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Record W4200499140 · doi:10.1038/s41598-021-02990-w

Emergence of uniform linearly-arranged micro-droplets entrapping DNA and living cells through water/water phase-separation

2021· article· en· W4200499140 on OpenAlexfundno aff
Mayu Shono, Ritsuki Ito, Fumika Fujita, Hiroki Sakuta, Kenichi Yoshikawa

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of Science
KeywordsPolyethylene glycolPolymerProtocellAqueous solutionPhase (matter)Capillary actionPEG ratioChemical engineeringDNAPolystyreneMixing (physics)MicrofluidicsBeadMaterials scienceDextranChemistryNanotechnologyChromatographyBiophysicsMembraneOrganic chemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Living cells maintain their lives through self-organization in an environment crowded with a rich variety of biological species. Recently, it was found that micro-droplets containing biomacromolecules, which vary widely in size, are generated accompanied by water/water phase-separation by simple mechanical mixing of an aqueous solution with binary polymers. Here, we report that cell-sized droplets of nearly the same size are generated as a linear array within a glass capillary upon the introduction of a binary polymer solution of polyethylene glycol (PEG) and dextran (DEX). Interestingly, when DNA molecules are added to the polymer solution, stable droplets entrapping DNA molecules are obtained. Similarly, living cells are entrapped spontaneously for the linearly-arranged cell-sized droplets. This simple method for generating micro-droplets entrapping DNA and also living cells is expected to stimulate further study on the self-construction of protocells and micro organoids.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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 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

Citations8
Published2021
Admission routes1
Has abstractyes

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