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.

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.

Current ambient mass spectrometry ionization often requires external auxiliary equipment such as high-voltage power supply,gas cylinder,and syringe pump.Moreover,the process of sample preparation is cumbersome,and the experimental operations are complex,which makes it difficult to adapt to real-time on-site detection.In this work,a novel method was proposed,in which direct sampling of raw samples,online extraction of interest analytes,and ionization of target molecules were integrated into a single unit.With the developed method,the in-situ extraction and nano-electrospray ionization for both liquid and solid raw samples were achieved.Also,a handheld ion source and its pose adjustment device were developed,and the position and angle parameters were subsequently optimized.The performance of the ionization device was tested using standard solutions of caffeine and reserpine.The limits of detection(LODs)were 0.08 μg/L and 0.14 μg/L,with relative standard deviations(RSDs)≤3.7% and≤5.6%,respectively,indicating that the device possessed high sensitivity and stability.Using this device,three different concentrations of reserpine standard solutions were continuously tested for five days.The intra-day RSDs were consistently≤4.7% and the inter-day RSDs were all≤10.3%,showing the good working stability of the device.Without any pretreatment,a rapid qualitative detection of medicinal components including astragaloside II and cycloastragenol in five traditional Chinese medicines was carried out,with RSDs≤8.0% and≤7.1%,respectively.Additionally,rapid qualitative detection of gallic acid,a medicinal component,in white peony roots,and hypaphorine as well as quercetin in cowherb seeds were carried out,with RSDs≤7.0%,≤6.4% and≤6.1%,respectively.These results demonstrated that the ionization technology and device exhibited good stability during qualitative detection of raw samples.

Near infrared spectroscopy(NIRS)analysis technology has become an important process analysis tool in industrial and agricultural production,and has been widely used for qualitative and quantitative analysis in the fields of tobacco,agriculture,and pharmaceuticals.To address issues such as poor generalization ability and low prediction accuracy in NIRS modeling,a two-dimensional convolutional neural network(2DCNN)quantitative analysis model based on competitive adaptive reweighted sampling(CARS)and Gramian angular difference field(GADF)(CARS-GADF-2DCNN)was proposed.CARS-GADF-2DCNN used the CARS method to select an optimal wavelength set from the full spectrum,then employed GADF to encode the selection results into two-dimensional images,and finally used 2DCNN for prediction analysis.The 2DCNN model consisted of convolutional layers,parallel convolution modules,flattening layer,and fully connected layers.Simulation experiments were conducted on three public near-infrared(NIR)spectral datasets encompassing soil,tablet,and grain datasets to evaluate the CARS-GADF-2DCNN model.The results demonstrated that,compared to the one-dimensional convolutional neural network(1DCNN),the GADF-2DCNN model achieved 16.74％,23.40％,and 7.13％improvement in prediction accuracy for the soil,tablet,and grain datasets,respectively.Compared to GADF-2DCNN,VCPA-GADF-2DCNN,and IRIV-GADF-2DCNN models,the CARS-GADF-2DCNN model further improved prediction accuracy.For the soil dataset,prediction accuracy improved by 39.00％,30.78％and 4.13％;for the tablet dataset,the improvements were 9.52％,6.94％and 2.56％;for the grain dataset,the improvements were 20.57％,9.85％and 15.66％.In conclusion,CARS-GADF-2DCNN effectively selected the optimal wavelength subset from near infrared spectra,and revealed the latent features between different wavelengths.CARS-GADF-2DCNN addresses the issues of high complexity in prediction models and low prediction accuracy in near infrared spectral modeling,and could be effectively applied to near infrared spectral prediction analysis of different substances.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

ObjectiveTo evaluate the levels of physical exercise, mental health and social response in children with autism spectrum disorder (ASD), and explore the mediating effect of social response on physical exercise and mental health. MethodsFrom September, 2019 to April, 2024, 211 children with ASD from three special education schools in Haidian District and Shijingshan District of Beijing were selected. They were assessed with general data questionnaire, Physical Activity Rating Scale (PARS-3), Chinese version of Psycho-Educational Profile (C-PEP) and Social Response Scale-Short Form (SRS-SF). The correlation among physical exercise, mental health and social response was analyzed. The mediating effect of social response on physical exercise and mental health was explored. ResultsThe average physical exercise level was (58.72±3.34), the average mental health level was (14.85±1.67), and the average social response level was (24.98±3.79). Physical exercise was positively correlated with mental health (r = 0.546, P < 0.05) and negatively correlated with social response (r = -0.298, P < 0.05). Mental health was negatively correlated with social response (r = -0.397, P < 0.05). Average monthly family income, parental relationship, repeated transcranial magnetic stimulation therapy, physical exercise, social response were the influencing factors of mental health (P < 0.05). Social response was intermediary between physical exercise and mental health, accounting for 14.56%. ConclusionThe mental health level of children with ASD is poor, and there are many influencing factors. Physical exercise can directly affect the mental health of children with ASD, and can also play an indirect role through social response.

AIM: To investigate the impact of corneal fluorescein sodium(NaF)staining on the examination results of iTrace visual function analyzer(iTrace).METHODS: Prospective cohort study. Totally 100 patients(100 eyes)with ametropia who visited the outpatient department of Anhui Eye Hospital from April to November 2024 were recruited. They were divided into an experimental group and a control group, with 50 patients(50 eyes, and only the right eyes were selected for inclusion)in each group. In the experimental group, corneal staining was performed using fluorescein sodium staining test strips, while in the control group, 1 drop of 0.9% normal saline was instilled into the eyes. The iTrace examination was conducted before the intervention and at 5, 10, and 20 min after the intervention. The total corneal higher-order aberrations, spherical aberration, coma aberration, trefoil aberration, best sphere value(RO value), asphericity factor(Q value), and corneal vertical refractive power difference(IS value)at each time of examination were recorded and compared.RESULTS: There was no statistically significant difference in the baseline levels between the two groups(all P>0.05). Intra-group comparison revealed that the total higher-order aberrations, spherical aberration, coma aberration, and trefoil aberration measured 5 min after NaF staining in the experimental group were significantly increased compared with those before staining(all P<0.05). Inter-group comparison showed that the changes(differences from the baseline)in the total corneal higher-order aberrations, spherical aberration, coma aberration, and trefoil aberration measured by iTrace 5 min after the intervention in the experimental group were significantly greater than those in the control group(all P<0.05). There was no statistically significant difference in the changes(differences from the baseline)of various iTrace parameters measured at 10 and 20 min after the intervention between the two groups(all P>0.05). There was no statistical significance in the RO value, Q value, and IS value in the two groups(all P>0.05).CONCLUSION: Corneal NaF staining can cause a short-term increase in the wavefront aberration values(total corneal higher-order aberrations, spherical aberration, coma aberration, trefoil aberration)measured by iTrace, and it gradually disappears with the passage of time. However, it has no impact on the measurement of corneal topography parameters(RO value, Q value, IS value).

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*