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.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

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.

Aim To investigate the effects of m6A demethylase ALKBH5 on cardiomyocytes pyroptosis in mice with myocardial infarction(MI).Methods The MI model of left anterior descending coronary artery ligation surgery was established by knocking down ALKBH5 using adeno-associated virus,and the hypox-ia model of mouse cardiomyocytes(HL-1)was estab-lished by knocking down small interfering RNA.The effects of ALKBH5 on the pyroptosis of MI mice and hypoxic HL-1 cells were observed.Subsequently,mechanism studies were conducted at the cellular lev-el,and the binding of ALKBH5 and IGF2BP2 to NL-RP3 mRNA was detected through RNA pull down and RNA immunoprecipitation(RIP)experiments.The MeRIP-qPCR method was used to determine the effects of ALKBH5 on the mRNA m6A level of NLRP3.Acti-nomycin D for RNA stability experiments were conduc-ted to detect the effects of ALKBH5 and IGF2BP2 on the stability of NLRP3 mRNA.Results Knocking down ALKBH5 in vivo and in vitro both inhibited NL-RP3 inflammasome activation and alleviated pyroptosis in MI mice and hypoxic HL-1 cells.Mechanistically,the results showed that NLRP3 mRNA could bind to ALKBH5 protein in HL-1 cells;knocking down ALK-BH5 could increase the m6A level of NLRP3 and re-duce the stability of NLRP3 mRNA;subsequently,it was confirmed that NLRP3 mRNA and IGF2BP2 pro-tein bound to each other;knocking down IGF2BP2 in-creased the mRNA stability of NLRP3.The Rescue ex-periment showed that knocking down IGF2BP2 re-versed the decrease in NLRP3 mRNA expression caused by knocking down ALKBH5.Conclusions ALKBH5 mediated m6A modification of NLRP3 pro-motes cardiomyocytes pyroptosis in mice with myocardi-al infarction.