Imaging Secondary Structure of Individual Amyloid Fibrils of a β<sub>2</sub>-Microglobulin Fragment Using Near-Field Infrared Spectroscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Amyloid fibril diseases are characterized by the abnormal production of aggregated proteins and are associated with many types of neuro- and physically degenerative diseases. X-ray diffraction techniques, solid-state magic-angle spinning NMR spectroscopy, circular dichroism (CD) spectroscopy, and transmission electron microscopy studies have been utilized to detect and examine the chemical, electronic, material, and structural properties of amyloid fibrils at up to angstrom spatial resolution. However, X-ray diffraction studies require crystals of the fibril to be analyzed, while other techniques can only probe the bulk solution or solid samples. In the work reported here, apertureless near-field scanning infrared microscopy (ANSIM) was used to probe the secondary structure of individual amyloid fibrils made from an in vitro solution. Simultaneous topographic and infrared images of individual amyloid fibrils synthesized from the #21-31 peptide fragment of β(2)-microglobulin were acquired. Using this technique, IR spectra of the amyloid fibrils were obtained with a spatial resolution of less than 30 nm. It is observed that the experimental scattered field spectrum correlates strongly with that calculated using the far-field absorption spectrum. The near-field images of the amyloid fibrils exhibit much lower scattering of the IR radiation at approximately 1630 cm(-1). In addition, the near-field images also indicate that composition and/or structural variations among individual amyloid fibrils were present.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it