1.Analysis of Blood-absorbed Components and Their Metabolic Differences of Xiebaisan in Normal and Chronic Bronchitis Mice Based on UPLC-Q-Exactive Orbitrap MS
Peng PENG ; Jiaxin LI ; Xinyue YANG ; Fangle LIU ; Chenchen ZHU ; Chaozhan LIN ; Yufeng YAO
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(1):219-227
ObjectiveThis study aims to systematically analyze the blood-absorbed components and metabolic profiles of Xiebaisan(XBS) in normal and chronic bronchitis (CB) mice using ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry(UPLC-Q-Exactive Orbitrap MS), while comparing differences between the two states. MethodsThirty female BABL/c mice were randomly divided into the normal group, the normal drug administration group, the CB group, the CB drug administration group and the dexamethasone group, with 6 mice in each group. The CB mouse model was established by inducing with ovalbumin (OVA). The mice in the normal drug administration group and the CB drug administration group started to be gavaged with XBS(13.2 g·kg-1) from the 21st day, and the dexamethasone group mice were simultaneously gavaged with dexamethasone (0.5 mg·kg-1) until the end of the 35th day of the experiment. Subsequently, serum samples were collected and evaluated for their efficacy, based on the pharmacological evaluation indicators, to determine the efficacy of XBS in treating CB. Then the UPLC-Q-Exactive Orbitrap MS was employed to identify and analyze the chemical constituents, blood-absorbed components, and metabolites of XBS. Chemometric analysis was conducted to reveal metabolic profile differences under "dual states". Concurrently, Real-time PCR technology was utilized to detect the expression levels of key liver metabolic enzymes CYP2E1, CYP3A1, UGT1A1, and UGT1A6. ResultsA total of 28 prototype components and 158 metabolites (including 48 phase Ⅰ metabolites and 110 phase Ⅱ metabolites) of XBS were unambiguously identified in the serum of normal mice. Additionally, a comprehensive characterization was performed on a total of 32 prototype components and 178 metabolites (including 50 phase Ⅰ metabolites and 128 phase Ⅱ metabolites) of XBS in the serum of CB mice. Among them, 27 prototype components were detected in both states, including 12 flavonoids, 2 alkaloids, 3 triterpenes, 4 organic acids, 3 amides, 1 stilbene and 2 other compounds. The chemometrics analysis revealed no significant difference in the prototype components and metabolites of XBS between normal and CB mice; however, there was a significant increase in the in-vivo exposure of XBS in CB mice. Compared to normal mice, the levels of phase Ⅰ metabolites such as oxidation, reduction and methylation of blood components of XBS as well as phase Ⅱ metabolites of glucuronidation showed significant changes in CB mice. Real-time PCR further confirmed that these alterations were attributed to the upregulation of CYP2E1 (P<0.05), CYP3A1 (P>0.05), UGT1A1 (P<0.01) and UGT1A6 (P<0.01) enzymes expression in the liver of CB mice. ConclusionThis study elucidated the disparities in the levels of the blood-absorbed components and metabolic profiles of XBS in normal and CB mice, especially in oxidation, reduction, methylation in phase Ⅰ metabolism and glucoaldehyde acidification in phase Ⅱ metabolism. And there are related to the differences in the expression levels of phase Ⅰ and phase Ⅱ metabolic enzymes CYP2E1, CYP3A1, UGT1A1 and UGT1A6 in the liver.
2.Constructing an actor-network theory for integrating sports activity into rehabilitation based on Rehabilitation in Health Service System
Yaning CHENG ; Di CHEN ; Chenchen TANG ; Yifan TIAN ; Lixu LIU ; Yingxin ZHANG ; Yizheng WANG ; Yaling HUANG
Chinese Journal of Rehabilitation Theory and Practice 2026;32(5):508-521
ObjectiveTo construct an actor-network for integrating physical activity into rehabilitation services based on the World Health Organization Rehabilitation in Health Service System framework and actor-network theory (ANT). MethodsContent analysis was employed using the six building blocks of health service systems as the theoretical framework. Actors related to rehabilitation services were extracted and categorized into a rehabilitation actor pool, while a physical activity actor pool was formed based on four major physical activity scenarios. Actors from both pools were integrated, deduplicated and classified to form a final list of integrated actors. Using ANT, the construction process of the actor network integrating physical activity into rehabilitation was analyzed through the four stages of translation: problematization, interessment, enrollment and mobilization. ResultsA dynamic integration network was constructed, comprising human actors (patients, rehabilitation professionals, researchers, sports coaches, government departments, medical institutions, community organizations and industry media, etc.) and non-human actors (assistive devices, sports infrastructure, smart equipment, information systems, online exercise guidance systems, laws and regulations, strategic documents, and exercise prescriptions, etc.). The study identified maximizing rehabilitation outcomes as the mandatory passage point and elaborated on the critical role of government departments as focal actors in coordinating various stakeholders. ConclusionThe integration of physical activity into rehabilitation services is a dynamic network constructed by diverse actors through a process of translation. ANT provides an operational theoretical framework for cross-departmental governance of rehabilitation policies in China, promotes the spatial expansion of the rehabilitation field, and drives its transformation toward a networked and ecological system. The government needs to play a leading role in facilitating role reconstruction and synergy among heterogeneous actors in both the sports and rehabilitation sectors through mechanism design, to create a bidirectional empowerment mechanism that fosters mutual progress and ensures the sustainable development of integrated services.
3.Treatment of Diabetic Kidney Disease with Active Ingredients of Astragali Radix Based on Inflammation: A Review
Xinze YUAN ; Chenchen LIU ; Shengnan WANG ; Xinyu SUN
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(2):295-302
Diabetic kidney disease (DKD) is one of the common microvascular complications of diabetes mellitus (DM) and a primary cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD). Inflammation is currently a hot topic in exploring the pathogenesis of DKD. Macrophages, T cells, interleukins, tumor necrosis factor, NOD-like receptor protein 3 (NLRP3) inflammasome, Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway, and nuclear factor-kappa B (NF-κB)-related signaling pathway all play a role in regulating the inflammation of DKD and accelerating its progression. Astragali Radix, a Chinese herbal medicine, is widely used in the treatment of DKD and possesses strong anti-inflammatory effects. Studies have revealed that active ingredients of Astragali Radix, including polysaccharides, astragaloside Ⅳ, total flavonoids, calycosin, and quercetin, can regulate multiple signaling pathways to ameliorate the microinflammatory state and alleviate kidney damage, thereby slowing down the progression of DKD. This article systematically reviews the factors influencing the inflammation in DKD and analyzes recent research findings and mechanisms concerning active ingredients of Astragali Radix in the management of DKD inflammation, aiming to offer novel insights and directions for the prevention, treatment, and research of DKD.
4.Impact of GA/ALB on the prognosis of heart failure in patients with coronary heart disease
Chenchen LIU ; Haoran WANG ; Huifang XING ; Hongli LI ; Zhihong GUO ; Lele ZHANG ; Dong YANG ; Hongping LIANG
International Journal of Laboratory Medicine 2025;46(19):2311-2318
Objective To explore the potential clinical value of the ratio of glycated albumin to albumin(GA/ALB)in the occurrence of heart failure(HF)among patients with coronary atherosclerotic heart disease(CHD).Methods A total of 337 CHD patients admitted to the Department of Cardiology in Shanxi Provincial People's Hospital from July 2023 to June 2024 were selected in this study.CHD patients were divided into HF group and non-HF group based on whether they progressed to HF.The clinical data and laboratory parame-ters of the two groups were compared.Restricted cubic spline curve was used to analyze the relationship be-tween GA/ALB levels and the risk of HF in CHD patients.Receiver operating characteristic curve was applied to evaluate the diagnostic efficacy of GA/ALB,GA,platelet to lymphocyte ratio(PLR),and monocyte to lym-phocyte ratio(MLR)in CHD patients with the occurrence of HF.Logistic regression was used to explore the relationship between serum GA/ALB levels and the risk of CHD patients occurrence of HF,and to analyze the degree of influence and stability of subgroup variables on results.Results There were statistically significant differences in GA/ALB,GA,PLR,MLR,and other indicators between the HF group and the non-HF group in CHD patients(P<0.05).A non-linear relationship was observed between GA/ALB levels and the risk of HF in CHD patients.When the value of GA/ALB multiplied by 10 was less than 5.751,the risk of HF in CHD pa-tients increased with the increase of GA/ALB levels(P<0.001).GA/ALB was an effective predictor for HF occurrence in CHD patients.Multivariable Logistic regression model showed that GA/ALB was an independ-ent risk factor for CHD patients with occurrence of HF.Subgroup analysis also confirmed the stability of GA/ALB in predicting the occurrence of HF in CHD patients.Conclusion GA/ALB is an independent risk factor for the occurrence of HF in CHD patients,and monitoring GA/ALB levels provides predictive value for the oc-currence of HF in these patients.
5.A deep learning model for the diagnosis of first-episode schizophrenia and grading of EEG abnormalities using EEG signals
Lili SHUI ; Chenchen LIU ; Yumin LI
Sichuan Mental Health 2025;38(4):308-314
BackgroundSchizophrenia is a highly heterogeneous disease with different clinical subtypes. Artificial intelligence technology represented by deep learning models has provided considerable benefits for the electroencephalogram (EEG)-based schizophrenia diagnosis, treatment and research, however, to date little research has been conducted regarding any of these benefits among Chinese schizophrenic patients. ObjectiveTo investigate the application of deep learning techniques utilizing EEG parameters for the diagnosis of first-episode schizophrenia and grading of EEG abnormalities in patients, with the aim of contributing to improved clinical diagnosis and treatment strategies for the disorder. MethodsFrom January 2020 to January 2023, a total of 130 patients with first-episode schizophrenia who met the diagnostic criteria of International Classification of Diseases, tenth edition (ICD-10), and attended at the Third People's Hospital of Fuyang, along with 150 health checkup examinees, were enrolled. All of them underwent EEG examination. An optimized long short-term memory (LSTM) deep learning model was developed utilizing EEG signals. Ten-fold cross-validation method was employed to evaluate the model's performance. The dataset was then split into two components: a training set (90%) for LSTM model development and a test set (10%) for validation. The accuracy, recall rate, precision, F1-score, schizophrenia diagnosis and EEG abnormality grading were used as evaluation indicators, and the results of the proposed model were compared to the assessments made by experienced psychiatrists. ResultsFor schizophrenia diagnosis, the modeling group achieved the following performance metrics: precision (94.40±3.03)%, recall rate (94.30±3.23)%, accuracy (94.60±2.22)%, and F1-score (94.20±2.20)%. In the validation group, the corresponding metrics were precision (90.90±2.85)%, recall rate (92.20±1.14)%, accuracy (92.20±1.69)%, and F1-score (91.50±1.78)%. Statistical analysis revealed no significant differences between the LSTM diagnostic model and the experienced psychiatrists in terms of precision, recall rate, accuracy, and F1-score for schizophrenia diagnosis (χ2=1.500, 0.750, 2.722, 1.056, P>0.05). The modeling group demonstrated an accuracy rate of (91.71±1.73)% in grading EEG abnormalities. For Grade 1 abnormalities, the modeling group reported a precision of (96.40±2.39)%, a recall rate of (94.77±1.40)%, and an F1-score of (95.55±1.14)%. In the case of Grade 2 abnormalities, the precision was (85.89±2.04)%, the recall rate was (88.10±6.18)%, and the F1-score was (87.06±3.12)%. For the more severe Grade 3 abnormalities, the modeling group's precision was (79.61±7.33)%, the recall rate was (81.79±9.87)%, and the F1-score was (80.41±6.79)%. Additionally, the validation group exhibited an accuracy rate of (85.61±6.16)%. The precision, recall rate, and F1-score for Grade 1 abnormalities were (91.43±6.25)%, (92.64±9.65)% and (91.56±4.83)%, respectively. For Grade 2 abnormalities, these metrics were (71.17±19.02)%, (77.64±17.24)% and (71.88±11.33)%. In the case of Grade 3 abnormalities, the precision was (90.00±21.08)%, the recall rate was (80.00±25.82)%, and the F1-score was (81.67±19.95)%. There was no significant difference in the accuracy, recall, accuracy and F1 value between LSTM model and senior doctors in evaluating the abnormal degree of EEG in schizophrenia (χ2=0.098, 0.036, 0.020, 0.336, P>0.05). The LSTM model takes less time to diagnose schizophrenia and EEG abnormalities than senior doctors, and the differences were statistically significant (t=57.147, 43.104, P<0.01). ConclusionThe study utilizes an EEG-based LSTM deep learning model for diagnosing first-episode schizophrenia and grading EEG abnormalities, and the model not only matches the performance of experienced psychiatrists but also significantly reduces the time required for diagnosis.
6.The IL-33/ST2 Axis Protects Retinal Ganglion Cells by Modulating the Astrocyte Response After Optic Nerve Injury.
Zhigang QIAN ; Mengya JIAO ; Na ZHANG ; Xuhuan TANG ; Shiwang LIU ; Feng ZHANG ; Chenchen WANG ; Fang ZHENG
Neuroscience Bulletin 2025;41(1):61-76
IL-33 and its receptor ST2 play crucial roles in tissue repair and homeostasis. However, their involvement in optic neuropathy due to trauma and glaucoma remains unclear. Here, we report that IL-33 and ST2 were highly expressed in the mouse optic nerve and retina. Deletion of IL-33 or ST2 exacerbated retinal ganglion cell (RGC) loss, retinal thinning, and nerve fiber degeneration following optic nerve (ON) injury. This heightened retinal neurodegeneration correlated with increased neurotoxic astrocytes in Il33-/- mice. In vitro, rIL-33 mitigated the neurotoxic astrocyte phenotype and reduced the expression of pro-inflammatory factors, thereby alleviating the RGC death induced by neurotoxic astrocyte-conditioned medium in retinal explants. Exogenous IL-33 treatment improved RGC survival in Il33-/- and WT mice after ON injury, but not in ST2-/- mice. Our findings highlight the role of the IL-33/ST2 axis in modulating reactive astrocyte function and providing neuroprotection for RGCs following ON injury.
Animals
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Interleukin-33/genetics*
;
Interleukin-1 Receptor-Like 1 Protein/genetics*
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Optic Nerve Injuries/pathology*
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Retinal Ganglion Cells/pathology*
;
Astrocytes/pathology*
;
Mice
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Mice, Knockout
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Mice, Inbred C57BL
;
Neuroprotection/physiology*
7.Expert consensus on orthodontic treatment of protrusive facial deformities.
Jie PAN ; Yun LU ; Anqi LIU ; Xuedong WANG ; Yu WANG ; Shiqiang GONG ; Bing FANG ; Hong HE ; Yuxing BAI ; Lin WANG ; Zuolin JIN ; Weiran LI ; Lili CHEN ; Min HU ; Jinlin SONG ; Yang CAO ; Jun WANG ; Jin FANG ; Jiejun SHI ; Yuxia HOU ; Xudong WANG ; Jing MAO ; Chenchen ZHOU ; Yan LIU ; Yuehua LIU
International Journal of Oral Science 2025;17(1):5-5
Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans
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Orthodontics, Corrective/methods*
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Consensus
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Malocclusion/therapy*
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Patient Care Planning
;
Cephalometry
8.Expert consensus on the prevention and treatment of enamel demineralization in orthodontic treatment.
Lunguo XIA ; Chenchen ZHOU ; Peng MEI ; Zuolin JIN ; Hong HE ; Lin WANG ; Yuxing BAI ; Lili CHEN ; Weiran LI ; Jun WANG ; Min HU ; Jinlin SONG ; Yang CAO ; Yuehua LIU ; Benxiang HOU ; Xi WEI ; Lina NIU ; Haixia LU ; Wensheng MA ; Peijun WANG ; Guirong ZHANG ; Jie GUO ; Zhihua LI ; Haiyan LU ; Liling REN ; Linyu XU ; Xiuping WU ; Yanqin LU ; Jiangtian HU ; Lin YUE ; Xu ZHANG ; Bing FANG
International Journal of Oral Science 2025;17(1):13-13
Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans
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Consensus
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Dental Caries/etiology*
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Dental Enamel/pathology*
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Tooth Demineralization/etiology*
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Tooth Remineralization
9.Expert consensus on imaging diagnosis and analysis of early correction of childhood malocclusion.
Zitong LIN ; Chenchen ZHOU ; Ziyang HU ; Zuyan ZHANG ; Yong CHENG ; Bing FANG ; Hong HE ; Hu WANG ; Gang LI ; Jun GUO ; Weihua GUO ; Xiaobing LI ; Guangning ZHENG ; Zhimin LI ; Donglin ZENG ; Yan LIU ; Yuehua LIU ; Min HU ; Lunguo XIA ; Jihong ZHAO ; Yaling SONG ; Huang LI ; Jun JI ; Jinlin SONG ; Lili CHEN ; Tiemei WANG
International Journal of Oral Science 2025;17(1):21-21
Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans
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Malocclusion/diagnostic imaging*
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Child
;
Consensus
10.Expert consensus on early orthodontic treatment of class III malocclusion.
Xin ZHOU ; Si CHEN ; Chenchen ZHOU ; Zuolin JIN ; Hong HE ; Yuxing BAI ; Weiran LI ; Jun WANG ; Min HU ; Yang CAO ; Yuehua LIU ; Bin YAN ; Jiejun SHI ; Jie GUO ; Zhihua LI ; Wensheng MA ; Yi LIU ; Huang LI ; Yanqin LU ; Liling REN ; Rui ZOU ; Linyu XU ; Jiangtian HU ; Xiuping WU ; Shuxia CUI ; Lulu XU ; Xudong WANG ; Songsong ZHU ; Li HU ; Qingming TANG ; Jinlin SONG ; Bing FANG ; Lili CHEN
International Journal of Oral Science 2025;17(1):20-20
The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans
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Malocclusion, Angle Class III/classification*
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Orthodontics, Corrective/methods*
;
Consensus
;
Child

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