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.

Based on the theory of toxin in The Inner Canon of Yellow Emperor （《黄帝内经》）， this paper explores the concept and connotation of toxin from several aspects， including medicinal toxicity， pathogenic toxicity， pathoge-nesis and treatment of toxin pathogen. It explores the mechanism and significance of using toxin substances in curing and inducing diseases， sorts out the etiological and pathological evolution of toxic pathogens， clarifies the derivation and differentiation process from external toxins to internal toxins， and elucidates the interactions between toxin and other pathogenic factors such as phlegm， stasis， dampness， and fire. It further distinguishes the logical hierarchy of toxin caused by metabolic disorders such as sugar， fat， and drowning， clarifies that the essence of the etiology of "hidden toxin"， and determines the corresponding treatment principles and methods for toxic pathogens. It establishes a theoretical framework of traditional Chinese medicine toxic pathogen theory， providing theoretical basis for the clinical treatment of many diseases.

This article introduces Professor LIU Xing's clinical experience in treatment of peripheral facial paralysis at the recovery and sequelae stages with the combination of acupotomy, cupping and herbal medication. Based on the analysis of etiology and pathogenesis of peripheral facial paralysis, Professor LIU believes that "invasion of pathogenic wind to collaterals and obstruction of qi and blood" is crucial. Therefore, the treatment focuses on "dispelling wind and harmonizing blood". The compound therapeutic mode is proposed, with acupotomy, cupping and herbal decoction involved, in which, "three-step sequential method of acupotomy" is predominated. Firstly, in the prone position, five "feng" (wind) points are stimulated in patient, Fengfu (GV16), Fengchi (GB20), Yifeng (TE17), Bingfeng (SI12) and Fengmen (BL12). Secondly, in the lateral position, three-facial points are stimulated (FaceⅠneedle: Yangbai [GB14]-Yuyao [EX-HN4]; Face Ⅱ needle: Sibai [ST2]-Quanliao [SI18]; Face Ⅲ needle: Jiache [ST6]-Dicang [ST4]) to restore the deviated facial muscles. Finally, in the supine, two Dantian points are stimulated on the forehead and chest, respectively (upper Dantian: Yintang [GV24⁺], middle Dantian: Danzhong [CV17]), to regulate qi and blood. As the adjunctive therapies, cupping is used to remove stasis, and herbal decoction is to harmonize the body interior. In view of holistic regulation, the treatment is administered in accordance with the affected meridians, so as to expel wind, remove obstruction in collaterals and regulate qi and blood.
Humans ; Facial Paralysis/drug therapy* ; Drugs, Chinese Herbal/administration & dosage* ; Acupuncture Therapy ; Male ; Female ; Middle Aged ; Adult ; Combined Modality Therapy ; Acupuncture Points ; Cupping Therapy ; Aged ; Young Adult

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

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

OBJECTIVES: To evaluate the strategies and outcomes of assisted reproductive technology (ART) for fertility preservation and promotion in women with malignant tumors, and to analyze ART outcomes across different tumor types. METHODS: We conducted a retrospective analysis of female patients who underwent ART for fertility preservation or treatment at the Reproductive Center of the Women's Hospital, Zhejiang University School of Medicine, between January 1, 2018, and December 31, 2023. A total of 163 ART-aided pregnancy patients with malignant tumors were included in the case group, among which 6 patients underwent embryo cryopreservation for fertility preservation before radiotherapy or chemotherapy. Additionally, 11 unmarried women underwent oocyte cryopreservation due to borderline ovarian tumors, ovarian cancer, breast cancer, or hematological malignancies. The control group was selected from women without a history of malignant tumors who received ART treatment during the same period, using propensity score matching at a ratio of 1∶2, resulting in 326 cases. Data were collected through the reproductive medical record system and telephone follow-up (as of October 31, 2024). Baseline characteristics, controlled ovarian hyperstimulation parameters, laboratory indicators, and pregnancy outcomes were compared between case and control groups and among patients with different tumor types, and the tumor recurrence of the patients was followed up. RESULTS: Patients in the case group had significantly lower ovarian reserve (AMH, AFC) and a higher proportion of diminished ovarian reserve compared to the control group (all P<0.01). Regarding the ovulation induction protocol, the proportion of patients using the minimal stimulation protocol in the case group was significantly higher than that in the control group (29.45% vs. 12.88%, P<0.01), and the total dosage of gonadotropins used was lower (P<0.01). In terms of assisted reproductive outcomes, there were no statistically significant differences between the two groups in the number of retrieved oocytes, number of high-quality embryos, fertilization rate, cumulative pregnancy rate, cumulative live birth rate, or miscarriage rate (all P>0.05). However, the number of oocyte retrieval cycles and embryo transfer cycles required to achieve a live birth outcome in the case group were significantly higher than those in the control group (both P<0.05). Subgroup analysis showed that there were no significant differences in cumulative pregnancy rate and live birth rate among patients with different tumor types (thyroid cancer, reproductive system tumors, breast cancer, lung cancer). Nevertheless, lung cancer patients had the lowest ovarian reserve and required the most oocyte retrieval cycles due to their older age; breast cancer patients had a relatively lower fertilization rate partially because some of them were complicated with male factors. A follow-up of 154 tumor patients (with a follow-up rate of 88.5%) revealed that 6 patients (4.20%) had tumor recurrence, and 1 breast cancer patient died due to tumor recurrence. None of the 11 unmarried patients who had undergone oocyte cryopreservation had used the cryopreserved oocytes for assisted pregnancy yet, and 1 patient who had undergone fertility preservation died due to tumor recurrence. CONCLUSIONS Women of reproductive age with malignant tumors are at risk of diminished fertility. ART can effectively preserve and promote fertility, enabling favorable pregnancy and live birth outcomes. It is recommended to initiate a multidisciplinary assessment promptly prior to radiotherapy/chemotherapy and formulate an individualized ART regimen for fertility preservation or promotion, so as to achieve reproductive goals or safeguard future fertility potential.

OBJECTIVE: To explore the relationship between serum chloride levels and prognosis in patients with hepatic coma in the intensive care unit (ICU). METHODS: We analyzed 545 patients with hepatic coma in the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Associations between serum chloride levels and 28-day and 1-year mortality rates were assessed using restricted cubic splines (RCSs), Kaplan-Meier (KM) curves, and Cox regression. Subgroup analyses, external validation, and mechanistic studies were also performed. RESULTS: A total of 545 patients were included in the study. RCS analysis revealed a U-shaped association between serum chloride levels and mortality in patients with hepatic coma. The KM curves indicated lower survival rates among patients with low chloride levels (< 103 mmol/L). Low chloride levels were independently linked to increased 28-day and 1-year all-cause mortality rates. In the multivariate models, the hazard ratio ( HR) for 28-day mortality in the low-chloride group was 1.424 (95% confidence interval [ CI]: 1.041-1.949), while the adjusted hazard ratio for 1-year mortality was 1.313 (95% CI: 1.026-1.679). Subgroup analyses and external validation supported these findings. Cytological experiments suggested that low chloride levels may activate the phosphorylation of the NF-κB signaling pathway, promote the expression of pro-inflammatory cytokines, and reduce neuronal cell viability. CONCLUSION Low serum chloride levels are independently associated with increased mortality in patients with hepatic coma.
Humans ; Male ; Female ; Middle Aged ; Intensive Care Units ; Prognosis ; Chlorides/blood* ; Aged ; Coma/blood* ; Adult