A Convolutional Neural Network for Automatic Brain Tumor Detection

Magnetic resonance imaging (MRI) combined with artificial intelligence (AI) algorithms to detect brain tumors is one of the important medical applications.  In this study, a Convolutional neural network (CNN) model is proposed to detect meningioma and pituitary, which was tested with a dataset consisting of two categories of tumors with 1,800 MRI images from several persons. The CNN model is trained via a Python library, namely TensorFlow, with an automatic tuning approach to obtain the highest testing accuracy of tumor detection. The CNN model used Python programming language in Google Colab to detect sensitivity, precision, the area under the PR and receiver operating characteristic (ROC), error matrix, and accuracy. The results show that the proposed CNN model has a high performance in the detection of brain tumors. It achieves an accuracy of 95.78% and a weighted average precision of 95.82%

Functionalized graphene oxide tablets for sample preparation of drugs in biological fluids: Extraction of ritonavir, a HIV protease inhibitor, from human saliva and plasma using LC-MS/MS.

In this work, graphene oxide-based tablets (GO-Tabs) were prepared by applying a thin layer of functionalized GO on a polyethylene substrate. The GO was functionalized with amine groups (-NH2 ) by poly(ethylene glycol)bis(3-aminopropyl) terminated (GO-NH2 -PEG-NH2 ). The functionalized GO-Tabs were used for the extraction of ritonavir (RTV) in human saliva samples. RTV in plasma and saliva samples was analyzed using LC-MS/MS. Gradient LC system with MS/MS in the positive-ion mode [electrospray ionization (ESI+)] was used. The transitions m/z 721 → 269.0 and m/z 614 → 421 were used for RTV and the internal standard indinavir, respectively. This study determined the human immunodeficiency virus protease inhibitor RTV in human saliva samples using functionalized GO-Tab and LC-MS/MS, and the method was validated. The standard calibration curve for plasma and saliva samples was constructed from 5.0 to 2000 nmol L-1 . The limit of detection was 0.1 nmol L-1 , and the limit of quantification was 5.0 nmol L-1 in both plasma and saliva matrices. The intra- and inter-assay precision values were found to be between 1.5 and 5.8%, and the accuracy values ranged from 88.0 to 108% utilizing saliva and plasma samples. The extraction recovery was more than 80%, and the presented functionalized GO-Tabs could be reused for more than 10 extractions without deterioration in recovery

Interferon therapy shifts natural killer subsets among Egyptian patients with chronic hepatitis C

AbstractNatural killer cells can be divided into five subpopulations based on the relative expression of CD16 and CD56 markers. The majority of natural killer cells are CD56dim, which are considered to be the main cytotoxic effectors. A minority of the natural killer cells are CD56bright, and function as an important source of immune-regulatory cytokines. Shifts of these subsets have been reported in patients with chronic hepatitis C virus infection. We sought to investigate the shift of natural killer subsets among Egyptian patients with chronic HCV and to analyze the influence of interferon therapy on this shift. We applied a flow cytometric analysis of peripheral blood natural killer subsets for 12 interferon-untreated and 12 interferon-treated patients with chronic HCV, in comparison to 10 control subjects. Among interferon-untreated patients, there was a significant reduction of CD56-16+ (immature natural killer) cells. Among interferon-treated patients, the absolute count of natural killer cells was reduced, with expansion of the CD56bright subset and reduction of the CD56dim16+ subset. Natural killer subset counts were not significantly correlated to HCV viral load and were not significantly different among interferon responders and non-responders. In conclusion, HCV infection in Egyptian patients has been observed to be statistically and significantly associated with reduction of the CD56-16+NK subset, while a statistically significant expansion of CD56bright and reduction of CD56dim16+ subsets were observed after interferon therapy. Further studies are required to delineate the molecular basis of interferon-induced shift of natural killer subsets among patients with HCV

In Vitro and In Silico Antioxidant Efficiency of Bio-Potent Secondary Metabolites From Different Taxa of Black Seed-Producing Plants and Their Derived Mycoendophytes

Oxidative stress is involved in the pathophysiology of multiple health complications, and it has become a major focus in targeted research fields. As known, black seeds are rich sources of bio-active compounds and widely used to promote human health due to their excellent medicinal and pharmaceutical properties. The present study investigated the antioxidant potency of various black seeds from plants and their derived mycoendophytes, and determined the total phenolic and flavonoid contents in different extracts, followed by characterization of major constituents by HPLC analysis. Finally, in silico docking determined their binding affinities to target myeloperoxidase enzymes. Ten dominant mycoendophytes were isolated from different black seed plants. Three isolates were then selected based on high antiradical potency and further identified by ITS ribosomal gene sequencing. Those isolated were Aspergillus niger TU 62, Chaetomium madrasense AUMC14830, and Rhizopus oryzae AUMC14823. Nigella sativa seeds and their corresponding endophyte A. niger had the highest content of phenolics in their n-butanol extracts (28.50 and 24.43 mg/g), flavonoids (15.02 and 11.45 mg/g), and antioxidant activities (90.48 and 81.48%), respectively, followed by Dodonaea viscosa and Portulaca oleracea along with their mycoendophytic R. oryzae and C. madrasense. Significant positive correlations were found between total phenolics, flavonoids, and the antioxidant activities of different tested extracts. The n-butanol extracts of both black seeds and their derived mycoendophytes showed reasonable IC50 values (0.81–1.44 mg/ml) compared to the control with significant correlations among their phytochemical contents. Overall, seventeen standard phenolics and flavonoids were used, and the compounds were detected in different degrees of existence and concentration in the examined extracts through HPLC analysis. Moreover, the investigation of the molecular simulation results of detected compounds against the myeloperoxidase enzyme revealed that, as a targeted antioxidant, rutin possessed a high affinity (−15.3184 kcal/mol) as an inhibitor. Taken together, the black seeds and their derived mycoendophytes are promising bio-prospects for the broad industrial sector of antioxidants with several valuable potential pharmaceutical and nutritional applications

New Trend in Sample Preparation: On-line Microextraction in Packed Syringe for Liquid and Gas Chromatography Applications: I. Determination of Local Anaesthetics in Human Plasma Samples Using Gas Chromatography–Mass Spectrometry.

Abstract A new technique for sample preparation on-line with LC and GC-MS assays was developed. Microextraction in a packed syringe (MEPS) is a new miniaturised, solid-phase extraction technique that can be connected on-line to GC or LC without any modifications. In MEPS approximately 1 mg of the solid packing material is inserted into a syringe (100-250 l) as a plug. Sample preparation takes place on the packed bed. The bed can be coated to provide selective and suitable sampling conditions. The new method is very promising. It is very easy to use, fully automated, of low cost and rapid in comparison with previously used methods. This paper presents the development and validation of a method for microextraction in packed syringe MEPS on-line with GC-MS. Local anaesthetics in plasma samples were used as model substances. The method was validated and the standard curves were evaluated by the means of quadratic regression and weighted by inverse of the concentration: 1/x for the calibration range 5-2000 nM. The applied polymer could be used more than 100 times before the syringe was discarded. The extraction recovery was between 60 and 90%. The results showed close correlation coefficients (R > 0.99) for all analytes in the calibration range studied. The accuracy of MEPS-GC-MS was between 99 and 115% and the inter-day precision (n = 3 days), expressed as the relative standard deviation (R.S.D.%), was 3-10%