Protein by-products: Composition, extraction, and biomedical applications.

Significant upsurge in animal by-products such as skin, bones, wool, hides, feathers, and fats has become a global challenge and, if not properly disposed of, can spread contamination and viral diseases. Animal by-products are rich in proteins, which can be used as nutritional, pharmacologically functional ingredients, and biomedical materials. Therefore, recycling these abundant and renewable by-products and extracting high value-added components from them is a sustainable approach to reclaim animal by-products while addressing scarce landfill resources. This article appraises the most recent studies conducted in the last five years on animal-derived proteins' separation and biomedical application. The effort encompasses an introduction about the composition, an overview of the extraction and purification methods, and the broad range of biomedical applications of these ensuing proteins.

Biosynthesis of exopolysaccharide from waste molasses using Pantoea sp. BCCS 001 GH: a kinetic and optimization study.

The bacterium Pantoea sp. BCCS 001 GH produces an exopolysaccharide (EPS) named Pantoan through using sugar beet molasses (SBM) as an inexpensive and widely available carbon source. This study aims to investigate the kinetics and optimization of the Pantoan biosynthesis using Pantoea sp. BCCS 001 GH in submerged culture. During kinetics studies, the logistic model and Luedeking-Piret equation are precisely fit with the obtained experimental data. The response surface methodology (RSM)-central composite design (CCD) method is applied to evaluate the effects of four factors (SBM, peptone, Na2HPO4, and Triton X-100) on the concentration of Pantoan in batch culture of Pantoea sp. BCCS 001 GH. The experimental and predicted maximum Pantoan production yields are found 9.9 ± 0.5 and 10.30 g/L, respectively, and the best prediction factor concentrations are achieved at 31.5 g/L SBM, 2.73 g/L peptone, 3 g/L Na2HPO4, and 0.32 g/L Triton X-100 after 48 h of submerged culture fermentation, at 30 °C. The functional groups and major monosaccharides (glucose and galactose) of a purified Pantoan are described and confirmed by 1HNMR and FTIR. The produced Pantoan is also characterized by thermogravimetric analysis and the rheological properties of the biopolymer are investigated. The present work guides the design and optimization of the Pantoea sp. BCCS 001 GH culture media, to be fine-tuned and applied to invaluable EPS, which can be applicable in food and biotechnology applications.

The Effect of Hematocrit and Nanoparticles Diameter on Hemodynamic Parameters and Drug Delivery in Abdominal Aortic Aneurysm with Consideration of Blood Pulsatile Flow.

BACKGROUND AND OBJECTIVE: The present article has simulated to investigate the efficient hemodynamic parameters, the drug persistence, and drug distribution on an abdominal aortic aneurysm. METHODS: Blood as a non-Newtonian fluid enters the artery acting as a real pulse waveform; its behavior is dependent on hematocrit and strain rate. In this simulation of computational fluid dynamic, magnetic nanoparticles of iron oxide which were in advance coated with the drug, are injected into the artery during a cardiac cycle. A two-phase model was applied to investigate the distribution of these carriers. RESULTS: The results are presented for different hematocrits and the nanoparticle diameter. It is observed that hematocrit significantly affects drug persistence, so that lower hematocrit incites more accumulation of the drug in the dilatation part of the artery. The better drug accumulation is noticed, at the higher wall shear stress. Although no considerable impact on the flow pattern and wall shear stress was found with various nanoparticle diameters, the smaller size of the nanoparticles results in a greater amount of drug augmentation in the aneurysm wall output. CONCLUSIONS: At the higher hematocrit levels, the blood resistance to drug delivery increases throughout the artery. Also, the drug accumulates less on the aneurysm wall and stays longer on the aneurysm wall. On the contrary, the drug accumulates more by decreasing hematocrit level and stays shorter on the aneurysm wall. Moreover, the maximum drug concentration is observed at the lowest hematocrit level and nanoparticle diameter; also, the diameter of nanoparticles imposes no significant effect on the vorticity and wall shear stress. It is seen that the increment of the hematocrit level reduces the strength of vorticity and increases the amount of wall shear stress in the dilatation segment of the artery. The shear stress at three points of the dilatation wall is extreme, where the maximum density of nanoparticles occurs.

Bacteria-assisted biogreen synthesis of radical scavenging exopolysaccharide-iron complexes: an oral nano-sized nutritional supplement with high in vivo compatibility.

Microbial exopolysaccharides (EPSs) have recently served as an efficient substrate for the production of biocompatible metal nanoparticles (NPs) given their favorable stabilizing and reducing properties due to the presence of polyanionic functional groups in their structure. In the present work, Pantoea sp. BCCS 001 GH was used to produce EPS-stabilized biogenic Fe NPs as a complex through a novel biosynthesis reaction. Physicochemical characterization of the EPS-Fe complex was performed, indicating high thermal stability, desirable magnetic properties due to the uniform distribution of the Fe NPs with the average size of ∼10 nm and spherical shape within the EPS matrix. In addition, the in vivo toxicity of the EPS-stabilized Fe NPs was evaluated to investigate their potential for the treatment of iron deficiency anemia. Biological blood parameters and organ histology studies confirmed very high safety of the biosynthesized composite, making EPS-Fe a suitable candidate with an economical and environment friendly synthesis method for a wide spectrum of potential fields in medicine.

Recurrent spatio-temporal modeling of check-ins in location-based social networks.

Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users' movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a time-varying multinomial distribution for the location of check-ins of users in the location-based social networks. We learn the model parameters by using an efficient EM algorithm, which distributes over the users, and has a linear time complexity. Experiments on synthetic and real data gathered from Foursquare show that the proposed inference algorithm learns the parameters efficiently and our method models the real data better than other alternatives.