The construction of a training system for visiting physicians in the department of rare diseases in China is an important measure to improve the overall diagnosis and treatment capacity for rare diseases and address the critical challenge of insufficient knowledge and skills among clinicians in practice. This article systematically describes the visiting physician training system established by the Department of Rare Diseases at Peking Union Medical College Hospital. It summarizes the training objectives and positioning, design logic, and learning modules of the system, aiming to provide a reference for the construction of the specialized talent team for rare diseases in China.

Objective To observe the value of Swin2SR network based on Transformer architecture for reconstructing chest super-resolution CT images.Methods Chest CT data of 218 patients were retrospectively collected.Swin2SR model based on Transformer architecture was adopted to enhance standard 512 matrix(512 × 512)CT images(standard-512 group)into 1 024(SR-1 024 group)and 2 048(SR-2 048 group)matrix SR CT images,respectively.Subjective and objective evaluation of image quality were performed,and the results were compared among groups.Results The subjective scores of overall imaging quality and lesion clarity in SR-1 024 and SR-2 048 groups were both higher than those in standard-512 group(all P＜0.05),while no significant difference was found between the former two(P＞0.05).Meanwhile,no significant difference of objective indexes of imaging quality was observed among 3 groups(all P＞0.05).Conclusion Swin2SR model could reconstruct chest SR CT images without increasing noise and improve imaging quality.

Objective:To fine-tune the mT5 (massively multilingual pre-trained text-to-text transformer) large language model, automatically generate report conclusions for teaching purposes from chest CT image descriptions, and assess the quality of automatically generated conclusions.Methods:The training set included 3 000 high-quality physical examination chest CT reports from one hospital, and the external validation set consisted of 600 physical examination chest CT reports from two other hospitals. Experienced radiology teaching physicians assessed the consistency between the generated conclusions and the original physician-written conclusions in the external validation set using a 5-point Likert scale across five linguistic indicators (correctness of examination information, correctness of lesion detection, standardization of terminology, applicability of the conclusions, and simplicity of conclusions). Using the original report conclusions as the reference, the accuracy of the conclusions generated based on the external validation set in describing four major thoracic conditions (pulmonary nodules, pneumonia, emphysema, pleural effusion) was evaluated. Perform chi square test using SPSS 25.0.Results:In the external validation set, the mean consistency score between the generated conclusions and the original conclusions given by the radiology teaching physicians was >4 points, indicating agreement with the original conclusions. In the generated conclusions, the description of the four major thoracic conditions demonstrated 0.95-1.00 (95% CI=0.91-1.00) accuracy, 0.76-1.00 (95% CI=0.59-1.00) sensitivity, and 0.97-1.00 (95% CI=0.91-1.00) specificity. Conclusions:The chest CT report conclusion generation system based on the mT5 large language model demonstrated high accuracy and is expected to provide immediate and efficient automated guidance for standardized residency training.

Objective To observe the value of Swin2SR network based on Transformer architecture for reconstructing chest super-resolution CT images.Methods Chest CT data of 218 patients were retrospectively collected.Swin2SR model based on Transformer architecture was adopted to enhance standard 512 matrix(512 × 512)CT images(standard-512 group)into 1 024(SR-1 024 group)and 2 048(SR-2 048 group)matrix SR CT images,respectively.Subjective and objective evaluation of image quality were performed,and the results were compared among groups.Results The subjective scores of overall imaging quality and lesion clarity in SR-1 024 and SR-2 048 groups were both higher than those in standard-512 group(all P＜0.05),while no significant difference was found between the former two(P＞0.05).Meanwhile,no significant difference of objective indexes of imaging quality was observed among 3 groups(all P＞0.05).Conclusion Swin2SR model could reconstruct chest SR CT images without increasing noise and improve imaging quality.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective:To explore the impact of age on the genetic variant spectrum and prognosis of patients with previously untreated Diffuse large B-cell lymphoma (DLBCL).Methods:A retrospective analysis was conducted on the clinical data and follow-up information of 254 previously untreated DLBCL patients from 14 hospitals in the Jiangsu Cooperative Lymphoma Group (JCLG) enrolled from July 2018 and July 2023. Following extraction of DNA from tumor tissue samples, next-generation sequencing (NGS) technique was employed to analyze the genetic variant spectrum of the DLBCL patients, with an evaluation of the relationship between age and genetic variants as well as prognosis. This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Nantong University (Ethics No.: 2023-K048-01).Results:The median age of the 254 DLBCL patients was 62 years old, with 55% of patients aged 60 years or above. Clinical evaluation showed that younger (< 60 years) patients had higher complete response (CR) (70% vs. 59%), and objective response rate (ORR) (88% vs. 79%) than older patients, though the difference between the two groups was not statistically. Survival analysis indicated that both the five-year overall survival (OS) (82.7% vs. 71.7%, P=0.006) and progression-free survival (PFS) (70.6% vs. 50.2%, P<0.05) rates were significantly higher in younger patients. NGS showed that 99.6% of the patients harbored genetic variants, with PIM1, KMT2D, TP53, MYD88, and CD79B being the most common genes. Age significantly affected the variant frequency of certain genes, with MYC variants serving an adverse prognostic factor for OS in younger patients ( P=0.001), while TP53 ( P=0.024) and BCL2 ( P=0.002) variants significantly impacted OS in older patients. Prognostic analysis identified age ≥ 60 years ( HR=3.439, 95% CI=1.318~9.874), presence of B symptoms ( HR = 2.871, 95% CI=1.133~7.307), and elevated lactate dehydrogenase ( HR=3.528, 95% CI=1.231~10.66) as independent adverse prognostic factors. Conclusion:Age, genetic variants, and clinical factors may significantly affect the prognosis of the DLBCL patients. Younger patients have better survival compared to older patients. Variants of the MYC, BCL2, and TP53 genes are closely associated with poor prognosis.

Objective:To investigate the mechanism by which microRNA-183 (miR-183) regulates the progression of diabetic nephropathy (DN) through targeting phosphatase and tensin homolog deleted on chromosome 10 (PTEN) and modulating the AKT signaling pathway, and to identify potential therapeutic targets for DN.Methods:(1) Bioinformatic analysis of miRNA expression: MiRNA expression datasets from diabetic nephropathy (DN) and control samples were obtained from the Gene Expression Omnibus database. Differential expression analysis was performed, and differentially expressed miRNAs (DEmiRNAs) were identified using thresholds of an absolute log 2 (fold changes) >1 and an adjusted P-value<0.05. The results were visualized in a volcano plot and a heatmap. (2) Animal model establishment and in vivo interventional studies: A DN rat model was induced by administration of a high-fat/high-sucrose diet combined with an intraperitoneal injection of streptozotocin. Rats were randomly assigned into four groups ( n=10 per group) using a random number table: control group, DN model group, miR-183 inhibitor negative control (NC) group, and miR-183 inhibitor group. The latter two groups received tail vein injections of the miR-183 inhibitor NC or the miR-183 inhibitor, respectively, for eight consecutive weeks. Parameters including fasting blood glucose, 24-hour urinary protein excretion, urinary albumin excretion rate (UAER), serum creatinine, and blood urea nitrogen (BUN) were measured. Renal histopathological changes were assessed by HE and PAS staining. Furthermore, the expression of candidate miRNAs from patient data was validated, and the mechanism of action of miR-183 was investigated using quantitative real-time PCR and Western blotting. (3) In vitro mechanistic investigations in cultured podocytes: Mouse podocyte clone-5 (MPC5) cells were cultured in vitro and subjected to the following conditions: normal glucose (5.3 mmol/L glucose), high glucose (30 mmol/L glucose), and osmotic control (5.3 mmol/L glucose+19.5 mmol/L mannitol). Cells in the logarithmic growth phase were transfected with the miR-183 inhibitor (100 nmol/L), miR-183 mimic (50 nmol/L), or their corresponding negative controls. A dual-luciferase reporter assay was conducted to validate the binding interaction between miR-183 and the 3'-untranslated region (3'UTR) of PTEN. The effects of miR-183 on the AKT signaling pathway, apoptosis-related proteins, and cell viability were evaluated by quantitative real-time PCR, Western blotting, and the cell counting kit-8 assay, respectively. Results:MiR-183 expression was markedly upregulated in renal tissues from DN patients and DN model rats (both P<0.05). Inhibition of miR-183 significantly reduced renal miR-183 levels by 90.2% ( P<0.01), decreased fasting blood glucose by 65.3% ( P<0.01), and improved renal function parameters, including reductions in urinary protein (40.3%), blood urea nitrogen (32.1%), urinary albumin excretion rate (22.5%), and serum creatinine (40.2%) (all P<0.01). Histological analyses showed attenuation of glomerular lesions and glycogen accumulation. Bioinformatic prediction and experimental validation identified PTEN as a direct target of miR-183, confirmed by dual-luciferase assays. In vitro, miR-183 inhibition increased PTEN expression, reduced AKT phosphorylation, promoted podocyte proliferation, and suppressed apoptosis (upregulation of Bcl-2 and downregulation of cleaved-caspase-3). These effects were abolished upon PTEN knockdown. Conclusions:miR-183 aggravates DN by targeting PTEN and activating the AKT signaling pathway. Inhibition of miR-183 improves renal function and reduces podocyte apoptosis, suggesting miR-183 as a potential therapeutic target for DN.

OBJECTIVE: To explore the impact of age on the genetic variant spectrum and prognosis of patients with previously untreated Diffuse large B-cell lymphoma (DLBCL). METHODS: A retrospective analysis was conducted on the clinical data and follow-up information of 254 previously untreated DLBCL patients from 14 hospitals in the Jiangsu Cooperative Lymphoma Group (JCLG) enrolled from July 2018 and July 2023. Following extraction of DNA from tumor tissue samples, next-generation sequencing (NGS) technique was employed to analyze the genetic variant spectrum of the DLBCL patients, with an evaluation of the relationship between age and genetic variants as well as prognosis. This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Nantong University (Ethics No.: 2023-K048-01). RESULTS: The median age of the 254 DLBCL patients was 62 years old, with 55% of patients aged 60 years or above. Clinical evaluation showed that younger (< 60 years) patients had higher complete response (CR) (70% vs. 59%), and objective response rate (ORR) (88% vs. 79%) than older patients, though the difference between the two groups was not statistically. Survival analysis indicated that both the five-year overall survival (OS) (82.7% vs. 71.7%, P = 0.006) and progression-free survival (PFS) (70.6% vs. 50.2%, P < 0.05) rates were significantly higher in younger patients. NGS showed that 99.6% of the patients harbored genetic variants, with PIM1, KMT2D, TP53, MYD88, and CD79B being the most common genes. Age significantly affected the variant frequency of certain genes, with MYC variants serving an adverse prognostic factor for OS in younger patients (P = 0.002), while TP53 (P = 0.024) and BCL2 (P = 0.002) variants significantly impacted OS in older patients. Prognostic analysis identified age ≥ 60 years (HR = 3.439, 95%CI: 1.318~9.874), presence of B symptoms (HR = 2.871, 95%CI = 1.133~7.307), and elevated lactate dehydrogenase (HR = 3.528, 95%CI = 1.231~10.66) as independent adverse prognostic factors. CONCLUSION Age, genetic variants, and clinical factors may significantly affect the prognosis of the DLBCL patients. Younger patients have better survival compared to older patients. Variants of the MYC, BCL2, and TP53 genes are closely associated with poor prognosis.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Middle Aged ; Female ; Male ; Retrospective Studies ; Aged ; Prognosis ; Adult ; Aged, 80 and over ; High-Throughput Nucleotide Sequencing ; Young Adult ; Adolescent ; Genetic Variation

Objective:To investigate the distribution characteristics of CTLA-4 on the surface of CD4+T cells in patients with breast cancer at different stages,and to evaluate its predictive value for the efficacy of radical mastectomy.Methods:A retrospective study was conducted on 200 breast cancer patients admitted between January 2020 and December 2022.Patients were divided into four groups based on clinical staging:stage Ⅰ(64 cases),stage Ⅱ(57 cases),stage Ⅲ(43 cases),and stage Ⅳ(36 cases).The clinical pathological characteristics of the four groups were compared,and the expression level of CTLA-4 on the surface of CD4+T cells in peripheral venous blood(CTLA-4+CD4+)was detected.Patients were divided into a poor prognosis group(52 cases)and a good prognosis group(148 cases)based on their prognosis,and the clinical pathological characteristics of the two groups were compared.A stratified regression model was used to analyze the relationship between CTLA-4+CD4+expression levels and different clinical characteristics.Logistic regression analysis was employed to evaluate the independent correlation between CTLA-4+CD4+expression levels and the risk of poor prognosis.An unconditional logistic regression model was used to analyze the multiplicative interaction effect of CTLA-4+CD4+expression levels and clinical staging on prognosis prediction.Restricted cubic spline analysis was used to investigate the relationship between CTLA-4+CD4+expression levels and poor patient prognosis.Results:Significant differences were observed in tumor diameter,ECOG score,lesion multiplicity,lymph node metastasis,tumor differentiation degree,ER,PR,HER2,Ki-67,CA125,CA153,and CEA among patients with different clinical stages(P<0.05).Significant differences were also observed in CD3+,CD4+,CD8+,and CTLA-4+CD4+(P<0.05).As the clinical stage increased,the proportions of CD3+,CD4+,and CD8+decreased,while the proportion of CTLA-4 on the surface of CD4+T cells increased(P<0.05).Significant differences were observed in clinical stage,tumor diameter,lymph node metastasis,tumor differentiation degree,ECOG score,ER,PR,HER2,and CTLA-4+CD4+among patients with different prognosis groups(P<0.05).Hierarchical regression analysis indicated that clinical stage,tumor diameter,lymph node metastasis,tumor differentiation degree,ECOG score,and HER2 had a significant positive impact on CTLA-4+CD4+(P<0.05),while ER and PR had a significant negative impact on CTLA-4+CD4+(P<0.05).Logistic regression analysis showed that CTLA-4+CD4+was positively correlated with poor prognosis(P<0.05).CTLA-4+CD4+and clinical stage had multiplicative and additive interactions on prognosis.Regardless of the clinical stage,CTLA-4+CD4+on the surface of CD4+T cells was significantly positively correlated with poor prognosis.Conclusion:The expression level of CTLA-4+CD4+in patients with advanced breast cancer is significantly elevated,playing a crucial role in the clinical pathological characteristics of breast cancer.An elevated level may indicate a poor prognosis.

Objective:To fine-tune the mT5 (massively multilingual pre-trained text-to-text transformer) large language model, automatically generate report conclusions for teaching purposes from chest CT image descriptions, and assess the quality of automatically generated conclusions.Methods:The training set included 3 000 high-quality physical examination chest CT reports from one hospital, and the external validation set consisted of 600 physical examination chest CT reports from two other hospitals. Experienced radiology teaching physicians assessed the consistency between the generated conclusions and the original physician-written conclusions in the external validation set using a 5-point Likert scale across five linguistic indicators (correctness of examination information, correctness of lesion detection, standardization of terminology, applicability of the conclusions, and simplicity of conclusions). Using the original report conclusions as the reference, the accuracy of the conclusions generated based on the external validation set in describing four major thoracic conditions (pulmonary nodules, pneumonia, emphysema, pleural effusion) was evaluated. Perform chi square test using SPSS 25.0.Results:In the external validation set, the mean consistency score between the generated conclusions and the original conclusions given by the radiology teaching physicians was >4 points, indicating agreement with the original conclusions. In the generated conclusions, the description of the four major thoracic conditions demonstrated 0.95-1.00 (95% CI=0.91-1.00) accuracy, 0.76-1.00 (95% CI=0.59-1.00) sensitivity, and 0.97-1.00 (95% CI=0.91-1.00) specificity. Conclusions:The chest CT report conclusion generation system based on the mT5 large language model demonstrated high accuracy and is expected to provide immediate and efficient automated guidance for standardized residency training.