A gene therapy approach for long-term normalization of blood pressure in hypertensive mice by ANP-secreting human skin grafts
Bibliographic record
Abstract
The use of bioengineered human skin as a bioreactor to deliver therapeutic factors has a number of advantages including accessibility that allows manipulation and monitoring of genetically modified cells. We demonstrate a skin gene therapy approach that can regulate blood pressure and treat systemic hypertension by expressing atrial natriuretic peptide (ANP), a hormone able to decrease blood pressure, in bioengineered human skin equivalents (HSE). Additionally, the expression of a selectable marker gene, multidrug resistance (MDR) type 1, is linked to ANP expression on a bicistronic vector and was coexpressed in the human keratinocytes and fibroblasts of the HSE that were grafted onto immunocompromised mice. Topical treatments of grafted HSE with the antimitotic agent colchicine select for keratinocyte progenitors that express both MDR and ANP. Significant plasma levels of human ANP were detected in mice grafted with HSE expressing ANP from either keratinocytes or fibroblasts, and topical selection of grafted HSE resulted in persistent high levels of ANP expression in vivo. Mice with elevated plasma levels of human ANP showed lower renin levels and, correspondingly, had lower systemic blood pressure than controls. Furthermore, mice with HSE grafts expressing human ANP did not develop elevated blood pressure when fed a high-salt diet. These findings illustrate the potential of this human skin gene therapy approach to deliver therapeutic molecules systemically for long-term treatment of diverse diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".