Evidence map›Paper›PMID 21387035›Full record

ReviewIntegrative biology : quantitative biosciences from nano to macro2011

Bioengineering approaches to study multidrug resistance in tumor cells.

Brian Fallica, Guy Makin, Muhammad H Zaman

Open access · greenAbstract readReview
In one paragraph

Review in Integrative biology : quantitative biosciences from nano to macro, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Non-invasive imaging of PI3K/Akt/mTOR signalling in cancer.American journal of nuclear medicine and molecular imaging · 2012
    Article
  9. Article
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 2 countries.

Brian FallicaDepartment of Biomedical Engineering, Boston University, USA.
Guy Makin
Muhammad H Zaman
Boston University · USUniversity of Manchester · GB

Funding

TRAINING IN BIOMOLECULAR PHARMACOLOGYT32GM008541 · NIGMS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI FARB, DAVID H · 1997 to 2022
$5.2M
NIGMS NIH HHS T32 GM008541
6 · The paper itself

Abstract

The ability of cancer cells to become resistant to chemotherapeutic agents is a major challenge for the treatment of malignant tumors. Several strategies have emerged to attempt to inhibit chemoresistance, but the fact remains that resistance is a problem for every effective anticancer drug. The first part of this review will focus on the mechanisms of chemoresistance. It is important to understand the environmental cues, transport limitations and the cellular signaling pathways associated with chemoresistance before we can hope to effectively combat it. The second part of this review focuses on the work that needs to be done moving forward. Specifically, this section focuses on the necessity of translational research and interdisciplinary directives. It is critical that the expertise of oncologists, biologists, and engineers be brought together to attempt to tackle the problem. This discussion is from an engineering perspective, as the dialogue between engineers and other cancer researchers is the most challenging due to non-overlapping background knowledge. Chemoresistance is a complex and devastating process, meaning that we urgently need sophisticated methods to study the process of how cells become resistant.

Indexed as

Drug Resistance, MultipleAnimalsAntineoplastic AgentsBiomedical EngineeringCell Line, TumorDrug Evaluation, PreclinicalHumansNeoplasmsAntineoplastic Agents

Identifiers

PMID21387035
PMCPMC4437566
OpenAlexW2047049001

What OpenQuestion holds

Textmetadata
LicenceTDM
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.