Blocking of Intrinsic Fluorescence is Necessary Prior to the Immuno-fluorescence Study of Piglet Gonocytes.
Bibliographic record
Abstract
Gonocytes can be identified in situ and in histological cross-sections by their unique morphological attributes and distinctive topography within the seminiferous cords/tubules; however, specific biomarkers are required for their accurate quantification. In search for such a specific biomarker for piglet gonocytes, we encountered an intense auto-fluorescence in both neonatal testis tissue and disassociated testis cells. This intrinsic fluorescence was not previously described in neonatal pig testis, and could blur the distinction between specific and non-specific immune-fluorescence signals, interfering with characterization of piglet gonocytes. Therefore, the aim of the present study was to examine this intrinsic fluorescence in both the piglet testis tissue and cells, followed by developing an effective method to block the auto-fluorescence. We found that a number of granules within the testis interstitial cells were inherently fluorescent, detectable using epifluorescent microscope, confocal laser scanning microscope, or flow cytometry. The emission wavelength of the auto-fluorescent substance ranged from 425 to 700 nm, a range that could potentially interfere with the commonly used fluorophores. Following treatment of the testis tissue sections with Sudan Black B for 10-15 min or testis cells for 8 min, the intrinsic fluorescence was completely masked, allowing specific staining of gonocytes with lectin Dolichos biflorus agglutinin (DBA). We speculate that the lipofuscin within Leydig cell granules was mainly responsible for the observed intrinsic fluorescence in piglet testes. The method developed in the present study will facilitate the identification and characterization of piglet gonocytes using immuno-fluorescence techniques. (poster)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".