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Record W2374867100

The inhibitive effects of high intensity ultrasound on the second inoculation of the same tumor cells strain in mice with U14 cervical cancer

2006· article· en· W2374867100 on OpenAlexaff
Fanbin Kong

Bibliographic record

VenueZhonghua wuli yixue zazhi · 2006
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsInoculationGroup BCervical cancerGroup AStrain (injury)CancerMedicineInternal medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate the inhibitive effects of high intensity ultrasound (HIU) on the second inoculation of the same strain tumor cells in mice with U14 cervical cancer. Methods Seventy-two mice with U14 cervical cancer were divided into three groups: a group (group A, n=24), an operation group (group B, n=24) and a sham-HIU group (group C, n=24), and treated with (50 Watt/cm~2), operation and (0 Watt/cm~2) 7 d after inoculation, respectively. The mice in each group were divided into three sub-groups(n=8) and re-inoculated with 2×10~6, 2×10~7 or 0 U14 cancer cells at 17 d after first inoculation, and then the rate of survival mice without tumor (RSWT) in every group was recorded at 150 d after second inoculation. Results RSWTs in group A, group B and group C were 100.0%,75.0% and 0.0% after re-inoculation of 2×10~6 U14 cancer cell, 87.5% ,25.0% and 0.0% after re-inoculation of 2×10~7 cells, and 100%,100%and 0% without re-inoculation, respectively. Conclusion It was effective for to treat cervical cancer in mice, furthermore the effects of HIU, playing a role as HIU solidified tumor vaccine, on the second inoculation in mice with U14 cervical cancer might be more valuable than those of operation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.367
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.176
Teacher spread0.173 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2006
Admission routes1
Has abstractyes

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