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Record W3048711862 · doi:10.1039/d0md00229a

Peptide-based delivery vectors with pre-defined geometrical locks

2020· article· en· W3048711862 on OpenAlex
Ruchika Goyal, Gaurav Jerath, Aneesh Chandrasekharan, T. R. Santhosh Kumar, Vibin Ramakrishnan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRSC Medicinal Chemistry · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsInstitute of Cancer Research
FundersBoard of Research in Nuclear SciencesIndian Institute of Technology GuwahatiDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsPeptideHeLaFlow cytometryIn vitroChemistryCellCancer cellCell biologyBiochemistryMolecular biologyBiologyCancer

Abstract

fetched live from OpenAlex

on various cell lines, including breast cancer (MDA-MB-231), cervical cancer (HeLa), osteosarcoma (U2-OS) and non-cancer mammary epithelial cells (MCF-10A), by flow cytometry and confocal microscopy. The results showed differential cellular uptake in different cell types, as a result of the distinct electrostatic fingerprint encoded in their design. The uptake of serum pre-treated peptides by cells reveals the retention of peptide activity even after the incubation with serum. In addition, peptide-methotrexate (MTX) conjugates compared to the methotrexate drug showed enhanced apoptotic cell death in MTX-resistant MDA-MB-231 cells, indicating the increase in MTX bioavailability.

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.

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 score0.006
Threshold uncertainty score0.857

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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