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Record W1128887588 · doi:10.1089/ten.tec.2013.0203

Multimodal Ultrasound-Photoacoustic Imaging of Tissue Engineering Scaffolds and Blood Oxygen Saturation In and Around the Scaffolds

2013· article· en· W1128887588 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.

Bibliographic record

VenueTissue Engineering Part C Methods · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsFujiFilm VisualSonics (Canada)
FundersNational Institutes of Health
KeywordsPLGABiomedical engineeringMaterials scienceEx vivoScaffoldTissue engineeringIn vivoNanotechnologyNanoparticleMedicine

Abstract

fetched live from OpenAlex

Preclinical, noninvasive imaging of tissue engineering polymeric scaffold structure and/or the physiological processes such as blood oxygenation remains a challenge. In vitro or ex vivo, the widely used scaffold characterization modalities such as porosimetry, electron or optical microscopy, and X-ray microcomputed tomography have limitations or disadvantages-some are invasive or destructive, others have limited tissue penetration (few hundred micrometers) and/or show poor contrast under physiological conditions. Postmortem histological analysis, the most robust technique for the evaluation of neovascularization is obviously not appropriate for acquiring physiological or longitudinal data. In this study, we have explored the potential of ultrasound (US)-coregistered photoacoustic (PA) imaging as a noninvasive multimodal imaging modality to overcome some of the above challenges and/or provide complementary information. US-PA imaging was employed to characterize poly(lactic-co-glycolic acid) (PLGA) polymer scaffolds or single-walled carbon nanotube (SWCNT)-incorporated PLGA (SWCNT-PLGA) polymer scaffolds as well as blood oxygen saturation within and around the scaffolds. Ex vivo, PLGA and SWCNT-PLGA scaffolds were placed at 0.5, 2, and 6 mm depths in chicken breast tissues. PLGA scaffolds could be localized with US imaging, but generate no PA signal (excitation wavelengths 680 and 780 nm). SWCNT-PLGA scaffolds generated strong PA signals at both wavelengths due to the presence of the SWCNTs and could be localized with both US and PA imaging depths between 0.5-6 mm (lateral resolution = 90 μm, axial resolution = 40 μm). In vivo, PLGA and SWCNT-PLGA scaffolds were implanted in subcutaneous pockets at 2 mm depth in rats, and imaged at 7 and 14 days postsurgery. The anatomical position of both the scaffolds could be determined from the US images. Only SWCNT-PLGA scaffolds could be easily detected in the US-PA images. SWCNT-PLGA scaffolds had significant four times higher PA signal intensity compared with the surrounding tissue and PLGA scaffolds. In vivo blood oxygen saturation maps around and within the PLGA scaffolds could be obtained by PA imaging. There was no significant difference in oxygen saturation for the PLGA scaffolds at the two time points. The blood oxygen saturation maps complemented the histological analysis of neovascularization of the PLGA scaffolds.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.691
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.247
Teacher spread0.240 · 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