectively, these findings redefine GERD pathophysiology, highlighting fat depot specificity and brain-gut interactions as critical mechanistic drivers.

Overall, our findings suggest that multiple risk factors are associated with the risk of GERD. These results provide a theoretical basis for controlling body weight and plasticity, improving sleep habits, and preventing and timely seeking medical attention to reduce the occurrence of psychiatric disorders, which will be important strategies to prevent and alleviate GERD.

Seven new 4-[2-(dichloromethyl)pyrazolo[1,5-a][1,3,5]triazine derivatives were investigated for anticancer activity, possible molecular mechanisms of anticancer action, and ADMET properties.

The 4-benzenesulfonamide derivatives of pyrazolo[1,5-a][1,3,5]triazine were synthesized using the condensation of N-(2,2-dichloro-1-cyanovinyl)-amides IV with 1H-pyrazol-5-amine. Compound antitumor activities were evaluated using the NCI-60 human cancer cell line. AutoDockTools and AutoDock Vina software were used for molecular modeling. Using the ADMETlab 3.0 and pkCSM web sources, the ADMET properties of compounds 4, 5, and 7 were calculated.

Seven new pyrazolo[1,5-a][1,3,5]triazine derivatives were synthesized. The compounds 4, 5, and 7 exhibit high activity >1 µM against leukemia, colon, and renal cancer. Compound 4 exhibited the most potent activity, with IC50 values of 0.32  µM against leukemia, 0.49-0.89  µM against colon cancer, and 0.92  µM against renal cancer. Molecular modeling has demonstrated a potential antitumor mechanism involving CDK. The predicted ADMET profile of compounds 4, 5, and 7 is favorable.

The seven novel pyrazolo[1,5-a][1,3,5]triazines, as purine bioisosteres, were developed, synthesized, and investigated by in vitro and in silico methods.

Seven novel pyrazolo[1,5-a][1,3,5]triazine derivatives exhibited anticancer activity against the NCI-60 cancer cell lines. The compounds 4, 5, and 7 demonstrated strong anticancer activity, with growth inhibition (GI) values exceeding 50% across all nine cancer types tested. The most active compound, 4, is against leukemia, colon cancer, renal cancer, and lung cancer. All compounds exhibit low toxicity, with LC50 values of 100 µM or greater. The molecular docking of compounds 4, 5, and 7 revealed the potential to inhibit cancer-associated cyclin-dependent kinases. The predicted ADMET profiles of their compounds are favorable, providing a basis for further improvement of their anticancer activity.

Metabolic dysregulation, encompassing conditions such as type 2 diabetes mellitus, obesity, metabolic syndrome, and dyslipidemia, poses an increasing global health burden. The dysregulation of 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1), a key enzyme in glucocorticoid metabolism, has been strongly implicated in the pathogenesis of these disorders by influencing glucose homeostasis, lipid metabolism, and insulin sensitivity. Consequently, targeting 11β-HSD1 offers a promising therapeutic strategy for mitigating metabolic dysregulation and its associated complications.

The study aimed to identify resveratrol derivatives with high binding affinity and inhibitory potential against 11β-HSD1, using computational approaches to evaluate their pharmacokinetic and toxicity profiles.

A library of resveratrol derivatives was screened using molecular docking to identify high-affinity compounds. The hit compounds were further evaluated for absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, followed by molecular dynamics simulations to assess their stability.

The resveratrol cis-dehydrodimer emerged as the most promising candidate, demonstrating high binding affinity, favorable ADMET properties, and stability over a 200 ns simulation period. These findings suggest its potential as a small-molecule inhibitor of 11β-HSD1.

The resveratrol cis-dehydrodimer represents a viable candidate for further experimental validation as a therapeutic agent for metabolic disorders. Future studies should include synthetic validation and in vivo testing to confirm its efficacy.

Long COVID-19 (LC) is a condition that follows SARS-CoV-2, an acute infection defined by persistent fatigue, dyspnea, and impaired cognitive function. LC presents a complex array that imposes ongoing challenges on global health, patients' quality of life, and functional capacity. Many inconsistencies surround its pathophysiology, diagnosis, prevention, and treatment. This review aims to cover missed gaps in LC with a special focus on therapeutic strategies concerning non-pharmacological, pharmacological, experimental, and innovative approaches for better patient management and outcomes, as well as to evaluate their effectiveness and guide future research.

An online search was conducted using five digital repositories: PubMed, Scopus, Google Scholar, Web of Science, and the Cochrane Library. A combination of keywords associated with LC therapy was employed: “long COVID, “pharmacological options,” “non-pharmacological options,” “innovative strategies,” “experimental”, and” quality of life (QOL).” Relevant data were extracted and synthesized to categorize therapeutic approaches into subtypes. A critical analysis was conducted on their mechanism of action, indication, outcome, and limitations.

The pooled prevalence of LC was 42%, and the symptom duration ranged from 3 months to 2 years. The most important risk factors for LC were female sex, unvaccinated status, and cases with co-morbidities. Diagnosis of LC was challenging due to a lack of diagnostic standardization and reliable biomarkers.

Non-pharmacological strategies were employed first, showing diverse efficacies; however, the reported literature was hindered by small sampling. Pharmacological agents show promising results but need further validation. Experimental and innovative strategies need longer studies and validations.

LC has imposed a significant burden on community health, necessitating the appropriate allocation of health resources and community support. Preventive and therapeutic interventions show promise, but the variability in patient response underscores the need for personalized approaches and more well-designed trials. Collaborative research and multi-disciplinary teams are needed to mitigate the long-term effects of LC and improve patient outcomes.

This study aimed to develop, characterize, optimize, and evaluate the in vitro ex vivo drug release and stability of miconazole nitrate (MN)-loaded nanocrystal for topical drug delivery. MN is an antifungal agent with poor oral bioavailability and significant first-pass metabolism, necessitating alternative administration routes. Nanoformulations with lipidic/polymeric nanoparticles can overcome conventional system formulation limitations. However, it resulted in controlled MN drug release for up to 48 h and greater skin flux than did a 1% MN solution. This study aimed to identify optimized, stable, and effective in vitro/ex vivo MN-loaded nanocrystal-based hydrogels for topical drug delivery.

The nanocrystals (PN1-PN12) were developed via the precipitation method using Pluronic F-127 as a nonionic copolymer surfactant and stabilizer. The compatibility was evaluated via differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), and Fourier transform infrared spectroscopy (FT-IR). With the help of the zetasizer, particle size, PDI, and Zeta Potential are determined. The drug in-vitro release was determined using the dialysis bag method. Carbopol 934-P and methylparaben were dissolved in distilled water with heat and constant stirring to prevent agglomeration. Permeation experiments used excised abdominal skin from Wistar rats euthanized by cervical dislocation.

The highest solubility was found in PF-127, followed by Pluronic F68. Nanocrystals were prepared via the antisolvent precipitation method. The new diffraction pattern of the nanocrystals confirms their crystalline nature and complexation with the polymer, supporting the DSC and FT-IR findings. The developed nanocrystal shows a subtle shift from 1587 to 1589 cm^-1, with no significant changes in the vibrational frequencies of the physical mixture. The PN5 formulation, with a small PS of 303.4 nm, a low PDI of 0.248, the highest drug content of 99.23 ± 5.23%, and a % cumulative drug release of 92.32 ± 3.27, was selected for further characterization. The PN5 formulations were stored under various conditions for 3 months, resulting in consistent particle sizes. SEM images revealed long, crystalline MN structures and needle-like nanocrystals. PN5 was optimized for developing a topical nanocrystal gel (PG1), which provided sustained drug release and retained significantly more drug than the other formulations did. PG1 remained stable during the 3-month storage.

The PN5 formulation, optimized for developing a topical nanocrystal gel, resulted in consistent particle size, sustained drug release, and stability over 3 months.

Wound healing is a complex and dynamic biological process involving overlapping phases such as inflammation, proliferation, and tissue remodeling. Chronic wounds, which fail to heal in a timely manner, pose significant challenges in clinical practice. Static magnetic fields (SMFs) have shown potential in wound healing, particularly in their anti-inflammatory effects and ability to promote cell proliferation. However, the precise mechanisms underlying their effects remain unclear.

This study aims to investigate the effects of SMFs on wound repair and to explore the molecular mechanisms involved, particularly the role of key signaling pathways.

A rabbit ear full-thickness wound model was used to evaluate the effects of SMFs (160 mT) on wound healing. Normal human dermal fibroblasts (NHDFs), normal human epidermal keratinocytes (NHEKs), and human umbilical vein endothelial cells (HUVECs) were cultured under SMF conditions to assess their proliferation, migration, and angiogenic activity. Tissue repair, angiogenesis, and cell proliferation were analyzed through histological and immunohistochemical methods. Transcriptome sequencing and Western blotting were performed to identify key pathways affected by SMFs.

SMFs significantly accelerated wound healing in the rabbit ear model, as demonstrated by enhanced re-epithelialization, granulation tissue formation, and angiogenesis. In vitro, SMFs promoted the proliferation and migration of fibroblasts and keratinocytes, as well as tube formation in endothelial cells. Transcriptome and protein analyses revealed that SMFs activated the PI3K/AKT/mTOR signaling pathway, which played a critical role in regulating cell proliferation and angiogenesis.

This study demonstrates that SMFs promote wound healing by enhancing angiogenesis and cell proliferation through activation of the PI3K/AKT/mTOR signaling pathway. These findings provide a theoretical foundation for the application of SMFs as a non-invasive therapeutic approach for clinical wound management.

This investigation delves into the diagnosis of COVID-19, using X-ray images generated by way of an effective deep learning model. In terms of assessing the COVID-19 diagnosis learning model, the methods currently employed tend to focus on the accuracy rate level, while neglecting several significant assessment parameters. These parameters, which include precision, sensitivity and specificity, significantly, F1-score, and ROC-AUC influence the performance level of the model. In this paper, we have improved the InceptionResNet and called Enhanced InceptionResNet with restructured parameters termed, “Enhanced InceptionResNet,” which incorporates depth-wise separable convolutions to enhance the efficiency of feature extraction and minimize the consumption of computational resources.

For this investigation, three residual network (ResNet) models, namely ResNet, InceptionResNet model, and the Enhanced InceptionResNet with restructured parameters, were employed for a medical image classification assignment. The performance of each model was evaluated on a balanced dataset of 2600 X-ray images. The models were subsequently assessed for accuracy and loss, as well subjected to a confusion matrix analysis.

The Enhanced InceptionResNet consistently outperformed ResNet and InceptionResNet in terms of validation and testing accuracy, recall, precision, F1-score, and ROC-AUC demonstrating its superior capacity for identifying pertinent information in the data. In the context of validation and testing accuracy, our Enhanced InceptionResNet repeatedly proved to be more reliable than ResNet, an indication of the former’s capacity for the efficient identification of pertinent information in the data (99.0% and 98.35%, respectively), suggesting enhanced feature extraction capabilities.

The Enhanced InceptionResNet excelled in COVID-19 diagnosis from chest X-rays, surpassing ResNet and Default InceptionResNet in accuracy, precision, and sensitivity. Despite computational demands, it shows promise for medical image classification. Future work should leverage larger datasets, cloud platforms, and hyperparameter optimisation to improve performance, especially for distinguishing normal and pneumonia cases.

Ovarian reserve reflects the functional capacity of a woman’s ovaries, encompassing factors such as follicle quantity, egg quality, and fertilization potential. Assessment of ovarian reserve is essential in reproductive medicine, particularly for fertility evaluation and assisted reproductive technologies (ART). While traditional biochemical markers such as anti-Müllerian hormone (AMH) and follicle-stimulating hormone (FSH) are commonly used, instrumental diagnostic methods like ultrasound and magnetic resonance imaging (MRI) provide valuable morphological and functional insights. This systematic review without a comprehensive meta-analysis evaluates the role of ultrasound and MRI in assessing ovarian reserve and their potential applications in clinical and research settings.

A comprehensive literature search was conducted across multiple databases to identify relevant studies evaluating ovarian reserve using ultrasound and MRI. Studies were screened based on predefined inclusion criteria, focusing on imaging parameters such as ovarian volume, follicular count, stromal characteristics, and vascularization. The effectiveness of these imaging techniques was analyzed in comparison to established biochemical markers. Due to heterogeneity in the included studies, a systematic review was performed without a formal meta-analysis.

Ultrasound, particularly transvaginal ultrasound (TVUS), remains the gold standard for ovarian reserve assessment, allowing real-time visualization of antral follicle count (AFC), ovarian volume, and follicular morphology. Doppler ultrasound provides additional insights into ovarian blood flow, which correlates with follicular development and ovarian function. MRI offers high-resolution, three-dimensional imaging, enabling detailed assessment of ovarian structure, follicular density, and stromal composition. While MRI provides superior soft-tissue contrast, its role in routine ovarian reserve assessment is limited due to cost and accessibility. The findings indicate that although both modalities are valuable for ovarian reserve evaluation, there is no consensus on standardized imaging parameters for defining ovarian functional viability. The available literature also presents inconsistencies in the correlation between imaging findings and ovarian function.

Ultrasound and MRI are essential tools for assessing ovarian reserve, providing complementary morphological and functional data. However, the lack of standardized imaging parameters limits their ability to definitively determine ovarian functional viability. Further research is needed to establish validated diagnostic criteria and integrate imaging techniques with biochemical markers to enhance the accuracy of ovarian reserve assessment in clinical practice and reproductive research.

Early and precise diagnosis is essential for effectively treating and managing pulmonary tuberculosis. The purpose of this research is to leverage artificial intelligence (AI), specifically convolutional neural networks (CNNs), to expedite the diagnosis of tuberculosis (TB) using chest X-ray (CXR) images.

Mycobacterium tuberculosis, an aerobic bacterium, is the causative agent of TB. The disease remains a global health challenge, particularly in densely populated countries. Early detection via chest X-rays is crucial, but limited medical expertise hampers timely diagnosis.

This study explores the application of CNNs, a highly efficient method, for automated TB detection, especially in areas with limited medical expertise.

Previously trained models, specifically VGG-16, VGG-19, ResNet 50, and Inception v3, were used to validate the data. Effective feature extraction and classification in medical image analysis, especially in TB diagnosis, is facilitated by the distinct design and capabilities that each model offers. VGG-16 and VGG-19 are very good at identifying minute distinctions and hierarchical characteristics from CXR images; on the other hand, ResNet 50 avoids overfitting while retaining both low and high-level features. The inception v3 model is quite useful for examining various complex patterns in a CXR image with its capacity to extract multi-scale features.

Inception v3 outperformed other models, attaining 97.60% accuracy without pre-processing and 98.78% with pre-processing.

The proposed model shows promising results as a tool for improving TB diagnosis, and reducing the global impact of the disease, but further validation with larger and more diverse datasets is needed.

Cuproptosis, a newly discovered form of programmed cell death, has potential implications for tumorigenesis and cancer progression. This study investigates the role of cuproptosis in Acute Myeloid Leukemia (AML) and identifies associated biomarkers using bulk and single-cell RNA sequencing. Despite recent advances, the mechanisms of cuproptosis in AML remain unclear, and its relationship with immune cell infiltration could reveal novel therapeutic targets.

RNA-seq data from 151 AML patients and 70 healthy controls were obtained from TCGA and GTEx databases, and single-cell RNA-seq data from 16 AML patients (GEO) were used for validation. Differential expression of Cuproptosis-Related Genes (CRGs) was analyzed via RCircos and correlation analysis. Immune cell infiltration was assessed using CIBERSORT and ssGSEA. WGCNA identified key genes for AML and cuproptosis subtypes, which were validated with single-cell data. Intercellular communication was analyzed through ligand-receptor interactions. RNA interference experiments validated TLR4 and NCF2, with gene expression measured through RT-qPCR. Apoptosis and CCK-8 assays assessed cell viability.

We identified 19 CRGs with differential expression between AML subtypes linked to immune cell infiltration. Subtype analysis classified AML patients into C1 and C2 subgroups enriched in biosynthesis and metabolism pathways. WGCNA identified 2701 genes associated with AML and 92 with cuproptosis, leading to 15 intersecting genes. RETN was highlighted as key in intercellular communication. Experimental validation showed that elesclomol-induced cell death in THP-1 cells is reversible by TTM. Knockout of TLR4 and NCF2 promoted cuproptosis.

These findings offer new insights into the role of cuproptosis in AML, highlighting novel biomarkers, such as TLR4 and NCF2, which may provide promising targets for the development of future therapeutic strategies in AML treatment.

Doxorubicin (DOX) is a chemotherapeutic agent widely used for the treatment of various cancers; however, its clinical use is limited by its cardiotoxicity. However, the underlying molecular mechanisms remain poorly understood, hindering the development of effective preventive and treatment strategies. This study aimed to identify core target genes and explore the mechanisms involved in DOX-induced cardiotoxicity by integrating microarray analysis, machine learning, and molecular docking.

Differential expression analysis was performed using microarray data from DOX-induced cardiotoxic samples and healthy controls. Multiple machine learning algorithms were applied to identify core target genes. The predictive performance of these genes was evaluated using receiver operating characteristic (ROC) curves. Molecular docking was conducted to evaluate the binding affinity of DOX to the target genes. Functional analysis was performed to investigate potential toxic mechanisms.

In total, 276 differentially expressed genes were identified between DOX-induced cardiotoxicity samples and controls. The support vector machine algorithm demonstrated the best performance, leading to the identification of five core target genes: RAP1A, CTLA4, OR2M1P, TRIM53, and LOC149837. The ROC curves confirmed the strong predictive power of these genes, with area under the curve values greater than 0.85. Molecular docking showed stable binding between DOX and the target genes. Functional analysis suggested that the Rap1 signaling pathway and immune system regulation may be involved in DOX-induced cardiotoxicity.

Traditional toxicological studies often rely on limited experimental approaches that do not fully capture the complexity of disease mechanisms. The integration of microarray analysis, machine learning, and molecular docking in this study offers a comprehensive framework for investigating the toxicological pathways of DOX-induced cardiotoxicity, thereby providing insights into therapeutic development and safety regulations.

By combining microarray analysis, machine learning, and molecular docking, we identified five key target genes associated with DOX-induced cardiotoxicity. Functional analysis further suggested the involvement of the Rap1 signaling pathway and immune system regulation in DOX-induced cardiotoxicity. These findings offer insights into the molecular mechanisms underlying DOX-induced cardiotoxicity and have implications for the development of protective strategies and therapeutic interventions.

Dyshomeostasis of Cu²⁺ and abnormal interactions between Cu²⁺ and β Amyloid peptide (Aβ) can promote Aβ aggregation and oxidative stress, which are considered to trigger Alzheimer’s Disease (AD). Metal chelating therapy is a promising approach for the treatment of AD.

In this study, 2-(2-hydroxyphenyl)benzazoles were synthesized via microwave irradiation promotion. Chelators inhibiting Cu²⁺-induced Aβ aggregation were determined through turbidity assay and BCA protein assay, while anti-oxidants were detected via HRP/Amplex red assay and fluorescent probe of DCFH-DA. Cell viability was measured by MTT assay.

The bio-activity for inhibiting Cu²⁺ induced-Aβ aggregation of chelators S-1, S-3, S-4, S-5, S-7, S-10, N-5, N-9, N-10 O-2, O-4, X-N-2 was better than that of CQ. The ability of the chelators (S-1, S-10, O-2, O-5, N-9, and X-N-2) to decrease the level of ROS in Aβ+Cu²⁺ treated SH-SY5Y cells was better than that of CQ. The ability to attenuate Aβ-mediated cytotoxicity in SH-SY5Y cells of S-10 (O-2, O-5, and N-9) was better than that of CQ.

After the evolution of the bio-activities for the treatment of AD in vitro, it was found that 4 chelators (S-10, O-2, O-5, and N-9) exhibited better bio-activities than CQ in all aspects.

Osteosarcoma (OS) is one of the most common primary malignancies in children and adolescents. Disulfidptosis, a newly identified form of metabolically induced programmed cell death triggered by disulfide stress, has not yet been explored in OS.

We integrated data from public databases and applied a series of bioinformatics approaches, including clustering analysis to classify OS subtypes, and Cox and LASSO regression analysis to identify prognostic disulfidptosis-related genes (DRGs). Enrichment analysis was performed to explore the biological pathways associated with DRG-related molecular subtypes. The immune infiltration landscape was assessed to understand the tumor microenvironment in different risk subgroups. Additionally, drug sensitivity analysis was conducted to evaluate the potential clinical therapeutic strategies of the identified DRG score subgroups. The distribution of DRG expression across OS cell subtypes was further analyzed using single-cell RNA sequencing. In vitro assays, including Western blotting, qRT-PCR, and cell migration and invasion assays, were conducted to validate POLR1D expression and function in OS cells.

We established a DRG-based prognostic model that effectively stratifies OS patients into distinct risk groups with different survival outcomes. The model also revealed significant differences in immune cell infiltration between high and low DRG scores group, suggesting a link between disulfidptosis and the OS immune microenvironment. Drug sensitivity analysis indicated that the DRG signature could guide personalized therapeutic strategies. Single-cell RNA sequencing revealed heterogeneous expression of DRG signature across OS cell subtypes. Functional assays confirmed that POLR1D was aberrantly overexpressed in OS cells and promotes their migration and invasion, supporting its role as a potential oncogenic driver in OS.

Our study is the first to investigate the role of DRGs for risk stratification in OS, providing new insights and targets into OS pathogenesis.

Acute myeloid leukemia (AML) is the most common adult hematologic malignancy, with relapse and drug resistance posing major challenges despite treatment advances. Cryptotanshinone (CTS), a diterpenoid compound derived from Salvia miltiorrhiza, exhibits anticancer activity in various tumors. However, its role and mechanisms in AML remain unclear. This study aims to investigate the inhibitory effects of CTS on AML cells and its potential mechanisms.

Network pharmacology was employed to identify potential AML-related targets of CTS, and a disease-drug-target interaction network was constructed. The effects of CTS on KG-1 cells were assessed using CCK-8 proliferation assays, cell cycle analysis and apoptosis detection. Western blot and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to analyze the regulatory effects of CTS on the endoplasmic reticulum stress (ERS) signaling pathway. The role of the Hippo-YAP signaling pathway in CTS-induced AML inhibition was further explored.

Network pharmacology analysis identified key AML-related targets of CTS, enriched in multiple cancer-related signaling pathways. Experimental results showed that CTS inhibited KG-1 cell proliferation in a dose-dependent manner, induced S-phase arrest, and promoted apoptosis. Furthermore, CTS treatment significantly upregulated ERS-related key proteins. While YAP overexpression attenuated CTS-induced ERS activation and reduced apoptosis levels.

This study indicates that CTS inhibits AML cell proliferation and induces apoptosis while activating the ERS signaling pathway. However, aberrant activation of the Hippo-YAP pathway weakens this effect. These findings provide novel theoretical insights into potential therapeutic strategies for AML.

Pterygium is a common ocular surface disorder characterized by fibrovascular overgrowth, with recurrence remaining a major clinical challenge. While non-coding RNAs have been implicated in pterygium pathogenesis, the role of tRNA-derived small RNAs (tsRNAs) remains unexplored.

We performed small RNA sequencing on pterygium and adjacent normal conjunctiva tissues to profile tsRNA expression. Differentially expressed tsRNAs were validated using qRT-PCR, and their biological functions were investigated via cell proliferation and wound healing assays in human pterygium fibroblasts (HPF). Potential target genes and enriched pathways were analyzed using bioinformatics approaches, including KEGG and GO enrichment analysis.

We identified significantly dysregulated tsRNAs in pterygium, with tRF-1_30-His- GTG-1, tRF-1_31-Val-CAC-2, tRF-1_31-Gly-GCC-1, and tRF-1_30-Gly-CCC-1-M4 exhibiting notable upregulation. Functional assays demonstrated that tRF-1_30-His- GTG-1 promotes fibroblast proliferation and migration, while the other three tsRNAs enhance fibroblast migration. Pathway enrichment analysis revealed their involvement in cellular proliferation, extracellular matrix remodeling, and angiogenesis.

This study provides the first evidence of tsRNA involvement in pterygium pathogenesis, highlighting their potential as biomarkers and therapeutic targets. Future studies should focus on deciphering their precise regulatory mechanisms and developing RNA-based therapeutic strategies to mitigate disease progression.

With the rapid emergence of drug-resistant strains of tuberculosis, resistance to current first-line and second-line anti-tuberculosis drugs is becoming increasingly prevalent. Consequently, the discovery of new lead compounds is essential to address this challenge. GyrB has emerged as a promising target for tuberculosis treatment due to its pivotal role in DNA replication and topology regulation in Mycobacterium tuberculosis.

In this study, a multi-conformational virtual screening approach, complemented by antibacterial activity assays, was utilized to identify novel GyrB inhibitors from the ChemDiv database.

Among the 27 compounds purchased, 10 exhibited significant inhibitory effects against the H37Rv strain, with 8 featuring novel core scaffolds. Notably, three compounds (V027-7669, V017-8710, and 5132-0213) demonstrated a minimum inhibitory concentration (MIC) of 8 μg/mL. Compounds V027-7669 and V017-8710, in particular, showed antibacterial activity against a multidrug-resistant tuberculosis strain, with MIC values of 32 μg/mL and 16 μg/mL, respectively. Molecular dynamics simulations revealed that both V027-7669 and V017-8710 bind stably to GyrB, which are primarily driven by nonpolar interactions. Furthermore, both of them occupy a novel sub-pocket formed by residues Val99, Gly106, Val123, Gly124, and Val125, where they establish hydrogen bonds with Val125.

Our study underscores the effectiveness of a multi-conformational virtual screening strategy in identifying novel GyrB inhibitors and suggests V027-7669 and V017-8710 as promising lead compounds for the development of treatments against multidrug-resistant tuberculosis.

Diabetes mellitus (DM) is a chronic metabolic disorder that seeks treatment instead of available mitigative therapy.

Six (E)-3-(aryl)-1-phenylprop-2-en-1-one chalcones were synthesized and characterized through various spectroscopic techniques. Their anti-diabetic potential was examined through in-vitro (α-glucosidase and α-amylase inhibition assays), in-vivo (alloxan-induced hyperglycemia), and in-silico studies.

All the chalcones derivatives significantly inhibited α-glucosidase and α-amylase. Compounds 11 (IC50 = 1.10 ± 0.02) and 13 (IC50 = 3.25 ± 0.10 µM) exhibited the most potent activity against α-glucosidase. The effect of compounds 11 and 13 was also significant against α-amylase with IC50 of 13.2 ± 0.50 and 10.2 ± 0.4 µM, respectively. In alloxan-induced hyperglycemic model, a significant (p<0.001) reduction in blood glucose level (BGL) was observed by compounds 10, 11 and 14 with maximum percent inhibition of 47.48, 47.22 and 47.55, respectively. In the oral glucose tolerance test, a continuous reduction in BGL was noted at 60 minutes. No negative effect was seen on lipid profile, and in liver and renal function tests. However, a slight gain in body weight was noted. Moreover, docking result indicates good interaction of these molecules with the target enzymes, α-glucosidase and α-amylase.

These results demonstrate that all these molecules have significant anti-diabetic potential.

Alzheimer's disease (AD) is the most common cause of dementia worldwide, with a steadily increasing prevalence. However, the mechanisms underlying AD remain unclear, and current treatments have only limited efficacy.

This study aimed to identify potential biomarker genes for AD and to explore the underlying mechanisms by integrating microarray analysis, Mendelian randomization (MR), and experimental validation.

AD-related microarray datasets were downloaded from the Gene Expression Omnibus database. Differential expression analysis identified differentially expressed genes (DEGs) between AD and control samples. Summary-level data from genome-wide association studies on AD were integrated with expression quantitative trait loci data to identify genes with potential causal relationships with AD using MR. The intersections between DEGs and causal genes were identified as hub genes. Functional analysis was performed to explore underlying mechanisms. Quantitative real-time PCR was applied to validate the expression of hub genes in clinical samples.

Differential expression analysis identified 312 DEGs, whereas MR identified 202 genes with causal effects on AD. The intersection of these two sets identified four hub genes: FCRLB, MT2A, PFKFB3, and SRGN. Functional analysis indicated significant associations between AD and immune-related pathways. Correlation analysis revealed significant connections between hub genes and immune cells in AD. The expression of MT2A, PFKFB3, and SRGN was significantly upregulated, whereas FCRLB was downregulated in clinical AD samples compared with controls.

The integration of microarray analysis, MR, and experimental validation identified and validated four potential biomarker genes with causal effects on AD, namely FCRLB, MT2A, PFKFB3, and SRGN. Functional analysis indicated a pivotal role of the immune microenvironment in AD. These findings offer insights into the molecular mechanisms of AD and have implications for improving its diagnosis and treatment strategies.

RNA sequencing data and clinical information from GC patients were collected from the TCGA and GEO databases, excluding cases of pure IGC and DGC. Based on ECMR and CA-related genes, supervised clustering via non-negative Matrix Factorization (NMF) was used to identify molecular subtypes in MGC. Differential expression and Cox regression analyses were performed to identify prognostic genes, and an ECMR and CA-based gene signature (ECRS) was developed using machine learning techniques. Gene Set Variation Analysis (GSVA) was conducted to assess functional differences between risk groups, while TIDE and pRRophetic analyses were used to predict responses to immunotherapy and chemotherapy.

A total of 239 MGC patients were classified into two molecular subtypes with significant differences in prognosis. Subtype 2 displayed distinct ECM interactions and connective tissue development pathways. To refine the ECRS model, we tested 117 model combinations across 10 machine learning algorithms, selecting the configuration with the best predictive accuracy. This optimized model distinguished biological and immune characteristics between high- and low-risk groups, with low-risk patients showing greater sensitivity to immunotherapy and standard chemotherapy.

This study identifies novel molecular subtypes of MGC based on ECMR and CA-related genes and establishes an effective ECRS model to predict prognosis, immunotherapy response, and chemotherapy sensitivity. This model supports personalized treatment strategies for MGC.

Hepatocellular carcinoma (HCC) is a life-threatening cancer with rising incidence and mortality rates. Identifying new prognostic biomarkers is crucial for improving HCC management.

This study investigates the role of Double PHD Fingers 1 (DPF1) in hepatocellular carcinoma (HCC), exploring its potential as a prognostic indicator and therapeutic target.

We analyzed DPF1 expression in 374 hepatocellular carcinoma (HCC) tissues and 50 normal tissues from the TCGA-HCC database, as well as in 240 HCC tissues and 202 normal tissues from the ICGC-HCC repository. We examined the correlation between DPF1 expression and clinical parameters, immune cell infiltration, drug response profiles, cancer stem cell (CSC) characteristics, and its diagnostic/prognostic potential using various bioinformatics tools and statistical analyses. Validation was performed using the ICGC and HPA databases, and qRT-PCR was used to confirm DPF1 expression in HCC cell lines.

DPF1 exhibited abnormal expression in HCC and several other malignancies. Elevated DPF1 levels were significantly associated with higher Alpha-fetoprotein (AFP) levels (p = 0.043) and poorer clinical outcomes, including diminished overall survival (OS) (p = 0.002), progression-free survival (PFS) (p = 0.018), and disease-specific survival (DSS) (p = 0.001). DPF1 expression was also linked to immune cell infiltration, immune checkpoint gene expression, drug sensitivity, and CSC characteristics. Notably, DPF1 was significantly overexpressed in HCC tissues and cell lines at both transcriptional and translational levels.

Our study reveals that DPF1 is a novel prognostic biomarker in HCC, with potential implications for immunotherapy and drug resistance. Elevated DPF1 expression is associated with adverse clinical outcomes and may serve as a target for future therapeutic interventions in HCC.

Stanniocalcin 1 (STC1) has been implicated in cancer pathogenesis, yet its pan-cancer implications and mechanistic roles in tumor progression and immune modulation remain incompletely characterized. The clinical relevance of STC1 in predicting prognosis and its interaction with tumor immune microenvironment components requires systematic investigation.

This study aims to establish the pan-cancer prognostic significance of STC1 and elucidate its associations with immunological characteristics, including immune checkpoint proteins, tumor mutational burden (TMB), microsatellite instability (MSI), and immune cell infiltration. This study focuses specifically on validating its role in the pathogenesis of gastric adenocarcinoma (STAD).

Multi-omics analysis was performed using TCGA pan-cancer datasets and bioinformatics tools (UALCAN, cBioPortal, HPA, GTA). Experimental validation included multiplex fluorescence staining of STAD tissue microarrays (n=30) and Western blot analysis of STAD cell lines. Key parameters analyzed encompassed clinical outcomes, cancer stemness indices, neoantigen load, and epithelial-mesenchymal transition (EMT) signatures.

Pan-cancer analysis revealed significant STC1 overexpression in 18/33 cancer types (54.5%), particularly in prostate adenocarcinoma (94% deep deletions). STC1 expression correlated with poor prognosis (HR=1.32, p<0.01), elevated TMB (r=0.43), and MSI (r=0.38) across multiple malignancies. Single-cell RNA sequencing demonstrated a strong association with EMC (NES=2.18, FDR<0.001). In STAD, this study confirmed 3.7-fold protein overexpression (p=0.008) and identified positive correlations with CD8+ T cell infiltration (r=0.62, p=0.002) and CD4+ T cell infiltration (r=0.58, p=0.004).

This multi-modal study establishes STC1 as a novel pan-oncogenic factor with dual roles in tumor progression (via EMT and stemness regulation) and immune microenvironment remodeling. The strong association with immune checkpoints (PD-L1, CTLA4) and T cell infiltration patterns positions STC1 as a promising immunotherapeutic target, particularly in STAD and MSI-high cancers. These findings provide mechanistic insights for developing STC1-directed therapeutic strategies.

Over 85% of biologically active compounds are heterocycles or contain heterocyclic groups, underscoring their vital importance in contemporary drug development. Among them, nitrogen-containing derivatives, such as pyridines and pyrimidines, are considered privileged structures in approved drugs or are extensively studied due to their promising therapeutic effects.

In the current work, we would like to verify the hypothesis that incorporating heterocyclic pharmacophores into derivatives of pyrimidine-2(1H)-thione (PMT), 2-pyridone (P), pyridine-2(1H)-thione (PT), dihydropyrimidine-2(1H)-thione (DHPMT), dihydropyridin-2(1H)-one (DHP), and dihydropyridine-2(1H)-thione (DHPT) rings enhances antitumor activity.

A range of novel pyridine- and pyrimidine-based compounds were synthesized and assessed for their anticancer properties against the melanoma A375 cell line. The two most potent compounds (16b and 29) were then chosen for further evaluation of their effects on non-cancerous human dermal fibroblasts, cancer cell apoptosis, cell cycle phase distribution, and tubulin polymerization. Furthermore, in silico analyses were performed to assess the pharmacokinetics, toxicity, drug-likeness, and molecular target of the selected compounds.

Among the 33 compounds tested, pyridine analogs 16b and 29 demonstrated the strongest antiproliferative activity (with IC50 values of 1.85 ± 0.44 µM and 4.85 ± 1.67 µM, respectively) and selectivity (SI=65.08 and SI> 100, respectively) against cancer cells. Additional studies revealed that compound 16b, which features a thiophene ring at the C-5 position and a 3,4,5-trimethoxyphenyl (TMP) group, showed the most promising cell cycle arrest and tubulin polymerization inhibition (IC50=37.26 ± 10.86 µM), resulting in cancer cell apoptosis. In silico ADMET analysis confirmed the drug- likeness of the synthesized compounds.

This research reinforced the significance of heterocyclic rings as valuable pharmacophores. Additionally, it highlighted the antiproliferative and antimitotic potential of modified pyridine derivatives.

This study investigated the causes of Mitochondrial Dysfunction (MD) in Diabetic Kidney Disease (DKD) progression, and identified genes associated with DKD, especially those with significant genetic causal effects, to provide a theoretical basis for DKD treatment.

Using a large database and single-cell RNA sequencing (scRNA-seq) data, 333 MDRDEGs were discovered. MDRDEGs were linked to AGE-RAGE signaling, RNA processing, protein transport, and energy metabolism using functional enrichment analysis. Seven MDRDEGs with significant genetic causal effects in DKD were discovered using SMR and MR analyses: ACTN1, ALG11, CCNB1, HIVEP2, MANBA, TUBA1A, and WFS1. Co-localization and scRNA-seq analyses examined these genes' DKD connections. Due to the high significance of its prediction model and DKD expression, ACTN1 was studied in depth. PheWAS and molecular dynamics analysis assessed ACTN1's safety and efficacy as a therapeutic target, and its connection with other symptoms. ACTN1 protein expression in DKD tissues was confirmed by immunofluorescence.

Functional enrichment analysis revealed that MDRDEGs were mostly related to AGE-RAGE signaling, RNA processing, protein transport, and energy metabolism. Seven MDRDEGs caused DKD genetically in SMR and MR investigations. Genetic variations in ACTN1, ALG11, MANBA, and TUBA1A were linked to DKD by co-localization studies. scRNA-seq showed a dramatic increase in ACTN1 expression in DKD. Molecular dynamics analysis demonstrated that Dihydroergocristine can safely bind to ACTN1, while the PheWAS investigation found no significant relationships. DKD tissues exhibited higher ACTN1 protein levels via immunofluorescence.

This study identified MDRDEGs linked to inflammation, cytoskeletal stabilization, and glucose metabolism pathways critical in Diabetic Kidney Disease (DKD) pathogenesis, highlighting their clinical potential as therapeutic targets. Notably, ACTN1 emerged as a causally linked gene overexpressed in DKD, with the prediction of dihydroergocristine as a targeting compound, offering novel avenues for clinical intervention.

This study suggests that ACTN1 may be a therapeutic target for DKD and sheds light on its molecular pathogenesis, clinical prevention, and treatment.