Evidence map›Paper›PMID 38605211›Full record

ArticleAAPS PharmSciTech2024

Natural Polymer-Based Nanogel for pH-Responsive Delivery of Sorafenib Tosylate in Hemangiosarcoma.

Kiran K Mali, Yogeshkumar N Gavhane, Rita D Chakole

Abstract read
PubMed Publisher
In one paragraph

Article in AAPS PharmSciTech, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Kiran K MaliDepartment of Pharmaceutics, Government College of Pharmacy, Karad, Shivaji University, Kolhapur, Maharashtra, 415124, India. kiran.pharma1997@gmail.com.ORCID http://orcid.org/0000-0002-8051-716X
Yogeshkumar N GavhaneDepartment of Pharmaceutics, Government College of Pharmacy, Karad, Shivaji University, Kolhapur, Maharashtra, 415124, India.
Rita D ChakoleDepartment of Pharmacy, Government College of Pharmacy, Karad, Shivaji University, Kolhapur, Maharashtra, 415124, India.
Shivaji University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart nanomedicinal treatment for cancer manifests a solubility challenge with inherent nanoscale size and nonspecific release with stimuli-responsive potential. This is the limelight in novel chemotherapy to pursue physiochemical differences between the tumor microenvironment (TME) and normal cells, which introduces active groups of nanocarriers responding to various stimuli, endowing them with concise responses to various tumor-related signals. The nanogels were successfully prepared by a modified solvent evaporation technique. Nine batches were formulated by changing the chitosan concentration (12, 14, 16 mg/ml) and sonication time (5, 10, 15 min). The formulations were optimized for particle size and zeta potential with high percent entrapment efficiency (%EE) through Central Composite Design software. The optimized batch F7 had a 182-nm size and high zeta potential (64.5 mV) with 98% EE. The drug release of F7 was higher at pH 6 (97.556%) than at pH 7.4 (45.113%). The pharmacokinetic study shows that the release follows the Hixon plot model (R

Indexed as

HemangiosarcomaPolyethylene GlycolsPolyethyleneiminePolymersAnimalsDogsDrug CarriersHydrogen-Ion ConcentrationNanogelsSorafenibTumor MicroenvironmentDrug CarriersNanogelspolyethylene glycol polyethyleneimine nanogelPolyethylene GlycolsPolyethyleneiminePolymersSorafenibcationic polymerchitosanhemangiosarcomananogelnatural polymer

Identifiers

PMID38605211
OpenAlexW4394710402

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.