Deep Learning Based Method for Computer Aided Diagnosis of Diabetic Retinopathy

© 2019 IEEE. Diabetic retinopathy (DR) is a retinal disease caused by the high blood sugar levels that may damage and block the blood vessels feeding the retina. In the early stages of DR, the disease is asymptomatic; however, as the disease advances, a possible sudden loss of vision and blindness may occur. Therefore, an early diagnosis and staging of the disease is required to possibly slow down the progression of the disease and improve control of the symptoms. In response to the previous challenge, we introduce a computer aided diagnosis tool based on convolutional neural networks (CNN) to classify fundus images into one of the five stages of DR. The proposed CNN consists of a preprocessing stage, five stage convolutional, rectified linear and pooling layers followed by three fully connected layers. Transfer learning was adopted to minimize overfitting by training the model on a larger dataset of 3.2 million images (i.e. ImageNet) prior to the use of the model on the APTOS 2019 Kaggle DR dataset. The proposed approach has achieved a testing accuracy of 77% and a quadratic weighted kappa score of 78%, offering a promising solution for a successful early diagnose and staging of DR in an automated fashion

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin

Nanoparticles of a pyrazolo-pyridazine derivative as potential EGFR and CDK-2 inhibitors: design, structure determination, anticancer evaluation and in silico studies

The strategic planning of this study is based upon using the nanoformulation method to prepare nanoparticles 4-SLNs and 4-LPHNPs of the previously prepared 4,5-diphenyl-1H-pyrazolo[3,4-c]pyridazin-3-amine (4) after confirming its structure with single crystal X-ray analysis. These nanoparticles exhibited promising cytotoxic activity against HepG-2, HCT-116 and MCF-7 cancer cell lines in comparison with the reference doxorubicin and the original derivative 4. Moreover, their inhibitory assessment against EGFR and CDK-2/cyclin A2 displayed improved and more favorable impact than the parent 4 and the references. Detection of their influence upon cancer biomarkers revealed upregulation of Bax, p53 and caspase-3 levels and downregulation of Bcl-2 levels. The docking simulation demonstrated that the presence of the pyrazolo[3,4-c]pyridazin-3-amine scaffold is amenable to enclosure and binding well within EGFR and CDK-2 receptors through different hydrophilic interactions. The pharmacokinetic and physicochemical properties of target 4 were also assessed with ADME investigation, and the outcome indicated good drug-like characteristics

Alleviative effects of pinostrobin against cadmium-induced renal toxicity in rats by reducing oxidative stress, apoptosis, inflammation, and mitochondrial dysfunction

IntroductionCadmium (Cd) is a highly toxic heavy metal that can be found everywhere in the environment and can have harmful effects on both human and animal health. Pinostrobin (PSB) is a bioactive natural flavonoid isolated from Boesenbergia rotunda with several pharmacological properties, such as antiinflammatory, anticancer, antioxidant, and antiviral. This investigation was intended to assess the therapeutic potential of PSB against Cd-induced kidney damage in rats.MethodsIn total, 48 Sprague Dawley rats were divided into four groups: a control, a Cd (5 mg/kg), a Cd + PSB group (5 mg/kg Cd and 10 mg/kg PSB), and a PSB group (10 mg/kg) that received supplementation for 30 days.ResultsExposure to Cd led to a decrease in the activities of catalase (CAT), glutathione reductase (GSR), superoxide dismutase (SOD), and glutathione peroxidase (GSH-PX), whereas levels of reactive oxygen species (ROS) and malondialdehyde (MDA) increased. Cd exposure also caused a substantial increase in urea, kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and creatinine levels. Moreover, a noticeable decline was noticed in creatinine clearance. Moreover, Cd exposure considerably increased the levels of inflammatory indices, including interleukin-1b (IL-1b), tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), nuclear factor kappa-B (NF-kB), inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2) activity. Cd treatment decreased the expression of the antiapoptotic markers (Bcl-2) while increasing the expression of apoptotic markers (Bax and Caspase-3). Furthermore, Cd treatment substantially reduced the TCA cycle enzyme activity, such as alpha-ketoglutarate dehydrogenase, succinate dehydrogenase, malate dehydrogenase, and isocitrate dehydrogenase. Moreover, mitochondrial electron transport chain enzymes, succinatedehydrogenase, NADH dehydrogenase, cytochrome c-oxidase, and coenzyme Q-cytochrome reductase activities were also decreased following Cd exposure. PSB administration substantially reduced the mitochondrial membrane potential while inducing significant histological damage. However, PSB treatment significantly reduced Cd-mediated renal damage in rats.ConclusionThus, the present investigation discovered that PSB has ameliorative potential against Cd-induced renal dysfunction in rats

The role of generative adversarial networks in bioimage analysis and computational diagnostics.

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks (GANs). For that purpose, several studies were conducted. The first study is on domain translation, where we proposed a digital pathology system that can detect and quantify fibrosis in Hematoxylin and Eosin-stained digital slides. The proposed system features a comprehensive machine learning pipeline that includes conditional GANs based translation model, whole slide image registration algorithm, and color-based fibrosis detection module. In the second study, we propose a novel GANs-based model that reconstructs the 3D appearance of the tissue from the available interleaved tissue slices. The proposed model has a sandwich-shaped generator that utilizes a transfer learning strategy to learn the initial parameters from MRI domain before it starts training on the microscopic histology images. Deploying the proposed systems into the digital pathology workflow can improve the efficiency in terms of the processing time, labor cost and can improve diagnostic accuracy

Discovery of New Schiff Bases Tethered Pyrazole Moiety: Design, Synthesis, Biological Evaluation, and Molecular Docking Study as Dual Targeting DHFR/DNA Gyrase Inhibitors with Immunomodulatory Activity

A series of Bis-pyrazole Schiff bases (6a–d and 7a–d) and mono-pyrazole Schiff bases (8a–d and 9a–d) were designed and synthesized through the reaction of 5-aminopyrazoles 1a–d with aldehydes 2–5 using mild reaction condition with a good yield percentage. The chemical structure of newly formed Schiff bases tethered pyrazole core was confirmed based on spectral and experimental data. All the newly formed pyrazole Schiff bases were evaluated against eight pathogens (Gram-positive, Gram-negative, and fungi). The result exhibited that, most of them have good and broad activities. Among those, only six Schiff bases (6b, 7b, 7c, 8a, 8d, and 9b) displayed MIC values (0.97–62.5 µg/mL) compared to Tetracycline (15.62–62.5 µg/mL) and Amphotericin B (15.62–31.25 µg/mL), MBC values (1.94–87.5 µg/mL) and selectivity to tumor cell than normal cells. Immunomodulatory activities showed that the promising Schiff bases increase the immunomodulator effect of defense cell and the Schiff base 8a is the highest one by (Intra. killing activity = 136.5 ± 0.3%) having a pyrazole moiety as well as amide function (O=C-NH2) and piperidinyl core. Furthermore, the most potent one exhibited broad activity depending on both MIC and MBC values. Moreover, to study the mechanism of these pyrazole Schiff bases, two active Schiff bases 8a and 9b from six derivatives were introduced to study the enzyme assay as dihydrofolate reductase (DHFR) on E. coli organism and DNA gyrase with two different organisms, S. aureus and B. subtilis, to determine the inhibitory activities with lower values in the case of DNA gyrase (8a and 9b) or nearly as DHFR compound 9b, while pyrazole 8a showed excellent inhibitory against all enzyme assay. The molecular docking study against dihydrofolate reductase and DNA gyrase were performed to study the binding between active site in the pocket with the two Schiff bases (8a and 9b) that exhibited good binding affinity with different bond types as H-bonding, aren-aren, and arene-cation interaction as well as study the physicochemical and pharmacokinetic properties of the two active Schiff bases 8a and 9b

Synthesis and in vivo anti-ulcer evaluation of some novel piperidine linked dihydropyrimidinone derivatives

Dihydropyrimidinone derivatives containing piperidine moiety were synthesised in a good yield. All the compounds were confirmed by elemental analysis and spectral data. Anti-ulcer activity of novel dihydropyrimidinone-piperidine hybrids (1–18) was evaluated. Among them, four compounds (3, 8, 11 and 15) were found to be most active in 80% ethanol-induced ulcer experimental animal model. All the potent compounds were further evaluated for anti-ulcer activity by different in vivo anti-ulcer models to study the effect of compounds on anti-secretory and cytoprotective activities. All the active compounds inhibited the formation of gastric ulcers and increased the formation of gastric mucin secretion. Compound 15 was found to be the most potent compound of the series as anti-ulcer agent. Additional experimental studies on lead compound 15 will result in a new class of orally active molecule for anti-ulcer activity

Structural and Spectroscopic Characteristics of NiII and CuII Complexes with Poly (Vinyl Alcohol-Nicotinic Acid) Copolymers for Photocatalytic Degradation of Indigo Carmine Dye

Poly-vinyl-alcohol (PVA) has been cross-linked chemically with nicotinic-acid (NA) in an aqueous medium. The copolymers were complexed with NiII and CuII ions. The complexes and copolymers were analyzed using FT-IR and UV–Visible spectroscopy, XRD and TGA, but copolymers were extra analyzed with nuclear magnetic resonance (1H NMR). FT-IR spectra of copolymer revealed the presence of C=O & C–N groups due to the esterification of PVA-NA. The Cu/NA-PVA formed via bidentate interaction of the pyridinyl and carboxyl of NA. EPR/UV-vis data shows the square-planar geometry for NiII and CuII complexes. The adsorption of IC dye onto CuII/NA-PVA complex was noticeably greater (90%) in 35 min than NiII/NA-PVA. The DFTB3LYP with 6- 311G* quantum chemical calculations were carried out for tested compounds. The DFT was conducted to examine an interaction mode of the target compounds with the reaction system. The QSPR was calculated as: optimization geometries, (FMOs), chemical-reactivities and NLO for the copolymers. The (MEPs) were figured to predict the interaction behavior of the ligand and its complexes