BACKGROUND:Scoliosis is a three-dimensional deformity characterized by lateral bending and rotation of the spine.Its onset age covers the entire life cycle,becoming an important health issue that threatens people's health.Artificial intelligence continues to advance with the development of computer science.At present,artificial intelligence has great potential for application in medical diagnosis and treatment,and is gradually being applied in screening and diagnosis of scoliosis.OBJECTIVE:To comprehensively review the application of artificial intelligence in screening and diagnosis of scoliosis,elaborate on the progress of its application in recent years from multiple aspects,and look forward to its innovative points,providing reference for the future trend of intelligence.METHODS:Search covered databases such as PubMed,IEEE Xplore,CNKI,and WanFang,using Chinese and English search terms such as"scoliosis,artificial intelligence,machine learning,screen,diagnosis."Boolean logic was used to optimize the search strategy.Articles directly related to the application of artificial intelligence in screening and diagnosis of scoliosis were included,and articles with weak correlation,outdated experimental design,or poor credibility were excluded.Finally,83 articles were included for analysis.RESULTS AND CONCLUSION:(1)Artificial intelligence has shown unique application value and development prospects in multiple fields such as early screening of scoliosis,chest X-ray screening,smartphone screening,X-ray diagnosis,CT and MRI diagnosis,and reconstruction of three-dimensional spinal images.(2)The application of artificial intelligence in the screening and diagnosis of scoliosis has improved efficiency,reduced misdiagnosis rates,and alleviated the burden on medical staff,facilitating early detection and diagnosis of scoliosis and safeguarding spinal health.

ObjectiveTo explore the effect of cluster scalp acupuncture combined with Taijiquan training on depressive symptom, motor function, activities of daily living, serum markers, as well as brain functional connectivity (FC) and network topological properties in patients with post-stroke depression (PSD). MethodsA total of 40 PSD patients in the Second Affiliated Hospital of Heilongjiang University of Chinese Medicine from September, 2022 to September, 2023 were enrolled and randomly divided into control group (n = 20) and experimental group (n = 20). The control group received cluster scalp acupuncture alone, while the experimental group underwent Taijiquan training in addition, for four weeks. They were assessed with Hamilton Depression Scale-17 (HAMD-17), Fugl-Meyer Assessment (FMA) and Barthel Index (BI) before and after treatment, while the serum levels of dopamine (DA), 5-hydroxytryptamine (5-HT), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were detected with enzyme-linked immunosorbent assay. Resting-state functional magnetic resonance imaging (rs-fMRI) was applied to assess brain FC, as well as the global efficiency (Eg) and small-world property (σ) of brain networks. ResultsThe scores of HAMD-17, FMA and BI improved in both groups (t > 2.922, P < 0.01) after treatment, and improved more in the experimental group than in the control group (t > 2.517, P < 0.05). The serum levels of DA and 5-HT increased in both groups (t > 2.637, P < 0.05), and increased more in the experimental group (t > 2.192, P < 0.05). The serum levels of IL-6 and TNF-α decreased in the experimental group after treatment (t > 4.059, P < 0.001), and they were less than those in the control group (t > 2.154, P < 0.05). FC between left middle frontal gyrus and right anterior cingulate gyrus, as well as between left hippocampus and right precuneus were higher in the experimental group than in the control group after treatment (t > 3.867, P < 0.001), while Eg and σ increased in both groups (t > 2.828, P < 0.05), and they were higher in the experimental group (t > 2.675, P < 0.05). ConclusionCombination of Taijiquan training is more effective on depressive symptoms, motor function and activities of daily living in PSD patients, which may be related to up-regulation of serum DA and 5-HT, reduction of inflammatory factors, enhancement of prefrontal-limbic system functional connectivity and optimization of brain network topological properties.

BACKGROUND:Scoliosis is a three-dimensional deformity characterized by lateral bending and rotation of the spine.Its onset age covers the entire life cycle,becoming an important health issue that threatens people's health.Artificial intelligence continues to advance with the development of computer science.At present,artificial intelligence has great potential for application in medical diagnosis and treatment,and is gradually being applied in screening and diagnosis of scoliosis.OBJECTIVE:To comprehensively review the application of artificial intelligence in screening and diagnosis of scoliosis,elaborate on the progress of its application in recent years from multiple aspects,and look forward to its innovative points,providing reference for the future trend of intelligence.METHODS:Search covered databases such as PubMed,IEEE Xplore,CNKI,and WanFang,using Chinese and English search terms such as"scoliosis,artificial intelligence,machine learning,screen,diagnosis."Boolean logic was used to optimize the search strategy.Articles directly related to the application of artificial intelligence in screening and diagnosis of scoliosis were included,and articles with weak correlation,outdated experimental design,or poor credibility were excluded.Finally,83 articles were included for analysis.RESULTS AND CONCLUSION:(1)Artificial intelligence has shown unique application value and development prospects in multiple fields such as early screening of scoliosis,chest X-ray screening,smartphone screening,X-ray diagnosis,CT and MRI diagnosis,and reconstruction of three-dimensional spinal images.(2)The application of artificial intelligence in the screening and diagnosis of scoliosis has improved efficiency,reduced misdiagnosis rates,and alleviated the burden on medical staff,facilitating early detection and diagnosis of scoliosis and safeguarding spinal health.

BACKGROUND:Cervical disc herniation can cause pain in the neck and shoulder area,as well as radiating pain in the upper limbs.The incidence rate is increasing year by year and tends to affect younger individuals.Fully understanding the biomechanical characteristics of the cervical spine in adolescents is of great significance for preventing and delaying the onset of cervical disc herniation in this age group. OBJECTIVE:To reconstruct cervical spine models for both healthy adolescents and adolescent patients with cervical disc herniation utilizing finite element analysis techniques,to analyze the motion range of the C1-T1 cervical vertebrae as well as the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and the cartilage of the small joints. METHODS:A normal adolescent's cervical spine and an adolescent patient with cervical disc herniation were selected in this study.The continuous scan cervical spine CT raw image data were imported into Mimics 21.0 in DICOM format.The C1-T1 vertebrae were reconstructed separately.Subsequently,the established models were imported into the 3-Matic software for disc reconstruction.The perfected models were then imported into Hypermesh software for meshing of the vertebrae,nucleus pulposus,annulus fibrosus,and ligaments,creating valid geometric models.After assigning material properties,the final models were imported into ABAQUS software to observe the joint motion range of the C1-C7 cervical vertebrae segments under different conditions,and to analyze the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and small joint cartilage of each cervical spine segment. RESULTS AND CONCLUSION:(1)In six different conditions,the joint motion range of the C1 vertebra in the cervical spine models of both normal adolescent and adolescent patient with cervical disc herniation was higher than that of the other vertebrae.Additionally,the joint motion range of each cervical spine segment in normal adolescent was greater than that in adolescent patient with cervical disc herniation.(2)In the cervical spine model of normal adolescent,the maximum stress values in the annulus fibrosus and nucleus pulposus were found on the left side during C2-3 flexion conditions(0.43 MPa and 0.17 MPa,respectively).In the cervical spine model of adolescent patient with cervical disc herniation,the maximum stress values were found on the left side during C7-T1 flexion conditions(0.54 MPa and 0.18 MPa,respectively).(3)In the cervical spine model of normal adolescent,the maximum stress value on the endplate was found on the left side of the upper endplate of C3 during flexion conditions(1.46 MPa).In the model of adolescent patient with cervical disc herniation,the maximum stress value on the endplate was found on the left side of the lower endplate of C7 during flexion conditions(1.32 MPa).(4)In the cervical spine model of normal adolescent,the maximum stress value in the small joint cartilage was found in the C2-3 left rotation conditions(0.98 MPa).In adolescent patient with cervical disc herniation,the stress in the small joint cartilage significantly increased under different conditions,especially in C1-2,with the maximum stress found during left flexion(3.50 MPa).(5)It is concluded that compared to normal adolescent,adolescent patient with cervical disc herniation exhibits altered cervical curvature and a decrease in overall joint motion range in the cervical spine.In adolescent with cervical disc herniation,there is a significant increase in stress on the annulus fibrosus,nucleus pulposus,and endplates in the C7-T1 segment.The stress on the left articular cartilage of the C1-2 is notable.Abnormal cervical curvature may be the primary factor causing these stress changes.

Objective To understand the epidemiological characteristics of road traffic accident injuries in Beijing can provide a theoretical basis for improving the pre-hospital emergency service capabilities and levels,and increasing patient survival rates while reducing disability,mortality rates.Methods A retrospective analysis was conducted on the medical records of 9207 patients who made pre-hospital emergency calls due to road traffic accident injuries at the Beijing Emergency Medical Center in 2023 to understand the patients' age,gender,injury time,injury location,injury degree and other characteristics.Results Traumatic diseases ranked first in the classification of emergency medical conditions in Beijing.Among them,road traffic accidents account for 37％.The ratio of male to female patients was 1.32∶1.The largest number of patients were aged 31-40,accounting for nearly 25％.The proportion of underage patients and those aged 71 and above was 12.16％.The differences in gender and age distribution were statistically significant,while the differences in gender distribution among different age groups were not statistically significant.Road traffic accident injuries occured most frequently in September and least in January.There were more cases in summer and autumn,and fewer in winter and spring.The most common injury sites in road traffic accidents were limbs/skin and head and neck,accounting for 81.06％.The patients with moderate severity of injuries were the most numerous,accounting for 85.29％.Conclusion To avoid road traffic accidents,prevention should be the priority.It is necessary to strengthen the joint governance of multiple departments and minimize the occurrence of road traffic accident from the source.Pre-hospital emergency care must focus on key populations and key seasons,strengthen professional skills training and resource allocation,ensure efficient and smooth connection between pre-hospital and in-hospital care.Popularize and publicize the importance of self-rescue and mutual rescue,promote first aid knowledge and skills training for the public,and create a social atmosphere where"rescue is right beside us".

Objective:To establish a fluorescent quantitative RT-PCR assay based on N_sgRNA of SARS-CoV-2 and preliminarily apply it on real samples.Methods:Recombinant plasmid, specific primers and probes of N_sgRNA were designed and synthesized based on Wuhan-Hu-1/2019_MN908947 and synthesis mechanism of subgenomic RNA (sgRNA). Using recombinant plasmid as amplification templates, the optimal reaction conditions and reaction system were screened according to the Ct value, fluorescence intensity, and shape of amplification curve and was evaluated for sensitivity, reproducibility, and specificity. Meanwhile, the possibility of practical application of the method was explored by testing 172 clinical samples and 256 municipal wastewater samples. Results:A qRT-PCR assay for N_sgRNA in SARS-CoV-2 was initially established. The detection limit of the assay was 20 copies/mL, and the variation coefficients of in-batch (0.002%~0.767%) and batch to batch repetition (0.016%~0.752%) were less than 1%. Only N_sgRNA recombinant plasmid was detected in the specificity assay. So the method is more highly sensitive, specific and reproducible. The RatiosgRNA/ gRNA of clinical samples HK.3, EG.5.1, JN.1 and their sub-lineages and their corresponding urban sewage samples in epidemic period were significantly different ( P<0.05). There is a strong correlation between the median of RatiosgRNA/ gRNA in clinical samples and sewage samples in the same period (correlation coefficient r=1.000, P=0.010). Conclusions:In this study, a qRT-PCR method for detecting N_sgRNA of SARS-CoV-2 was established and the method has the characteristics of higher sensitivity, stronger specificity and better repeatability, and it can be used to detect SARS-CoV-2 infectivity.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Traditionally, type 2 diabetes was regarded as a chronic, progressive metabolic disorder, with its pathogenesis considered a continuous and irreversible process. However, with advancements in diabetes research, treatment options have become more diverse, offering the potential for " diabetes remission". Achieving remission holds substantial significance for patients, their families, and society as a whole. This article provides an overview of the latest research progress on the remission of type 2 diabetes mellitus.

Objective To identify the key influencing factors and role mechanisms of large-scale medical equip-ment allocation decision-making in public hospitals,and to provide a reference basis for optimizing resource alloca-tion strategies.Methods Through searching the literature related to large-scale medical equipment decision-making in public hospitals and combing the policies,the system of decision-making influencing factors was initially screened.The Delphi method and decision-making trial and evaluation laboratory method were used to obtain the key influencing factors of equipment allocation decision-making and to determine the interaction effects among the factors.Results A total of seven cause factors and nine effect factors were screened.Among them,cost-benefit analysis,equipment technical performance,and evaluation of similar equipment were the top three key drivers;leadership emphasis,equipment market price,and equipment supporting facilities were the top three key con-straints.Conclusion Priority be given to strengthening the management of driving factors,mainly by conducting a full-cycle assessment of cost-effectiveness,paying attention to the clinical value output of equipment technical performance,and monitoring regionally similar equipment.A dynamic response mechanism for constraints should be established,mainly to strengthen leadership decision-making,implement a centralized procurement price nego-tiation model and improve the pre-assessment system for ancillary facilities.

Objective: To investigate independent risk factors for lower extremity amputation (LEA) in hospitalized patients with diabetic foot ulcers ( DFUs) . Methods: A multicenter retrospective analysis was conducted on the clinical data of 329 DFUs hospitalized patients with diabetic foot ulcers from four general hospitals across the na⁃tion. A multivariate Logistic regression model was constructed , and prediction analysis was performed using R 4. 2. 1 . The discriminative ability of the model was assessed using receiver operating characteristic curves , while calibration accuracy and clinical applicability were evaluated via calibration curves and decision curve analysis. Results : The study revealed that patients with higher education backgrounds showed lower disease severity (Wagnergrade) (Z = - 4. 331 , P < 0. 05) . A history of amputation , pre⁃existing lower extremity vascular disease , abnormal dorsalis pedis artery pulsation , and a history of coronary heart disease were significantly associated with the severity of DFUs , resulting in higher Wagner scores (P < 0. 05) . In the amputation prognosis analysis , prolonged duration of diabetes and elevated white blood cell count were positively correlated with amputation risk ( both P < 0. 01) .Multivariable regression identified non⁃higher education , low hemoglobin levels , decreased total cholesterol , and abnormally elevated platelet counts as independent risk factors for high Wagner grades ( ≥ grade 3 ) ( all P <0. 05) . The integrated predictive model incorporating these factors demonstrated strong discriminative performance ,with an area under curve of 0. 880 (95% CI: 0. 801 - 0. 960) . The calibration curve slope approached the ideal value , and decision curve analysis confirmed the model ′s clinical net benefit within a threshold probability range of 10% - 65% . Conclusion Lower education level , poor baseline nutritional status , infection , hypercoagulability ,and underlying vascular diseases collectively constitute key factors contributing to elevated amputation risk in DFUs patients. The developed predictive model exhibits high accuracy and may assist clinicians in formulating individual⁃ized intervention strategies.