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Record W2290866488 · doi:10.1134/s1819712415040066

Semax prevents the death of tyrosine hydroxylase-positive neurons in a mixed neuroglial cell culture derived from the embryonic rat mesencephalon in a model of 6-hydroxydopamine-induced neurotoxicity

2015· article· en· W2290866488 on OpenAlexfundno aff
О. В. Долотов, К. О. Еремин, Л. А. Андреева, Е. В. Новосадова, К. С. Раевский, N. F. Myasoedov, И. А. Гривенников

Bibliographic record

VenueNeurochemical Journal · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsnot available
FundersInstitute of GeneticsRussian Academy of SciencesRussian Science Foundation
KeywordsHydroxydopamineTyrosine hydroxylaseNeurotoxinNeurotoxicityDopaminergicTyrosineProgrammed cell deathEmbryonic stem cellInternal medicineChemistryBiologyEndocrinologyPharmacologyToxicityDopamineBiochemistryMedicineApoptosis

Abstract

fetched live from OpenAlex

The peptide Semax (MEHFPGP), which is an analogue of the ACTH (4–10) fragment, has a wide spectrum of activity in the nervous system of mammals, including humans. Using a model of neurotoxicity induced by hydroxydopamine, we studied the ability of Semax to prevent the death of tyrosine hydroxylase-positive neurons in a primary mixed neuroglial cell culture derived from the mesencephalon of rat embryos. We found that the application of 6-hydroxydopamine at concentrations of 2 and 5 µM to the culture medium induced a dose-dependent loss of tyrosine hydroxylase-positive neurons by 25 and 65%, respectively. The application of Semax at a concentration of 0.1 µM 30 min prior to treatment with 5 µM 6-hydroxydopamine significantly increased the number of tyrosine hydroxylase-positive neurons by 30–40%. Addition of Semax to cell cultures 24 h prior to the neurotoxin did not reveal the protective effect of the peptide. These data show that Semax may potentially be used for the treatment of some neurodegenerative diseases that are associated with a loss of dopaminergic neurons in the CNS.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
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 head0.053
GPT teacher head0.265
Teacher spread0.211 · 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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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