MétaCan
Menu
Back to cohort
Record W1969103895 · doi:10.4103/0253-7613.66840

Antiamnesic effect of stevioside in scopolamine-treated rats

2010· article· en· W1969103895 on OpenAlexaff
Nirmal Singh, Deepika Sharma, Munish Puri, A K Tiwary, Amteshwar Singh Jaggi

Bibliographic record

VenueIndian Journal of Pharmacology · 2010
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsTBARSSteviosideMorris water navigation taskOxidative stressThiobarbituric acidChemistryPharmacologyAchéGlutathioneCholinergicMemory impairmentAcetylcholinesteraseEndocrinologyPsychologyMedicineLipid peroxidationBiochemistryNeuroscienceCognitionEnzyme

Abstract

fetched live from OpenAlex

The present study was undertaken to explore the potential of stevioside in memory dysfunction of rats. Memory impairment was produced by scopolamine (0.5 mg/kg, i.p.) in animals. Morris water maze (MWM) test was employed to assess learning and memory. Brain acetylcholinestrase enzyme (AChE) activity was measured to assess the central cholinergic activity. The levels of brain thiobarbituric acid-reactive species (TBARS) and reduced glutathione (GSH) were estimated to assess the degree of oxidative stress. Scopolamine administration induced significant impairment of learning and memory in rats, as indicated by a marked decrease in MWM performance. Scopolamine administration also produced a significant enhancement of brain AChE activity and brain oxidative stress (increase in TBARS and decrease in GSH) levels. Pretreatment of stevioside (250 mg/kg dose orally) significantly reversed scopolamine-induced learning and memory deficits along with attenuation of scopolamine-induced rise in brain AChE activity and brain oxidative stress levels. It may be concluded that stevioside exerts a memory-preservative effect in cognitive deficits of rats possibly through its multiple actions.

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 score0.030
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.307
Teacher spread0.301 · 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

Citations52
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueIndian Journal of PharmacologySame topicBiochemical Analysis and Sensing TechniquesFrench-language works237,207