In Situ Hybridization for the Differentiation of Actinomyces and Nocardia in Tissue Sections
Bibliographic record
Abstract
The specific identification of filamentous bacteria in tissue sections can be difficult. The filamentous bacteria Actinomyces and Nocardia often produce similar host responses and single bacterial organisms seem morphologically similar; however, their differentiation may be clinically significant. In situ hybridization (ISH) may assist in the rapid and accurate identification of these microorganisms. In this study, DNA probes were directed against the variable regions of 16S ribosomal RNA genes of multiple Actinomyces and Nocardia spp. Probes were tested on 26 formalin-fixed, paraffin-embedded tissue specimens, each of which contained diagnostic foci of filamentous bacteria confirmed by both Gram and Grocott methenamine silver stains. On the basis of histology and clinical features, cases were classified as Actinomyces-related, n = 13 with 6 culture-proven cases and Nocardia-related, n = 13 with 11 culture-proven cases. Using this classification, all cases were assessed for cross-reactivity using other species-specific probes and probe specificity was determined. Overall, Gram and Grocott methenamine silver histochemical stains (100% sensitivity) were more sensitive than ISH (77% sensitivity for both Actinomyces and Nocardia probes). The slender caliber of filamentous bacteria was a limitation for ISH interpretation and necessitated careful examination of some slides. Probes demonstrated 100% specificity for identifying both species, 100% positive predictive value and 81% negative predictive value. No mixed infections were observed. This study demonstrates that ISH is highly specific for distinguishing between Actinomyces and Nocardia spp. in tissue sections. Although histochemical stains demonstrate greater sensitivity for organism detection, ISH is a rapid and specific technique that is especially useful for evaluating culture-negative or clinically unsuspected cases of filamentous bacterial infection.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".