BACKGROUND: The application of programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) antibodies has greatly improved the clinical outcomes of lung cancer patients. Here, we retrospectively analyzed the efficacy of PD-1 antibody therapy in locally advanced non-surgical or metastatic lung cancer patients, and preliminarily explored the correlation between peripheral blood biomarkers and clinical responses. METHODS: We conducted a single center study that included 61 IIIA-IV lung cancer patients who received PD-1 antibody treatment from March 2020 to December 2021, and collected the medical record data on PD-1 antibody first-line or second-line treatment. The levels of multiple Th1 and Th2 cytokines in the patient's peripheral blood serum, as well as the phenotype of peripheral blood T cells, were detected and analyzed. RESULTS: All the patients completed at least 2 cycles of PD-1 monoclonal antibody treatment. Among them, 42 patients (68.9%) achieved partial response (PR); 7 patients (11.5%) had stable disease (SD); and 12 patients (19.7%) had progressive disease (PD). The levels of peripheral blood interferon gamma (IFN-γ) (P=0.023), tumor necrosis factor α (TNF-α) (P=0.007) and interleukin 5 (IL-5) (P=0.002) before treatment were higher in patients of the disease control rate (DCR) (PR+SD) group than in the PD group. In addition, the decrease in absolute peripheral blood lymphocyte count after PD-1 antibody treatment was associated with disease progression (P=0.023). Moreover, the levels of IL-5 (P=0.0027) and IL-10 (P=0.0208) in the blood serum after immunotherapy were significantly increased compared to baseline. CONCLUSIONS Peripheral blood serum IFN-γ, TNF-α and IL-5 in lung cancer patients have certain roles in predicting the clinical efficacy of anti-PD-1 therapy. The decrease in absolute peripheral blood lymphocyte count in lung cancer patients is related to disease progression, but large-scale prospective studies are needed to further elucidate the value of these biomarkers.
Humans ; Lung Neoplasms/metabolism* ; Interleukin-5/therapeutic use* ; Tumor Necrosis Factor-alpha/therapeutic use* ; Retrospective Studies ; Programmed Cell Death 1 Receptor ; Biomarkers ; Immunotherapy ; Disease Progression ; B7-H1 Antigen

OBJECTIVE: To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images. METHODS: Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD. RESULTS: A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set. CONCLUSIONS The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.
Humans ; Non-alcoholic Fatty Liver Disease/diagnostic imaging* ; Ultrasonography ; Anthropometry ; Algorithms ; China

Biosensor analysis technology is a kind of technology with high specificity that can convert biological reactions into optical and electrical signals. In the development of drugs for Alzheimer's disease (AD), according to different disease hypotheses and targets, this technology plays an important role in confirming targets and screening active compounds. This paper briefly describes the pathogenesis of AD and the current situation of therapeutic drugs, introduces three biosensor analysis techniques commonly used in the discovery of AD drugs, such as surface plasmon resonance (SPR), biolayer interferometry (BLI) and fluorescence analysis technology, explains its basic principle and application progress, and summarizes their advantages and limitations respectively.

Based on the strategy of metabolomics combined with bioinformatics, this study analyzed the potential allergens and mechanism of pseudo-allergic reactions (PARs) induced by the combined use of Reduning injection and penicillin G injection. All animal experiments and welfare are in accordance with the requirements of the First Affiliated Experimental Animal Ethics and Animal Welfare Committee of Henan University of Chinese Medicine (approval number: YFYDW2020002). Based on UPLC-Q-TOF/MS technology combined with UNIFI software, a total of 21 compounds were identified in Reduning and penicillin G mixed injection. Based on molecular docking technology, 10 potential allergens with strong binding activity to MrgprX2 agonist sites were further screened. Metabolomics analysis using UPLC-Q-TOF/MS technology revealed that 34 differential metabolites such as arachidonic acid, phosphatidylcholine, phosphatidylserine, prostaglandins, and leukotrienes were endogenous differential metabolites of PARs caused by combined use of Reduning injection and penicillin G injection. Through the analysis of the "potential allergen-target-endogenous differential metabolite" interaction network, the chlorogenic acids (such as chlorogenic acid, neochlorogenic acid, cryptochlorogenic acid, and isochlorogenic acid A) and β-lactam allergens in the combination of the two may be mainly regulated by PLD1, PLA2G12A and CYP1A1. The three upstream signal target proteins mainly activate the arachidonic acid metabolic pathway, promote the degranulation of mast cells, release downstream endogenous inflammatory mediators, and induce PARs.

Humans ; Adolescent ; Acne Vulgaris/therapy* ; Skin Care ; Surveys and Questionnaires ; Cognition ; China ; Skin

Ferroptosis is an iron-dependent form of regulated cell death,which is distinct from apoptosis,ne-crosis,and pyroptosis.Recent studies have found that activators of ferroptosis,such as Erastin,can activate autophagy-re-lated proteins,induce the formation of autophagosomes,and ultimately release ferric ions to mediate ferroptosis.This pro-cess,called ferritinophagy,is initiated by the binding of an autophagic cargo receptor protein,nuclear receptor coactivator 4(NCOA4),to iron-laden ferritin.The transfer of NCOA4-ferritin to the lysosome by ferritinophagy results in the proteoly-sis of ferritin,and,in turn,the release of its iron content and lipid-reactive oxygen species(ROS)accumulation.Ferritin-ophagy has been closely associated with central nervous system disorders,circulatory system diseases,and cancer.Fur-thermore,the regulation mechanism of ferritinophagy is also a hot topic in the study of iron-dependent cell death process.With the in-depth study of ferritinophagy,great progress has been made in the study of key components of ferritinophagy as well as its molecular mechanisms and processes.However,a comprehensive summary of the methods for detecting ferritin-ophagy is still unclear.To further deepen the understanding of ferritinophagy and its detection methods,this review focus-es on the concept,characteristics,methods,and precautions during detection of ferritinophagy.This review provided ex-perimental reference for subsequent researchers and promoting the progress of research related to ferritinophagy.

Objective:To investigate the distribution characteristics of urinary tract pathogens in patients with community-acquired urinary tract infection and their sensitivity to nenoxacin and levofloxacin.Methods:This prospective, multicenter clinical trial included patients with community-acquired urinary tract infection who were admitted to urological clinics at 9 clinical research centers from November 2021 to August 2022.Inclusion criteria: Patients aged 18-70 years with community-acquired acute uncomplicated cystitis(AUC), recurrent acute episodes of urinary tract infection(rUTI), and non-febrile complicated urinary tract infection(cUTI) with signs of urinary tract irritation and abnormal elevation of routine white blood cells in urine. Exclusion criteria: ①Patients who received effective antimicrobial therapy within 72 h before enrollment and lasted for more than 24 h. ②Fever (>37.3℃) or symptoms of upper urinary tract infection such as low back pain, tapping pain in the kidney area, etc. ③Indwelling urinary catheter. At the first visit, clean midstream urine samples were taken for bacterial culture, and the distribution characteristics of urinary pathogens of different types of urinary tract infections were analyzed. Extended spectrum β-lactamases (ESBLs) were measured for Gram-negative bacteria. The susceptibility of nenoxacin and levofloxacin to urinary tract pathogens was determined by disk diffusion method. Drug resistance rate, sensitivity rate were analyzed between different disease groups.Results:There were 404 enrolled patients from 9 hospitals, including 364 (90.1%) females and 40 (9.9%) males. A total of 177 strains of pathogenic bacteria were isolated, among which the highest proportion of Escherichia coli was 66.1% (117/177).Klebsiella pneumoniae was followed by 6.8% (12/177) and Streptococcus agalactis 5.1% (9/177). The bacterial spectrum distribution of AUC and rUTI were similar, and the proportions of Escherichia coli were 70.6% (85/119) and 65.9% (29/44), respectively. However, the proportions of Escherichia coli isolated from cUTI patients were only 28.6% (4/14) and Enterococcus faecalis 7.1%(1/14). The overall detection rate of ESBLs in Gram-negative bacteria was 30.9%(43/139). The sensitivity rate of nenoxacin was 74.6%(91/122), and the resistance rate was 25.4%(31/122). The overall sensitivity rate of levofloxacin was 44.9%(70/156) and the resistance rate was 36.5%(57/156). The rate of resistance of urinary tract pathogens to levofloxacin was 48.2% (27/56) in patients with previous urinary tract infection history, and 30.0% (30/100) in patients with no previous urinary tract infection history, the difference was statistically significant( P=0.023).The sensitivity rate of Gram-negative bacteria to nenofloxacin was 70.7% (65/92) and that to levofloxacin was 50.0% (46/92, P<0.001). The sensitivity of Gram-positive bacteria to nenofloxacin was 80.0% (16/20), and that to levofloxacin was 70.0% (14/20, P=0.009). Conclusions:The bacterial profile of out-patient community acquired urinary tract infection varies greatly according to different diseases. The proportion of Escherichia coli in AUC and rUTI patients is higher than that in cUTI. The detection rate of ESBLs in Gram-negative bacteria was lower than the domestic average.Patients with a history of urinary tract infection had a high risk of treatment failure with levofloxacin. The sensitivity of common urinary tract pathogens to nenofloxacin was higher than levofloxacin.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.

Tendon-bone healing is a complex biological process. Multiple signaling pathways are involved in tendon-bone healing， including transforming growth factor-β signaling pathway， bone morphogenetic protein signaling pathway， Wnt signaling pathway， fibroblast growth factor signaling pathway and nuclear transcription factor-κB signaling pathway. This paper summarizes the research status of traditional Chinese medicine regulating related signaling pathways to promote tendon-bone healing. It is found that a variety of traditional Chinese medicine monomers or herbal extracts （such as baicalein， icariin， total flavonoids of Drynaria fortunei， parthenolide， total saponins of Panax notoginseng， etc.） and traditional Chinese medicine compounds （such as Taohong siwu decoction， Liuwei dihuang pill， Xujin jiegu liquid， etc.） can promote bone formation， anti-inflammatory， anti-oxidation， by regulating the above signaling pathways， thereby effectively promoting tendon-bone healing.

Objective:To explore the potential therapeutic targets of apigenin in the treat-ment of thyroid carcinoma by network pharmacology.Methods:The targets of apigenin were screened by HIT(High Throughput),Binding Database,SEA(Similarity Ensemble Approach),STITCH(Search Tool for Interactions of Chemicals),PharmMapper.Thyroid carcinoma related targets were mined from TTD(Therapeutic Target Database),DrugBank,CTD(Comparative Toxicogenomics Da-tabase),DisGeNET databases.The String database and Cytoscape 3.2.1 software were used to identify and screen out the hub targets of apigenin for thyroid carcinoma.The David database was used for Gene Ontology(GO)enrichment and KEGG signal pathway enrichment analysis of hub tar-gets.Finally,the Kaplan-Meier Plotter database was used to analyze the prognosis of hub targets.Results:175potential targets of apigenin and 168 potential targets related to thyroid carcinoma were included.37 overlapping targets of apigenin and thyroid carcinoma were obtained.32 hub targets were finally selected by network topology analysis.These hub targets of apigenin in the treatment of thyroid carcinoma were mainly enriched in involving HIF-1 signaling pathway,path-ways in cancer,etc.Finally,8 targets were screened to be associated with the survival and prog-nosis of thyroid carcinoma patients.Conclusion:Our study suggested that ALB,CCNA2,CCND1,CYP2C19,TERT,TTR,BCL2,CBR1 might be potential therapeutic targets for apigenin in the treatment of thyroid carcinoma.