Objective To analyze the influenza-like illness (ILI) data in Ordos City from 2017 to 2023 and conduct nucleic acid detection of the virus to understand the local influenza epidemic situation, and to provide a reliable basis for influenza prevention and control in the city. Methods Real-time quantitative polymerase chain reaction (qPCR) was used to identify virus subtypes in ILI throat swab samples. Comparisons of positive rates were conducted using the chi-square test, with a significance level of α=0.05. Results From 2017 to 2023, a total of 3,283,434 outpatient and emergency visits were recorded at the Ordos City Central Hospital, including 74,159 ILI cases, with an ILI proportion of 2.26%. The majority of ILI cases (74.43%) occurred in children aged 0~14 years old. The overall positive rate of influenza virus nucleic acid detection was 10.87%, with the highest proportion being subtype A (seasonal H3) at 43.03%. The highest detection rate was observed in the 5~14 years age group, with statistically significant differences in positive rates across age groups (χ²=155.638, P<0.001). Influenza peaks occurred mainly from November to March of the following year. From January to April, three types of influenza were prevalent alternately or mixed, while from October to December, subtype A (seasonal H3) predominated. Positive rates varied significantly across months (χ²=250.923, P<0.001). The temporal trends of ILI proportions and PCR-positive rates were consistent. Conclusion Influenza in Ordos City exhibits distinct seasonal and age distribution characteristics, with alternating or mixed circulation of three virus types. Continued efforts are needed to strengthen influenza surveillance, especially the prevention and control of influenza in infants and adolescents.

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.

ObjectiveTo investigate the metabolic alterations of serum short chain fatty acids （SCFAs） in pediatric patients with atopic dermatitis （AD） and their correlation with different clinical phenotypes using targeted metabolomics. MethodsThis study enrolled 87 AD patients and 67 healthy controls （HC）. Serum levels of eight SCFAs were quantified by ultra-high-performance liquid chromatography-mass spectrometry. The associations between SCFAs and AD were assessed using various statistical methods. ResultsCompared with the HC group， levels of acetic acid （AA）， propionic acid （PA）， and caproic acid （CA） （P=0.002，P=0.002，P=0.043） decreased in the AD group. Logistic regression analysis identified AA （OR=0.449， 95% CI： 0.289–0.698） and PA （OR = 0.487， 95% CI： 0.324–0.732） as protective factors against AD. The combination of AA and PA yielded an area under the curve （AUC） greater than 0.7， indicating good diagnostic efficacy. Age-stratified analysis revealed that AA reduction was predominant in childhood， whereas PA reduction was predominant in adolescence. Pathway enrichment analysis showed significant enrichment of fatty acid biosynthesis （FDR=0.341， P=0.003） and vitamin K metabolism （FDR=1， P=0.039） pathways. Furthermore， subgroup analyses based on disease severity， personal/family history of atopy， and sex revealed no significant differences in SCFAs levels among the groups. ConclusionDifferential serum SCFAs and their enriched metabolic pathways may be implicated in the pathogenesis of AD.

Prolonged standing work can lead to various lower limb health issues. Footwear, as a convenient and noninvasive intervention, plays a key role in foot protection. The purpose of this review was to evaluate the impact of footwear characteristics on foot comfort among workers engaged in prolonged standing occupations. A systematic search of PubMed, Web of Science, Scopus, and the Cochrane Library was conducted until March 2025 for experimental and observational studies; the review is registered in International Prospective Register of Systematic Reviews (CRD420251003253).Given the diversity of study designs, participant characteristics, and outcome measures, results were synthesized narratively, organizing findings by footwear design factors. The synthesis indicated that soft soles reduce foot impact and fatigue but offer limited support, whereas hard soles enhance stability but may cause localized pressure and discomfort. Sole hardness should balance cushioning and support based on activity: hard soles for standing and soft soles for walking. Insole hardness must be carefully considered as semirigid arch supports can cause discomfort. Most insoles improve pressure distribution by adjusting arch loading, and some enhance intrinsic foot muscles by promoting toe engagement, reducing leg swelling. Custom orthotic insoles outperform standard ones in comfort and balance. Future research should promote interdisciplinary collaboration with footwear designers to explore key design parameters and establish a scientific framework for protective footwear.

Objective To investigate the epidemiological characteristics of malaria and provide a basis for developing improved prevention and control measures. Methods Data were obtained from the Chinese Disease Prevention and Control Information System. Malaria surveillance data for Nanning City from January 1,2023, to December 31,2024, were exported from the Infectious Disease Reporting Information Management Subsystem. The characteristics of the two groups of malaria cases were compared. Results A total of 103 imported malaria cases were reported in Nanning City in 2024, representing a 38.32% decrease compared with the same period of the previous year. No statistically significant difference were observed between cases reported in 2023 and 2024 in terms of average age, gender ratio, proportion of parasite species, and monthly reporting distribution;however, statistically significant differences were found in the proportion of reporting areas and current residence areas(χ2= 13.572 and 10.355, respectively; P = 0.001 and 0.035, respectively). The proportion of cases reported in Shanglin County and the proportion of cases residing in Shanglin County were both lower than those during the same period of the previous year. Conclusions The high aggregation of imported malaria cases in Nanning City has decreased. Medical institutions in areas other than Shanglin County should strengthen their vigilance against malaria.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

OBJECTIVE: To investigate the effect of human adipose-derived mesenchymal stem cells (hASCs) exosomes on osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) extracted from osteoporotic mice, and to evaluate the effect of hASCs exosomes on preventing bone loss induced by estrogen deficiency. METHODS: hASCs exosomes were extracted by ultracentrifugation. The osteoporotic mice were established by bilateral ovariectomy (OVX). BMSCs were isolated from osteo-porotic mice and cultured for further analysis. In the experimental group, these BMSCs were exposed to an osteogenic induction medium supplemented with hASCs exosomes to evaluate their potential effects on osteogenesis. In contrast, the control group was treated with the same osteogenic induction medium, but without the addition of hASCs exosomes, to serve as a baseline comparison for the study. To comprehensively assess the osteogenic differentiation of BMSCs influenced by hASCs exosomes, alkaline phosphatase (ALP) staining, ALP activity quantitative analysis and quantitative reverse transcription polymerase chain reaction (qPCR) were performed. These evaluations provided critical insights into the role of hASCs exosomes in promoting osteoblast differentiation and bone formation in osteoporotic conditions. The fluorescence labeled hASCs exosomes were injected via the tail vein to observe the biodistribution of exosomes. Two weeks after OVX, the mice were divided into three groups: The experimental group consisted of estrogen-deficient mice receiving hASCs exosome injections; the negative control group consisted of estrogen-deficient mice receiving phosphate-buffered saline (PBS) injections; and the positive control group consisted of mice that underwent Sham surgery and received PBS injections.The injections were administered once every 3 days, for a total of 8 injections. Afterward, the femurs were collected from the mice, and micro-computed tomography (micro-CT) was performed to measure bone mineral density and conduct bone morphometric analysis. RESULTS: hASCs exosomes were successfully extracted using ultracentrifugation. After the induction by hASCs exosomes, ALP staining and ALP activity in the BMSCs extracted from osteoporotic mice were significantly enhanced, the expression of osteogenesis related genes in BMSCs were significantly up-regulated. More trabecular bone and higher bone mineral density were observed in estrogen-deficient mice injected with hASCs exosomes compared with estrogen-deficient mice injected with PBS, and there was no significant decrease in bone mineral density compared with the Sham operation group. CONCLUSION hASCs exosomes promoted the osteogenic differentiation of BMSCs extracted from osteoporotic mice. hASCs exosomes prevented bone loss induced by estrogen deficiency.
Animals ; Mesenchymal Stem Cells/cytology* ; Exosomes ; Estrogens/deficiency* ; Humans ; Osteogenesis ; Cell Differentiation ; Female ; Mice ; Osteoporosis/prevention & control* ; Ovariectomy ; Adipose Tissue/cytology* ; Cells, Cultured

BACKGROUND: Early control of low-density lipoprotein cholesterol (LDL-C) is crucial for reducing the progress of cardiovascular disease. However, its additional role to the risk of primary osteoporosis in men with coronary heart disease was inconclusive. Our study aims to determine the association of LDL-C and its trajectories for osteoporosis risk in the middle-aged and aged men of China. METHODS: The retrospective cohort study of 1546 men aged 69.74 ± 11.30 years conducted in Beijing, China from 2015 to 2022. And the incidence of primary osteoporosis was annually recorded. LDL-C trajectories were further identified by latent class growth model using repeated measurements of LDL-C. The association of baseline LDL-C for osteoporosis was estimated using hazard ratio (HR) with 95% CI in Cox proportional hazard model, while mean level and trajectories of LDL-C for osteoporosis were evaluated using odds ratio (OR) with 95% CI in logistic regression model. RESULTS: During the median 6.2-year follow-up period, 70 men developed primary osteoporosis. The higher level of baseline LDL-C (HR = 1.539, 95% CI: 1.012-2.342) and mean LDL-C (OR = 2.190, 95% CI: 1.443-3.324) were associated with higher risk of osteoporosis in men with coronary heart disease after adjusted for covariates. Compared with those in the LDL-C trajectory of low-stable decrease, participants with medium-fluctuant trajectory, whose longitudinal LDL-C started with a medium LDL-C level and appeared an increase and then decrease, were negatively associated with osteoporosis risk (OR = 2.451, 95% CI: 1.152-5.216). And participants with initially high LDL-C level and then a rapid decrease demonstrated a tendency towards reduced risk (OR = 0.718, 95% CI: 0.212-2.437). CONCLUSIONS Elevated LDL-C level and its long-term fluctuation may increase the risk of primary osteoporosis in men. Early controlling a stable level of LDL-C is also essential for bone health.

BACKGROUND: The relationship between glycated hemoglobin (HbA1c) and cognitive impairment in older adults with coronary heart disease (CHD) remains unclear. METHODS: The present study used a prospective cohort study design and included 3244 participants aged ≥ 65 years in Beijing, China. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. Serum HbA1c was detected at admission. All patients were divided into high HbA1c group (≥ 6.5 mmol/L) and low HbA1c group (< 6.5 mmol/L) based on their HbA1c levels. Logistic regression analyses were used to evaluate the association between HbA1c and cognitive impairment. RESULTS: In this study of 3244 participants, 1201 (37.0%) patients were in high HbA1c group and 2045 (63.0%) patients were in a state of cognitive impairment. Logistic regression analyses demonstrated that HbA1c was an independent risk factor for cognitive impairment regardless of whether the HbA1c was a continuous or categorical variable (OR = 1.27, 95% CI: 1.15-1.40, P < 0.001; OR = 1.79, 95% CI: 1.41-2.26, P ≤ 0.001, respectively). The restricted cubic spline curve exhibited that the relationship between the HbA1c and cognitive impairment was linear (p for non-linear = 0.323, P < 0.001). CONCLUSION Elevated levels of HbA1c were associated with an increased risk of cognitive impairment in older patients with CHD. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations.