Amid the global wave of digital economy, China's medical artificial intelligence applications are rapidly advancing through technological innovation and policy support, while facing multifaceted evaluation and regulatory challenges. The dynamic algorithm evolution undermines the consistency of assessment criteria, multimodal systems lack unified evaluation metrics, and conflicts persist between data sharing and privacy protection. To address these issues, the China National Health Development Research Center has established a value assessment framework for artificial intelligence medical technologies, formulated the country's first technical guideline for clinical evaluation, and validated their practicality through scenario-based pilot studies. Furthermore, this paper proposes introducing a "regulatory sandbox" model to test technical compliance in controlled environments, thereby balancing innovation incentives with risk governance.
Artificial Intelligence/legislation & jurisprudence* ; China ; Humans ; Algorithms

OBJECTIVE: To investigate the clinical characteristics and prognostic factors of elderly patients with diffuse large B-cell lymphoma (DLBCL). METHODS: Clinical data of elderly DLBCL patients diagnosed pathologically between 2010 and 2015 were extracted from the SEER database. Cox proportional hazards model was used for multivariate analysis, and Kaplan-Meier survival curves were plotted to explore the prognostic factors affecting overall survival (OS). RESULTS: A total of 11 523 elderly DLBCL patients were included, of whom 58.6% had stage Ⅲ/Ⅳ disease, and 28.8% exhibited extranodal involvement. Besides lymph nodes (68.5%), common primary extranodal sites included the gastrointestinal tract (9.8%) and lip, mouth, and pharynx (4.1%). The median survival time for the entire cohort was 47 months, with a 3-year survival rate of 52.0%, and a 5-year survival rate of 47.8%. Multivariate Cox regression analysis revealed that age, sex, race, Ann Arbor stage, primary site, B symptoms, treatment modality, treatment sequence, and whether DLBCL was the first malignant primary indicator were independent prognostic factors affecting OS in elderly DLBCL patients (all P <0.05). CONCLUSION Age≥70 years, male, black race, advanced Ann Arbor stage, primary sites in the lungs, liver, or kidney, presence of B symptoms, and preoperative systemic therapy were independent risk factors for poor prognosis in elderly DLBCL patients.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Prognosis ; Aged ; Male ; Female ; Survival Rate ; Proportional Hazards Models ; Aged, 80 and over ; Kaplan-Meier Estimate ; Neoplasm Staging

Objective To obtain differential spectral characteristics of etomidate and its structural ana-logues,and to establish a rapid identification method using surface-enhanced Raman spectroscopy(SERS)combined with machine learning algorithms for distinguishing etomidate and its analogues.Methods Silver nanoparticles(AgNPs)were used as the SERS substrate to collect SERS spectra of etomidate,metomidate,propoxate,and isopropoxate at two concentrations of 1×10-4 and 1×10-5 mol/L.SERS spectra were also obtained from blood and urine samples containing 1×10-5 mol/L of etomidate,metomidate,propoxate,and isopropoxate,as well as from confiscated e-cigarette oil containing etomi-date.Uniform manifold approximation and projection(UMAP)was employed for nonlinear dimensiona-lity reduction and visualization,and a classification model based on the XGBoost algorithm was con-structed to enable discriminant analysis of these four structurally highly similar compounds.Results Mi-nor characteristic peak shifts(5-3 cm-1)were identified in the range of 1 398-811 cm-1.Qualitative identification of the compounds in serum,urine and e-cigarette oil samples was achieved without pre-treatment.After UMAP dimensionality reduction,distinct clustering separation among different sub-stances was observed.The XGBoost model achieved 100%classification accuracy on the test set.Feature weight analysis revealed that C-N stretching vibration(841 cm-1),C=O stretching vibration(1 367 cm-1),and C-O-C asymmetric vibration(1 049 cm-1)were the key spectral bands for discrimination.Conclu-sion The combination of SERS and machine learning can effectively amplify subtle differences in mo-lecular structures,enabling rapid and accurate identification of etomidate and its analogues.This ap-proach is suitable for on-site rapid screening in forensic toxicology.

Objective To understand the pathogen detection of hospitalized patients before antimicrobial therapy in a hospital through implementation of comprehensive intervention measures,and provide reference basis for the de-velopment of targeted measures.Methods Hospitalized patients who received therapeutic antimicrobial agents in this hospital were selected as the research subjects.Patients who were hospitalized from January to May 2022 were selected as the pre-intervention group,comprehensive intervention measures were taken from June to October 2022,and those who were hospitalized from November 2022 to March 2023 were selected as the post-intervention group.The pathogen detection rate before antimicrobial therapy,sterile specimen detection rate,antimicrobial use rate,de-tection rate of key multidrug-resistant organisms of patients before and after the intervention were analyzed.Results Compared to before intervention,the proportion of pathogen detection rate before antimicrobial therapy(62.09％vs 74.04％),detection rate of healthcare-associated infection diagnosis-related pathogens(62.82％vs 92.73％),and sterile specimen detection rate(35.17％vs 41.06％)of hospitalized patients after intervention all increased signifi-cantly,with statistically significant differences(all P＜0.05).After intervention,pathogen detection rate before the combination use of key antimicrobial agents was not statistically different from before intervention(93.33％vs 90.48％,P＞0.05),while antimicrobial use rate was lower than before intervention(39.93％vs 44.95％,P＜0.05).There was no statistically significant difference in the detection rate of key multidrug-resistant organisms be-fore and after intervention(all P＞0.05).Conclusion Adopting scientific and rational intervention measures can improve the pathogen detection rate,provide a reference basis for the rational use of antimicrobial agents.There was no significant improvement in the pathogen detection rate before the combination use of key antimicrobial agents and the detection rate of key multidrug-resistant organisms,indicating that relevant measures still need to be further optimized.

Objective:To evaluate the utility of the 9-gene panel as a differential diagnostic method for thyroid nodules within determinate cytological diagnosis and as a parallel diagnostic method for thyroid fine-needle aspiration (FNA) cytology.Methods:579 liquid-based cytology samples from 544 patients were collected after thyroid FNA diagnosis in our hospital from December 2014 to April 2021. Mutations at any site of 9 genes, namely, BRAF, NRAS, HRAS, KRAS, GNAS, RET, TERT, TP53, and PIK3CA as recorded by the Catalogue of Somatic Mutations in Cancer (COSMIC), were analyzed by next-generation sequencing. Taking postoperative histopathology and cytology results with definite benign or malignant diagnosis as the gold standard, the diagnostic efficacy of the 9-gene panel as a reclassified method for thyroid nodules with indeterminate cytological diagnosis and as a parallel diagnostic method for thyroid FNA cytology were evaluated and compared with that of the BRAF V600E single-gene detection method.Results:Of the 579 thyroid nodules, 196 (33.85%) were Bethesda Ⅱ, 11 (1.90%) were Bethesda Ⅲ, 31 (5.35%) were Bethesda Ⅳ, 27 (4.66%) were Bethesda Ⅴ, and 314 (54.23%) were Bethesda Ⅵ, as diagnosed by thyroid FNA cytology. Among these 579 thyroid nodules, 275 were tested positive for 9-gene mutations, with a mutation rate of 47.5%. Of the 329 thyroid nodules surgically removed, 30 (9.12%) were benign, 5 (1.52%) were borderline, and 294 (89.36%) were malignant. Regarding borderline nodules as malignant nodules, the mutation rates of the 9 genes in the 299 malignant thyroid nodules from high to low were BRAF 62.21% (186/299), NRAS 5.02% (15/299), HRAS 1.00% (3/299), PIK3CA 0.67% (2/299), GNAS 0.67% (2/299), KRAS 0.33% (1/299), TP53 0.33% (1/299), TERT 0.33% (1/299) and RET 0.00% (0/299). The malignant risks of the 9 genes from high to low were BRAF 100% (186/186), PIK3CA 100.00% (2/2), GNAS 100.00% (2/2), TERT 100.00% (1/1), TP53 100.00% (1/1), NRAS 78.95% (15/19), HRAS 75.00% (3/4), and KRAS 50.00% (1/2). For thyroid nodules of Bethesda Ⅲ-Ⅳ (indeterminate diagnosis), the sensitivity (SN) of the 9-gene panel in diagnosing thyroid cancer is 34.48% (10/29), the specificity (SP) is 61.54% (8/13), and the accuracy is 42.86% (18/42); whereas the SN of the BRAF V600E detection method is 0%. Therefore, the diagnostic efficiency of the 9-gene panel is significantly better than that of BRAF V600E single gene detection. For thyroid nodules of Bethesda Ⅱ-Ⅵ, the SN of the 9-gene panel in diagnosing thyroid cancer was 68.83% (254/369), the SP was 90.00% (189/210), the accuracy was 76.51% (443/579), and the area under the curve (AUC) was 0.79; whereas the SN of BRAF V600E single-gene detection in diagnosing thyroid cancer was 63.69% (235/369), the SP was 99.52% (209/210), the accuracy was 76.68% (444/579), and the AUC was 0.82. The SP of BRAF V600E detection is higher than that of the 9-gene panel ( P＜0.01), but there is no significant difference in SN, accuracy (both P＞0.05), and AUC ( Z=0.85, P=0.396) between them. Gene mutations indicating poor prognosis were detected in 4 nodules of papillary thyroid carcinoma and 1 nodules of follicular thyroid carcinoma, including 2 nodules with TERT and BRAF V600E co-mutations, 1 nodule with TP53 mutation, and 2 nodules with PIK3CA mutation. Conclusions:As a reclassified method for thyroid lesions with indeterminate cytological diagnosis, the 9-gene panel is better than BRAF V600E single gene detection. As a parallel diagnostic method of thyroid FNA cytology, the 9-gene panel has similar diagnostic efficacy as BRAF V600E single-gene detection. The 9-gene panel can detect individual cases with gene mutations indicating poor prognosis. The identification of patients with these special gene mutations has certain implications for the clinical management of them.

Objective:To evaluate the utility of the 9-gene panel as a differential diagnostic method for thyroid nodules within determinate cytological diagnosis and as a parallel diagnostic method for thyroid fine-needle aspiration (FNA) cytology.Methods:579 liquid-based cytology samples from 544 patients were collected after thyroid FNA diagnosis in our hospital from December 2014 to April 2021. Mutations at any site of 9 genes, namely, BRAF, NRAS, HRAS, KRAS, GNAS, RET, TERT, TP53, and PIK3CA as recorded by the Catalogue of Somatic Mutations in Cancer (COSMIC), were analyzed by next-generation sequencing. Taking postoperative histopathology and cytology results with definite benign or malignant diagnosis as the gold standard, the diagnostic efficacy of the 9-gene panel as a reclassified method for thyroid nodules with indeterminate cytological diagnosis and as a parallel diagnostic method for thyroid FNA cytology were evaluated and compared with that of the BRAF V600E single-gene detection method.Results:Of the 579 thyroid nodules, 196 (33.85%) were Bethesda Ⅱ, 11 (1.90%) were Bethesda Ⅲ, 31 (5.35%) were Bethesda Ⅳ, 27 (4.66%) were Bethesda Ⅴ, and 314 (54.23%) were Bethesda Ⅵ, as diagnosed by thyroid FNA cytology. Among these 579 thyroid nodules, 275 were tested positive for 9-gene mutations, with a mutation rate of 47.5%. Of the 329 thyroid nodules surgically removed, 30 (9.12%) were benign, 5 (1.52%) were borderline, and 294 (89.36%) were malignant. Regarding borderline nodules as malignant nodules, the mutation rates of the 9 genes in the 299 malignant thyroid nodules from high to low were BRAF 62.21% (186/299), NRAS 5.02% (15/299), HRAS 1.00% (3/299), PIK3CA 0.67% (2/299), GNAS 0.67% (2/299), KRAS 0.33% (1/299), TP53 0.33% (1/299), TERT 0.33% (1/299) and RET 0.00% (0/299). The malignant risks of the 9 genes from high to low were BRAF 100% (186/186), PIK3CA 100.00% (2/2), GNAS 100.00% (2/2), TERT 100.00% (1/1), TP53 100.00% (1/1), NRAS 78.95% (15/19), HRAS 75.00% (3/4), and KRAS 50.00% (1/2). For thyroid nodules of Bethesda Ⅲ-Ⅳ (indeterminate diagnosis), the sensitivity (SN) of the 9-gene panel in diagnosing thyroid cancer is 34.48% (10/29), the specificity (SP) is 61.54% (8/13), and the accuracy is 42.86% (18/42); whereas the SN of the BRAF V600E detection method is 0%. Therefore, the diagnostic efficiency of the 9-gene panel is significantly better than that of BRAF V600E single gene detection. For thyroid nodules of Bethesda Ⅱ-Ⅵ, the SN of the 9-gene panel in diagnosing thyroid cancer was 68.83% (254/369), the SP was 90.00% (189/210), the accuracy was 76.51% (443/579), and the area under the curve (AUC) was 0.79; whereas the SN of BRAF V600E single-gene detection in diagnosing thyroid cancer was 63.69% (235/369), the SP was 99.52% (209/210), the accuracy was 76.68% (444/579), and the AUC was 0.82. The SP of BRAF V600E detection is higher than that of the 9-gene panel ( P＜0.01), but there is no significant difference in SN, accuracy (both P＞0.05), and AUC ( Z=0.85, P=0.396) between them. Gene mutations indicating poor prognosis were detected in 4 nodules of papillary thyroid carcinoma and 1 nodules of follicular thyroid carcinoma, including 2 nodules with TERT and BRAF V600E co-mutations, 1 nodule with TP53 mutation, and 2 nodules with PIK3CA mutation. Conclusions:As a reclassified method for thyroid lesions with indeterminate cytological diagnosis, the 9-gene panel is better than BRAF V600E single gene detection. As a parallel diagnostic method of thyroid FNA cytology, the 9-gene panel has similar diagnostic efficacy as BRAF V600E single-gene detection. The 9-gene panel can detect individual cases with gene mutations indicating poor prognosis. The identification of patients with these special gene mutations has certain implications for the clinical management of them.

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

OBJECTIVE: To explore pathogenesis of glucocortocoid-induced osteoporosis(GIOP) based on label-free mass proteomics. METHODS: Twevle female Sprague-Dawley(SD) rats were randomly divided into two groups, named as sham group and GIOP group. After one-week adaptive feeding, the rats of GIOP group were administered with dexamethasone via intramuscular injection according to 2.5 mg/kg weighting, while the rats of sham group were administered with the same amount of saline, twice a week. The tibias of each group were collected after 8-week modeling and made pathological sections to confirm the success of modeling. Three samples of each group were picked up to perform label-free mass proteomics. After quality control, differentially expressed proteins were identified according to qualitative and quantitative analyses. Then gene ontology(GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, cluster analysis as well as protein-protein interaction analysis were performed using bioinformatics analysis. RESULTS: Compared with sham group, the structure of bone trabecular in GIOP group showed abnormal arrangement, uneven distribution and obvious fragmentation, which could demonstrate successful modeling. A total of 47 differentially expressed proteins (DEPs) were identified including 20 up-regulated and 27 down-regulated proteins. The expression of protein nucleophosmin 1(NPM1), adipocyte plasma membrane associated protein (APMAP), cytochromec oxidase subunit 6A1 (COX6A1) and tartrate-resistant acid phosphatase (ACP5) showed a significant difference between two groups. KEGG results showed DEPs were enriched on metabolism-related pathways, immune-related pathways and AMP-activated kinase (AMPK) signaling pathway. CONCLUSION Protein NPM1, APMAP, COX6A1 and ACP5 showed a close relationship with pathogenesis of GIOP, which could serve as potential biomarkers of GIOP. AMPK signaling pathway played an important role in the occurrence and development of GIOP, which could be regarded as potential signaling pathway to treatment GIOP.
Female ; Rats ; Animals ; Glucocorticoids/adverse effects* ; AMP-Activated Protein Kinases ; Proteomics ; Rats, Sprague-Dawley ; Osteoporosis/genetics* ; Nuclear Proteins/adverse effects*

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens