Marker-assisted Backcrossing for Identification of Salt Tolerant Rice Lines

SSR or microsatellite markers are proved to be ideal for making genetic maps, assisting selection and studying genetic diversity in germplasm. SSR markers are playing important role to identify gene for salt tolerance that can be helpful for plant breeders to develop new cultivars. The experiment was conducted during the period from July 2009 to November 2010 in the experimental field and Biotechnology Laboratory of Plant Breeding Division, Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh to identify salt tolerant rice line of BC1F1 progenies of Binadhan-5 x FL-478 using SSR markers. Salt tolerant genotype, FL-478 was crossed with high yielding variety, Binadhan-5. Randomly selected 40 BC1F1 progenies along with their two parents (Binadhan-5, FL-478 and F1) were genotyped with microsatellite or SSR markers for identification of salt tolerant rice lines. Parental polymorphism survey was assayed by 10 SSR markers and three polymorphic SSR markers viz., RM 336, RM 510, and RM 585 were selected to evaluate BC1F1 rice lines for salt tolerance. In respect of Primer RM 336, 11 lines were found as salt tolerant and 25 lines were heterozygous and 3 lines were susceptible. Primer RM 510 identified two tolerant, 14 heterozygous and 22 susceptible lines. And primer RM 585 identified 4 lines as tolerant and 35 lines as susceptible. Thus, these markers could be efficiently used in tagging salt tolerant genes, in marker-assisted selection and quantitative trait loci (QTL) mapping. The selected BC1F1 could be used for developing BC2F1 and BC2F2 and mapping genes for salinity tolerance. DOI: http://dx.doi.org/10.3329/ijarit.v2i2.14008 Int. J. Agril. Res. Innov. & Tech. 2 (2): 1-8, December, 201

Medullary carcinoma of the breast: Role of contrast-enhanced MRI in the diagnosis of multiple breast lesions

Medullary carcinoma is a rare breast carcinoma with a syncytial growth pattern and high-grade cytology. It can be difficult to diagnose and may be missed on conventional imaging as the findings may overlap with benign lesions i.e. fibroadenomas. The authors report a case of a 25-year-old female who presented with multifocal breast lumps diagnosed with medullary carcinoma and fibroadenomas. Imaging and pathological correlation with contrast-enhanced MRI are presented in the diagnosis of these lesions

NPI-0052 and γ-radiation induce a synergistic apoptotic effect in medulloblastoma

Medulloblastoma (MB) is the most common malignant solid paediatric brain tumour. The standard treatment for MB is surgical resection of the tumour, radiation and chemotherapy. This therapy is associated with high morbidity and adverse side effects. Hence, more targeted and less toxic therapies are vitally needed to improve the quality of life of survivors. NPI-0052 is a novel proteasome inhibitor that irreversibly binds the 20S proteasome subunit. This compound has anti-tumour activity in metastatic solid tumours, glioblastoma and multiple myeloma with a good safety profile. Importantly, NPI-0052 has a lipophilic structure and can penetrate the blood-brain barrier, making it a suitable treatment for brain tumours. In the present study, we performed an in silico gene expression analysis to evaluate the proteasome subunit expression in MB. To evaluate the anticancer activity of NPI-0052, we used a range of MB patient-derived MB cells and cell lines. The synergistic cell death of NPI-0052 with γ-radiation was evaluated in tumour organoids derived from patient-derived MB cells. We show that high expression of proteasome subunits is a poor prognostic factor for MB patients. Also, our preclinical work demonstrated that NPI-0052 can inhibit proteasome activity and activate apoptosis in MB cells. Moreover, we observe that NPI-0052 has a synergistic apoptotic effect with γ-radiation, a component of the current MB therapy. Here, we present compelling preclinical evidence that NPI-0052 can be used as an adjuvant treatment for p53-family-expressing MB tumours

Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning

Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks

Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning

Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks

Hemoglobin E syndromes in Pakistani population

<p>Abstract</p> <p>Background</p> <p>Hemoglobin E is an important hemoglobin variant with a worldwide distribution. A number of hemoglobinopathies have been reported from Pakistan. However a comprehensive description of hemoglobin E syndromes for the country was never made. This study aimed to describe various hemoglobin E disorders based on hematological parameters and chromatography. The sub-aim was to characterize hemoglobin E at molecular level.</p> <p>Methods</p> <p>This was a hospital based study conducted prospectively for a period of one year extending from January 1 to December 31, 2008. EDTA blood samples were analyzed for completed blood counts and hemoglobin variants through automated hematology analyzer and Bio-Rad beta thalassaemia short program respectively. Six samples were randomly selected to characterize HbE at molecular level through RFLP-PCR utilizing <it>Mnl</it>I restriction enzyme.</p> <p>Results</p> <p>During the study period, 11403 chromatograms were analyzed and Hb E was detected in 41 (or 0.36%) samples. Different hemoglobin E syndromes identified were HbEA (n = 20 or 49%), HbE/β-thalassemia (n = 14 or 34%), HbEE (n = 6 or 15%) and HbE/HbS (n = 1 or 2%). Compound heterozygosity for HbE and beta thalassaemia was found to be the most severely affected phenotype. RFLP-PCR utilizing <it>Mnl</it>I successfully characterized HbE at molecular level in six randomly selected samples.</p> <p>Conclusions</p> <p>Various HbE phenotypes are prevalent in Pakistan with HbEA and HbE/β thalassaemia representing the most common syndromes. Chromatography cannot only successfully identify hemoglobin E but also assist in further characterization into its phenotype including compound heterozygosity. Definitive diagnosis of HbE can easily be achieved through RFLP-PCR.</p

Are we failing to protect threatened mangroves in the Sundarbans world heritage ecosystem?

The Sundarbans, the largest mangrove ecosystem in the world, is under threat from historical and future human exploitation and sea level rise. Limited scientific knowledge on the spatial ecology of the mangroves in this world heritage ecosystem has been a major impediment to conservation efforts. Here, for the first time, we report on habitat suitability analyses and spatial density maps for the four most prominent mangrove species - Heritiera fomes, Excoecaria agallocha, Ceriops decandra and Xylocarpus mekongensis. Globally endangered H. fomes abundances declined as salinity increased. Responses to nutrients, elevation, and stem density varied between species. H. fomes and X. mekongensis preferred upstream habitats. E. agallocha and C. decandra preferred down-stream and mid-stream habitats. Historical harvesting had negative influences on H. fomes, C. decandra and X. mekongensis abundances. The established protected area network does not support the most suitable habitats of these threatened species. We therefore recommend a reconfiguration of the network to include these suitable habitats and ensure their immediate protection. These novel habitat insights and spatial predictions can form the basis for future forest studies and spatial conservation planning, and have implications for more effective conservation of the Sundarbans mangroves and the many other species that rely on them

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente