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  1. Deep learning predicts tissue outcomes in retinal organoids

    This article has 12 authors:
    1. Cassian Afting
    2. Norin Bhatti
    3. Christina Schlagheck
    4. Encarnación Sánchez Salvador
    5. Laura Herrera-Astorga
    6. Rashi Agarwal
    7. Risa Suzuki
    8. Nicolaj Hackert
    9. Hanns-Martin Lorenz
    10. Lucie Zilova
    11. Joachim Wittbrodt
    12. Tarik Exner

    Reviewed by Review Commons

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  2. MAVISp : A modular structure‐based framework for protein variant effects

    This article has 33 authors:
    1. Matteo Arnaudi
    2. Mattia Utichi
    3. Kristine Degn
    4. Matteo Tiberti
    5. Ludovica Beltrame
    6. Karolina Krzesińska
    7. Pablo Sánchez‐Izquierdo Besora
    8. Eleni Kiachaki
    9. Simone Scrima
    10. Laura Bauer
    11. Katrine Meldgård
    12. Anna Melidi
    13. Lorenzo Favaro
    14. Anu Oswal
    15. Guglielmo Tedeschi
    16. Terézia Dorčaková
    17. Alberte Heering Estad
    18. Joachim Breitenstein
    19. Jordan Safer
    20. Paraskevi Saridaki
    21. Valentina Sora
    22. Francesca Maselli
    23. Philipp Becker
    24. Jérémy Vinhas
    25. Alberto Pettenella
    26. Matteo Lambrughi
    27. Claudia Cava
    28. Anna Rohlin
    29. Mef Nilbert
    30. Sumaiya Iqbal
    31. Peter Wad Sackett
    32. Burcu Aykac Fas
    33. Elena Papaleo

    Reviewed by Review Commons

    This article has 8 evaluationsAppears in 2 listsLatest version Latest activity
  3. Importin α characterizes a micronuclear environment associated with genomic instability in human cancer cells

    This article has 18 authors:
    1. Yoichi Miyamoto
    2. Reo Kisanuki
    3. Rieko Oshima
    4. Shige H. Yoshimura
    5. Mutsumi Yokota
    6. Kazumitsu Maehara
    7. Yoshiatsu Aomine
    8. Chiaki Hata
    9. Taro Tachibana
    10. Masaharu Hazawa
    11. Hiroyuki Okada
    12. Hiroshi Kimura
    13. Masato Koike
    14. Yasuyuki Ohkawa
    15. Toyomasa Katagiri
    16. Yoshihiro Yoneda
    17. Masahiro Oka
    18. Hisato Saitoh

    Reviewed by Review Commons

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  4. Microbiota impact Drosophila ageing via Acetobacter, Tachykinin, and TkR99D

    This article has 7 authors:
    1. Diana Marcu
    2. David R Sannino
    3. Anthony J Dornan
    4. Rita Ibrahim
    5. Atharv Kapoor
    6. Miriam Wood
    7. Adam J Dobson
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This important study demonstrates that in Drosophila melanogaster, tachykinin (Tk) expression is regulated by the microbiota. The authors present convincing evidence that axenic flies raised with no microbiota are longer-lived than conventionally reared animals, and that Tk expression and Tk receptors in the nervous system are required for this effect. They further test individual bacterial strains for their role in these effects and connect the effect to loss of lipid stores and suggest that FOXO may be involved in the phenotype, results that are of interest to the fields of environmental perception, host microbiome interactions, and geroscience.

      [Editors' note: this paper was reviewed by Review Commons.]

    Reviewed by eLife, Review Commons

    This article has 9 evaluationsAppears in 2 listsLatest version Latest activity