Bibliographic record
Abstract
PURPOSE OF REVIEW: Several viruses have recently gained importance for the transplant recipient. The purpose of this review is to give an update on emerging viruses in transplantation. RECENT FINDINGS: BK virus-associated nephropathy (BKVAN) causes graft loss after kidney transplantation. Immunosuppression lowering strategies have now been shown to have benefit in decreasing the incidence of BKVAN. Guidelines for screening, prevention, and therapy have also been developed. Another polyomavirus, JC virus, is a cause of progressive multifocal leukoencephalopathy and has also gained prominence due to the increasing use of monoclonal antibodies in transplant recipients. The significance of human herpesvirus-6 and -7 continues to be debated in the literature, and new data is available on their association with clinical disease. Finally, newly discovered respiratory viruses, such as human metapneumovirus, bocavirus, KI and WU viruses, have also been described in transplant recipients. Human metapneumovirus appears to cause significant respiratory disease whereas the significance of bocavirus, KI and WU viruses in transplant recipients remains uncertain. SUMMARY: Viral infections, such as polyomaviruses, human herpesvirus-6 and -7 and respiratory viruses, are emerging as causes of significant disease in transplantation. Antiviral options for these viruses are limited, and decreasing immunosuppression is the cornerstone of therapy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".