Dataset Information

Characterization and Cellular Internalization of Spherical Cellulose Nanocrystals (CNC) into Normal and Cancerous Fibroblasts.

ABSTRACT: The aim was to isolate cellulose nanocrystals (CNC) from commercialized oil palm empty fruit bunch cellulose nanofibre (CNF) through sulphuric acid hydrolysis and explore its safeness as a potential nanocarrier. Successful extraction of CNC was confirmed through a field emission scanning electron microscope (FESEM) and attenuated total reflection Fourier transmission infrared (ATR-FTIR) spectrometry analysis. For subsequent cellular uptake study, the spherical CNC was covalently tagged with fluorescein isothiocyanate (FITC), resulting in negative charged FITC-CNC nanospheres with a dispersity (Ð) of 0.371. MTT assay revealed low degree cytotoxicity for both CNC and FITC-CNC against C6 rat glioma and NIH3T3 normal fibroblasts up to 50 µg/mL. FITC conjugation had no contribution to the particle's toxicity. Through confocal laser scanning microscope (CLSM), synthesized FITC-CNC manifested negligible cellular accumulation, indicating a poor non-selective adsorptive endocytosis into studied cells. Overall, an untargeted CNC-based nanosphere with less cytotoxicity that posed poor selectivity against normal and cancerous cells was successfully synthesized. It can be considered safe and suitable to be developed into targeted nanocarrier.

SUBMITTER: Shazali NAH

PROVIDER: S-EPMC6803863 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Characterization and Cellular Internalization of Spherical Cellulose Nanocrystals (CNC) into Normal and Cancerous Fibroblasts.

Shazali Nur Aima Hafiza NAH Zaidi Noorzaileen Eileena NE Ariffin Hidayah H Abdullah Luqman Chuah LC Ghaemi Ferial F Abdullah Jafri Malin JM Takashima Ichiro I Nik Abd Rahman Nik Mohd Afizan NMA

Materials (Basel, Switzerland) 20191004 19

The aim was to isolate cellulose nanocrystals (CNC) from commercialized oil palm empty fruit bunch cellulose nanofibre (CNF) through sulphuric acid hydrolysis and explore its safeness as a potential nanocarrier. Successful extraction of CNC was confirmed through a field emission scanning electron microscope (FESEM) and attenuated total reflection Fourier transmission infrared (ATR-FTIR) spectrometry analysis. For subsequent cellular uptake study, the spherical CNC was covalently tagged with fluo ...[more]

PMID: 31590332

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Project description:Cellulose nanocrystals (CNCs) are renewable, naturally derived polymeric nanomaterials receiving substantial attention for a wide range of potential applications. The recent availability of high quality reference materials will facilitate the development and validation of measurement methods needed to advance the scientific and commercial use of CNCs. In the present study, we demonstrate an optimized method to fractionate CNCs with narrow size dispersion based on asymmetrical-flow field-flow fractionation (AF4) coupled with on-line multi-angle light scattering (MALS), dynamic light scattering (DLS), and differential refractometry (dRI). A stable suspension of CNC (Certified Reference Material CNCD-1, National Research Council-Canada) in deionized water was prepared using a dispersion method provided by NRC and adopted from a protocol originally developed at the National Institute of Standards and Technology. The as-prepared material was initially characterized in batch mode to validate the NRC dispersion method. AF4 was then optimized for channel and cross flow, mobile phase composition, and injection volume, among other parameters. Additionally, suspensions containing (1.25-10) mg mL-1 CNC were injected directly into the dRI detector (off-line), yielding a dn/dc value of 0.148 ± 0.003 mL g-1. dRI was then used as an on-line mass sensitive detector to quantify recovery. Results show that maximum recovery (≈ 99%) was achieved under optimized conditions. The weight-averaged molar mass (Mw) was estimated at roughly 107 Da from a partial Zimm analysis. The optical radius of gyration, Rg, and the hydrodynamic radius, Rh, were measured during elution. The shape factor (Rg/Rh) ranged from 1.5 to 1.9 for the fractionated material, supporting an elongated or rod-like structure. To our knowledge, this is the first time that both the morphology and molar mass of CNCs have been directly measured for the full distribution of species. Finally, we developed and demonstrated a semi-preparatory fractionation method to separate CNCs at the milligram scale for off-line research and analysis.

Project description:BackgroundMulticompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer.PurposeTo optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo.Study typeRetrospective.SubjectsForty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer.Field strength/sequence3T multishell diffusion-weighted sequence.AssessmentMulticompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps.Statistical testsAnalysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models.ResultsThe lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm2 /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P < 0.05). Residuals were lowest in the peripheral zone and highest in tumors. Tumor tissue showed the largest reduction in fitting residual by increasing model order. Tumors had a greater proportion of signal from compartment 1 than normal tissue (P < 0.05). Tumor CNR and SIR were greater on compartment-1 signal maps than conventional DWI (P < 0.05) and increased with model order.Data conclusionThe 4-compartment signal model best described diffusion in the prostate. Compartmental signal contributions revealed by this model may improve assessment of prostate cancer. Level of Evidence 3 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:628-639.

Dataset Information

Characterization and Cellular Internalization of Spherical Cellulose Nanocrystals (CNC) into Normal and Cancerous Fibroblasts.

Publications

Characterization and Cellular Internalization of Spherical Cellulose Nanocrystals (CNC) into Normal and Cancerous Fibroblasts.

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