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  1. Book ; Online ; E-Book: Uterine fibroids and adenomyosis

    Sugino, Norihiro

    (Comprehensive gynecology and obstetrics)

    2018  

    Author's details Norihiro Sugino editor
    Series title Comprehensive gynecology and obstetrics
    Keywords Medicine ; Gynecology ; Oncology
    Subject code 618.1
    Language English
    Size 1 Online-Ressource (vii, 173 Seiten), Illustrationen
    Publisher Springer
    Publishing place Singapore
    Publishing country Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019760413
    ISBN 978-981-10-7167-6 ; 9789811071669 ; 981-10-7167-5 ; 9811071667
    DOI 10.1007/978-981-10-7167-6
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: First healthy baby by anonymous oocyte donation in Japan.

    Sugino, Norihiro

    Reproductive medicine and biology

    2018  Volume 17, Issue 3, Page(s) 219

    Language English
    Publishing date 2018-06-06
    Publishing country Japan
    Document type Editorial
    ZDB-ID 2185775-1
    ISSN 1447-0578 ; 1445-5781
    ISSN (online) 1447-0578
    ISSN 1445-5781
    DOI 10.1002/rmb2.12210
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Introducing

    Sugino, Norihiro

    Reproductive medicine and biology

    2016  Volume 16, Issue 1, Page(s) 3

    Language English
    Publishing date 2016-12-26
    Publishing country Japan
    Document type Editorial
    ZDB-ID 2185775-1
    ISSN 1447-0578 ; 1445-5781
    ISSN (online) 1447-0578
    ISSN 1445-5781
    DOI 10.1002/rmb2.12016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Correction: Genome-wide DNA methylation analysis revealed stable DNA methylation status during decidualization in human endometrial stromal cells.

    Maekawa, Ryo / Tamura, Isao / Shinagawa, Masahiro / Mihara, Yumiko / Sato, Shun / Okada, Maki / Taketani, Toshiaki / Tamura, Hiroshi / Sugino, Norihiro

    BMC genomics

    2024  Volume 25, Issue 1, Page(s) 343

    Language English
    Publishing date 2024-04-05
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2041499-7
    ISSN 1471-2164 ; 1471-2164
    ISSN (online) 1471-2164
    ISSN 1471-2164
    DOI 10.1186/s12864-024-10222-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Analysis of cell-cell interaction between mural granulosa cells and cumulus granulosa cells during ovulation using single-cell RNA sequencing data of mouse ovary.

    Shirafuta, Yuichiro / Tamura, Isao / Shiroshita, Amon / Fujimura, Taishi / Maekawa, Ryo / Taketani, Toshiaki / Sugino, Norihiro

    Reproductive medicine and biology

    2024  Volume 23, Issue 1, Page(s) e12564

    Abstract: Purpose: We investigated the interactions between mural granulosa cells (MGCs) and cumulus granulosa cells (CGCs) during ovulation after the LH surge.: Methods: We performed clustering, pseudotime, and interactome analyses utilizing reported single- ... ...

    Abstract Purpose: We investigated the interactions between mural granulosa cells (MGCs) and cumulus granulosa cells (CGCs) during ovulation after the LH surge.
    Methods: We performed clustering, pseudotime, and interactome analyses utilizing reported single-cell RNA sequencing data of mouse ovary at 6 h after eCG-hCG injection.
    Results: Clustering analysis classified granulosa cells into two distinct populations, MGCs and CGCs. Pseudotime analysis divided granulosa cells into before and after the LH surge, and further divided them into two branches, the ovulatory MGCs and the ovulatory CGCs. Interactome analysis was performed to identify the interactions between MGCs and CGCs. Twenty-six interactions were acting from CGCs toward MGCs, involving ovulation and steroidogenesis. Thirty-six interactions were acting from MGCs toward CGCs, involving hyaluronan synthesis. There were 25 bidirectional interactions, involving the EGFR pathway. In addition, we found three novel interactions: Ephrins-Ephs pathway and Wnt-Lrp6 pathway from CGCs to MGCs, associated with steroidogenesis and lipid transport, respectively, and TGF-β-TGFBR1 pathway from MGCs to CGCs, associated with hyaluronan synthesis.
    Conclusions: MGCs and CGCs interact with each other in the preovulatory follicle after the LH surge, and their interactions have roles in corpus luteum formation, oocyte maturation, and follicle rupture.
    Language English
    Publishing date 2024-02-14
    Publishing country Japan
    Document type Journal Article
    ZDB-ID 2185775-1
    ISSN 1447-0578 ; 1445-5781
    ISSN (online) 1447-0578
    ISSN 1445-5781
    DOI 10.1002/rmb2.12564
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Differential gene expression in decidualized human endometrial stromal cells induced by different stimuli.

    Doi-Tanaka, Yumiko / Tamura, Isao / Shiroshita, Amon / Fujimura, Taishi / Shirafuta, Yuichiro / Maekawa, Ryo / Taketani, Toshiaki / Sato, Shun / Sugino, Norihiro

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 7726

    Abstract: Decidualization can be induced by culturing human endometrial stromal cells (ESCs) with several decidualization stimuli, such as cAMP, medroxyprogesterone acetate (MPA) or Estradiol ( ... ...

    Abstract Decidualization can be induced by culturing human endometrial stromal cells (ESCs) with several decidualization stimuli, such as cAMP, medroxyprogesterone acetate (MPA) or Estradiol (E
    MeSH term(s) Female ; Humans ; Cells, Cultured ; Endometrium/metabolism ; Medroxyprogesterone Acetate/pharmacology ; Stromal Cells/metabolism ; Gene Expression ; RNA/metabolism ; Decidua/metabolism
    Chemical Substances Medroxyprogesterone Acetate (C2QI4IOI2G) ; RNA (63231-63-0)
    Language English
    Publishing date 2024-04-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-58065-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Identification of long noncoding RNAs downregulated specifically in ovarian high-grade serous carcinoma.

    Hayashi-Okada, Maki / Sato, Shun / Nakashima, Kengo / Sakai, Takahiro / Tamehisa, Tetsuro / Kajimura, Takuya / Tamura, Isao / Sueoka, Kotaro / Sugino, Norihiro

    Reproductive medicine and biology

    2024  Volume 23, Issue 1, Page(s) e12572

    Abstract: Purpose: To investigate whether long noncoding RNAs (lncRNAs) are involved in the development or malignant behavior of ovarian high-grade serous carcinoma (HGSC), we attempted to identify lncRNAs specific to HGSC.: Methods: Total RNAs were isolated ... ...

    Abstract Purpose: To investigate whether long noncoding RNAs (lncRNAs) are involved in the development or malignant behavior of ovarian high-grade serous carcinoma (HGSC), we attempted to identify lncRNAs specific to HGSC.
    Methods: Total RNAs were isolated from HGSC, normal ovarian, and fallopian tube tissue samples and were subjected to a PCR array that can analyze 84 cancer-associated lncRNAs. The lncRNAs that were upregulated and downregulated in HGSC in comparison to multiple samples of normal ovary and fallopian tube were validated by real-time RT-PCR. To infer the function, ovarian cancer cell lines that overexpress the identified lncRNAs were established, and the activation of cell proliferation, migration, and invasion was analyzed.
    Results: Eleven lncRNAs (ACTA2-AS1, ADAMTS9-AS2, CBR3-AS1, HAND2-AS1, IPW, LINC00312, LINC00887, MEG3, NBR2, TSIX, and XIST) were downregulated in HGSC samples. We established the cell lines that overexpress ADAMTS9-AS2, CBR3-AS1, or NBR2. In cell lines overexpressing ADAMTS9-AS2, cell proliferation was suppressed, but migration and invasion were promoted. In cell lines overexpressing CBR3-AS1 or NBR2, cell migration tended to be promoted, although cell proliferation and invasion were unchanged.
    Conclusion: We identified eleven lncRNAs that were specifically downregulated in HGSC. Of these, CBR3-AS1, NBR2, and ADAMTS9-AS2 had unique functions in the malignant behaviors of HGSC.
    Language English
    Publishing date 2024-04-03
    Publishing country Japan
    Document type Journal Article
    ZDB-ID 2185775-1
    ISSN 1447-0578 ; 1445-5781
    ISSN (online) 1447-0578
    ISSN 1445-5781
    DOI 10.1002/rmb2.12572
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Molecular mechanisms of luteinization.

    Sugino, Norihiro

    Obstetrics & gynecology science

    2014  Volume 57, Issue 2, Page(s) 93–101

    Abstract: Dynamic changes in steroidogenesis occur in ovarian granulosa cells during ovulation after the LH surge. The ovulatory LH surge induces rapid up-regulation of steroidogenic acute regulatory (StAR) protein and rapid down-regulation of aromatase (Cyp19a1) ... ...

    Abstract Dynamic changes in steroidogenesis occur in ovarian granulosa cells during ovulation after the LH surge. The ovulatory LH surge induces rapid up-regulation of steroidogenic acute regulatory (StAR) protein and rapid down-regulation of aromatase (Cyp19a1) in granulosa cells undergoing luteinization during ovulation. These rapid changes in StAR and Cyp19a1 gene expression after the LH surge efficiently facilitate progesterone production, which plays a crucial role in ovulation and the following luteinization. Recently, it has become clear that epigenetic regulation such as histone modifications and DNA methylation play a key role in gene expression through the chromatin remodeling of the promoter region. This study reports the in vivo evidence that epigenetic mechanisms including histone modifications, DNA methylation and chromatin remodeling are involved in the rapid changes of StAR and Cyp19a1 gene expression in granulosa cells undergoing luteinization during ovulation.
    Language English
    Publishing date 2014-03-15
    Publishing country Korea (South)
    Document type Journal Article
    ZDB-ID 2814367-X
    ISSN 2287-8580 ; 2287-8572
    ISSN (online) 2287-8580
    ISSN 2287-8572
    DOI 10.5468/ogs.2014.57.2.93
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Establishment of Noninvasive Prediction Models for the Diagnosis of Uterine Leiomyoma Subtypes.

    Tamehisa, Tetsuro / Sato, Shun / Sakai, Takahiro / Maekawa, Ryo / Tanabe, Masahiro / Ito, Katsuyoshi / Sugino, Norihiro

    Obstetrics and gynecology

    2023  Volume 143, Issue 3, Page(s) 358–365

    Abstract: Objective: To establish prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using magnetic resonance imaging (MRI) data.: Methods: This is a prospective observational study. Ninety uterine leiomyoma samples ... ...

    Abstract Objective: To establish prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using magnetic resonance imaging (MRI) data.
    Methods: This is a prospective observational study. Ninety uterine leiomyoma samples were obtained from 51 patients who underwent surgery for uterine leiomyomas. Seventy-one samples (49 mediator complex subunit 12 [ MED12 ] mutation-positive and 22 MED12 mutation-negative leiomyomas) were assigned to the primary data set to establish prediction models. Nineteen samples (13 MED12 mutation-positive and 6 MED12 mutation-negative leiomyomas) were assigned to the unknown testing data set to validate the prediction model utility. The tumor signal intensity was quantified by seven MRI sequences (T2-weighted imaging, apparent diffusion coefficient, magnetic resonance elastography, T1 mapping, magnetization transfer contrast, T2* blood oxygenation level dependent, and arterial spin labeling) that can estimate the collagen and water contents of uterine leiomyomas. After surgery, the MED12 mutations were genotyped. These results were used to establish prediction models based on machine learning by applying support vector classification and logistic regression for the diagnosis of uterine leiomyoma subtypes. The performance of the prediction models was evaluated by cross-validation within the primary data set and then finally evaluated by external validation using the unknown testing data set.
    Results: The signal intensities of five MRI sequences (T2-weighted imaging, apparent diffusion coefficient, T1 mapping, magnetization transfer contrast, and T2* blood oxygenation level dependent) differed significantly between the subtypes. In cross-validation within the primary data set, both machine learning models (support vector classification and logistic regression) based on the five MRI sequences were highly predictive of the subtypes (area under the curve [AUC] 0.974 and 0.988, respectively). External validation with the unknown testing data set confirmed that both models were able to predict the subtypes for all samples (AUC 1.000, 100.0% accuracy). Our prediction models with T2-weighted imaging alone also showed high accuracy to discriminate the uterine leiomyoma subtypes.
    Conclusion: We established noninvasive prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using MRI data.
    MeSH term(s) Female ; Humans ; Uterine Neoplasms/diagnostic imaging ; Uterine Neoplasms/genetics ; Leiomyoma/diagnostic imaging ; Magnetic Resonance Imaging/methods ; Diffusion Magnetic Resonance Imaging/methods ; Mutation
    Language English
    Publishing date 2023-12-07
    Publishing country United States
    Document type Observational Study ; Journal Article
    ZDB-ID 207330-4
    ISSN 1873-233X ; 0029-7844
    ISSN (online) 1873-233X
    ISSN 0029-7844
    DOI 10.1097/AOG.0000000000005475
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Different DNA methylome, transcriptome and histological features in uterine fibroids with and without MED12 mutations.

    Maekawa, Ryo / Sato, Shun / Tamehisa, Tetsuro / Sakai, Takahiro / Kajimura, Takuya / Sueoka, Kotaro / Sugino, Norihiro

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 8912

    Abstract: Somatic mutations in Mediator complex subunit 12 (MED12m) have been reported as a biomarker of uterine fibroids (UFs). However, the role of MED12m is still unclear in the pathogenesis of UFs. Therefore, we investigated the differences in DNA methylome, ... ...

    Abstract Somatic mutations in Mediator complex subunit 12 (MED12m) have been reported as a biomarker of uterine fibroids (UFs). However, the role of MED12m is still unclear in the pathogenesis of UFs. Therefore, we investigated the differences in DNA methylome, transcriptome, and histological features between MED12m-positive and -negative UFs. DNA methylomes and transcriptomes were obtained from MED12m-positive and -negative UFs and myometrium, and hierarchically clustered. Differentially expressed genes in comparison with the myometrium and co-expressed genes detected by weighted gene co-expression network analysis were subjected to gene ontology enrichment analyses. The amounts of collagen fibers and the number of blood vessels and smooth muscle cells were histologically evaluated. Hierarchical clustering based on DNA methylation clearly separated the myometrium, MED12m-positive, and MED12m-negative UFs. MED12m-positive UFs had the increased activities of extracellular matrix formation, whereas MED12m-negative UFs had the increased angiogenic activities and smooth muscle cell proliferation. The MED12m-positive and -negative UFs had different DNA methylation, gene expression, and histological features. The MED12m-positive UFs form the tumor with a rich extracellular matrix and poor blood vessels and smooth muscle cells compared to the MED12m-negative UFs, suggesting MED12 mutations affect the tissue composition of UFs.
    MeSH term(s) Epigenome ; Female ; Humans ; Leiomyoma/pathology ; Mediator Complex/genetics ; Mediator Complex/metabolism ; Mutation ; Myometrium/metabolism ; Transcription Factors/metabolism ; Transcriptome
    Chemical Substances MED12 protein, human ; Mediator Complex ; Transcription Factors
    Language English
    Publishing date 2022-05-26
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-12899-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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