Evidence map›Paper›PMID 39320092›Full record

ArticleAmerican journal of physiology. Lung cellular and molecular physiology2024

Inference of alveolar capillary network connectivity from blood flow dynamics.

Kerstin Schmid, Andy L Olivares, Oscar Camara, Wolfgang M Kuebler, Matthias Ochs, Andreas C Hocke, Sabine C Fischer

Abstract read
In one paragraph

Article in American journal of physiology. Lung cellular and molecular physiology, 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

7 authors.

Kerstin SchmidFakultät für Biologie, Center for Computational and Theoretical Biology, Julius-Maximilians-Universität Würzburg, Würzburg, Germany.
Andy L OlivaresSensing in Physiology and Biomedicine (PhySense), Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Oscar CamaraSensing in Physiology and Biomedicine (PhySense), Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.ORCID 0000-0002-5125-6132
Wolfgang M KueblerInstitute of Physiology, Charité-Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0003-4100-2961
Matthias OchsInstitute of Functional Anatomy, Charité-Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0002-0936-6979
Andreas C HockeDepartment of Infectious Diseases, Respiratory Medicine and Critical Care, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Sabine C FischerFakultät für Biologie, Center for Computational and Theoretical Biology, Julius-Maximilians-Universität Würzburg, Würzburg, Germany.ORCID 0000-0001-7237-814X

Funding

Deutsche Forschungsgemeinschaft (DFG) SFB1449 B01Deutsche Forschungsgemeinschaft (DFG) SFB-TR 84Einstein Stiftung Berlin (Einstein Foundation Berlin) EC3REuropean Molecular Biology Organization (EMBO) 9271Universitaetsbund Wuerzburg AZ21-16
6 · The paper itself

Abstract

The intricate lung structure is crucial for gas exchange within the alveolar region. Despite extensive research, questions remain about the connection between capillaries and the vascular tree. We propose a computational approach combining three-dimensional (3-D) morphological modeling with computational fluid dynamics simulations to explore alveolar capillary network connectivity based on blood flow dynamics. We developed three-dimensional sheet-flow models to accurately represent alveolar capillary morphology and conducted simulations to predict flow velocities and pressure distributions. Our approach leverages functional features to identify plausible system architectures. Given capillary flow velocities and arteriole-to-venule pressure drops, we deduced arteriole connectivity details. Preliminary analyses for nonhuman species indicate a single alveolus connects to at least two 20-µm arterioles or one 30-µm arteriole. Hence, our approach narrows down potential connectivity scenarios, but a unique solution may not always be expected. Integrating our blood flow model results into our previously published gas exchange application, Alvin, we linked these scenarios to gas exchange efficiency. We found that increased blood flow velocity correlates with higher gas exchange efficiency. Our study provides insights into pulmonary microvasculature structure by evaluating blood flow dynamics, offering a new strategy to explore the morphology-physiology relationship that is applicable to other tissues and organs. Future availability of experimental data will be crucial in validating and refining our computational models and hypotheses.

Indexed as

CapillariesPulmonary AlveoliAnimalsArteriolesBlood Flow VelocityComputer SimulationHumansHydrodynamicsModels, CardiovascularPulmonary Gas Exchangearteriole connectivitycomputational fluid dynamicsdata-driven in silico modelingfunctional morphologypulmonary microvasculature

Identifiers

PMID39320092
PMCPMC11684946

What OpenQuestion 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 OpenQuestion graph.