Objective: To explore the effect of a computer assisted audiovisual combined intervention model on the core symptoms of children with autism spectrum disorder (ASD), in order to provide references for enriching intervention and treatment methods for ASD children. Methods: From December 2023 to March 2024, 36 ASD children aged 4-8 years were recruited from Tianjin Disabled Persons Rehabilitation Center and Xinxinyu Children s Rehabilitation Center, and were divided into a training group (22 cases) and a control group (14 cases). The training group completed a 12 week audiovisual training course (visual sessions:twice a week, for 50-60 minutes each session; auditory sessions:three times a week, for 15 minutes each time), while the control group received only conventional treatment interventions. Before and after the intervention, the core symptoms of ASD children were assessed using the Short Sensory Profile (SSP), Social Responsiveness Scale (SRS), and Repetitive Behavior Questionnaire-2 ( RBQ- 2). Eye tracking experiments were used to test preferences for social attention. Results: Before the intervention, there were no statistically significant differences in the total scores and factor scores of the SSP and RBQ-2 scales between the two groups ( t =-1.63, 0.38, both P >0.05). The SRS total score, social communication, and restricted interests and repetitive behavior factor scores of the training group (90.68±25.83, 33.36±11.80, 15.64±7.00) were significantly higher than those of the control group (72.29±19.84, 24.93±7.85, 10.21±5.67) ( t =2.27, 2.36, 2.43, all P <0.05). Children in the training group with higher social communication factor scores before the intervention scored lower than the control group at the post intervention test (simple slope=-14.17, t =-2.48, P = 0.02), while there was no statistically significant difference in post intervention scores between children with lower social communication factor scores before the intervention and the control group (simple slope=2.31, t =0.57, P >0.05). Eye tracking experiments showed that the total fixation time on geometric images decreased significantly more in the training group [ -4.56 (-11.42, 1.21)] compared to the control group [6.55 (-0.32, 16.53)] after the intervention ( Z=2.48, P <0.05). Conclusions The computer assisted audiovisual intervention model can effectively improve the core symptoms of ASD children with poorer social communication levels. The promotion of the intervention model needs to consider individual differences in ASD.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveTo explore the mechanism through which Banxia Baizhu Tianmatang ameliorates cognitive impairment in epileptic rats induced by lithium chloride-pilocarpine by regulating the neuroinflammatory reaction mediated by NOD-like receptor protein 3 （NLRP3） inflammasomes. MethodsSixty male SD rats were randomly allocated into blank， model， carbamazepine （0.125 g·kg^-1·d^-1）， Banxia Baizhu Tianmatang （1.04 g·kg^-1·d^-1）， and carbamazepine （0.125 g·kg^-1·d^-1） + Banxia Baizhu Tianmatang （1.04 g·kg^-1·d^-1） groups （n=12）. After the modeling of epilepsy， rats were administrated with corresponding agents by gavage for 12 weeks. At the 6th and 12th week of the intervention， the rats’ hyper-excited behavior was evaluated by the stylus experiment， and at the 12^th week of intervention， the cognitive function was evaluated by Barnes maze. At the same time， the seizure frequency and severity grade （Racine score） were recorded. The serum and hippocampus tissue samples were collected after anesthesia for the following tests. Nissl staining was used to evaluate the degree of neuronal damage in the hippocampal CA1 area. The content of malondialdehyde （MDA） in the hippocampus was determined by the thiobarbituric acid （TBA） method. Serum levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-18 （IL-18） were quantified by enzyme-linked immunosorbent assay （ELISA）. Immunohistochemical method was adopted to detect the expression of apoptosis-associated speck-like protein containing a card （ASC） in the hippocampus. Western blot was employed to quantitatively analyze the protein levels of NLRP3， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， and brain-derived neurotrophic factor （BDNF） in the hippocampus. ResultsThe model group showed increased stylus scores at the 6th and 12^th week after modeling， a decreased Barnes maze strategy score at the 12^th week， a prolonged incubation period （P<0.05）， elevated serum levels of inflammatory factors （P<0.05）， decreased neurons with scattered arrangement and large gaps in the hippocampus， increased content of MDA in the hippocampus （P<0.05）， an increased positive expression of ASC， and up-regulated protein levels of Caspase-1， NLRP3， and BDNF （P<0.05）. Compared with the model group， the intervention with Banxia Baizhu Tianmatang for 12 weeks was accompanied by a decreased stylus score， epileptic seizures with a decreased score， a decreased number， and shortened duration， an increased Barnes maze strategy score， shortened escape latency （P<0.01）， declined serum levels of inflammatory factors （P<0.05）， regular morphology of hippocampal neurons， reduced MDA content in the hippocampus （P<0.05）， a decreased positive expression of ASC， and down-regulated protein levels of Caspase-1， NLRP3， and BDNF （P<0.05， P<0.01）. In addition， compared with the carbamazepine group， Banxia Baizhu Tianmatang + carbamazepine showed improved performance in controlling the seizure， improved the cognitive behavior score and morphology of hippocampal neurons， alleviated the oxidative stress products， lowered the levels of inflammatory factors， reduced the positive expression of ASC in the hippocampus， and down-regulated the expression of Caspase-1， NLRP3 and BDNF， with no significant differences. ConclusionBanxia Baizhu Tianmatang may reduce neuroinflammation， control epileptic seizures， and ameliorate cognitive impairment by inhibiting the expression of NLRP3 inflammasomes.

Molar-incisor hypomineralization (MIH) is a developmental defect of enamel that is characterized primarily by abnormal enamel mineralization affecting the first permanent molars and permanent incisors. Due to insufficient mineralization, teeth affected by MIH are prone to post-eruptive breakdown and caries, potentially leading to sequelae such as tooth sensitivity and occlusal problems. The diagnosis of MIH is primarily based on relevant perinatal and infantile medical history, the characteristic distribution of affected teeth, and the morphological features of the enamel defects. Based on the extent and severity of the enamel defect, MIH is classified as mild or severe. Diagnosis and treatment strategies emphasize early screening, diagnosis, and intervention, prioritizing prevention, providing symptomatic care, and implementing regular recall assessments. Mild MIH predominantly manifests as demineralized enamel opacities or discoloration, typically without significant enamel breakdown. Treatment focuses on caries prevention and aesthetic restoration, employing techniques such as remineralization, micro-abrasion, resin infiltration, bleaching, fluoride application, and fissure sealants. Severe MIH typically presents with extensive enamel opacities accompanied by substantial enamel breakdown and may be complicated by caries and tooth sensitivity. Management primarily involves restoring the structural defects or, for teeth that cannot be preserved, extraction followed by orthodontic treatment. Comprehensive management often requires a multimodal approach integrating various therapeutic modalities to restore both the function and aesthetics of the affected teeth and overall dentition. This article provides a review of advancements in diagnosis and the treatment strategies for MIH, offering a reference for clinical practice.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

Objective: To compare the Reveos automated blood processing system with the current method, and to evaluate the feasibility and validity of using the Reveos system for blood component preparation. Methods: Forty units of 400 mL whole blood samples were divided into two groups: 2C group (for two-component preparation) and 3C group (for three-component preparation). Each group was further divided into a Reveos subgroup and a control subgroup. Blood components were prepared using the Reveos system and the current centrifugation method respectively. The 2C group yielded suspended red blood cells and plasma, while the 3C group yielded suspended red blood cells, plasma, and platelets. Key quality indicators for red blood cells, plasma, and platelets were measured before and after separation. Inter-group differences were analyzed using SPSS 25.0. Results: The trend of changes in the main performance indicators of red blood cells, plasma, and platelets before and after separation was generally consistent between the Reveos group and the control group, with no significant differences for most performance indicators. The Reveos system outperformed the current method in several aspects: in the 3C group, the hematocrit (Hct) was significantly higher in the Reveos group than in the control group [(62.82%±1.64%) vs (53.62%±3.04)%, P<0.001]; the white blood cell count in red blood cell suspensions was significantly lower than that in the control group [(3.37±1.42)×10 /L vs (8.42±2.30)×10 /L, P<0.001]; plasma yield was 27.5% higher than that in the control group [(183.90±17.37) mL vs (144.28±20.53) mL, P<0.001]; and the platelet activation rate was significantly lower than that in the control group [(21.97±14.25)% vs (34.73±11.92)%, P=0.044]. Conclusion: The Reveos system demonstrates good consistency with the current method in preparing blood components, and outperforms the current method in terms of leukocyte reduction and red blood cell concentration.

OBJECTIVE To systematically evaluate risk prediction models for chemotherapy-induced myelosuppression in pediatric patients with malignant tumors， evaluate their modeling strategies， key predictors， and predictive performance， and provide evidence-based references for clinical decision-making and research. METHODS A literature search was conducted across 11 databases， including CNKI， Wanfang Data， and PubMed， for relevant studies published before April 2025. Two reviewers independently performed literature screening and data extraction， and the risk of bias and applicability of the models were evaluated using the PROBAST tool. RESULTS Ultimately， seven studies were selected， of which four were English articles and three were Chinese articles， involving 12 risk prediction models. Although model discrimination was good （AUC 0.748-0.981）， only two models underwent external validation； furthermore， calibration was inadequately reported in three studies. PROBAST indicated that all models exhibited a high risk of bias， with major issues including a predominance of retrospective designs， inadequate sample representativeness， and lack of blinding. However， in terms of applicability， all models received favorable evaluations. In terms of modeling methods， most studies employed traditional logistic regression approaches to construct models， while only a minority introduced machine learning algorithms and conducted systematic comparisons among multiple algorithms. Models developed using machine learning methods significantly outperformed those constructed with traditional statistical methods. CONCLUSIONS The existing risk prediction models for myelosuppression after chemotherapy in children with malignant tumors demonstrate potential in clinical risk early warning. However， they generally suffer from design and methodological limitations， such as a predominance of retrospective single-center designs， few events per variable， opaque handling of missing data， and inconsistent reporting of model coefficients. Future studies should adopt prospective designs， incorporate machine learning with key clinical predictors， and follow TRIPOD reporting guidelines to enhance scientific rigor and clinical utility.