Jun Xu

Background: Pseudomonas aeruginosa , a member of the “ESKAPE” pathogens, possesses a robust ability to form biofilms—a key factor that contributes to its antibiotic resistance and poses significant challenges for clinical management. Identifying potential therapeutic targets through bioinformatic analysis of genomic data is therefore critical for developing more effective treatment strategies. Methods: In this study, five gene expression datasets from the Gene Expression Omnibus were integrated to investigate transcriptional differences between planktonic and biofilm-associated P. aeruginosa populations. R was used to identify differentially expressed genes (DEGs), followed by weighted gene co-expression network analysis (WGCNA), to determine significant co-expression modules. Overlapping genes between the DEGs and WGCNA-derived modules were subsequently analyzed to screen for robust hub genes using three machine-learning algorithms: Random Forest, Support Vector Machine-Recursive Feature Elimination, and Least Absolute Shrinkage and Selection Operator. Their diagnostic performance and discriminative ability were evaluated using receiver operating characteristic analysis and boxplot visualization. Furthermore, a systematic literature review was conducted to examine the relationship between P. aeruginosa biofilm formation and host immune status, enabling a preliminary assessment of associations between the identified biomarkers and immune cell infiltration. Finally, potential inhibitory compounds were screened from an FDA-approved drug library, validated through molecular docking and molecular dynamics simulations, and subjected to RNA-sequencing (RNA-seq) analysis to assess their effects on biofilm-forming P. aeruginosa. Results: By intersecting the key module genes with the DEGs, a total of 25 overlapping genes were identified, among which wspA emerged as a candidate hub gene functionally associated with P. aeruginosa biofilm formation. Virtual screening revealed that DL-menthol exhibits a strong and stable binding affinity toward the wspA protein. RNA-seq further confirmed its significant effects on P. aeruginosa during active biofilm formation, with wspA representing a major responsive target. Collectively, these findings provide new insights into therapeutic strategies for biofilm-associated infections, highlight the potential clinical utility of wspA inhibitors, and offer a foundation for developing more effective intervention strategies.

Pseudomonas aeruginosa is a leading cause of nosocomial infections, particularly in individuals with a compromised immune system. Due to its strong adaptive ability, P. aeruginosa tends to develop antibiotic resistance and establish chronic infection, making its eradication through traditional antibiotics challenging. Thus, the development of novel therapeutic targets and corresponding inhibitors is urgently required. We conducted bioinformatics analyses of gene-chip datasets (GSE10362, GSE21966) of P. aeruginosa from patients with cystic fibrosis (CF) in the Gene Expression Omnibus (GEO) database, ranging from early to late stages of infection. Differentially expressed gene (DEG) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and Weighted Gene Co-expression Network Analysis (WGCNA) were performed to identify key functional DEGs. Among these genes, candidate genes were refined using three machine learning algorithms: LASSO regression, random forest (RF), and support vector machine (SVM). Using this integrated approach and published reports, target gene was identified consequently. With reported inhibitors, a structure-based virtual screening model against the target protein was established to screen inhibitors from an FDA-approved drug library. Screened hits were experimentally validated through in vitro MIC and checkerboard broth microdilution assays to determine their antibacterial activity and the synergistic effect of tobramycin (TOB) and amikacin (AMK). Enzyme activity was measured to evaluate target protein inhibition. Transcriptome sequencing analysis was performed to explain the effect of target inhibition and reveal the possible mechanism of inhibition. We identified 210 upregulated genes in the late stage of infection. KEGG functional enrichment demonstrated that the up-regulated genes were mainly enriched in metabolic pathways. Eight metabolism-related key DEGs were obtained by the intersection of genes from metabolic pathways and genes from the key module of WGCNA. Machine learning algorithms (LASSO, RF, and SVM) and literature investigation results identified glcB, which encodes malate synthase G (MS), as a therapeutic target for developing inhibitors. In virtual screening, we formulated four rules for a screening model based on the docking results, and finally identified three FDA-approved drugs prednisolone, dienogest and carbinoxamine maleate salt (CAR) as candidates. In vitro MIC assay and checkerboard assay suggested that CAR had an antibacterial effect with a concentration-dependent trend and could enhance the effect of tobramycin and amikacin. Consistent with MIC assay, the inhibition rate in MS activity assay showed a concentration-dependent trend. Transcriptome sequencing analysis showed that carbon metabolism was remodeled when MS was inhibited, thus impairing the growth of P. aeruginosa, and the synergistic effect with TOB and AMK may be explained by the impaired ability to combat oxidative stress. This study identified and validated drug target glcB (encodes MS) and potential inhibitor CAR in treating chronic P. aeruginosa infection based on an integrated method of bioinformatics, virtual screening, and in vitro experiments. Graphical Abstract The alternative text for this image may have been generated using AI. The main workflow for identifying glcB-encoded protein as a drug target, screening, and validating its inhibitors.

Introduction: While the APOLLO trial confirmed the clinical efficacy of first-line anlotinib plus penpulimab in unresectable hepatocellular carcinoma (HCC), its economic impact on China’s healthcare system remains underexplored. This study was conducted to evaluate the cost-effectiveness of this novel combination vs. sorafenib from the perspective of the Chinese healthcare system. Methods: A partitioned survival model with three health states was developed to simulate economic outcomes for patients with advanced HCC. Survival data were derived from the APOLLO trial using parametric fitting. Direct medical costs and utility values were obtained from local public databases and the published literature. The primary outcomes included total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) evaluated against the willingness-to-pay (WTP) threshold of $40334.05/QALY. Model robustness was assessed through deterministic and probabilistic sensitivity analyses (PSA). Results: The base-case analysis revealed that anlotinib plus penpulimab incurred a total cost of $25681.69 and yielded 1.42 QALYs, compared with sorafenib’s total cost of $18082.48 and 1.19 QALYs. This resulted in an incremental cost of $7599.21 and an incremental effectiveness of 0.22 QALYs, resulting in an ICER of $34050.28/QALY, which is below the predefined WTP threshold. Sensitivity analyses identified anlotinib treatment duration (cycles) and progression-free survival (PFS) utility values as key drivers of model variability. The PSA indicated an 85.9% probability of cost-effectiveness at the WTP threshold. Conclusion: Anlotinib plus penpulimab represents a potentially cost-effective first-line treatment for advanced HCC from a Chinese healthcare system perspective. These findings support incorporating this regimen into guidelines for selecting cost-effective immunotherapeutic strategies and provide evidence to inform decision-making about resource allocation for advanced HCC management.

Pseudomonas aeruginosa, a member of the “ESKAPE” group of bacterial pathogens, exhibits biofilm-forming capacity, a key factor contributing to its resistance to conventional antibiotics and posing significant challenges in clinical treatment. To develop more effective therapeutics against such infections, identifying potential drug targets through bioinformatics analysis is essential. Consequently, we utilized data from the GEO database to investigate differentially expressed genes between planktonic and biofilm groups, and identified drug targets through the construction of a protein–protein interaction (PPI) network and the cytoHubba algorithm. Inhibitors targeting this protein were identified through molecular docking screening of the FDA-approved drug library, and their anti-biofilm activity was validated in vitro. Through bioinformatics analysis, we identified GacS as the drug target in this study for treating biofilm-related infections. Virtual screening revealed that oxidized glutathione (GSSG) and arformoterol tartrate (ARF) are both capable of tightly binding to GacS and demonstrating good stability. In vitro experiments further confirmed that both GSSG and ARF demonstrated anti-biofilm activity, particularly when combined with azithromycin (AZM) or clarithromycin (CAM), significantly enhancing the biofilm inhibition effects of these antibiotics. This combination therapy offers a new and innovative strategy to combat biofilm-associated infections, showcasing the potential of GacS inhibitors in clinical applications. In conclusion, GSSG and ARF may serve as effective GacS inhibitors, and their combination with AZM or CAM could provide a novel approach for treating biofilm-related infections, paving the way for more effective treatment options.

This study investigates the skin-whitening potential of 4-Hydroxyacetophenone (4-HAP), a compound commonly used as a preservative in cosmetics. Despite its widespread use, its whitening activity has not been extensively reported. Our preliminary research identified several commercial cosmetic formulations exhibiting whitening effects without known whitening agents. We hypothesized that 4-HAP might be a key ingredient. To test this, we employed a mushroom tyrosinase model, B16 mouse melanoma cells, and zebrafish to systematically evaluate the whitening activity of 4-HAP. Our findings demonstrate that 4-HAP is a potent tyrosinase inhibitor, significantly reducing melanin content in vitro and in vivo. Additionally, molecular docking and dynamics analyses revealed that the stable binding of 4-HAP to tyrosinase is crucial for its whitening effect. In formulations containing 2% 4-HAP, human skin models showed nearly complete recovery from UV-induced pigmentation after 4 weeks, while control groups exhibited persistent UV marks. These results confirm the efficacy of 4-HAP as a stable whitening agent in cosmetic formulations, highlighting its potential for further development in skin lightening products. This study has confirmed that 4-HAP holding the potential to become an effective whitening ingredient in the cosmetics field.

RhlR plays a key role in the quorum sensing of Pseudomonas aeruginosa. The current structure–activity relationship (SAR) studies of RhlR inhibitors mainly focus on elucidating the functional groups. Based on a systematic review of previous research on RhlR inhibitors, this study aims to establish a systematic, hierarchical screening model for RhlR inhibitors. We initially established a database and utilized principal component analysis (PCA) to categorize the inhibitors into two classes. Based on the training set, pharmacophore models were established to elucidate the structural characteristics of ligands. Subsequently, molecular docking, molecular dynamics simulations, and the calculation of binding free energy and strain energy were performed to validate the crucial interactions between ligands and receptors. Then, the screening criteria for RhlR inhibitors were established hierarchically based on ligand structure characteristics, ligand–receptor interaction, and receptor affinity. Test sets were finally employed to validate the hierarchical virtual screening model by comparing it with the current SAR studies of RhlR inhibitors. The hierarchical screening model was confirmed to possess higher accuracy and a true positive rate, which holds promise for subsequent screening and the discovery of active RhlR inhibitors.

Pseudomonas aeruginosa is a clinically challenging pathogen due to its high resistance to antibiotics. Quorum sensing inhibitors (QSIs) have been proposed as a promising strategy to overcome this resistance by interfering with the bacterial communication system. Among the potential targets of QSIs, PqsR is a key regulator of quorum sensing in Pseudomonas aeruginosa. However, the current research on PqsR inhibitors is limited by the lack of diversity in the chemical structures and the screening methods. Therefore, this study aims to develop a multidimensional screening model for PqsR inhibitors based on both ligand- and receptor-based approaches. First, a pharmacophore model was constructed from a training set of PqsR inhibitors to identify the essential features and spatial arrangement for the activity. Then, molecular docking and dynamics simulations were performed to explore the core interactions between PqsR inhibitors and their receptor. The results indicate that an effective PqsR inhibitor should possess two aromatic rings, one hydrogen bond acceptor, and two hydrophobic groups and should form strong interactions with the following four amino acid residues: TYR_258, ILE_236, LEU_208, and GLN_194. Moreover, the docking score and the binding free energy should be lower than −8 kcal/mol and −40 kcal/mol, respectively. Finally, the validity of the multidimensional screening model was confirmed by a test set of PqsR inhibitors, which showed a higher accuracy than the existing screening methods based on single characteristics. This multidimensional screening model would be a useful tool for the discovery and optimization of PqsR inhibitors in the future.

Pseudomonas aeruginosa with difficult-to-treat resistance has been designated as an urgent or serious threat by the CDC in the United States; therefore, novel antibacterial drugs and combination strategies are urgently needed. The sensor kinase RoxS is necessary for the aerobic growth of Pseudomonas aeruginosa. This study aimed to screen candidate RoxS inhibitors and evaluate their efficacy in treating multi-drug-resistant and extensively drug-resistant Pseudomonas aeruginosa in combination with meropenem and amikacin to identify promising combination strategies. RoxS protein structures were constructed using homology modeling and potential RoxS inhibitors, including Ezetimibe, Deferasirox, and Posaconazole, were screened from the FDA-approved ZINC drug database using molecular docking and molecular dynamics simulations. MIC and checkerboard assays were used to determine the in vitro antimicrobial efficacy of the three drugs in combination with antibiotics. The results of in vitro experiments showed an additive effect of 100 μg/mL Deferasirox or 16 μg/mL Posaconazole in combination with meropenem and a synergistic effect of 1.5 μg/mL Deferasirox and amikacin. In summary, these three drugs are potential inhibitors of RoxS, and their combination with meropenem or amikacin is expected to reverse the resistance of P. aeruginosa, providing new combination strategies for the treatment of clinically difficult-to-treat Pseudomonas aeruginosa.

Sceletium tortuosum (SCT) has been utilized medicinally by indigenous Koi-San people purportedly for mood elevation. SCT extracts are reported to be neuroprotective and have efficacy in improving cognition. However, it is still unclear which of the pharmacological mechanisms of SCT contribute to the therapeutic potential for neurodegenerative disorders. Hence, this study investigated two aspects–firstly, the abilities of neuroprotective sub-fractions from SCT on scavenging radicals, inhibiting some usual targets relevant to Alzheimer’s disease (AD) or Parkinson’s disease (PD), and secondly utilizing the network pharmacology related methods to search probable mechanisms using Surflex-Dock program to show the key targets and corresponding SCT constituents. The results indicated sub-fractions from SCT could scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, inhibit acetylcholinesterase (AChE), monoamine oxidase type B (MAO-B) and N-methyl-D-aspartic acid receptor (NMDAR). Furthermore, the results of gene ontology and docking analyses indicated the key targets involved in the probable treatment of AD or PD might be AChE, MAO-B, NMDAR subunit2B (GluN2B-NMDAR), adenosine A_2A receptor and cannabinoid receptor 2, and the corresponding constituents in Sceletium tortuosum might be N-trans-feruloyl-3-methyldopamine, dihydrojoubertiamine and other mesembrine type alkaloids. In summary, this study has provided new evidence for the therapeutic potential of SCT in the treatment of AD or PD, as well as the key targets and notable constituents in SCT. Therefore, we propose SCT could be a natural chemical resource for lead compounds in the treatment of neurodegenerative disorders.

Two new isostructural dinuclear complexes, Ln₂(4-cpa)₆(phen)₂ (Ln = Eu (1); Tb (2), 4-cpa^– = 4-chlorophenylacetate, phen = 1,10-phenanthroline), have been hydrothermally synthesized and characterized by IR spectroscopy, elemental analysis, thermogravimetric analysis, powder X-ray diffraction, and single-crystal X-ray diffraction. The lanthanides are bridged by two bidentate and two tridentate carboxylato groups to give centrosymmetric dimers with Ln···Ln separations of 3.967(2) and 3.937(3) Å for 1 and 2, respectively. Each metal is nine-coordinate and exhibits a distorted tricapped trigonal prismatic geometry. Both 1 and 2 emit characteristic, intense luminescence at room temperature with lifetimes up to 0.890 ms (at 611 nm) and 0.995 ms (at 543 nm). Poor luminescence efficiency is observed for 2. 4-Chlorophenylacetate, 1 and 2 have been screened for their phytogrowth-inhibitory activities against Brassica napus L. and Echinochloa crusgalli L., and the results are compared with the activity of quizalofop-P-ethyl.