Accurate detection of brain tumor using optimized feature selection based on deep learning techniques.

An unusual increase of nerves inside the brain, which disturbs the actual working of the brain, is called a brain tumor. It has led to the death of lots of lives. To save people from this disease timely detection and the right cure is the need of time. Finding of tumor-affected cells in the human brain is a cumbersome and time- consuming task. However, the accuracy and time required to detect brain tumors is a big challenge in the arena of image processing. This research paper proposes a novel, accurate and optimized system to detect brain tumors. The system follows the activities like, preprocessing, segmentation, feature extraction, optimization and detection. For preprocessing system uses a compound filter, which is a composition of Gaussian, mean and median filters. Threshold and histogram techniques are applied for image segmentation. Grey level co-occurrence matrix (GLCM) is used for feature extraction. The optimized convolution neural network (CNN) technique is applied here that uses whale optimization and grey wolf optimization for best feature selection. Detection of brain tumors is achieved through CNN classifier. This system compares its performance with another modern technique of optimization by using accuracy, precision and recall parameters and claims the supremacy of this work. This system is implemented in the Python programming language. The brain tumor detection accuracy of this optimized system has been measured at 98.9%.

Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function.

Recent studies have shown that computed tomography (CT) scan images can characterize COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for diagnosis in the literature, including convolutional neural networks (CNN). But, with inefficient patient classification models, the number of 'False Negatives' can put lives at risk. The primary objective is to improve the model so that it does not reveal 'Covid' as 'Non-Covid'. This study uses Dense-CNN to categorize patients efficiently. A novel loss function based on cross-entropy has also been used to improve the CNN algorithm's convergence. The proposed model is built and tested on a recently published large dataset. Extensive study and comparison with well-known models reveal the effectiveness of the proposed method over known methods. The proposed model achieved a prediction accuracy of 93.78%, while false-negative is only 6.5%. This approach's significant advantage is accelerating the diagnosis and treatment of COVID-19.

Ubiquitous and smart healthcare monitoring frameworks based on machine learning: A comprehensive review.

During the COVID-19 pandemic, the patient care delivery paradigm rapidly shifted to remote technological solutions. Rising rates of life expectancy of older people, and deaths due to chronic diseases (CDs) such as cancer, diabetes and respiratory disease pose many challenges to healthcare. While the feasibility of Remote Patient Monitoring (RPM) with a Smart Healthcare Monitoring (SHM) framework was somewhat questionable before the COVID-19 pandemic, it is now a proven commodity and is on its way to becoming ubiquitous. More health organizations are adopting RPM to enable CD management in the absence of individual monitoring. The current studies on SHM have reviewed the applications of IoT and/or Machine Learning (ML) in the domain, their architecture, security, privacy and other network related issues. However, no study has analyzed the AI and ubiquitous computing advances in SHM frameworks. The objective of this research is to identify and map key technical concepts in the SHM framework. In this context an interesting and meaningful classification of the research articles surveyed for this work is presented. The comprehensive and systematic review is based on the "Preferred Reporting Items for Systematic Review and Meta-Analysis" (PRISMA) approach. A total of 2540 papers were screened from leading research archives from 2016 to March 2021, and finally, 50 articles were selected for review. The major advantages, developments, distinctive architectural structure, components, technical challenges and possibilities in SHM are briefly discussed. A review of various recent cloud and fog computing based architectures, major ML implementation challenges, prospects and future trends is also presented. The survey primarily encourages the data driven predictive analytics aspects of healthcare and the development of ML models for health empowerment.

Development of potent and selective Cathepsin C inhibitors free of aortic binding liability by application of a conformational restriction strategy.

Cathepsin C plays a key role in the activation of several degradative enzymes linked to tissue destruction in chronic inflammatory and autoimmune diseases. Therefore, Cathepsin C inhibitors could potentially be effective therapeutics for the treatment of diseases such as chronic obstructive pulmonary disease (COPD) or acute respiratory distress syndrome (ARDS). In our efforts towards the development of a novel series of Cathepsin C inhibitors, we started working around AZD5248 (1), an α-amino acid based scaffold having potential liability of aortic binding. A novel series of amidoacetonitrile based Cathepsin C inhibitors were developed by the application of a conformational restriction strategy on 1. In particular, this work led to the development of a potent and selective Cathepsin C inhibitor 3p, free of aortic binding liability.

Effect of dietary mannanoligosaccharide supplementation on nutrient digestibility, hindgut fermentation, immune response and antioxidant indices in dogs.

BACKGROUND: Use of prebiotics in companion animal nutrition is often considered advantageous over probiotics because of the ease of handling, ability to withstand processing and storage etc. While most of the studies on prebiotic use in dogs have been done with processed food as basal diet, the response in relation to homemade diet feeding is not very well explored. METHODS: The study was conducted to evaluate the effects of dietary mannanoligosaccharide (MOS) supplementation on nutrient digestibility, hindgut fermentation, immune response and antioxidant indices in dogs. Ten Spitz pups were divided into two groups: control (CON) with no supplementation, and experimental (MOS) wherein the basal diet was supplemented with MOS at 15 g/kg diet. All dogs were fed on a home-prepared diet for a period of 150 days. The study protocol included a digestion trial, periodic blood collection and analysis for lipid profile and erythrocytic antioxidants. Immune response of the animals was assessed towards the end of the feeding period. RESULTS: Results revealed no significant (P > 0.05) variations in palatability score, intake and apparent digestibility of nutrients between the groups. Faecal score, faeces voided, faecal pH, concentrations of ammonia, lactate and short-chain fatty acids were comparable (P > 0.05) between the two groups. Cell-mediated immune response, assessed as delayed-type of hypersensitivity response, was significantly higher (P < 0.05) in the MOS group. The percent of lymphocyte sub-populations CD4+ and ratio of CD4+:CD8+ were also significantly (P < 0.05) higher in MOS group. The serum IgG levels were similar (P > 0.05) in both the groups. Supplementation of MOS lowered (P < 0.05) serum total- and LDL- cholesterol levels, when compared with the control group. The erythrocytic antioxidant indices were similar (P > 0.05) between the two groups. CONCLUSIONS: The results indicated that supplementation of MOS at the rate of 15 g/kg in the diet of dog augmented the cell-mediated immune response and serum lipid profile without any influences on digestibility of nutrients, hindgut fermentation and antioxidants indices.

10 years after implementation of TRIPS obligations in India.

The Patent (Amendment) Act of 2005 enforced after TRIPS raises many issues which hinder growth of Indian pharma companies. To tackle this, Indian pharma companies doubled their R&D expenditure and became significant players in global generic drug market. Indian pharmaceutical companies, which predominantly focused on import-oriented market, shifted to research-based approach by signing various agreements with MNCs that led to M&A and technology transfer. At the same time growth in R&D activities increased ANDA and DMF filing in the USA and Europe. Companies also kept their social responsibility by selling medicines at affordable price to patients. This paper highlights the changing business scenario of Indian pharmaceutical companies to counteract various issues evolved from new patent regime after TRIPS.

Bioactive thermoresponsive polyblend nanofiber formulations for wound healing.

The rationale of this work is to develop new bioactive thermoresponsive polyblend nanofiber formulations for wound healing (topical). Various polymer compositions of thermoresponsive, poly(N-isopropylacrylamide), egg albumen and poly(ε-caprolactone) blend solutions with and without a drug [gatifloxacin hydrochloride, Gati] were prepared. Non-woven nanofibers of various compositions were fabricated using an electrospinning technique. The morphology of the nanofibers was analyzed by an environmental scanning electron microscope. The morphology was influenced by the concentration of polymer, drug, and polymer blend composition. Fourier transform infrared spectroscopy analysis showed the shift in bands due to hydrogen ion interactions between polymers and drug. Thermogram of PNIPAM/PCL/EA with Gati recorded a shift in lower critical solution temperature (LCST) and glass transition temperature (Tg) of PNIPAM. Similarly Tg and melting temperature (Tm) of PCL were shifted. X-ray diffraction patterns recorded a decrease in the crystalline state of PCL nanofibers and transformed crystalline drug to an amorphous state. In vitro release study of nanofibers with Gati showed initial rapid release up to 10h, followed by slow and controlled release for 696h (29days). Nanofiber mats with Gati exhibited antibacterial properties to Staphylococcus aureus, supported suitable controlled drug release with in vitro cell viability and in vivo wound healing.

Development of 2-aryl substituted quinazolin-4(3H)-one, pyrido[4,3-d]pyrimidin-4(3H)-one and pyrido[2,3-d]pyrimidin-4(3H)-one derivatives as microsomal prostaglandin E(2) synthase-1 inhibitors.

mPGES-1 is inducible terminal synthase acting downstream of COX enzymes in arachidonic acid pathway, regulates the biosynthesis of pro-inflammatory prostaglandin PGE2. Cardiovascular side effect of coxibs and NSAIDs, selective for COX-2 inhibition, stimulated interest in mPGES-1, a therapeutic target with potential to deliver safe and effective anti-inflammatory drugs. The synthesis and structure activity relationship of a series of compounds from 2-aryl substituted quinazolin-4(3H)-one, pyrido[4,3-d]pyrimidin-4(3H)-one and pyrido[2,3-d]pyrimidin-4(3H)-one scaffolds as mPGES-1 inhibitor are discussed. A set of analogs (28, 48, 49) were identified with <10nM potencies in the recombinant human mPGES-1 enzyme and in the A549 cellular assays. These analogs were also found to be potent in the human whole blood assay (<400 nM). Furthermore, the representative compound 48 was shown to be selective with other prostanoid synthases and was able to effectively regulate PGE2 biosynthesis in clinically relevant inflammatory settings, in comparison with celecoxib.

Imidazopyridazinones as novel PDE7 inhibitors: SAR and in vivo studies in Parkinson's disease model.

The synthesis and structure-activity relationship studies of a series of compounds from imidazopyridazinone scaffold as PDE7 inhibitors are disclosed. Potent analogs such as compounds 7 (31nM), 8 (27nM), and 9 (12nM) were identified. The PDE selectivity and pharmacokinetic profile of compounds 7, 8 and 9 are also disclosed. The adequate CNS penetration of compound 7 in mice allowed it to be tested in the MPTP induced PD model and haloperidol induced catalepsy model to probe the differential pharmacology of PDE7 in the striatal pathway.