Evidence map›Paper›PMID 23761969›Full record

ReviewInternational journal of nanomedicine2013

Particle platforms for cancer immunotherapy.

Rita Elena Serda

Open access · goldAbstract readReview
In one paragraph

Review in International journal of nanomedicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

18 citing papers in PubMed, 56 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Polyelectrolyte-Enrobed Cancer Cells in View of Personalized Immune-Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2017
    Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Adjuvants for peptide-based cancer vaccines.Journal for immunotherapy of cancer · 2016
    Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
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

1 author at 1 institution in 1 country.

Rita Elena SerdaDepartment of Nanomedicine, The Methodist Hospital Research Institute, Houston, TX 77030, USA. reserda@tmhs.org
Houston Methodist · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Elevated understanding and respect for the relevance of the immune system in cancer development and therapy has led to increased development of immunotherapeutic regimens that target existing cancer cells and provide long-term immune surveillance and protection from cancer recurrence. This review discusses using particles as immune adjuvants to create vaccines and to augment the anticancer effects of conventional chemotherapeutics. Several particle prototypes are presented, including liposomes, polymer nanoparticles, and porous silicon microparticles, the latter existing as either single- or multiparticle platforms. The benefits of using particles include immune-cell targeting, codelivery of antigens and immunomodulatory agents, and sustained release of the therapeutic payload. Nanotherapeutic-based activation of the immune system is dependent on both intrinsic particle characteristics and on the immunomodulatory cargo, which may include danger signals known as pathogen-associated molecular patterns and cytokines for effector-cell activation.

Indexed as

ImmunotherapyNanomedicineNanoparticlesNeoplasmsAdjuvants, ImmunologicAnimalsAntineoplastic AgentsCancer VaccinesDendritic CellsHumansAdjuvants, ImmunologicAntineoplastic AgentsCancer Vaccinesadjuvantcancerdendritic cellimmunotherapyparticlevaccine

Identifiers

PMID23761969
PMCPMC3674015
OpenAlexW1970764871

What OpenQuestion holds

Textmetadata
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.