Cultivation of the Bacillus of Whipple's Disease
Bibliographic record
Abstract
BACKGROUND: Whipple's disease is a systemic bacterial infection, but to date no isolate of the bacterium has been established in subculture, and no strain of this bacterium has been available for study. METHODS: Using specimens from the aortic [corrected] valve of a patient with endocarditis due to Whipple's disease, we isolated and propagated a bacterium by inoculation in a human fibroblast cell line (HEL) with the use of a shell-vial assay. We tested serum samples from our patient, other patients with Whipple's disease, and control subjects for the presence of antibodies to this bacterium. RESULTS: The bacterium of Whipple's disease was grown successfully in HEL cells, and we established subcultures of the isolate. Indirect immunofluorescence assays showed that the patient's serum reacted specifically against the bacterium. Seven of 9 serum samples from patients with Whipple's disease had IgM antibody titers of 1:50 or more, as compared with 3 of 40 samples from the control subjects (P<0.001). Polyclonal antibodies against the bacterium were generated by inoculation of the microorganism into mice and were used to detect bacteria in the excised cardiac tissue from our patient on immunohistochemical analysis. The 16S ribosomal RNA gene of the cultured bacterium was identical to the sequence for Tropheryma whippelii identified previously in tissue samples from patients with Whipple's disease. The strain we have grown is available in the French National Collection. CONCLUSIONS: We cultivated the bacterium of Whipple's disease, detected specific antibodies in tissue from the source patient, and generated specific antibodies in mice to be used in the immunodetection of the microorganism in tissues. The development of a serologic test for Whipple's disease may now be possible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".