Evidence map›Paper›PMID 39057463›Full record

ReviewGels (Basel, Switzerland)2024

Stimulus-Responsive Hydrogels for Targeted Cancer Therapy.

Raghu Solanki, Dhiraj Bhatia

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Gels (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

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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

2 authors.

Raghu SolankiDepartment of Biological Sciences and Engineering, Indian Institute of Technology Gandhinagar, Palaj 382355, Gujarat, India.ORCID 0000-0003-4970-9961
Dhiraj BhatiaDepartment of Biological Sciences and Engineering, Indian Institute of Technology Gandhinagar, Palaj 382355, Gujarat, India.ORCID 0000-0002-1478-6417

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a highly heterogeneous disease and remains a global health challenge affecting millions of human lives worldwide. Despite advancements in conventional treatments like surgery, chemotherapy, and immunotherapy, the rise of multidrug resistance, tumor recurrence, and their severe side effects and the complex nature of the tumor microenvironment (TME) necessitates innovative therapeutic approaches. Recently, stimulus-responsive nanomedicines designed to target TME characteristics (e.g., pH alterations, redox conditions, enzyme secretion) have gained attention for their potential to enhance anticancer efficacy while minimizing the adverse effects of chemotherapeutics/bioactive compounds. Among the various nanocarriers, hydrogels are intriguing due to their high-water content, adjustable mechanical characteristics, and responsiveness to external and internal stimuli, making them promising candidates for cancer therapy. These properties make hydrogels an ideal nanocarrier for controlled drug release within the TME. This review comprehensively surveys the latest advancements in the area of stimulus-responsive hydrogels for cancer therapy, exploring various stimuli-responsive mechanisms, including biological (e.g., pH, redox), chemical (e.g., enzymes, glucose), and physical (e.g., temperature, light), as well as dual- or multi-stimuli responsiveness. Furthermore, this review addresses the current developments and challenges in hydrogels in cancer treatment. Our aim is to provide readers with a comprehensive understanding of stimulus-responsive hydrogels for cancer treatment, offering novel perspectives on their development for cancer therapy and other medical applications.

Indexed as

cancerdrug deliveryhydrogelsstimuli-responsive

Identifiers

PMID39057463
PMCPMC11275390

What OpenQuestion holds

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Registered trials

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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.