Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,091

The DOI matches its Crossref record.

Pakistan Journal of Pharmaceutical Sciences

Open access
·2019·Pakistan Journal of Pharmaceutical Sciences

Abstract

Lung cancer is the most typical form of cancer that results in death worldwide. Patients with non-small cell lung cancer (NSCLC) have an around 15% survival rate despite of advancement in cancer treatment. This study aimed to evaluate the combined effect of celecoxib and bevacizumab on NSCLC using A549 cells as an in vitro model. The A549 cells were culture and treated with celecoxib, bevacizumab and their combination and the cell proliferation was assessed using MTT assay, whereas cell apoptosis was analyzed using flowcytometry. The effects on the apoptotic genes were examined using western blotting, while qPCR was used for analyzing the VEGF and MMP-9 expression. Celecoxib, bevacizumab and their combination exhibited a dose dependent inhibition (p<0.001). The rate of apoptosis was 14.1% and 26.5% but when the two drugs were combined, the rate of apoptosis was significantly increased due to synergism by 52.2% (p<0.001). Western blotting displayed that co-treatment significantly upregulated proapoptotic genes (caspase-3 and -9) and downregulated anti-apoptotic gene (Bcl-2) (p<0.001). Additionally, VEGF and MMP-9 expression were both significantly reduced with co-treatment compared to the control (p<0.001). Celecoxib combined with bevacizumab synergistically inhibited NSCLC by inducing apoptosis and modulating VEGF and MMP-9 expression.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.36721/pjps

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 1,091

Metadata

Venue
Pakistan Journal of Pharmaceutical Sciences
Published
2019-12-11
ISSN
1011-601X (ISSN-L)
OpenAlex
W4249329707
Cited by
1,091
References
0
Type
paratext
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Pakistan Journal of Pharmaceutical Sciences. https://app.cochat.ai/papers/10.36721/pjps
The paper
Pakistan Journal of Pharmaceutical Sciences. (2019). Pakistan Journal of Pharmaceutical Sciences. https://doi.org/10.36721/pjps

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.