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

Objective: To explore the dynamic changes in serum lipid levels and nutritional status during BCMA-CAR-T-cell therapy in patients with refractory or relapsed multiple myeloma (R/R MM) based on LEGEND-2. Methods: The data of patients with R/R MM who underwent BCMA-CAR-T therapy at our hospital between March 30, 2016, and February 6, 2018, were retrospectively collected. Serum lipid levels, controlled nutritional status (CONUT) score, and other clinical indicators at different time points before and after CAR-T-cell infusion were compared and analyzed. The best cut-off value was determined by using the receiver operator characteristic (ROC) curve. The patients were divided into high-CONUT score (>6.5 points, malnutrition group) and low-CONUT score groups (≤6.5 points, good nutrition group), comparing the progression-free survival (PFS) and total survival (OS) of the two groups using Kaplan-Meier survival analysis. Results: Before the infusion of CAR-T-cells, excluding triglycerides (TG), patients' serum lipid levels were lower than normal on average. At 8-14 d after CAR-T-cell infusion, serum albumin (ALB), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and apolipoprotein A1 (Apo A1) levels dropped to the minimum, whereas CONUT scores reached the maximum. In addition to TG, apolipoprotein B (Apo B) levels increased compared with baseline. After CAR-T-cell therapy, the patients' serum lipid levels significantly increased with well-improved nutritional status. Spearman's related analysis showed that TC, HDL, and ApoA1 levels after CAR-T-cell injection were significantly negatively correlated with the grade of cytokine-release syndrome (CRS) (r=-0.548, P=0.003; r=-0.444, P=0.020; r=-0.589, P=0.001). Furthermore, survival analysis indicated that the CONUT score was unrelated to PFS, and the median OS of patients with R/R MM in the high-CONUT score group was shorter than that in the low-CONUT score group (P=0.046) . Conclusions: During CAR-T-cell therapy, hypolipidemia and poor nutritional status were aggravated, which is possibly related to CRS. The patients' serum lipid levels and nutritional status were significantly improved after CAR-T-cell treatment. The CONUT score affected the median OS in patients treated with CAR-T-cells. Therefore, specific screening and intervention for nutritional status in patients receiving CAR-T-cell therapy are required.
Humans ; Multiple Myeloma/drug therapy* ; Nutritional Status ; Retrospective Studies ; Receptors, Chimeric Antigen/therapeutic use* ; B-Cell Maturation Antigen/therapeutic use* ; Cell- and Tissue-Based Therapy ; Lipids/therapeutic use*

Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.
Humans ; Male ; Middle Aged ; Aged ; Coronary Artery Disease/diagnostic imaging* ; Stroke Volume ; Myocardial Perfusion Imaging ; Retrospective Studies ; Ventricular Function, Left ; Myocardial Ischemia

With the development of artificial intelligence (AI) technology, it has a wide range of explorations in orthodontics. AI has greater application prospects in precise measurement, multidimensional diagnosis, treatment planning and efficacy prediction. At the same time, there are certain limitations in the application of AI, such as risks caused by individual variability, black box properties and unclear delineation of medical responsibilities. This paper summarized the history and current status of AI applications in orthodontics and discussed future development trends, to provide reference for clinical orthodontics.
Humans ; Artificial Intelligence ; Orthodontics ; Dental Care ; Forecasting ; Delivery of Health Care

Objective: To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. Methods: A total of 35 000 clinical orthodontic images were collected in the Department of Orthodontics, Capital Medical University School of Stomatology, from October to November 2020 and June to July 2021. The images were from 490 orthodontic patients with a male-to-female ratio of 49∶51 and the age range of 4 to 45 years. After data cleaning based on inclusion and exclusion criteria, the final image dataset included 17 453 face images (frontal, smiling, 90° right, 90° left, 45° right, and 45° left), 8 026 intraoral images [frontal occlusion, right occlusion, left occlusion, upper occlusal view (original and flipped), lower occlusal view (original and flipped) and coverage of occlusal relationship], 4 115 X-ray images [lateral skull X-ray from the left side, lateral skull X-ray from the right side, frontal skull X-ray, cone-beam CT (CBCT), and wrist bone X-ray] and 684 other non-orthodontic images. A labeling team composed of orthodontic doctoral students, associate professors, and professors used image labeling tools to classify the orthodontic images into 20 categories, including 6 face image categories, 8 intraoral image categories, 5 X-ray image categories, and other images. The data for each label were randomly divided into training, validation, and testing sets in an 8∶1∶1 ratio using the random function in the Python programming language. The improved SqueezeNet deep learning model was used for training, and 13 000 natural images from the ImageNet open-source dataset were used as additional non-orthodontic images for algorithm optimization of anomaly data processing. A multi-classification orthodontic image recognition system based on deep learning models was constructed. The accuracy of the orthodontic image classification was evaluated using precision, recall, F1 score, and confusion matrix based on the prediction results of the test set. The reliability of the model's image classification judgment logic was verified using the gradient-weighted class activation mapping (Grad-CAM) method to generate heat maps. Results: After data cleaning and labeling, a total of 30 278 orthodontic images were included in the dataset. The test set classification results showed that the precision, recall, and F1 scores of most classification labels were 100%, with only 5 misclassified images out of 3 047, resulting in a system accuracy of 99.84%(3 042/3 047). The precision of anomaly data processing was 100% (10 500/10 500). The heat map showed that the judgment basis of the SqueezeNet deep learning model in the image classification process was basically consistent with that of humans. Conclusions: This study developed a multi-classification orthodontic image recognition system for automatic classification of 20 types of orthodontic images based on the improved SqueezeNet deep learning model. The system exhibitted good accuracy in orthodontic image classification.
Humans ; Male ; Female ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Deep Learning ; Reproducibility of Results ; Radiography ; Algorithms ; Cone-Beam Computed Tomography

Eosinophilia/genetics* ; Gene Rearrangement ; Humans ; Myeloproliferative Disorders/genetics* ; Neoplasms ; Oncogene Proteins, Fusion/genetics* ; Receptor, Platelet-Derived Growth Factor alpha/genetics*

The detection method of characteristic spectrum for reference samples was established by preparing 15 batches of the reference samples of Huagan Decoction, and the peak attribution and the similarity range in the characteristic spectrum were clarified. The ranges of paste-forming rate, content, and transfer rate of the index components including geniposide, paeonol, and paeoniflorin were analyzed. The key quality attribute of the reference samples of Huagan Decoction was defined. The results showed that the 15 batches of the reference samples of Huagan Decoction had good similarities in the characteristic spectrum, which were all higher than 0.9. According to the information of characteristic peak, there were 18 characteristic peaks in the whole prescription, including seven common characteristic peaks from green tangerine peel and dried tangerine peel, four characteristic peaks from tree peony root bark(three of them were common characteristic peaks from tree peony root bark and red peony root), five characteristic peaks from cape jasmine fruit, one characteristic peak from paniculate bolbostemma, and one characteristic peak from oriental waterplantain rhizome.The paste-forming rate of the 15 batches of reference samples was 14.73%-18.83%. The content of geniposide was 1.68%-2.87%, with the average transfer rate of 70.05%±11.13%. The content of paeonol was 0.10%-0.16%, with the average transfer rate of 9.38%±1.78%. The content of paeoniflorin was 1.94%-2.74%, with the average transfer rate of 36.69%±4.63%. This study analyzed the quality value transfer of the reference samples of Huagan Decoction by the evaluation mode of combining the characteristic spectrum, the paste-forming rate, and the content of index components. The findings of this study initially established a stable and feasible standard decoction evaluation method and provided references for the quality control and the subsequent development of relevant preparations of Huagan Decoction.
Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal ; Paeonia ; Prescriptions ; Quality Control

Children in the mixed dentition grow rapidly, and various types of malocclusion often appear in this period. At the same time, there are many environmental factors affecting the development of the occlusion at this stage. Functional abnormalities related to lip, tongue, articulation and breathing, and impacted teeth should be actively intervened and blocked to avoid the continued development of the deformity. Appropriate orthopedic devices should be used in patients with skeletal malocclusion, if necessary, for growth modification and the influence of congenital factors and the prognosis of treatment should be fully evaluated. Over-intervention of the temporary malocclusions in the mixed dentition should be avoided. In conclusion, early orthodontic treatment in the mixed dentition requires a comprehensive assessment of the treatment need, risks, timing, cost and the ultimate benefit of the patient. The timing of orthodontic treatment is not the sooner the better. The indications must be strictly controlled, and the necessity and limitations must be carefully considered.
Child ; Dentition, Mixed ; Humans ; Malocclusion/therapy* ; Tongue ; Tongue Habits ; Tooth, Impacted

Objective:Based on fingerprint， index component content and dry extract yield， a quality evaluation method for substance benchmark of Xiebaisan was established to study the key quality attributes， to explore the quantitative transfer relationship between decoction pieces and substance benchmark， and to preliminarily formulate the quality standard of substance benchmark of Xiebaisan. Method:The substance benchmark of Xiebaisan was prepared according to the records of ancient formulas， fingerprints of 15 batches of decoction pieces and substance benchmarks were collected by high performance liquid chromatography （HPLC） and the index components were determined with the mobile phase of acetonitrile-0.05% phosphoric acid solution for gradient elution. The dry extract yield， fingerprint similarity and transfer rate of index components were combined to study the quantity value transmitting. Result:Ten characteristic peaks were identified in fingerprint of the substance benchmark and two characteristic peaks from stir-fried Mori Cortex， four characteristic peaks from baked Lycii Cortex， four characteristic peaks from Glycyrrhizae Radix et Rhizoma Praeparata cum Melle. Mulberroside A， liquiritin and glycyrrhizic acid were used as index components for the determination， the contents of mulberroside A， liquiritin and glycyrrhizic acid in substance benchmark of Xiebaisan were 2.69%-4.26%， 0.09%-0.17% and 0.09%-0.16%， and their transfer rates were （31.37±4.14）%， （36.12±4.03）% and （12.25±0.88）%， respectively. The similarity of fingerprint of substance benchmarks was good， the fingerprint similarities of 14 batches of substance benchmarks and control fingerprint were >0.9. The dry extract yield of substance benchmark of Xiebaisan ranged from 8.09% to 11.29%. Conclusion:The established quality evaluation method of substance benchmark of Xiebaisan is scientific and reasonable， and the transfer process of decoction pieces to substance benchmarks is stable and controllable. The preliminary quality standard of the substance benchmark can provide basis and reference for the development of modern preparations of Xiebaisan in the future.

BACKGROUND: Histidine-tryptophan-ketoglutarate (HTK) is a solution commonly used for organ transplantation. However, there is no certified fixed regimen for on-pump heart surgery in neonates. We aimed to retrospectively evaluate the outcomes related to different HTK dosages and to analyze the safety of high-dosage perfusion. METHODS: A total of 146 neonates who underwent on-pump heart surgery with single-shot HTK perfusion were divided into two groups according to HTK dosages: a standard-dose (SD) group (n = 63, 40 mL/kg < HTK ≤ 60 mL/kg) and a high-dose (HD) group (n = 83, HTK >60 mL/kg). Propensity score matching (PSM) was performed to control confounding bias. RESULTS: The SD group had a higher weight (3.7 ± 0.4 vs. 3.4 ± 0.4 kg, P < 0.0001), a lower proportion of complete transposition of the great artery (69.8% vs. 85.5%, P = 0.022), a lower cardiopulmonary bypass (CPB) time (123.5 [108.0, 136.0] vs. 132.5 [114.8, 152.5] min, P = 0.034), and a lower aortic x-clamp time (82.9 ± 27.1 vs. 95.5 ± 26.0 min, P = 0.005). After PSM, 44 patients were assigned to each group; baseline characteristics and CPB parameters between the two groups were comparable. There were no significant differences in peri-CPB blood product consumption after PSM (P > 0.05). The incidences of post-operative complications were not significantly different between the two groups. There were no significant differences in ventilation time, intensive care unit stay, and post-operative hospital stay (P > 0.05). Follow-up echocardiography outcomes at 1 month, 3 to 6 months, and 1 year showed that left ventricular ejection fraction and end-diastolic dimension were comparable between the two groups. CONCLUSIONS In neonatal on-pump cardiac surgery patients, single-shot HD (>60 mL/kg) HTK perfusion had a comparable heart protection effect and short-term post-operative prognosis as standard dosage perfusion of 40 to 60 mL/kg. Thus, this study provides supporting evidence of the safety of HD HTK perfusion.
Glucose/therapeutic use* ; Histidine ; Humans ; Infant, Newborn ; Mannitol ; Organ Preservation Solutions ; Potassium Chloride/therapeutic use* ; Prognosis ; Retrospective Studies ; Stroke Volume ; Tryptophan ; Ventricular Function, Left