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Record W2002093707 · doi:10.1117/12.2001464

Overview of photo-induced therapy for ATP production

2012· article· en· W2002093707 on OpenAlexaff
Mahmoud A. Abdalla, Agnès A. Nagy, Winnie N. Ye, Tofy Mussivand

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsWavelengthLight therapyAdenosine triphosphateLasing thresholdOptoelectronicsLaserTherapeutic windowIntensity (physics)Materials scienceOpticsBiophysicsMedicinePhysicsPharmacologyInternal medicineBiology

Abstract

fetched live from OpenAlex

The purpose of this report is to provide a review of the effects of low-power photo-induced therapy using lasers of different device parameters such as intensity, wavelength, lasing mechanism (i.e., pulsed or continuous) on the production of Adenosine triphosphate (ATP) in mammalian cells. This is a very important research topic as it is suggested in literature that there might be a relationship between the ATP levels and specific diseases. It has been shown that the ATP production was enhanced at wavelengths ranging between 600 nm and 1000 nm (also known as the optical window), in particular at 600nm, 632.8nm, 635nm, 650nm, and 904nm. However, certain experiments showed that the effectiveness of the photo-induced therapy was also dependent on the dosage and the duration of the supplied light. We present the research conclusions drawn from the experiments reported within the last decade, and provide a list of potential medical treatment(s) for patients using visible and near infrared (NIR) light.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.061
GPT teacher head0.312
Teacher spread0.251 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicPhotoreceptor and optogenetics researchFrench-language works237,207