A standardized autopsy procurement allows for the comprehensive study of DIPG biology
Bibliographic record
Abstract
// Madhuri Kambhampati 1 , Jennifer P. Perez 1 , Sridevi Yadavilli 1 , Amanda M. Saratsis 1,2,3 , Ashley D. Hill 4 , Cheng-Ying Ho 4 , Eshini Panditharatna 1,7 , Melissa Markel 5 , Roger J. Packer 6 and Javad Nazarian 1,8 1 Research Center for Genetic Medicine, Children’s National Health System, Washington, DC, USA 2 Division of Pediatric Neurosurgery, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA 3 Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA 4 Division of Pathology, Children’s National Health System, Washington, DC, USA 5 Department of Neuro Oncology, Riley hospital for Children, Indiana University Health, Indianapolis, IN USA 6 Brain Tumor Institute, Center for Neuroscience and Behavioral Medicine, Children’s National Health System, Washington, DC, USA 7 Institute for Biomedical Sciences, George Washington University, Washington, DC, USA 8 Department of Integrative Systems Biology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA Correspondence to: Javad Nazarian, email: // Keywords : Diffuse Intrinsic Pontine Glioma (DIPG), Brainstem Glioma, Autopsy, Histone 3, Orthotopic Injection Received : December 09, 2014 Accepted : January 15, 2015 Published : January 24, 2015 Abstract Diffuse intrinsic pontine glioma (DIPG) is one of the least understood and most deadly childhood cancers. Historically, there has been a paucity of DIPG specimens for molecular analysis. However, due to the generous participation of DIPG families in programs for postmortem specimen donation, there has been a recent surge in molecular analysis of newly available tumor specimens. Collaborative efforts to share data and tumor specimens have resulted in rapid discoveries in other pediatric brain tumors, such as medulloblastoma, and therefore have the potential to shed light on the biology of DIPG. Given the generous gift of postmortem tissue donation from DIPG patients, there is a need for standardized postmortem specimen accrual to facilitate rapid and effective multi-institutional molecular studies. We developed and implemented an autopsy protocol for rapid procurement, documenting and storing these specimens. Sixteen autopsies were performed throughout the United States and Canada and processed using a standard protocol and inventory method, including specimen imaging, fixation, snap freezing, orthotopic injection, or preservation. This allowed for comparative clinical and biological studies of rare postmortem DIPG tissue specimens, generation of in vivo and in vitro models of DIPG, and detailed records to facilitate collaborative analysis.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".