1.Staged Characteristics of Mitochondrial Energy Metabolism in Chronic Heart Failure with Heart-Yang Deficiency Syndrome and Prescription Intervention from Theory of Reinforcing Yang
Zizheng WU ; Xing CHEN ; Lichong MENG ; Yao ZHANG ; Peng LUO ; Jiahao YE ; Kun LIAN ; Siyuan HU ; Zhixi HU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(5):129-138
Chronic heart failure (CHF) is a complex clinical syndrome caused by ventricular dysfunction, with mitochondrial energy metabolism disorder being a critical factor in disease progression. Heart-Yang deficiency syndrome, as the core pathogenesis of CHF, persists throughout the disease course. Insufficiency of heart-Yang leads to weakened warming and propelling functions, resulting in the accumulation of phlegm-fluid, blood stasis, and dampness. This eventually causes Qi stagnation with phlegm obstruction and blood stasis with water retention, forming a vicious cycle that exacerbates disease progression. According to the theory of reinforcing Yang, the clinical experience of the traditional Chinese medicine (TCM) master Tang Zuxuan in treating CHF with heart-Yang deficiency syndrome, and achievements from molecular biological studies, this study innovatively proposes an integrated research framework of "TCM syndrome differentiation and staging-mitochondrial metabolism mechanisms-intervention with Yang-reinforcing prescriptions" which is characterized by the integration of traditional Chinese and Western medicine. Heart-Yang deficiency syndrome is classified into mild (Stage Ⅰ-Ⅱ), severe (Stage Ⅲ), and critical (Stage Ⅳ) stages. The study elucidates the precise correlations between the pathogenesis of each stage and mitochondrial metabolism disorders from theoretical, pathophysiological, and therapeutic perspectives. The mild stage is characterized by impaired biogenesis and substrate-utilization imbalance, corresponding to heart-Yang deficiency and phlegm-fluid aggregation. Linggui Zhugantang and similar prescriptions can significantly improve the expression of peroxisome proliferator-activated receptor gamma co-activator-1α(PGC-1α)/silent information regulator 2 homolog 1 (SIRT1) and ATPase activity. The severe stage centers on oxidative stress and structural damage, reflecting Yang deficiency with water overflow and phlegm-blood stasis intermingling. At this stage, Zhenwu Tang and Qiangxin Tang can effectively mitigate oxidative stress damage, increase adenosine triphosphate (ATP) content, and repair mitochondrial structure. The critical stage arises from calcium overload and mitochondrial disintegration, leading to the collapse of Yin-Yang equilibrium. At this stage, Yang-restoring and crisis-resolving prescriptions such as Fuling Sini Tang and Qili Qiangxin capsules can inhibit abnormal opening of the mitochondrial permeability transition pore (MPTP), reduce cardiomyocyte apoptosis rate, and protect mitochondrial function. By summarizing the characteristics of mitochondrial energy metabolism disorders at different stages of CHF, this study explores the application of the theory of reinforcing Yang in treating heart-Yang deficiency syndrome and provides new insights for the clinical diagnosis and treatment of CHF.
2.Danhong Injection Regulates Ventricular Remodeling in Rat Model of Chronic Heart Failure with Heart-Blood Stasis Syndrome via p38 MAPK/NF-κB Signaling Pathway
Zizheng WU ; Xing CHEN ; Jiahao YE ; Lichong MENG ; Yao ZHANG ; Junyu ZHANG ; Zhixi HU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(5):149-159
ObjectiveTo explore the mechanism of ventricular remodeling mediated by the p38 mitogen-activated protein kinase (MAPK)/nuclear factor kappa B (NF-κB) signaling pathway in the rat model of chronic heart failure (CHF) with heart-blood stasis syndrome, as well as the intervention effect of Danhong injection. MethodsIn vivo experiment: SPF-grade male SD rats were assigned via the random number table method into 4 groups: Sham operation, model, captopril (8.8 mg·kg-1), and Danhong injection (6.0 mL·kg-1). The model of CHF with heart-blood stasis syndrome was established by abdominal aortic constriction, and the sham operation group only underwent laparotomy without constriction. All the groups were treated continuously for 15 days. The tongue color of rats was observed. Echocardiography, hemorheology, heart mass index (HMI), and left ventricular mass index (LVMI) were measured. Hematoxylin-eosin (HE) staining and Masson staining were performed to observe the pathological and fibrotic changes of the myocardial tissue. Enzyme-linked immunosorbent assay (ELISA) was employed to quantify the levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), interleukin-6 (IL-6), angiotensin Ⅱ (AngⅡ), tumor necrosis factor-α (TNF-α), and Creactive protein (CRP) in the serum, as well as the levels of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) in the myocardial tissue. Western blot was used to quantify the protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue. In vitro experiment: H9C2 cardiomyocytes were treated with 1×10-6 mol·L-1 AngⅡ to establish a model of myocardial hypertrophy. H9C2 cardiomyocytes were allocated into normal, model, inhibitor + Danhong injection, Danhong injection (20 mL·L-1), and inhibitor (SB203580, 5 μmol·L-1) groups. CCK-8 assay was used to detect the viability of H9C2 cardiomyocytes. Rhodamine-labeled phalloidin staining was used to reveal the area of cardiomyocytes. Real-time PCR was performed to determine the mRNA levels of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP). Western blot was used to assess the protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65. ResultsIn vivo experiment: Compared with the sham operation group, the model group showed purplish-dark tongue with decreased R, G, B values of the tongue surface (P<0.01), increased whole blood viscosity (at low, medium, and high shear rates) (P<0.01), decreased left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) (P<0.01), increased left ventricular end-diastolic diameter (LVIDd), left ventricular end-systolic diameter (LVIDs), and left ventricular posterior wall thickness at end-diastole (LVPWd) (P<0.01), raised LVMI and HMI (P<0.01), and elevated levels of NT-proBNP, TNF-α, IL-6, and CRP in the serum and MMP-2 and MMP-9 in the myocardial tissue (P<0.01). The HE and Masson staining of the myocardial tissue showed compensatory myocardial hypertrophy, fibrosis, and massive inflammatory cell infiltration in the model group. Additionally, the model group presented up-regulated protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue (P<0.01). Compared with the model group, each administration group showed increased R, G, B values of the tongue surface (P<0.05, P<0.01), decreased whole blood viscosity (at low, medium, and high shear rates) (P<0.05, P<0.01), increased LVEF and LVFS (P<0.01), decreased LVIDd, LVIDs, and LVPWd (P<0.05, P<0.01), declined LVMI and HMI (P<0.05, P<0.01), and lowered levels of NT-proBNP, TNF-α, IL-6, and CRP in the serum and MMP-2 and MMP-9 in the myocardial tissue (P<0.01). HE and Masson staining showed alleviated compensatory myocardial hypertrophy, reduced fibrosis, and decreased expression of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue (P<0.01). In vitro experiment: When the concentration of Danhong injection reached 20 mL·L-1, the survival rate of H9C2 cardiomyocytes was the highest (P<0.01). Compared with the normal group, the model group showed up-regulated mRNA levels of ANP and BNP (P<0.01), increased relative cell surface area (P<0.01), and raised protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 (P<0.01). Compared with the model group, each administration group showed down-regulated mRNA levels of ANP and BNP (P<0.01), reduced relative cell surface area (P<0.05, P<0.01), and down-regulated protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 (P<0.05, P<0.01). ConclusionDanhong injection can regulate ventricular remodeling through the p38 MAPK/NF-κB pathway, thereby exerting a protective effect on the rat model of CHF with heart-blood stasis syndrome.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
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.
4.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
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.
5.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
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.
6.The Connotation and Application of Toxicity Theory in Traditional Chinese Medicine from the Perspective of The Inner Canon of Yellow Emperor (《黄帝内经》)
Xiyan ZHANG ; Yurui XING ; Cuijuan LI ; Yong HU
Journal of Traditional Chinese Medicine 2025;66(15):1517-1521
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.
7.LIU Xing's experience in treatment of peripheral facial paralysis with combined therapy of acupotomy, cupping and herbal medication.
Dunlin FANG ; Siyi LI ; Wanchun HU ; Tong LIU ; Changchang ZHANG ; Pengpeng PENG ; Junjie ZHANG ; Xing LIU
Chinese Acupuncture & Moxibustion 2025;45(11):1639-1644
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
8.Associations of systemic immune-inflammation index and systemic inflammation response index with maternal gestational diabetes mellitus: Evidence from a prospective birth cohort study.
Shuanghua XIE ; Enjie ZHANG ; Shen GAO ; Shaofei SU ; Jianhui LIU ; Yue ZHANG ; Yingyi LUAN ; Kaikun HUANG ; Minhui HU ; Xueran WANG ; Hao XING ; Ruixia LIU ; Wentao YUE ; Chenghong YIN
Chinese Medical Journal 2025;138(6):729-737
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
9.Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.
Jia-Ying HU ; Zhen-Zhe LIN ; Li DING ; Zhi-Xing ZHANG ; Wan-Ling HUANG ; Sha-Sha HUANG ; Bin LI ; Xiao-Yan XIE ; Ming-De LU ; Chun-Hua DENG ; Hao-Tian LIN ; Yong GAO ; Zhu WANG
Asian Journal of Andrology 2025;27(2):254-260
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*
10.Genetic and clinical characteristics of children with RAS-mutated juvenile myelomonocytic leukemia.
Yun-Long CHEN ; Xing-Chen WANG ; Chen-Meng LIU ; Tian-Yuan HU ; Jing-Liao ZHANG ; Fang LIU ; Li ZHANG ; Xiao-Juan CHEN ; Ye GUO ; Yao ZOU ; Yu-Mei CHEN ; Ying-Chi ZHANG ; Xiao-Fan ZHU ; Wen-Yu YANG
Chinese Journal of Contemporary Pediatrics 2025;27(5):548-554
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

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