Objective To investigate the relationship between serum glial fibrillary acidic protein(GFAP)level and transcranial Doppler(TCD)parameters in carotid stenosis patients after carotid stent implantation.Methods A total of 123 patients with carotid stenosis who received carotid stent implantation in our hospital from September 2021 to February 2024 were recruited,and di-vided into a normal group(39 cases)and a damaged group(84 cases)according to their cerebro-vascular reserve.The GFAP level and TCD parameters were collected before and after treatment.ROC curve analysis was employed to analyze the value of GFAP level in evaluating cerebrovascu-lar reserve in the patients.Results Significantly larger proportion of diabetes and higher level of total cholesterol were observed in the damaged group than the normal group(P＜0.05).Mean flow velocity(MFV),pulse index(PI),peak systolic velocity(PSV),and levels of GFAP,neuron-specific enolase(NSE)and S-100β were all obviously decreased in both groups after surgery than the levels before(P＜0.05).When compared with the normal group,the damaged group had nota-bly higher serum GFAP level before operation,and lower PI and PSV values and higher GFAP,NSE and S-100β levels after operation(P＜0.05,P＜0.01).Both pre-and post-operative serum GFAP levels were negatively correlated with postoperative MFV,PI and PSV(P＜0.01).The concomitant diabetes,pre-and post-operative serum GFAP levels,and postoperative PSV value and NSE and S-100β levels were independent influencing factors for cerebrovascular reserve in ca-rotid stenosis patients after carotid stent implantation(P＜0.05,P＜0.01).The post-operative se-rum GFAP level showed significantly better value than the pre-operative level in assessing cere-brovascular reserve,with an AUC value of 0.860(95％CI:0.786-0.916)and 0.777(95％CI:0.693-0.847),respectively.Conclusion Serum GFAP level is related to TCD parameters in ca-rotid stenosis patients after carotid stent implantation.Combined GFAP level and TCD parameters together can be used to evaluate the cerebrovascular reserve for the patients.

Objective·To investigate the causal relationship between plasma zinc-alpha-2-glycoprotein 1(AZGP1)and heart failure(HF)by using Mendelian randomization(MR)analysis and experimental validation.Methods·A two-sample MR analysis was performed to assess the causal relationship between AZGP1 and HF by integrating large-scale genome-wide association study(GWAS)data on plasma proteins and HF.The inverse-variance weighted(IVW)method was employed as the primary analytical approach,supplemented by MR-Egger regression,weighted median,and simple median methods.Horizontal pleiotropy was tested by using MR-PRESSO global test and MR-Egger intercept analysis.Colocalization analysis was conducted to validate genetic locus overlap.Additionally,a clinical cohort(84 HF patients and 68 healthy controls)was analyzed,with plasma AZGP1 levels quantified by enzyme-linked immunosorbent assay(ELISA).Results·MR analysis showed that elevated plasma AZGP1 levels were significantly associated with reduced HF risk(OR=0.82,95%CI 0.75?0.90,P=1.70×10-5).Colocalization analysis confirmed that AZGP1 expression and HF shared causal genetic variants(posterior probability for H4=0.69).Sensitivity and reverse MR analyses supported the robustness of the results.ELISA confirmed that plasma AZGP1 levels were significantly lower in HF patients compared to healthy controls,reinforcing its protective role in HF.Conclusion·This study demonstrates AZGP1 exerts a protective causal effect on HF and may serve as a potential biomarker for HF treatment.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective·To investigate the causal relationship between plasma zinc-alpha-2-glycoprotein 1(AZGP1)and heart failure(HF)by using Mendelian randomization(MR)analysis and experimental validation.Methods·A two-sample MR analysis was performed to assess the causal relationship between AZGP1 and HF by integrating large-scale genome-wide association study(GWAS)data on plasma proteins and HF.The inverse-variance weighted(IVW)method was employed as the primary analytical approach,supplemented by MR-Egger regression,weighted median,and simple median methods.Horizontal pleiotropy was tested by using MR-PRESSO global test and MR-Egger intercept analysis.Colocalization analysis was conducted to validate genetic locus overlap.Additionally,a clinical cohort(84 HF patients and 68 healthy controls)was analyzed,with plasma AZGP1 levels quantified by enzyme-linked immunosorbent assay(ELISA).Results·MR analysis showed that elevated plasma AZGP1 levels were significantly associated with reduced HF risk(OR=0.82,95%CI 0.75?0.90,P=1.70×10-5).Colocalization analysis confirmed that AZGP1 expression and HF shared causal genetic variants(posterior probability for H4=0.69).Sensitivity and reverse MR analyses supported the robustness of the results.ELISA confirmed that plasma AZGP1 levels were significantly lower in HF patients compared to healthy controls,reinforcing its protective role in HF.Conclusion·This study demonstrates AZGP1 exerts a protective causal effect on HF and may serve as a potential biomarker for HF treatment.

Objective To investigate the relationship between serum glial fibrillary acidic protein(GFAP)level and transcranial Doppler(TCD)parameters in carotid stenosis patients after carotid stent implantation.Methods A total of 123 patients with carotid stenosis who received carotid stent implantation in our hospital from September 2021 to February 2024 were recruited,and di-vided into a normal group(39 cases)and a damaged group(84 cases)according to their cerebro-vascular reserve.The GFAP level and TCD parameters were collected before and after treatment.ROC curve analysis was employed to analyze the value of GFAP level in evaluating cerebrovascu-lar reserve in the patients.Results Significantly larger proportion of diabetes and higher level of total cholesterol were observed in the damaged group than the normal group(P＜0.05).Mean flow velocity(MFV),pulse index(PI),peak systolic velocity(PSV),and levels of GFAP,neuron-specific enolase(NSE)and S-100β were all obviously decreased in both groups after surgery than the levels before(P＜0.05).When compared with the normal group,the damaged group had nota-bly higher serum GFAP level before operation,and lower PI and PSV values and higher GFAP,NSE and S-100β levels after operation(P＜0.05,P＜0.01).Both pre-and post-operative serum GFAP levels were negatively correlated with postoperative MFV,PI and PSV(P＜0.01).The concomitant diabetes,pre-and post-operative serum GFAP levels,and postoperative PSV value and NSE and S-100β levels were independent influencing factors for cerebrovascular reserve in ca-rotid stenosis patients after carotid stent implantation(P＜0.05,P＜0.01).The post-operative se-rum GFAP level showed significantly better value than the pre-operative level in assessing cere-brovascular reserve,with an AUC value of 0.860(95％CI:0.786-0.916)and 0.777(95％CI:0.693-0.847),respectively.Conclusion Serum GFAP level is related to TCD parameters in ca-rotid stenosis patients after carotid stent implantation.Combined GFAP level and TCD parameters together can be used to evaluate the cerebrovascular reserve for the patients.

Octapeptin has strong antibacterial activity against Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii, while it also has activity against some Gram-positive bacteria. This study used natural octapeptin A3 and B3 as lead compounds for structural modification. Twenty-one peptide derivatives (including A3 and B3) containing eight amino acid residues were prepared by solid-phase synthesis, and evaluated for antibacterial activity and renal cytotoxicity. Among them, three compounds 6, 7 and 17 exhibited broad-spectrum antibacterial activity and significantly enhanced the activity for Gram-positive bacteria while maintaining the activity of Gram-negative bacteria. Several compounds improved the activity for Pseudomonas aeruginosa. Compound 7 was active against all test strains and had relatively low renal cytotoxicity. The results provide a basis for the further development of novel polypeptide antibiotics.

Objective To investigate the expression of serum Elabela and leucine-rich-alpha-2-glycoprotein-1(LRG1)in ulcerative colitis(UC)patients and their correlation with disease activity index(DAI).Methods A total of 98 patients with UC admitted to Yuncheng Central Hospital from January to December 2022 were selected as the UC group,including 62 patients in active stage and 36 patients in remission stage.According to the severity of the disease,these patients were divided into mild group(n=26),moderate group(n=43)and severe group(n=29).In addition,these patients were grouped into gradeⅠ group(n=25),grade Ⅱ group(n=40)and grade Ⅲ group(n=33)based on the endoscopic activity index(EAI).According to the mucosal healing condition under endoscopy,these patients were divided into the healed group(n=65)and the unhealed group(n=33).Another 51 patients with colonic polyps were selected as control group 1,and 50 healthy individuals were selected as control group 2.Serum Elabela and LRG1 levels were detected by enzyme-linked immunosorbent assay(ELISA).Pearson method was used to analyze the correlation between serum Elabela,LRG1 levels and DAI in UC patients.Receiver operating characteristic(ROC)curve was applied to analyze the predictive value of serum Elabela and LRG1 for endoscopic mucosal healing.Results The levels of Elabela(4.77±1.36 ng/ml)and LRG1(352.12±39.45 ng/ml)in UC group were higher than those in control group 1(2.51±0.53 ng/ml,121.02±21.06 ng/ml)and control group 2(2.35±0.42 ng/ml,120.35±23.49 ng/ml),and the differences were statistically significant(t= 11.410～39.000,all P＜0.05).The levels of Elabela(5.26±0.54 ng/ml)and LRG1(370.42±12.49 ng/ml)in the active group were higher than those in the remission group(3.93±0.42 ng/ml,320.60±8.47 ng/ml),and the differences were statistically significant(t=12.705,21.242,all P＜0.05).The levels of Elabela(5.89±0.20 ng/ml)and LRG1(369.92±16.59 ng/ml)in the severe group were higher than those in the moderate groups(4.51±0.67 ng/ml,356.12±18.75 ng/ml)and mild groups(3.95±0.21 ng/ml,325.65±10.14 ng/ml),and the differences were statistically significant(t=3.205～35.077,all P＜0.05).The levels of Elabela(5.80±0.18 ng/ml)and LRG1(369.16±13.47 ng/ml)in grade Ⅲ group were higher than those in grade Ⅱ group(4.49±0.35 ng/ml,355.46±16.34 ng/ml)and grade Ⅰgroup(3.86±0.16 ng/ml,324.15±8.71 ng/ml),and the differences were statistically significant(t= 3.854～48.725,all P＜0.05).The levels of Elabela(5.12±0.42 ng/ml)and LRG1(367.12±14.27 ng/ml)in unhealed group were higher than those in healed group(4.08±0.37 ng/ml,322.57±10.35 ng/ml),and the differences were statistically significant(t=12.043,15.917,all P＜0.05).The serum levels of Elabela and LRG1 in UC patients were positively correlated with EAI and ESR(r=0.602,0.298;0.576,0.302,all P＜0.05),but negatively correlated with hemoglobin level(r=-0.351,-0.334,all P＜0.05).The area under the curve predicted by the combination of serum Elabela and LRG1 for endoscopic mucosal healing was 0.926(95%CI:0.880～0.958),was higher than the 0.803(95%CI:0.741～0.856)and 0.783(95%CI:0.720～0.838)predicted by Elabela and LRG1 alone,and the difference was statistically significant(Z=4.101,4.228,all P＜0.05).Conclusion The serum levels of Elabela and LRG1 in UC patients increased,and they were related to the increase of DAI and worsening of the condition.Testing serum Elabela and LRG1 can provide a reference for evaluating mucosal healing under UC endoscopy.

Exploring the action targets (groups) of traditional Chinese medicine (TCM) is an important proposition to promote the innovation and development of TCM, but it has attracted a lot of attention as to whether it is related to the efficacy or the disease. Our team found that the metabolomic signature molecules in the development of diabetes mellitus (DM) were significantly associated with the clinical efficacy of Yuquan Pill through a large clinical sample study. Taking this as a clue, our team intends to expand the information on the omics features of DM development, and discover the key targets (groups) and their lead compounds for the hypoglycemic effect of Yuquan Pill. The project includes: ① Based on the retrospective clinical trials, using omics technology integrated with generative artificial intelligence, mining the characteristic information of proteome and microbiome, forming driving factors together with metabolome characteristic molecules, and characterizing the molecular trajectories of diabetes evolution and their interference by Yuquan Pill; ② Taking the evolving molecular trajectories as a link and pointer, using anthropomorphic modeling and molecular biology techniques such as chemical proteomics to discover the key targets (groups) of Yuquan Pill's hypoglycemic effect, with the prospective clinical samples for validation; ③ Evaluate the overall response of key targets (groups) using graph neural network technology, and search for drug-derived/endogenous lead compounds with proven clinical pathologies and clear mechanisms of action, so as to provide a new paradigm and technology for the discovery of complex active ingredient targets (groups) of TCM that are related to their clinical efficacy, as well as for the discovery of innovative medicines.

ObjectiveThe advent of atomic force microscope (AFM) provides a powerful tool for the studies of life sciences. Particularly, AFM-based indentation assay has become an important method for the detection of cellular mechanics, yielding numerous novel insights into the physiological and pathological activities from the single-cell level and considerably complementing traditional biochemical ensemble-averaged assays. However, current AFM indentation technology is mainly dependent on manual operation with low efficiency, seriously restricting its practical applications in the field of life sciences. Here, a method based on the combination of deep learning image recognition and AFM is developed for precisely and efficiently detecting the mechanical properties of single isolated cells and clustered cells. MethodsThe YOLO deep learning algorithm was used to recognize the central region of the cell in the optical image, the dual UNet neural network with an embedded vision transformer (ViT) module was used to recognize the peripheral regions of cell, and the template matching algorithm was used to recognize the tip of spherical probe. Based on the automatic determination of the positional relationships between the microsphere tip and the different parts of cell, the AFM tip was accurately moved to the central and peripheral regions of the target cell for rapid measurements of cell mechanical properties. Two types of cells, including HEK 293 cell (human embryonic kidney cell) and HGC-27 cell (human undifferentiated gastric cancer cell), were used for the experiments. The Hertz model was applied to analyze the force curves obtained on cells to obtain cellular Young’s modulus. ResultsAFM probe can be precisely moved to the different parts (central areas and peripheral areas) of cells to perform mechanical measurements under the guidance of deep learning-based optical image automatic recognition. The experimental results show that the proposed method is not only suitable for single isolated cells, but also suitable for clustered cells. ConclusionThe research demonstrates the great potential of deep learning image recognition to aid AFM in the precise and efficient detection of cellular mechanical properties mechanics, and combining deep learning-based image recognition with AFM will benefit the development of high-throughput AFM-based methodology to measure the mechanical properties of cells.