Biodistribution and dosimetry of <sup>89</sup> Zirconium‐labeled microbiota transplants in the pig gut
Bibliographic record
Abstract
Abstract Background The gastrointestinal (GI) microbiota, composed of diverse microbial communities, is essential for physiological processes, including immune modulation. Strains such as Escherichia coli Nissle 1917 support gut health by reducing inflammation and resisting pathogens. Microbial therapies using such strains may restore GI balance and offer alternatives to antibiotics, whose overuse contributes to antibiotic resistance. However, effective treatment will require optimizing delivery and understanding microbial dissemination and engraftment. Purpose We developed a method to monitor microbial migration and GI permeability post‐ingestion using hybrid PET/MRI. To simulate probiotic therapy, bacteria were radiolabeled with 89 Zr, encapsulated, and administered to pigs. Organ level and whole‐body dosimetry was determined from the time activity curves recorded over 7 days post ingestion. Methods We administered 89 Zr‐labeled Lactobacillus crispatus ATCC33820 (Gram‐positive) to six female Duroc pigs (weight = 33.3 ± 4.6 kg) and E. coli Nissle 1917 (Gram‐negative). Scans were performed between 6 h and 7 days post‐ingestion using a hybrid PET/MRI system. The mean administered dose was 74.7 ± 12.9 MBq. Whole‐body PET scans were acquired simultaneously with MRI using a T 2 ‐weighted HASTE sequence. Images were processed using 3D‐Slicer co‐registering PET with MRI and semi‐automated organ segmentation was performed. Gender‐averaged human equivalent organ‐level effective doses (ED) and whole body ED were calculated using OLINDA. Results PET imaging showed 89 Zr‐labeled L. crispatus and E. coli post‐ingestion localized primarily within the GI tract before excretion within feces. The highest mean ED for 89 Zr‐labeled L. crispatus and E. coli were in the distal colon (26.8 ± 4.9 µSv/MBq and 28.4 ± 7.9 µSv/MBq, respectively) and proximal colon (17.9 ± 3.7 µSv/MBq and 18.4 ± 5.1 µSv/MBq, respectively). EDs in other organs were low. Whole body ED were 60.5 ± 9.5 µSv/MBq ( L. crispatus ) and 66.7 ± 14.9 µSv/MBq ( E. coli ). Conclusions The whole‐body ED for L. crispatus and E. coli is lower than reported values for ingested tracers, such as that from 89 Zr labelled antibodies and 111 In labelled “meals” used to determine gut transit times. Hence ingestion of 89 Zr labelled bacteria shows promise for becoming a human nuclear‐medicine procedure to determine the effectiveness of probiotic therapies.
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 | 0.000 | 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 | 0.000 |
| 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".