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.

Background: Surgeons face challenges in selecting cost-effective and biologically active agents for rotator cuff healing, given the numerous commercial products available, such as polydeoxyribonucleotide (PDRN) and atelocollagen (ATC). However, the precise efficacy of PDRN and ATC in rotator cuff healing remains debatable, and there is currently a lack of studies directly comparing the effects of the 2 agents on repaired cuff tendons. Therefore, the purpose of this study was to compare the efficacy of PDRN and ATC on bone-to-tendon interface (BTI) healing using a chronic rotator cuff tear (RCT) model in rabbits. Methods: Forty-eight rabbits were randomly divided into 3 groups. To create chronic RCT models, transected tendons were left untreated for 6 weeks, and then were repaired in a transosseous manner with PDRN and ATC injection into the repair site according to group allocation (group A: saline, group B: PDRN, group C: ATC; n = 16 per group). Genetic and immunofluorescence analyses were performed at 4 weeks after surgery. Furthermore, genetic, histologic, and biomechanical analyses were performed at 12 weeks after surgery. Results: At 4 weeks after surgery, ATC-injected shoulders showed the highest mRNA expression levels of collagen type I alpha 1 and aggrecan compared to the other 2 groups (p < 0.001 and p = 0.002, respectively). Meanwhile, there was more preliminary fibrocartilaginous matrix formation in the ATC-injected group. At 12 weeks after surgery, ATC-injected shoulders demonstrated better collagen fiber continuity and orientation, denser collagen fibers, a more mature bone-to-tendon junction, and greater fibrocartilage layer formation compared to the other 2 groups (all p < 0.001). Furthermore, ATC-injected shoulders also demonstrated a significantly higher load-to-failure value (40.4 ± 4.5 N/kg) than the remaining groups (group A, 26.7 ± 3.0 N/kg; group B, 32.8 ± 4.2 N/kg; p < 0.001). Conclusions ATC demonstrated superior efficacy in promoting BTI healing following surgical repair in a chronic RCT model of rabbits.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

Background Diarrhea disease is a common intestinal infectious disease, and its incidence is affected by meteorological conditions. A better understanding of its epidemiological patterns and influencing factors, together with the construction of reliable prediction models, is of great significance for precise public health prevention and control. Objective To clarify the epidemic characteristics of adult diarrhea disease in Shanghai, analyze the associations of meteorological factors and a web search index with adult diarrhea disease, and develop and compare forecasting models to support precise regional prevention and control. Methods Weekly surveillance data of adult diarrhea disease cases from the Shanghai Comprehensive Surveillance Information System for Diarrhea Diseases, together with concurrent meteorological observation data and web search index (Baidu index) data from 2014 to 2019, were collected. A distributed lag non-linear model (DLNM) was adopted to analyze the associations of multiple meteorological factors and the web search index with the number of diarrhea disease cases. By integrating meteorological factors and web search index data, three types of forecasting models were developed, including autoregressive integrated moving average (ARIMA), Random Forest, and extreme gradient boosting (Xgboost), and their predictive performances were evaluated. Results Adult diarrhea disease in Shanghai exhibited seasonal variation, with an major incidence peak in summer and winter peaks in some years. The number of cases declined annually after 2015. Mean temperature was significantly associated with the risk of diarrhea disease, and both low and high temperature exposures were associated with increased risks. The highest risk was observed at 32.8°C (RR=2.04, 95%CI: 1.62, 2.55), while the strongest effect of low temperature was observed at 0.9 °C (RR=1.53, 95%CI: 1.25, 1.88). When relative humidity exceeded 69%, the risk of diarrhea disease increased with relative humidity, reaching a peak at 81% (RR=1.20, 95%CI: 1.07, 1.35). When weekly cumulative precipitation exceeded 16 mm, the risk also increased with increasing precipitation, reaching a maximum at 105 mm (RR=1.23, 95%CI: 1.07, 1.42). The web search index was positively associated with the risk of diarrhea disease. Model prediction indicated that both the Random Forest model and the Xgboost model adequately captured the overall trend in diarrhea disease cases, with R² values generally exceeding 0.7. Notably, the Xgboost model demonstrated greater accuracy in capturing peak intensities. Conclusion Meteorological factors are associated with adult diarrhea disease in Shanghai. The web search index may serve as an auxiliary indicator for diarrhea forecasting. Machine learning models, with advantages in integrating multisource data, may provide effective predictive tools for the prevention and control of diarrhea disease.

This study was aimed at determining the molecular characteristics of Yersinia pestis in the natural plague foci around Qinghai Lake through single nucleotide polymorphism technology,to lay a foundation for molecular epidemiological and source-tracing analysis of Y.pestis in this area.Using the whole genome sequencing technology,we obtained the whole genome sequences of 84 representative Y.pestis strains.Using the sequences of Y.pestis and Yersinia pseudotuberculosis IP32953 from the NCBI database as references,we compared and analyzed the 2 298 SNP loci of these strains.From 1957 to 2020,84 representative strains of Y.pestis from the natural plague foci around Qinghai Lake were divided into two clades:1.IN2 and 3.ANT1.The 1.IN2 clade was the characteristic population of Y.pestis throughout all epidemic years in this area.Additionally,analysis of the SNP distribution and hosts in the region indicated that the 1.IN2 clade was located in five counties except Wulan,whereas the 3.ANT1 clade was isolated from Himalayan marmot and dog in two counties.In conclusion,the population structure of SNP of Y.pestis in the natural plague foci around Qinghai Lake is relatively simple,and SNP analysis of Y.pestis provided a scientific basis for tracing plague epidemic sources and formulating plague prevention and control measures in this area.

CRM 197(cross-reacting material 197),a naturally occurring mutant of diphtheria toxin,is a safe and effective vaccine vector and extensively used on developing conjugate or combined vaccines.The mutant loses its enzymatic activity,but fully retains its receptor-binding ability and immunogenicity.In current work,the diphtheria toxin mutant CRM 197 and its fusion proteins with the receptor-binding do-main of botulinum neurotoxin serotype E(EHc)were developed using genetic engineering technology.These recombinant proteins were confirmed by Western blotting and SDS-PAGE.BALB/c mice were im-munized with the CRM197-EHc and EHc-CRM197 fusion proteins,and their immunogenicity was evalua-ted.These two fusion protein molecules,CRM197-EHc and EHc-CRM197,as subunit vaccines,elicited a robust humoral immune response targeting both CRM197 and EHc antigens in the immunized mice.Compared to the mixture of CRM197 and EHc,the mice vaccinated with the fusion proteins(CRM197-EHc and EHc-CRM197)induced higher levels of anti-CRM197 antibodies,and the mice vaccinated with EHc-CRM197 also generated strongest anti-EHc antibodies.Consequently,as a carrier molecule in the fusion protein vaccine,EHc enhances the immunogenicity of CRM197 molecules.Likewise,CRM197 boosts the immunogenicity of EHc in the EHc-CRM197 fusion protein.

Objective:To compare the efficacy of body posture combined with pharmacotherapy and pharmacotherapy alone in the treatment of chronic subdural hematoma(CSDH).Methods:Firstly, retrospective case series study was conducted. Thirty cases of CSDH that had received body posture combined with pharmacotherapy at Department of Neurosurgery, Huashan Hospital Affiliated to Fudan University from December 2016 to October 2020 were studied retrospectively. Twenty-seven patients were male, and 3 patients were female. The age of patients ( M(IQR)) was 66(16) years (range:28 to 84). Nineteen patients had unilateral hematoma, and 11 patients had bilateral hematoma. All patients received pharmacotherapy and body posture therapy that was to raise their lower limbs 20 to 30 cm with leg lift pad and get abdominal compressed with customized abdominal belt in supine position. Patients were required to maintain the body posture as much as possible, with the maximum to 16 to 18 hours per day. Patients with unilateral hematoma should tilt the head to the affected side and avoid tilting it to the opposite side. For patients with bilateral hematoma, there was no need for head lateralization. Patient were treated with oral dexamethasone and atorvastatin simultaneously. The preliminary efficacy of body posture combined with pharmacotherapy was determined by hematoma improvement rate which was analyzed by Clopper-Pearson method. Then, the multi-center, prospective, randomized controlled trial had carried out in 9 medical centers from August 2020 to November 2021. The stratified block randomization method was adopted. Patients were randomized in a ratio of 1∶1 to either receive pharmacotherapy alone(the control group) or body posture combined with pharmacotherapy(the experiment group) for 3 months and followed up for 6 months. Effective treatment was defined as complete absorption of hematoma, or the hematoma volume decreased by more than 10 ml and Markwalder grading scale score had improved by more than 1 point compared to the baseline. The efficacy rate and surgery conversion rate at 3 months and recurrence at 6 months were observed. Comparison between groups was performed with paired sample t test, Mann-Whitney U test, χ2 test, corrected χ2 test, or Fisher exact probability method. Logistic regression was used to compare the effective rate and operation rate between the two groups. Results:In the respective study, 30 patients completed follow-up 13 to 353 days after treatment. At the last follow-up, the incidence of almost complete absorption or significantly absorption of hematoma (hematoma volume was significantly reduced accompanied by symptom improvement) was 93.3%. The 95% CI for the incidence that analyzed by the Clopper-Pearson method was 77.9% to 99.2%. One hundred and six patients were enrolled in the multicenter study. Fifty-five patients underwent body posture combined with pharmacotherapy. The age was 74(17) years (range:26 to 92). Thirty-nine patients were males and 16 were females. Fifty-one patients underwent pharmacotherapy alone. The age was 69(12) years (range:48 to 84). Thirty-seven patients were males and 14 were females. The length of body posture recorded in diary card was (15.7±2.3) hours(range:7.6 to 19.3 hours). The efficacy rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 83.6% (46/55) and 56.9% (29/51), respectively at 3 months. The result of the logistic regression analysis showed that the efficacy of body posture combined with pharmacotherapy group was better than that of pharmacotherapy alone group ( OR=3.88,95% CI:1.57 to 9.58, P=0.003). Surgery rate in the body posture combined with pharmacotherapy group and pharmacotherapy alone group were 5.5% (3/55) and 21.6% (11/51) respectively. The result of Logistic regression showed that the pharmacotherapy alone group was more likely to be converted to surgery ( OR=0.21,95% CI:0.05 to 0.80, P=0.023). At the 6 months, no recurrence of cases was found in the body posture combined with pharmacotherapy group. However, the recurrence rate of pharmacotherapy alone group was 6.3% (3/48), there was no significant difference between the two groups ( P>0.05). Conclusion:The effect of body posture combined with pharmacotherapy for chronic subdural hematoma is better than that of pharmacotherapy alone.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

The epidemiological and spatiotemporal clustering characteristics of dengue fever in Fujian Province were ana-lyzed,to provide a scientific basis for dengue fever prevention and control.Descriptive epidemiology,spatial autocorrelation a-nalysis,and spatiotemporal scanning were used to analyze dengue fever cases in Fujian Province from 2011 to 2023.In this peri-od,a total of 3 586 cases of dengue fever were reported in Fujian Province,including 2 360 local cases,1 134 imported cases from abroad,and 92 imported cases from China.Cases were reported in ten prefectures and cities of the province,and 81 out of 88 counties reported cases.Imported cases were reported throughout the year in Fujian Province,but the occurrence of local ca-ses showed clear seasonality.Local cases and domestic imports were concentrated in August to October,whereas overseas im-ports occurred primarily from June to October.The imported cases were mainly from Southeast Asian countries,but a trend of spreading from Southeast Asian countries to South Asia,Africa,the Americas,and other regions,was observed.Spatio-tem-poral clustering of dengue fever was found in Fujian Province(Moran's I value 0.14-0.66,P＜0.05),and the high-high ag-gregation areas were distributed primarily in Fuzhou,Quanzhou,and Putian.Spatio-temporal scanning detected three aggrega-tion areas:one main and two secondary.The aggregation time was from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.The distribution of dengue fever in Fujian Province showed clear spatial and temporal clustering from the end of July to October,and the distribution was primarily in Fuzhou,Quanzhou,Putian,Zhangzhou,and Xiamen.For high concentration areas,national health campaigns,mosquito prevention and control,epidemic surveillance,medical personnel training,and other relevant measures could be carried out in advance before local cases appear every year.Reduce local transmission of dengue fever due to importation.