eLife

Latest preprint reviews

1. Discovery of a heparan sulfate binding domain in monkeypox virus H3 as an anti-poxviral drug target combining AI and MD simulations

   This article has 10 authors:

   1. Bin Zheng
   2. Meimei Duan
   3. Yifen Huang
   4. Shangchen Wang
   5. Jun Qiu
   6. Zhuojian Lu
   7. Lichao Liu
   8. Guojin Tang
   9. Lin Cheng
   10. Peng Zheng

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This work presents important findings regarding the interaction of the monkeypox virus (MPXV) attachment H3 protein with the cellular receptor heparan sulfate and the use of this information to develop antivirals potentially effective against all orthopoxviruses. Using a combination of state-of-the art computational and wet experiments the authors present convincing evidence to sustain their claims. These results will interest those working on basic orthopoxviruses biology and antiviral development.

   Reviewed by eLife

2. Stimulus-specificity of surround-induced responses in primary visual cortex

   This article has 8 authors:

   1. Nisa Cuevas
   2. Boris Sotomayor-Gómez
   3. Athanasia Tzanou
   4. Irene Onorato
   5. Brian Rummell
   6. Cem Uran
   7. Ana Broggini
   8. Martin Vinck

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This valuable study investigates the selectivity of neuronal responses in the neocortex and thalamus to visual stimuli presented far outside their receptive fields. The study shows convincing evidence for a long-latency surround-induced response in primary visual cortex that is absent in the dorsal lateral geniculate nucleus and does not depend strongly on the visual characteristics of the surround stimulus. The paper should be of interest to neurophysiologists interested in vision and contextual modulations.

   Reviewed by eLife

3. The novel role of Kallistatin in linking metabolic syndromes and cognitive memory deterioration by inducing amyloid-β plaques accumulation and tau protein hyperphosphorylation

   This article has 14 authors:

   1. Weiwei Qi
   2. Yanlan Long
   3. Ziming Li
   4. Zhen Zhao
   5. Jinhui Shi
   6. Wanting Xie
   7. Laijian Wang
   8. Yandan Tan
   9. Ti Zhou
   10. Minting Liang
   11. Ping Jiang
   12. Bin Jiang
   13. Xia Yang
   14. Guoquan Gao

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This important study identified a molecular mechanism linking diabetes to AD risk and the data presented are convincing. The authors investigated the role of kallistatin in metabolic abnormalities associated with AD and identified that Kallistatin is a key player that mediates Aβ accumulation and tau hyperphosphorylation in AD. This manuscript provides novel insights into the pathogenesis of AD, indicating that the hypolipidemic drug fenofibrate attenuates AD-like pathology in Kallistatin transgenic mice.

   Reviewed by eLife

4. Growth consequences of the inhomogeneous organization of the bacterial cytoplasm

   This article has 4 authors:

   1. Johan H van Heerden
   2. Alicia Berkvens
   3. Daan H de Groot
   4. Frank J Bruggeman

   This article has been curated by 1 group:

   • Curated by eLife

     eLife assessment

     This important study examines E. coli growth and division, suggesting that inhomogeneous organization of ribosomes in the cytoplasm results in cell size-dependent growth rate perturbations. The work is conceptually appealing, but incomplete due to shortcomings in the experiments and modeling.

   Reviewed by eLife

5. Adaptive chunking improves effective working memory capacity in a prefrontal cortex and basal ganglia circuit

   This article has 2 authors:

   1. Aneri Soni
   2. Michael J Frank

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This important work proposes a neural network model of interactions between the prefrontal cortex and basal ganglia to implement adaptive resource allocation in working memory, where the gating strategies for storage are adjusted by reinforcement learning. Numerical simulations provide convincing evidence for the superiority of the model in improving effective capacity, optimizing resource management, and reducing error rates, as well as for its human-like performance. This work will be of broad interest to computational and cognitive neuroscientists, and may also interest machine-learning researchers who seek to develop brain-inspired machine-learning algorithms for memory.

   Reviewed by eLife

6. JAK inhibition decreases the autoimmune burden in Down syndrome

   This article has 22 authors:

   1. Angela L Rachubinski
   2. Elizabeth Wallace
   3. Emily Gurnee
   4. Belinda A Enriquez-Estrada
   5. Kayleigh R Worek
   6. Keith P Smith
   7. Paula Araya
   8. Katherine A Waugh
   9. Ross E Granrath
   10. Eleanor Britton
   11. Hannah R Lyford
   12. Micah G Donovan
   13. Neetha Paul Eduthan
   14. Amanda A Hill
   15. Barry Martin
   16. Kelly D Sullivan
   17. Lina Patel
   18. Deborah J Fidler
   19. Matthew D Galbraith
   20. Cory A Dunnick
   21. David A Norris
   22. Joaquín M Espinosa

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     Rachubinski and colleagues provide an important manuscript that includes two major advances in understanding immune dysregulation in a large cohort of individuals with Down syndrome. The work comprises compelling, comprehensive, and state-of-the-art clinical, immunological, and autoantibody assessment of autoimmune/inflammatory manifestations. Additionally, the authors report promising results from a clinical trial with the JAK inhibitor tofacitinib for individuals with dermatological autoimmune disease.

   Reviewed by eLife

7. PPI-hotspotID: A Method for Detecting Protein-Protein Interaction Hot Spots from the Free Protein Structure

   This article has 6 authors:

   1. Yao Chi Chen
   2. Karen Sargsyan
   3. Jon D Wright
   4. Yu-Hsien Chen
   5. Yi-Shuian Huang
   6. Carmay Lim

   This article has been curated by 1 group:

   • Curated by eLife

     eLife assessment

     The manuscript presents a machine-learning method to predict protein hotspot residues. The validation is incomplete, along with the misinterpretation of the results with other current methods like FTMap.

   Reviewed by eLife

8. A Ctnnb1 enhancer transcriptionally regulates Wnt signaling dosage to balance homeostasis and tumorigenesis of intestinal epithelia

   This article has 10 authors:

   1. Xiaojiao Hua
   2. Chen Zhao
   3. Jianbo Tian
   4. Junbao Wang
   5. Xiaoping Miao
   6. Gen Zheng
   7. Min Wu
   8. Mei Ye
   9. Ying Liu
   10. Yan Zhou

   This article has been curated by 1 group:

   • Curated by eLife

     eLife assessment

     Ctnnb1 encodes β-catenin, an essential component of the canonical Wnt signaling pathway. In this important study, the authors identify an upstream enhancer of Ctnnb1 responsible for the specific expression level of β-catenin in the gastrointestinal track. Deletion of this enhancer in mice and analyses of its association with human colorectal tumors provide compelling support that it controls the dosage of Wnt signaling critical to the homeostasis in intestinal epithelia and colorectal cancers.

   Reviewed by eLife

9. Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control

   This article has 4 authors:

   1. Yiheng Zhang
   2. Yun Chen
   3. Tianwei Wang
   4. He Cui

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This useful study examines the neural activity in the motor cortex as a monkey reaches to intercept moving targets, focusing on how tuned single neurons contribute to an interesting overall population geometry. The presented results and analyses are solid, though the investigation of this novel task could be strengthened by clarifying the assumptions behind the single neuron analyses, and further analyses of the neural population activity and its relation to different features of behaviour.

   Reviewed by eLife

10. Pathway activation model for personalized prediction of drug synergy

    This article has 18 authors:

    1. Quang Thinh Trac
    2. Yue Huang
    3. Tom Erkers
    4. Päivi Östling
    5. Anna Bohlin
    6. Albin Osterroos
    7. Mattias Vesterlund
    8. Rozbeh Jafari
    9. Ioannis Siavelis
    10. Helena Backvall
    11. Santeri Kiviluoto
    12. Lukas Orre
    13. Mattias Rantalainen
    14. Janne Lehtiö
    15. Soren Lehmann
    16. Olli Kallioniemi
    17. Yudi Pawitan
    18. Trung Nghia Vu

    This article has been curated by 1 group:

    • Curated by eLife

      eLife Assessment

      This valuable study presents a deep learning framework for predicting synergistic drug combinations for cancer treatment in the AstraZeneca-Sanger (AZS) DREAM Challenge dataset. The level of evidence seems solid, although performance on some datasets seems unconvincing and further validation would be required to demonstrate the generalizability of the model and, in turn, its clinical relevance. The reported tool, DIPx, could be of use for personalized drug synergy prediction and exploring the activated pathways related to the effects of drug combinations.

    Reviewed by eLife