The DOI matches its Crossref record.
Antibody-Based Bio-Nanotube Membranes for Enantiomeric Drug Separations
Abstract
Synthetic bio-nanotube membranes were developed and used to separate two enantiomers of a chiral drug. These membranes are based on alumina films that have cylindrical pores with monodisperse nanoscopic diameters (for example, 20 nanometers). Silica nanotubes were chemically synthesized within the pores of these films, and an antibody that selectively binds one of the enantiomers of the drug was attached to the inner walls of the silica nanotubes. These membranes selectively transport the enantiomer that specifically binds to the antibody, relative to the enantiomer that has lower affinity for the antibody. The solvent dimethyl sulfoxide was used to tune the antibody binding affinity. The enantiomeric selectivity coefficient increases as the inside diameter of the silica nanotubes decreases.
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
Cited by
Smart Nanotubes for Bioseparations and Biocatalysis
Mitchell, D. T., Lee, S. B., Trofin, L., Li, N., Nevanen, T. K., Söderlund, H., & Martin, C. R. (2002) · Journal of the American Chemical Society · doi:10.1021/ja027247b · Cited by 549
Self-citationNanoadsorbents: Classification, Preparation, and Applications (with Emphasis on Aqueous Media)
Khajeh, M., Laurent, S., & Dastafkan, K. (2013) · Chemical Reviews · doi:10.1021/cr400086v · Cited by 528
Coarse grain models and the computer simulation of soft materials
Nielsen, S. O., Lopez, C. F., Srinivas, G., & Klein, M. L. (2004) · Journal of Physics: Condensed Matter · doi:10.1088/0953-8984/16/15/r03 · Cited by 423
Metadata
- Authors
- Lee, S. B., Mitchell, D. T., Trofin, L., Nevanen, T. K., Söderlund, H., & Martin, C. R.
- Venue
- Science
- Published
- 2002-06-21
- Volume
- 296
- Issue
- 5576
- Pages
- 2198-2200
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2058713133
- Cited by
- 619
- References
- 0
- FWCI
- 14.87
- Type
- journal article
- Language
- en
- Open access
- closed
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: Antibody-Based Bio-Nanotube Membranes for Enantiomeric Drug Separations. https://app.cochat.ai/papers/10.1126/science.1071396
- The paper
- Lee, S. B., Mitchell, D. T., Trofin, L., Nevanen, T. K., Söderlund, H., & Martin, C. R. (2002). Antibody-Based Bio-Nanotube Membranes for Enantiomeric Drug Separations. Science. https://doi.org/10.1126/science.1071396
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.