An actinomycete producing L-3,4-dihydroxyphenylalanine from L-tyrosine

An actinomycete was isolated during a soil screening programme to obtain L-3,4-dihydroxyphenylalanine producers. A mutant of this organism was isolated by chemical mutagenesis and it accumulated 1 g/litre L-dihydroxyphenylalanine when grown on L-tyrosine. Resting cells converted 30% of tyrosine in the reaction mixture. The use of resting cells for dihydroxyphenylalanine production is advantageous as it eliminates interfering substances which accumulate during fermentation

Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process

A variant of neural network for processing with images is a convolutional neural network (CNN). This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to effectively do the classification, detection, and many other tasks. In the present work, U-Net convolutional neural network is implemented on Jupyter platform by using Python programming for fracture surface image segmentation in Oil Hardening Non-Shrinking (OHNS) die steel after the machining process. The results showed that the fracture cracks can be validated by testing with higher accuracy

Cell cycle-dependent regulation of the bi-directional overlapping promoter of human BRCA2/ZAR2 genes in breast cancer cells

<p>Abstract</p> <p>Background</p> <p>BRCA2 gene expression is tightly regulated during the cell cycle in human breast cells. The expression of BRCA2 gene is silenced at the G0/G1 phase of cell growth and is de-silenced at the S/G2 phase. While studying the activity of BRCA2 gene promoter in breast cancer cells, we discovered that this promoter has bi-directional activity and the product of the reverse activity (a ZAR1-like protein, we named ZAR2) silences the forward promoter at the G0/G1 phase of the cell. Standard techniques like cell synchronization by serum starvation, flow cytometry, N-terminal or C-terminal FLAG epitope-tagged protein expression, immunofluorescence confocal microscopy, dual luciferase assay for promoter evaluation, and chromatin immunoprecipitation assay were employed during this study.</p> <p>Results</p> <p>Human <it>BRCA2 </it>gene promoter is active in both the forward and the reverse orientations. This promoter is 8-20 fold more active in the reverse orientation than in the forward orientation when the cells are in the non-dividing stage (G0/G1). When the cells are in the dividing state (S/G₂), the forward activity of the promoter is 5-8 folds higher than the reverse activity. The reverse activity transcribes the ZAR2 mRNA with 966 nt coding sequence which codes for a 321 amino acid protein. ZAR2 has two C4 type zinc fingers at the carboxyl terminus. In the G0/G1 growth phase ZAR2 is predominantly located inside the nucleus of the breast cells, binds to the BRCA2 promoter and inhibits the expression of BRCA2. In the dividing cells, ZAR2 is trapped in the cytoplasm.</p> <p>Conclusions</p> <p><it>BRCA2 </it>gene promoter has bi-directional activity, expressing BRCA2 and a novel C4-type zinc finger containing transcription factor ZAR2. Subcellular location of ZAR2 and its expression from the reverse promoter of the BRCA2 gene are stringently regulated in a cell cycle dependent manner. ZAR2 binds to BRCA2/ZAR2 bi-directional promoter <it>in vivo </it>and is responsible, at least in part, for the silencing of BRCA2 gene expression in the G0/G1 phase in human breast cells.</p

Subglottic Stenosis: A Real Nightmare for Anaesthesiologist, Occurred In a Newborn with Tracheoesophageal Fistula

Subglottis stenosis is a real nightmare situation for anaesthetist more so in a neonate. We came across such an emergency of unanticipated difficult intubation in a case of type D tracheoesophageal fistula. We managed the situation with surgical tracheostomy with use of endotracheal tube. There are limited references of managing such emergency in a newborn in the present literature. We have also discussed other means of managing such situation

An Algae Bioreactor from Recycle Water bottle for Cultivation of Algae

Abstract: The cultivation of algae provides excellent perspectives for renewable energy production and as a source of &apos;green&apos; products. Algae cultivation can thus contribute substantially to a reduction of CO 2 emissions. This paper describes systems used to cultivate algae from recycle water bottle for biofuel production. For the better quality of Algae cultivation it required a treatment of Nutrients. In this paper we discussed about the construction of Algae bioreactor from recycle water bottle and the treatments of nutrients (Ammonium sulphate, Urea) which required for cultivation of Algae. Result shows that the Algae cultivated from this Algae bioreactor from recycle water bottle is containing large amount of oil than the Algae grow in a rives, wells, ponds etc

To Study and Analyze to foresee market Using Data Mining Technique

Abstract In every field there is huge growth and demand in knowledge and information over the internet. The automation using data mining and predictive technologies are doing an advance amount of deals in the markets. Data mining is all based on the theory that the historic data holds the essential memory for predicting the future direction. This technology is designed to help shareholders to discover hidden patterns from the historic data that have probable predictive capability in their investment decisions. The prediction of stock markets is regarded as a challenging task of financial time series prediction. Data analysis is one way of predicting if future stocks prices will increase or decrease. There are some methods of analyzing stocks which were combined to predict if the day&apos;s closing price would increase or decrease. These methods include study of Price, Index, and Average. (For e.g.Typical Price (TP), Bands, Relative Strength Index (RSI), CMI and Moving Average (MA))

Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process

A variant of neural network for processing with images is a convolutional neural network (CNN). This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to effectively do the classification, detection, and many other tasks. In the present work, U-Net convolutional neural network is implemented on Jupyter platform by using Python programming for fracture surface image segmentation in Oil Hardening Non-Shrinking (OHNS) die steel after the machining process. The results showed that the fracture cracks can be validated by testing with higher accuracy. The plot of accuracy vs. number of epochs showed the obtained accuracy score 0f 1.0 which means that 100 % of points were correctly labeled by our implemented algorithm

Serendipitous alkylation of a Plk1 ligand uncovers a new binding channel

We obtained unanticipated synthetic byproducts from alkylation of the δ[superscript 1] nitrogen (N3) of the histidine imidazole ring of the polo-like kinase-1 (Plk1) polo-box domain (PBD)-binding peptide PLHSpT. For the highest-affinity byproduct, bearing a C[subscript 6]H[subscript 5](CH[subscript 2])[subscript 8]– group, a Plk1 PBD cocrystal structure revealed a new binding channel that had previously been occluded. An N-terminal PEGylated version of this peptide containing a hydrolytically stable phosphothreonyl residue (pT) bound the Plk1 PBD with affinity equal to that of the non-PEGylated parent but showed markedly less interaction with the PBDs of the two closely related proteins Plk2 and Plk3. Treatment of cultured cells with this PEGylated peptide resulted in delocalization of Plk1 from centrosomes and kinetochores and in chromosome misalignment that effectively induced mitotic block and apoptotic cell death. This work provides insights that might advance efforts to develop Plk1 PBD-binding inhibitors as potential Plk1-specific anticancer agents.National Institutes of Health (U.S.) (Grant GM60594)National Institutes of Health (U.S.) (Grant GM68762)National Institutes of Health (U.S.) (Grant CA112967