ObjectiveTo explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P0.05）， and compared with the model group， both were significantly increased in the Sini San group （P0.05， P0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P0.05， P0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.

ObjectiveTo explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P<0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P<0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P<0.05）， and compared with the model group， both were significantly increased in the Sini San group （P<0.05， P<0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P<0.05， P<0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P<0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.

OBJECTIVE To provide reference for medical institutions to establish the record management mode and review rules of off-label use of 5-aminolevulinic acid （ALA） in photodynamic therapy based on the level of evidence. METHODS All ALA-containing outpatient prescriptions in the rational drug use system in our hospital from January 1， 2024 to December 31， 2025 were retrospectively collected. Based on the drug instructions， the current status of off-label use of ALA in photodynamic therapy was identified . The relevant studies in Micromedex， PubMed， CNKI， Wanfang Data and other databases were systematically searched as the relevant evidence-based evidence of ALA off-label use. According to the Off-label Drug Use Filing Standard of the hospital，the evidence-based evaluation method was used to evaluate the evidence-based evidence of ALA off-label use and carry out hierarchical management. RESULTS A total of 1 803 effective prescriptions were included， of which 676 （37.49%） were off-label use， distributed in the dermatology department （564 prescriptions，83.43%） and the plastic surgery department （112 prescriptions，16.57%）. All 676 prescriptions were off-indications medication， involving ten types of skin diseases， primarily including moderate to severe acne （39.94%）， skin warts （25.44%）， Bowen’s disease （11.98%）， and others. According to evidence-based evidence，off-label uses such as moderate to severe acne， actinic keratosis， and Bowen’s disease were managed according to the evidence categoryⅠ orⅡ.The uses of extramammary Paget’s disease and rosacea were managed according to the evidence category Ⅲ.The uses of lichen sclerosus and keloids were managed according to the evidence category Ⅳ.The results of evidence-based evaluation showed that 92.01% of off-label use in our hospital had high-level evidence-based support （ evidence category was gradeⅠ-Ⅱ）. CONCLUSIONS Off-label uses supported by high-level evidence， such as moderate to severe acne， skin warts， and Bowen’s disease， can be managed under filing category Ⅰ or Ⅱ. For the use of lichen sclerosus and keloids， evidence-based evidence is insufficient and should be strictly restricted.The vast majority of ALA off-label use in our hospital has sufficient evidence-based basis.

Objective: To explore the nonlinear dynamic effects of social capital, adverse childhood experiences (ACEs) and depressive symptoms on suicidal behavior among vocational high school students, so as to provide theoretical basis and practical references for formulating suicide prevention strategies. Methods: A convenience sampling method was employed to include 668 students from a vocational high school from Wuhan in March 2023. Social capital was used as the asymmetry variable, while ACEs and depressive symptoms were used as bifurcation variables, a cusp catastrophe model was constructed to analyze the nonlinear changes in suicidal behavior among vocational high school students, and its fit was compared with linear and Logistic regression models. Results: Among students in the health vocational high school in Wuhan, only suicidal ideation accounted for 8.5%, only suicide attempt for 18.6%, neither accounted for 31.9%, and both for 41.0%. Gender, left behind experience, family economic status, parental parenting styles, depressive symptoms, social capital, and ACEs were all related factors influencing suicidal behavior among vocational high school students ( χ 2/H=19.03, 13.33, 21.11, 46.70, 144.38, 24.61, 118.77, all P <0.05). Violin plots showed a bimodal distribution of suicidal behavior, indicating nonlinear variation characteristics. The cusp catastrophe model results showed that social capital was negatively correlated with suicidal behavior, but the relationship was bifurcated by ACEs ( α social capital = -0.006 , β ACEs =0.075) and depressive symptoms ( α social capital =-0.013, β depressive =0.028) (all P <0.05). When both ACEs and depressive symptoms coexisted, the impact of ACEs was stronger ( β ACEs =0.077, β depressive =0.014) (both P <0.05). The cusp catastrophe model fitted ( R 2=0.886, 0.881, 0.882) better than the linear ( R 2=0.258, 0.219, 0.258) and Logistic regression models ( R 2= 0.242, 0.211 , 0.176). Gender stratified analysis results showed that bifurcation effect of ACEs was stronger in males than in females( β boys =0.224, β girls =0.086); in females, both ACEs and depressive symptoms had a bifurcation effect, with the former showing a stronger effect ( β ACEs =0.062, β depressive =0.015) (all P <0.05). Conclusions Suicidal behavior among vocational high school students exhibits nonlinear characteristics. Improving social capital to reducing ACEs and depressive symptoms may contribute to decreasing adolescent suicidal behaviors.

Optical microscopy is essential for exploring biological and material structures, with resolution determining the level of observable detail. The advent of super-resolution fluorescence microscopy has broken the diffraction limit, achieving nanoscale resolution. However, traditional assessment methods, such as the Rayleigh criterion and point spread function (PSF) width measurement, rely on empirical judgments and diffraction-limited models, rendering them inadequate for modern super-resolution imaging. This review systematically traces the evolution of resolution assessment methodologies, from classical criteria to advanced strategies tailored for various super-resolution modalities. We first discuss Fourier-based quantitative methods. Fourier ring correlation (FRC) and its 3D counterpart, Fourier shell correlation (FSC), objectively determine resolution by evaluating the statistical correlation of two independent image reconstructions in frequency space. These methods offer robustness against noise and provide a global resolution metric, but they require data independence and are computationally intensive. They have become the prevailing standards in electron and super-resolution microscopy. Subsequently, we examine adaptations for specific super-resolution techniques. For single-molecule localization microscopy (SMLM) techniques such as PALM and STORM, the Fourier image resolution (FIRE) method extends FRC by incorporating a physical model that accounts for localization precision and labeling density. For stimulated emission depletion (STED) microscopy and other nonlinear techniques, assessment strategies differ. While PSF shrinkage measurements using fluorescent beads are useful for system calibration, evaluating the effective resolution directly on biological samples is more practical. This is typically performed via linewidth analysis of known structures (e.g., microtubules) or edge-spread function measurements, capturing the effects of photobleaching and sample-induced aberrations. A major paradigm shift is parameter-free resolution estimation based on decorrelation analysis. This method analyzes the autocorrelation decay of a single image’s Fourier spectrum to identify the cutoff spatial frequency without requiring dual datasets or user-defined thresholds. Its high efficiency and broad applicability have been validated across widefield, confocal, STED, SIM, and SMLM modalities. Optimized rendering strategies for SMLM data further enhance its accuracy, and it is emerging as a tool for real-time optimization of experimental parameters. The review also addresses the “gold standard” of resolution validation using well-defined nanostructures, such as DNA origami and nuclear pore complexes, which provide ground truth for verifying resolution claims and detecting artifacts. In the era of artificial intelligence, deep learning plays a dual role: it powerfully enhances image resolution but also introduces challenges, as models may generate “hallucinations” or false details. This underscores the need for new validation metrics to verify the physical fidelity of AI-generated content. Finally, we outline future directions: developing unified cross-modality standards, enabling real-time dynamic resolution monitoring for live-cell imaging, creating techniques for generating local resolution maps to capture sample heterogeneity, and integrating intelligent error correction to ensure data veracity. By providing a comprehensive overview of resolution assessment progress and challenges, this review aims to equip researchers with the knowledge to select appropriate tools, thereby fostering rigorous quantitative imaging in the life and material sciences.

Since its emergence in the 1980s, the human immunodeficiency virus (HIV) has caused a global pandemic, posing a severe threat to human life and health as well as social development. Although pre-exposure prophylaxis (PrEP) effectively curbs HIV transmission and antiretroviral therapy (ART) significantly extends the lifespan of patients, vaccines remain a pivotal tool for blocking transmission and ending the pandemic. The high genetic variability of HIV-1, the glycan shield of its envelope glycoproteins, and the long-term persistence of latent reservoirs have repeatedly led to bottlenecks in traditional vaccine strategies. In recent years, mRNA technology has offered a novel approach to addressing these challenges, leveraging advantages such as sequence programmability, short production cycles, native conformational expression of antigens, and self-adjuvant effects. In recent years, mRNA vaccine technology has emerged as a transformative solution to longstanding vaccinology challenges, characterized by its sequence programmability, rapid production cycles, native conformational antigen expression, and intrinsic self-adjuvanting properties. Unlike traditional platforms reliant on pathogen culture or recombinant proteins, mRNA vaccines can be expeditiously designed and updated based solely on viral genomic sequences. Lipid nanoparticle (LNP)-encapsulated mRNA facilitates endogenous antigen expression and presentation, simultaneously eliciting potent humoral and cellular immune responses. Within this landscape, self-amplifying mRNA (saRNA) further extends in vivo antigen expression to enhance the persistence of immune responses. Moreover, the LNP delivery system not only protects mRNA from degradation and mediates endosomal escape but also synergizes with mRNA to optimize immune activation via self-adjuvant effects. Importantly, mRNA platforms circumvent the pre-existing immunity associated with viral vectors and the genomic integration risks of DNA vaccines, positioning them as a cornerstone for global pandemic preparedness. This review systematically delineates recent advances in mRNA technology for HIV-1 vaccine development, focusing on four pivotal research frontiers. First, mRNA innovations building upon the RV144 trial optimize antigens through codon modification and multivalent designs to induce more durable and broad-spectrum immunity. Second, particulate mRNA vaccine strategies, utilizing virus-like particles (VLPs) and ferritin nanoparticles, achieve in situ antigen self-assembly, significantly enhancing B cell activation and reducing infection risks in non-human primate models. Third, germline-targeting mRNA vaccines address the low-affinity barrier of broadly neutralizing antibody (bNAp) precursors, efficiently activating rare precursor B cells and promoting affinity maturation. Fourth, therapeutic mRNA vaccines offer unique advantages for an HIV functional cure; combining immunogens with mRNA-encoded adjuvants potentiates cellular immunity, while LNP-mediated “shock-and-kill” strategies specifically activate latent reservoirs to guide immune clearance. Comparative analyses with traditional platforms reveal that mRNA technology redefines antigen production and presentation, simulating chronic infection through sustained expression and enabling dual-pathway presentation via endogenous synthesis. Furthermore, we explore the mechanistic innovations of mRNA vaccines in inducing bNAps: sustained in vivo production prolongs the activation window for precursor B cells and maintains germinal center (GC) reactions; endogenously expressed antigens adopt native conformations to expose conserved epitopes; and self-adjuvanting effects modulate the functions of antigen-presenting cells (APCs) and follicular helper T cells (Tfh), driving somatic hypermutation and affinity maturation. We also address critical clinical translation challenges, including immune durability, adaptability to special populations, and large-scale LNP manufacturing, while proposing targeted optimization strategies. In conclusion, this review establishes a theoretical framework for utilizing mRNA technology to overcome HIV-1 immune escape, transitioning from a descriptive paradigm to a problem-solving-based synthesis of evidence. By integrating preclinical and early clinical data, we bridge the gap between basic design and translational verification. mRNA technology is poised to become a central pillar inHIV-1 prevention and therapy, providing a robust toolset to achieve the global goal of ending the AIDS pandemic and offering a blueprint for vaccine development against other recalcitrant infectious diseases.

ObjectivePost-ischemic acute inflammation and the subsequent persistent dysregulation of the immune microenvironment represent major pathological drivers that aggravate neuronal injury and severely restrict functional recovery following ischemic stroke. Although current reperfusion therapies partially restore blood flow, they fail to effectively modulate the secondary inflammatory cascade and oxidative stress, which remain critical barriers to neurological restoration. To address this challenge, this study aimed to engineer and systematically evaluate a biomimetic nanosystem composed of transforming growth factor-β1 (TGF-β1)-loaded platelet membrane-camouflaged lipid nanoparticles (PLP). This nanosystem was designed to achieve dual lesion-targeted delivery and immune microenvironment remodeling. By verifying its spatiotemporal accumulation, anti-inflammatory activity, and neuroprotective efficacy, we sought to establish an integrated therapeutic strategy that simultaneously enables lesion targeting, immune regulation, and functional recovery after ischemic injury. MethodsThe physicochemical properties of PLP, including hydrodynamic particle size, zeta potential, structural stability, and morphology, were characterized using dynamic light scattering, zeta potential analysis, and transmission electron microscopy. The preservation of platelet membrane-derived adhesion and immunoregulatory proteins was confirmed by SDS-PAGE through comparative analysis of protein band profiles between PLP and native platelet membranes. The in vitro biological activities of PLP were evaluated using two complementary cellular models. LPS-induced M1-polarized RAW264.7 macrophages were employed to assess inflammatory modulation, while oxygen glucose deprivation/reperfusion (OGD/R)-induced BV2 microglial cells and SH-SY5Y neuronal cells were utilized to investigate neuroinflammatory regulation and neuronal protection. For in vivo validation, a transient middle cerebral artery occlusion (tMCAO) mouse model was established to mimic ischemia-reperfusion injury. The spatiotemporal biodistribution and lesion-targeting capability of the PLP were monitored through live fluorescence imaging. Therapeutic efficacy was comprehensively evaluated by triphenyltetrazolium chloride (TTC) staining, glial fibrillary acidic protein (GFAP) immunofluorescence analysis, body weight monitoring, and neurological severity score (NSS) assessment. ResultsPLP nanoparticles displayed a uniform spherical morphology, nanoscale particle size distribution, and stable negative surface charge, indicating favorable colloidal stability and circulation potential. SDS-PAGE results confirmed the effective retention of key platelet membrane proteins associated with endothelial adhesion, immune evasion, and inflammatory regulation, demonstrating the successful biomimetic construction. Optimal therapeutic concentrations were determined in OGD/R-induced BV2 cells, where PLP exhibited excellent cytocompatibility and anti-inflammatory activity.In vitro experiments demonstrated that PLP significantly inhibited the polarization of RAW264.7 macrophages toward the pro-inflammatory M1 phenotype and markedly reduced neuronal apoptosis under ischemia-reperfusion conditions. In vivo fluorescence imaging revealed that PLP rapidly accumulated in the ischemic brain hemisphere and maintained prolonged retention for up to 7 d, suggesting enhanced lesion-specific targeting and sustained drug release. Compared with control group, PLP treatment significantly reduced cerebral infarct volume, attenuated reactive astrogliosis, improved weight recovery, and accelerated neurological functional restoration, as reflected by significantly improved NSS scores. ConclusionThis study establishes a multifunctional biomimetic nanoplatform that integrates platelet membrane-mediated active targeting with the anti-inflammatory, antioxidative, and neuroprotective properties of TGF-β1. The PLP system enables rapid lesion homing and long-term retention while synergistically regulating the post-stroke inflammatory microenvironment by suppressing pro-inflammatory immune activation, reducing neuronal apoptosis, and limiting excessive astrocyte reactivity. Importantly, this study proposes a conceptually therapeutic paradigm that combines targeted delivery with immune microenvironment remodeling to achieve comprehensive neurovascular protection. These findings provide strong experimental evidence supporting the translational potential of biomimetic nanotherapeutics as next-generation precision interventions for ischemic stroke.

BackgroundAdolescents with depressive disorder often engage in non-suicidal self-injury （NSSI） behaviors， which severely impacts their physical and mental health. Impulsivity and emotional regulation are key factors influencing NSSI behaviors. However， research on the mechanisms through which impulsivity and emotional regulation affect NSSI behaviors in adolescent depressive disorder patients with NSSI remains insufficient， limiting the development of effective intervention strategies. ObjectiveTo explore the differences in impulsivity and emotion regulation abilities between adolescent patients with depressive disorder accompanied by and without NSSI behaviors， and to analyze the association between NSSI behaviors and impulsivity and emotion regulation abilities in adolescent patients with depressive disorder accompanied by NSSI behaviors. MethodsA total of 184 adolescents hospitalized in the child and adolescent psychiatry department of Wuxi Mental Health Center from October 2023 to August 2024， who met the diagnostic criteria for depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， were consecutively enrolled as study subjects. Based on the diagnostic criteria for NSSI in DSM-5， patients were divided into NSSI group （n=108） and non-NSSI group （n=76）. The Barratt Impulsiveness Scale-11 （BIS-11）， the Emotion Regulation Questionnaire （ERQ）， the Adolescent Self-Harm Questionnaire， and the Positive and Negative Suicide Ideation （PANSI） were used for assessment. Spearman correlation analysis was employed to explore the correlation between the scores of the Adolescent Self-Harm Questionnaire and the scores of BIS-11 and ERQ in the NSSI group. Multiple regression analysis was conducted to examine the effects of impulsivity and emotion regulation on NSSI behaviors in the NSSI group. ResultsCompared to the non-NSSI group， the NSSI group showed significantly higher scores in BIS-11 non-planned impulsivity （Z=-4.181， P<0.05）， action impulsivity （t=4.944， P<0.05）， cognitive impulsivity （Z=-3.392， P<0.05）， and total score （t=4.763， P<0.05）， and lower scores in the cognitive reappraisal of ERQ （t=-4.094， P<0.05） and total score （Z=-2.299， P<0.05）， and higher scores in the expression inhibition of ERQ （Z=-3.019， P<0.05）. The correlation analysis results showed that the score of the adolescent self-harm questionnaire in the NSSI group was positively correlated with the behavioral impulsivity factor score in the BIS-11 （r=0.434， P<0.05）. Multiple regression analysis indicated that action impulsivity factor was a significant correlate of self-injury behaviors in the NSSI group （B=0.855， P<0.05）， explaining 22.30% of the total variance. ConclusionAdolescent patients with depressive disorder accompanied by NSSI behaviors exhibit higher levels of impulsivity and poorer emotional regulation abilities. Action impulsivity may play a significant role in the mechanism of NSSI behaviors. ［Funded by Wuxi Municipal Health Commission Research Project （number， Q202320）］

This article adopts Professor CHEN Chaozu′s " sanjiao composed by membrane-striae" theory as its foundation to explore the relationship between irritable bowel syndrome and functional/structural abnormalities of the membrane-striae. Sanjiao encompasses both the tangible membrane and the intangible striae. These striae permeate the entire body，and their pathological changes comprehensively reflect qi，body fluids，and fasciae. Based on the physiological function of the membrane-striae in regulating qi and fluids，the pathogenesis of irritable bowel syndrome is characterized by a disharmony of membrane-striae and an imbalance of the qi-fluid interactions. In the early stage，external pathogens，emotional factors，or dietary stimuli often cause membrane-striae constriction and disordered qi-fluid circulation. In the middle stage，stagnant fluids gradually transform into phlegm retention，leading to membrane-striae obstruction. In the late stage，deficiency of vital qi becomes predominant，manifesting as laxity of membrane-striae with impaired control or weakened conduction. The treatment of irritable bowel syndrome should adopt " unblocking" as the guiding principle. In the early stage，therapy should focus on eliminating pathogenic factors and soothing membrane-striae to promptly restore qi-fluid circulation，thereby attaining unblocking through spasm relief. In the middle stage，treatment should focus on resolving tangible obstructions in membrane-striae，achieving unblocking via dredging. In the late stage，the emphasis should shift to reinforcing healthy qi，particularly by strengthening spleen-kidney yang qi，and achieving unblocking through supplementation. Concurrently，throughout the entire treatment process，the regulation of mental state and easing of emotional tension should be integrated to alleviate patient′s anxiety，achieving the goal of holistic treatment of both body and mind.

Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.