PNA6, a Lactosyl Analogue of Angiotensin-(1—7), Reverses Pain Induced in Murine Models of Inflammation, Metastatic Bone Disease, and Chemotherapy-Induced Peripheral Neuropathy
Bibliographic record
Abstract
The renin-angiotensin system (RAS) plays a role in cardiovascular homeostasis and hydro-electrolyte balance influencing organ function throughout the body. The classical view of RAS focused on a single biologically active metabolite, the octapeptide angiotensin (Ang)ll, created by the Angiotensin-converting enzyme (ACE). The past two decades have revealed new functions for intermediate products of the RAS beyond their role as substrates. Angiotensin 1-7 (Ang-(1—7), a RAS peptide product with actions at the Mas receptor, reportedly prevents cardiovascular disease-induced cognitive decline and cancer-induced bone pain (CIBP). However, Ang-(1—7) has a short half-life in vivo; here, we hypothesized that activating the MasR1 with a lactoside Ang-(1—7) analogue- PNA6-would attenuate inflammatory, cancer pain confined to the long bones, and chemotherapy-induced peripheral neuropathy (CIPN) for a longer-lasting efficacious therapeutic effect. PNA6, Asp-Arg-Val-Tyr-Ile-His-Ser-(O-β-Lact)-amide, was successfully synthesized on solid phase peptide synthesis (SPPS). PNA6 significantly reversed inflammatory pain induced by 2% carrageenan in mice. In a second study modeling a complex pain state, E0771 breast adenocarcinoma cells were implanted into the femur of female C57BLK/6J wild-type mice to induce cancer-induced bone pain (CIBP). Both acute and chronic dosing of PNA6 significantly reduced the spontaneous pain behaviors associated with CIBP. A third murine model of platinum drug-induced painful peripheral neuropathy was established using oxaliplatin. Mice in the oxaliplatin-vehicle treatment groups demonstrated significant mechanical allodynia compared to oxaliplatin- PNA6 treatment group mice. These data suggest that PNA6 is a viable lead candidate for treating chronic inflammatory and complex neuropathic pain.
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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) | 0.001 | 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 | 0.002 |
| 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".