Cancer remains a second leading cause of deaths and major public health problem. It occurs due to extensive DNA damage caused by ultraviolet radiations, ionizing radiations, environmental agents, ...therapeutic agents, etc. Among all cancers, the most frequently diagnosed cancers are lung (12.7%), breast (10.9%), colorectal (9.7%), and gastric cancer (7.81%). Natural compounds are most favorable against cancer on the count of their anti-cancerous ability, easy to avail and efficient. Among natural compounds, polyphenols (flavonoids, catechin, hesperetin, flavones, quercetin, phenolic acids, ellagic acid, lignans, stilbenes, etc.) represent a large and diverse group used in the prevention and treatment of cancer. Natural flavonoids are derived from different plant sources and from various medicinal plants including Petroselinum crispum, Apium graveolens, Flemingia vestita, Phyllanthus emblica, etc. Natural flavonoids possess antioxidant, anti-inflammation, as well as anti-cancerous activities through multiple pathways, they induce apoptosis in breast, colorectal, and prostate cancers, lower the nucleoside diphosphate kinase-B activity in lung, bladder and colon cancers, inhibit cell-proliferation and cell cycle arrest by suppressing the NF-kB pathway in various cancers, etc. The current review summarized the anticancer activities of natural polyphenols and their mechanisms of action.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK, VSZLJ
For effective monitoring and control of the fermentation process, an accurate real-time measurement of important variables is necessary. These variables are very hard to measure in real-time due to ...constraints such as the time-varying, nonlinearity, strong coupling, and complex mechanism of the fermentation process. Constructing soft sensors with outstanding performance and robustness has become a core issue in industrial procedures. In this paper, a comprehensive review of existing data pre-processing approaches, variable selection methods, data-driven (black-box) soft-sensing modeling methods and optimization techniques was carried out. The data-driven methods used for the soft-sensing modeling such as support vector machine, multiple least square support vector machine, neural network, deep learning, fuzzy logic, probabilistic latent variable models are reviewed in detail. The optimization techniques used for the estimation of model parameters such as particle swarm optimization algorithm, ant colony optimization, artificial bee colony, cuckoo search algorithm, and genetic algorithm, are also discussed. A comprehensive analysis of various soft-sensing models is presented in tabular form which highlights the important methods used in the field of fermentation. More than 70 research publications on soft-sensing modeling methods for the estimation of variables have been examined and listed for quick reference. This review paper may be regarded as a useful source as a reference point for researchers to explore the opportunities for further enhancement in the field of soft-sensing modeling.
Microcalcification clusters in mammograms are one of the major signs of breast cancer. However, the detection of microcalcifications from mammograms is a challenging task for radiologists due to ...their tiny size and scattered location inside a denser breast composition. Automatic CAD systems need to predict breast cancer at the early stages to support clinical work. The intercluster gap, noise between individual MCs, and individual object’s location can affect the classification performance, which may reduce the true-positive rate. In this study, we propose a computer-vision-based FC-DSCNN CAD system for the detection of microcalcification clusters from mammograms and classification into malignant and benign classes. The computer vision method automatically controls the noise and background color contrast and directly detects the MC object from mammograms, which increases the classification performance of the neural network. The breast cancer classification framework has four steps: image preprocessing and augmentation, RGB to grayscale channel transformation, microcalcification region segmentation, and MC ROI classification using FC-DSCNN to predict malignant and benign cases. The proposed method was evaluated on 3568 DDSM and 2885 PINUM mammogram images with automatic feature extraction, obtaining a score of 0.97 with a 2.35 and 0.99 true-positive ratio with 2.45 false positives per image, respectively. Experimental results demonstrated that the performance of the proposed method remains higher than the traditional and previous approaches.
Objective characterization of affective states during music clip watching could lead to disruptive new technologies, such as affective brain–computer interfaces, neuromarketing tools, and affective ...video tagging systems, to name a few. To date, the majority of existing systems have been developed based on analyzing electroencephalography (EEG) patterns in specific brain regions. With music videos, however, a complex interplay of information transfer exists between various brain regions. In this paper, we propose the use of EEG graph-theoretic analysis to characterize three emotional ratings: valence, arousal, and dominance, as well as the “liking” subjective rating. For characterization, graph-theoretic features were used to classify emotional states through support vector machine (SVM) and relevance vector machine (RVM) classifiers. Moreover, fusion schemes at feature and decision levels were also used to improve classification performance. In general, our study shows that the EEG graph-theoretic features are better suited for emotion classification than traditionally used EEG features such as, spectral power features (SPF) and asymmetry index (AI) features. The percentage increase in classification performance, represented by F1-scores, obtained using the proposed methodologies relative to the traditionally used SPF and AI features ranged from: Valence (7–9%), Arousal (3–8%), Dominance (5–6%) and Liking (4–7%). These findings suggest that an EEG graph-theoretical approach along with a robust classifier can better characterize human affective states evoked during music clip watching.
Heavy metal exist naturally in environment, but due to human and some natural activities they have been entered to water bodies, air and soil and have become one of the major global issue. They are ...equally toxic to both plants and animals as most of them have no role inside the bodies of plants and humans. After entry to the body most of them accumulate there for longer period of time producing various complications like in plants it can damage organs like root, leaves, and components of cells or even interfere with important biochemical process such as photosynthesis, absorption of minerals. Similarly in animals they can damage body basic organs like kidney, liver also cause serious diseases like cancer. The disorders produced by these heavy metals largely depend upon their dose, time of exposure and level of concentration. Heavy metals toxicity has become a serious problem due to their hazardous nature, bioaccumulation and non-biodegradable nature. Living things have been exposed to these heavy metals by various sources but water particularly drinking water is a prominent source. Extensive work has been carried out to remove these metals from water. But the conventional methods have various drawbacks like, not economical, have some impact on environment. Magnetic iron oxide nanoparticles have emerged an ultimate choice of water cleaning adsorbent. It has lot of qualities like, ecofriendly, cost effective, easy use, regeneration and surface modification.
•Toxicity of heavy metals in plants and animals•Toxicity of heavy metals in humans•Synthesis and applications of iron oxide NPs•Removal of heavy metals by magnetic iron oxide NPs
Patients with breast cancer are prone to serious health-related complications with higher mortality. The primary reason might be a misinterpretation of radiologists in recognizing suspicious lesions ...due to technical issues in imaging qualities and heterogeneous breast densities which increases the false-(positive and negative) ratio. Early intervention is significant in establishing an up-to-date prognosis process which can successfully mitigate complications of disease with higher recovery. The manual screening of breast abnormalities through traditional machine learning schemes misinterpret the inconsistent feature-extraction process which poses a problem, i.e., patients being called-back for biopsies to eliminates the suspicions. However, several deep learning-based methods have been developed for reliable breast cancer prognosis and classification but very few of them provided a comprehensive overview of lesions segmentation. This research focusses on providing benefits and risks of breast multi-imaging modalities, segmentation schemes, feature extraction, classification of breast abnormalities through state-of-the-art deep learning approaches. This research also explores various well-known databases using "Breast Cancer" keyword to present a comprehensive survey on existing diagnostic schemes to open-up new research challenges for radiologists and researchers to intervene as early as possible to develop an efficient and reliable breast cancer prognosis system using prominent deep learning schemes.
Non-traumatic chylothorax refers to accumulation of chyle in the pleural space in the absence of any traumatic disruption to the thoracic duct. Chyle originates from the intestines and is transported
...via
the thoracic duct into systemic circulation. The anatomical course of the thoracic duct is complex with considerable variation; therefore, development of chylothorax is dependent on the site and level of the thoracic duct defect. Non-traumatic chylothorax is associated with a wide range of medical disorders, but malignancy accounts for three-quarters of cases. In up to 9% of cases, the aetiology remains unknown (termed idiopathic chylothorax). Gross appearance of pleural fluid is neither sensitive nor specific enough to diagnose chylothorax; therefore, biochemical analysis of the pleural fluid is required. Pleural fluid triglyceride level >1.24 mmol·L
−1
(110 mg·dL
−1
) with a cholesterol level <5.18 mmol·L
−1
(200 mg·dL
−1
) is diagnostic of chylothorax. In borderline cases, lipoprotein electrophoresis can help confirm the diagnosis by detecting chylomicrons in the pleural fluid.
Once the diagnosis of chylothorax is confirmed, the next step is to find the cause and identify the leakage point, for which various lymphatic specific radiological investigations may have an important role. There is paucity of data on the most suitable approach to manage non-traumatic chylothoraces and treatment often depends on the underlying cause. In general, conservative treatment is tried first, usually for a limited time, before considering more invasive measures. A multidisciplinary approach is recommended with close liaison among the respiratory physicians, thoracic surgeons, oncologists, interventional radiologists, dietitians and pharmacists.
Educational aims
To review the pathophysiology, aetiology, and epidemiology of non-traumatic chylothorax.
To discuss diagnostic and therapeutic strategies in the management of non-traumatic chylothorax.
We have observed that the various individual heat transfer findings exist in the literature for both Newtonian and non-Newtonian fluids through the plane and cylindrical surfaces. These efforts ...contain specific thermophysical observations and one can get facilitated in one frame at a time. Therefore, in the present attempt, we execute a comparative heat transfer study because the unifying of different theories always receive appreciation from the research community. To support the idea, we considered convective magnetized and thermally stratified Jeffrey flow fields over inclined cylindrical and plane surfaces with and without non-linear thermal radiations. Stagnation point flow equations are constructed for cylindrical/plane surfaces in the presence of heat generation and heat absorption effects. The shooting method is used to solve reduced ordinary differential equations. We come to conclude that the Jeffrey fluid flow over a cylindrical surface subject to magnetic field parameter is large in magnitude in comparison with a plane surface. The strength of the temperature regime and heat transfer rate are also enriched for the cylindrical surface. Collectively, we come to know as a remark that thermophysical flow field aspects are enriched for magnetized stratified convective flow towards the cylindrical surface as compared to a plane surface.
It is well trusted that the physical believe subject to non-Newtonian fluid models in a magnetized frame always yield the complex mathematical equations and an exact solution in this direction seems ...impossible. Therefore, it remains challenging task for the researchers to report acceptable solutions. The current pagination contains a systemic remedy in this direction. To be more specific, the Carreau fluid flow towards flat surface is considered along with an externally applied magnetic field. The flow regime is manifested with pertinent physical believes namely, the heat source/sink and chemical reaction. The flow field is additionally supported with both the velocity and thermal slip effects. The Lie group of transformations is proposed for the present problem by means of group theoretic approach. The symmetry generator is constructed against developed Lie group of transformations. The characteristic equation subject to symmetry generator gives suitable set of variables. Such set of variables are used to step down the flow narrating differential equations in terms of an independent variables. Further, the reduced system is solved by numerical algorithm and the observations are offered by way of graphs. It is observed that the Carreau fluid velocity is suppressed for the case of magnetized flow field as compared to non-magnetized Carreau flow field. Further, the temperature of flow regime is higher in strength when the heat source is present. Finally, the results are validated by constructing comparison with an existing work.
•Two layer liquids subject to Carreau model are considered.•Mathematical model is proposed for two layer flow fields.•Order reduction application of Lie symmetry is debated.•Compatibility of problem is justified by graphical and tabular trends.
The mutual interaction of thermal stratification and solutal stratification in mixed convection flow regimes claims many thermal engineering standpoints in daily life and so holds the interest of ...researchers in the thermal science of fluid flows. Owning to such interest, the current attempt contains a comparative thermal case study on a non-Newtonian fluid flow field subject to inclined surfaces. The stagnation point temperature flow regime is manifested with non-linear radiations, magnetic field, and heat generation/absorptions effects. The physical problem is translated mathematically in terms of a non-linear coupled differential system. The solution is reported by using the shooting method for Jeffrey fluid flow. The surface quantities namely are Sherwood and Nusselt numbers are evaluated for various important physical domains namely radiative flow field, non-radiative flow field, stratified and non-stratified fields, magnetic and non-magnetic fields. We observed that the thermophysical characteristics of stagnation point flow of Jeffrey fluid are enriched in magnitude for the cylindrical surface. Further, the heat transfer normal to the cylindrical surface is higher in magnitude with temperature stratification in comparison with the flow regime without temperature stratification.
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