Evidence map›Paper›PMID 39354756›Full record

ArticleCurrent drug discovery technologies2025

Nirenjen Shanmugasundaram, Narayanan Jayasankar

Abstract read
PubMed Publisher
In one paragraph

Article in Current drug discovery technologies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Bioactive Furan Derivatives fromCurrent drug discovery technologies · 2026
    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

2 authors.

Nirenjen ShanmugasundaramDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology (SRMIST), Kattankulathur, Chengalpattu, 603203, Tamil Nadu, India.
Narayanan JayasankarDepartment of Pharmacology, SRM College of Pharmacy, SRM Institute of Science and Technology (SRMIST), Kattankulathur, Chengalpattu, 603203, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic wound healing poses a significant challenge due to the intricate disruptions in cellular and molecular processes induced by hyperglycaemia, leading to delayed or impaired tissue repair. Computational techniques offer a promising avenue for unravelling the complexities of diabetic wound healing by elucidating the molecular mechanisms involved. METHODOLOGY: This study utilized RESULTS AND DISCUSSION: Our findings have revealed olivetol to be a promising candidate for targeting multiple pathways implicated in diabetic wound healing. Its ability to modulate inflammation, oxidative stress, extracellular matrix remodeling, angiogenesis, and cell signaling suggests a multifaceted approach to promoting effective wound repair. Moreover, olivetol has been found to demonstrate strong binding affinity with key MRSA target proteins, indicating its potential as an antimicrobial agent against MRSA infections in diabetic wounds. The

conclusionOlivetol emerges as a promising candidate for targeted interventions in non-healing diabetic wounds, particularly due to its ability to address prolonged inflammation, a common obstacle in diabetic wound healing.

Indexed as

Diabetes MellitusWound HealingComputer SimulationHumansMolecular Docking SimulationMolecular Dynamics Simulationcomputational pharmacologyDiabetic wound healinghyperglycaemia.molecular dockingMRSA infectionsolivetol

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.