Dextran Hydrogels Incorporated with Bioactive Glass-Ceramic: Nanocomposite Scaffolds for Bone Tissue Engineering

A series of nanocomposite scaffolds comprised of dextran (Dex) and sol–gel derived bioactive glass ceramic nanoparticles (nBGC: 0–16 (wt%)) were fabricated as bioactive scaffolds for bone tissue engineering. Scanning electron microscopy showed Dex/nBGC scaffolds were consisting of a porous 3D microstructure with an average pore size of 240 μm. Energy-dispersive x-ray spectroscopy illustrated nBGC nanoparticles were homogenously distributed within the Dex matrix at low nBGC content (2 wt%), while agglomeration was observed at higher nBGC contents. It was found that the osmotic pressure and nBGC agglomeration at higher nBGC contents leads to increased water uptake, then reduction of the compressive modulus. Bioactivity of Dex/nBGC scaffolds was validated through apatite formation after submersion in the simulated body fluid. Dex/nBGC composite scaffolds were found to show improved human osteoblasts (HOBs) proliferation and alkaline phosphatase (ALP) activity with increasing nBGC content up to 16 (wt%) over two weeks. Owing to favorable physicochemical and bioactivity properties, the Dex/nBGC composite hydrogels can be offered as promising bioactive scaffolds for bone tissue engineering applications

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

A Rare Missense Mutation and a Polymorphism with High Frequency in LDLR Gene among Iranian Patients with Familial Hypercholesterolemia

Background: Familial hypercholesterolemia (FH) is a disorder that is inherited by autosomal dominant pattern. The main cause of FH disease is the occurrence of mutations in low-density lipoprotein receptor (LDLR) gene sequence, as well as apolipoprotein B and proprotein convertase subtilisin/kexin type 9 genes, located in the next ranks, respectively. Materials and Methods: Forty-five unrelated Iranian patients with FH were screened using a high-resolution melting (HRM) method for exon 9 along with intron/exon boundaries of LDLR gene. Samples with shift in resultant HRM curves were compared to normal ones, sequenced, and analyzed. Results: Our findings revealed a missense mutation c. 1246C>T and a known variant IVS9-30C>T (rs1003723) that was recognized in 71% of the patients (22%: homozygous and 49%: heterozygous genotypes). In silico analysis, predicted the pathological effect of the c. 1246C>T mutation in LDLR protein structure, but IVS9-30C>T variant had no predicted effect on splice site and branch point function. Conclusion: FH is a hereditary type of hypercholesterolemia that leads to premature cardiovascular disease and atherosclerosis, and early diagnosis is needed. We detected a rare missense mutation (1246C>T) and a common single nucleotide polymorphism (SNP) in the Iranian population. These reports could help in the genetic diagnosis and counseling of FH patients