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Record W2384930828

Evaluation of the hot and cold characteristics of seven antiarrhythmic drugs by cytological method

2015· article· en· W2384930828 on OpenAlexaff
Wang Si-we

Bibliographic record

VenueZhonghua zhongyiyao zazhi · 2015
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsScience North
Fundersnot available
KeywordsMetoprolol TartrateMetoprololBisoprololPharmacologyDiltiazem hydrochloridePropafenoneDiltiazemHydrochlorideVerapamilMedicineChemistryInternal medicineCalciumBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Objective: To evaluate the hot and cold characteristics of 7 antiarrhythmic drugs.Methods: MTT assay was used to investigate the effect of 7 antiarrhythmic drugs on the growth and proliferation of SMMC7721 cells and MFC-7 cells in vitro.Morphological changes were observed with inverted microscope.Results: Diltiazem hydrochloride,verapamil hydrochloride,amiodarone hydrochloride,propafenone hydrochloride showed cold or cool characteristics,and metoprolol tartrate,bisoprolol fumarate,carvedilol showed hot or warm characteristics.Morphological observation demonstrated that cells treated with diltiazem hydrochloride,verapamil hydrochloride,amiodarone hydrochloride,propafenone hydrochloride showed lower cell density and rounder pyknosis.The cells treated with metoprolol tartrate,bisoprolol fumarate,carvedilol showed higher cell density,tighter cell structure and more vigorous growth.Conclusion: The cytological method could be used to evaluate the hot and cold characteristics of western drugs,which may provide a simple and practical evaluation method for Chinese medicalization of western drugs.

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)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.106
GPT teacher head0.412
Teacher spread0.306 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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