Monosodium Glutamate Reduces <sup>68</sup>Ga-PSMA-11 Uptake in Salivary Glands and Kidneys in a Preclinical Prostate Cancer Model
Bibliographic record
Abstract
We evaluated the ability of monosodium glutamate (MSG) to reduce salivary and kidney uptake of a prostate-specific membrane antigen (PSMA) radioligand without affecting tumor uptake. Methods: LNCaP tumor–bearing mice were intraperitoneally injected with MSG (657, 329, or 164 mg/kg) or phosphate-buffered saline (PBS). Fifteen minutes later, the mice were intravenously administered 68Ga-PSMA-11. PET/CT imaging and biodistribution studies were performed 1 h after administration. Results: Tumor uptake (percentage injected dose per gram [%ID]) was not statistically different between groups, at 8.42 ± 1.40 %ID in the 657 mg/kg group, 7.19 ± 0.86 %ID in the 329 mg/kg group, 8.20 ± 2.44 %ID in the 164 mg/kg group, and 8.67 ± 1.97 %ID in the PBS group. Kidney uptake was significantly lower in the 657 mg/kg group (85.8 ± 24.2 %ID) than in the 329 mg/kg (159 ± 26.2 %ID), 164 mg/kg (211 ± 27.4 %ID), and PBS groups (182 ± 33.5 %ID) (P < 0.001). Salivary gland uptake was lower in the 657 mg/kg (3.72 ± 2.12 %ID) and 329 mg/kg (5.74 ± 0.62 %ID) groups than in the PBS group (10.04 ± 2.52 %ID) (P < 0.01). Conclusion: MSG decreased salivary and kidney uptake of 68Ga-PSMA-11 in a dose-dependent manner, whereas tumor uptake was unaffected.
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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) | 0.001 | 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".