BMC Pharmacology & Toxicology最新文献

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the interplay of genetic and environmental factors, and currently, there there is a lack of effective diagnostic or therapeutic strategies available. This study aims to identify circulating biomarkers for ALS and investigate their interactions with environmental toxins.

Methods: This research utilizes plasma proteomic genome-wide association study (GWAS) data and whole blood transcriptomic data from ALS patients to screen for potential circulating biomarkers through Mendelian randomization (MR). Subsequently, functional enrichment analysis and immune infiltration analysis were performed. An integrated machine learning approach will be used to construct a diagnostic model, with hub genes selected based on SHAP values. The model's performance will be validated using receiver operating characteristic (ROC) curves, nomogram, and decision curve analysis (DCA). Finally, reverse network toxicology will be used to explore the interaction mechanisms between hub genes and environmental toxins.

Results: Based on a MR analysis of plasma proteomics, we identified 68 plasma proteins significantly associated with the risk of ALS. By integrating differentially expressed genes (DEGs) from whole blood transcriptomics (1,116 DEGs), we selected four potential circulating biomarkers: FCRL3, HTATIP2, RNASE6, and SF3B4. Functional enrichment analysis indicated that the pathogenesis of ALS is closely related to autophagy, apoptosis, the endoplasmic reticulum unfolded protein response, and the NF-κB signaling pathway. Immune infiltration analysis revealed a disruption of the immune microenvironment mediated by T cells/myeloid cells in ALS patients. Validation through 113 machine learning algorithms showed that the random forest model exhibited the best diagnostic performance (AUC = 0.786), while SHAP analysis confirmed the contribution ranking of hub biomarkers: RNASE6 > FCRL3 > HTATIP2 > SF3B4. Further validation of their diagnostic value was performed using ROC curves, nomograms, and DCA. Environmental toxins analysis revealed that substances such as benzo(a)pyrene exhibit significant neurotoxicity, and molecular docking confirmed that they can interfere with the function of hub biomarkers through strong binding (∆G < -5 kcal·mol⁻¹), suggesting potential environmental pathogenic mechanisms in ALS.

Conclusions: This study not only highlights the value of FCRL3, HTATIP2, RNASE6, and SF3B4 as potential diagnostic biomarkers and therapeutic targets for ALS but also provides new evidence for the involvement of environmental toxins, particularly benzo(a)pyrene, in the pathogenesis of ALS through gene-environment interactions.

Background: Nanoparticles have been used in nanomedicine for therapeutic purposes. Lipids have been a popular choice of material in the synthesis of biocompatible nanoparticles due to their ability to encapsulate diverse therapeutic agents. However, once introduced into biological environments, nanoparticles rapidly adsorb proteins on their surface, forming a protein corona that can alter drug release, targeting and cellular interactions. Understanding these effects is essential for optimizing solid lipid nanoparticles (SLNs) as drug delivery systems.

Methods: SLNs were synthesized using stearic acid (SA) as the lipid core and stabilized with surfactants, Tween 80 and SDS (sodium dodecyl sulphate). To mimic in vitro conditions, SLNs were incubated with 5% FBS (foetal bovine serum) for varying durations to allow soft and hard protein corona formation. SLNs were characterized for size and surface charge via dynamic light scattering while UV visible spectroscopy, protein adsorption studies, FTIR and the Bradford Assay were employed to confirm and quantify protein corona formation. In parallel, molecular docking was conducted to analyse protein-nanoparticle interactions. To investigate the potential influence of protein corona formation on drug release, ceftriaxone (CTX) was encapsulated within SLNs followed by immediate incubation to allow corona formation. Subsequent evaluations included drug leakage, release profile and antibacterial efficacy against Staphylococcus aureus and Pseudomonas aeruginosa.

Results: Protein adsorption was confirmed on all SLN formulations and closely correlated with nanoparticle surface charge. Formulations with more negative zeta potentials adsorbed higher amounts of protein. SDS concentration influenced protein adsorption with higher SDS content reducing overall corona formation. Molecular docking revealed that protein-ligand interactions were maintained by hydrogen bonding and hydrophobic forces. Drug release studies confirmed that the protein corona reduced cumulative drug release by 6%. Antibacterial assays confirmed slightly reduced efficacy against both strains aligning with the reduced cumulative drug release.

Conclusions: This study demonstrated that protein corona formation on dual-surfactant SLNs is strongly influenced by surface charge and surfactant composition and in turn modulates drug release dynamics. The protein corona was shown to modulate drug release with potential implications for antibacterial efficacy. These findings highlight the importance of tailoring surface properties to control protein-nanoparticle interactions thus providing insight into the design of lipid-based nanoparticles for therapeutic applications.