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.

Under the background of climate change, the escalating air pollution and extreme weather events have been identified as risk factors for chronic respiratory diseases (CRD), causing serious public health burden worldwide. This review aims to summarize the effects of changed atmospheric environment caused by climate change on CRD. Results indicated an increased risk of CRD (mainly COPD, asthma) associated with environmental factors, such as air pollutants, adverse meteorological conditions, extreme temperatures, sandstorms, wildfire, and atmospheric allergens. Furthermore, this association can be modified by factors such as socioeconomic status, adaptability, individual behavior, medical services. Potential pathophysiological mechanisms linking climate change and increased risk of CRD involved pulmonary inflammation, immune disorders, oxidative stress. Notably, the elderly, children, impoverished groups and people in regions with limited adaptability are more sensitive to respiratory health risks caused by climate change. This review provides a reference for understanding risk factors of CRD in the context of climate change, and calls for the necessity of adaptive strategies. Further interdisciplinary research and global collaboration are needed in the future to enhance adaptability and address climate health inequality.
Climate Change ; Humans ; Air Pollution/adverse effects* ; Risk Factors ; Respiratory Tract Diseases/etiology* ; Chronic Disease ; Air Pollutants/adverse effects* ; Environmental Exposure/adverse effects*

Objective To investigate the clinical and radiological features of patients with different phenotypes of multiple system atrophy （MSA）. Methods A total of 400 patients with MSA who attended the outpatient service or were hospitalized in Department of Neurology，Chinese PLA General Hospital，were enrolled，among whom there were 294 patients with MSA-cerebellar type （MSA-C） and 106 patients with MSA-Parkinsonian type （MSA-P）. The t-test and the chi-square test were used to analyze the clinical manifestations，radiological features，and blood biochemical indicators of the two groups. Results As for clinical manifestations，there were significant differences in cerebellar symptoms，constipation，and Babinski sign between MSA-C patients and MSA-P patients （P<0.05）. As for radiological features，positron emission tomography/computed tomography （PET/CT） showed that MSA-P patients had a typical reduction in DAT uptake in the putamen and the caudate nucleus，while magnetic resonance imaging showed that compared with the MSA-C group，the MSA-P group had a significantly higher proportion of patients with putamen fissure sign or white matter demyelination； for MSA-C patients，PET/CT showed cerebellar hypometabolism，and magnetic resonance imaging showed the cross sign and high signal intensity in the pontine arm，as well as a significantly higher proportion of patients cerebellar and pontine atrophy than MSA-P patients （P<0.05）. As for laboratory markers，MSA-P patients had a significantly lower level of uric acid than MSA-C patients （P=0.029）. Conclusion Patients with different subtypes of MSA have specific clinical features，radiological features，and uric acid level，which has a certain significance in the accurate diagnosis of MSA.

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.

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 ; Interleukin-33/genetics* ; Interleukin-1 Receptor-Like 1 Protein/genetics* ; Optic Nerve Injuries/pathology* ; Retinal Ganglion Cells/pathology* ; Astrocytes/pathology* ; Mice ; Mice, Knockout ; Mice, Inbred C57BL ; Neuroprotection/physiology*

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 ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

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 ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

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 ; Malocclusion/diagnostic imaging* ; Child ; Consensus

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 ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic