Evidence map›Paper›PMID 26193431›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2015

pH-Responsive Isoniazid-Loaded Nanoparticles Markedly Improve Tuberculosis Treatment in Mice.

Angela A Hwang, Bai-Yu Lee, Daniel L Clemens, Barbara Jane Dillon, Jeffrey I Zink, Marcus A Horwitz

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

26 citing papers in PubMed, 90 citations in OpenAlex.

  1. Antimicrobial Resistance inAntibiotics (Basel, Switzerland) · 2026
    Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Organically Modified Mesoporous Silica Nanoparticles against Bacterial Resistance.Chemistry of materials : a publication of the American Chemical Society · 2023
    Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Potential Impact of Long-Acting Products on the Control of Tuberculosis: Preclinical Advancements and Translational Tools in Preventive Treatment.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Article
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  19. Article
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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

6 authors at 2 institutions in 1 country.

Angela A HwangDepartment of Chemistry and Biochemistry, University of California, Los Angeles, 3013 Young Dr. East, CA, 90095-1569, USA.
Bai-Yu LeeDivision of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CHS 37-121, 10833 Le Conte Ave., CA, 90095-1688, USA.
Daniel L ClemensDivision of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CHS 37-121, 10833 Le Conte Ave., CA, 90095-1688, USA.
Barbara Jane DillonDivision of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CHS 37-121, 10833 Le Conte Ave., CA, 90095-1688, USA.
Jeffrey I ZinkDepartment of Chemistry and Biochemistry, University of California, Los Angeles, 3013 Young Dr. East, CA, 90095-1569, USA.
Marcus A HorwitzDivision of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CHS 37-121, 10833 Le Conte Ave., CA, 90095-1688, USA.
University of California, Los Angeles · USCalifornia NanoSystems Institute · US

Funding

Leadership and Operations Center (LOC), AIDS Clinical Trials Group (ACTG); LOC 1/UM1AI068636 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Joseph J Eron, RAJESH T GANDHI · 2011 to 2026
$1073.1M
NIAID NIH HHS UM1 AI068636NIAID NIH HHS UM1AI068636
6 · The paper itself

Abstract

Tuberculosis is a major global health problem for which improved therapeutics are needed to shorten the course of treatment and combat emergence of drug resistance. Mycobacterium tuberculosis, the etiologic agent of tuberculosis, is an intracellular pathogen of mononuclear phagocytes. As such, it is an ideal pathogen for nanotherapeutics because macrophages avidly ingest nanoparticles even without specific targeting molecules. Hence, a nanoparticle drug delivery system has the potential to target and deliver high concentrations of drug directly into M. tuberculosis-infected cells-greatly enhancing efficacy while avoiding off-target toxicities. Stimulus-responsive mesoporous silica nanoparticles of two different sizes, 100 and 50 nm, are developed as carriers for the major anti-tuberculosis drug isoniazid in a prodrug configuration. The drug is captured by the aldehyde-functionalized nanoparticle via hydrazone bond formation and coated with poly(ethylene imine)-poly(ethylene glycol) (PEI-PEG). The drug is released from the nanoparticles in response to acidic pH at levels that naturally occur within acidified endolysosomes. It is demonstrated that isoniazid-loaded PEI-PEG-coated nanoparticles are avidly ingested by M. tuberculosis-infected human macrophages and kill the intracellular bacteria in a dose-dependent manner. It is further demonstrated in a mouse model of pulmonary tuberculosis that the nanoparticles are well tolerated and much more efficacious than an equivalent amount of free drug.

Indexed as

AldehydesAnimalsCHO CellsCricetinaeCricetulusDisease Models, AnimalFemaleHumansHydrogen-Ion ConcentrationIsoniazidLungMacrophagesMice, Inbred BALB CMicrobial ViabilityMycobacterium tuberculosisNanoparticlesAldehydesIsoniazidPolyethylene GlycolsPolyethyleneimineProdrugsSilicon Dioxidedrug deliverymesoporous silicamesoporous silica nanoparticlesmultifunctional nanoparticlestuberculosis

Identifiers

PMID26193431
PMCPMC5628743
OpenAlexW2100807825

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.