Evidence map›Paper›PMID 41333430›Full record

ArticleResearch square2025

High-dimensional solid-state NMR facilitated by transverse-mixing optimal control.

Alexander Klein, Jan Blahut, Suresh K Vasa, Dmitrii Blohkin, Zdeněk Tošner, Rasmus Linser

Abstract readPreprint
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexander KleinDepartment Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany.ORCID 0000-0002-4963-1626
Jan BlahutDepartment of Chemistry, Faculty of Science, Charles University, Albertov 6, 12842 Prague, Czech Republic.ORCID 0000-0001-7752-8370
Suresh K VasaDepartment Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany.
Dmitrii BlohkinDepartment Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany.
Zdeněk TošnerDepartment of Chemistry, Faculty of Science, Charles University, Albertov 6, 12842 Prague, Czech Republic.ORCID 0000-0003-2741-9154
Rasmus LinserDepartment Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany.ORCID 0000-0001-8983-2935

Funding

TRD3 NMRbox: Bayesian AnalyticsP41GM111135 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI HOCH, JEFFREY C · 2015 to 2024
$14.0M
NIGMS NIH HHS P41 GM111135
6 · The paper itself

Abstract

Owing to fast magic-angle spinning, solid-state nuclear magnetic resonance has evolved as a versatile method to decipher protein structure, dynamics, and chemical properties. While higher-dimensional approaches such as 4D and 5D correlation spectra are generally capable of exceeding the established molecular-weight limitations by ameliorating signal overlap, their intrinsic implications for sensitivity and measurement times required have severely limited these important prospects in practice. Here we show that the extensive use of dedicated transverse-mixing optimal control pulses (TROPs) in high-dimensional experiments to enable concomitant transfer of complex signals along complex magnetization transfer pathways can reduce the necessary measurement time by an order of magnitude. Owing to the multiplicative benefits of the enhancement for successive indirect chemical-shift dimensions, combined with non-linear benefits upon spectral reconstruction, the combination of non-uniformly sampled, higher-dimensional approaches with an extensive use of TROPs hence presents itself as transformative for the conventional limitations of solid-state NMR.

Indexed as

Higher-dimensionality experimentsNMR SpectroscopyResonance assignmentSensitivity enhancement

Identifiers

PMID41333430
PMCPMC12668127

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.