The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Quadrivalent influenza nanoparticle vaccines induce broad protection
Open accessAbstract
Influenza vaccines that confer broad and durable protection against diverse viral strains would have a major effect on global health, as they would lessen the need for annual vaccine reformulation and immunization1. Here we show that computationally designed, two-component nanoparticle immunogens2 induce potently neutralizing and broadly protective antibody responses against a wide variety of influenza viruses. The nanoparticle immunogens contain 20 haemagglutinin glycoprotein trimers in an ordered array, and their assembly in vitro enables the precisely controlled co-display of multiple distinct haemagglutinin proteins in defined ratios. Nanoparticle immunogens that co-display the four haemagglutinins of licensed quadrivalent influenza vaccines elicited antibody responses in several animal models against vaccine-matched strains that were equivalent to or better than commercial quadrivalent influenza vaccines, and simultaneously induced broadly protective antibody responses to heterologous viruses by targeting the subdominant yet conserved haemagglutinin stem. The combination of potent receptor-blocking and cross-reactive stem-directed antibodies induced by the nanoparticle immunogens makes them attractive candidates for a supraseasonal influenza vaccine candidate with the potential to replace conventional seasonal vaccines3. A nanoparticle influenza vaccine candidate is shown to induce broad cross-reactive antibody responses in animal models.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 29,915
MolProbity : all-atom structure validation for macromolecular crystallography
Chen, V. B., Arendall, W. B., Headd, J. J., Keedy, D. A., Immormino, R. M., Kapral, G. J., Murray, L. W., Richardson, J. S., & Richardson, D. C. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909042073 · Cited by 14,115
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A. (2017) · Nature Methods · doi:10.1038/nmeth.4169 · Cited by 11,626
Liebschner, D., Afonine, P. V., Baker, M. L., Bunkóczi, G., Chen, V. B., Croll, T. I., Hintze, B., Hung, L.-W., Jain, S., McCoy, A. J., et al. (2019) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798319011471 · Cited by 7,953
Protein production by auto-induction in high-density shaking cultures
Studier, F. W. (2005) · Protein Expression and Purification · doi:10.1016/j.pep.2005.01.016 · Cited by 5,931
CTFFIND4: Fast and accurate defocus estimation from electron micrographs
Rohou, A., & Grigorieff, N. (2015) · Journal of Structural Biology · doi:10.1016/j.jsb.2015.08.008 · Cited by 4,913
New tools for automated high-resolution cryo-EM structure determination in RELION-3
Zivanov, J., Nakane, T., Forsberg, B. O., Kimanius, D., Hagen, W. J., Lindahl, E., & Scheres, S. H. (2018) · eLife · doi:10.7554/elife.42166 · Cited by 4,621
Estimates of global seasonal influenza-associated respiratory mortality: a modelling study
Iuliano, A. D., Roguski, K. M., Chang, H. H., Muscatello, D. J., Palekar, R., Tempia, S., Cohen, C., Gran, J. M., Schanzer, D., Cowling, B. J., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(17)33293-2 · Cited by 3,019
Automated molecular microscopy: The new Leginon system
Suloway, C., Pulokas, J., Fellmann, D., Cheng, A., Guerra, F., Quispe, J., Stagg, S., Potter, C. S., & Carragher, B. (2005) · Journal of Structural Biology · doi:10.1016/j.jsb.2005.03.010 · Cited by 1,764
Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction
Punjani, A., Zhang, H., & Fleet, D. J. (2020) · Nature Methods · doi:10.1038/s41592-020-00990-8 · Cited by 1,683
Cited by
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · doi:10.1101/2022.12.09.519842 · Cited by 2,369
Self-citationDe novo design of protein structure and function with RFdiffusion
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature · doi:10.1038/s41586-023-06415-8 · Cited by 2,325
Self-citationRobust deep learning based protein sequence design using ProteinMPNN
Dauparas, J., Anishchenko, I., Bennett, N., Bai, H., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Courbet, A., de Haas, R. J., Bethel, N., et al. (2022) · doi:10.1101/2022.06.03.494563 · Cited by 2,107
Self-citationRobust deep learning–based protein sequence design using ProteinMPNN
Dauparas, J., Anishchenko, I., Bennett, N., Bai, H., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Courbet, A., de Haas, R. J., Bethel, N., et al. (2022) · Science · doi:10.1126/science.add2187 · Cited by 2,210
Self-citationZhu, J., Avakyan, N., Kakkis, A., Hoffnagle, A. M., Han, K., Li, Y., Zhang, Z., Choi, T. S., Na, Y., Yu, C.-J., et al. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00308 · Cited by 285
Metadata
- Authors
- Boyoglu-Barnum, S., Ellis, D., Gillespie, R. A., Hutchinson, G. B., Park, Y.-J., Moin, S. M., Acton, O. J., Ravichandran, R., Murphy, M., Pettie, D., Matheson, N., Carter, L., Creanga, A., Watson, M. J., Kephart, S., Ataca, S., Vaile, J. R., Ueda, G., Crank, M. C., Stewart, L., Lee, K. K., Guttman, M., Baker, D., Mascola, J. R., Veesler, D., Graham, B. S., King, N. P., & Kanekiyo, M.
- Venue
- Nature
- Published
- 2021-03-24
- Volume
- 592
- Issue
- 7855
- Pages
- 623-628
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3136996287
- Cited by
- 304
- References
- 79
- FWCI
- 31.40
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quadrivalent influenza nanoparticle vaccines induce broad protection. https://app.cochat.ai/papers/10.1038/s41586-021-03365-x
- The paper
- Boyoglu-Barnum, S., Ellis, D., Gillespie, R. A., Hutchinson, G. B., Park, Y.-J., Moin, S. M., Acton, O. J., Ravichandran, R., Murphy, M., Pettie, D., Matheson, N., Carter, L., Creanga, A., Watson, M. J., Kephart, S., Ataca, S., Vaile, J. R., Ueda, G., Crank, M. C., . . . Kanekiyo, M. (2021). Quadrivalent influenza nanoparticle vaccines induce broad protection. Nature. https://doi.org/10.1038/s41586-021-03365-x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
