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Record W3083266420 · doi:10.1002/jbio.202000209

Use of photoacoustic imaging for monitoring vascular disrupting cancer treatments

2020· article· en· W3083266420 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Biophotonics · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsToronto Metropolitan UniversitySt. Michael's Hospital
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaRyerson University
KeywordsSalineHemoglobinPathologyMedicineCancerIndocyanine greenParenchymaBiomedical engineeringChemistryInternal medicine

Abstract

fetched live from OpenAlex

Vascular disrupting agents disrupt tumor vessels, blocking the nutritional and oxygen supply tumors need to thrive. This is achieved by damaging the endothelium lining of blood vessels, resulting in red blood cells (RBCs) entering the tumor parenchyma. RBCs present in the extracellular matrix are exposed to external stressors resulting in biochemical and physiological changes. The detection of these changes can be used to monitor the efficacy of cancer treatments. Spectroscopic photoacoustic (PA) imaging is an ideal candidate for probing RBCs due to their high optical absorption relative to surrounding tissue. The goal of this work is to use PA imaging to monitor the efficacy of the vascular disrupting agent 5,6-Dimethylxanthenone-4-acetic acid (DMXAA) through quantitative analysis. Then, 4T1 breast cancer cells were injected subcutaneously into the left hind leg of eight BALB/c mice. After 10 days, half of the mice were treated with 15 mg/kg of DMXAA and the other half were injected with saline. All mice were imaged using the VevoLAZR X PA system before treatment, 24 and 72 hours after treatment. The imaging was done at six wavelengths and linear spectral unmixing was applied to the PA images to quantify three forms of hemoglobin (oxy, deoxy and met-hemoglobin). After imaging, tumors were histologically processed and H&E and TUNEL staining were used to detect the tissue damage induced by the DMXAA treatment. The total hemoglobin concentration remained unchanged after treatment for the saline treated mice. For DMXAA treated mice, a 10% increase of deoxyhemoglobin concentration was detected 24 hours after treatment and a 22.6% decrease in total hemoglobin concentration was observed by 72 hours. A decrease in the PA spectral slope parameters was measured 24 hours after treatment. This suggests that DMXAA induces vascular damage, causing red blood cells to extravasate. Furthermore, H&E staining of the tumor showed areas of bleeding with erythrocyte deposition. These observations are further supported by the increase in TUNEL staining in DMXAA treated tumors, revealing increased cell death due to vascular disruption. This study demonstrates the capability of PA imaging to monitor tumor vessel disruption by the vascular disrupting agent DMXAA.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.263
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it