Determination of the tensile properties and biodegradability of cornstarch-based biopolymers plasticized with sorbitol and glycerol

In this study, the effects of various quantities of sorbitol and glycerol plasticizers (0%, 30%, 45%, and 60%) on cornstarch-based film were examined to develop a novel polymer for usage with biodegradable materials. The film was prepared using the casting process. According to the test findings, the application of the plasticizer concentrations affected the thickness, moisture content, and water absorption of the film. When plasticizer concentrations were increased to 60%, the tensile stress and Young’s modulus of plasticized films dropped regardless of plasticizer type. However, the thin film with addition of 30% sorbitol plasticizer demonstrated a steady value of Young’s modulus (60.17 MPa) with an increase in tensile strength (13.61 MPa) of 46%, while the lowest combination of tensile strength and Young’s modulus is the film that was plasticized with 60% glycerol, with 2.33 MPa and 16.23 MPa, respectively. In summary, the properties and performance of cornstarch-based film were greatly influenced by plasticizer types and concentrations. The finest set of features in this research appeared in the film plasticized with 30% sorbitol, which achieved the best mechanical properties for food packaging applications

Improving white dwarfs as chronometers with gaia parallaxes and spectroscopic metallicities

White dwarfs (WDs) offer unrealized potential in solving two problems in astrophysics: stellar age accuracy and precision. WD cooling ages can be inferred from surface temperatures and radii, which can be constrained with precision by high-quality photometry and parallaxes. Accurate and precise Gaia parallaxes along with photometric surveys provide information to derive cooling and total ages for vast numbers of WDs. Here we analyze 1372 WDs found in wide binaries with main-sequence (MS) companions and report on the cooling and total age precision attainable in these WD+MS systems. The total age of a WD can be further constrained if its original metallicity is known because the MS lifetime depends on metallicity at fixed mass, yet metallicity is unavailable via spectroscopy of the WD. We show that incorporating spectroscopic metallicity constraints from 38 wide binary MS companions substantially decreases internal uncertainties in WD total ages compared to a uniform constraint. Averaged over the 38 stars in our sample, the total (internal) age uncertainty improves from 21.04% to 16.77% when incorporating the spectroscopic constraint. Higher mass WDs yield better total age precision; for eight WDs with zero-age MS masses ≥2.0 M⊙, the mean uncertainty in total ages improves from 8.61% to 4.54% when incorporating spectroscopic metallicities. We find that it is often possible to achieve 5% total age precision for WDs with progenitor masses above 2.0 M⊙ if parallaxes with ≤1% precision and Pan-STARRS g, r, and i photometry with ≤0.01 mag precision are available

Scaffold Repurposing Reveals New Nanomolar Phosphodiesterase Type 5 (PDE5) Inhibitors Based on Pyridopyrazinone Scaffold: Investigation of In Vitro and In Silico Properties

Inhibition of PDE5 results in elevation of cGMP leading to vascular relaxation and reduction in the systemic blood pressure. Therefore, PDE5 inhibitors are used as antihypertensive and antianginal agents in addition to their major use as male erectile dysfunction treatments. Previously, we developed a novel series of 34 pyridopyrazinone derivatives as anticancer agents (series A–H). Herein, a multi-step in silico approach was preliminary conducted to evaluate the predicted PDE5 inhibitory activity, followed by an in vitro biological evaluation over the enzymatic level and a detailed SAR study. The designed 2D-QSAR model which was carried out to predict the IC50 of the tested compounds revealed series B, D, E and G with nanomolar range of IC50 values (6.00–81.56 nM). A further docking simulation model was performed to investigate the binding modes within the active site of PDE5. Interestingly, most of the tested compounds showed almost the same binding modes of that of reported PDE5 inhibitors. To validate the in silico results, an in vitro enzymatic assay over PDE5 enzyme was performed for a number of the promising candidates with different substitutions. Both series E and G exhibited a potent inhibitory activity (IC50 = 18.13–41.41 nM). Compound 11b (series G, oxadiazole-based derivatives with terminal 4-NO2 substituted phenyl ring and rigid linker) was the most potent analogue with IC50 value of 18.13 nM. Structure–activity relationship (SAR) data attained for various substitutions were rationalized. Furthermore, a molecular dynamic simulation gave insights into the inhibitory activity of the most active compound (11b). Accordingly, this report presents a successful scaffold repurposing approach that reveals compound 11b as a highly potent nanomolar PDE5 inhibitor worthy of further investigation

Formation, vertex deviation, and age of the Milky Way’s bulge: input from a cosmological simulation with a late-forming bar

We present the late-time evolution of m12m, a cosmological simulation of a Milky Way-like galaxy from the FIRE project. The simulation forms a bar after redshift z = 0.2. We show that the evolution of the model exhibits behaviours typical of kinematic fractionation, with a bar weaker in older populations, an X-shape traced by the younger, metal-rich populations and a prominent X-shape in the edge-on mean metallicity map. Because of the late formation of the bar in m12m, stars forming after 10Gyr 10Gyr (z = 0.34) significantly contaminate the bulge, at a level higher than is observed at high latitudes in the Milky Way, implying that its bar cannot have formed as late as in m12m. We also study the model’s vertex deviation of the velocity ellipsoid as a function of stellar metallicity and age in the equivalent of Baade’s Window. The formation of the bar leads to a non-zero vertex deviation. We find that metal-rich stars have a large vertex deviation (∼40°), which becomes negligible for metal-poor stars, a trend also found in the Milky Way, despite not matching in detail. We demonstrate that the vertex deviation also varies with stellar age and is large for stars as old as 9Gyr 9Gyr ⁠, while 13Gyr 13Gyr old stars have negligible vertex deviation. When we exclude stars that have been accreted, the vertex deviation is not significantly changed, demonstrating that the observed variation of vertex deviation with metallicity is not necessarily due to an accreted population

Amorphous formulations of indomethacin and griseofulvin prepared by electrospinning

Following an array of optimization experiments, two series of electrospun polyvinylpyrrolidone (PVP) fibers were prepared. One set of fibers contained various loadings of indomethacin, known to form stable glasses, and the other griseofulvin (a poor glass former). Drug loadings of up to 33% w/w were achieved. Electron microscopy data showed the fibers largely to comprise smooth and uniform cylinders, with evidence for solvent droplets in some samples. In all cases, the drug was found to exist in the amorphous physical state in the fibers on the basis of X-ray diffraction and differential scanning calorimetry (DSC) measurements. Modulated temperature DSC showed that the relationship between a formulation’s glass transition temperature (<i>T</i>_g) and the drug loading follows the Gordon–Taylor equation, but not the Fox equation. The results of Gordon–Taylor analysis indicated that the drug/polymer interactions were stronger with indomethacin. The interactions between drug and polymer were explored in more detail using molecular modeling simulations and again found to be stronger with indomethacin; the presence of significant intermolecular forces was further confirmed using IR spectroscopy. The amorphous form of both drugs was found to be stable after storage of the fibers for 8 months in a desiccator (relative humidity <25%). Finally, the functional performance of the fibers was studied; in all cases, the drug-loaded fibers released their drug cargo very rapidly, offering accelerated dissolution over the pure drug

Feature selection using Haar wavelet power spectrum

BACKGROUND: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. RESULTS: Haar wavelet power spectra of genes were analysed and it was observed to be different in different diagnostic categories. This difference in trend and magnitude of the spectrum may be utilized in gene selection. Most of the genes selected by earlier complex methods were selected by the very simple present method. Each earlier works proved only few genes are quite enough to approach the classification problem [1]. Hence the present method may be tried in conjunction with other classification methods. The technique was applied without removing the noise in data to validate the robustness of the method against the noise or outliers in the data. No special softwares or complex implementation is needed. The qualities of the genes selected by the present method were analysed through their gene expression data. Most of them were observed to be related to solve the classification issue since they were dominant in the diagnostic category of the dataset for which they were selected as features. CONCLUSION: In the present paper, the problem of feature selection of microarray gene expression data was considered. We analyzed the wavelet power spectrum of genes and proposed a clustering and feature selection method useful for classification based on Haar wavelet power spectrum. Application of this technique in this area is novel, simple, and faster than other methods, fit for a wide range of data types. The results are encouraging and throw light into the possibility of using this technique for problem domains like disease classification, gene network identification and personalized drug design