eLife

Latest preprint reviews

1. We couldn't get details of this article at this time:
   10.1101/2022.08.19.504510

2. We couldn't get details of this article at this time:
   10.1101/2023.12.10.570982

3. We couldn't get details of this article at this time:
   10.1101/2024.04.29.591675

4. We couldn't get details of this article at this time:
   10.1101/2024.05.02.592254

5. Temporally controlled nervous system-to-gut signaling bidirectionally regulates longevity in C. elegans

   This article has 5 authors:

   1. Lingxiu Xu
   2. Chengxuan Han
   3. Lei Chun
   4. XZ Shawn Xu
   5. Jianfeng Liu

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This is an important study that addresses the temporal aspects of cell non-autonomous regulation of lifespan. It demonstrates that the same neurons and neurotransmitter have distinct impacts on longevity at different ages. The data convincingly supports the authors' claims.

   Reviewed by eLife

6. We couldn't get details of this article at this time:
   10.1101/2024.04.09.588807

7. The Drosophila EcR-Hippo component Taiman promotes epithelial cell fitness by control of the Dally-like glypican and Wg gradient

   This article has 3 authors:

   1. Colby K. Schweibenz
   2. Victoria C. Placentra
   3. Kenneth H. Moberg

   This article has been curated by 1 group:

   • Curated by eLife

     eLife assessment

     The authors study how cells with lower levels of the conserved steroid hormone signaling component Taiman (tai) are out-competed by neighboring wild-type cells with higher fitness in Drosophila imaginal discs. The findings are useful since they uncover an unexpected link between tai and Wingless signaling in cell competition. The evidence however is incomplete, since the tai loss-of-clone phenotype is based on one allele and the mechanism involved in cell competition through Dlp and Wg lacks adequate supporting data.

   Reviewed by eLife

8. We couldn't get details of this article at this time:
   10.1101/2024.03.28.587206

9. Establishing the foundations for a data-centric AI approach for virtual drug screening through a systematic assessment of the properties of chemical data

   This article has 6 authors:

   1. Allen Chong
   2. Ser-Xian Phua
   3. Yunzhi Xiao
   4. Woon Yee Ng
   5. Hoi Yeung Li
   6. Wilson Wen Bin Goh

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This study reports valuable findings that highlight the importance of data quality and data representation for ligand-based virtual screening experiments. The authors' claims are supported by solid evidence, although the conclusions have been inferred from only two datasets. The work would gain much impact if additional datasets were used. The main findings will be of interest to cheminformaticians and medicinal chemists working in QSAR modeling, and possibly in other areas related to machine learning.

   Reviewed by eLife

10. We couldn't get details of this article at this time:
    10.1101/2024.03.26.586840