Evidence map›Paper›PMID 25173621›Full record

ReviewNeurosurgical review2015

"Extremely minimally invasive": recent advances in nanotechnology research and future applications in neurosurgery.

Tobias A Mattei, Azeem A Rehman

Abstract readReview
PubMed Publisher
In one paragraph

Review in Neurosurgical review, 2015. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Theranostic Nanomedicine for Malignant Gliomas.Frontiers in bioengineering and biotechnology · 2019
    Review
  7. Review
  8. Review
  9. Article
  10. 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

2 authors.

Tobias A MatteiDepartment of Neurosurgery, Brain & Spine Center-InvisionHealth/Buffalo-NY, 400 International Dr., Buffalo, NY, ZIP 14221, USA, tobiasmattei@yahoo.com.
Azeem A Rehman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The term "nanotechnology" refers to the development of materials and devices that have been designed with specific properties at the nanometer scale (10(-9) m), usually being less than 100 nm in size. Recent advances in nanotechnology have promised to enable visualization and intervention at the subcellular level, and its incorporation to future medical therapeutics is expected to bring new avenues for molecular imaging, targeted drug delivery, and personalized interventions. Although the central nervous system presents unique challenges to the implementation of new therapeutic strategies involving nanotechnology (such as the heterogeneous molecular environment of different CNS regions, the existence of multiple processing centers with different cytoarchitecture, and the presence of the blood-brain barrier), numerous studies have demonstrated that the incorporation of nanotechnology resources into the armamentarium of neurosurgery may lead to breakthrough advances in the near future. In this article, the authors present a critical review on the current 'state-of-the-art' of basic research in nanotechnology with special attention to those issues which present the greatest potential to generate major therapeutic progresses in the neurosurgical field, including nanoelectromechanical systems, nano-scaffolds for neural regeneration, sutureless anastomosis, molecular imaging, targeted drug delivery, and theranostic strategies.

Indexed as

Drug Delivery SystemsMinimally Invasive Surgical ProceduresNeurosurgical ProceduresCentral Nervous SystemHumansNanotechnologyNerve Regeneration

Identifiers

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.