Effects of the preparation technique on the physicochemical characteristics and dissolution improvement of ketoprofen-SBE7-β-CD binary inclusion complexes

Enhanced oral delivery of hesperidin-loaded sulfobutylether-β-cyclodextrin/chitosan nanoparticles for augmenting its hypoglycemic activity: in vitro-in vivo assessment study

Hesperidin (Hsd), a bioactive phytomedicine, experienced an antidiabetic activity versus both Type 1 and Type 2 Diabetes mellitus. However, its intrinsic poor solubility and bioavailability is a key challenging obstacle reflecting its oral delivery. From such perspective, the purpose of the current study was to prepare and evaluate Hsd-loaded sulfobutylether-β-cyclodextrin/chitosan nanoparticles (Hsd/CD/CS NPs) for improving the hypoglycemic activity of the orally administered Hsd. Hsd was first complexed with sulfobutylether-β-cyclodextrin (SBE-β-CD) and the complex (CX) was found to be formed with percent complexation efficiency and percent process efficiency of 50.53 ± 1.46 and 84.52 ± 3.16%, respectively. Also, solid state characterization of the complex ensured the inclusion of Hsd inside the cavity of SBE-β-CD. Then, Hsd/CD/CS NPs were prepared using the ionic gelation technique. The prepared NPs were fully characterized to select the most promising one (F1) with a homogenous particle size of 455.7 ± 9.04 nm, a positive zeta potential of + 32.28 ± 1.12 mV, and an entrapment efficiency of 77.46 ± 0.39%. The optimal formula (F1) was subjected to further investigation of in vitro release, ex vivo intestinal permeation, stability, cytotoxicity, and in vivo hypoglycemic activity. The results of the release and permeation studies of F1 manifested a modulated pattern between Hsd and CX. The preferential stability of F1 was observed at 4 ± 1 °C. Also, the biocompatibility of F1 with oral epithelial cell line (OEC) was retained up to a concentration of 100 µg/mL. After oral administration of F1, a noteworthy synergistic hypoglycemic effect was recorded with decreased blood glucose level until the end of the experiment. In conclusion, Hsd/CD/CS NPs could be regarded as a hopeful oral delivery system of Hsd with enhanced antidiabetic activity.

Governing the aggregation of type I collagen mediated through β-cyclodextrin

The effect of carbohydrates on collagen self-assembly behavior has been widely investigated because of their regulation on collagen fibrogenesis in vivo. In this paper, β-cyclodextrin (β-CD) was selected as an external disturbance to explore its intrinsic regulating mechanism on collagen self-assembly. The results of fibrogenesis kinetics indicated that β-CD had a bilateral regulation on collagen self-aggregation process, which was closely related to the content of β-CD: collagen protofibrils with low β-CD content were less aggregated compared to collagen protofibrils with high β-CD content. However, typical periodic stripes of ~67 nm on collagen fibrils were observed from transmission electron microscope (TEM), indicating that β-CD did not disturb the lateral arrangement of collagen molecules to form a 1/4 staggered structure. Correspondingly, the degree of aggregation of collagen self-assembled fibrils was closely correlated with the addition of β-CD content, as confirmed by field emission scanning electron microscopy (FESEM) and atomic force microscope (AFM). In addition, collagen/β-CD fibrillar hydrogel had good thermal stability and cytocompatibility. These results provide a better understanding of how to construct a structurally reliable collagen/β-CD fibrillar hydrogel as a biomedical material in a β-CD-regulated environment.

Toward a Greener World-Cyclodextrin Derivatization by Mechanochemistry

Cyclodextrin (CD) derivatives are a challenge, mainly due to solubility problems. In many cases, the synthesis of CD derivatives requires high-boiling solvents, whereas the product isolation from the aqueous methods often requires energy-intensive processes. Complex formation faces similar challenges in that it involves interacting materials with conflicting properties. However, many authors also refer to the formation of non-covalent bonds, such as the formation of inclusion complexes or metal–organic networks, as reactions or synthesis, which makes it difficult to classify the technical papers. In many cases, the solubility of both the starting material and the product in the same solvent differs significantly. The sweetest point of mechanochemistry is the reduced demand or complete elimination of solvents from the synthesis. The lack of solvents can make syntheses more economical and greener. The limited molecular movements in solid-state allow the preparation of CD derivatives, which are difficult to produce under solvent reaction conditions. A mechanochemical reaction generally has a higher reagent utilization rate. When the reaction yields a good guest co-product, solvent-free conditions can be slower than in solution conditions. Regioselective syntheses of per-6-amino and alkylthio-CD derivatives or insoluble cyclodextrin polymers and nanosponges are good examples of what a greener technology can offer through solvent-free reaction conditions. In the case of thiolated CD derivatives, the absence of solvents results in significant suppression of the thiol group oxidation, too. The insoluble polymer synthesis is also more efficient when using the same molar ratio of the reagents as the solution reaction. Solid reactants not only reduce the chance of hydrolysis of multifunctional reactants or side reactions, but the spatial proximity of macrocycles also reduces the length of the spacing formed by the crosslinker. The structure of insoluble polymers of the mechanochemical reactions generally is more compact, with fewer and shorter hydrophilic arms than the products of the solution reactions.

Estimation of tumor parameters using neural networks for inverse bioheat problem

BACKGROUND AND OBJECTIVE

Some types of cancer cause rapid cell growth, while others cause cells to grow and divide at a slower rate. Certain forms of cancer result in visible growths called tumors. This work proposes an inverse estimation of the size and location of the tumor using a feedforward Neural Network (FFNN) model.

METHODS

The forward model is a 3D model of the breast induced with a tumor of various sizes at different locations within the breast, and it is solved using the Pennes equation. The data obtained from the simulation of the bioheat transfer is used for training the neural network. In order to optimize the neural network architecture, the work proposes varying the number of neurons in the hidden layer and thus finding the best fit to create a relationship between the temperature profile and tumor parameters which can be used to estimate the tumor parameters given the temperature profile.

RESULTS

These simulations resulted in a temperature distribution profile that could thus be used to locate and determine the parameters of the cancerous tumor within the breast. The prediction accuracy showed the capacity of the trained Feed Forward Neural Network to estimate the unknown parameters within an acceptable range of error. The model validations use the Root Mean Square Error method to quantify and minimize the prediction error.

CONCLUSIONS

In this work, a non-intrusive method for the diagnosis of breast cancer was modelled, which yields conclusive results for the estimation of the tumor parameters.