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Record W3048727725 · doi:10.3390/bioengineering7030094

Recent Advances of Polyaniline-Based Biomaterials for Phototherapeutic Treatments of Tumors and Bacterial Infections

2020· review· en· W3048727725 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

VenueBioengineering · 2020
Typereview
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPhotothermal therapyNanotechnologyBiocompatibilityPolyanilineMaterials scienceImmunogenicityMedicinePolymerImmunology

Abstract

fetched live from OpenAlex

Conventional treatments fail to completely eradicate tumor or bacterial infections due to their inherent shortcomings. In recent years, photothermal therapy (PTT) has emerged as an attractive treatment modality that relies on the absorption of photothermal agents (PTAs) at a specific wavelength, thereby transforming the excitation light energy into heat. The advantages of PTT are its high efficacy, specificity, and minimal damage to normal tissues. To this end, various inorganic nanomaterials such as gold nanostructures, carbon nanostructures, and transition metal dichalcogenides have been extensively explored for PTT applications. Subsequently, the focus has shifted to the development of polymeric PTAs, owing to their unique properties such as biodegradability, biocompatibility, non-immunogenicity, and low toxicity when compared to inorganic PTAs. Among various organic PTAs, polyaniline (PANI) is one of the best-known and earliest-reported organic PTAs. Hence, in this review, we cover the recent advances and progress of PANI-based biomaterials for PTT application in tumors and bacterial infections. The future prospects in this exciting area are also addressed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.030
GPT teacher head0.285
Teacher spread0.254 · 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