Evidence map›Paper›PMID 35404562›Full record

ArticleACS applied materials & interfaces2022

Fully Automated Computational Approach for Precisely Measuring Organelle Acidification with Optical pH Sensors.

Anil Chandra, Saumya Prasad, Francesco Alemanno, Maria De Luca, Riccardo Rizzo, Roberta Romano, Giuseppe Gigli, Cecilia Bucci, Adriano Barra, Loretta L Del Mercato

Open access · hybridAbstract read
In one paragraph

Article in ACS applied materials & interfaces, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Anil ChandraInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.ORCID 0000-0003-4553-931X
Saumya PrasadInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.
Francesco AlemannoInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.
Maria De LucaDipartimento di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy.
Riccardo RizzoInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.
Roberta RomanoDipartimento di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy.
Giuseppe GigliInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.
Cecilia BucciDipartimento di Scienze e Tecnologie Biologiche ed Ambientali (DiSTeBa), Università del Salento, Via Monteroni, Lecce 73100, Italy.
Adriano BarraDipartimento di Matematica e Fisica, Università del Salento, Via Monteroni, Lecce 73100, Italy.
Loretta L Del MercatoInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), Campus Ecotekne, Via Monteroni, Lecce 73100, Italy.ORCID 0000-0001-9733-7088
University of Salento · ITIstituto di Nanotecnologia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

pH balance and regulation within organelles are fundamental to cell homeostasis and proliferation. The ability to track pH in cells becomes significantly important to understand these processes in detail. Fluorescent sensors based on micro- and nanoparticles have been applied to measure intracellular pH; however, an accurate methodology to precisely monitor acidification kinetics of organelles in living cells has not been established, limiting the scope of this class of sensors. Here, silica-based fluorescent microparticles were utilized to probe the pH of intracellular organelles in MDA-MB-231 and MCF-7 breast cancer cells. In addition to the robust, ratiometric, trackable, and bioinert pH sensors, we developed a novel dimensionality reduction algorithm to automatically track and screen massive internalization events of pH sensors. We found that the mean acidification time is comparable among the two cell lines (Δ

Indexed as

Fluorescent DyesOrganellesHomeostasisHumansHydrogen-Ion ConcentrationMCF-7 CellsFluorescent Dyesautomated cluster analysisdata compressionfluorescencemicroparticle trackingorganelle acidificationpH sensingratiometric pH sensorssilica microparticles

Identifiers

PMID35404562
PMCPMC9052195
OpenAlexW4223569954

What Socratic 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 Socratic graph.