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.

Hepatocellular carcinoma （HCC） is the sixth most common cancer in the world. In recent years， the clinical early diagnosis and treatment protocols of HCC have been improved， whereas the prognosis of patients is still not satisfactory， which is due to the fact that the mechanism of HCC development has not been fully elucidated. Therefore， it is of great significance to explore the molecular mechanisms and key regulatory links of hepatocellular carcinoma development to further improve the diagnosis and treatment of HCC in China. Epigenetics has become a research hotspot because of its reversibility and easy regulation. According to relevant studies， HCC involves the accumulation of multiple genetic and epigenetic changes during the initiation， promotion， and progression stages. HCC is categorized as infantile malnutrition with accumulation， hypochondriac pain， tympan ites， and abdominal mass in traditional Chinese medicine （TCM）. In the treatment of HCC， TCM with low toxicity， multi-targets， and multi-mechanisms can inhibit tumor growth， alleviate the clinical symptoms， and enhance the quality of life of the patients. Chinese medicines and their active ingredients exert anti-HCC effects through epigenetic regulation of DNA methylation， histone modification， and non-coding RNA. Abnormal gene expression due to epigenetic regulation disorders is involved in all stages of HCC development. There are few studies on epigenetic regulation in TCM treatment of HCC， and there is still much room for development in basic and clinical trials. This paper reviews the mechanism of epigenetic regulation in HCC and summarizes the experimental results of TCM research on the related mechanism， with a view to providing a theoretical basis for future research on the mechanism of HCC development and clinical diagnosis and treatment of hepatocellular carcinoma with TCM.

Objective To investigate the diagnostic potential of low-dose computed tomography angiography(CTA)and global biomimetic three-dimensional model reconstruction technology in patients with arterial erectile dysfunction(ED).Methods A total of 136 patients with ED were selected.Digital subtraction angiography(DSA)was performed on all patients as per their treatment requirements and conditions,following ultrasound and CTA examination,and 75 patients finally completed DSA examination.All patients with International Index for Erectile Function(IIEF5)score ranged from 1 to 20.All patients received immediate ultrasound monitoring after injection of alprostadil 10 μg and underwent CTA examination.DSA was conducted at a minimum interval of 72 h.The global biomimetic three-dimensional model tool was used to reconstruct the CTA data and evaluate the stenosis of the pudendal vessels.The diagnostic efficacy of CTA examination,ultrasound and DSA examination were compared and calculated.Results A total of 1 632 vessels were evaluated in 136 patients,including 155 stenoses.DSA was performed in 75 patients.A total of 900 vessels were evaluated,of which 88 were stenoses.Compared with the results of CTA,ultrasound and DSA,the average stenosis scores of all measured vessels were not statistically significant(P＜0.05).The correlation between CTA and ultrasound(r2=0.939 9,P＜0.000 1)and DSA(r2=0.944 0,P＜0.000 1)in the evaluation of vascular stenosis were good,and the diagnostic consistency was consistent.Conclusion Low-dose CTA and global biomimetic three-dimensional model reconstruction technology can effectively diagnose pudendal artery stenosis,and can perform all-round reconstruction observation,which is worthy of further clinical application.

OBJECTIVES: Shear wave elastography (SWE) is a novel quantitative elastography technique that can assess the hardness of different tissues. This study introduces a novel shear wave parameter-frequency of mass characteristic (f_mass)-and investigates its correlation, along with other shear wave parameters, with the histopathological features and immunohistochemical (IHC) biomarkers of invasive breast cancer (IBC). The study aims to explore whether SWE can provide useful information for IBC treatment and prognosis. METHODS: With the pathological results as the gold standard, 258 malignant breast lesions were collected, and all patients underwent conventional ultrasound and SWE examinations. The SWE parameters [maximum elastic value (E_max), minimum elastic value (E_min), mean elastic value (E_mean), standard deviation of elastic value of the whole lesion (E_sd)] and f_mass] in the transverse and longitudinal orthogonal sections were measured, and their correlations with the prognostic factors of IBC [including tumor diameters, axillary lymph node (ALN) metastasis, lymphatic vessel invasion (LVI), calcification, histological type, histological grade, and IHC biomarkers (ER, PR, HER-2, Ki-67), and molecular subtypes] were analyzed. The correlations between the SWE parameters of the transverse and longitudinal sections of the tumors with different prognostic factors and the above indicators were analyzed. At the same time, the receiver operating characteristic (ROC) curve was used to analyze the efficacy of f_mass in predicting ER and PR expression. RESULTS: E_mean, E_max, E_sd, and f_mass were correlated with tumor diameters; E_mean, E_max and E_sd were correlated with histological types and histological grades. E_max and E_sd were correlated with ALN metastasis, LVI and pathological types. In the IHC biomarker-labeled masses, f_mass was correlated with ER and PR (both P<0.05), and E_mean, E_max, and E_sd were correlated with HER-2 and Ki-67 (all P<0.05). E_mean, E_max, and f_mass were all correlated with breast cancer subtypes (all P<0.05), and E_mean and E_max were higher in Luminal B [HER-2(+)] breast cancer, while f_mass was lower in HER-2(+) and triple-negative breast cancer. Among the statistically significant prognostic factors, the P values of the transverse sections of the masses were all less than or equal to those of the longitudinal sections. The AUC of f_mass in the transverse sections of the masses for predicting ER and PR expression were 0.73 (95% CI 0.65 to 0.80) and 0.67 (95% CI 0.60 to 0.74), respectively, with the optimal cut-off values being 76.50 and 60.66, the sensitivities being 72.45% and 81.98%, the specificities being 66.13% and 45.35%, and the accuracies being 70.93% and 69.77%, respectively. The AUC of f_mass in the longitudinal sections of the masses for predicting ER and PR expression were 0.74 (95% CI 0.67 to 0.81) and 0.65 (95% CI 0.58 to 0.72), respectively, with the optimal cut-off values being 131.8 and 137.5, the sensitivities being 69.90% and 66.28%, the specificities being 72.58% and 60.47%, and the accuracies being 70.54% and 64.34%, respectively. The f_mass in the transverse sections of the masses was more statistically significant. CONCLUSIONS The poor prognosis factors of IBC are related to high E_mean, E_min, E_max, E_sd, and low f_mass. The f_mass can predict the expression of ER and PR, and the transverse cut data are more meaningful. SWE is helpful for predicting the invasiveness of IBC.
Humans ; Breast Neoplasms/metabolism* ; Female ; Elasticity Imaging Techniques/methods* ; Biomarkers, Tumor/metabolism* ; Middle Aged ; Adult ; Prognosis ; Immunohistochemistry ; Neoplasm Invasiveness ; Receptor, ErbB-2/metabolism* ; Aged ; Lymphatic Metastasis ; Receptors, Estrogen/metabolism* ; Receptors, Progesterone/metabolism* ; Ki-67 Antigen/metabolism*

ObjectiveTo investigate the protective effect of cytochrome P4502D6 （CYP2D6） and cytochrome P4503A4 （CYP3A4）， key enzymes of drug metabolism in liver， on acute liver injury in water extract of Glycyrrhizae Radix et Rhizoma （WEOGRR）. MethodHealthy male Kunming mice were divided into normal group， model group， WEOGRR low-， medium- and high-dose groups （5， 10， 15 g·kg^-1·d^-1） and positive drug group （diammonium glycyrrhizinate， 75 mg·kg^-1·d^-1）， with 10 in each group. One week after preventive administration， acute liver injury model was induced by single intragastric administration of 270 mg·kg^-1 Tripterygium Glycosides tablets， and samples were collected after 18 h. The pathological changes of liver were observed by hematoxylin-eosin （HE） staining. Serum liver function indexes including alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， γ-glutamyl transpeptadase （γ-GT）， alkaline phosphatase （ALP）， and total bilirubin （TBIL） as well as the levels of oxidative stress indexes including malondialdehyde （MDA） and superoxide dismutase （SOD） in hepatocytes were determined by biochemical method. Real-time polymerase chain reaction （Real-time PCR） and Western blot were performed to detect the mRNA and protein expression levels of CYP2D6 and CYP3A4， respectively. ResultCompared with normal group， model group had significant hepatocyte swelling and inflammatory cell infiltration （P<0.01）， increased AST， ALT， γ-GT， ALP and TBIL （P<0.05）， elevated MDA and decreased SOD （P<0.01） as well as down-regulated mRNA and protein expression levels of CYP2D6 and CYP3A4 （P<0.05）. Compared with the model group， the normal group had intact liver structure without obvious abnormality， and the WEOGRR groups and positive drug group presented alleviated hepatocyte swelling and inflammatory cell infiltration （P<0.01）， reduced AST， ALT， γ-GT， ALP and TBIL （P<0.01）， lowered MDA and increased SOD （P<0.01） as well as up-regulated expression levels of CYP2D6 and CYP3A4 （P<0.01）. ConclusionThe protective effect of WEOGRR on acute liver injury induced by Tripterygium glycosides tablets may be related to reducing the contents of AST， ALT， γ-GT， ALP and TBIL in serum， inhibiting MDA and increasing the activity of SOD in liver cells， and enhancing the activities of CYP2D6 and CYP3A4， thus accelerating the metabolism of toxic substances.

Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.

Objective:To investigate the value of artificial intelligence (AI) cytomorphologic analysis system in the cytomorphological diagnosis and therapeutic evaluation of acute myeloid leukemia (AML).Methods:Bone marrow smear samples were collected from 150 patients with newly diagnosed and treated acute myeloid leukemia who were inpatients and outpatients at the Department of Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College from June 1, 2021 to July 31, 2022 for retrospective analysis. Among them, there were 50 patients in the newly diagnosed group, including 28 males and 22 females, with the onset age of 43.5(32.3,58.8)years. There were 100 patients in the post-treatment group, including 36 males and 64 females, with the onset age of 34.5(23.0,47.0)years. The results from cytomorphology expert were used as the gold standard and the Python 3.6.7 was used for analysis to evaluate the accuracy, sensitivity, and specificity of the AI cytomorphologic analysis system for blast cell recognition in AML diagnosis and treatment.Results:The proportion of blasts in AI analysis of 50 samples in the newly diagnosed group was≥20%, which met the diagnostic criteria of AML. AI analysis of blasts had an accuracy of 90.3%, sensitivity of 85.5%, and specificity of 98.0%. The correlation coefficient between AI and the proportion of blasts analyzed by experts was positively correlated( r=0.882, P<0.001). Meanwhile, in the post-treatment group, the sensitivity and specificity of AI analysis of blasts were 89.7% and 99.2%, respectively. The correlation coefficient between AI and the proportion of blasts analyzed by experts was positively correlated( r=0.957, P<0.001). According to AI analysis data, there are 8 samples in this group whose AI efficacy evaluation results on AML are inconsistent with expert analysis. Conclusion:AI cytomorphologic analysis system has high accuracy, sensitivity and specificity for blast cell recognition in AML morphological diagnosis and therapeutic evaluation.

ObjectiveTo investigate the effect and mechanism of Shenling Baizhusan on the treatment of oligoasthenospermia with hyperuricemia （HUA）. MethodThirty-two male Kunming （KM） mice were randomly divided into blank group （n=6）， model group （n=6）， high-dose Shenling Baizhusan group （n=7）， low-dose Shenling Baizhusan group （n=7）， and febuxostat group （n=6）. Except for the blank group， all other groups received intraperitoneal injection of potassium oxazinate suspension （600 mg·kg^-1） for 7 days. After modeling， the high-dose Shenling Baizhusan group and the low-dose Shenling Baizhusan group were orally administered with 20.14 g·kg^-1 and 10.07 g·kg^-1 of Shenling Baizhusan， respectively. The Febuxostat group was orally administered with 0.25 g·kg^-1 of Febuxostat， while the blank group and model group were orally administered with the same volume of physiological saline. Oral administration was performed once a day for 14 consecutive days， after which samples were collected. Biochemical methods were used to measure serum uric acid （UA）， superoxide dismutase （SOD） and malondialdehyde （MDA） in testicular tissue. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes in testicular tissue and evaluate the spermatogenesis function. Automated sperm analyzer was used to measure sperm density and motility. Single-cell gel electrophoresis （SCGE） was used to assess sperm DNA integrity. Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling （TUNEL） was used to detect testicular cell apoptosis rate. Western blot analysis was performed to measure the protein expression levels of Kelch-like ECH-associated protein 1 （Keap1）， nuclear factor E₂-related factor 2 （Nrf2）， heme oxygenase-1 （HO-1）， B-cell lymphoma-2 （Bcl-2）， Bcl-2-associated X protein （Bax）， and Caspase-3 in testicular tissue. Real-time polymerase chain reaction （PCR） was conducted to evaluate the mRNA expression levels of Keap1， Nrf2， and HO-1 in testicular tissue. ResultCompared with the blank group， the model group showed elevated serum UA level （P<0.01）， decreased testicular spermatogenesis function， sperm density， and motility （P<0.01）， and increased sperm trailing rate and testicular cell apoptosis rate （P<0.01）. Compared with the model group， the high-dose Shenling Baizhusan group showed significant improvements in the above-mentioned indicators （P<0.05， P<0.01）. Additionally， the expression levels of Keap1， Bax， and Caspase-3 in testicular tissue were reduced， while the expression levels of Nrf2， HO-1， and Bcl-2 increased （P<0.05， P<0.01）. The mRNA level of Keap1 decreased （P<0.05， P<0.01）， while the mRNA levels of Nrf2 and HO-1 increased （P<0.05， P<0.01）. ConclusionShenling Baizhusan can significantly improve HUA oligoasthenospermia， and its mechanism may be related to the Nrf2/antioxidant response element （ARE） signaling pathway.