DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

Alzheimer’s Disease (AD) is a neurological brain disorder that causes dementia and neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a kind of Artificial Intelligence (AI), has paved the way for new AD detection and automation methods. The DL model’s prediction accuracy depends on the dataset’s size. The DL models lose their accuracy when the dataset has an imbalanced class problem. This study aims to use the deep Convolutional Neural Network (CNN) to develop a reliable and efficient method for identifying Alzheimer’s disease using MRI. In this study, we offer a new CNN architecture for diagnosing Alzheimer’s disease with a modest number of parameters, making it perfect for training a smaller dataset. This proposed model correctly separates the early stages of Alzheimer’s disease and displays class activation patterns on the brain as a heat map. The proposed Detection of Alzheimer’s Disease Network (DAD-Net) is developed from scratch to correctly classify the phases of Alzheimer’s disease while reducing parameters and computation costs. The Kaggle MRI image dataset has a severe problem with class imbalance. Therefore, we used a synthetic oversampling technique to distribute the image throughout the classes and avoid the problem. Precision, recall, F1-score, Area Under the Curve (AUC), and loss are all used to compare the proposed DAD-Net against DEMENET and CNN Model. For accuracy, AUC, F1-score, precision, and recall, the DAD-Net achieved the following values for evaluation metrics: 99.22%, 99.91%, 99.19%, 99.30%, and 99.14%, respectively. The presented DAD-Net outperforms other state-of-the-art models in all evaluation metrics, according to the simulation results.     

Sheath-assisted focusing of microparticles on lab-on-a-chip platforms

Lab-on-a-chip (LOC) technologies can take advantage of sheath flows for particle/cell focusing before sensing or sorting. The integration of focusing with other microscale manipulation techniques (e.g., sorting) creates a trade-off between the throughput of the device and its performance. Therefore, exploring the effective parameters for cells/particles focusing enables us to improve the desired output of LOC devices. A common configuration for sheath-assisted focusing is Y junctions, which are parametrically studied in this paper. First, a computational model was developed and validated by comparing it with our experimental results. Using COMSOL Multiphysics modeling, the effects of multiple parameters were studied. These parameters include the sheath flow ratio (sheath flow over total flow), width ratio (width of the sheath inlet over the total width), junction angles, and particle size on the focusing width and the distribution of the particles within the focusing region. Then, the numerical data were used to develop two generalized linear models to predict the focusing width of the particles and the standard deviation of the position of the particles. The results showed that the focusing width is greatly impacted by the sheath flow rate ratio. Further, the standard deviation of the position of the particles, which represents the concentration of the particles, is mostly dependent on the flow rate ratio, width ratio, and particle size. Our results provide a better understanding of how the device geometrical and operational factors affect the position of the particles in the development of high-performance on-chip sensing and sorting of both cells and particles.     

Prospect of Anterior Gradient 2 homodimer inhibition via repurposing FDA-approved drugs using structure-based virtual screening

Anterior Gradient 2 (AGR2) has recently been reported as a tumor biomarker in various cancers, i.e., breast, prostate and lung cancer. Predominantly, AGR2 exists as a homodimer via a dimerization domain (E60-K64); after it is self-dimerized, it helps FGF2 and VEGF to homo-dimerize and promotes the angiogenesis and the invasion of vascular endothelial cells and fibroblasts. Up till now, no small molecule has been discovered to inhibit the AGR2–AGR2 homodimer. Therefore, the present study was performed to prepare a validated 3D structure of AGR2 by homology modeling and discover a small molecule by screening the FDA-approved drugs library on AGR2 homodimer as a target protein. Thirteen different homology models of AGR2 were generated based on different templates which were narrowed down to 5 quality models sorted by their overall Z-scores. The top homology model based on PDB ID?=?3PH9 was selected having the best Z-score and was further assessed by Verify-3D, ERRAT and RAMPAGE analysis. Structure-based virtual screening narrowed down the large library of FDA-approved drugs to ten potential AGR2–AGR2 homodimer inhibitors having FRED score lower than ? 7.8 kcal/mol in which the top 5 drugs’ binding stability was counter-validated by molecular dynamic simulation. To sum up, the present study prepared a validated 3D structure of AGR2 and, for the first time reported the discovery of 5 FDA-approved drugs to inhibit AGR2–AGR2 homodimer by using structure-based virtual screening. Moreover, the binding of the top 5 hits with AGR2 was also validated by molecular dynamic simulation.

Graphic abstract

A validated 3D structure of Anterior Gradient 2 (AGR2) was prepared by homology modeling, which was used in virtual screening of FDA-approved drugs library for the discovery of prospective inhibitors of AGR2–AGR2 homodimer.

     

Measurement of photon statistics via electromagnetically induced transparency

We propose a method to measure the photon statistics of a quantized radiation field in an electromagnetically induced transparency setup. The proposed method provides a direct way of measuring the photon statistics. This method is insensitive to the detector efficiency.     

Preparation,characterization, and binding profile of imprinted semi-IPN cryogel composite for aluminum

Human body is greatly exposed to aluminum due to its high abundance in the environment. This nonessential metal is a threat to the patients of chronic renal disorders, as it is easily retained in their plasma and quickly accumulates in different tissues. Thus, there is great need to remove it from the aqueous environment. In this study, Al³⁺ imprinted semiinterpenetrating polymer network (semi-IPN)-based cryogel composite was prepared and applied for the purification of environmental and drinking water samples from aluminum. Poly (2-hydroxyethyl methacrylate) (pHEMA) discs were produced via cryogenic treatment and imprinted semi-IPN was introduced to the 3-(trimethoxysilyl) propyl acrylatemodified macroporous cryogel discs. The adsorption properties and selectivity of the aluminum (III) imprinted semi-IPN cryogel composite were studied in detail. The imprinted semi-IPN cryogel composite showed good selectivity towards aluminum (III) ions with the imprinting factor (IF) of 76.4 in the presence of competing copper (II), nickle (II), and iron (III) ions. The maximum adsorption capacity of 271 μmol g^-1 was obtained for aluminum (III) at pH 7.0 within 10 min using imprinted semi-IPN cryogel composite. The good selectivity and reusability of aluminum (III)-imprinted semi-IPN cryogel composite makes this material an eligible candidate for the purification of drinking water from aluminum (III) leaving important minerals remained in the water.     

Pyridine-thiourea based high performance polymers: Synthesis and characterization

A novel diamine monomer, pyridine-2, 6-bis((4-aminophenyl)thioureido)carbonyl(PATC) was synthesized efficiently and polymerized with various aromatic dianhydrides. Consequently, poly(pyridine thiourea-imide)s(PPTIs) with good thermal properties and flame retardancy were fabricated. The structures of PATC and PPTIs were characterized by FTIR, 1H-NMR, 13C-NMR spectroscopy along with elemental analysis, crystallinity, organosolubility, inherent viscosity and gel permeation chromatographic measurements. PPTIs containing C=S, CONH and meta substituted pyridine moieties in the polymer backbone showed amorphous nature and were readily soluble in highly polar organic solvents and even in less polar solvents such as tetrahydrofuran(THF). Polymers had inherent viscosities in the range of 0.91-1.16 d L/g and molecular weight was found between 68000-77000 g/mol. The electrical properties of the PPTIs were estimated in terms of dielectric constant over a range of frequencies. Their thermal stability was determined by 10% weight loss temperature found in the range of 519-563 °C under inert atmosphere. The glass transition temperature of the polyimides varied between 247 °C and 267 °C. The flame retardant properties of PPTIs were investigated in terms of limiting oxygen index(LOI) which was found in the range of 38.26-39.95. Introduction of thiourea in the polymer backbone is an effective way to improve the thermal stability and flame retardancy. Thus PATC can be considered as an excellent candidate for the synthesis of high performance polymers.     

Rational design of a BiFeWO6 nanostructure for supercapacitor applications

Journal of Solid State Electrochemistry - Scientists are increasingly interested in improving electroactive technologies for supercapacitor applications, since energy storage devices have improved...     

A subdivision collocation method for solving two point boundary value problems of order three

In this paper, we propose a method for the numerical solution of self adjoint singularly perturbed third order boundary value problems in which the highest order derivative is multiplied by a small parameter $\varepsilon$. In this method, first we introduce the derivatives of two scale relations satisfied by the subdivision schemes. After that we use these derivatives to construct the subdivision collocation method for the numerical solution of singularly perturbed boundary value problems. Convergence of the subdivision collocation method is also discussed. Numerical examples are presented to illustrate the proposed method.     

Revisiting diterpene lactones of Suregada multiflora

Phytochemical investigations on the organic extracts of the leaves of Suregada multiflora have led to the isolation of ten tetracyclic diterpene lactones 1-10, members of a rare class of abiatene diterpene lactones. Compounds 1-5 were found to be new. The structures of gelomulides F (11), D (12) and E (13) were revised on the basis of 2D NMR and X-ray diffraction evidences. Compounds 1 and 2 contain an epoxy linkage between C-8 and C-14, whereas compounds 3-5 were identified as 8,14-dihydroxy analogues of diterpene lactones. The stereochemical assignments in new compound 1 are based on X-ray diffraction analysis. Compounds 6 and 7 were identified as the known gelomulides A, G. The structures of compounds 7-9 were unambiguously confirmed by X-ray diffraction analyses.