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Record W4400047106 · doi:10.3390/nano14131093

Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer’s and Other Neurodegenerative Diseases

2024· article· en· W4400047106 on OpenAlexafffund
Elisabetta Di Gregorio, Michael Staelens, Nazanin Hosseinkhah, Mahroo Karimpoor, Janine Liburd, Lew Lim, Karthik Shankar, Jack A. Tuszyński

Bibliographic record

VenueNanomaterials · 2024
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsRaman spectroscopyTransition (genetics)Helix (gastropod)SpectroscopyNeurodegenerationMaterials scienceChemistryBiophysicsNanotechnologyMedicineBiologyPhysicsBiochemistryOpticsDiseasePathologyGene

Abstract

fetched live from OpenAlex

In small clinical studies, the application of transcranial photobiomodulation (PBM), which typically delivers low-intensity near-infrared (NIR) to treat the brain, has led to some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, despite the extensive literature detailing the mechanisms of action underlying PBM outcomes, the specific mechanisms affecting neurodegenerative diseases are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and thus provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer’s and other neurodegenerative diseases. Thus, we investigated the effects of PBM on these cellular structures in the quest for insights into the underlying therapeutic mechanisms. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300–1900 cm−1)—in particular, in the amide I band (1600–1700 cm−1)—were used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed, producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of polymerized NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent increase in β-sheets compared to the control samples. This PBM-induced α-helix to β-sheet transition connects to reduced microtubule stability and the introduction of dynamism to allow for the remodeling and, consequently, refreshing of microtubule structures. This newly discovered mechanism could have implications for reducing the risks associated with brain aging, including neurodegenerative diseases like Alzheimer’s disease, through the introduction of an intervention following this transition.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.573

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 head0.035
GPT teacher head0.356
Teacher spread0.320 · 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 teacher head, 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

Citations8
Published2024
Admission routes2
Has abstractyes

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