To analyze the antimicrobial sensitivity against clinical isolates in the first affiliated hospital of air force medical university in the past three years.

The nonduplicate clinical isolates were collected in 2021—2023, identification and drug sensitivity test were performed by using VITEK2-compact automatic bacteria identification system. The data was analyzed using WHONET 5.6 software and interpreted according to the Clinical and Laboratory Standards Institute (CLSI) 2023 breakpoints.

A total of 20 536 clinical isolates were collected, of which 28.78% were gram-positive, 58.64% were gram-negative, 11.94% were fungi and 0.64% were anaerobe. The prevalence of methicillin-resistant strains in Staphylococcus aureus and coagulase-negative Staphylococcus were 49.11% and 73.06%, respectively. No Staphylococcus resistant to vancomycin, linezolid, or tigecycline was detected. The resistance rates of Enterococcus faecium to most antimicrobial agents were much higher than Enterococcus faecalis. 8 strains of vancomycin-resistant Enterococcus faecium were isolated, and a few linezolid-resistant strains were identiffed in both species. The prevalence of penicillin-susceptible Streptococcus pneumoniae (PSSP) was 95.85%. The resistance rate to carbapenems was 0.2% to 12.8% in Enterobacterales species, and the detection rate of carbapenem-resistant Enterobacteriaceae (CRE) was 6.6%, with Klebsiella pneumoniae accounting for 66.53%. The resistance rates of Acinetobacter spp to imipenem and meropenem were 75.3% and 76.7%, respectively. Meanwhile, the rates of Pseudomonas aeruginosa were 22.9% and 19.9% respectively.

The antimicrobial resistance of clinical isolates in our hospital is still serious. All relevant departments should strengthen the monitoring of bacterial resistance in order to curb the development and spread of bacterial resistance.

To study the bioequivalence of two formulations of haloperidol tablets in healthy Chinese subjects.

The randomized, open, single dose, two periods, crossover study design was adopted in the study. Twenty-eight healthy subjects were enrolled under fasting condition and given either test preparation or reference preparation 2 mg respectively in one period. After collecting plasma samples, the plasma concentrations of haloperidol were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The pharmacokinetic parameters were calculated by WinNonlin 8.0 and the bioequivalence was evaluated using the average bioequivalence (ABE) method.

The pharmacokinetic parameters of haloperidol of the test preparation or reference preparation were as follow: C_max were (719.50±378.43) and (703.43±329.63) pg·mL^-1, AUC_0-t were (1.94×10⁴±6 766.21) and (1.94×10⁴±6 522.79) pg·h·mL^-1, AUC_0-∞ were (2.31×10⁴±7 693.66) and (2.30×10⁴±7 309.97) pg·h·mL^-1. The 90% confidence intervals (CI) of the geometric mean ratio (GMR) were 92.46%-114.76%, 96.70%-108.15%, 96.36%-111.34% for C_max, AUC_0-t and AUC_0-∞, respectively, which were within the acceptance criteria of 80.00%-125.00%.

The two preparations of haloperidol tablets were bioequivalent in Chinese healthy subjects.

To develop a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying 16 bioactive constituents of Gardenia jasminoides Eills in various murine tissues.

The ileum, colon, stomach, liver, kidney and brain tissues of mice were collected following intragastric administration of Gardenia jasminoides Ellis. Subsequently, the samples were processed by precipitating protein. The analysis was performed using the Waters CORTECS C₁₈ column (4.6 mm×150.0 mm, 2.7 μm) with mobile phase gradient elution consisting of a methanol-water solution, and specnuezhenide was used as the internal standard; the flow rate was set at 0.4 mL·min^-1 while maintaining a column temperature of 40 ℃; detection was performed in negative ion mode utilizing an electrospray ion source. Furthermore, the method was evaluated for its specificity, standard curve and lower limit of quantification, precision and recovery, stability and reproducibility. Additionally, the tissue distribution characteristics of the active components of Gardenia jasminoides Ellis in mice were investigated.

This study established a method for the analysis of 16 bioactive constituents in Gardenia jasminoides Ellis within complex matrices. The linear range spanned from 0.98 to 6.00×10⁴ ng·mL^-1, with a limit of quantitation ranging from 0.92 to 11.72 ng·mL^-1, and the RSD values for intra-day and inter-day precision as well as recovery were all below 15%. Amongst the examined tissues, ileum tissue exhibited the highest levels of these active components, followed by gastric tissue. Iridoid components demonstrated extensive distribution across various tissues. The diterpenoid constituent crocetin was predominantly found in the liver and brain, while crocin Ⅱ showed higher distribution in the colon.

The method exhibits high specificity, excellent sensitivity, reproducibility, and stability. Moreover, the matrix effect can be controlled effectively, rendering it suitable for analyzing Gardenia jasminoides Ellis in complex matrices. The intestine is the major tissue for the distribution of Gardenia jasminoides Ellis, which may be an important part for its efficacy. Furthermore, the extensive pharmacological effects of Gardenia jasminoides Ellis may be related to the component tendency to different tissues.

To establish a pharmacodynamic model of sodium-glucose transporter 2 inhibitors (SGLT-2i) in order to evaluate the efficacy characteristics of the drugs.

A model-based meta-analysis was used. By searching randomized controlled trials of SGLT-2i monotherapy in patients with type 2 diabetes (T2DM) in databases, the change in glycosylated hemoglobin (HbA1c) from baseline was used as the efficacy indicator. The pharmacodynamic models of SGLT-2i and placebo were constructed, and the covariates were screened to determine the factors affecting the drug’s efficacy.

A total of 39 studies were included, involving 96 trial groups, 8 534 participants, and 13 drugs (dapagliflozin, canagliflozin, empagliflozin, ipragliflozin, luseogliflozin, ertuglilfozin, enavogliflozin, henagliflozin, licogliflozin, sotagliflozin, bexagliflozin, janagliflozin and tofogliflozin). The time-effect relationships of the drug group and the placebo group were consistent with the E_max model, and fasting plasma glucose baseline had an effect on the pharmacodynamic parameters of SGLT-2i.

The final model can describe the pharmacodynamic characteristics of the drug and placebo groups, and there is a significant association between FPB baseline and drug efficacy.

To analyze iron death genes and related pathogenesis in chronic thromboembolic pulmonary hypertension (CTEPH) based on bioinformatics, and to screen potential traditional Chinese medicine (TCM) active ingredients for treating CTEPH through iron death related pathways.

The differentially expressed genes in dataset GSE130391 were analyzed by R language, and the genes related to iron death were obtained from FerrDB database. The intersection of the two genes was selected, and the intersection genes were enriched by Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO). The intersection genes were analyzed by random forest algorithm, and the key genes were obtained. The immune infiltration analysis of GSE130391 was performed by cibesort algorithm. Potential TCM active ingredients were screened by cMAP database, and the binding stability and affinity of TCM active ingredients and key targets were analyzed by molecular docking and molecular dynamics simulation.

A total of 878 DEGs were obtained, 264 iron death related genes and 14 intersection genes were obtained from FerrDB database. There were 630 items in GO enrichment analysis, and 13 pathways were enriched by KEGG. Three key genes were obtained by random forest algorithm. Immunoinfiltration analysis showed that dendritic cells and mast cells were inhibited in CTEPH group, and immunoinfiltration correlation showed that mast cells were strongly correlated with M1 macrophages, M1 macrophages were strongly correlated with T cells, and the key gene arachidonic acid 12-lipoxygenase 12R type (ALOX12B) was positively correlated with M2 macrophages. Cytokine signal transduction inhibitor 1 (SOCS1) was negatively correlated with M2-type macrophages. The active ingredients of traditional Chinese medicine were ononanthine and rotensin screened in cMAP database. Molecular docking and molecular dynamics simulation analysis showed that rotensin and ALOX12B had stable binding energy and strong affinity.

The therapeutic targets related to iron death in CTEPH are found by bioinformatics method and the active components of Chinese medicine that can be targeted for intervention are screened.

To study the possible mechanism and related signaling pathway of cell senescence in hypertensive nephropathy with the help of bioinformatics.

The microarray data GSE37455 was downloaded from the gene expression database, and the data was merged with R software to remove the batch effect, so as to obtain differentially expressed genes. Cell aging genes were obtained from the CellAge database, and differential genes related to cell aging were obtained through R package “ggVennDiagram”. Gene interaction network string database was imported to obtain protein protein interaction (PPI) network map, and Cytoscape3.8.0 software was used to mine core differential genes. The function and pathway of core differential genes were analyzed by gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA).

A total of 41 differential genes were obtained, including 32 up-regulated genes and 9 down-regulated genes. Four differential genes related to cell senescence were obtained after intersection. The core differential gene-activated transcription factor 3(ATF3) was obtained by PPI analysis and Cytoscape treatment. GSEA analysis showed that cell senescence might play a role in hypertensive nephropathy through the thermogenesis of mitochondrial uncoupling protein 1 and the signal transduction of type Ⅰ interferon response (TYPE-Ⅰ-IFN).

Cellular senescence may play a role in hypertensive nephropathy through pathways such as mitochondrial uncoupling protein-1 thermogenesis and TYPE-Ⅰ-IFN signaling, which provides a therapeutic target for the study of hypertensive nephropathy.