ObjectiveTo investigate the effects and potential mechanisms of Tongmai Yangxin Pills （通脉养心丸） （TYPs） in preventing ischemia-reperfusion （I/R）-induced arrhythmia. MethodsSixty male SD rats were randomly assigned to sham operation group， model group， amiodarone group， low-dose and high-dose TYPs group， with 12 rats in each group. The sham operation group and the model group received 10 g/（kg·d） normal saline by gavage， the amiodarone group received 60 mg/（kg·d） amiodarone， and the low-dose and high-dose TMP groups received 1 g/（kg·d） and 2 g/（kg·d） TYPs solution respectively， for 21 days， administered twice daily. On the day after the last administration， the I/R model was established in the model and medication groups by ligation of the left anterior descending coronary artery with a cannula， while the sham operation group underwent the same procedure without ligation. Electrocardiogram recordings were continuously monitored throughout the modeling process. Heart rate was recorded at five time points， before ischemia （t-0）， 5-10 min after ischemia （t-1）， 10-15 min after ischemia （t-2）， 15-30 min after ischemia （t-3）， and during the first 2 min of reperfusion （t-4）； the incidence of arrhythmia including ventricular premature beats （VPB）， ventricular tachycardia （VT）， and ventricular fibrillation （VF） was recorded； arrhythmia scores were calculated. After 24 hours of reperfusion， left ventricular myocardial tissue was collected. Hematoxylin-eosin （HE） staining was performed to observe pathological changes. RT-PCR was used to detect the mRNA expression of microRNA-1 （miRNA-1）， microRNA-133a （miRNA-133a）， and potassium （K⁺） and calcium （Ca²⁺） ion channel-related genes including KCND2， KCNH2， KCNE2， KCNQ1， KCNE1， KCNJ2， CACNA1C， and CACNB1. Western blot analysis was used to measure protein levels of transient outward potassium current protein （Kv4.2）， rapidly activating delayed rectifier potassium current protein （HERG）， slowly activating delayed rectifier potassium current protein （KvLQT1）， inward rectifier potassium current protein （Kir2.1）， and L-type calcium channel protein （Cav1.2）. ResultsCompared with sham operation group， the model group showed diffuse myocardial hemorrhage， inflammatory cell infiltration， myocardial necrosis， nuclear pyknosis， vacuolar degeneration， and disrupted myocardial fibers； the model group also exhibited a decreased heart rate （t-1 to t-4）， increased arrhythmia scores， elevated miRNA-1 and miRNA-133a expression， and decreased mRNA expression of KCND2， KCNH2， KCNE2， KCNQ1， KCNE1， KCNJ2， CACNA1C， and CACNB1 in myocardial tissue； additionally， Kv4.2， HERG， KvLQT1， Kir2.1， and Cav1.2 protein levels significantly reduced （P＜0.01）. Compared to the model group， all medication-treated groups showed reduced myocardial damage， including less hemorrhage， reduced inflammatory infiltration， and improved myocardial structure， with the high-dose TYPs group exhibiting the most significant improvement； the amiodarone group and high-dose TYPs group showed a significant increase in heart rate （t-1 to t-4）， lower arrhythmia scores， reduced miRNA-1 and miRNA-133a expression； the high-dose TYPs group exhibited significantly increased mRNA expression levels of KCND2， KCNH2， KCNQ1， KCNJ2， and CACNA1C， as well as elevated protein levels of Kv4.2， HERG， KvLQT1， Kir2.1， and Cav1.2 （P＜0.05 or P＜0.01）. ConclusionTMPs can improve myocardial damage and reduce the incidence of ventricular arrhythmia in I/R rats. The underlying mechanism may be related to the downregulation of miRNA-1 and miRNA-133a gene expression， as well as the upregulation of K⁺ and Ca²⁺ channel-related genes and proteins.

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.

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.

BACKGROUND: The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM. METHODS: A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM. RESULTS: Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses. CONCLUSION The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/immunology* ; Prospective Studies ; Adult ; Inflammation/immunology* ; Glucose Tolerance Test ; Birth Cohort

Randomized controlled trial(RCT) is considered to represent the gold standard for evaluating the efficacy of interventions and has been widely used to evaluate the clinical efficacy of traditional Chinese medicine(TCM). However, there are unique challenges in implementing RCT in TCM. Patients seeking TCM treatment often have preferences for TCM due to the unsatisfactory therapeutic effect of western medicine, their personal intolerance, and their rejection of certain drugs, medical devices, or surgery. Patients are generally reluctant to be randomly assigned to a group, making it challenging to enroll patients in the control group of western medicine during the implementation of RCT in TCM. This has become a prominent problem restricting the implementation of RCT in TCM and needs to be solved urgently. Therefore, this paper introduced commonly used research designs used in solving the problem of enrolling patients in control group during the implementation of RCT in TCM, including Zelen design, partially randomized patient preference trial(PRPP), single-arm objective performance criteria(OPC), cohort studies, single-arm clinical trials using real world data(RWD) alone as the external control group, and the design method based on RWD-augmented control group samples in RCT. The paper outlined the definitions and principles of these methods, evaluated their advantages, disadvantages, and applicable scenarios, and explored their applications in the TCM field, so as to offer insights for solving the difficulty in enrolling patients in the control group during the implementation of RCT in TCM.
Humans ; Medicine, Chinese Traditional/methods* ; Randomized Controlled Trials as Topic/methods* ; Research Design ; Patient Selection ; Drugs, Chinese Herbal/therapeutic use* ; Control Groups

OBJECTIVE: To investigate the effectiveness of digital three-dimensional (3D) assisted unilateral biportal endoscopy (UBE) in the treatment of highly isolated lumbar disc herniation (LDH) with translaminar approach. METHODS: The clinical data of 59 patients who met the selection criteria and underwent UBE treatment due to highly isolated LDH between January 2022 and December 2023 were retrospectively analyzed. Among them, 25 cases were treated with digital 3D assisted translaminar approach (observation group) and 34 cases were treated with interlaminar approach (control group). There was no significant difference in gender, age, disease duration, surgical segment, and preoperative visual analogue scale (VAS) score and Oswestry disability index (ODI) between the two groups ( P>0.05). The operation time, intraoperative blood loss, and lateral articular surface preservation rate were recorded and compared between the two groups. VAS score and ODI were used to evaluate the improvements of pain and function before operation and at 3 and 6 months after operation. The modified MacNab criteria was used to evaluate the effectiveness at last follow-up. RESULTS: One patient in the control group had dural tear, and the other patients had no nerve injury, infection, dural tear, or other related complications. There was no significant difference in operation time and intraoperative blood loss between the two groups ( P>0.05). Patients in both groups were followed up 6-13 months, with an average of 8.3 months. The lateral articular surface preservation rate in the observation group was significantly higher than that in the control group ( P<0.05). Three patients in the observation group and 2 patients in the control group had calf muscle venous thrombosis, which was cured after anticoagulant treatment with rivaroxaban and delayed exercise time. There was no recurrence or second operation during the follow-up period. The VAS score and ODI of the two groups at 3 and 6 months after operation significantly improved when compared with those before operation ( P<0.05). There was no significant difference between the two groups at each time point after operation ( P>0.05). At last follow-up, the effectiveness was evaluated according to the modified MacNab criteria, and there was no significant difference in the evaluation grade and excellent and good rate between the two groups ( P>0.05). CONCLUTION UBE via translaminar approach is safe and effective for the treatment of highly isolated LDH, which is beneficial to protect the facet joint, maintain spinal stability, and reduce soft tissue injury. With the assistance of digital 3D technique, preoperative planning can be performed accurately.
Humans ; Intervertebral Disc Displacement/diagnostic imaging* ; Lumbar Vertebrae/diagnostic imaging* ; Male ; Retrospective Studies ; Female ; Endoscopy/methods* ; Treatment Outcome ; Middle Aged ; Adult ; Imaging, Three-Dimensional ; Operative Time ; Pain Measurement

Trauma is an important cause of death in young- and middle-aged people. Trauma is comprehensive and includes many surgical specialties, and the surgical techniques of these specialties have long been mature. To reduce the mortality and disability rate of trauma patients, it is necessary to improve trauma management. Trauma has attracted attention in China and trauma treatment and care developed rapidly in recent years. To decrease traumatic mortality and disability rates, our team is committed to building an efficient trauma system in Shaanxi province and has successfully developed a trauma limb salvage map to address the high rates of amputation and disability in patients with limb injuries. This article elaborates on the construction experience of a trauma limb salvage map and its application details in Shaanxi province of China.
Humans ; China ; Limb Salvage/methods* ; Wounds and Injuries/surgery* ; Male ; Extremities/injuries* ; Adult ; Amputation, Surgical ; Middle Aged ; Female

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*

OBJECTIVES: To investigate the genomic characteristics and prognostic factors of juvenile myelomonocytic leukemia (JMML) with RAS mutations. METHODS: A retrospective analysis was conducted on the clinical data of JMML children with RAS mutations treated at the Hematology Hospital of Chinese Academy of Medical Sciences, from January 2008 to November 2022. RESULTS: A total of 34 children were included, with 17 cases (50%) having isolated NRAS mutations, 9 cases (27%) having isolated KRAS mutations, and 8 cases (24%) having compound mutations. Compared to children with isolated NRAS mutations, those with NRAS compound mutations showed statistically significant differences in age at onset, platelet count, and fetal hemoglobin proportion (P<0.05). Cox proportional hazards regression model analysis revealed that hematopoietic stem cell transplantation (HSCT) and hepatomegaly (≥2 cm below the costal margin) were factors affecting the survival rate of JMML children with RAS mutations (P<0.05); hepatomegaly was a factor affecting survival in the non-HSCT group (P<0.05). CONCLUSIONS Children with NRAS compound mutations have a later onset age compared to those with isolated NRAS mutations. At initial diagnosis, children with NRAS compound mutations have poorer peripheral platelet and fetal hemoglobin levels than those with isolated NRAS mutations. Liver size at initial diagnosis is related to the prognosis of JMML children with RAS mutations. HSCT can improve the prognosis of JMML children with RAS mutations.
Humans ; Leukemia, Myelomonocytic, Juvenile/therapy* ; Mutation ; Male ; Female ; Child, Preschool ; Retrospective Studies ; Child ; Infant ; GTP Phosphohydrolases/genetics* ; Membrane Proteins/genetics* ; Adolescent ; Hematopoietic Stem Cell Transplantation ; Proportional Hazards Models ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis