Evidence map›Paper›PMID 32228107›Full record

ArticleDrug delivery2020

Lysine-mediated hydroxyethyl starch-10-hydroxy camptothecin micelles for the treatment of liver cancer.

Guofei Li, Mingming Zhao, Limei Zhao

Open access · goldAbstract read
In one paragraph

Article in Drug delivery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Drug delivery · 2021
    Article
  11. Article
  12. Article
  13. Review
  14. 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 1 institution in 1 country.

Guofei LiDepartment of Pharmacy, Shengjing Hospital, China Medical University, Shenyang, China.ORCID http://orcid.org/0000-0001-6194-541X
Mingming ZhaoDepartment of Pharmacy, Shengjing Hospital, China Medical University, Shenyang, China.
Limei ZhaoDepartment of Pharmacy, Shengjing Hospital, China Medical University, Shenyang, China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver cancer is a malignant tumor with extremely high morbidity and mortality. At present, traditional chemotherapy is still the most commonly used therapeutic approach. However, serious side effects lead to the treatment of liver cancer is not ideal. Therefore, it is imperative to develop a new drug delivery system based on nanotechnology and liver cancer microenvironment. In this study, a pH/reduction/α-amylase multi-sensitive hydroxyethyl starch-10-hydroxy camptothecin micelles (HES-10-HCPT-SS-Ly) targeting over-expressed amino acid (AA) transporters on the surface of liver cancer cell by applying lysine were successfully synthesized. The prepared micelles showed regular structure, suitable particle size, and intelligent drug release property. Compared with conventional HES-10-HCPT micelles and 10-HCPT injection, HES-10-HCPT-SS-Ly micelles demonstrated better

Indexed as

AnimalsAntineoplastic Agents, PhytogenicCamptothecinCell SurvivalDrug CarriersDrug Delivery SystemsDrug LiberationHep G2 CellsHumansHydroxyethyl Starch DerivativesLiver NeoplasmsLysineMaleMiceMicellesMice, Nude10-hydroxycamptothecinAntineoplastic Agents, PhytogenicCamptothecinDrug CarriersHydroxyethyl Starch DerivativesLysineMicellesamino acid transporterschemotherapyHydroxyethyl starch conjugateliver cancer therapytargeted drug delivery

Identifiers

PMID32228107
PMCPMC7170360
OpenAlexW3013198806

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.