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Record W4285019182 · doi:10.1101/2022.07.08.499362

Cytocapsular cancer evolution analyses of 311 kinds of cancers

2022· preprint· en· W4285019182 on OpenAlexfundno aff
Tingfang Yi, Gerhard Wagner

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMathematics
TopicMathematical Biology Tumor Growth
Canadian institutionsnot available
FundersMcGill University
KeywordsCancerCancer cellMetastasisCancer researchSomatic evolution in cancerMedicineBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Cancer is a leading cause of human lethality. Cytocapsular tube, a newly discovered cancer cell specific organelle in vivo , plays pleiotropic biological functions and its generation distinguishes incomplete from complete cancer cells. It is essential for complete malignant tumor growth, cancer metastasis, conventional cancer drug pan-resistance, and cancer relapse. However, mechanisms of cytocapsular cancer evolution are still elusive. Here, we investigated cytocapsular cancer evolution in 311 kinds/subtype of cancers, including 265 types/subtypes of solid cancers and 46 types/subtypes of liquid/hematological cancers. We analyzed 9,856 pieces of annotated clinical tissue samples from 9,682 cancer patients in the asymptotic early stage, Stages I-IV, and before, during and after cancer treatments. We discovered that cytocapsular cancer evolution in solid cancers includes: transformation, formation of incomplete cancer cells, transition to complete cancer cells surrounded by cytocapsulae (CC), merging of complete cancer cells by devolution, formation of cytocapsular tubes (CCTs) and complete malignant tumors in superlarge CC. This is followed by generation of CCT networks, cancer metastasis, CCT network-tumor system (CNTS), CCT degradation and decomposition, and spatiotemporal moving CNTS. In addition, cytocapsular cancer evolution related to liquid ( hematological) cancers including bone marrow, thymus, lymph nodes, and spleen, mirrors the process in solid cancers, except that cancer cells in the blood only form CCs but not CCTs. In summary, our study established a cytocapsular cancer evolution atlas, which may pave an avenue for the research on therapy of both solid and liquid cancers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.054
GPT teacher head0.321
Teacher spread0.267 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations0
Published2022
Admission routes1
Has abstractyes

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