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Record W2168563493 · doi:10.4021/gr2008.10.1231

Diphenyl Dimethyl Bicarboxylate in the Treatment of Viral Hepatitis, Adjuvant or Curative?

2008· review· en· W2168563493 on OpenAlexvenueno aff
Chen Wang

Bibliographic record

VenueGastroenterology Research · 2008
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdjuvantMalignancyViral hepatitisGastroenterologyInternal medicineClinical trialHepatitisAdjuvant therapyLiver diseasePharmacologyImmunologyChemotherapy

Abstract

fetched live from OpenAlex

Diphenyl dimethyl bicarboxylate (DDB) has been used in some countries as hepatoprotectant adjuvant in the treatment of liver diseases, such as chronic viral hepatitis, chemical or drug induced hepatic damage. Its early confirmed efficacy is to normalize elevated blood alanine aminotransferase (ALT) from different etiologies, however, it can rarely affect the rest hepatic enzymes. In addition, the lowering or normalization of ALT in most cases occurs during DDB treatment, withdrawal of DDB administration results in ALT re-elevated. Hence, for a long time, it has been only used as adjuvant of liver disease therapy. It is still controversial that whether DDB can be beneficial to liver histology. The normalization of ALT in hepatitis does not indicate therapeutic efficacy if without substantial liver histology improvement. In recent years, more studies showed that DDB might have new therapeutical potentials in liver diseases, it may have the effect of anti-viral, anti-malignancy. These new findings were mostly based on the in vitro or animal experiments, more basic studies and clinical trials are needed to ascertain these efficacies, prior to that stage, it is recommended to be cautious to apply DDB clinically for anti-virus and anti-malignancy purposes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.461
GPT teacher head0.563
Teacher spread0.103 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2008
Admission routes1
Has abstractyes

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