Triptolide （TP）， the core active component of the traditional Chinese medicine Tripterygium wilfordii ， exhibits remarkable pharmacological activities including anti-inflammatory， immunosuppressive and anti-tumor effects， and holds broad application prospects in the treatment of major diseases such as autoimmune diseases and malignant tumors. However， TP has a narrow therapeutic window and causes multi-organ toxicities including liver， kidney and reproductive toxicities， which severely restrict its safe clinical application and new drug development. Therefore， toxicity reduction and efficacy enhancement has become a core scientific problem urgently to be solved in this field. This paper systematically reviews the four core strategies for TP toxicity reduction and efficacy enhancement， including structural modification， dosage form improvement， herbal compatibility， and external therapies of traditional Chinese medicine. Among them， structural modification optimizes the toxic and efficacy characteristics of TP from the molecular structure level， with typica l derivatives including （5 R ）-5-hydroxy triptolide， ZT01， PG490-88， etc. Dosage form modification achieves toxicity reduction and efficacy enhancement via targeted and sustained-controlled drug release of diverse delivery systems. It includes triptolide preparations such as nanoparticles， liposomes， microemulsion gels and liquid crystals， possessing favorable clinical transformation potential. The herbal compatibility and external therapies of traditional Chinese medicine conform to the holistic view of traditional Chinese medicine and have a profound clinical application foundation， but their mechanisms of action are insufficiently elucidated， and they lack unified standardized specifications and high-quality evidence-based proof. In the future， we should rely on multi-omics technology to elucidate the toxic and efficacy mechanisms， integrate technologies to optimize preparations， improve the evaluation system and promote clinical transformation.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

OBJECTIVE: To evaluate the effectiveness of minimally invasive reduction and ulna bicortical angulation intramedullary fixation in the management of Bado typeⅠMonteggia fracture in pediatric patients. METHODS: Between August 2018 and August 2020, the clinical data of 15 pediatric patients diagnosed with Bado typeⅠfresh Monteggia fracture were retrospectively analyzed. There were 11 males and 4 females. The left side was implicated in 5 cases, while the right side was involved in 10 cases. The age ranged from 4 to 12 years old. There were a total of 10 cases of upper ulna fractures and 5 cases of middle ulna fractures. Among these, the ulnar fracture line presented as transverse or short oblique in 9 cases, and long oblique or spiral in 6 cases. The pediatric patients underwent treatment utilizing minimally invasive reduction and ulna bicortical angulation intramedullary fixation. The effectiveness of the treatment was assessed based on the Mayo elbow scoring system. RESULTS: The follow-up period for all 15 cases ranged from 6 to 24 months. Among them, the occurrence of needle tail irritation was observed in 3 cases, all of which exhibited satisfactory healing following routine disinfection and dressing change. The other children had no re dislocation of the radial capitulum, no epiphyseal injury, no osteofascial compartment syndrome, elbow instability and other complications. The degree of limitation of daily life, range of motion of joints, pain level and appearance of limbs were recorded at the last follow-up. According to Mayo elbow scoring system, 12 cases were excellent and 3 cases were good. CONCLUSION The minimally invasive reduction and ulna bicortical angulation intramedullary fixation technique is a simple and effective treatment for Bado typeⅠfresh Monteggia fractures in children.
Humans ; Male ; Female ; Child ; Monteggia's Fracture/surgery* ; Child, Preschool ; Minimally Invasive Surgical Procedures/methods* ; Fracture Fixation, Intramedullary/methods* ; Retrospective Studies

OBJECTIVE: To investigate the clinical efficacy and safety of ultrasound-guided closed reduction and internal fixation using Kirschner wire for the treatment of olecranon fractures of the ulna in children. METHODS: Between January 2019 and January 2021, 13 children with olecranon fracture were treated with ultrasound-guided closed reduction and percutaneous Kirschner wire internal fixation, including 10 males and 3 females. The age ranged from 3 to 14 years old. Children with ulnar olecranon fractures were evaluated using the Gicquel scoring system. The clinical evaluation encompassed postoperative pain, functional status, and range of motion, with a maximum score of 15 points. The radiological assessment contributed an additional 4 points. A cumulative score of more than 18 scores was classified as excellent, more than 17 scores as good, more than16 scores as fair, and less than 16 scores as poor. Clinical assessment:A score of 14 indicates excellent performance, a score of 13 reflects good performance, a score of 12 denotes fair performance, and a score of less than 11 signifies poor performance. RESULTS: A total of 13 patients were followed up, with a duration ranging from 6 to 12 months. According to the Gicquel scoring criteria, the comprehensive evaluation of clinical and radiographic findings yielded 10 excellent and 3 good outcomes. Evaluation based solely on clinical findings resulted in 13 excellent outcomes. CONCLUSION Ultrasound-guided percutaneous cross Kirschner wire fixation for children's olecranon fracture has the advantages of less trauma, rapid recovery, less fluoroscopy, and good recovery of elbow function. The clinical effect is satisfactory.
Humans ; Child ; Male ; Female ; Fracture Fixation, Internal/instrumentation* ; Ulna Fractures/physiopathology* ; Bone Wires ; Child, Preschool ; Adolescent ; Olecranon Process/surgery* ; Ultrasonography ; Closed Fracture Reduction/methods* ; Olecranon Fracture

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

OBJECTIVE: To explore the efficacy and apoptosis of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the treatment of acute myeloid leukemia (AML) with ASXL1 mutation. METHODS: The clinical data of 80 AML patients with ASXL1 mutation treated in our hospital from January 2019 to December 2021 were retrospectively analyzed. The clinical characteristics of the patients were summarized, and the therapeutic effect and prognostic factors of allo-HSCT for the patients were analyzed. RESULTS: Among the 80 patients, 38 were males and 42 were females, and the median age was 39(14-65) years. There were 17 patients in low-risk group, 25 patients in medium-risk group and 38 patients in high-risk group. ASXL1 mutation co-occurred with many other gene mutations, and the frequent mutated genes were TET2 (71.25%), NRAS (18.75%), DNMT3A (16.25%), NPM1 (15.00%), CEBPA (13.75%). Among medium and high-risk patients, 29 underwent allo-HSCT, while 34 received chemotherapy. The 2-year overall survival (OS) rate and disease-free survival (DFS) rate of the allo-HSCT group were 72.4% and 70.2%, while those of the chemotherapy group were 44.1% and 34.0%, respectively. The statistical analysis showed significant differences between the two groups (both P < 0.01). Multivariate analysis showed that age at transplantation >50- years and occurrence of acute graft-versus-host disease after transplantation were poor prognostic factors for OS and DFS in transplantation patients. CONCLUSION Allo-HSCT can improve the prognosis of AML patients with ASXL1 mutation.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Middle Aged ; Mutation ; Adult ; Repressor Proteins/genetics* ; Adolescent ; Retrospective Studies ; Aged ; Nucleophosmin ; Young Adult ; Transplantation, Homologous ; Prognosis ; Survival Rate

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective:To report the follow-up status of patients participating phase Ⅲ clinical trial (ZGDD3) of Donafenib tosilate (abbreviated as Donafenib) in the treatment of progressive radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC), and to explore its efficacy, safety and prognostic factors.Methods:This study was a randomized controlled trial, and the clinicopathological data and follow-up results of 29 patients (16 males, 13 females, age 40-68 years) who participated in the clinical trial ZGDD3 between August 2018 and March 2021 were analyzed. Patients were divided into Donafenib group and placebo group using the central dynamic randomization method with the ratio of 2∶1. Adverse reactions (AE) during the trial were observed. Independent-sample t test, Mann-Whitney U test and Fisher exact test were used to analyze the differences of baseline characteristics between the two groups. Progression-free survival (PFS) and overall survival (OS) were followed up. Kaplan-Meier method was used to draw the survival curve (log-rank test) and Cox regression analysis was used to analyze the prognostic factors. Results:There were 22 patients in Donafenib group and 7 patients in placebo group. There were no significant differences of baseline characteristics between the two groups ( t values: -0.68, Z values: from -1.47 to -0.56, all P>0.05). The follow-up was 32.07(21.07, 49.85) months. During the trial, drug-related AEs occurred in all patients in Donafenib group, mostly was grade Ⅰ-Ⅱ, no grade Ⅳ or Ⅴ AEs were found. The median PFS was significantly longer in Donafenib group than that in placebo group (13.23 vs 4.03 months; χ2=9.68, P=0.002), and the median OS was 55.00 and 24.30 months respectively ( χ2=2.07, P=0.150). Metastasis to less common sites was the independent risk factor for OS (hazard ratio ( HR)=6.789, 95% CI: 1.272-36.246, P=0.025). Conclusions:Donafenib shows good clinical application in the treatment of RAIR-DTC, demonstrating good safety and efficacy. Metastasis to less common sites is closely related to OS.

Objective:To explore the risk factors for malnutrition after a traumatic brain injury and to construct a model which usefully predicts that risk.Methods:This was a retrospective study of 374 patients with a craniocerebral injury for whom the relevant clinical data were available. Based on their nutritional status, they were stratified into a malnutrition group ( n=220) and a control group ( n=154). Univariate and multivariate logistic regressions were evaluated seeking to identify the independent risk factors associated with malnutrition, and a prediction model was constructed based on the results. The model′s discrimination ability and accuracy were assessed using a receiver operating characteristics (ROC) curve. Results:A total of 220 patients (58.8%) developed malnutrition. Multifactorial logistic regression analysis showed that the independent risk factors for malnutrition were: age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8, or a Barthel index ≤40. In the ROC curve analysis, the area under the curve quantifying the model′s ability to predict malnutrition was 0.924 (95% CI: 0.896, 0.951), with a sensitivity of 0.868 and a specificity of 0.857, indicating its good prediction performance. Conclusions:Age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8 or a Barthel index ≤40 are independent predictors of malnutrition after a traumatic brain injury. The prediction model constructed based on those risk factors has demonstrated useful predictive power for malnutrition.