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Record W2028837010 · doi:10.1159/000024521

Clustering of Murine Lung Metastases Reflects Fractal Nonuniformity in Regional Lung Blood Flow

2000· article· en· W2028837010 on OpenAlexaff
Wayne S. Kendal

Bibliographic record

VenueInvasion and Metastasis · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsOttawa Regional Cancer Foundation
Fundersnot available
KeywordsMetastasisLungCluster analysisCellCancer researchCancerBiologyPathologyMedicineInternal medicineGeneticsMathematicsStatistics

Abstract

fetched live from OpenAlex

In the experimental metastasis assay certain animals, from groups of similarly treated animals, develop more lung metastases than expected from random chance alone. This clustering of metastases is characterized by a power function relationship, sigma(2) = amu(b), between the variance, sigma(2), and mean, mu, of the numbers of lung metastases per animal (a and b are constants). To determine whether this clustering could be an artifact of experimental metastasis, whether it could be influenced by different experimental conditions, and to attempt to clarify its cause, 22 published data sets from experimental metastasis utilizing 2,145 mice, as well as 8 data sets from spontaneous metastasis utilizing 1,020 mice were analyzed. In these experiments cell cloning, cell-cell fusion, treatment with a protein kinase C inhibitor, treatment with cell adhesion compounds, and transfection with either the ras oncogene, the sialidase gene, or the urokinase sense and antisense genes were used to influence metastasis. They employed 14 different cell lines and 6 different strains of inbred mice. Clustering of metastasis was evident in animals from the spontaneous metastasis assays as well as from the experimental metastasis assays. It was apparent whether mice were injected with tumor cells derived from clones or from cell lines. Clustering was demonstrated within each data set, regardless of the experimental conditions employed. A single variance to mean power function (with a = 2.2 and b = 1.51) characterized the clustering in the 30 data sets. The regional distribution of blood flow through lungs and other organs is nonuniform, exhibiting a fractal symmetry on change of scale. This symmetry implies that the variance of a region's blood flow is related to its mean by the same power function as was observed with metastasis. Indeed, measurements of blood flow from isolated canine lungs yield b = 1.56, similar to the corresponding figure from murine lung metastasis. These findings lend support to the hypothesis that the observed clustering of metastases is a consequence of fractal variations in lung blood flow.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.271
Teacher spread0.258 · 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 designSimulation or modeling
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".

Quick stats

Citations9
Published2000
Admission routes1
Has abstractyes

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