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.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

OBJECTIVE To analyze the incidence of cyclosporine （CsA）-associated acute kidney injury （AKI） in hospitalized patients， identify influencing factors， and construct a risk prediction model. METHODS A single-center retrospective study was conducted， enrolling clinical data from hospitalized patients treated with CsA at the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital from January 2018 to July 2024. The patients were classified into AKI group and non-AKI group based on the occurrence of CsA-related AKI. Univariate analysis and multivariate Logistic regression analysis were used to identify independent risk factors for CsA-related AKI， and a risk prediction model was constructed and its performance was evaluated. RESULTS A total of 439 patients were included， of whom 54 developed CsA-related AKI， with an incidence rate of 12.30%. The occurrence of CsA-associated AKI was positively correlated with concurrent bacterial pulmonary infection， cytomegalovirus viremia， respiratory failure， renal insufficiency， gastrointestinal bleeding， and peripheral central venous catheterization （odds ratios of 763.750， 16.944， 41.933， 236.806， 17.537 and 212.789， respectively； P ＜0.05）； while uric acid， prealbumin， and calcium levels were negatively associated with it （odds ratios of 0.983， 0.967 and 0.058， respectively； P ＜0.05）. The prediction model constructed based on the above factors yielded a χ 2 value of 10.254 （ P ＞0.05） in the Hosmer-Lemeshow test. The average area under the curve （AUC） from 10-fold cross-validation was 0.885. The AUC of the receiver operating characteristic curve was 0.883， with a sensitivity of 84.3% and a specificity of 80.4%， respectively， at the optimal cutoff value of 0.1. CONCLUSIONS Six factors， including concurrent bacterial pulmonary infection and cytomegalovirus viremia， are positively associated with the occurrence of CsA-related AKI； while uric acid， prealbumin， and calcium levels are negatively associated. The Logistic regression model constructed based on these factors demonstrates good predictive performance and can assist clinic in conducting early risk assessment and personalized interventions.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a steadily rising global prevalence, yet effective pharmacological interventions remain notably limited, highlighting an urgent need for safe, accessible, and mechanism-based therapeutic strategies. Physical exercise has emerged as a promising non-pharmacological intervention that ameliorates both core symptoms—social communication deficits and restricted repetitive behaviors—and associated features including cognitive dysfunction and motor impairments, in children and adolescents with ASD. However, the molecular mechanisms mediating these beneficial effects remain incompletely defined, impeding the development of evidence-based exercise prescriptions and biomarker-driven rehabilitation protocols. MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that post-transcriptionally regulate approximately 60% of protein-coding genes. Within the central nervous system, miRNAs orchestrate diverse neurobiological processes including neural progenitor proliferation, neuronal differentiation, dendritic spine morphogenesis, synaptic plasticity, and neuroinflammatory homeostasis. Notably, miRNAs are remarkably stable in biological fluids and can be packaged into extracellular vesicles, rendering them attractive candidates as both mechanistic mediators and non-invasive peripheral biomarkers. Among the hundreds of miRNAs expressed in the brain, three—miR-132, miR-34a, and miR-146a—have emerged as particularly relevant to ASD pathophysiology. This review focuses on these three miRNAs for the following reasons: miR-132 is a master regulator of activity-dependent synaptic plasticity through its modulation of BDNF/MeCP2/PTEN signaling and has been consistently downregulated in ASD prefrontal cortex; miR-34a functions as a pro-apoptotic factor that suppresses Bcl-2-mediated neuronal survival pathways and is upregulated in ASD cerebellum; and miR-146a serves as a key brake on neuroinflammation via TLR7/IRAK1 signaling and shows region-specific dysregulation in ASD temporal lobe. We first summarize evidence from human post-mortem brain tissues and ASD animal models demonstrating the consistent dysregulation of these three miRNAs. Notably, the pathological consequences of these miRNA alterations—impaired synaptic plasticity, excessive neuronal apoptosis, and sustained neuroinflammation—are interconnected and collectively contribute to the heterogeneous symptomatology of ASD. We then present a synthesis of emerging evidence demonstrating that various exercise modalities, including swimming, treadmill running, and voluntary wheel running, can concurrently reverse these ASD-like behavioral phenotypes and normalize the expression of the three key miRNAs. These data provide the first direct experimental evidence linking exercise-induced miRNA modulation to ASD symptom improvement. On the basis of these findings, we propose an integrative “exercise-miRNA-ASD” framework wherein exercise functions as a multi-targeted modulator—simultaneously enhancing synaptic plasticity, promoting neuronal survival, and attenuating neuroinflammation—through coordinated regulation of the three miRNAs. Importantly, this framework is not merely descriptive but offers testable predictions: exercise-induced miRNA changes should be dose-dependent, show temporal correlation with behavioral improvements, and be blunted by miRNA-specific antagonists or CRISPR/Cas9-mediated knockout. Beyond its specific application to ASD, this framework has broader implications. The miR-132/BDNF, miR-34a/Bcl-2, and miR-146a/TLR7 pathways are not ASD-specific but represent fundamental neural stress and repair mechanisms that are dysregulated across Alzheimer’s disease (AD), traumatic brain injury, Parkinson’s disease (PD), and major depressive disorder. Exercise has been shown to modulate these same miRNAs in several of these conditions, suggesting that the “exercise-miRNA-neural function” axis may represent a conserved neuroprotective mechanism that transcends diagnostic boundaries. Thus, we propose that ASD serves as an ideal model disease for elucidating this universal mechanism, with findings potentially generalizable to other neurological disorders. We also critically evaluate current translational barriers: the near-absence of human clinical trials with serial miRNA profiling; the undefined dose-response relationships between exercise parameters and miRNA expression; the unresolved causality issue (current evidence demonstrates association, not causation); and the uncertain correlation between peripheral exosomal miRNA levels and brain miRNA dynamics. We argue that future research must prioritize CRISPR/Cas9-based miRNA manipulation in animal models combined with longitudinal exercise interventions to establish causality, and that cross-disease validation studies are essential to determine whether exercise-induced miRNA changes represent a shared neuroprotective signature or disease-specific responses. Ultimately, we envision a paradigm where a simple blood test measuring exosomal miR-132, miR-34a, and miR-146a levels could guide personalized exercise prescriptions, enabling precision rehabilitation for individuals with ASD and potentially other neurological conditions.

ObjectiveThis study aimed to provide a scientific basis for the safety management of drinking water by assessing the contamination levels of 21 per- and polyfluoroalkyl substances (PFASs) in water samples collected from the Yangtze River Delta region. MethodsSolid-phase extraction coupled with ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was employed to determine 21 PFASs in 6 source water samples, 20 treated water samples, and 60 tap water samples collected from 5 administrative districts in the Yangtze River Delta region across four seasons in 2023. The Kruskal-Wallis H test was used to compare differences in PFAS concentrations among the three types of water samples, followed by post hoc pairwise comparisons with Bonferroni correction. Removal efficiencies of target compounds were also calculated. ResultsAmong the 86 samples, 14 PFASs were detected, with 7 compounds detected in 100% of samples. The total concentrations of PFASs in source water, treated water, and tap water ranged from 63.85 to 190.54 ng·L^-¹, 55.75 to 774.36 ng·L^-¹, and 40.72 to 689.80 ng·L^-¹, respectively. The compounds with the highest median concentrations were perfluorobutanoic acid (PFBA) (40.19, 15.20, and 14.05 ng·L^-¹), perfluorohexanoic acid (PFHxA) (29.69, 32.62, and 34.24 ng·L^-¹), perfluorooctanoic acid (PFOA) (17.65, 39.45, and 36.83 ng·L^-¹), and potassium perfluorobutanesulfonic acid (PFBS) (16.99, 24.38, and 23.89 ng·L^-¹). Notably, concentrations of PFOA (7.71‒71.63 ng·L^-¹) and PFOS (-¹) in tap water were below the regulatory limits specified in GB 5749‒2022 Standards for Drinking Water Quality (PFOA: 0.000 08 mg·L^-1, PFOS: 0.000 04 mg·L^-1). Significant seasonal variations in PFAS concentrations were observed, with total PFAS levels in March being higher than those in September and November (adjusted P<0.001, and P=0.006), and levels in May being higher than those in September (adjusted P=0.037). The removal efficiencies of PFASs in the water treatment plants ranged from -14% to 34%. ConclusionPFAS contamination is widespread in source water, treated water, and tap water in the Yangtze River Delta region, and concentrations of PFOA and PFOS in all tested water samples comply with the Chinese national standards for drinking water quality (GB 5749‒2022). The use of PFASs should be continuously regulated to ensure water safety.

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.

Cervical cancer(CC),a common malignant tumor afflicting women,poses serious threats to their health.Therefore,it is critical to develop a thorough understanding of the molecular mechanisms underlying the pathogenesis of CC,and to identify new therapeutic targets and methods for early diagnosis.The multi-omics research in tumors,involving proteomics,transcriptomics,genomics,microbiomics,and metabolomic,offers valuable insights.The multi-omics analysis of biological samples from patients with cervical intraepithelial neoplasia(CIN)and CC can help clarify the pathways involved in the pathogenesis and development of CC.Furthermore,multi-omics studies have identified a number of molecules associated with CC,including actin,lumican,family member with sequence similarity 83(FAM83A),cadherin EGF-LAG seven-pass G-type receptor 3(CELSR3),and 5,10-methylenetetrahydrofolate reductase(MTHFR),all of which show potential to be used as new biomarkers.These biomarkers will help make early diagnosis,improve the survival and prognosis of CC patients,and ultimately reduce CC incidence and mortality.This review synthesizes current advances in multi-omics research on cervical cancer.

OBJECTIVE: To explore the effect mechanism of electroacupuncture (EA) for ameliorating diabetic peripheral neuropathy (DPN) based on the analysis of gut microbiota and metabolomics. METHODS: Thirty SPF-grade male SD rats were randomly divided into a normal group, a model group, and an EA group, with 10 rats in each one. Except in the normal group, the intraperitoneally injection with streptozotocin was used to induce diabetes mellitus model in the rest groups. In the EA group, acupuncture was delivered at bilateral "Zusanli" (ST36), "Sanyinjiao" (SP6), "Pishu" (BL20) and "Shenshu" (BL23), and electric stimulation was attached to "Zusanli" (ST36)-"Sanyinjiao" (SP6) and "Pishu" (BL20)-"Shenshu" (BL23), on the same side, with continuous wave and a frequency of 2 Hz, for 10 min in each intervention. The intervention measure of each group was delivered once every 2 days, 3 times a week, for 8 consecutive weeks. Body weight, random blood glucose (RBG), thermal withdrawal latency (TWL), and mechanical withdrawal threshold (MWT) before intervention, and in 4 and 8 weeks of intervention, separately, as well as sensory nerve conduction velocity (SCV) and motor nerve conduction velocity (MCV) of the sciatic nerve after intervention were measured. Metagenomic sequencing (MS) was used to analyze gut microbiota and screen for differential species. Liquid chromatography-mass spectrometry (LC-MS) was employed to detect the differential metabolites in plasma, and the metabolic pathway enrichment analysis was performed on the differential metabolites. Spearman correlation analysis was adopted to assess the relationship between gut microbiota and metabolomics. RESULTS: After 4 and 8 weeks of intervention, when compared with the model group, the EA group showed the increase in body weight, TWL, MWT (P<0.01), and the decrease in RBG (P<0.01). Compared with the normal group, SCV and MCV, as well as Chao1 index were dropped in the model group (P<0.01), and those were elevated in the EA group when compared with those in the model group (P<0.01). The dominant bacterial phyla of each group were Firmicutes (F) and Bacteroidota (B), the ratio of them (F/B) in the model group was lower than that of the normal group (P<0.05), and F/B in the EA group was higher when compared with that in the model group (P<0.05). In comparison with the normal group, the relative abundance increased in Prevotella, Segatella, Prevotella-hominis and Segatella-copri (P<0.05); and it decreased in Ligilactobacillus, Eubacterium, Pseudoflavonifractor, Ligilactobacillus-murinus (P<0.05) in the model group. Compared with the model group, the relevant abundance of the above mentioned gut bacteria was all ameliorated in the EA group (P<0.05, P<0.01). Among the three groups, 120 differential metabolites were identified and enriched in 28 key metabolic pathways, such as glycerophospholipid and linoleic acid, of which, glycerophospholipid was the most significantly affected pathway in EA intervention. Spearman correlation analysis showed that 6 phosphatidylcholine metabolites were significantly positively correlated with Pseudoflavonifractor and were negatively with Prevotella, Segatella, Prevotella-hominis, Segatella-copri; 5 phosphatidylethanolamine metabolites were significantly negatively correlated with Pseudoflavonifractor and positively correlated with Prevotella, Segatella, Prevotella-hominis, Segatella-copri. CONCLUSION EA may regulate metabolic pathways such as glycerophospholipid, modulate specific gut microbiota such as Pseudoflavonifractor, Prevotella, and Segatella, and the co-expressed differential metabolites like phosphatidylcholine and phosphatidylethanolamine, thereby reducing blood glucose and protecting nerve function, so as to relieve the symptoms of DPN of rats.
Animals ; Electroacupuncture ; Male ; Gastrointestinal Microbiome ; Diabetic Neuropathies/microbiology* ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Humans ; Acupuncture Points