Evidence map›Paper›PMID 40777315›Full record

ArticlebioRxiv : the preprint server for biology2025

An Atomic Force Microscopic analysis of Exosomes derived from Tumor Associated pluripotent Mesenchymal Stem Cells.

Tanmay Kulkarni, Simone Newell, Erik Armstrong, Narendra Banerjee, Jasmine Cuffee, Santanu Bhattacharya, Hirendra Banerjee

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Simone Newell
Erik Armstrong
Narendra BanerjeeORCID 0009-0004-4660-2266
Jasmine Cuffee
Santanu BhattacharyaORCID 0000-0003-3579-4317
Hirendra BanerjeeORCID 0000-0002-1836-1731

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mesenchymal stem cell (MSC)-derived exosomes are recognized as critical mediators within the tumor microenvironment (TME), exerting both pro- and anti-tumorigenic effects depending on contextual factors. These vesicles are also gaining attention for their potential as therapeutic vehicles in regenerative medicine and targeted drug delivery. However, the influence of the TME on the physical characteristics of MSC-derived exosomes remains poorly understood. In this study, we utilized Atomic Force Microscopy (AFM) to investigate the morphological and nanomechanical properties of MSC-derived exosomes under standard and TME-like conditions. AFM imaging in fluid mode preserved the native structure of exosomes and enabled high-resolution analysis of their topography, surface roughness, stiffness, adhesion, and deformation. AFM offers unique advantages in exosome research by enabling label-free, nanoscale analysis of vesicle properties in near-physiological conditions. The ability to detect such subtle but functionally significant changes highlights the relevance of AFM in exosome characterization and quality assessment. Our results revealed that exposure to the TME induces marked changes in exosomal membrane morphology and mechanical behavior, including increased surface heterogeneity, higher stiffness, and altered adhesive interactions. These biophysical alterations may reflect changes in membrane composition and protein or lipid cargo, potentially affecting exosome function, uptake, and therapeutic efficacy. Overall, our findings provide new insights into how the TME modulates MSC exosome biophysics and underscore the utility of AFM-based techniques for advancing the development of exosome-based diagnostics and therapies.

Identifiers

PMID40777315
PMCPMC12330461

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.