Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier

This article proposes a novel and efficient methodology for the detection of Glioblastoma tumor in brain MRI images. The proposed method consists of the following stages as preprocessing, Non‐subsampled Contourlet transform (NSCT), feature extraction and Adaptive neuro fuzzy inference system classification. Euclidean direction algorithm is used to remove the impulse noise from the brain image during image acquisition process. NSCT decomposes the denoised brain image into approximation bands and high frequency bands. The features mean, standard deviation and energy are computed for the extracted coefficients and given to the input of the classifier. The classifier classifies the brain MRI image into normal or Glioblastoma tumor image based on the feature set. The proposed system achieves 99.8% sensitivity, 99.7% specificity, and 99.8% accuracy with respect to the ground truth images available in the dataset.     

Single-phase and binary phase nanogranular ferrites for magnetic hyperthermia application

The study demonstrates the performance of heating efficiency in single-phase and binary phase spinel ferrite nanosystems. Ferrimagnetic cobalt ferrite (CoFe₂O₄) (CFO) and superparamagnetic copper ferrite/copper oxide (CuFe₂O₄/CuO) (CuF) nanosystems of different particle sizes were synthesized through a microwave-assisted coprecipitation method. The heating behavior was observed in range of both field amplitudes (8-24 kA/m at 516 kHz) and frequencies (325-973 kHz at 12 kA/m). The heating efficiency was analyzed and compared by means of particle size, magnetization, effective anisotropy constant, and Néel relaxation mechanism. Indeed, the heating rate was maximized in larger ferrite particles with low effective anisotropy constant. Moreover, though the magnetization and effective anisotropy constant of single-phase CoFe₂O₄ nanoparticles were higher, the binary phase CuFe₂O₄/CuO nanosystems of similar crystallite size (28 nm) exhibited superior heating efficiency (4.21°C/s). For a field amplitude and frequency of 24 kA/m and 516 kHz, the heating rate of CuF and CFO ferrites with different crystallite sizes decreased in the order of 4.21 > 2.14 > 0.58 > 0.52°C/s for 29 nm > 25 nm > 12 nm > 15 nm, respectively. The results emphasize that binary phase ferrite nanoparticles are better thermoseeds than the single-phase ferrites for the magnetic hyperthermia application.     

Rheum rhaponticum Root Extract Improves Vasomotor Menopausal Symptoms and Estrogen-Regulated Targets in Ovariectomized Rat Model

Ovarian insufficiency and ovariectomy are characterized by deregulated heat loss mechanisms. Unlike hormone therapy, ERr 731 (a standardized botanical extract of Siberian rhubarb Rheum rhaponticum L. high in rhaponticin) acts like a selective estrogen receptor modulator for ERβ receptors and may offer a higher degree of safety while maintaining the desired efficacy profile. In this study, we examined the relationship between oral administration of ERr 731 and the underlying components of skin vasomotion responses in an ovariectomized (OVX) rat model. ERr 731 dose-dependently reduced tail skin temperature (T_skin) values by an average of 1 °C. The rapid onset of this effect was observed in 1 and 3 mg/kg/day ERr 731 groups as early as day 2 of administration, and remained in place for the duration of the treatment (2 weeks). Substituting ERr 731 after E₂ withdrawal helped maintain body temperature similarly to E₂ alone, suggesting the usefulness of ERr 731 for replacing existing hormonal therapy in humans. ERr 731 also acted as a highly selective agonist for ERβ in the hypothalamus of OVX rats, as well as in ERα/β cell-based reporter assays. These data validate the OVX/T_skin rat model as a suitable screening platform to evaluate botanical and pharmaceutical treatments of menopause, while providing further evidence for the efficacy of ERr 731 towards alleviating vasomotor menopausal symptoms and improving wellbeing during the menopausal transition.     

Computer aided automated detection and classification of brain tumors using CANFIS classification method

The development of abnormal cells in human brain leads to the formation of tumors. This article proposes an efficient approach for brain tumor detection and segmentation using image fusion and co-active adaptive neuro fuzzy inference system (CANFIS) classification method. The brain MRI images are fused and the dual tree complex wavelet transform is applied on the fused image. Then, the statistical features, local ternary pattern features and gray level co-occurrence matrix features. These extracted features are classified using CANFIS classification approach for the classification of source brain MRI image into either normal or abnormal. Further, morphological operations are applied on the abnormal brain MRI image for segmenting the tumor regions. The proposed methodology is evaluated with respect to the performance metrics sensitivity, specificity, positive predictive value, negative predictive value, tumor segmentation accuracy with detection rate. The proposed image fusion based brain tumor detection and classification methodology stated in this article achieves 96.5% of average sensitivity, 97.7% of average specificity, 87.6% of positive predictive value, 96.6% of negative predictive value, and 98.8% of average accuracy.     

Brightness preserving bi‐level fuzzy histogram equalization for MRI brain image contrast enhancement

In this article, brightness preserving bi‐level fuzzy histogram equalization (BPFHE) is proposed for the contrast enhancement of MRI brain images. Histogram equalization (HE) is widely used for improving the contrast in digital images. As a result, such image creates side‐effects such as washed‐out appearance and false contouring due to the significant change in brightness. In order to overcome these problems, mean brightness preserving HE based techniques have been proposed. Generally, these methods partition the histogram of the original image into sub histograms and then independently equalize each sub‐histogram. The BPFHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two sub‐histograms based on the mean intensities of the multi‐peaks in the original image and then equalizes them independently to preserve image brightness. The quantitative and subjective enhancement of proposed BPBFHE algorithm is evaluated using two well known parameters like entropy or average information contents (AIC) and Feature Similarity Index Matrix (FSIM) for different gray scale images. The proposed method have been tested using several images and gives better visual quality as compared to the conventional methods. The simulation results show that the proposed method has better performance than the existing methods, and preserve the original brightness quite well, so that it is possible to be utilized in medical image diagnosis.     

Edible foxtail millet flour stabilises and retain the in vitro activity of blueberry bioactive components

Blueberries, a functional food, are rich in bioactive polyphenols and anthocyanins. However, the shelf life is short and requires cold storage. This study provides evidence that edible foxtail millet flour (FMF) efficiently sorbs only blueberry bioactive components (polyphenols and anthocyanins) but not sugars, improves their stability and retains the activity. The concentration of blueberry polyphenols and anthocyanins sorbed to FMF ranged from 6 to 113 and 4 to 41 mg g^?1, respectively. The concentration of bioactive components in one serving of blueberries (73 g) is equivalent to those present in 1.2 g of blueberry‐enriched foxtail millet flour (BFMF). The blueberry bioactive sorbed onto FMF remained stable for at least 16 weeks at 40 °C. BFMF eluates inhibited α‐glucosidase enzyme activity and scavenged the free radicals conferring that blueberry bioactive components in BFMF retained the activity. The sorption process described here provides a practical way of creating low glycemic protein‐rich edible flour enriched with plant bioactive compounds without sugars.     

Type Inversion and Certain Physical Properties of Spray Pyrolysed SnO::A1Films for Novel Transparent Electronics Applications

Aluminium doped tin oxide films have been deposited onto glass substrates by using a simplified and low cost spray pyrolysis technique.The Al doping level varies between 0 and 30 at.%in the step of 5 at.%.The resistivity(ρ) is the minimum(0.38 Ω cm) for 20 at.%of Al doping.The possible mechanism behind the phenomenal zig-zag variation in resistivity with respect to Al doping is discussed in detail.The nature of conductivity changes from n-type to p-type when the Al doping level is 10 at.%.The results show that20 at.%is the optimum doping level for good quality p-type SnO_2:AI films suitable for transparent electronic devices.     

The synthesis and photophysical studies of quinoxaline and pyridopyrazine derivatives

A simple and facile method for the synthesis of 2,3-bis[(E)-2-aryl vinyl]-quinoxaline and 2,3-bis[(E)-2-aryl vinyl]-pyrido(2,3-b)pyrazine is described. Condensation of cinnamils with 1,2-diaminobenzene and 2,3-diaminopyridine in water using conventional heating and microwave irradiation afforded high yields (71–92%) of 2,3-bis[(E)-2-aryl vinyl]-quinoxalines and 2,3-bis[(E)-2-arylvinyl]-pyrido(2,3-b)pyrazines. The photophysical properties of the resultant quinoxaline and pyrazine derivatives were studied; the pyridopyrazine derivatives were found to exhibit halochromism.