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 21^st day， and the dexamethasone group mice were simultaneously gavaged with dexamethasone （0.5 mg·kg^-1） until the end of the 35^th 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.

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.

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.

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.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Hypoxia-related diseases,such as altitude sickness,acute lung injury,and heart failure,have emerged as significant public health challenges worldwide and are strongly associated with increased mortality risks.These conditions tend to cause functional impairment and structural alterations in multiple organs,primarily due to inadequate oxygen supply or the inability of tissues to utilize oxygen effectively.To elucidate the pathophysiological mechanisms underlying hypoxia-associated diseases and to explore potential therapeutic strategies,researchers have employed animal models to conduct extensive mechanistic studies and drug development trials.In this review,we provide a comprehensive overview of the methods used to construct animal models for various hypoxia-related diseases.We made a thorough evaluation of the strengths,weaknesses,limitations,and applicability of each approach.In particular,we focus on modeling strategies for key pathologies such as altitude sickness,acute lung injury,pulmonary hypertension,and heart failure,discussing their respective advantages and restrains.Furthermore,we examined the potential application of gene editing technologies in optimizing animal models,especially its role in enhancing the accuracy and reproducibility of the models.The integration of these advanced technologies holds great promise for developing animal models with improved specificity and simulation of key features of diseases,which will serve as a solid foundation for basic research,drug screening,and preclinical trials concerning hypoxia-related diseases.Herein,we present a systematic summary and future outlook of animal models for hypoxia-related diseases,ultimately providing theoretical support for developing clinical treatment strategies and improving patient outcomes.

Objective:To explore the effect of scalp electroacupuncture (EA) on central pain sensitization in rats with knee osteoarthritis (KOA).Methods:Thirty-two 8-week-old female Sprague-Dawley rats were randomly divided into a blank control group, a model group, an electroacupuncture (EA) group and a sham EA group, each of 8. All of the rats except those in the control group had KOA induced through intra-articular monosodium iodoacetate injections in the right knee. Two weeks later the EA group rats began receiving daily head EA sessions 6 days/week for 2 weeks. The sham EA group received identical but non-therapeutic stimulation. The blank control and model groups received no EA intervention. Before the modelling and 3, 7, 14, 21 and 28 days later, all of the rats completed bipedal balance pain tests and mechanical allodynia evaluations. After the testing on day 28, all of the rats were euthanized for molecular analyses. Western blotting and immunohistochemistry were performed to examine protein expression of brain-derived neurotrophic factor (BDNF), tropomyosin receptor kinase B (TrkB), and cannabinoid receptor type 1 (CB1R) in both the periaqueductal gray (PAG) matter and spinal dorsal horns (SDHs). Serum levels of substance P (SP) and 5-hydroxytryptamine (5-HT) were also quantified using enzyme-linked immunosorbent assays.Results:Three days after successful modeling, the average weight-bearing capacity of the right hind limb in the model, sham EA and EA groups was significantly lower than that of the blank controls. It reached its lowest level on the 14th day after modeling. Concurrently, the pain responses in those three groups were significantly higher than among the controls, also peaking on the 14th day after modeling. After two weeks of electroacupuncture, the electroacupuncture group showed significant improvement in both right hind limb weight-bearing capacity and pain response compared to the model group. Meanwhile, the levels of BDNF and TrkB protein in the periaqueductal gray matter were significantly higher in the model group than among the blank controls, while the electroacupuncture group exhibited significantly reduced expression of BDNF and TrkB proteins compared to the model group, along with significantly increased CB1R protein expression. The model group showed significantly elevated expression of both BDNF and TrkB proteins in the spinal dorsal horn compared to the blank control group, while there were significant differences between the EA and model groups in the expression of BDNF, TrkB and CB1R proteins. Immunohistochemical analysis on day 28 revealed that the EA group had significantly fewer BDNF- and TrkB-positive cells in the PAG compared to the model group, with significantly more CB1R-positive cells. In the SDH, the model group exhibited significantly increased numbers of BDNF- and TrkB-positive cells compared to the blank control group, whereas significant differences were found between the EA and blank control groups in the numbers of BDNF-, TrkB- and CB1R-positive cells. Serum analysis on day 28 demonstrated that substance P and 5-hydroxytryptamine levels in the model, sham EA and EA groups were significantly higher than in the blank control group, on average. However, no significant differences were observed in serum SP and 5-HT levels between the EA and model groups.Conclusions:Scalp EA significantly alleviates central pain sensitization in KOA, at least in rats, potentially by suppressing BDNF and TrkB expression while upregulating CB1R expression in the PAG matter and the SDH.

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*