Abstract 5049: Development of huPBMC-NCG mice to study xenogenic graft versus host disease (GVHD)
Bibliographic record
Abstract
Abstract Graft versus host disease (GVHD) is a severe complication of allogeneic stem cell transplantation for leukemia treatment. NCG mice lacking functional murine T, B, NK cells as well as decreasing functional macrophage and dendritic cells could be used as recipients of human peripheral blood mononuclear cells (huPBMC) for the studies of human GVHD. In this study, huPBMC-NCG mice were developed by the engraftment of huPBMC into unconditioned or irradiated NCG mice. The engraftment kinetics, irradiation effect, and preclinical treatment were explored in these mice. After huPBMC engraftment, NCG mice developed GVHD symptoms, including body weight loss, fur loss, reduced activity, hunched posture and severe ruffling, and eventually led to mortality. We also observed human T cell trafficking to target organs including gut, heart, liver, skin, and lung by flow cytometry and immunohistochemistry. Interestingly, irradiation could significantly accelerate the onset of GVHD following huPBMC engraftment. Meanwhile, irradiated huPBMC-NCG mice presented less variability in the kinetics of GVHD and the frequency of this disease in comparison with unconditioned counterparts, thus providing a more stable model for human GVHD studies. For preclinical studies, we found immunomodulatory drugs including Abatacept (CTLA4-Ig) targeting APC cells or anti-Ly6G antibody targeting neutrophils could alleviate GVHD-associated symptoms along with improving overall survival of huPBMC-NCG mice. Taken together, this study established stable huPBMC-NCG mice to mimic the onset and development of human GVHD, which was helpful for the development of therapeutic intervention. Citation Format: Cunxiang Ju, Hongyan Sun, Dingyu Wang, Shiying Guo, Mingkun Zhang, Hainan Wu, Shuai Li, Chao Ju, Jing Zhao, Xiang Gao. Development of huPBMC-NCG mice to study xenogenic graft versus host disease (GVHD) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5049.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".