Response: Re: Analysis of Fecal DNA Methylation to Detect Gastrointestinal Neoplasia
Bibliographic record
Abstract
We appreciate the comment made by Dr Hayatsu and would like to provide further clarification of our methodology to address his concerns. From the outset, we would like to say that the actual concentration of sodium bisulfite in our study was not “8.64 N.” We dissolved 1.8 g sodium bisulfite in 2.0 mL distilled water; however, following the addition of sodium bisulfite, the final volume of this solution became 2.4 mL. Consequently, the actual concentration of sodium bisulfite in this suspension was approximately 7.2 M and not 8.64 N. We put 125 μL of this suspension into 200-μL liquid fecal specimens with 17.5 μL of 10 mM hydroquinone and 7.5 μL of 12 M NaOH for the incubation step (here, the final bisulfite concentration was 2.6 M). A complete conversion of cytosine residues to uracils is absolutely essential for the success of our fecal DNA methylation assay and conventional bisulfite methods do typically recommend that the final bisulfite concentration be 3 M or more during the incubation step ( 1 ). However, whereas conventional bisulfite methods often are geared toward bisulfite modification of greater quantities of DNA (eg, 1 μg DNA), our one-step bisulfite modification needs to convert only a very small amount of DNA in dilute liquified fecal specimens. Therefore, after rigorous experimentation, we determined that 2.6 M sodium bisulfite is sufficient to convert cytosine to uracil in our one-step bisulfite modification methodology. We have confirmed complete cytosine conversion in our polymerase chain reaction products from fecal DNA, and some of the results from our assay development were presented in our article ( 2 ). We are now engaged in a large cohort study to screen people with gastrointestinal cancers by our “Hi-SA” fecal methylation assay at multiple sites in Japan, Canada, and the United States. So far, we have not experienced any problems with incomplete cytosine–uracil conversion in our fecal methylation assay.
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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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.030 | 0.024 |
| Insufficient payload (model declined to judge) | 0.031 | 0.028 |
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".