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.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Dry eye disease (DED) is a prevalent and intractable ocular disease induced by a variety of causes. Elevated sphingomyelin (SM) levels and pro-inflammatory cytokines were detected on the ocular surface of DED patients, particularly in the meibomian glands. Sphingomyelin synthase 2 (SMS2), one of the proteins involved in SM synthesis, would light a novel way of developing a DED therapy strategy. Herein, we report the design and optimization of a series of novel thiophene carboxamide derivatives to afford 14l with an improved highly potent inhibitory activity on SM synthesis (IC_{50, SMS2} = 28 nmol/L). Moreover, 14l exhibited a notable protective effect of anti-inflammation and anti-apoptosis on human corneal epithelial cells (HCEC) under TNF-α-hyperosmotic stress conditions in vitro, with an acceptable ocular specific distribution (corneas and meibomian glands) and pharmacokinetics (PK) profiles (t _{1/2, cornea} = 1.11 h; t _{1/2, meibomian glands} = 4.32 h) in rats. Furthermore, 14l alleviated the dry eye symptoms including corneal fluorescein staining scores and tear secretion in a dose-dependent manner in mice. Mechanically, 14l reduced the mRNA expression of Tnf-α, Il-1β and Mmp-9 in corneas, as well as the proportion of very long chain SM in meibomian glands. Our findings provide a new strategy for DED therapy based on selective SMS2 inhibitors.

OBJECTIVE To investigate the antidepressant mechanism of Shugan hewei tang （SGHWT） based on the metabolomics of prefrontal cortex （PFC）-nucleus accumbens （NAc）-ventral tegmental area （VTA） neural circuit. METHODS Male SD rats were randomly divided into blank group， model group， SGHWT low-， medium- and high-dose groups [3.67， 7.34， 14.68 g/（kg·d）， by raw material]， and fluoxetine group [1.58 mg/（kg·d）， positive control]， with 12 rats in each group. Except for the blank group， the depression model was established by chronic unpredictable mild stress combined with individual cage housing in the remaining groups， and the corresponding drug solution or normal saline was administered via gavage during modeling， once a day， for 6 consecutive weeks. After the last administration， the body weight， sucrose preference rate， total moving distance， frequency into the center and immobility time of rats in each group were detected. Samples of PFC， NAc and VTA areas of rats in the blank group， model group， SGHWT medium-dose group and fluoxetine positive control groups were collected，and their histomorphological features were observed， and non-targeted metabolomics analysis （except for fluoxetine group）were performed and validated. RESULTS Compared with model group， the cytolysis， structural damage and other pathological damages in three brain regions of rats were significantly alleviated in each drug group， while their body weight， sucrose preference rate， total moving distance and frequency into the center were all significantly higher or longer （P＜0.05）， and immobility time was significantly shorter （P＜0.05）. The results of non-targeted metabolomics showed that a total of 78 endogenous differential metabolites were identified， with 40， 35 and 24 in the PFC， NAc and VTA regions respectively， mainly involved in amino acid， lipid and sphingolipid metabolism. The results of metabolic pathway enrichment analysis showed that SGHWT affected the neural circuits of depressed rats by regulating sphingolipid metabolism， alanine， aspartic acid and glutamic acid metabolism， saturated fatty acid biosynthesis， among which alanine， aspartic acid and glutamic acid metabolism was predominantly involved. Validation experiments showed that SGHWT significantly increased the phosphorylation levels of protein kinase B （Akt） and mammalian target of rapamycin （mTOR）， and decreased the protein expression of N-methyl-D-aspartic acid receptor 1 （NMDAR1） in the NAc region of rats. CONCLUSIONS SGHWT significantly improves the depression-like behavior and attenuates pathological damage of PFC-NAc-VTA neural circuit of model rats， the mechanism of which is associated with inhibiting NMDAR1 expression and activating the Akt/mTOR signaling pathway.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Cardiovascular disease remains the leading cause of death in China, with its morbidity and mortality continue to rise. Ferroptosis, a unique form of iron-dependent cell death, plays a major role in many heart diseases. The classical mechanisms of ferroptosis include iron metabolism disorder, oxidative antioxidant imbalance and lipid peroxidation. Recent studies have found many additional mechanisms of ferroptosis, such as coenzyme Q10, ferritinophagy, lipid autophagy, mitochondrial metabolism disorder, and the regulation by nuclear factor erythroid 2-related factor 2 (NRF2). This article reviews recent advances in understanding the mechanisms of ferroptosis and its role in heart failure, myocardial ischemia/reperfusion injury, diabetic cardiomyopathy, myocardial toxicity of doxorubicin, septic cardiomyopathy, and arrhythmia. Furthermore, we discuss the potential of ferroptosis inhibitors/inducers as therapeutic targets for heart diseases, suggesting that ferroptosis may be an important intervention target of heart diseases.
Ferroptosis/physiology* ; Humans ; Heart Diseases/physiopathology* ; NF-E2-Related Factor 2/physiology* ; Animals ; Myocardial Reperfusion Injury/physiopathology* ; Lipid Peroxidation ; Heart Failure/physiopathology* ; Iron/metabolism* ; Diabetic Cardiomyopathies/physiopathology* ; Ubiquinone/analogs & derivatives*

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

Objective To establish a prediction model for the occurrence of non-occupational carbon monoxide poisoning events in Beijing, and to provide scientific basis and theoretical support for the prevention and warning of poisoning events. Methods Based on the monitoring data of non-occupational carbon monoxide poisoning events in Beijing from 2016 to 2024, the seasonal ARIMA model and seasonal index model were established to analyze the data and predict the occurrence of events. Results Between 2016 and 2024, a total of 436 cases of non-occupational carbon monoxide poisoning were reported in Beijing, showing a downward trend. The established SARIMA model and seasonal index model were SARIMA (1,0,0) (1,1,0) 12, Yt = (-0.0339t+5.8863) × St, and the average relative errors were 65.42% and 29.19%, respectively. In terms of months, the SARIMA model had better predictive performance during April and summer (June to August), while the seasonal index model was superior in other months. By combining the two models, the predicted number of events in 2025 was as follows: 3, 2, 2, 3, 1, 5, 2, 7, 1, 1, 1, and 2. Conclusion The seasonal index model has the best prediction effect on the non-occupational carbon monoxide poisoning events in Beijing throughout the year, and the number of summer events predicted by SARIMA model is closer to the actual values. The two models can be combined to predict the trend of non-occupational carbon monoxide poisoning, which provides a scientific basis for the prevention and control of carbon monoxide poisoning in the future.

Objective: To investigate the association of physical activity and screen time with overweight and obesity among children and adolescents with special needs in Tianjin, so as to provide scientific evidence for childhood obesity prevention and intervention measures in the population. Methods: From January 2022 to June 2024, 296 children and adolescents with intellectual disabilities and autism spectrum disorders aged 2-18 years were recruited from special education schools and institutions in Tianjin. Height and weight were measured, and a standardized questionnaire was used to assess physical activity and screen time. Binary Logistic regression analysis was carried out to investigate the association of physical activity and screen time with overweight and obesity. Results: The prevalence of overweight and obesity among children and adolescents with special needs in Tianjin were 17.2% and 21.6%, respectively, and the combined prevalence of overweight and obesity was 38.9%. The median of moderatetovigorous physical activity (MVPA) time was 0.20 h/d, and physical activity sufficiency rate was 7.8%. The median of screen time was 1.79 h/d, and the screen time compliance rate was 68.2%. The binary Logistic regression results showed that lower levels of MVPA time and increased screen time were associated with a higher risk of overweight and obesity among children and adolescents with special needs [OR(95%CI)=1.80(1.06-3.07), 2.40(1.42-4.07),P<0.05]. Conclusions Insufficient physical activity and excessive screen time are associated with an increased risk of overweight and obesity among children and adolescents with special needs. Therefore, comprehensive intervention measures should be implemented as early as possible to prevent and reduce the incidence of overweight and obesity in this population.