Synthesis and Characterization of Multi-Modal Phase-Change Porphyrin Droplets
Bibliographic record
Abstract
Phase-change droplets are a class of ultrasound contrast agents that can convert into echogenic microbubbles in situ with the application of sufficient acoustic energy. Droplets are smaller and more stable than their microbubble counterparts. However, traditional ultrasound contrast agents are not trackable beyond acoustic feedback measurements, which makes quantifying contrast agent bio-distribution or accumulation ex vivo difficult. Researchers may have to rely on fluorescent or optically absorbent companion diagnostic particles to infer bio-distribution. The purpose of this protocol is to detail steps for creating multi-modal phase-change porphyrin droplets using a condensation method. Porphyrins are fluorescent molecules with distinct absorbance bands that can be conjugated onto lipids and incorporated into droplets to extend droplet versatility, enabling more robust bio-distribution while retaining acoustic properties. Seven formulations with varying porphyrin-lipid and base lipid contents were made to investigate microbubble and droplet size distributions. Characterizations suited to porphyrin-containing structures are also described in the protocol to demonstrate their analytic versatility in-solution. Sizing showed that the post-condensed mean diameters were 1.72 to 2.38 times smaller than precursor populations. Absorbance characterization showed intact assemblies had a Q-band peak of 700 nm while disrupted samples had an absorbance peak at 671 nm. Fluorescence characterization showed intact 30% porphyrin-lipid assemblies were fluorescently quenched (>97%), with fluorescence recovery achieved upon disruption. Acoustic vaporization showed that porphyrin droplets were non-echogenic at lower pressures and could be converted into echogenic microbubbles with sufficient pressures. These characterizations show the potential for porphyrin droplets to eliminate the need for absorbance or fluorescence-based companion diagnostic strategies to quantify ultrasound contrast agent bio-distribution for delivery or therapeutic applications in vivo or ex vivo.
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".