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Record W1849025727 · doi:10.5539/apr.v7n6p13

Reactive Oxygen Species Registration in Planarian Regeneration

2015· article· en· W1849025727 on OpenAlexvenueno aff
Х. П. Тирас, Sergey V. Gudkov, V. I. Emelyanenko, К. Б. Асланиди

Bibliographic record

VenueApplied Physics Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlanarian Biology and Electrostimulation
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsPlanarianReactive oxygen speciesRegeneration (biology)PhagocytosisCell biologyOxidative stressBiophysicsMitosisLuminescenceBiologyIn vivoApoptosisKineticsChemistryBiochemistryMaterials science

Abstract

fetched live from OpenAlex

<p class="1Body">Reactive oxygen species (ROS) are directly involved in cell proliferation, differentiation and apoptosis in a variety of organisms. We studied kinetics of own luminescence induced by changes of ROS in early stages of planarian regeneration. Kinetics of chemiluminescence were measured in intact planarians and the same individuals after decapitation within 15 hours. We analyzed the traumatic fluorescent signal obtained as the difference between kinetics of intact and decapitated planarians. It was found that regeneration is accompanied by changes in the content of ROS correlated with the energy-intensive process in regenerating planarians. Oxidative stress was caused by damage to cell membranes in the dissection of the planarian and it was accompanied by a drop in the intensity of luminescence with a time constant of about 3.6 hours. Phagocytosis of dying cells by neoblasts was accompanied by an increase of the luminescence intensity after 2 - 3 hours after decapitation. Neoblast mitosis was described by two maximums of luminescence over 5.1 hours and 8.3 hours after decapitation. For the first time we demonstrated the opportunity of registering the physiological state of pluripotent stem cells at the level of the organism <em>in vivo</em>.</p>

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)0.001
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 score0.080
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.102
GPT teacher head0.346
Teacher spread0.243 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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