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Record W3207975923 · doi:10.1101/2021.10.15.464509

Blood flow synchronization in renal microcirculation - a high-resolution imaging study

2021· preprint· en· W3207975923 on OpenAlexaff
Dmitry D. Postnov, Donald J. Marsh, W. A. Cupples, Niels‐Henrik Holstein‐Rathlou, Olga Sosnovtseva

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsSimon Fraser University
FundersH. Lundbeck A/SNovo Nordisk FondenNovo NordiskLundbeckfonden
KeywordsRenal blood flowBlood flowMicrocirculationKidneySpeckle patternAngiotensin IIWaveletVasodilationChemistryInternal medicineMedicinePhysicsComputer scienceBlood pressureOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

ABSTRACT Aims Internephron signalling and interaction are fundamental for kidney function. Earlier studies have shown that nephrons signal to each other over short distances and adjust their activity accordingly. Micropuncture experiments revealed synchronous clusters of 2-3 nephrons formed from such interactions, while imaging and modelling results suggested the possibility of larger clusters. Such clusters are expected to play an important role in renal autoregulation, but their presence has not been confirmed and their size has not been estimated. In this study, we present methodology for high resolution renal blood flow imaging and apply it to estimate frequency and phase angle differences in kidney blood vessels under normal conditions and after administration of the vasoactive agents angiotensin II and acetylcholine. Methods and results To resolve signals from separate arterioles in a sufficiently large field of view, we developed a method for renal laser speckle contrast imaging. Our setup provides imaging of blood flow in the kidney cortex with a limit of image resolution at 0.8 μ m per pixel and imaging frequency of 160Hz. We used the method to record from 1.5×1.5 mm 2 sections of the renal surface in anaesthetised Sprague-Dawley rats in unstimulated conditions and during IV infusion of the vasoconstrictor angiotensin II or the vasodilator acetylcholine. In each section, we resolved and segmented 94.8±15.66 individual arterioles and venules, and analyzed blood flow using wavelet spectral analysis to identify clusters of synchronized blood vessels. Conclusions We observed spatial and temporal evolution of blood vessel clusters of various sizes, including the formation of large (>90 vessels) long-lived clusters (>10 periods) locked at the frequency of the tubular glomerular feedback (TGF) mechanism. The analysis showed that synchronization patterns and thus the co-operative dynamics of nephrons change significantly when either of the vasoactive agents is administered. On average, synchronization was stronger (larger clusters, longer duration) with angiotensin II administration than in the unstimulated state or with acetyl choline. While it weakens with distance, increased synchronization duration spanned the whole field of view, and likely, beyond it. Neighbouring vessels tend to demonstrate in-phase synchronization, especially in the vasoconstricted condition, which is expected to cause locally increased pressure variation. Our results confirm both the presence of the local synchronization in the renal microcirculatory blood flow and the fact that it changes depending on the condition of the vascular network and the blood pressure, which might have further implications for the role of such synchronization in pathologies development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.238
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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