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Record W1989952413 · doi:10.1089/cpt.2006.9996

Mammalian Cell Desiccation: Facing The Challenges

2006· article· en· W1989952413 on OpenAlexaff
Tamir Kanias, Jason P. Acker

Bibliographic record

VenueCell Preservation Technology · 2006
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsCanadian Blood ServicesUniversity of Alberta
Fundersnot available
KeywordsDesiccationStem cellDesiccation toleranceRegenerative medicineCell biologyBiotechnologyBiologyPlateletCryopreservationSpermChemistryImmunologyBotanyEmbryo

Abstract

fetched live from OpenAlex

The current techniques for the biopreservation of mammalian cells, such as red blood cells, human platelets, sperm cells, and stem cells, rely on hypothermic storage, which has many disadvantages including high cost of maintenance and limited transportation ability. Preservation of biomaterial in the dry state at room temperature is a novel approach to meeting the growing demand for human mammalian cells in regenerative medicine. Presently, many proteins, bacteria, pharmaceutical drugs, and foods are successfully preserved in the dried state. However, mammalian cells are desiccation sensitive and cannot be stabilized in the dried state without the use of biotechnology. Several techniques have been developed to overcome this challenge including the introduction of sugars into the cells. To date there has been encouraging, but limited, success in the development of techniques for the desiccation and dry storage of human platelets and sperm cells. This review summarizes the current state of the preservation of mammalian cells in the dried state, including the major achievements with red blood cells, platelets, stem cells, and spermatozoa.

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 score0.240
Threshold uncertainty score0.321

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 head0.023
GPT teacher head0.227
Teacher spread0.204 · 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

Citations43
Published2006
Admission routes1
Has abstractyes

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