4.7 Article

At regulates centrosome migration and spindle orientation in the early Drosophila melanogaster embryo

期刊

JOURNAL OF CELL BIOLOGY
卷 180, 期 3, 页码 537-548

出版社

ROCKEFELLER UNIV PRESS
DOI: 10.1083/jcb.200705085

关键词

-

资金

  1. Biotechnology and Biological Sciences Research Council [BBS/B/08019] Funding Source: researchfish
  2. Biotechnology and Biological Sciences Research Council [BBS/B/08019] Funding Source: Medline

向作者/读者索取更多资源

Correct positioning and morphology of the mitotic spindle is achieved through regulating the interaction between microtubules (MTs) and cortical actin. Here we find that, in the Drosophila melanogaster early embryo, reduced levels of the protein kinase Akt result in incomplete centrosome migration around cortical nuclei, bent mitotic spindles, and loss of nuclei into the interior of the embryo. We show that At is enriched at the embryonic cortex and is required for phosphorylation of the glycogen synthase kinase-3 beta homologue Zeste-white 3 kinase (Zw3) and for the cortical localizations of the adenomatosis polyposis coli (APC)-related protein APC2/ E-APC and the MT + Tip protein EB1. We also show that reduced levels of Akt result in mislocalization of APC2 in postcellularized embryonic mitoses and misorientation of epithelial mitotic spindles. Together, our results suggest that Akt regulates a complex containing Zw3, Armadillo, APC2, and EB1 and that this complex has a role in stabilizing MT-cortex interactions, facilitating both centrosome separation and mitotic spindle orientation.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Biology

A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes

Mohammad KaramiNejadRanjbar, Sahand Sharifzadeh, Nina C. Wietek, Mara Artibani, Salma El-Sahhar, Tatjana Sauka-Spengler, Christopher Yau, Volker Tresp, Ahmed A. Ahmed

Article Oncology

The Oxford Classic Links Epithelial-to-Mesenchymal Transition to Immunosuppression in Poor Prognosis Ovarian Cancers

Zhiyuan Hu, Paula Cunnea, Zhe Zhong, Haonan Lu, Oloruntoba I. Osagie, Leticia Campo, Mara Artibani, Katherine Nixon, Jennifer Ploski, Laura Santana Gonzalez, Abdulkhaliq Alsaadi, Nina Wietek, Stephen Damato, Sunanda Dhar, Sarah P. Blagden, Christopher Yau, Joanna Hester, Ashwag Albukhari, Eric O. Aboagye, Christina Fotopoulou, Ahmed Ahmed

Summary: In this study, a 52-gene NanoString panel was developed to validate the robustness of the OxC classifier for serous ovarian cancers (SOCs). The results revealed that EMT-high SOCs have a particularly poor prognosis, independent of established clinical parameters, and are associated with a high frequency of immunosuppressive macrophages, suggesting a potential therapeutic target to improve clinical outcomes.

CLINICAL CANCER RESEARCH (2021)

Article Psychology, Clinical

Associations between baseline opioid use disorder severity, mental health and biopsychosocial functioning, with clinical responses to computer-assisted therapy treatment

Sarah Elison-Davies, Kaspar Martens, Christopher Yau, Glyn Davies, Jonathan Ward

Summary: CAT may reduce opioid use and improve biopsychosocial functioning in individuals with OUD, with those participants with greater baseline clinical impairment demonstrating a greater magnitude of improvement from baseline to post-treatment.

AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE (2021)

Article Genetics & Heredity

Pan-cancer detection of driver genes at the single-patient resolution

Joel Nulsen, Hrvoje Misetic, Christopher Yau, Francesca D. Ciccarelli

Summary: sysSVM2 is a machine learning software that integrates cancer genetic alterations with gene systems-level properties to predict driver genes in individual patients, showing low false-positive rate and stability, with applicability to rare cancer types. It can be used to identify driver alterations in patients lacking sufficient canonical drivers, furthering the goals of precision oncology.

GENOME MEDICINE (2021)

Review Oncology

Promises and challenges of adoptive T-cell therapies for solid tumours

Matteo Morotti, Ashwag Albukhari, Abdulkhaliq Alsaadi, Mara Artibani, James D. Brenton, Stuart M. Curbishley, Tao Dong, Michael L. Dustin, Zhiyuan Hu, Nicholas McGranahan, Martin L. Miller, Laura Santana-Gonzalez, Leonard W. Seymour, Tingyan Shi, Peter Van Loo, Christopher Yau, Helen White, Nina Wietek, David N. Church, David C. Wedge, Ahmed A. Ahmed

Summary: Cancer remains a leading cause of death globally, with metastatic disease posing challenges even with advancements in targeted therapies and immunotherapies. Adoptive T-cell therapy has shown promise in providing durable responses and potential cures for cancer patients. Advancements in genomics, immunology, and cell manufacturing are bringing personalized therapies for cancer patients closer to reality, challenging traditional standards of care and offering opportunities for a paradigm shift in cancer therapy.

BRITISH JOURNAL OF CANCER (2021)

Article Obstetrics & Gynecology

Epidemiology of pre-existing multimorbidity in pregnant women in the UK in 2018: a population-based cross-sectional study

Siang Ing Lee, Amaya Azcoaga-Lorenzo, Utkarsh Agrawal, Jonathan Kennedy, Adeniyi Francis Fagbamigbe, Holly Hope, Anuradhaa Subramanian, Astha Anand, Beck Taylor, Catherine Nelson-Piercy, Christine Damase-Michel, Christopher Yau, Francesca Crowe, Gillian Santorelli, Kelly-Ann Eastwood, Zoe Vowles, Maria Loane, Ngawai Moss, Peter Brocklehurst, Rachel Plachcinski, Shakila Thangaratinam, Mairead Black, Dermot O'Reilly, Kathryn M. Abel, Sinead Brophy, Krishnarajah Nirantharakumar, Colin McCowan

Summary: This study investigated the prevalence of pre-existing multimorbidity in pregnant women in the United Kingdom and found that it is a common occurrence. The study also identified older age, multiple pregnancies, higher body mass index, and preconception smoking as factors associated with a higher risk of multimorbidity in pregnant women.

BMC PREGNANCY AND CHILDBIRTH (2022)

Article Medicine, General & Internal

Protocol for the development of a core outcome set for studies of pregnant women with pre-existing multimorbidity

Siang Ing Lee, Kelly-Ann Eastwood, Ngawai Moss, Amaya Azcoaga-Lorenzo, Anuradhaa Subramanian, Astha Anand, Beck Taylor, Catherine Nelson-Piercy, Christopher Yau, Colin McCowan, Dermot O'Reilly, Holly Hope, Jonathan Ian Kennedy, Kathryn Mary Abel, Louise Locock, Peter Brocklehurst, Rachel Plachcinski, Sinead Brophy, Utkarsh Agrawal, Shakila Thangaratinam, Krishnarajah Nirantharakumar, Mairead Black

Summary: This study aims to develop a core outcome set for maternal and offspring outcomes in pregnant women with pre-existing multimorbidity. The study design includes systematic literature search, focus groups, Delphi surveys, and consensus group meetings, intended for broad application in various pregnancy settings.

BMJ OPEN (2021)

Article Oncology

Patient Derived Organoids Confirm That PI3K/AKT Signalling Is an Escape Pathway for Radioresistance and a Target for Therapy in Rectal Cancer

Kasun Wanigasooriya, Joao D. Barros-Silva, Louise Tee, Mohammed E. El-asrag, Agata Stodolna, Oliver J. Pickles, Joanne Stockton, Claire Bryer, Rachel Hoare, Celina M. Whalley, Robert Tyler, Toritseju Sillo, Christopher Yau, Tariq Ismail, Andrew D. Beggs

Summary: This study investigates the mechanisms of resistance to chemoradiotherapy in rectal cancer using patient derived organoid models. The upregulation of PI3K/AKT/mTOR pathway is found to contribute to radioresistance, and its targeted pharmacological inhibition leads to significant improvement in cancer cell sensitivity to radiotherapy.

FRONTIERS IN ONCOLOGY (2022)

Article Medicine, General & Internal

Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK

Siang Ing Lee, Holly Hope, Dermot O'Reilly, Lisa Kent, Gillian Santorelli, Anuradhaa Subramanian, Ngawai Moss, Amaya Azcoaga-Lorenzo, Adeniyi Francis Fagbamigbe, Catherine Nelson-Piercy, Christopher Yau, Colin McCowan, Jonathan Ian Kennedy, Katherine Phillips, Megha Singh, Mohamed Mhereeg, Neil Cockburn, Peter Brocklehurst, Rachel Plachcinski, Richard D. Riley, Shakila Thangaratinam, Sinead Brophy, Sudasing Pathirannehelage Buddhika Hemali Sudasinghe, Utkarsh Agrawal, Zoe Vowles, Kathryn Mary Abel, Krishnarajah Nirantharakumar, Mairead Black, Kelly-Ann Eastwood, MuM PreDiCT

Summary: This observational study aims to compare maternal and child outcomes for pregnant women with multiple long-term conditions to those without multiple long-term conditions. Data from routine health records in the UK and the Born in Bradford birth cohort will be used to examine the association of multiple long-term conditions with various outcomes. The results will be published in peer-reviewed journals and presented at conferences.

BMJ OPEN (2023)

Article Biotechnology & Applied Microbiology

CIDER: an interpretable meta-clustering framework for single-cell RNA-seq data integration and evaluation

Zhiyuan Hu, Ahmed A. Ahmed, Christopher Yau

Summary: CIDER is a meta-clustering workflow based on inter-group similarity measures, which outperforms other methods in clustering single-cell RNA-Seq data and can be used to assess the biological correctness of integration without prior cellular annotations.

GENOME BIOLOGY (2021)

Correction Multidisciplinary Sciences

Publisher Correction: Bayesian statistics and modelling (10.1038/s43586-020-00001-2 )

Rens van de Schoot, Sarah Depaoli, Ruth King, Bianca Kramer, Kaspar Martens, Mahlet G. Tadesse, Marina Vannucci, Andrew Gelman, Duco Veen, Joukje Willemsen, Christopher Yau

Summary: The paper has been corrected.

NATURE REVIEWS METHODS PRIMERS (2021)

Review Multidisciplinary Sciences

Bayesian statistics and modelling

Rens van de Schoot, Sarah Depaoli, Ruth King, Bianca Kramer, Kaspar Maertens, Mahlet C. Tadesse, Marina Vannucci, Andrew Gelman, Duco Veen, Joukje Willemsen, Christopher Yau

Summary: Bayesian statistics is a data analysis approach based on Bayes' theorem, which involves determining parameters through prior distributions, likelihood functions, and posterior distributions. This method has shown successful applications in various disciplines and has improved accuracy in predicting future events.

NATURE REVIEWS METHODS PRIMERS (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Neural Decomposition: Functional ANOVA with Variational Autoencoders

Kaspar Martens, Christopher Yau

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108 (2020)

Proceedings Paper Computer Science, Artificial Intelligence

BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders

Kaspar Martens, Christopher Yau

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108 (2020)

Meeting Abstract Hematology

Exploiting VDJ recombination of T cells to dissect the anti-cancer immune interactions in T cell lymphoma

D. Murray, S. Eldershaw, H. Pearce, C. Yau, J. Scarisbrick, P. Moss

BRITISH JOURNAL OF HAEMATOLOGY (2020)

暂无数据