Comparing the Potential of Helmholtz and Planar NMR Microcoils for Analysis of Intact Biological Samples
Bibliographic record
Abstract
Nuclear magnetic resonance (NMR) spectroscopy has played an integral role in medical and environmental metabolic research. However, smaller biological entities, such as eggs and small tissue samples, are becoming increasingly important to better understand toxicity, biological growth/development, and diseases. Unfortunately, their small sizes make them difficult to study using conventional 5 mm NMR probes due to limited sensitivity. The use of microcoil NMR holds great potential for the analysis of such samples, where the coil can be designed to match the sample size to significantly improve NMR mass sensitivity and the filling factor. Here, we compare the potential of planar and Helmholtz microcoil designs to execute complex experiments for the analysis of intact, mass-limited biological samples. The planar coil offers the advantage of an open access design, potentially allowing flow systems to be incorporated and varying sample sizes to be studied; however, its relatively inhomogeneous B 1 field leads to reduced NMR performance. The Helmholtz microcoil overcomes this drawback with its symmetrical design, improving B 1 homogeneity across the sample but with the caveat that the size and shape of the sample is limited to the spacing between the two parallel coils. The line shape, sensitivity, and RF performance are compared on both coils using standard samples and biological samples. This study found that the Helmholtz microcoil used here considerably outperforms the planar coil in multipulse experiments and has great potential to study complex biological samples in the 50–200 nL range.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".