Attention deficit and hyperactive disorder （ADHD） is the most common neurodevelopmental disorder of childhood. It seriously impairs academic achievement， social interaction， and vocational development， and increases the risk of accidental injury and substance abuse. In some cases， the symptoms may also exert an indirect disruptive effect on public order. Its aetiology involves interactions among genetic， perinatal environmental， and psychosocial factors that cannot be fully disentangled by single clinical studies. Therefore， a systematic evaluation of existing animal models is essential for revealing pathophysiology and developing novel therapies. Using the keywords "attention deficit and hyperactive disorder"， "models， animal"， "validity"， and their English equivalents， we systematically searched PubMed， Web of Science， CNKI， and Wanfang for publications from 2000 to 2025 （retrieving 328 publications） and added further references by citation tracking. Eighty-six rodent ADHD models that provided detailed construction protocols， behavioural assessments， neurobiological mechanisms， or pharmacological data were included and classified into spontaneous genetic， genetically engineered， and environmentally induced paradigms. Their face， construct， and predictive validity were compared. Among spontaneous genetic models， spontaneously hypertensive rats reproduce hyperactivity， impulsivity， and stimulant responses well， yet hypertension and sex differences limit specificity. Acallosal mouse strains link corpus callosum absence to ADHD-like behaviours， but neurotransmitter studies remain scarce. Genetically engineered rodents—including dopamine transporter， neurokinin-1 receptor and mediator complex subunit 23 knockout or conditional gene knockout lines—precisely dissect dopaminergic， noradrenergic， synaptic， or epigenetic pathways， yet generally lack full phenotypic coverage， social-deficit modelling， and comorbidity representation， and are accompanied by adverse effects such as growth retardation or ocular defects. Environmentally induced models employ lead， polychlorinated biphenyls， alcohol， nicotine exposures， 6-hydroxydopamine lesions， neonatal hypoxia， early social isolation， or maternal stress to recapitulate core symptoms. However， dose-schedule standardisation is lacking. Behavioural reversibility diverges from clinical persistence， and non-specific phenotypes such as anxiety or depression are common. Overall， no single paradigm simultaneously achieves high validity across all three dimensions. Currently， ADHD models have progressed from single-factor simulations to multidimensional evaluation， yet significant gaps remain in genetic-background standardisation， sex differences， cross-species translation， and syndrome-differentiation modelling under traditional Chinese medicine. Future directions should integrate genetic， environmental， and epigenetic interactions， establish life-span validation systems， and incorporate computational neuroscience alongside integrative Chinese-Western strategies to enhance clinical relevance and translational utility， thereby providing robust evidence-based support for mechanistic elucidation， drug screening and precision intervention in ADHD.

Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveTo understand the mental health literacy levels and influencing factors among middle school students in Minhang District, Shanghai, and to provide a basis for formulating mental health promotion strategies. MethodsA multi-stage stratified cluster sampling method was adopted. From September to October 2023, middle school students (including junior and senior high school) from 14 streets, towns, and industrial zones in Minhang District, Shanghai, were recruited to participate in a questionnaire survey. The survey collected demographic information and employed the Adolescent Mental Health Literacy Assessment Scale. This scale comprises four dimensions (knowledge, recognition ability, attitude, and behavior) with a total of 22 items, using a Likert 5-point scale (1‒5 points), giving a maximum total score of 110 points. Reverse-scored items were inverted, and the sum of all item scores constituted the total scale score, with higher scores indicating better mental health literacy. A total score of ≥88 points was defined as having adequate mental health literacy. Multiple linear regression was used to analyze the factors influencing mental health literacy. ResultsThe average mental health literacy score of the 3 963 middle school students in Minhang District of Shanghai City was (85.42±11.27) points, with 45.22% of students having adequate mental health literacy. Univariate analyses showed that female students, junior high school students, and those without stressful events or physical illnesses in the past three months had higher total scores of mental health literacy. Statistically significant differences in total scores were also observed among students with different family economic statuses, parental education levels, frequency of physical exercise, parental relationships, father‑child relationships, and mother‑child relationships (all P<0.05). Multiple linear regression analyses showed that middle school students who were female, had better family economic conditions, higher maternal education levels (university degree or above), and harmonious mother-child relationships had higher mental health literacy scores. In contrast, high school students and those middle school students who participated in less physical activity had lower mental health literacy scores. Multivariate logistic regression analyses indicated that students who were female (OR=1.336, 95%CI: 1.174‒1.520), had superior family economic status (OR=2.000, 95%CI: 1.101‒3.725), had mothers with a university education level (OR=1.501, 95%CI: 1.217‒1.856), had lost one parent (OR=2.189, 95%CI: 1.176~4.158), or reported harmonious mother‑child relationships (OR=2.052, 95%CI: 1.432‒2.987) were more likely to meet the criteria for mental health literacy, whereas those who rarely engaged in physical exercise (OR=0.502, 95%CI: 0.358‒0.694) were less likely to have adequate mental health literacy. Stratified analyses showed that mental health literacy levels among junior high school students were positively correlated with being female, having a mother with a university education level, and having a mother‑child relationship that was average or harmonious and having a harmonious father‑child relationship, and negatively correlated with occasional or rare participation in physical exercise. Among senior high school students, mental health literacy levels were positively correlated with being female, having good or superior family economic status, having a mother with a university education level or above, and having a harmonious mother‑child relationship. ConclusionThe rate of adequate mental health literacy among middle school students in Minhang District, Shanghai, was approximately 45.22%. Gender, grade level, family economic status, maternal education level, physical activity participation, and mother-child relationship are independent factors associated with the level of mental health literacy among middle school students. Mother-child relationship and physical activity are potential intervention entry points. It is recommended to implement targeted health promotion initiatives focusing on key groups, such as high school boys, students from economically disadvantaged families, and those with insufficient physical activity.

Objective To draw the genome-wide distribution and remodeling characteristics of H3K27me3 silencers in signet-ring cell carcinoma of the stomach(SRCC)through epigenetic sequencing technology,and to investigate their roles in transcriptional regulation in order to elucidate the regulatory mechanism of SRCC malignant progression.Methods The study was conducted on 35 gastric samples obtained by gastroendoscopic biopsy(15 normal and 20 SRCC tissues)from Department of Gastroenterology of Army Medical Center of PLA between January 2021 and December 2023.Multi-omics analyses,including assay for transposase-accessible chromatin with high-throughput sequencing(ATAC-seq),cleavage under targets and tagmentation(CUT&Tag)and transcriptome sequencing(RNA-seq),were performed to identify chromatin accessibility,H3K27me3 silencer regions,and transcriptional changes,with aid of Illumina NovaSeq 6000.H3K27me3 related differentially expressed genes(|Log2FC|>1,FDR<0.05)were screened using DESeq2.Gene Ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were employed to analyze the enrichment function,and Homer was employed to identify transcription factor motifs.A regulatory network was constructed using Cytoscape,and then validated using immunohistochemistry to explore its regulatory mechanism.Results H3K27me3 silencers were primarily located in distal intergenic regions(37.06%)in SRCC.Compared with the normal tissues,SRCC showed a significant reduction in H3K27me3 silencer signals(95%CI:1.34～2.30,P=0.007)with 6 257 lost sites(FDR<0.01).Integrating CUT&Tag and RNA-seq revealed 380 up-regulated immune-related genes,particularly in T cell receptor signaling(OR=4.2,95%CI:2.8～6.3,P=0.002).Immunohistochemistry confirmed elevated expression of transcription factor EHF(P<0.05).Conclusion There is the remodeling of H3K27me3 silencers in SRCC,and EHF may potentially play a crucial role in the SRCC malignant progression.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

Objective The incidence of Alzheimer's disease(AD)in postmenopausal women is significantly increased with ageing.Menopause induced ovarian estrogen deficiency has been regarded as one of the causative risk factor of AD,but currently the detail mechanisms underlying estrogen regulation on the hippocampus remain unclear.This study aimed to uncover the potential pathways and key molecules through which estrogen deficiency induced by ovariectomy promotes AD pathogenesis by integrating transcriptomic and proteomic analyses.Methods The ovariectomy(OVX)mouse model was established to simulate postmenopausal estrogen decline.Transcriptomic(n=3)and proteomic(n=3)differences in the hippocampal tissues of OVX mice were analyzed using RNA sequencing and protein mass spectrometry.Co-trend molecules identified from both omics datasets were subjected to GO/KEGG enrichment and cluster analyses.These molecules were further compared with the human AD hippocampal database(AlzDate)for expression trend consistency;and online resources such as String,GeneCards/Uniports were employed to analyze protein interactions and networks of the co-trend genes to identify key molecules.Results A total of 139 differentially expressed genes(DEG)and 248 differentially expressed proteins(DEP)were identified,with 18 molecules showing consistent expression trends in both omics.Functional enrichment analysis revealed that these molecules were primarily involved in axonogenesis,cytoskeleton dynamics regulation,and long-chain fatty acid transport.After comparison with the human AD database,11 of the 18 co-trend molecules exhibited expression inhibition consistent with AD-associated genes in the human hippocampal databases.Interaction network analysis identified Aldoc(involved in glycolysis),Aldh6a1(involved in ROS scavenging),Etnppl(involved in mitochondrial energy metabolism),and Itih3(involved in hyaluronic acid-mediated extracellular matrix remodeling)as key genes contributing to AD pathogenesis.Additionally,3 co-trend molecules(Prxl2a,Set,Plin4)were not detected in human AD databases.Conclusion Postmenopausal estrogen deficiency decreases the expression levels of hippocampal Aldoc,Etnppl and Aldh6a1 then affects mitochondrial energy metabolism;and decreases levels of Itih3 expression then disables extracellular matrix remodeling.These effects collectively impair hippocampal axonal regenerative capacity,destabilize the cytoskeleton,and hinder the transport of long-chain fatty acids,ultimately driving the progression of AD pathology.

Objective:To explore the molecular mechanism of TCM compound Shengxue Tongbian Granules in improving intestinal injury in septic rats through bioinformatics and experimental validation methods.Methods:The GSE131761 gene set was processed by bioinformatics to screen differential genes, then weighted gene co-expression network analysis (WGCNA) was applied to screen modular genes. The intersection of modular genes and differential genes was taken, and finally, the least absolute shrinkage and selection operator (LASSO) technique was applied to further obtain the key targets of sepsis, which was validated by experiments. Totally 72 SD rats were divided into sham-operation group, model group, dexamethasone group (0.15 mg/kg), Shengxue Tongbian Granules low- (0.3 g/kg), medium- (0.6 g/kg), and high-dosage (1.2 g/kg) groups, with 12 rats in each group. Corresponding drug interventions were administered to each treatment group before and 12 hours after modeling. The sham-operation group and the model group were gavaged daily with equal amounts of saline. Samples were collected after 24 hours. HE staining was used to detect the pathological morphology of intestinal tissues in each group of rats; ELISA was used to detect the levels of TNF-α, diamine oxidase (DAO), IL-6, IL-10, and myeloperoxidase (MPO) in rat serum. Immunohistochemistry was used to detect the protein expressions of MPO and neutrophil elastase (NE/LANE) in intestinal tissue, and Western blot was used to detect the protein expression of peptidyl arginine deaminase (PAD4) in intestinal tissue.Results:Seven final key genes related to sepsis were selected, namely ANXA3, CYP1B1, FCAR, LILRA5, PADI4, NOV, and S100A12. Experimental results showed that drug administration alleviated intestinal injury; compared with the model group, the levels of TNF-α, IL-6, MPO, and DAO decreased in the Shengxue Tongbian Granules high-dosage group ( P<0.05), the levels of ELANE and MPO were reduced in Shengxue Tongbian Granules low-, medium-, and high-dosage groups ( P<0.05), and PAD4 expression was reduced in the Shengxue Tongbian Granules high-dosage group ( P<0.05). Conclusion:Shengxue Tongbian Granules can improve the intestinal injury of septic rats, and the mechanism may be related to the inhibition of PAD4-mediated formation of NETs and the improvement of inflammatory response.