Application of iot medical image detection and prenatal genetic testing in obstetric clinic

The use of new techniques and methods can be significantly improved during prenatal examination and screening of fetal genetic abnormalities. Expanding the number of vectors in screening and screening for single-cell gene diseases in fetal DNA will increase the probability of success of the whole screening test.Recently, sub chromosomal abnormalities have been introduced into prenatal care. The lack of suitable tools makes it very difficult to obtain information about collection, management, and prenatal genetic testing. The purpose of this study is to improve the accessibility of nutritional information by using the advantages of advanced medical image detection and integrating the IoT (Internet of Things) and prenatal genetic testing platforms in obstetric outpatient clinics. Records are kept that the platform will allow IoT to interact with sensor practitioners and provide immediate access to medical images prior to delivery. This proposed system provides an IoT application for managing obstetric outpatient information and prenatal genetic testing requirements. The requirement for establishment is the realization of the development of an IoT platform for complete medical image detection information management with IoT input required for integration with existing medical information systems. In response, the purpose of the study is to use integrated IoT applications to help nutrition professionals, researchers, patients, and especially mothers, to enhance their collection of medical imaging and prenatal genetic testing IoT sensor based information transfer.     

Supervised two-step feature extraction for structured representation of text data

Training data matrix used for classification of text documents to multiple categories is characterized by large number of dimensions while the number of manually classified training documents is relatively small. Thus the suitable dimensionality reduction techniques are required to be able to develop the classifier. The article describes two-step supervised feature extraction method that takes advantage of projections of terms into document and category spaces. We propose several enhancements that make the method more efficient and faster than it was presented in our former paper. We also introduce the adjustment score that enables to correct defected targets or helps to identify improper training examples that bias extracted features.     

Identification of peptide-mediated interactions between human PTTG and SH3 domains in pALL gene expression profile

Human pituitary tumor-transforming gene (PTTG) plays an essential role in the development and progression of pediatric acute lymphoblastic leukemia (pALL). PTTG has two SH3-binding peptide motifs that can be recognized by a variety of SH3-containing proteins in the pALL through peptide-mediated interactions. In this study, the gene expression profile of pALL was examined in detail by integrating computational modeling and experimental assay, aiming to identify those potential partner proteins of human PTTG. The binding potency of domain candidates to peptide motifs was ranked using knowledge-based scoring and fluorescence titration. A number of SH3 domains found in a variety of pALL proteins were identified as potent binders with moderate or high affinity for PTTG. It is revealed that the PTTG peptide motifs show different affinity profiles for various candidate proteins, indicating that the PTTG selectivity is optimized across pALL gene expression space. The PTTG peptides were then mutated rationally to target the SH3 domains of identified partner proteins by competing with the native peptide motifs.     

Bioisosteric approach in designing new monastrol derivatives: An investigation on their ADMET prediction using in silico derived parameters

Medicinal chemists are facing an increasing challenge to deliver safer and more effective medicines. An appropriate balance between drug-like properties such as solubility, permeability, metabolic stability, efficacy and toxicity is one of the most challenging problems during lead optimization of a potential drug candidate. Insoluble and impermeable compounds can result in erroneous biological data and unreliable SAR in enzyme and cell-based assays. The weak inhibitory activity and non-drug-like properties of monastrol, the first small mitotic kinesin Eg5 inhibitor, has hampered its further development. In this investigation, a bioisosteric approach was applied that resulted in the replacement of C-5 carbonyl of monastrol with thio-carbonyl. Further lead optimization of drug-like properties was evaluated through in silico predictions by using ADMET predictor software. This minor structural modification resulted in upgraded human effective jejunal permeability (Peff) and improved permeability in Madin–Darby canine kidney (MDCK) cells. Furthermore, C-5 thiocarbonyl analogue of monastrol (named as Special-2) was found safe to administer orally with no phospholipidosis toxicity, no raised levels of serum glutamate oxaloacetate transaminase (SGOT) and no potential towards cardiotoxicity. Molecular docking study was also carried out to understand the binding modes of these compounds. The docking study showed high binding affinity of the designed compounds against KSP. Hence a combination of in silico ADMET studies and molecular docking can help to improve prediction success and these compounds might be act as potential candidate for KSP inhibition.     

Polymers in nanotechnology

The natural length scales of polymer chains and their morphologies in the bulk, which lie in the nanometer domain, make polymers ideal building blocks for nanotechnology. In this review we will discuss a number of recent developments in the use of polymers for the fabrication of nanostructures via lithographic and self-assembling strategies.     

Synthesis of scalable 1T/2H–MoSe2 nanosheets with a new source of Se in basic media and study of their HER activity

In this report MoSe₂ nanosheets were fabricated using new precursors of MoCl₅ and Na₂SeO₃ and a very simple chemical procedure without using inert atmosphere and complex methods for preparing Se ion source. The structural properties of fabricated nanosheets were examined by means of XRD, field emission scanning electron microscopy (FESEM), elemental mapping of energy dispersive x-ray spectroscopy (EDS), transmission electron microscopy (TEM), atomic force microscopy (AFM), Raman spectroscopy and isotherm gas adsorption-desorption technique. The results showed the nanosheets are mixed phase metallic-semiconductor 1T-2H with thicknesses about 3.6–6.1 nm and are stable for several months. The effective surface area is obtained 28 m² g⁻¹ and mean pore size of 6–8 nm for MoSe₂ nanosheets. Electro-impedance spectroscopy showed low resistivity of nanosheets due to presence of metallic phase of MoSe₂. HER activity of nanosheets obtains a Tafel slope of 60 mV.dec⁻¹ and high current density values up to 150 mA cm⁻² and the value of over potential at 10 mA cm⁻² is 155 mV.