Identification of MHC Class II Binders/ Non-binders using Negative Selection Algorithm

The identification of major histocompatibility complex (MHC) class-II restricted peptides is an important goal in human immunological research leading to peptide based vaccine design. These MHC class–II peptides are predominantly recognized by CD4+ T-helper cells, which when turned on, have profound immune regulatory effects. Thus, prediction of such MHC class-II binding peptides is very helpful towards epitope-based vaccine design. HLA-DR proteins were found to be associated with autoimmune diseases e.g. HLA-DRB1*0401 with rheumatoid arthritis. It is important for the treatment of autoimmune diseases to determine which peptides bind to MHC class II molecules. The experimental methods for identification of these peptides are both time consuming and cost intensive. Therefore, computational methods have been found helpful in classifying these peptides as binders or non-binders. We have applied negative selection algorithm, an artificial immune system approach to predict MHC class–II binders and non-binders. For the evaluation of the NSA algorithm, five fold cross validation has been used and six MHC class–II alleles have been taken. The average area under ROC curve for HLA-DRB1*0301, DRB1*0401, DRB1*0701, DRB1*1101, DRB1*1501, DRB1*1301 have been found to be 0.75, 0.77, 0.71, 0.72, and 0.69, and 0.84 respectively indicating good predictive performance for the small training set

Teamwork delivers biotechnology products to Indian small-holder crop-livestock producers: Pearl millet hybrid “HHB 67 Improved” enters seed delivery pipeline

HHB 67, released in 1990 by CCS Haryana Agricultural University, is one such single-cross pearl millet hybrid. HHB 67 is highly popular because of its extra-early maturity (it needs less than 65 days from sowing to grain maturity) and is now grown on over 500 000 ha in Haryana and Rajasthan, India. Recent surveys have indicated that this hybrid is starting to succumb to downy mildew (DM; caused by the pseudo-fungus Sclerospora graminicola), showing up to 30% incidence in farmers' fields. By rapidly adopting hybrid "HHB 67 Improved", farmers in Haryana and Rajasthan can avoid grain production losses of Rs36 crores (US$8 million) which would be expected in the first year of a major DM outbreak on the original HHB 67

Benign external hydrocephalus: a review, with emphasis on management

Benign external hydrocephalus in infants, characterized by macrocephaly and typical neuroimaging findings, is considered as a self-limiting condition and is therefore rarely treated. This review concerns all aspects of this condition: etiology, neuroimaging, symptoms and clinical findings, treatment, and outcome, with emphasis on management. The review is based on a systematic search in the Pubmed and Web of Science databases. The search covered various forms of hydrocephalus, extracerebral fluid, and macrocephaly. Studies reporting small children with idiopathic external hydrocephalus were included, mostly focusing on the studies reporting a long-term outcome. A total of 147 studies are included, the majority however with a limited methodological quality. Several theories regarding pathophysiology and various symptoms, signs, and clinical findings underscore the heterogeneity of the condition. Neuroimaging is important in the differentiation between external hydrocephalus and similar conditions. A transient delay of psychomotor development is commonly seen during childhood. A long-term outcome is scarcely reported, and the results are varying. Although most children with external hydrocephalus seem to do well both initially and in the long term, a substantial number of patients show temporary or permanent psychomotor delay. To verify that this truly is a benign condition, we suggest that future research on external hydrocephalus should focus on the long-term effects of surgical treatment as opposed to conservative management

The First Data Release of the Sloan Digital Sky Survey

The Sloan Digital Sky Survey has validated and made publicly available its First Data Release. This consists of 2099 square degrees of five-band (u, g, r, i, z) imaging data, 186,240 spectra of galaxies, quasars, stars and calibrating blank sky patches selected over 1360 square degrees of this area, and tables of measured parameters from these data. The imaging data go to a depth of r ~ 22.6 and are photometrically and astrometrically calibrated to 2% rms and 100 milli-arcsec rms per coordinate, respectively. The spectra cover the range 3800--9200 A, with a resolution of 1800--2100. Further characteristics of the data are described, as are the data products themselves.Comment: Submitted to The Astronomical Journal. 16 pages. For associated documentation, see http://www.sdss.org/dr

ICAR: endoscopic skull‐base surgery

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Tiered-Service Fair Queueing (TSFQ): A Practical and Efficient Fair Queueing Algorithm

A router in today’s Internet has to satisfy two important properties in order to efficiently provide the Quality of Service (QoS) requested by the users. It should be fair among flows and also have low operational complexity. The packet scheduling techniques that have been proposed earlier do not have both these properties. Schedulers like Weighted Fair Queueing (WFQ) provide good fairness among flows but have high operational complexity. Schedulers like Weighted Round Robin (WRR) are efficient but provide poor fairness among flows. We propose a new packet scheduling technique, Tiered Service Fair Queueing (TSFQ), which is both fair and efficient. We achieve our goal by applying the concept of traffic quantization. A quantized network offers a small set of service levels (tiers), each with its own weight. Each flow is then mapped to one of the service levels so as to guarantee a QoS at least as good as that requested by the flow. We propose different versions of TSFQ, each with its own level of fairness. We present the complexity analysis of the TSFQ scheduler. Finally, we demonstrate through simulations on the TSFQ implementation on ns − 2, that TSFQ provides good fairness among flows