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Record W4409735377 · doi:10.1021/acs.jpclett.4c03546

Imaging Ultraweak Photon Emission from Living and Dead Mice and from Plants under Stress

2025· article· en· W4409735377 on OpenAlexafffund
Vahid Salari, V. Seshan, L. Frankle, David England, Christoph Simon, Daniel Oblak

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2025
Typearticle
Languageen
FieldMedicine
TopicBiofield Effects and Biophysics
Canadian institutionsNational Research Council CanadaHotchkiss Brain InstituteUniversity of Calgary
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsPhysicsOpticsChemistryBiophysicsBiology

Abstract

fetched live from OpenAlex

) in the spectral range of 200-1000 nm, has been observed in all living systems that have been examined. Here, we report experiments that exemplify the ability of novel imaging systems to detect variations in UPE for a set of physiologically important scenarios. We use electron-multiplying charge-coupled device (EMCCD) and charge-coupled device (CCD) cameras to capture single visible-wavelength photons with low noise and quantum efficiencies higher than 90%. Our investigation reveals significant contrast between the UPE from live vs dead mice. In plants, we observed that an increase in the temperature and injuries both caused an increase in UPE intensity. Moreover, chemical treatments modified the UPE emission characteristics of plants, particularly the application of a local anesthetic (benzocaine) to injury, which showed the highest emission among the compounds tested. As a result, UPE imaging provides the possibility of non-invasive label-free imaging of vitality in animals and the responses of plants to stress.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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

Citations8
Published2025
Admission routes2
Has abstractyes

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