Antibodies play a critical role in adaptive immune responses and serve as key components in disease diagnosis and treatment. These molecules exhibit dynamic post-translational modifications (PTMs), such as glycosylation and phosphorylation, which regulate their effector functions. To date, nearly all of our knowledge about antibody repertoires has come from B cell receptor (BCR) sequencing (BCR-seq), which facilitates the profiling of clonal composition and the tracing of maturation trajectories within B-cell repertoires. However, circulating antibodies found in bodily fluids—such as serum, saliva, milk, mucosal secretions, and cerebrospinal fluid—exhibit diversities and specificities beyond what BCR-seq alone can predict. Therefore, identifying and quantifying antibody clonotypes at the protein level could enhance diagnosis, prognosis, and treatment strategies in personalized medicine. The critical gap between genotype and phenotype necessitates complementary methodologies that enable the direct characterization of antibody proteins in their native functional states. Mass spectrometry (MS)-based antibody repertoire sequencing (Ab-seq) is currently the only feasible approach for this task and primarily includes database-dependent methods—such as bottom-up, middle-down, and top-down approaches—as well as database-independent de novo sequencing technology. These strategies enable multi-level, high-precision characterization ranging from peptides and domains to intact antibody molecules. Unlike the shotgun strategy commonly used in routine proteomics, obtaining full sequences of all antibodies presents unique challenges. It requires specialized methodological adaptations to address issues related to dynamic range, sequence variation, and sample complexity. This review introduces the technical principles, methodological workflows, and recent applications of various mass spectrometry-based antibody repertoire sequencing (Ab-seq) strategies, with a focus on approaches designed to improve sequence coverage and identification accuracy. These include multi-enzyme digestion, hybrid fragmentation methods, and artificial intelligence-assisted de novo sequencing. By systematically comparing database-dependent techniques—such as bottom-up, middle-down, and top-down approaches—with database-independent de novo sequencing, this review outlines their respective advantages and limitations in terms of sample throughput, sequence coverage, post-translational modification characterization, and data analysis complexity. In addition, this review discusses emerging technological trends, including the integration of ion mobility separation, native mass spectrometry, and artificial intelligence-driven data interpretation, which are expected to enhance the depth and accuracy of antibody characterization. Although current methods continue to face challenges related to sample complexity, dynamic range, and unambiguous sequence variant assignment, we emphasize the importance of integrating BCR-seq and Ab-seq data to construct gene-protein association maps. These maps help validate sequence accuracy and facilitate epitope discovery. This dual-platform strategy helps bridge the gap between genotype and phenotype, thereby enhancing both the resolution and scope of antibody repertoire studies. Such an integrative approach also offers a valuable tool for therapeutic antibody development, structure-function analysis, and precise evaluation of vaccine efficacy.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.

Aim To investigate the therapeutic effect of newly formulated Tadalafil tablets on liver fibrosis in mice induced by carbon tetrachloride(CCl4)and its impact on the activation of hepatic stellate cells(HSCs).Methods Liver fibrosis model was estab-lished by intraperitoneally injecting 20％CCl4 corn oil solution twice a week for eight weeks.After four weeks of modeling,the treatment group was administered ei-ther the newly formulated Tadalafil tablets(1.0 mg·kg-1)or the Cialis(2.5 mg·kg-1)via gavage for the remaining four weeks.We assessed the effects of Tadalafil on collagen deposition,tissue structural dam-age,and HSCs activation markers in the fibrotic liver of mice using serum biochemical analysis,histopathologi-cal staining,and Western blotting following the treat-ment period.LX-2 cells were cultured and treated with tadalafil after TGF β1 stimulation,and the effects of tadalafil on LX-2 cell activation were assessed via Western blot.Results Compared to the normal mice,the model group mice exhibited a significantly higher liver-specific index,increased liver function indicators,and notable hepatocyte necrosis.Additionally,liver lobules were damaged,accompanied by severe infiltra-tion of inflammatory cells.Both smooth muscle actin(α-SMA)and fibronectin(Fn)were elevated,serving as markers of HSCs activation.As a result of treatment with the newly formulated Tadalafil tablets,liver tissue damage was significantly reduced,transaminase levels decreased,necrosis and inflammatory cell infiltration were reduced,and collagen fiber deposition was allevia-ted,and α-SMA and Fn expression was reduced.It was worth noting that low-dose newly formulated Tadalafil tablets were found to be as effective as high-dose Cia-lis.In a cellular model,Tadalafil significantly inhibited the activation of LX-2 cells and reduced the expression of proteins related to cell activation.Conclusions The newly formulated Tadalafil tablets can significantly inhibit HSCs activation,reduce extracellular matrix(ECM)deposition,improve liver fibrosis and liver function damage caused by CCl4.This new formulation offers a significant advantage over Cialis in terms of ef-fectiveness,with a lower effective dose.

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

Objective:To observe the impact of ultra early neurorehabilitation combined with cognitive intervention training on the psychological state,neurological function,and quality of life of stroke patients.Methods:89 stroke patients who were admitted to our hospital from April 2023 to May 2024 were divided into control group(conventional rehabilitation intervention combined with cognitive intervention training,44 cases)and study group(control group combined with ultra early neurological rehabilitation,45 cases)by using random number table method.The neurological function,daily self-care ability,psychological state,quality of life,and satisfaction between two groups were compared.Results:14 d after intervention,the study group had lower scores on the national institutes of health stroke scale(NIHSS),self rating anxiety scale(SAS),and self rating depression Scale(SDS)compared to the control group,had higher scores of the comprehensive quality of life evaluation questionnaire-74(CQOLI-74)and the modified barthel index(MBI)(P＜0.05).The overall satisfaction rate of the study group was higher than that of the control group(P＜0.05).Conclusion:Ultra early neurorehabilitation combined with cognitive intervention training can effectively improve the neurological function and daily self-care ability of stroke patients,reduce anxiety and depression,improve their quality of life,and achieve good patient satisfaction.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

We aimed to explore the value of personalized narrative intervention in the nursing care of elderly patients with stroke hemiplegia(SH).A total of 68 elderly patients with SH were selected and divided into two groups using the ball-rolling method,with 34 cases in each group.The control group received routine nursing care,while the observation group received routine care and personalized narrative nursing.The nursing outcomes of the two groups were compared.Compared with the control group,the observation group had lower scores in anxiety and depression(P<0.05),and higher scores in the Functional Evaluation of Cognitive State-Short Screening(FECS-SS)(P<0.05).The rehabilitation effects of normal rate in the observation group was higher than that in the control group(P<0.05).Personalized narrative nursing for SH patients can effectively relieve the patients'negative emotions,enhance their compliance with rehabilitation,and improve the outcomes of rehabilitation.

Objective:To observe the impact of ultra early neurorehabilitation combined with cognitive intervention training on the psychological state,neurological function,and quality of life of stroke patients.Methods:89 stroke patients who were admitted to our hospital from April 2023 to May 2024 were divided into control group(conventional rehabilitation intervention combined with cognitive intervention training,44 cases)and study group(control group combined with ultra early neurological rehabilitation,45 cases)by using random number table method.The neurological function,daily self-care ability,psychological state,quality of life,and satisfaction between two groups were compared.Results:14 d after intervention,the study group had lower scores on the national institutes of health stroke scale(NIHSS),self rating anxiety scale(SAS),and self rating depression Scale(SDS)compared to the control group,had higher scores of the comprehensive quality of life evaluation questionnaire-74(CQOLI-74)and the modified barthel index(MBI)(P＜0.05).The overall satisfaction rate of the study group was higher than that of the control group(P＜0.05).Conclusion:Ultra early neurorehabilitation combined with cognitive intervention training can effectively improve the neurological function and daily self-care ability of stroke patients,reduce anxiety and depression,improve their quality of life,and achieve good patient satisfaction.

Objective:The current study was designed to elucidate the expression pattern,prognosis value,im-mune characteristics and potential molecular mechanisms of HDGF in HCC.Methods:Clinical and gene expression data of the TCGA-LIHC cohort were collected.The Kaplan-Meier method,time-dependent receiver operating charac-teristic(ROC)curves and Cox regression analysis were used to analyze the prognostic value of HDGF.The expression level difference of HDGF was analyzed using the R package DESeq2.Gene ontology,KEGG and GSEA analyses were used to determine the biological function of HDGF in HCC development.The SsGSEA method were used to analyze the immune infiltrates of HCC.Human methylation 450 data and level 3 HTSeq-FPKM data from TCGA-LIHC were used to analyze the effects of DNA methylation level on HDGF expression.Results:Our results indicated that HDGF was over-expressed in HCC and correlated with historical grade and AFP levels(P<0.001).HDGF expression level is an indepen-dent risk factor for overall survival in patients with HCC(P=0.008).The functional and immune analysis indicated that HDGF is closely related to tumor-immune microenvironment and immune infiltration,especially Cytotoxic cells,pDC and Th2 cells(P<0.001).In addition,high HDGF expression in HCC was associated with demethylation of its promoter region(P<0.05).Conclusion:Our results demonstrated that HDGF independently predicts unfavorable prognosis and regu-lates the immune microenvironment of HCC,suggesting HDGF as a potential immunotherapeutic target for HCC.