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Record W2992471635

PROTECTION AGAINST IRON NEUROTOXICITY BY FACTORS RELEVANT IN MULTIPLE SCLEROSIS

2014· article· en· W2992471635 on OpenAlexaffvenueabout
Yasamin Mahjoub

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMinocyclineNeurotoxicityNeuroprotectionMultiple sclerosisOxidative stressMedicineAllopregnanoloneMicrogliaPregnancyCentral nervous systemPhysiologyPharmacologyInternal medicineEndocrinologyImmunologyBiologyToxicityAntibioticsInflammationBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Multiple sclerosis (MS) is the most common disabling neurological condition affecting young adults, and the prevalence of the disease in Canada, at 240 per 100000, is one of the highest in the world. Neuronal degeneration is thought to contribute to progression in multiple sclerosis (MS). Iron accumulation in the central nervous system (CNS) of MS patients may lead to neuronal degeneration, partly by enhancing oxidative stress. Women with MS tend to have fewer clinical relapses during pregnancy. Minocycline, a tetracycline antibiotic with neuroprotective properties, has garnered interest in the treatment of MS. Based on these observations, we hypothesized that pregnancy-associated hormones and minocycline would protect against iron neurotoxicity.METHODS Primary human foetal neuronal cultures were plated at 100,000 cell/well in 96-well plates and pretreated with s-estradiol, progesterone, prolactin, allopregnanolone, and several tetracycline antibiotics for 24 hours (n=4). Cultures were then exposed to a 24-hour FeSO4 challenge, after which they were fixed with 4% paraformaldehyde. Immunocytochemistry was used to mark microtubule associated protein-2 (MAP-2), a neuronal marker in culture. MAP-2 positive neurons were quantified objectively using ImageXpress Micro.RESULTS24-hour exposure to FeSO4 resulted in significant, concentration-dependent loss of MAP-2 positive neurons. Pre-treatment with progesterone and minocycline preserved the number of MAP-2 positive neurons compared to FeSO4 alone. Protection by minocycline was dependent on its co-presence with iron, suggesting a chemical interaction that may include alleviating oxidative stress; removing minocycline prior to iron exposure negated the protection. The effect of minocycline was compared to that of four other tetracycline antibiotics (tetracycline, oxycycline, doxycycline, demeclocycline), and only minocycline resulted in a preservation of MAP-2 positive neurons compared to iron alone. At the concentrations investigated, none of the pregnancy hormones examined (i.e. progesterone, s-estradiol, estriol and allopregnanolone at 300ng/mL and prolactin at 30nM) were protective against iron.DISCUSSION AND CONCLUSIONS The accumulation of iron in the CNS of MS can have neurotoxic outcomes.  This results of this experiment showed that minocycline can protect against the neurotoxicity of iron, possibly through a mechanism involving chemical interaction that could include countering oxidative stress. Since minocycline is being investigated in the treatment of MS, these results may bode well for its therapeutic efficacy. Furthermore, these findings may aid in development of treatments to reduce neurodegeneration in MS and other conditions involving iron accumulation and neurotoxicity.

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 score0.006

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 integrity0.0000.000
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 head0.156
GPT teacher head0.316
Teacher spread0.160 · 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".

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Citations0
Published2014
Admission routes3
Has abstractyes

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