Microsomal prostaglandin E synthase-1: the inducible synthase for prostaglandin E(2)

Microsomal prostaglandin E synthase-1 (mPGES-1) is an inducible enzyme that catalyzes the conversion of prostaglandin (PG)H(2 )to PGE(2). Proinflammatory stimuli markedly increase levels of mPGES-1 expression both in vivo and in vitro. mPGES-1 knockout studies and animal models of inflammatory arthritis also provide a strong basis for the contribution of mPGES-1 in the increased local production of PGE(2 )observed in inflammatory arthritis. The focus of this article is to review some recent advances in our understanding of mechanisms specific to the regulation of inducible mPGES-1 in inflammatory arthritis

Search for optical bursts from the gamma ray burst source GBS 0526-66

Attempts were made to detect optical bursts from the gamma-ray burst source GBS 0526-66 during Dec. 31, 1984 to Jan. 2, 1985 and Feb. 23 to Feb. 24, 1985, using the one meter reflector of the Kavalur Observatory. Jan. 1, 1985 coincided with the zero phase of the predicted 164 day period of burst activity from the source (Rothschild and Lingenfelter, 1984). A new optical burst photon counting system with adjustable trigger threshold was used in parallel with a high speed photometer for the observations. The best time resolution was 1 ms and maximum count rate capability was 255,000 counts s(-1). Details of the instrumentation and observational results are presented

Myeloid dendritic cells display downregulation of C-type lectin receptors and aberrant lectin uptake in systemic lupus erythematosus

Abstract Introduction There is a growing body of evidence implicating aberrant dendritic cell function as a crucial component in the immunopathogenesis of systemic lupus erythematosus. The purpose of the present study was to characterize the phagocytic capacity and expression of receptors involved in pathogen recognition and self-nonself discrimination on myeloid dendritic cells from patients with lupus. Methods Unstimulated or stimulated monocyte-derived dendritic cells were obtained from lupus patients and healthy control individuals, and expression of C-type lectin receptors (mannose receptor and dendritic cell-specific intercellular adhesion molecule-grabbing nonintegrin), complement-receptor 3 and Fcγ receptors was determined by flow cytometry. Dextran uptake by lupus and control dendritic cells was also assessed by flow cytometry. Serum IFNγ was quantified by ELISA, and uptake of microbial products was measured using fluorescently labeled zymosan. Results When compared with dendritic cells from healthy control individuals, unstimulated and stimulated lupus dendritic cells displayed significantly decreased dextran uptake and mannose receptor and dendritic cell-specific intercellular adhesion molecule-grabbing nonintegrin expression. Decreased expression of the mannose receptor was associated with high serum IFNγ levels, but not with maturation status or medications. Diminished dextran uptake and mannose receptor expression correlated with lupus disease activity. There were no differences between control and lupus dendritic cells in the expression of other pattern recognition receptors or in the capacity to uptake zymosan particles Conclusions Lupus dendritic cells have diminished endocytic capacity, which correlates with decreased mannose receptor expression. While this phenomenon appears primarily intrinsic to dendritic cells, modulation by serum factors such as IFNγ could play a role. These abnormalities may be relevant to the aberrant immune homeostasis and the increased susceptibility to infections described in lupus.http://deepblue.lib.umich.edu/bitstream/2027.42/112498/1/13075_2008_Article_2366.pd

Decadal analysis of the flatfish fishery of India

Decadal analysis of the flatfish fishery of Indi

Different types of X-ray bursts from GRS 1915+105 and their origin

We report the X-ray observations of the Galactic X-ray transient source GRS 1915+105 with the PPCs of the Indian X-ray Astronomy Experiment(IXAE) onboard the Indian satellite IRS-P3 during 1997 June - August, which have revealed the presence of four types of intense X-ray bursts. All the observed bursts have a slow exponential rise, a sharp linear decay, and they can broadly be put in two classes: irregular and quasi-regular bursts in one class, and regular bursts in another class. The regular bursts are found to have two distinct time scales and they persist over extended durations. There is a strong correlation between the preceding quiescent time and the burst duration for the quasi-regular and irregular bursts. No such correlation is found for the regular bursts. The ratio of average flux during the burst time to the average flux during the quiescent phase is high and variable for the quasi- regular and irregular bursts while it is low and constant for the regular bursts. We suggest that the peculiar bursts that we have seen are charact- eristic of the change of state of the source. The source can switch back and forth between the low-hard state and the high-soft state near critical accretion rates in a very short time scale. A test of the model is presented using the publicly available 13-60 keV RXTE/PCA data for irregular and regular bursts concurrent with our observations.Comment: 13 pages, 12 figures, Accepted in APJ, emulateapj style use

Computer-Aided Detection of Skin Cancer Detection from Lesion Images via Deep-Learning Techniques

More and more genetic and metabolic abnormalities are now known to cause cancer, which is typically fatal. Any particular body part may become infected by cancerous cells, which can be fatal. One of the most prevalent types of cancer is skin cancer, which is spreading worldwide.The primary subtypes of skin cancer are squamous and basal cell carcinomas, as well as melanoma, which is clinically aggressive and accounts for the majority of fatalities. Screening for skin cancer is so crucial.Deep Learning is one of the best options to quickly and precisely diagnose skin cancer (DL).This study used the Convolution Neural Network (CNN) deep learning technique to distinguish between the two primary types of cancers, malignant and benign, using the ISIC2018 dataset. The 3533 skin lesions in this dataset range from benign to malignant, and nonmelanocytic to melanocytic malignancies. The images were initially enhanced and edited using ESRGAN. The preprocessing stage involved resizing, normalising, and augmenting the images. By combining the results of numerous repetitions, the CNN approach might be used to categorise images of skin lesions. Several transfer learning models, such as Resnet50, InceptionV3, and Inception Resnet, were then used for fine-tuning. The uniqueness and contribution of this study are the preprocessing stages using ESRGAN and the testing of various models (including the intended CNN, Resnet50, InceptionV3, and Inception Resnet). Results from the model we developed matched those from the pretrained model exactly. The efficiency of the suggested strategy was proved by simulations using the ISIC 2018 skin lesion dataset. In terms of accuracy, the CNN model performed better than the Resnet50 (83.7%), InceptionV3 (85.8%), and Inception Resnet (84%) models

The role of aldosterone blockade in murine lupus nephritis

Abstract Background The purpose of this study was to examine the effect of aldosterone receptor blockade on the immunopathogenesis and progression of nephritis in the (NZB × NZW) F1 murine lupus model. Methods Female NZB/W F1 mice (11 weeks old) were treated daily with 25 or 50 mg/kg oral spironolactone or vehicle. Proteinuria, renal function, and serum autoantibody levels were monitored. Renal histopathology, immune complex deposition, and immunohistochemistry were analyzed at various time points. Targeted microarray analysis was performed on renal tissue, with subsequent real-time PCR analysis of several differentially expressed genes. Results Treatment with spironolactone was well tolerated by the mice throughout the course of their disease progression, with no significant differences in azotemia or serum potassium levels between vehicle-treated and spironolactone-treated animals. By 36 weeks of age, fewer spironolactone-treated mice developed nephrotic range proteinuria as compared with the control mice (control 70.8%, 25 mg/kg spironolactone 51.3%, and 50 mg/kg spironolactone 48.6%). Compared with control mice, mice treated with 25 mg/kg spironolactone had significantly lower serum anti-single-stranded DNA levels (2,042 μg/ml versus 1,036 μg/ml; P = 0.03) and anti-double-stranded DNA levels (3,433 μg/ml versus 614 μg/ml; P = 0.05). Spironolactone-treated mice exhibited decreased histopathologic evidence of inflammation and tissue damage, as compared with control mice. Additionally, spironolactone treatment resulted in decreased expression in the kidney of several inflammatory and proapoptotic genes, including those encoding interferon-γ, B lymphocyte stimulator (BlyS), tumor necrosis factor related apoptosis inducing ligand (TRAIL), tumor necrosis factor related weak inducer of apoptosis (TWEAK), and Fas ligand. Conclusion Aldosterone receptor blockade is safe and well tolerated in progressive murine lupus nephritis, and it results in decreased levels of clinical proteinuria, lower serum levels of autoantibodies, and decreased kidney damage. It appears to modulate inflammatory changes during the progression of glomerulonephritis and may also have a previously undescribed role in attenuating apoptosishttp://deepblue.lib.umich.edu/bitstream/2027.42/112839/1/13075_2007_Article_2203.pd

LOCATE: a mammalian protein subcellular localization database

LOCATE is a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of mouse and human proteins. Over the past 2 years, the data in LOCATE have grown substantially. The database now contains high-quality localization data for 20% of the mouse proteome and general localization annotation for nearly 36% of the mouse proteome. The proteome annotated in LOCATE is from the RIKEN FANTOM Consortium Isoform Protein Sequence sets which contains 58 128 mouse and 64 637 human protein isoforms. Other additions include computational subcellular localization predictions, automated computational classification of experimental localization image data, prediction of protein sorting signals and third party submission of literature data. Collectively, this database provides localization proteome for individual subcellular compartments that will underpin future systematic investigations of these regions. It is available at http://locate.imb.uq.edu.au