A customized affordable multiplexed immunofluorescence method visualizes early changes in the mouse brain microenvironment upon laser cytoreduction
Bibliographic record
Abstract
Introduction: Multiplex immunofluorescence (mIF) utilizes distinct fluorophore-conjugated antibodies to enable the simultaneous visualization and quantification of multiple protein targets within a single tissue section. mIF allows high-resolution spatial mapping of cellular phenotypes within the native tissue microenvironment (TME). mIF facilitates the comprehensive analysis of complex biological systems, such as brain tumors, immune cell infiltration, and tissue heterogeneity. Laser interstitial thermal therapy (LITT) is a minimally invasive, hyperthermia-based laser cytoreductive method for the treatment of surgically inaccessible brain tumors, treatment-resistant epilepsy, and radiation necrosis. Laser-induced heat causes tissue damage, vascular leakage, and the appearance of heat-induced neo-antigens. There is an urgent clinical need to understand the elusive immunomodulatory roles of LITT in the brain TME. We describe a versatile, affordable, and customizable mIF method for the spatial imaging of multiple early tissue responses in post-LITT mouse brain. Methods: We have developed a customizable and affordable mIF protocol that uses standard histological and microscopy equipment to assess TME changes in formalin-fixed paraffin-embedded (FFPE) mouse brain tissue sections. We combined mIF with a laser cytoreduction workflow that uses MRI to monitor laser-induced tissue damage in post-LITT normal and tumor murine brains. Multiplex IF on individual tissue sections enabled the simultaneous spatial image analysis of multiple cellular and molecular immunotargets, including resident brain cell responses and immune cell infiltration, as exemplified with a mouse brain TME on Day 10 post-LITT. Results: targeted laser-induced hyperthermic brain tissue ablation on FFPE mouse brain sections on Day 10 post-LITT. This enabled the spatial visualization of activation states of resident brain cells and the emergence and distribution of diverse phagocytic immune cell populations at the post-LITT site. Conclusion: Multiplex IF on mouse models of laser cytoablation treatment in non-tumor and tumor brains offers a significant advancement by aiding in our understanding of repair and immune responses in post-LITT brains. Our customizable mIF protocol is cost-effective and simultaneously investigates the spatial distribution of multiple immune cell populations and the activation states of different resident brain cells in the post-LITT brain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".