MétaCan
Menu
Back to cohort
Record W4288448213 · doi:10.1002/bit.28197

Recent developments in cell shipping methods

2022· review· en· W4288448213 on OpenAlexaff
Shabnam Heydarzadeh, Sima Kheradmand Kia, Seti Boroomand, Mehdi Hedayati

Bibliographic record

VenueBiotechnology and Bioengineering · 2022
Typereview
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCryopreservationCryoprotectantCell therapyCell survivalCellApoptosisBiologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

As opposed to remarkable advances in the cell therapy industry, research reveal inexplicable difficulties associated with preserving and post-thawing cell death. Post cryopreservation apoptosis is a common occurrence that has attracted the attention of scientists to use apoptosis inhibitors. Transporting cells without compromising their survival and function is crucial for any experimental cell-based therapy. Preservation of cells allows the safe transportation of cells between distances and improves quality control testing in clinical and research applications. The vitality of transported cells is used to evaluate the efficacy of transportation strategies. For many decades, the conventional global methods of cell transfer were not only expensive but also challenging and had adverse effects. The first determination of some projects is optimizing cell survival after cryopreservation. The new generation of cryopreservation science wishes to find appropriate and alternative methods for cell transportation to ship viable cells at an ambient temperature without dry ice or in media-filled flasks. The diversity of cell therapies demands new cell shipping methodologies and cryoprotectants. In this review, we tried to summarize novel improved cryopreservation methods and alternatives to cryopreservation with safe and viable cell shipping at ambient temperature, including dry preservation, hypothermic preservation, gel-based methods, encapsulation methods, fibrin microbeads, and osmolyte solution compositions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.088
GPT teacher head0.367
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBiotechnology and BioengineeringSame topicReproductive Biology and FertilityFrench-language works237,207