A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography.

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delicate to diagnose accurately as the quality and interpretation of images can vary depending on the operator's experience and proficiency. Therefore, computer-aided diagnosis technology can facilitate diagnosis by visualizing abnormal information such as tumors and masses in ultrasound images. In this study, we implemented deep learning-based anomaly detection methods for breast ultrasound images and validated their effectiveness in detecting abnormal regions. Herein, we specifically compared the sliced-Wasserstein autoencoder with two representative unsupervised learning models autoencoder and variational autoencoder. The anomalous region detection performance is estimated with the normal region labels. Our experimental results showed that the sliced-Wasserstein autoencoder model outperformed the anomaly detection performance of others. However, anomaly detection using the reconstruction-based approach may not be effective because of the occurrence of numerous false-positive values. In the following studies, reducing these false positives becomes an important challenge.

Fabrication of 1,4-alpha-D-glucan glucanohydrolase holding Gel-Scaffolds using Agar-Agar, a natural polysaccharide and Polyacrylamide, a synthetic organic polymer for continuous liquefaction of starch

1,4-alpha-D-glucan glucanohydrolase is among the most widely used commercial hydrolytic enzymes acting randomly on the glycosidic linkages of starch resulting in its saccharification and liquefaction. Its applicability in different industries can be improved by enhancing its stability and reusability. Therefore, in the present study attempts have been made to enhance the industrial applicability of 1,4-alpha-D-glucan glucanohydrolase from Bacillus subtilis KIBGE-HAR by adapting immobilization technology. The study developed mechanically stable, enzyme containing gel-frameworks using two support matrices including agar-agar, a natural polysaccharide and polyacrylamide gel, a synthetic organic polymer. These catalytic gel-scaffolds were compared with each other in terms of kinetics and stability of entrapped 1,4-α-D-glucan glucanohydrolase. In case of polyacrylamide gel, Km value for immobilized enzyme increased to 7.95 mg/mL, while immobilization in agar-agar resulted in decreased Km value i.e 0.277 mg/mL as compared to free enzyme. It was found that immobilized enzyme showed maximum activity at 70 °C in both the supports as compared to free enzyme having maximum activity at 60 °C. Immobilized 1,4-α-D-glucan glucanohydrolase exhibited no change in optimal pH 7.0 before and after entrapment in polyacrylamide gel and agar-agar. The enzyme containing gel-scaffold was found suitable for repeated batches of starch liquefaction in industrial processes. Agar-agar entrapped 1,4-α-D-glucanglucanohydrolase was capable to degrade starch up to seven repeated operational cycles whereas polyacrylamide entrapped enzyme conserved its activity up to sixth operational cycle.

Application of NIR Spectroscopy Coupled with PLS Regression for Quantification of Total Polyphenol Contents from the Fruit and Aerial Parts of Citrullus colocynthis.

INTRODUCTION: Citrullus colocynthis (L.) Schrad is extensively used to treat diabetes, obesity, fever, cancer, amenorrhea, jaundice, leukemia, rheumatism, and respiratory diseases. Chemical studies have indicated the presence of several cucurbitacins, flavones, and other polyphenols in this plant. These phytochemical constituents are responsible for the interesting antioxidant and other biological activities of C. colocynthis. OBJECTIVE: In the present study, for the first time, near infrared (NIR) spectroscopy coupled with partial least square (PLS) regression analysis was used to quantify the polyphenolic phytochemicals of C. colocynthis. METHODOLOGY: The fruit and aerial parts of the C. colocynthis were extracted individually in methanol followed by fractionation in n-hexane, chloroform, ethyl acetate, n-butanol, and water. Near infrared (NIR) spectra were obtained in absorption mode in the wavelength range 700-2500 nm. The PLS regression model was then built from the obtained spectral data to quantify the total polyphenol contents in the selected plant samples. RESULTS: The PLS regression model obtained had a R2 value of 99% with a 0.98 correlationship value and a good prediction with a root mean square error of prediction (RMSEP) value of 1.89% and correlation of 0.98. These results were further confirmed through UV-vis spectroscopy and it is found that the ethyl acetate fraction has the maximum value for polyphenol contents (101.7 mg/100 g; NIR, 100.4 mg/100 g; UV-vis). CONCLUSIONS: The polyphenolic phytochemicals of the fruit and aerial parts of C. colocynthis have been quantified successfully by using multivariate analysis in a non-destructive, economical, precise, and highly sensitive method, which uses very simple sample preparation. Copyright © 2017 John Wiley & Sons, Ltd.

New design of experiment combined with UV-Vis spectroscopy for extraction and estimation of polyphenols from Basil seeds, Red seeds, Sesame seeds and Ajwan seeds.

New experimental designs for the extraction of polyphenols from different seeds including Basil seed, Red seed, Sesame seeds and Ajwan seeds were investigated. Four variables the concentration and volume of methanol and NaOH solutions as well as the temperature and time of extraction were varied to see their effect on total phenol extraction. The temperature was varied in the range from 25°C to 200°C while the time in the range from 30 to 200minutes. Response surface methodology was used to optimize the extraction parameters. The estimation of polyphenols was measured through phenols reduction UV-Vis spectroscopic method of phosphotungstic-phosphomolybdic acids (Folin-Ciocalteu's reagent). Calibration curve was made by using tannic acid as a polyphenols standard in the concentration range from 0.1 to 10ppm. The regression line obtained shows the value of correlation coefficient i.e. R=0.930 and Root mean square error of cross validation (RMSEC) value of 0.0654. The Basil seeds were found containing the highest amount of total phenols i.e. 785.76mg/100g. While the Sesame seeds having the least amount i.e. 33.08mg/100g. The Ajwan seeds and the Red seeds are containing the medium amounts i.e. 379mg/100g and 220.54mg/100g respectively.

Isolation and bioactivities of the flavonoids morin and morin-3-O-ß-D-glucopyranoside from Acridocarpus orientalis-A wild Arabian medicinal plant.

Acridocarpus orientalis is an important medicinal plant for some of the locals of Arabian region. Very little is known about its phytochemical constituents. In the present study, we aimed to isolate bioactive chemicals from the crude methanolic extract of the aerial parts of A. orientalis. The extraction and isolation resulted in the purification of two flavonoids: morin (1) and morin-3-O-ß-D-glucopyranoside (2). The structure elucidation was carried out by extensive analysis of spectroscopic data and comparison with the reported data for the known constituents. The pure isolates were subjected to various biological assays for their bioactivities. The compounds 1 and 2 were significantly active against the growth of various pathogenic fungi and phytotoxic against lettuce seed at higher concentrations. Furthermore, the free radical scavenging activities, anti-lipid peroxidation, and cytotoxic effects against HepG2, HT29, and HCT116 cancer cell lines were also assayed and the results are presented in this paper.