Evidence map›Paper›PMID 38740832›Full record

ArticleScientific reports2024

An in-silico modeling approach to separate exogenous and endogenous plasma insulin appearance, with application to inhaled insulin.

Agnese Piersanti, Giovanni Pacini, Andrea Tura, David Z D'Argenio, Micaela Morettini

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

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

5 authors.

Agnese PiersantiDepartment of Information Engineering, Università Politecnica Delle Marche, Via Brecce Bianche 12, Ancona, Italy.
Giovanni Pacini, Padua, Italy.
Andrea TuraCNR Institute of Neuroscience, Padua, Italy.
David Z D'ArgenioDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Micaela MorettiniDepartment of Information Engineering, Università Politecnica Delle Marche, Via Brecce Bianche 12, Ancona, Italy. m.morettini@univpm.it.

Funding

TrainingP41EB001978 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI REDLINE, SUSAN S. · 2003 to 2017
$18.1M
NIBIB NIH HHS P41 EB001978
6 · The paper itself

Abstract

The aim of this study was to develop a dynamic model-based approach to separately quantify the exogenous and endogenous contributions to total plasma insulin concentration and to apply it to assess the effects of inhaled-insulin administration on endogenous insulin secretion during a meal test. A three-step dynamic in-silico modeling approach was developed to estimate the two insulin contributions of total plasma insulin in a group of 21 healthy subjects who underwent two equivalent standardized meal tests on separate days, one of which preceded by inhalation of a Technosphere

Indexed as

Computer SimulationInsulinAdministration, InhalationBlood GlucoseFemaleHumansMaleModels, BiologicalBlood GlucoseInsulin

Identifiers

PMID38740832
PMCPMC11091049

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.