Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

OBJECTIVE: To investigate the predictive value of morphology, immunology, and cytogenetics for isocitrate dehydrogenase 1 and 2 (IDH1/2) gene mutation in newly diagnosed acute myeloid leukemia (AML) patients. METHODS: The clinical data of 186 newly diagnosed AML patients (except M3 subtype) in the First People's Hospital of Changzhou were retrospectively analyzed, and the variables associated with IDH1/2 mutation in patients were screened using LASSO regression to construct a multivariate logistic regression analysis model. The Bootstrap method was used for internal validation of the model and nomograms were used to visualize the model, and receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the model. RESULTS: A total of 60 AML patients had IDH1/2 mutation at initial diagnosis. LASSO regression screened 9 predictive variables associated with IDH1/2 mutation, including CD7, CD56, CD11b, CD15, CD64, HLA-DR, platelet count≥50×10⁹/L, isolated +8 and normal karyotype. The nomogram and ROC curve were plotted based on the above 9 variables. The area under the ROC curve (AUC) of the training set and the validation set were 0.871 and 0.806, respectively. Internal validation showed that the nomogram had good predictive ability. CONCLUSION The prediction model based on MIC typing constructed in this study has a good predictive ability for the presence of IDH1/2 mutations in newly diagnosed AML patients and has important clinical application value when the gene mutation detection results are unavailable.
Humans ; Isocitrate Dehydrogenase/genetics* ; Leukemia, Myeloid, Acute/genetics* ; Mutation ; Retrospective Studies ; Nomograms ; Female ; Male ; ROC Curve ; Middle Aged

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

This article reports a case of primary Müllerian adenosarcoma(MA)of the ovary admitted to the Obstetrics and Gynecology Hospital,Fudan University in 2022,reviews the literature on this rare disease,and shares the experience of its diagnosis and treatment.The patient was a 29-year-old unmarried woman who underwent laparoscopic resection of an ovarian lesion in another hospital.Intraoperatively,it was observed that"the right ovary was enlarged with a cauliflower-shaped mass at the lower pole,measuring about 11 cm×8 cm,unencapsulated,with a fish-like texture,which was completely excised and sent for examination."Postoperative consultation with a(tertiary)hospital in Beijing and our pathology department suggested the diagnosis of ovarian adenosarcoma.Therefore,we performed a comprehensive staged surgery for the patient,i.e.,laparoscopic right salpingo-oophorectomy,cystectomy of the left ovary,omentectomy,multiple peritoneal biopsies,and hysteroscopic resection of cervical canal lesions.The patient received four cycles of postoperative chemotherapy with paclitaxel and ifosfamide.After chemotherapy,the patient has been regular followed up and showed no signs of recurrence during the almost 2-year postoperative follow-up period.

Assessment is an indispensable and critical activity in the educational process. In the recent decades, with the birth and development of competence-based educational paradigm, the rationale behind assessment is shifting from "assessment of learning" to "assessment for learning". Workplace-based assessment (WPBA), which aims to improve the quality of both learning and teaching through assessment in real workplace circumstances, is a set of assessment tools that conforms to the new concepts of medical education. In this article, with the purpose to promote the application of WPBA and thus enhance the quality of dental education in our country, a thorough discussion is performed regarding the core principles, tools, advantages of WPBA as well as attentions that should be noted when applying WPBA. It is recommended to establish a longitudinal assessment system which employs various WPBA tools and assesses the development of students' competencies through the whole educational process. Such a dynamic assessment system may be helpful to provide all-rounded and competent dental talents who can eventually benefit the society.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective To establish a Nomogram model for predicting the occurrence of stigma in elderly patients with colostomy after colorectal cancer (CRC) surgery. Methods A total of 123 elderly patients with colostomy after CRC surgery in the Northern Jiangsu People's Hospital Affiliated to Yangzhou University from June 2022 to December 2023 were selected as research objects, and they were divided into stigma group (n=62) and non-stigma group (n=61) according to the occurrence of stigma. Logistic regression analysis was used to screen risk factors, and a Nomogram was drawn and evaluated for its discrimination and consistency. Results Score of the Social Impact Scale (SIS) in 123 elderly patients with colostomy after CRC surgery ranged from 34 to 90, with an average score of (60.14±12.08) and a median score of 48. Female (95%CI, 2.467 to 20.978, P < 0.001), presence of stoma complications (95%CI, 1.766 to 10.093, P=0.001), moderate to low level of perceived social support (95%CI, 1.654 to 12.710, P=0.003), and moderate to low level of psychosocial adaptation (95%CI, 1.568 to 10.869, P=0.004) were identified as independent risk factors for stigma in elderly patients with colostomy after CRC surgery. The area under the receiver operating characteristic curve was 0.816 (95% CI, 0.744 to 0.889); the calibration curve had a slope close to 1, and the Hosmer-Lemeshow goodness-of-fit test showed better results (χ²=7.722, P=0.461). Conclusion Female, presence of stoma complications, moderate to low level of perceived social support, and moderate to low level of psychosocial adaptation are independent risk factors for stigma in elderly patients with colostomy after CRC surgery. Nomogram model established based on these factors can help identify high-risk populations for stigma, so as to obtain individualized precise intervention and reduce the incidence of stigma.

Objective To establish an analytical method combining gas chromatography-tandem mass spectrometry(GC-MS)and liquid chromatography-tandem mass spectrometry(LC-MS)to detect diazepam residue in bait nest materials and fish samples,and improve the pretreatment steps of samples to make the experimental results accurate and the sample processing convenient and fast.Methods Taking diazepam as the research object,samples were extracted with methanol and dichloromethane/n-hexane as solvents according to the type,and the supernatant was taken for detection after centrifugation.Results The diazepam standard sample showed a good linear relationship in the range of 10～10 000 ng/mL.The retention times in methanol and mixed solvent were 13.54 min and 13.83 min,respectively,and the correlation coefficients were 0.998 and 0.999,respectively;The limit of detection(LOD)of using methanol as extraction solvent was 2 ppb,and limit of quantification(LOQ)was 6 ppb.The LOD of using mixed solvents was 5 ppb,and the LOQ was 15 ppb.When the sample is a bait nest material,the GC-MS spectrum was clear and standard,and the peak shape was sharp and prominent;When the sample is biological specimen,the GC-MS spectra are disturbed by matrix,while the LC-MS data is more accurate and faster.Conclusion It is more appropriate to use GC-MS to determine the content of bait nest materialsamples,and it is more accurate to LC-MS to determine the content of fish samples due to the complexity of the organism.

Objective:To construct a chain mediating model based on two mediating variables of positive psychological capital and general self-efficacy, so as to explore the impact mechanism of social support on posttraumatic growth in thyroid cancer patients.Methods:From March to December 2023, convenience sampling was used to select 270 postoperative patients with thyroid cancer from the Chinese People's Liberation Army General Hospital as participants. The patients were surveyed using the General Information Questionnaire, Post Traumatic Growth Inventory, Social Support Rating Scale, Positive Psychological Questionnaire, and General Self-efficacy Scale. Spearman correlation was used to analyze the correlation between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in thyroid cancer patients. SPSS PROCESS program was used to test for the chain mediating effect.Results:A total of 270 questionnaires were distributed, and 257 questionnaires were collected. After excluding questionnaires with missing items exceeding 10% and regular responses, 246 valid questionnaires were collected, with a valid response rate of 91.11% (246/270). Spearman correlation showed that there was positive correlations between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in patients ( P<0.01). Mediating effect analysis showed that social support directly and positively predicted posttraumatic growth in thyroid cancer [ β=0.403, 95% CI (0.258, 0.547) ], and also affected patients' posttraumatic growth through three indirect pathways, namely social support → positive psychological capital → posttraumatic growth, with an effect value of 0.083 [95% CI (0.002, 0.173) ], accounting for 13.63% of the total effect, and social support → general self-efficacy → posttraumatic growth, with an effect value of 0.099 [95% CI (0.040, 0.166) ], accounting for 16.26% of the total effect, and social support → positive psychological capital → general self-efficacy → posttraumatic growth, with an effect value of 0.025 [95% CI (0.005, 0.051) ], accounting for 4.11% of the total effect. The total indirect effect accounted for 33.83% of the total effect. Conclusions:Social support can not only directly affect the post-traumatic growth of thyroid cancer patients, but also indirectly affect post-traumatic growth through the mediating effect of positive psychological capital and general self-efficacy.