Algorithmic Super-Resolution - STED-FM
Bibliographic record
Abstract
We acquired pairs confocal and STED images on our Abberior Infinity line microscope, a different microscope than the one used for the generation of the STED-FM dataset. The Vesicular Inhibitory Amino Acid Transporter (VGAT) was stained with Atto490LS. The images in this dataset correspond to the confocal images of the VGAT-LQHQ dataset. We registered the confocal image on the STED with translation using the SimpleITK library. Images were then cropped to 224x224 pixels for training. The STED image was acquired with 10 accumulations. The pixel dwell time was set at 10µs, the excitation power at 4.2µW (488 nm), and the STED depletion power at 88.1mW (775 nm). Method STED imaging | Super-resolution imaging was performed using an Abberior INFINITY STED microscope (Abberior Instruments GmbH, Germany). The system was equipped with a 60x oil immersion objective lens (NA 1.42; Olympus UPLXAPO60XO), a motorized stage, and adaptive optics with spherical aberration correction ranging from 0 to 0.30 during imaging. Wavelengths of 485nm and 640nm were used for the experiment. The system is equipped with a 775 nm depletion laser (40 MHz, 1.2 ns pulse duration; MPB Communications). All lasers were operated at 40MHz. The emitted fluorescence photons were detected by avalanche photodiode detectors (APDs) through a pinhole set at approximately 0.81 Airy unit. Emission from ATTO 490LS was collected using a tunable detection filter with a bandwidth of 650–755 nm. The acquired images were visualized and processed using the FIJI software (ImageJ, version 1.54p). Acute brain slices preparation | All animal procedures were conducted in accordance with the guidelines of the Animal Protection Committee of Université Laval. C57BL/6 mice (Charles River Laboratories, Kingston, NY) were sacrificed by intracardiac perfusion. Animals were first anesthetized via intraperitoneal injection of a 20% urethane solution. Residual blood was then washed out by intracardiac perfusion with ice-cold PBS, followed by perfusion with a hybrid fixative solution containing paraformaldehyde (PFA) and glyoxal, based on a solution described by Yao et al. [1] (4% PFA, 0.4% glyoxal, 0.1% methanol in PBS). Brains were collected and post-fixed in the same solution for 24 hours. Brains were collected and post-fixed in the same solution for 24 hours. Tissue was then sectioned into 40-µm-thick slices using a vibratome. Finally, slices were cryopreserved at −20 °C in a cryopreservation solution until use. Staining procedure | Brain slices were washed in PBS containing 0.1 M glycine, then permeabilized and blocked for 30 minutes in PBS (20 mM) containing 0.2% Triton X-100 and 2% normal goat serum. Slices were incubated overnight at 4 °C on a shaker with VGAT (Synaptic Systems, rabbit, Cat. No. 131 003) diluted in blocking solution (1:500). The following day, slices were incubated for 2 hours at room temperature on a shaker with goat anti-rabbit ATTO 490LS secondary antibody (Hypermol, Cat. No. 2309-1MG) and a gephyrin antibody fluorescence-labeled with abberior STAR RED (Synaptic System, mouse, Cat. No. 147 011AbRED) diluted in blocking solution (1:250 and 1:500, respectively). Slices were washed with PBS between immunostaining steps to wash out unbinded antibodies. Finally, the slices were mounted in PVA with DABCO for imaging. For the needs of the experiment, only gephyrin was imaged.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".