Thiolated mucoadhesive and PEGylated nonmucoadhesive organosilica nanoparticles from 3-Mercaptopropyltrimethoxysilane

A novel approach has been developed to synthesize thiolated sub-100 nm organosilica nanoparticles from 3-mercaptopropyltrimethoxysilane (MPTS) through its self-condensation in dimethylsulfoxide in contact with atmospheric oxygen. The formation of MPTS nanoparticles proceeds through the condensation of methoxysilane groups and simultaneous disulfide bridging caused by partial oxidation of thiol groups. These nanoparticles showed excellent colloidal stability in dilute aqueous dispersions but underwent further self-assembly into chains and necklaces at higher concentrations. They exhibited very good ability to adhere to ocular mucosal surfaces, which can find applications in drug delivery. The thiolated nanoparticles could also be easily modified through PEGylation resulting in a loss of their mucoadhesive properties

Influence of Formulation Factors on Tablet Formulations with Liquid Permeation Enhancer Using Factorial Design

For a drug with low bioavailability, a matrix tablet with liquid permeation enhancer (Labrasol®) was formulated. Factorial design was used to evaluate the effect of three formulation factors: drug percentage, polymer type (Methocel® K100M or Eudragit® L 100-55), and tablet binder percentage (Plasdone® S-630) on tablet characteristics. Tablets were prepared by direct compression and characterized. Compressibility index values ranged between 15.90% and 29.87% and tablet hardness values from 7.8 to 29.78 Kp. Eudragit®-containing formulations had better compressibility index values with higher tablet hardness. Time for 75% of drug release (T75) was calculated, and formulations containing Eudragit® L 100-55 had faster release rates than tablet formulations with Methocel® K100M. Formulations with Methocel® K100M fit well in the Higuchi model as indicated by their R2 values (>0.98). Among all the formulation factors studied, polymer type displayed the highest and statistically significant effect on compressibility index, tablet hardness, and dissolution rate. Statistical design helped in better understanding the effect of formulation factors on tablet characteristics important for designing formulations with desired characteristics

Love Thy Neighbour: Automatic Animal Behavioural Classification of Acceleration Data Using the K-Nearest Neighbour Algorithm

Researchers hoping to elucidate the behaviour of species that aren’t readily observed are able to do so using biotelemetry methods. Accelerometers in particular are proving particularly effective and have been used on terrestrial, aquatic and volant species with success. In the past, behavioural modes were detected in accelerometer data through manual inspection, but with developments in technology, modern accelerometers now record at frequencies that make this impractical. In light of this, some researchers have suggested the use of various machine learning approaches as a means to classify accelerometer data automatically. We feel uptake of this approach by the scientific community is inhibited for two reasons; 1) Most machine learning algorithms require selection of summary statistics which obscure the decision mechanisms by which classifications are arrived, and 2) they are difficult to implement without appreciable computational skill. We present a method which allows researchers to classify accelerometer data into behavioural classes automatically using a primitive machine learning algorithm, k-nearest neighbour (KNN). Raw acceleration data may be used in KNN without selection of summary statistics, and it is easily implemented using the freeware program R. The method is evaluated by detecting 5 behavioural modes in 8 species, with examples of quadrupedal, bipedal and volant species. Accuracy and Precision were found to be comparable with other, more complex methods. In order to assist in the application of this method, the script required to run KNN analysis in R is provided. We envisage that the KNN method may be coupled with methods for investigating animal position, such as GPS telemetry or dead-reckoning, in order to implement an integrated approach to movement ecology research