Electrophoretic Study of d-Block Metal Ions on Plain and Tri-n-Butylamine (TBA) Impregnated Titanium (IV) Tungstate Layers

RPTLE of ninteen d block metal ion studied on TBA impregnated titanium(IV)tungstate layer in nine solvent system among them three are complex forming acids OA,TA, CA to study the effect of complexation on migration. Electrophoretic migration also correlated with Ionc potential,Kd of metal ions and Ka of acids,pH of electrolytes.The spots are well defined in RPTLE and Mi is positiv

Xpert MTB/RIF - why the lack of morbidity and mortality impact in intervention trials?

: Compared with smear microscopy, the Xpert MTB/RIF assay (Xpert), with superior accuracy and capacity to diagnose rifampicin resistance, has advanced TB diagnostic capability. However, recent trials of Xpert impact have not demonstrated reductions in patient morbidity and mortality. We conducted a narrative review of Xpert impact trials to summarize which patient-relevant outcomes Xpert has improved and explore reasons for no observed morbidity or mortality reductions. We searched PubMed, Google Scholar, Cochrane Library and Embase and identified eight trials meeting inclusion criteria: three individually randomized, three cluster-randomized, and two pre-post trials. In six trials Xpert increased diagnostic yield of bacteriologically-confirmed TB from sputa and in four trials Xpert shortened time to TB treatment. However, all-cause mortality was similar between arms in all six trials reporting this outcome, and the only trial to assess Xpert impact on morbidity reported no impact. Trial characteristics that might explain lack of observed impact on morbidity and mortality include: higher rates of empiric TB treatment in microscopy compared with Xpert arms, enrollment of study populations not comprised exclusively of populations most likely to benefit from Xpert, and health system weaknesses. So far as equipoise exists, future trials that address past limitations are needed to inform Xpert use in resource-limited settings.<br/

Motion Deblurring in the Wild

The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object. Due to the complexity of the general image model we propose a novel convolutional network architecture which directly generates the sharp image.This network is built in three stages, and exploits the benefits of pyramid schemes often used in blind deconvolution. One of the main difficulties in training such a network is to design a suitable dataset. While useful data can be obtained by synthetically blurring a collection of images, more realistic data must be collected in the wild. To obtain such data we use a high frame rate video camera and keep one frame as the sharp image and frame average as the corresponding blurred image. We show that this realistic dataset is key in achieving state-of-the-art performance and dealing with occlusions

Optimum sowing dates for soybean in Central India using CROPGRO and ClimProb symbiosis

The optimum sowing dates for soybean cv. Gaurav were derived for Jabalpur, Raipur and Gwalior in the state of Madhya Pradesh in central India. Dates were derived based on two strategies: (a) probabilities of rainfall and temperature events using ClimProb, a PC based software package, and (b) the CROPGRO Soybean v3.0 crop growth simulation model. In Madhya Pradesh, the optimum sowing dates for multiple cropping, with the first crop as soybean under rainfed conditions, are between weeks 25 and 27, while the optimum sowing dates for rainfed mono-cropping are between weeks 28 and 29

Predicting the long-term impact of antiretroviral therapy scale-up on population incidence of tuberculosis.

OBJECTIVE: To investigate the impact of antiretroviral therapy (ART) on long-term population-level tuberculosis disease (TB) incidence in sub-Saharan Africa. METHODS: We used a mathematical model to consider the effect of different assumptions about life expectancy and TB risk during long-term ART under alternative scenarios for trends in population HIV incidence and ART coverage. RESULTS: All the scenarios we explored predicted that the widespread introduction of ART would initially reduce population-level TB incidence. However, many modelled scenarios projected a rebound in population-level TB incidence after around 20 years. This rebound was predicted to exceed the TB incidence present before ART scale-up if decreases in HIV incidence during the same period were not sufficiently rapid or if the protective effect of ART on TB was not sustained. Nevertheless, most scenarios predicted a reduction in the cumulative TB incidence when accompanied by a relative decline in HIV incidence of more than 10% each year. CONCLUSIONS: Despite short-term benefits of ART scale-up on population TB incidence in sub-Saharan Africa, longer-term projections raise the possibility of a rebound in TB incidence. This highlights the importance of sustaining good adherence and immunologic response to ART and, crucially, the need for effective HIV preventive interventions, including early widespread implementation of ART

Tuberculosis Incidence Rates during 8 Years of Follow-Up of an Antiretroviral Treatment Cohort in South Africa: Comparison with Rates in the Community

BACKGROUND: Although antiretroviral therapy (ART) is known to be associated with time-dependent reductions in tuberculosis (TB) incidence, the long-term impact of ART on incidence remains imprecisely defined due to limited duration of follow-up and incomplete CD4 cell count recovery in existing studies. We determined TB incidence in a South African ART cohort with up to 8 years of follow-up and stratified rates according to CD4 cell count recovery. We compared these rates with those of HIV-uninfected individuals living in the same community. METHODOLOGY/PRINCIPAL FINDINGS: Prospectively collected clinical data on patients receiving ART in a community-based cohort in Cape Town were analysed. 1544 patients with a median follow-up of 5.0 years (IQR 2.4-5.8) were included in the analysis. 484 episodes of incident TB (73.6% culture-confirmed) were diagnosed in 424 patients during 6506 person-years (PYs) of follow-up. The TB incidence rate during the first year of ART was 12.4 (95% CI 10.8-14.4) cases/100PYs and decreased to 4.92 (95% CI 3.64-8.62) cases/100PYs between 5 and 8 years of ART. During person-time accrued within CD4 cell strata 0-100, 101-200, 201-300, 301-400, 401-500, 501-700 and ≥700 cells/µL, TB incidence rates (95% CI) were 25.5 (21.6-30.3), 11.2 (9.4-13.5), 7.9 (6.4-9.7), 5.0 (3.9-6.6), 5.1 (3.8-6.8), 4.1 (3.1-5.4) and 2.7 (1.7-4.5) cases/100PYs, respectively. Overall, 75% (95% CI 70.9-78.8) of TB episodes were recurrent cases. Updated CD4 cell count and viral load measurements were independently associated with long-term TB risk. TB rates during person-time accrued in the highest CD4 cell count stratum (>700 cells/µL) were 4.4-fold higher that the rate in HIV uninfected individuals living in the same community (2.7 versus 0.62 cases/100PYs; 95%CI 0.58-0.65). CONCLUSIONS/SIGNIFICANCE: TB rates during long-term ART remained substantially greater than rates in the local HIV uninfected populations regardless of duration of ART or attainment of CD4 cell counts exceeding 700 cells/µL

Histone deacetylase adaptation in single ventricle heart disease and a young animal model of right ventricular hypertrophy.

BackgroundHistone deacetylase (HDAC) inhibitors are promising therapeutics for various forms of cardiac diseases. The purpose of this study was to assess cardiac HDAC catalytic activity and expression in children with single ventricle (SV) heart disease of right ventricular morphology, as well as in a rodent model of right ventricular hypertrophy (RVH).MethodsHomogenates of right ventricle (RV) explants from non-failing controls and children born with a SV were assayed for HDAC catalytic activity and HDAC isoform expression. Postnatal 1-day-old rat pups were placed in hypoxic conditions, and echocardiographic analysis, gene expression, HDAC catalytic activity, and isoform expression studies of the RV were performed.ResultsClass I, IIa, and IIb HDAC catalytic activity and protein expression were elevated in the hearts of children born with a SV. Hypoxic neonatal rats demonstrated RVH, abnormal gene expression, elevated class I and class IIb HDAC catalytic activity, and protein expression in the RV compared with those in the control.ConclusionsThese data suggest that myocardial HDAC adaptations occur in the SV heart and could represent a novel therapeutic target. Although further characterization of the hypoxic neonatal rat is needed, this animal model may be suitable for preclinical investigations of pediatric RV disease and could serve as a useful model for future mechanistic studies

Can ground truth label propagation from video help semantic segmentation?

For state-of-the-art semantic segmentation task, training convolutional neural networks (CNNs) requires dense pixelwise ground truth (GT) labeling, which is expensive and involves extensive human effort. In this work, we study the possibility of using auxiliary ground truth, so-called \textit{pseudo ground truth} (PGT) to improve the performance. The PGT is obtained by propagating the labels of a GT frame to its subsequent frames in the video using a simple CRF-based, cue integration framework. Our main contribution is to demonstrate the use of noisy PGT along with GT to improve the performance of a CNN. We perform a systematic analysis to find the right kind of PGT that needs to be added along with the GT for training a CNN. In this regard, we explore three aspects of PGT which influence the learning of a CNN: i) the PGT labeling has to be of good quality; ii) the PGT images have to be different compared to the GT images; iii) the PGT has to be trusted differently than GT. We conclude that PGT which is diverse from GT images and has good quality of labeling can indeed help improve the performance of a CNN. Also, when PGT is multiple folds larger than GT, weighing down the trust on PGT helps in improving the accuracy. Finally, We show that using PGT along with GT, the performance of Fully Convolutional Network (FCN) on Camvid data is increased by $2.7\%$ on IoU accuracy. We believe such an approach can be used to train CNNs for semantic video segmentation where sequentially labeled image frames are needed. To this end, we provide recommendations for using PGT strategically for semantic segmentation and hence bypass the need for extensive human efforts in labeling.Comment: To appear at ECCV 2016 Workshop on Video Segmentatio