Diabetes is a very complex endocrine disease whose common feature is the increase in blood glucose concentration. Persistent hyperglycemia can lead to blindness, kidney and heart disease, neurodegeneration, and many other serious complications that have a significant impact on human health and quality of life. The number of people with diabetes is increasing yearly. The global diabetes prevalence in 20-79 year olds in 2021 was estimated to be 10.5% (536.6 million), and it will rise to 12.2% (783.2 million) in 2045. The main modes of intervention for diabetes include medication, dietary management, and exercise conditioning. Medication is the mainstay of treatment. Marketed diabetes drugs such as metformin and insulin, as well as GLP-1 receptor agonists, are effective in controlling blood sugar levels to some extent, but the preventive and therapeutic effects are still unsatisfactory. Peptide drugs have many advantages such as low toxicity, high target specificity, and good biocompatibility, which opens up new avenues for the treatment of diabetes and other diseases. Currently, insulin and its analogs are by far the main life-saving drugs in clinical diabetes treatment, enabling effective control of blood glucose levels, but the risk of hypoglycemia is relatively high and treatment is limited by the route of delivery. New and oral anti-diabetic drugs have always been a market demand and research hotspot. Inhibitor cystine knot (ICK) peptides are a class of multifunctional cyclic peptides. In structure, they contain three conserved disulfide bonds (C3-C20, C7-C22, and C15-C32) form a compact “knot” structure, which can resist degradation of digestive protease. Recent studies have shown that ICK peptides derived from legume, such as PA1b, Aglycin, Vglycin, Iglycin, Dglycin, and aM₁, exhibit excellent regulatory activities on glucose and lipid metabolism at the cellular and animal levels. Mechanistically, ICK peptides promote glucose utilization by muscle and liver through activation of IR/AKT signaling pathway, which also improves insulin resistance. They can repair the damaged pancrease through activation of PI3K/AKT/Erk signaling pathway, thus lowering blood glucose. The biostability and hypoglycemic efficacy of the ICK peptides meet the requirements for commercialization of oral drugs, and in theory, they can be developed into natural oral anti-diabetes peptide drugs. In this review, the structural properties, activity and mechanism of ICK pattern peptides in regulating glucose and lipid metabolism were summaried, which provided a reference for the development of new oral peptides for diabetes.

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

Diabetic foot ulcer (DFU) is one of the common chronic complications in diabetic patients. Its course is complex and the therapeutic effect is limited, which seriously affects the quality of life of patients. In recent years, significant progress has been made in the research on the mechanism of DFU wound repair. Studies have found that dysregulation of the inflammatory microenvironment, vascular dysfunction, obstruction of re-epithelialization, insufficient collagen deposition, and formation of wound biofilms are the core factors affecting healing. Intervention strategies targeting these mechanisms have become research hotspots. For instance, hydrogel scaffolds could provide an appropriate healing microenvironment, immune regulation strategies could promote inflammation resolution and tissue remodeling, and stem cell exosomes and growth factors have shown good potential in cell migration, angiogenesis, and matrix remodeling. Various natural compounds, such as components from Chinese herbal medicines, are also applied in diabetic foot ulcers. And it demonstrates excellent anti-inflammatory and restorative capabilities. However, existing research still faces obstacles in clinical translation, such as the immaturity of individualized treatment strategies and the difficulty of animal models in simulating complex clinical situations. By systematically summarizing the latest research progress on the repair mechanism of DFU, it is expected to provide theoretical support for precise treatment.
Humans ; Diabetic Foot/drug therapy* ; Wound Healing ; Animals

OBJECTIVE: To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia. METHODS: Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry. RESULTS: DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABA_A receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01). CONCLUSION DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABA_A receptors expressions and GA/GABA ratio.
Animals ; Dendrobium/chemistry* ; Rats, Sprague-Dawley ; Male ; Sleep Initiation and Maintenance Disorders/blood* ; Plant Extracts/therapeutic use* ; Receptors, GABA-A/metabolism* ; Noise/adverse effects* ; Light/adverse effects* ; gamma-Aminobutyric Acid/metabolism* ; Sleep/drug effects* ; Rats ; Receptors, GABA/metabolism*

The anti-inflammatory efficacy of Callicarpa nudiflora extract were evaluated upon lipopolysaccharide (LPS)-induced infective inflammation in rats. Pathological changes of lung and colon tissues observed with hematoxylin-eosin (H&E) staining, together with inflammatory factors in serum, including nitric oxide (NO), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), were applied to assess the mitigating effects of C. nudiflora water extract on model rats. The experimental protocol strictly adhered to the guidelines of the Ethics Committee of Animal Research of Guangdong Pharmaceutical University (Approval: gdpulac2022132). Quality markers with anti-inflammatory activities were recognized by network pharmacology analysis. Subsequently, a reliable method for simultaneously quantifying six components was established. As a result, the pathological injury on lung and colon tissues of model rats induced by LPS were improved by C. nudiflora water extract. Compared with model group, C. nudiflora extract had decreased the release of proinflammatory factors in serum, including TNF-α and IL-6, and reduced the NO (P < 0.01). Network pharmacological analysis obtained 83 chemical components, 466 component targets, 584 disease targets and 129 action targets, which were mainly concentrated in 624 biological processes such as inflammatory response and positive regulation of nitric oxide biosynthesis, as well as 162 pathways such as phosphatidylinositol-3-hydroxykinase-protein kinase (PI3K-Akt) signal pathway and Janus kinase-signal transducer and activator of transcription 3 (JAK-STAT3) signal pathway. Upon analyzing their specificity, effectiveness, detectability, and quantity transfer rule from herb to extract, 6-hydroxyluteolin 7-glucoside, cynaroside, caffeic acid, acteoside, isoacteoside, and forsythoaside B were identified as the quality markers. Their anti-inflammatory activities were verified with LPS-induced inflammation model of RAW264.7 cells. Then contents of these 6 quality markers in 16 batches of C. nudiflora were determined. Thereby, the anti-inflammatory efficacy of C. nudiflora extract were confirmed in vivo, 6-hydroxyluteolin 7-glucoside, cynaroside, caffeic acid, acteoside, isoacteoside, and forsythoaside B were identified as anti-inflammatory ingredients, which can be used as quality control indicators for the herb and related formulation.

Objective To systematically evaluate the application efficacy of failure mode and effect analysis(FMEA)management mode in the prevention and control of healthcare-associated infection(HAI).Methods Li-terature on the application of FMEA management mode in HAI prevention and control were retrieved from PubMed,Embase,the Cochrane Library,China National Knowledge Infrastructure(CNKI),VIP Database,Wanfang Data-base,and China Biomedical Literature Database(CBM).Two researchers independently screened the literature,ex-tracted data,and conducted cross checking.Risk and quality assessments were performed on the included studies of randomized controlled trials by ROB tool,the included cohort studies were scored by Newcastle-Ottawa(NOS)scale,and Meta-analysis was conducted by RevMan 5.4 software.Results A total of 22 studies involving 42 815 patients were included in the analysis,with 21 784 in the FMEA management mode group and 21 031 in the control group.Meta-analysis results showed that the incidence of HAI in the FMEA management mode group was lower than that in the control group(OR=0.31,95％CI[0.24,0.40]).Compared with the conventional management mode,incidences of superficial surgical site infection(OR=0.53,95％CI[0.36,0.78]),respiratory system infec-tion(OR=0.44,95％CI[0.35,0.56]),urinary system infection(OR=0.45,95％CI[0.38,0.53]),and blood system infection(OR=0.29,95％CI[0.18,0.45])in the FMEA management mode group were all lower(all P＜0.01).Conclusion The application of FMEA management mode in HAI prevention and control can reduce the inci-dence of HAI,which should be actively promoted in hospital management.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.