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Record W2895757673 · doi:10.18240/ijo.2018.08.05

Cytotoxic effect of interleukin-8 in retinal ganglion cells and its possible mechanisms

2018· article· en· W2895757673 on OpenAlexaff
Jingjing Wang, Williams Walana, Bing Wang, Jing Wei, Lu Xia, Jya‐Wei Cheng, John Gordon, Jingmin Li, Fang Li

Bibliographic record

VenueInternational Journal of Ophthalmology · 2018
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsMedicineCytotoxic T cellRetinalNeuroscienceOphthalmologyGeneticsIn vitro

Abstract

fetched live from OpenAlex

AIM: To investigate the effect of interleukin-8 (IL-8) on neural retinal ganglion cells (RGCs) and whether it can be alleviated by G31P. METHODS: RGC-5 cells were exposed to IL-8 with or without its specific receptor antagonist G31P for 24h, and the cell viability was assessed by Cell Counting Kit 8 (CCK-8). Apoptosis was measured by examining nuclear morphology and quantifying with flow cytometry. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) and Western blot were used to investigate the expression of apoptosis-related genes. RESULTS: CCK-8 assay showed that IL-8 significantly inhibits the viability of RGC-5 cells in a dose-dependent manner. Cell apoptosis assays exhibited higher apoptotic rate in IL-8 treatment group compared to control group. We further found that IL-8 could promote Bax and caspase-3 expressions, but decrease the level of Bcl-2 in the aspect of mRNA and protein. However, pre-treatment with G31P partly attenuated these effects in RGC-5 cells (P<0.05). CONCLUSION: These results indicate that anti-proliferation effects of IL-8 through induction of cell apoptosis regulated by Bcl-2, Bax and caspase-3 expressions, can be ameliorated by G31P.

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)0.000
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 score0.065
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.328
Teacher spread0.310 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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