Mouse Alport podocytes are susceptible to AAV9 transduction in vivo
Bibliographic record
Abstract
INTRODUCTION: Alport syndrome features a defective glomerular basement membrane (GBM) due to variants in COL4A3, COL4A4, and COL4A5. The most severe forms, which lack the GBM's collagen α3α4α5(IV) network, progress from hematuria in early childhood to proteinuria, chronic kidney disease, and kidney failure by the age of ∼30. As a monogenic disease without specific treatments, and with podocytes being the only glomerular cells that synthesize collagen α3α4α5(IV), the ability to efficiently deliver genes to Alport podocytes could open up new possibilities for treatment. METHODS: ; Ai14 (Cre-activatable tdTomato) Alport mice, respectively. The kidneys were collected two weeks later and subjected to quantification of podocyte transduction by fluorescence assays using synaptopodin as a podocyte marker. RESULTS: ssAAV9-CAG-tdTomato delivered to controls failed to transduce podocytes, but heterozygous female and hemizygous male Alport podocytes showed a range of transduction efficiencies, from 1.8% to 26%, which correlated positively with levels of albuminuria. Similar correlation between podocyte transduction and albuminuria was observed in the more sensitive Ai14 system with scAAV9-CMV-Cre administration. A subset of tubular and mesangial cells could also be transduced, the former in Alport mice and the latter in both Alport and control mice. CONCLUSIONS: The Alport GBM becomes leaky to AAV9 as mice mature, allowing viruses to reach and transduce a substantial subset of podocytes. This is promising for someday using AAV9 or other vehicles in gene therapy for patients with Alport syndrome. Interestingly, mesangial cells of control and young Alport mice were moderately susceptible to transduction, demonstrating that gene delivery to mesangial cells in mice is a viable approach for investigating mesangial cell biology in any context.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".