MétaCan
Menu
Back to cohort
Record W2270848170 · doi:10.1080/10826068.2015.1085400

Catalase purification from rat liver with iron-chelated poly(hydroxyethyl methacrylate-<i>N</i>-methacryloyl-(<scp>l</scp>)-glutamic acid) cryogel discs

2015· article· en· W2270848170 on OpenAlexfundno aff
Ilgım Göktürk, Işık Perçin, Adi̇l Deni̇zli̇

Bibliographic record

VenuePreparative Biochemistry & Biotechnology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsnot available
FundersHacettepe ÜniversitesiUniversity of Lethbridge
KeywordsCatalaseNuclear chemistrySwellingMethacrylateAdsorptionChemistryFourier transform infrared spectroscopyChelationSwelling capacityMaterials sciencePolymer chemistryCopolymerPolymerBiochemistryEnzymeChemical engineeringInorganic chemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

In this study, iron-chelated poly(hydroxyethyl methacrylate-N-methacryloyl-(l)-glutamic acid) (PHEMAGA/Fe(3+)) cryogel discs were prepared. The PHEMAGA/Fe(3+) cryogel discs were characterized by elemental analysis, scanning electron microscopy, Fourier transform infrared spectroscopy, swelling tests, and surface area measurements. The PHEMAGA/Fe(3+) cryogel discs had large pores ranging from 10 to 100 µm with a swelling degree of 9.36 g H2O/g cryogel. Effects of pH, temperature, initial catalase concentration, and flow rate on adsorption capacity of the PHEMAGA/Fe(3+) cryogel discs were investigated. Maximum catalase adsorption capacity (62.6 mg/g) was obtained at pH 7.0, 25°C, and 3 mg/ml initial catalase concentration. The PHEMAGA/Fe(3+) cryogel discs were also tested for the purification of catalase from rat liver. After tissue homogenization, purification of catalase was performed using the PHEMAGA/Fe(3+) cryogel discs and catalase was obtained with a yield of 54.34 and 16.67 purification fold.

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), Insufficient payload (model declined to judge)
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 score0.007
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 studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePreparative Biochemistry & BiotechnologySame topicNanoparticle-Based Drug DeliveryFrench-language works237,207