Evidence map›Paper›PMID 39148286›Full record

ArticleACS nano2024

Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping.

Aceer Nadeem, Sarah Lyons, Aidan Kindopp, Amanda Jamieson, Daniel Roxbury

Abstract read
In one paragraph

Article in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. High-throughput SWCNT NIR-II screening enables cell andbioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Aceer NadeemDepartment of Chemical Engineering, University of Rhode Island, Kingston, Rhode Island 02881, United States.ORCID 0000-0002-5381-3561
Sarah LyonsDepartment of Chemical Engineering, University of Rhode Island, Kingston, Rhode Island 02881, United States.
Aidan KindoppDepartment of Chemical Engineering, University of Rhode Island, Kingston, Rhode Island 02881, United States.
Amanda JamiesonDepartment of Molecular Microbiology and Immunology, Brown University, Providence, Rhode Island 02912, United States.ORCID 0000-0002-5781-9231
Daniel RoxburyDepartment of Chemical Engineering, University of Rhode Island, Kingston, Rhode Island 02881, United States.

Funding

Training CoreP20GM103430 · NIGMS · UNIVERSITY OF RHODE ISLAND · PI Ang Cai · 2012 to 2026
$63.6M
Central role of Caspase-8 in control of host tolerance and resistance mechanisms in pulmonary macrophage populations during severe respiratory infectionsR01HL165259 · NHLBI · BROWN UNIVERSITY · PI Amanda M Jamieson · 2023 to 2026
$3.6M
Influence of the lung microbiome on macrophage responses to lung damageR01HL126887 · NHLBI · BROWN UNIVERSITY · PI JAMIESON, AMANDA M · 2018 to 2022
$2.4M
NHLBI NIH HHS R01 HL126887NHLBI NIH HHS R01 HL165259NIGMS NIH HHS P20 GM103430
6 · The paper itself

Abstract

Spectral fingerprinting has emerged as a powerful tool that is adept at identifying chemical compounds and deciphering complex interactions within cells and engineered nanomaterials. Using near-infrared (NIR) fluorescence spectral fingerprinting coupled with machine learning techniques, we uncover complex interactions between DNA-functionalized single-walled carbon nanotubes (DNA-SWCNTs) and live macrophage cells, enabling

Indexed as

DNAMachine LearningMacrophagesNanotubes, CarbonPhenotypeAnimalsMiceRAW 264.7 CellsSpectroscopy, Near-InfraredDNANanotubes, Carbonconfocal Raman microscopyintracellular processingmachine learningnanomaterialsnear-infrared fluorescencesingle-walled carbon nanotubesspectral fingerprinting

Identifiers

PMID39148286
PMCPMC12020776

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.