Mcculloughbuchanan5463

Correlation tests showed that coenzyme A was strongly correlated with SDEGs (0.82 ≤|r|≤ 0.96). Acetyl-CoA and adenosine 5'-monophosphate were strongly correlated with CCRN4L (0.90 ≤|r|≤ 0.92), indicating a strong correlation between the changes in SDEGs and these metabolites. In conclusion, Lys deficiency caused dysplasia and affected lipid metabolism in the liver by inhibiting lipolysis and lipid synthesis in calves.Gamma-aminobutyric acid (GABA) biosynthesis depended to a great extent on the biotransformation characterization of glutamate decarboxylase (GAD) and process conditions. In this paper, the enhancing effect of D101 macroporous adsorption resin (MAR) on the GABA production was investigated based on the whole-cell biotransformation characterization of Enterococcus faecium and adsorption characteristics of D101 MAR. The results indicated that the optimal pH for reaction activity of whole-cell GAD and pure GAD was 4.4 and 5.0, respectively, and the pH range retained at least 50% of GAD activity was from 4.8 to 5.6 and 4.0-4.8, respectively. No substrate inhibition effect was observed on both pure GAD and whole-cell GAD, and the maximum activity could be obtained when the initial L-glutamic acid (L-Glu) concentration exceeded 57.6 mmol/L and 96.0 mmol/L, respectively. Besides, GABA could significantly inhibit the activity of whole-cell GAD rather than pure GAD. When the initial GABA concentration of the reaction solution remained 100 mmol/L, 33.51 ± 9.11% of the whole-cell GAD activity was inhibited. D101 MAR exhibited excellent properties in stabilizing the pH of the conversion reaction system, supplementing free L-Glu and removing excess GABA. Comparison of the biotransformation only in acetate buffer, the GABA production, with 50 g/100 mL of D101 MAR, was significantly increased by 138.71 ± 5.73%. D101 MAR with pre-adsorbed L-Glu could significantly enhance the production of GABA by gradual replenishment of free L-Glu, removing GABA and maintaining the pH of the reaction system, which would eventually make the GABA production more economical and eco-friendly.BACKGROUND Oral squamous cell carcinoma is occupying the eighth position of all malignant neoplasia worldwide. Nowadays, natural compounds found in vegetables and fruits are important resources of many anticancer drugs especially those with high levels of phytochemicals representing an efficient strategy for cancer prevention and treatment. Artichoke (Cynara cardunculus L.) is a kind of antioxidant-rich vegetables demonstrated a potential anticancer activity on various types of cancer cells related to its content of phenolic compounds. Anticarcinogenic effects of polyphenolic extracts were reported to cause a reduction in cell viability, inhibition of cell growth, and initiation of apoptotic mechanisms. The present study aimed to investigate the cell cycle arrest, cytotoxic, and apoptotic effects of artichoke extract against the invasive oral squamous cell carcinoma. RESULTS A pure extract from the edible part and leaves of fresh artichoke was added to oral squamous carcinoma cell lines and to control group to evaluate the expression of caspase-9, Bcl-2, and Bax genes. Artichoke extract demonstrated the highest cytotoxic effect against cancer cell lines which increased in a time-dependent manner. No apparent effects were observed in the normal control group. Expression of Bax and caspase-9 genes revealed a highly significant increase in cancer cell lines (p = 0.0001) when compared to the control group. In addition to a highly significant decrease (p = 0.005) in Bcl-2 of cancer cells. It was demonstrated that artichoke extract induced cell growth arrest at G2/M phase which revealed a significant increase (p less then 0.05) in comparison to the untreated control group. CONCLUSION Artichoke exerts potent cell cycle arrest, cytotoxic, and apoptotic effects on oral squamous carcinoma cell lines.The present study investigated the acute (72 h) and sub-acute (14 days) toxicity of mercury, lead, and cadmium to the green microalga, Nannochloropsis oculata. The acute toxicity testing was conducted according to the modified OECD guideline (No. 201). The 72-h IC50 values of Hg, Pb, and Cd exposed to N. oculata were 0.87, 1.81, and 4.97 mg/L, respectively. These results showed that mercury is about twice as toxic as lead and about 5.7 times more toxic than cadmium to this marine microalga. Lead is about 2.7 times more toxic than cadmium. The chlorophyll a content of the microalga decreased in the 10th and 14th days of the sub-acute toxicity test. Although the carotenoid content increased following exposure to the low levels of tested heavy metals (which may show the protective role of carotenoids against oxidative stress), with increased exposure time the total carotenoid reduced compared to control. A regular monitoring program to examine the level of metals in the aquatic ecosystem for protecting microalgae should be implemented.INTRODUCTION Moisturizers are one of the mainstays of the topical treatment of atopic dermatitis (AD). One of the adverse effects of moisturizers is skin irritation, especially on excoriated AD skin. selleck kinase inhibitor We compared the potential for irritation of two commercially available moisturizer products for the treatment of AD a ceramide-based moisturizer (Ceradan® Cream; Hyphens Pharma Pte Ltd, Singapore) and a urea 5% moisturizer (Aqurea Lite Cream; ICA Pharma Pte Ltd, Singapore). METHODS We performed a prospective single-blind randomized controlled study recruiting AD patients aged between 8 and 16 years with symmetrical or near symmetrical scratch marks (excoriations) of at least grade 2 to 3 severity score, according to the Eczema Area and Severity Index (EASI), over bilateral antecubital fossae. Subjects were randomized to receive the ceramide-based moisturizer to either the left or right antecubital fossa or urea 5% cream to the other antecubital fossa. Subjects were asked to grade the immediate skin irritation of both creams on a standard visual analogue scale (VAS) and which cream they would prefer to use as a daily moisturizer. Primary outcome was the mean irritant score of each cream, and secondary outcome was the subjects' preference of either cream as their daily moisturizer. RESULTS A total of 42 participants were enrolled with a mean age of 11 years 5 months. The ceramide-based cream had a significantly lower mean VAS score (mean 0.69, SD = 1.63) for irritation compared with urea 5% cream (1.43, SD = 1.64) (p = 0.035). More participants also preferred the ceramide-based cream over urea 5% cream (62% versus 38%) as their daily moisturizer, but this did not reach statistical significance (p = 0.164). CONCLUSIONS A ceramide-based moisturizer may be considered as a suitable choice for children to minimize irritation from moisturizer treatment for AD.PURPOSE Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid-attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data. METHODS The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study. RESULTS The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly. CONCLUSION This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https//github.com/razeineldin/DeepSeg/.PURPOSE The registration of a preoperative 3D model, reconstructed, for example, from MRI, to intraoperative laparoscopy 2D images, is the main challenge to achieve augmented reality in laparoscopy. The current systems have a major limitation they require that the surgeon manually marks the occluding contours during surgery. This requires the surgeon to fully comprehend the non-trivial concept of occluding contours and surgeon time, directly impacting acceptance and usability. To overcome this limitation, we propose a complete framework for object-class occluding contour detection (OC2D), with application to uterus surgery. METHODS Our first contribution is a new distance-based evaluation score complying with all the relevant performance criteria. Our second contribution is a loss function combining cross-entropy and two new penalties designed to boost 1-pixel thickness responses. This allows us to train a U-Net end to end, outperforming all competing methods, which tends to produce thick responses. Our third contribution is a dataset of 3818 carefully labelled laparoscopy images of the uterus, which was used to train and evaluate our detector. RESULTS Evaluation shows that the proposed detector has a similar false false-negative rate to existing methods but substantially reduces both false-positive rate and response thickness. Finally, we ran a user study to evaluate the impact of OC2D against manually marked occluding contours in augmented laparoscopy. We used 10 recorded gynecologic laparoscopies and involved 5 surgeons. Using OC2D led to a reduction of 3 min and 53 s in surgeon time without sacrificing registration accuracy. CONCLUSIONS We provide a new set of criteria and a distance-based measure to evaluate an OC2D method. We propose an OC2D method which outperforms the state-of-the-art methods. The results obtained from the user study indicate that fully automatic augmented laparoscopy is feasible.PURPOSE The detection of clinically significant prostate cancer (PCa) is shown to greatly benefit from MRI-ultrasound fusion biopsy, which involves overlaying pre-biopsy MRI volumes (or targets) with real-time ultrasound images. In previous literature, machine learning models trained on either MRI or ultrasound data have been proposed to improve biopsy guidance and PCa detection. However, quantitative fusion of information from MRI and ultrasound has not been explored in depth in a large study. This paper investigates information fusion approaches between MRI and ultrasound to improve targeting of PCa foci in biopsies. METHODS We build models of fully convolutional networks (FCN) using data from a newly proposed ultrasound modality, temporal enhanced ultrasound (TeUS), and apparent diffusion coefficient (ADC) from 107 patients with 145 biopsy cores. The architecture of our models is based on U-Net and U-Net with attention gates. Models are built using joint training through intermediate and late fusion of the data.