As a patented characteristic medicine of Yi ethnic minority， Pingxuan capsules have the effects of nourishing the liver and kidney， pacifying the liver， and subduing Yang. With the main indications of dizziness， headache， palpitations， tinnitus， insomnia， dreaminess， waist and knee soreness caused by liver-kidney deficiency and liver Yang upward disturbance， Pingxuan capsules are widely used in the treatment of posterior circulation ischemic vertigo， vestibular migraine， benign paroxysmal positional vertigo. However， the current knowledge is limited regarding the efficacy， syndrome differentiation， and safety of this medicine. On the basis of summarizing the experience of clinicians and the existing evidence， this study invites clinical experts of traditional Chinese and Western medicine， pharmaceutical experts， and methodological experts from relevant fields across China to conduct evidence-based evaluation of Pingxuan capsules. The evaluation follows the Specifications for the Development of Clinical Expert Consensus on Chinese Patent Medicines issued by the Standardization Office of the China Association of Chinese Medicine， and reaches 5 recommendations and 16 consensus suggestions. The consensus clarifies the clinical applications， efficacy， dose， course of treatment， combination of medicines， precautions， and contraindications of Pingxuan capsules in the treatment of vertigo and explains the safety of clinical application. This consensus is applicable to clinicians （traditional Chinese medicine， Western medicine， and integrated traditional Chinese and Western medicine） and pharmacists in tertiary hospitals， secondary hospitals， and community-level medical and health institutions across China， providing a reference for the rational use of Pingxuan capsules in the treatment of vertigo. It is hoped that the promotion of this consensus can facilitate the rational use of drugs in clinical practice， reduce the risk of drug use， and give full play to the advantages of Pingxuan capsules in the treatment of vertigo diseases. This consensus has been reviewed and published by the China Association of Chinese Medicine， with the number GS/CACM330-2023.

Objective: To investigate the mechanism of action of Prim-O-glucosylcimifugin (POG) to improve cholesterol metabolism in osteoarthritic (OA) chondrocytes based on the long noncoding RNA nuclear-enriched transcript 1 (lncRNA NEAT1)/microRNA-128-3p (miR-128-3p) pathway. Methods: For in vivo experiments, 60 mice were divided into the normal, sham operation, model, and POG groups using the random number table method, with 15 mice per group. The osteoarthritis mouse model was constructed using the modified Hulth method in the model and POG groups. Mice in the POG group were administered 30 mg/(kg·d)POG by gavage. The other groups were administered an equal amount of normal saline for 8 weeks. The cartilage tissue structure of mice in each group was observed using hematoxylin and eosin staining. Real-time PCR was used to detect changes in the lncRNA NEAT1 and miR-128-3p mRNA expression levels in the cartilage tissues of mice. Western blotting was used to detect the protein expressions of ATP-binding cassette transporter A1 (ABCA1), liver X receptor β (LXRβ), matrix metalloprotein-3 (MMP-3), and B-lymphoblastoma-2-associated X protein (Bax) in articular cartilage of mice. An enzyme-linked immunosorbent assay was used to measure the tumor necrosis factor-α (TNF-α) content in the synovial fluid of mice. A biochemical microplate assay was used to measure the total cholesterol level in the synovial fluid of mice. The in vitro experiments were divided into the negative control, interleukin-1β(IL-1β), IL-1β+ POG, IL-1β+ oe-lncRNA NEAT1, IL-1β+ oe-lncRNA NEAT1 + POG, IL-1β + miR-128-3p inhibition, and IL-1β+ miR-128-3p inhibition+ POG groups. An OA model was established by inducing chondrocytes with IL-1β for 24 h, and 90 mg/L of POG and miR-128-3p inhibitor(50 nmol/L) were administered for 48 h as an intervention. lncRNA NEAT1 expression in chondrocytes was detected using fluorescence in situ hybridization. A dual luciferase assay was used to detect the targeting relationship between lncRNA NEAT1 and miR-128-3p. Lentiviral plasmids overexpressing lncRNA NEAT1 were used to transfect mouse chondrocytes. Real-time PCR was used to detect the effect of lncRNA NEAT1 overexpression on the mRNA level of miR-128-3p in chondrocytes. Western blotting was used to detect ABCA1, LXRβ, MMP-3, and Bax protein expression in chondrocytes after lncRNA NEAT1 overexpression and miR-128-3p inhibition. Results: POG significantly reduced OA cartilage tissue damage. Compared with the model group, the lncRNA NEAT1 mRNA level decreased, whereas the miR-128-3p mRNA level increased in the cartilage tissue of the POG group (P<0.05). Compared with the model group, ABCA1 and LXRβ protein expression increased in the POG group, whereas MMP-3 and Bax protein expression decreased (P<0.05). The TNF-α levels decreased in the POG group compared to the model group (P<0.05). Compared with the model group, the total cholesterol level in the synovial fluid of the joint of mice in the POG group decreased (P<0.05). The mean fluorescence intensity of lncRNA NEAT1 in the IL-1β+ POG group decreased compared with the IL-1β group (P<0.05). The relative luciferase activity in the miR-128-3p mimics group bound to the lncRNA NEAT1-WT plasmid decreased compared with the miR-128-3p negative control group (P<0.05). The lncRNA NEAT1 mRNA levels decreased, whereas the miR-128-3p mRNA levels increased in the IL-1β+ oe-lncRNA NEAT1 + POG group compared with the IL-1β+ oe-lncRNA NEAT1 group (P<0.05). Compared with the IL-1β+ POG group, ABCA1 and LXRβ protein expression decreased, whereas MMP-3 and Bax protein expression increased (P<0.05). Conclusion POG mediates lncRNA NEAT1/miR-128-3p to improve cholesterol metabolism in OA chondrocytes.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

Objective: To explore the association between negative life events and smartphone addiction among middle school students, so as to provide theoretical support and practical guidance for prevention and intervention of smartphone addiction among middle school students. Methods: Using cluster sampling, 8 890 students were selected to survey from 27 junior high schools and 3 senior high schools in a district of Shenzhen in 2022 (baseline) and 2023 (followup). Data were collected through selfresigned questionnaires on basic information, the Smartphone Addiction Scale-Short Version, and the Adolescent Selfrating Life Events Checklist. Mixedeffects models were employed to analyze the association. Results: Compared to 2022, the punishment scores of middle school students in 2023 [1.00 (0.00, 6.00) and 1.00 (0.00, 6.00)] decreased (Z=4.27), while the scores of interpersonal stress, learning stress and adaptation [4.00(0.00, 8.00), 4.00(0.00, 8.00); 4.00(1.00, 8.00), 5.00(2.00, 9.00); 2.00 (0.00, 6.00), 3.00 (0.00, 7.00)] increased (Z=-3.04, -8.36, -6.80) (P<0.01). Mixedeffects models revealed a positive doseresponse relationship between negative life events and smartphone addiction (OR=1.08-1.17, P<0.01). Stepwise regression showed independent positive effects of interpersonal stress (OR=1.05), academic stress (OR=1.03), and adaptation stress (OR=1.11) on smartphone addiction (P<0.01). Subgroup analysis of nonaddicted students in 2022 confirmed persistent associations for academic stress (OR=1.03) and adaptation (OR=1.07) (P<0.01). Conclusion Negative life events exhibit a positive doseresponse relationship with smartphone addiction, particularly interpersonal stress, academic stress, and adaptationrelated events.

Objective: To explore the longitudinal association between only-child status and smartphone addiction among middle school students, so as to provide a basis for establishing family intervention measures for smartphone addiction in middle school students. Methods: In October 2022 and October 2023, a preliminary survey and follow-up were conducted among 8 759 middle and high school students from 30 schools in a district of Shenzhen. A self-designed questionnaire was used to determine whether the students were the only-child, and the Chinese Version of the Smartphone Addiction Scale-Short Version (C-SAS-SV) was utilized to assess the students smartphone addiction status. A multilevel mixed-effects model and subgroup analysis were applied to examine the association between only-child status and smartphone addiction among middle school students. Results: During 2022 to 2023, the prevalence of smartphone addiction in the cohort of middle school students increased from 24.1% to 25.2%. Compared with only-child, non-only child were more likely to be addicted to smartphones (adjusted model: OR =1.2, 95% CI =1.1-1.4) and also scored higher on smartphone addiction (adjusted model: β =0.9, 95% CI =0.2-1.5)( P <0.05). Subgroup analysis further revealed that compared to baseline, non-only child demonstrated an increased prevalence of smartphone addiction (adjusted model: OR = 1.2 , 95% CI =1.0-1.5) and higher addiction scores (adjusted model: β =0.8, 95% CI =0.2-1.5) after one year( P <0.05). Conclusions Non-only child face higher risk of smartphone addiction. Under the current population policy, it is crucial to address smartphone addiction among middle school students who is not only child.

Objective: To explore the potential causal association between adolescent compulsive behaviour and smartphone addiction based on longitudinal data, so as to provide reference for the establishment of adolescent smartphone addiction interventions. Methods: A preliminary survey and follow-up were conducted on 8 907 middle and high school students in a district of Shenzhen in 2022 and 2023, respectively. Compulsive behaviours were measured by using the Mental Health Inventory for Middle School Students-60 Items (MMHI-60), smartphone addiction was assessed by using the Smartphone Addiction Scale-Short Version ( SAS- SV), and the associations between compulsive behaviours and smartphone addiction were analysed by using multilevel mixed-effects models and subgroup analyses. Results: Smartphone addiction detection rates among middle school students were significantly associated with genders, father s education level, mother s education level, study load subgroups, and whether or not they were single-parent families, and there were statistical differences ( χ 2=17.21-175.34, P <0.05). Students with compulsive behaviours were 2.98 times more likely to develop smartphone addiction than those without compulsive behaviours ( OR=2.98, 95%CI=2.77-3.22, P <0.05). Subgroup analysis of middle school students without smartphone addiction in the first year found that compulsive behaviours significantly predicted smartphone addiction ( OR= 1.76 , 95%CI=1.54-2.01, P <0.05). Conclusion There is a potential causal association between obsessive-compulsive behaviours and smartphone addiction in middle school students, and obsessive-compulsive behaviours in middle school students could significantly predicted the occurrence of smartphone addiction.