The outstanding questions in transplantation: It’s about time…
Bibliographic record
Abstract
To the Editor: Organ transplantation represents one of the most daring efforts of science and medicine to challenge end-stage organ diseases and ultimately death. This extraordinary gift of life would not have been possible without the early work of pioneers such as Jaboulay and Carrel in perfecting vascular anastomosis, and the scientific breakthroughs of Medawar and colleagues in understanding immune rejection. Outstanding courage and generosity of organ donors and recipients continue to inspire all of us to do more every day. Today, we look at the century-long history of extraordinary achievements by transplant scientists, clinicians, and patients with great pride but also with the dissatisfaction of knowing just how much we still don’t understand. More than 6 decades after the first successful kidney transplantation performed by Joseph Murray and colleagues at Peter Brigham Hospital in Boston, we are still facing tremendous challenges in improving our patients’ outcomes. Organ shortage, acute and chronic rejection, cardiovascular and renal complications of immunosuppressive medications, in addition to the increased risk of malignancy and infections, are only some of the current challenges in transplant medicine. Being part of this epic journey toward better patient outcomes in transplantation brings us great honor, but also carries the responsibility for us to work together and focus our efforts on the most pressing unanswered questions in transplantation. While we are all comfortable talking about what we know in transplantation, we are reluctant to talk about what we don’t know or do not even know how to approach. However, therein lie the answers to the challenges we are facing today. Within the American Society of Transplantation (AST), we are the Community of Basic Scientists (CoBS), collaborating with other AST Communities of Practice (COPs) including the Trainee and Young Faculty COP (TYFCOP), to create a platform that allows clinicians, scientists, and patients to meet and exchange ideas about the outstanding questions in transplantation. We thank the leadership of the AST for helping us create an online community called “Outstanding Questions in Transplantation” to host this discussion. We invite all members of the transplant community to actively participate and to share their ideas about the future direction of the transplantation field by logging in here: Outstanding Questions in Transplantation (http://community.myast.org/communities/community-home? Community Key=e89d51ba-8bdf-4db2-8d71-1908209dfd69). We are piloting this new site with the members of AST. We hope to offer access to others in the future. We envision that input of clinicians based on the challenges faced in their day-to-day clinical practice will be instrumental in allowing scientists to formulate key scientific questions that need to be addressed over the next few years. We also encourage patients to share their point of view on the most pressing challenges they face. We plan to share the information gathered over this year long process through a variety of knowledge translation activities (including a white paper to be submitted to the American Journal of Transplantation) that we hope will bring basic scientists and clinicians together to create a renewed sense of purpose to overcome the most pressing issues in the field of organ transplantation. The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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 | 0.010 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.017 | 0.047 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".