Bioactive-Tissue-Derived Nanocomposite Hydrogel for Permanent Arterial Embolization and Enhanced Vascular Healing

Transcatheter embolization is a minimally invasive procedure that uses embolic agents to intentionally block diseased or injured blood vessels for therapeutic purposes. Embolic agents in clinical practice are limited by recanalization, risk of non-target embolization, failure in coagulopathic patients, high cost, and toxicity. Here, a decellularized cardiac extracellular matrix (ECM)-based nanocomposite hydrogel is developed to provide superior mechanical stability, catheter injectability, retrievability, antibacterial properties, and biological activity to prevent recanalization. The embolic efficacy of the shear-thinning ECM-based hydrogel is shown in a porcine survival model of embolization in the iliac artery and the renal artery. The ECM-based hydrogel promotes arterial vessel wall remodeling and a fibroinflammatory response while undergoing significant biodegradation such that only 25% of the embolic material remains at 14 days. With its unprecedented proregenerative, antibacterial properties coupled with favorable mechanical properties, and its superior performance in anticoagulated blood, the ECM-based hydrogel has the potential to be a next-generation biofunctional embolic agent that can successfully treat a wide range of vascular diseases.     

Mapping concentrations of surface water quality parameters using a novel remote sensing and artificial intelligence framework

The deterioration of surface water quality occurs due to the presence of various types of pollutants generated from human, agricultural, and industrial activities. Thus, mapping concentrations of different surface water quality parameters (SWQPs), such as turbidity, total suspended solids (TSS), chemical oxygen demand (COD), biological oxygen demand (BOD), and dissolved oxygen (DO), is indeed critical for providing the appropriate treatment to the affected waterbodies. Traditionally, concentrations of SWQPs have been measured through intensive field work. Additionally, quite a lot of studies have attempted to retrieve concentrations of SWQPs from satellite images using regression-based methods. However, the relationship between SWQPs and satellite data is complex to be modelled accurately by using regression-based methods. Therefore, our study attempts to develop an artificial intelligence modelling method for mapping concentrations of both optical and non-optical SWQPs. In this context, a remote-sensing framework based on the back-propagation neural network (BPNN) is developed for the first time to quantify concentrations of different SWQPs from the Landsat8 satellite imagery. Compared to other methods, such as Support Vector Machine, significant coefficients of determination (R²) between the Landsat8 surface reflectance and concentrations of SWQPs were obtained using the developed Landsat8-based-BPNN models. The resulting R² values were 0.991, 0.933, 0.937, 0.930, and 0.934 for turbidity, TSS, COD, BOD, and DO, respectively. Indeed, these findings indicate that the developed Landsat8-based-BPNN framework is capable of developing highly accurate models for retrieving concentrations of different SWQPs from the Landsat8 imagery.     

Influence of omega fatty acids on skin permeation of a coenzyme Q10 nanoemulsion cream formulation: characterization,in silico and ex vivo determination

Objective: The aim of this study was to develop a coenzyme Q10 nanoemulsion cream, characterize and to determine the influence of omega fatty acids on the delivery of coenzyme Q10 across model skin membrane via ex vivo and in silico techniques.

Methods: Coenzyme Q10 nanoemulsion creams were prepared using natural edible oils such as linseed, evening primrose, and olive oil. Their mechanical features and ability to deliver CoQ10 across rat skin were characterized. Computational docking analysis was performed for in silico evaluation of CoQ10 and omega fatty acid interactions.

Results: Linseed, evening primrose, and olive oils each produced nano-sized emulsion creams (343.93–409.86?nm) and exhibited excellent rheological features. The computerized docking studies showed favorable interactions between CoQ10 and omega fatty acids that could improve skin permeation. The three edible-oil nanoemulsion creams displayed higher ex vivo skin permeation and drug flux compared to the liquid-paraffin control cream. The linseed oil formulation displayed the highest skin permeation (3.97?±?0.91?mg/cm²) and drug flux (0.19?±?0.05?mg/cm²/h).

Conclusion: CoQ10 loaded-linseed oil nanoemulsion cream displayed the highest skin permeation. The highest permeation showed by linseed oil nanoemulsion cream may be due to the presence of omega-3, -6, and -9 fatty acids which might serve as permeation enhancers. This indicated that the edible oil nanoemulsion creams have potential as drug vehicles that enhance CoQ10 delivery across skin.     

Enhancement in Physical Properties of Silver-Doped Fe–Ni Invar Nano-alloy Using Chemical Reduction Method

Journal of Superconductivity and Novel Magnetism - Silver-substituted Fe–Ni nano invar alloy is a new and innovative field of research due to their interesting invar, magnetic and electrical...     

Power Allocation Strategy for Secret Key Generation Method in Wireless Communications

Secret key generation (SKG) is an emerging technology to secure wireless communication from attackers. Therefore, the SKG at the physical layer is an alternate solution over traditional cryptographic methods due to wireless channels’ uncertainty. However, the physical layer secret key generation (PHY-SKG) depends on two fundamental parameters, i.e., coherence time and power allocation. The coherence time for PHY-SKG is not applicable to secure wireless channels. This is because coherence time is for a certain period of time. Thus, legitimate users generate the secret keys (SKs) with a shorter key length in size. Hence, an attacker can quickly get information about the SKs. Consequently, the attacker can easily get valuable information from authentic users. Therefore, we considered the scheme of power allocation to enhance the secret key generation rate (SKGR) between legitimate users. Hence, we propose an alternative method, i.e., a power allocation, to improve the SKGR. Our results show 72% higher SKGR in bits/sec by increasing power transmission. In addition, the power transmission is based on two important parameters, i.e., epsilon and power loss factor, as given in power transmission equations. We found out that a higher value of epsilon impacts power transmission and subsequently impacts the SKGR. The SKGR is approximately 40.7% greater at 250 from 50 mW at epsilon = 1. The value of SKGR is reduced to 18.5% at 250 mW when epsilonis 0.5. Furthermore, the transmission power is also measured against the different power loss factor values, i.e., 3.5, 3, and 2.5, respectively, at epsilon = 0.5. Hence, it is concluded that the value of epsilon and power loss factor impacts power transmission and, consequently, impacts the SKGR.     

Postponement growth and antioxidative response of Brassica nigra on CuO and ZnO nanoparticles exposure under soil conditions

Due to unique physiochemical properties, nanoparticles (NPs) have acquired substantial attention in the field of research. However, threats of ecotoxicity and phytotoxicity have limited their biological applications. In this study in vivo experiments were performed to determine the effect of CuO (12.5, 25 and 50 mg/kg) and ZnO (200, 400 and 600 mg/kg) NPs on growth, and antioxidant activities of Brassica nigra. The results showed that CuO NPs did not affect the seed germination while presence of ZnO NPs in the soil generated an inhibitory effect. Both CuO and ZnO NPs positively influenced the growth of stem and other physiological parameters i.e. stem height increased (23%) at 50 mg/kg CuO while root length decreased (up to 44%) with an increase in the concentration of NPs. Phytochemical screening of apical, middle and basal leaves showed elevated phenolic and flavonoid contents in the range of 15.3–59 μg Gallic Acid Equivalent (GAE)/mg Dry Weight (DW) and 10–35 μg Querceitin Equivalent (QE)/mg DW, respectively, in NPs‐treated plants. Antioxidant activity was higher in CuO NPs‐treated plants as compared to ZnO and control plants. Results conclude that CuO and ZnO NPs at low concentrations can be exploited as nanofertilisers in agriculture fields.Inspec keywords: biochemistry, enzymes, renewable materials, crops, nanoparticles, soil, nanofabrication, zinc compounds, organic compounds, agricultural products, toxicology, nanobiotechnologyOther keywords: antioxidative response, ZnO nanoparticles exposure, soil conditions, unique physiochemical properties, germination, antioxidant activities, brassica nigra plant, antioxidant activity, CuO NP‐treated plants, control plants, ZnO NPs effect, mass 15.3 mug to 59.0 mug, mass 10.0 mug to 35.0 mug, CuO, ZnO     

Essential oil composition of commercial black tea (Camellia sinensis)

The essential oil components of different tea brands were investigated by gas chromatography. The oil yields of dried tea samples were ranged from 0.09% to 0.63%. Twenty-five compounds from Supreme and Lipton Yellow Label tea brands representing 98.0% and 88.0% of the Camellia sinensis oil were identified, respectively. The main ones were β-pinene (51.2%) and α-pinene (30.2%). Nineteen components from Tapal tea brand representing 76.7% of the C. sinensis oil were determined with high contents of muurol-5-en-4-a-ol (10.5%) and muurol-5-en-4-b-ol (31.3%). Fifteen components from Deer and Diana tea brands were identified, accounting for 83.3% and 78.2% of the oil containing α-cadinol and β-pinene. Seventeen components from non-branded teas were determined with high contents of muurol-5-en-4-a-ol and muurol-5-en-4-b-ol. Twenty-one compounds from non-branded Bangladeshi Shezan and Indian teas were also identified. All oils consisted of monoterpenic hydrocarbons, oxygenated monoterpenes and sesquiterpenes.     

Estimation of global solar radiation using artificial neural networks

This paper introduces a neural network technique for the estimation of global solar radiation. There are 41 radiation data collection stations spread all over the kingdom of Saudi Arabia where the radiation data and sunshine duration information are being collected since 1971. The available data from 31 locations is used for training the neural networks and the data from the other 10 locations is used for testing. The testing data was not used in the modeling to give an indication of the performance of the system in unknown locations. Results indicate the viability of this approach for spatial modeling of solar radiation.