BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

ObjectiveTo explore the establishment of performance assessment indicators for the classification and grading of public health staff in district-level Centers for Disease Control and Prevention (CDCs), and to provide a basis for such evaluations. MethodsThrough literature review and group interviews, performance evaluation indicators were developed based on competency evaluation. Experts were invited to evaluate the weight of performance evaluation indicators for public health staff from different categories, with the average value used to represent the weight of each indicator. ResultsTwenty-nine experts from universities in Shanghai, municipal CDCs, and district CDCs participated, yielding an expert authority coefficient of 0.86. The performance evaluation indicators for department managers were categorized into three levels, with 4 indicators at the primary level, 16 indicators at the secondary level, and 42 indicators at the tertiary level, while those for general staff included 4 primary indicators, 15 secondary indicators, and 36 tertiary indicators. Significant differences were observed in the weight coefficients of the primary indicators (internal operations, professional work, and learning and growth) between department managers and general staff. The top three secondary indicators for department managers were department management, monitoring and prevention, and level of expertise. For mid-level and senior staff, the top three secondary indicators were monitoring and prevention, level of expertise, and research work. The top three secondary indicators for junior staff were monitoring and prevention, professional expertise, and professional attitude. No significant statistical differences were found among tertiary indicators. ConclusionThe developed performance evaluation indicators are reliable. Staff at different levels and classifications should be evaluated using different performance evaluation standards to accurately reflect individual performance and contributions.

Objective: To elucidate the expression level and transcript structure of the CD36 gene in megakaryocytes cultured in vitro. Methods: Using umbilical cord blood CD34 hematopoietic stem cells as the starting point, megakaryocytic lineage cells were directionally cultured in vitro using different combinations of cytokines. Total cell RNA was extracted from cultures at 0 d, 7 d, and 12 d, and megakaryocyte RNA was extracted from CD41a-sorted cells after 14 d and 18 d of culture. RNA-NGS sequencing technology was used to analyze the RNA gene expression profiles across the five culture periods and further investigate CD36 gene expression. Results: The number of megakaryocytes generated in the TPO (100 ng/mL) group [(2.2±0.02)×10 /mL] was significantly higher than that in the other five groups. A total of 22 066 expressed genes were detected in the RNA of the five culture periods, and gene expression levels at each time point were correlated with the culture timeline. CD36 gene expression increased with culture time, with FPKM values for CD36 expression in the megakaryocytic lineage at 14 d and 18 d being 18.35 and 101.85, respectively, which were much lower than those for ITGA2B and ITGB3 genes but slightly higher than that for CD109 gene in the megakaryocytic lineage. The longest transcript of CD36 in the 18 d megakaryocytic lineage was 3.8 kb, encompassing all sequence of exons E3 to E14 and a partial sequence of E15. Conclusion: This is the first report on the expression level and transcript structure of the CD36 gene in megakaryocytes cultured in vitro, providing fundamental data for research on the expression and regulation of the CD36 gene in the megakaryocytic lineage.

OBJECTIVE To screen the primary processing methods of Ligusticum sinense slice based on differential metabolites， and provide theoretical basis for the scientific processing of L. sinense. METHODS Using 13 groups of L. sinense slice processed by fresh-cutting or traditional methods as samples， UHPLC-QE-MS was employed for metabolite identification. Multivariate statistical analysis was applied to screen differential metabolites among the 13 sample groups， analyzing the effects of washing， soaking， drying methods， and drying cycles on both the relative expressions of differential metabolites and the contents of carboxylic acids and their derivatives in the samples （to reflect the total amino acid content）. RESULTS Principal component analysis and partial least squares-discriminant analysis both showed significant intergroup differences among the 13 sample groups. A total of 688 differential metabolites were screened from the 13 sample groups， with carboxylic acids and their derivatives showing the highest proportion. The relative expression levels of phosphatidylcholine significantly increased after washing treatment， while tryptophan expression significantly decreased after soaking treatment. Samples dried at 50-60 ℃ showed significantly increased expression of psoralen， whereas those dried at 40 ℃ showed significantly decreased expression of methyl -p- methoxycinnamate. Both washing and soaking treatments significantly reduced the total amino acid content in samples， while secondary drying significantly increased it. The three controlled-temperature drying methods maintained relatively stable total content of amino acids in samples. CONCLUSIONS The optimal processing protocol for L. sinense slice is as follows: fresh L. sinense slice should be freshly cut at the production site， undergo quick washing after soil removal， and be dried twice at 40 ℃ （before and after slicing）.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

INTRODUCTION: Lecanemab has shown promise in treating early Alzheimer's disease (AD), but its safety and efficacy in Chinese populations remain unexplored. This study aimed to evaluate the safety and 6-month clinical outcomes of lecanemab in Chinese patients with mild cognitive impairment (MCI) or mild AD. METHODS: In this single-arm, real-world study, participants with MCI due to AD or mild AD received biweekly intravenous lecanemab (10 mg/kg). The study was conducted at Hainan Branch, Ruijin Hospital Shanghai Jiao Tong University School of Medicine. Patient enrollment and baseline assessments commenced in November 2023. Safety assessments included monitoring for amyloid-related imaging abnormalities (ARIA) and other adverse events. Clinical and biomarker changes from baseline to 6 months were evaluated using cognitive scales (mini-mental state examination [MMSE], montreal cognitive assessment [MoCA], clinical dementia rating-sum of boxes [CDR-SB]), plasma biomarker analysis, and advanced neuroimaging. RESULTS: A total of 64 patients were enrolled in this ongoing real-world study. Safety analysis revealed predominantly mild adverse events, with infusion-related reactions (20.3%, 13/64) being the most common. Of these, 69.2% (9/13) occurred during the initial infusion and 84.6% (11/13) did not recur. ARIA-H (microhemorrhages/superficial siderosis) and ARIA-E (edema/effusion) were observed in 9.4% (6/64) and 3.1% (2/64) of participants, respectively, with only two symptomatic cases (one ARIA-E presenting with headache and one ARIA-H with visual disturbances). After 6 months of treatment, cognitive scores remained stable compared to baseline (MMSE: 22.33 ± 5.58 vs . 21.27 ± 4.30, P = 0.733; MoCA: 16.38 ± 6.67 vs . 15.90 ± 4.78, P = 0.785; CDR-SB: 2.30 ± 1.65 vs . 3.16 ± 1.72, P = 0.357), while significantly increasing plasma amyloid-β 42 (Aβ42) (+21.42%) and Aβ40 (+23.53%) levels compared to baseline. CONCLUSIONS: Lecanemab demonstrated a favorable safety profile in Chinese patients with early AD. Cognitive stability and biomarker changes over 6 months suggest potential efficacy, though high dropout rates and absence of a control group warrant cautious interpretation. These findings provide preliminary real-world evidence for lecanemab's use in China, supporting further investigation in larger controlled studies. REGISTRATION ClinicalTrials.gov , NCT07034222.
Humans ; Alzheimer Disease/drug therapy* ; Male ; Female ; Aged ; Middle Aged ; Cognitive Dysfunction/drug therapy* ; Aged, 80 and over ; Amyloid beta-Peptides/metabolism* ; Biomarkers ; East Asian People

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Objective To explore the epidemic characteristics of common pneumonia pathogens in preschool children in Xining area and analyze the influencing factors of progression to severe pneumonia. Methods A total of 522 preschool children with pneumonia who were treated in our hospital from May 2021 to March 2024 were retrospectively selected as the research subjects. Sputum samples from children were taken to identify the pathogens and analyze their pathogenic epidemic characteristics.According to the diagnostic criteria in the 2019 version of ^“Standards for the Diagnosis and Treatment of Community-Acquired Pneumonia in Children^”, determine whether it is severe pneumonia, and collect the clinical data of the children.Logistic regression was used to analyze the influencing factors of the progression of common pneumonia to severe pneumonia. Results Among the 522 children with pneumonia, 522 cases were infected with pathogens, of which 447 cases were single infection (85.63%), 75 cases were mixed infection (14.36%). A total of 597 pathogens were detected, including 257 viruses (43.05%), 240 bacteria (40.20%), 68 mycoplasma pneumoniae (11.39%) and 32 chlamydia pneumoniae (5.36) . The detection rates of Streptococcus pneumoniae (149, 24.96%) and respiratory syncytial virus (118, 19.77%) were higher. Logistic regression results showed that length of hospital stay (OR=2.235, 95% CI: 1.552-3.439), ICU admission (OR=2.426, 95% CI: 1.769-3.881), intestinal microbiota disorder (OR=1.626, 95% CI: 1.335-2.842), multi-drug resistance (OR=2.086, 95%CI 1.417-2.905), mixed infection (OR=3.134, 95% CI : 2.217-8.857), nutritional risk (OR=2.783, 95% CI: 2.038-4.764), CRP (OR=2.589, 95% CI: 1.805-4.117), PCT (OR=1.486, 95%CI: 1.077-1.649), and white blood cells (OR=1.329, 95% CI: 1.021-1.536) were all associated with the risk of severe pneumonia (P<0.05). Conclusion The main pathogens of pneumonia in preschool children in Xining are Streptococcus pneumoniae and respiratory syncytial virus. Paying attention to the treatment of children with intestinal disorders, multiple infections, and malnutrition is of great significance to improve the progression of pneumonia.