1.Structure and Function of GPR126/ADGRG6
Ting-Ting WU ; Si-Qi JIA ; Shu-Zhu CAO ; De-Xin ZHU ; Guo-Chao TANG ; Zhi-Hua SUN ; Xing-Mei DENG ; Hui ZHANG
Progress in Biochemistry and Biophysics 2025;52(2):299-309
GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.
2.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.
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.Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms.
Wen-Yu JIA ; Feng TONG ; Heng-Xu LIU ; Shu-Qin JIN ; Yong-Chao ZHANG ; Chen-Feng ZHANG ; Zhen-Zhong WANG ; Xin ZHANG ; Wei XIAO
China Journal of Chinese Materia Medica 2025;50(2):430-438
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods*
;
Drugs, Chinese Herbal/administration & dosage*
;
Machine Learning
;
Algorithms
;
Humans
;
Quality Control
6.Effects of Saccharomyces cerevisiae chassis cells with different squalene content on triterpenoid synthesis.
Feng ZHANG ; Kang-Xin HOU ; Yue ZHANG ; Hong-Ping HOU ; Yue ZHANG ; Chao-Yue LIU ; Xue-Mi HAO ; Jia LIU ; Cai-Xia WANG
China Journal of Chinese Materia Medica 2025;50(8):2130-2136
Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis*
;
Saccharomyces cerevisiae/genetics*
;
Triterpenes/metabolism*
;
Metabolic Engineering
;
Oleanolic Acid/biosynthesis*
;
Ursolic Acid
7.Identification and expression analysis of seed dehydration tolerance and PLD gene family in Panax medicinal plants.
Chao-Lin LI ; Min HUANG ; Na GE ; Qing-Yan WANG ; Jin-Shan JIA ; Ting LUO ; Jin-Yan ZHANG ; Ping ZHOU ; Jun-Wen CHEN
China Journal of Chinese Materia Medica 2025;50(12):3307-3321
Panax species are mostly valuable medicinal plants. While some species' seeds are sensitive to dehydration, the dehydration tolerance of seeds from other Panax species remains unclear. The phospholipase D(PLD) gene plays an important role in plant responses to dehydration stress. However, the characteristics of the PLD gene family and their mechanisms of response to dehydration stress in seeds of Panax species with different dehydration tolerances are not well understood. This study used seeds from eight Panax species to measure the germination rates and PLD activity after dehydration and to analyze the correlation between dehydration tolerance and seed traits. Bioinformatics analysis was also conducted to characterize the PnPLD and PvPLD gene families and to evaluate their expression patterns under dehydration stress. The dehydration tolerance of Panax seeds was ranked from high to low as follows: P. ginseng, P. zingiberensis, P. quinquefolius, P. vietnamensis var. fuscidiscus, P. japonicus var. angustifolius, P. japonicus, P. notoginseng, and P. stipuleanatus. A significant negative correlation was found between dehydration tolerance and seed shape(three-dimensional variance), with flatter seeds exhibiting stronger dehydration tolerance(r=-0.792). Eighteen and nineteen PLD members were identified in P. notoginseng and P. vietnamensis var. fuscidiscus, respectively. These members were classified into five isoforms: α, β, γ, δ, and ζ. The gene structures, subcellular localization, physicochemical properties, and other characteristics of PnPLD and PvPLD were similar. Both promoters contained regulatory elements associated with plant growth and development, hormone responses, and both abiotic and biotic stress. During dehydration, the PLD enzyme activity in P. notoginseng seeds gradually increased as the water content decreased, whereas in P. vietnamensis var. fuscidiscus, PLD activity first decreased and then increased. The expression of PLDα and PLDδ in P. notoginseng seeds initially increased and then decreased, whereas in P. vietnamensis var. fuscidiscus, the expression of PLDα and PLDδ consistently decreased. In conclusion, the dehydration tolerance of Panax seeds showed a significant negative correlation with seed shape. The dehydration tolerance in P. vietnamensis var. fuscidiscus and dehydration sensitivity of P. notoginseng seeds may be related to differences in PLD enzyme activity and the expression of PLDα and PLDδ genes. This study provided the first systematic comparison of dehydration tolerance in Panax seeds and analyzed the causes of tolerance differences and the optimal water content for long-term storage at ultra-low temperatures, thus providing a theoretical basis for the short-term and ultra-low temperature long-term storage of medicinal plant seeds with varying dehydration tolerances.
Seeds/metabolism*
;
Panax/physiology*
;
Plant Proteins/metabolism*
;
Gene Expression Regulation, Plant
;
Phospholipase D/metabolism*
;
Plants, Medicinal/enzymology*
;
Germination
;
Multigene Family
;
Water/metabolism*
;
Dehydration
;
Phylogeny
8.Guiding significance of intra-articular sagittal reduction in the treatment of tibial plateau fractures.
Jia-Fan ZHANG ; An-Hua LONG ; Da-Cheng HAN ; Zi-Chao JIA ; Ya-Kui ZHANG
China Journal of Orthopaedics and Traumatology 2025;38(1):100-104
Tibial plateau fracture is a fracture involving the proximal articular surface of the tibia, and its injury mechanism is complex, the fracture morphology is different, and it is often accompanied by different degrees of soft tissue injury, which is difficult to diagnose and treat. In recent years, the research hotspot has focused on solving the reduction and fixation of the posterior lateral column of the tibial plateau, because it has been clinically found that the residual sagittal plane after tibial plateau fracture is insufficient reduction or loss of reduction leads to knee joint dysfunction. The posterior inclination angle of the tibial plateau is an important parameter to describe the sagittal alignment of the tibia. In the natural state, the posterior tibial slope(PTS) is altered to involve the soft tissues around the knee joint such as anterior cruciate ligament(ACL) and posterior cruciate ligament(PCL), which affects the stability of the knee joint. In total knee arthroplasty(TKA), choosing the appropriate PTS can effectively increase the prosthesis survival rate, improve the flexion and extension knee efficacy, which is beneficial to knee joint stability. In the field of orthopedic trauma, correction of sagittal deformity is equally important, following the principle of "reverse mechanism of injury". Quantitative evaluation of postoperative sagittal realignment of tibial plateau fractures and investigation of the effect of sagittal realignment on long-term outcomes and complications are still poorly understood and require further clinical and biomechanical studies.
Humans
;
Tibial Fractures/physiopathology*
;
Fracture Fixation, Internal/methods*
;
Tibial Plateau Fractures
9.Relationship between polygenic risk scores for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder.
Zhao-Min WU ; Peng WANG ; Chao DONG ; Xiao-Lan CAO ; Lan-Fang HU ; Cong KOU ; Jia-Jing JIANG ; Lin-Lin ZHANG ; Li YANG ; Yu-Feng WANG ; Ying LI ; Bin-Rang YANG
Chinese Journal of Contemporary Pediatrics 2025;27(9):1089-1097
OBJECTIVES:
To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD).
METHODS:
Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software.
RESULTS:
Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05).
CONCLUSIONS
PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans
;
Attention Deficit Disorder with Hyperactivity/genetics*
;
Child
;
Male
;
Female
;
Cross-Sectional Studies
;
Neuropsychological Tests
;
Multifactorial Inheritance
;
Adolescent
;
Mental Disorders/etiology*
;
Executive Function
;
Genetic Risk Score
10.Significance of precise classification of sacral meningeal cysts by multiple dimensions radiographic reconstruction MRI in guiding operative strategy and rehabilitation.
Jianjun SUN ; Qianquan MA ; Xiaoliang YIN ; Chenlong YANG ; Jia ZHANG ; Suhua CHEN ; Chao WU ; Jingcheng XIE ; Yunfeng HAN ; Guozhong LIN ; Yu SI ; Jun YANG ; Haibo WU ; Qiang ZHAO
Journal of Peking University(Health Sciences) 2025;57(2):303-308
OBJECTIVE:
To precise classify sacral meningeal cysts, effective guide minimally invasive neurosurgery and postoperative personalized rehabilitation by multiple dimensions radiographic reconstruction MRI.
METHODS:
From March to December 2021, based on the original 3D-fast imaging employing steadystate acquisition (FIESTA) scanning sequence, 92 patients with sacral meningeal cysts were pre-operatively evaluated by multiple dimensional reconstruction MRI. The shape of nerve root and the leakage of cyst were reconstructed according to the direction of nerve root or leakage track showed on original MRI scans. Sacral canal cysts were accurately classified as including nerve root and without nerve root, so as to accurately design the incision of skin and formulate corresponding open range of the posterior wall of the sacral canal. Under the microscope intraoperation, the shape of the nerve roots inside cysts or leakage track of the cysts without nerve roots were verified and explored. After the reinforcement and shaping operation, several reexaminations of multiple dimensional reconstruction MRI were performed to understand the deformation of the nerve root and hydrops in the operation cavity, so as to formulate a persona-lized rehabilitation plan for the patients.
RESULTS:
Among the 92 patients with sacral mengingeal cyst, 58 (63.0%) cysts with nerve root cyst, 29 (31.5%) cysts without nerve root cyst, and 5 (5.4%) cysts with mixed sacral canal cyst. In 58 patients with nerve root cysts, the accuracy of preoperative clinical classification on MRI image reached 96.6% (56/58) through confirmation by operating microscope. Only 2 cases of large single cyst with nerve root on the head of cyst were mistaken for without nerve root type. In 29 patients with sacral cyst without nerve root, the accuracy of preoperative image reached 100% through confirmation by operating microscope. The accuracy of judging the internal nerve root and leakage of 12 cases with recurrent sacral cyst was also 100%. Two cases of delayed postoperative hydrops were found one month after operation. After rehabilitation treatment by moxibustion and bathing, the hydrops disappeared 4-6 months after operation.
CONCLUSION
Multiple dimensional reconstruction MRI can precisely make clinical classification of sacral meningeal cysts before operation, guide minimally invasive neurosurgery effectively, and improve the rehabilitation effect.
Humans
;
Magnetic Resonance Imaging/methods*
;
Male
;
Female
;
Sacrum/surgery*
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Adult
;
Middle Aged
;
Imaging, Three-Dimensional/methods*
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Cysts/rehabilitation*
;
Aged
;
Adolescent
;
Young Adult
;
Spinal Nerve Roots/diagnostic imaging*
;
Minimally Invasive Surgical Procedures
;
Neurosurgical Procedures/methods*

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