Evidence map›Paper›PMID 30670935›Full record

ReviewDose-response : a publication of International Hormesis Society

Natural Products Mediated Targeting of Virally Infected Cancer.

Iram Fatima, Sobia Kanwal, Tariq Mahmood

Open access · goldAbstract readReview
In one paragraph

Review in Dose-response : a publication of International Hormesis Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 19 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Iram FatimaDepartment of Plant Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
Sobia KanwalDepartment of Zoology, University of Gujrat Sub-campus Rawalpindi, Rawalpindi, Pakistan.
Tariq MahmoodDepartment of Plant Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
Quaid-i-Azam University · PKUniversity of Gujrat · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of viral infection in developing cancer was determined in the start of 20th century. Until now, 8 different virus-associated cancers have been discovered and most of them progressed in immunosuppressed individuals. The aim of the present study is to look into the benefits of natural products in treating virally infected cancers. The study focuses on bioactive compounds derived from natural sources. Numerous pharmaceutical agents have been identified from plants (vincristine, vinblastine, stilbenes, combretastatin, and silymarin), marine organisms (bryostatins, cephalostatin, ecteinascidins, didemnin, and dolastatin), insects (cantharidin, mastoparan, parectadial, and cecropins), and microorganisms (vancomycin, rhizoxin, ansamitocins, mitomycin, and rapamycin). Beside these, various compounds have been observed from fruits and vegetables which can be utilized in anticancer therapy. These include curcumin in turmeric, resveratrol in red grapes, S-allyl cysteine in allium, allicin in garlic, catechins in green tea, and β-carotene in carrots. The present study addresses various types of virally infected cancers, their mechanism of action, and the role of different cell surface molecules elicited during viral binding and entry into the target cell along with the anticancer drugs derived from natural products by targeting screening of bioactive compounds from natural sources.

Indexed as

cancercell surface moleculesnatural sourcesvirus

Identifiers

PMID30670935
PMCPMC6328957
OpenAlexW2911085048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.