FLI1 is a member of ETS family of transcription factors that regulate a variety of normal biologic activities including cell proliferation, differentiation, and apoptosis. The expression of FLI1 and its correlation with well-known breast cancer prognostic markers (ER, PR and HER2) was determined in primary breast tumors as well as four breast cancer lines including: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 using RT-qPCR with either 18S rRNA or ACTB (β-actin) for normalization of data. FLI1 mRNA level was decreased in the breast cancer cell lines under study compared to the normal breast tissue; however, Jurkat cells, which were used as a positive control, showed overexpression compared to the normal breast. Regarding primary breast carcinoma

Abstract The results showed that after treating <italic>C. albicans</italic> with Artemisinin (0.104 mg/ml) for 3 hours the number of <italic>C. albicans</italic> decreased and affected the morphology hyphae and growth of <italic>Candida</italic> compared with Fluconazole (150 mg/ml) and control (infected mice). The biomarker levels in the tongue showed high levels of MDA and TGFβ (623±1.5pg/ml, 586.1±0.13pg/ml respectively) in (infected mice with fungi). IL-37 was recorded high level (49.21±0.21pg/ml) in (Neoral +Fungi + artemisinin + fluconazole) compared with negative control. The finding biomarker levels in stomach showed high levels of MDA and IL-37 (533.8±1.9, 69.76±0.39pg/ml) in (Neor

Optical losses represent one of the primary obstacles to increasing the efficiency of silicon solar cells. The recommended solution to minimize optical losses is the use of plasmonic metal nanoparticles; however, they act as recombination centers within the solar cell construction, leading to a decrease in performance. The goal of this article is to introduce cobalt/graphene nanoparticles into the solar cell to minimize the optical losses. An ultra-thin film silicon PIN solar cell of dimensions (400 ×400 ×900) nm3 with ring metal contact shape was designed and numerically investigated using COMSOL Multiphysics software version 6.2 by the finite element method (FEM). Core/shell cobalt-graphene (Co/Gr) nanoparticles are periodically int

The Frequency-hopping Spread Spectrum (FHSS) systems and techniques are using in military and civilianradar recently and in the communication system for securing the information on wireless communications link channels, for example in the Wi-Fi 8.02.X IEEE using multiple number bandwidth and frequencies in the wireless channel in order to hopping on them for increasing the security level during the broadcast, but nowadays FHSS problem, which is, any Smart Software Defined Radio (S-SDR) can easily detect a wireless signal at the transmitter and the receiver for the hopping sequence in both of these, then duplicate this sequence in order to hack the signal on both transmitter and receiver messages using the order of the se

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

Despite extensive investigations, an effective treatment for sepsis remains elusive and a better understanding of the inflammatory response to infection is required to identify potential new targets for therapy. In this study we have used RNAi technology to show, for the first time, that the inducible lysophosphatidylcholine acyltransferase 2 (LPCAT2) plays a key role in macrophage inflammatory gene expression in response to stimulation with bacterial ligands. Using siRNA- or shRNA-mediated knockdown, we demonstrate that, in contrast to the constitutive LPCAT1, LPCAT2 is required for macrophage cytokine gene expression and release in response to TLR4 and TLR2 ligand stimulation but not for TLR-independent stimuli. In addition, cells transfe

A simple, economical and selective method employing ion pair dispersive liquid−liquid microextraction (DLLME) coupled with spectrophotometric determination of carbamazepine (CBZ) in pharmaceutical preparations and biological samples was developed. The method is based on reduction of Mo(VI) to Mo(V) using a combination of ammonium thiocyanate and ascorbic acid in acidic medium to form a red binary Mo(V) thiocyanate complex. After addition of CBZ to the complex, extraction of the formed CBZ−Mo(V)−(SCN)6 was performed using a mixture of methylene chloride and methanol. Then, the measurement of target complex was performed at the wavelength of 470 nm. The important extraction parameters affecting the efficiency of DLLME were studied and o

Activation of farnesoid X receptor (FXR) markedly attenuates development of atherosclerosis in animal models. However, the underlying mechanism is not well elucidated. Here, we show that the FXR agonist, obeticholic acid (OCA), increases fecal cholesterol excretion and macrophage reverse cholesterol transport (RCT) dependent on activation of hepatic FXR. OCA does not increase biliary cholesterol secretion, but inhibits intestinal cholesterol absorption. OCA markedly inhibits hepatic cholesterol 7α‐hydroxylase (Cyp7a1) and sterol 12α‐hydroxylase (Cyp8b1) partly through inducing small heterodimer partner, leading to reduced bile acid pool size and al

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte