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Record W2513710433 · doi:10.2217/nnm-2016-0151

Synthesis and Evaluation of Alendronate-Modified Gelatin Biopolymer as a Novel Osteotropic Nanocarrier for Gene Therapy

2016· article· en· W2513710433 on OpenAlex
George M. Mekhail, Amany O. Kamel, Gehanne A.S. Awad, Nahed D. Mortada, Rowena Rodrigo, Paul A. Spagnuolo, Shawn Wettig

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

VenueNanomedicine · 2016
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGelatinBiopolymerNanocarriersGenetic enhancementChemistryMaterials scienceNanotechnologyGeneBiochemistryPolymerDrug deliveryOrganic chemistry

Abstract

fetched live from OpenAlex

AIM: To synthesize an osteotropic alendronate functionalized gelatin (ALN-gelatin) biopolymer for nanoparticle preparation and targeted delivery of DNA to osteoblasts for gene therapy applications. MATERIALS & METHODS: Alendronate coupling to gelatin was confirmed using Fourier transform IR, (31)PNMR, x-ray diffraction (XRD) and differential scanning calorimetry. ALN-gelatin biopolymers prepared at various alendronate/gelatin ratios were utilized to prepare nanoparticles and were optimized in combination with DNA and gemini surfactant for transfecting both HEK-293 and MG-63 cell lines. RESULTS: Gelatin functionalization was confirmed using the above methods. Uniform nanoparticles were obtained from a nanoprecipitation technique. ALN-gelatin/gemini/DNA complexes exhibited higher transfection efficiency in MG-63 osteosarcoma cell line compared with the positive control. CONCLUSION: ALN-gelatin is a promising biopolymer for bone targeting of either small molecules or gene therapy applications.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.061
GPT teacher head0.348
Teacher spread0.287 · 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