53 resultados para Lines of transmission
Resumo:
We consider the problem of Probably Ap-proximate Correct (PAC) learning of a bi-nary classifier from noisy labeled exam-ples acquired from multiple annotators(each characterized by a respective clas-sification noise rate). First, we consider the complete information scenario, where the learner knows the noise rates of all the annotators. For this scenario, we derive sample complexity bound for the Mini-mum Disagreement Algorithm (MDA) on the number of labeled examples to be ob-tained from each annotator. Next, we consider the incomplete information sce-nario, where each annotator is strategic and holds the respective noise rate as a private information. For this scenario, we design a cost optimal procurement auc-tion mechanism along the lines of Myer-son’s optimal auction design framework in a non-trivial manner. This mechanism satisfies incentive compatibility property,thereby facilitating the learner to elicit true noise rates of all the annotators.
Resumo:
We investigate nucleosynthesis inside the outflows from gamma-ray burst (GRB) accretion disks formed by the Type II collapsars. In these collapsars, massive stars undergo core collapse to form a proto-neutron star initially, and a mild supernova (SN) explosion is driven. The SN ejecta lack momentum, and subsequently this newly formed neutron star gets transformed to a stellar mass black hole via massive fallback. The hydrodynamics and the nucleosynthesis in these accretion disks have been studied extensively in the past. Several heavy elements are synthesized in the disk, and much of these heavy elements are ejected from the disk via winds and outflows. We study nucleosynthesis in the outflows launched from these disks by using an adiabatic, spherically expanding outflow model, to understand which of these elements thus synthesized in the disk survive in the outflow. While studying this, we find that many new elements like isotopes of titanium, copper, zinc, etc., are present in the outflows. Ni-56 is abundantly synthesized in most of the cases in the outflow, which implies that the outflows from these disks in a majority of cases will lead to an observable SN explosion. It is mainly present when outflow is considered from the He-rich, Ni-56/Fe-54-rich zones of the disks. However, outflow from the Si-rich zone of the disk remains rich in silicon. Although emission lines of many of these heavy elements have been observed in the X-ray afterglows of several GRBs by Chandra, BeppoSAX, XMM-Newton, etc., Swift seems to have not yet detected these lines.
Resumo:
Aim: The present study was conducted to overcome the disadvantages associated with the poor water solubility and low bioavailability of curcumin by synthesizing nanotized curcumin and demonstrating its efficacy in treating malaria. Materials and methods: Nanotized curcumin was prepared by a modified emulsion-diffusion-evaporation method and was characterized by means of transmission electron microscopy, atomic force microscopy, dynamic light scattering, Zetasizer, Fourier transform infrared spectroscopy, and differential thermal analysis. The novelty of the prepared nanoformulation lies in the fact that it was devoid of any polymeric matrices used in conventional carriers. The antimalarial efficacy of the prepared nanotized curcumin was then checked both in vitro and in vivo. Results: The nanopreparation was found to be non-toxic and had a particle size distribution of 20-50 nm along with improved aqueous dispersibility and an entrapment efficiency of 45%. Nanotized curcumin (half maximal inhibitory concentration IC50]: 0.5 mu M) was also found to be ten-fold more effective for growth inhibition of Plasmodium falciparum in vitro as compared to its native counterpart (IC50: 5 mu M). Oral bioavailability of nanotized curcumin was found to be superior to that of its native counterpart. Moreover, when Plasmodium berghei-infected mice were orally treated with nanotized curcumin, it prolonged their survival by more than 2 months with complete clearance of parasites in comparison to the untreated animals, which survived for 8 days only. Conclusion: Nanotized curcumin holds a considerable promise in therapeutics as demonstrated here for treating malaria as a test system.
Resumo:
In this report, we present cationic dimeric (gemini) lipids for significant plasmid DNA (pDNA) delivery to different cell lines without any marked toxicity in the presence of serum. Six gemini lipids based on alpha-tocopherol were synthesized, which differed in their spacer chain lengths. Each of these gemini lipids mixed with a helper lipid, 1,2-dioleoyl phosphatidyl ethanolamine (DOPE), was capable of forming stable aqueous suspensions. These co-liposomal systems were examined for their potential to transfect pEGFP-C3 plasmid DNA into nine cell lines of different origins. The transfection efficacies noticed in terms of EGFP expression levels using flow cytometry were well corroborated using independent fluorescence microscopy studies. Significant EGFP expression levels were reported using the gemini co-liposomes, which counted significantly better than one well known commercial formulation, Lipofectamine 2000 (L2 K). Transfection efficacies were also analyzed in terms of the degree of intracellular delivery of labeled plasmid DNA (pDNA) using confocal microscopy, which revealed an efficient internalization in the presence of serum. The cell viability assays performed using optimized formulations demonstrated no significant toxicity towards any of the cell lines used in the study. We also had a look at the lipoplex internalization pathway to profile the uptake characteristics. A caveolae/lipid raft route was attributed to their excellent gene transfection capabilities. The study was further advanced by using a therapeutic p53-EGFP-C3 plasmid and the apoptotic activity was observed using FACS and growth inhibition assay.
Resumo:
We propose a two-dimensional (2-D) multicomponent amplitude-modulation, frequency-modulation (AM-FM) model for a spectrogram patch corresponding to voiced speech, and develop a new demodulation algorithm to effectively separate the AM, which is related to the vocal tract response, and the carrier, which is related to the excitation. The demodulation algorithm is based on the Riesz transform and is developed along the lines of Hilbert-transform-based demodulation for 1-D AM-FM signals. We compare the performance of the Riesz transform technique with that of the sinusoidal demodulation technique on real speech data. Experimental results show that the Riesz-transform-based demodulation technique represents spectrogram patches accurately. The spectrograms reconstructed from the demodulated AM and carrier are inverted and the corresponding speech signal is synthesized. The signal-to-noise ratio (SNR) of the reconstructed speech signal, with respect to clean speech, was found to be 2 to 4 dB higher in case of the Riesz transform technique than the sinusoidal demodulation technique.
Resumo:
Although several factors have been suggested to contribute to thermostability, the stabilization strategies used by proteins are still enigmatic. Studies on a recombinant xylanase from Bacilllus sp. NG-27 (RBSX), which has the ubiquitous (beta/alpha)(8)-triosephosphate isomerase barrel fold, showed that just a single mutation, V1L, although not located in any secondary structural element, markedly enhanced the stability from 70 degrees C to 75 degrees C without loss of catalytic activity. Conversely, the V1A mutation at the same position decreased the stability of the enzyme from 70 degrees C to 68 degrees C. To gain structural insights into how a single extreme N-terminus mutation can markedly influence the thermostability of the enzyme, we determined the crystal structure of RBSX and the two mutants. On the basis of computational analysis of their crystal structures, including residue interaction networks, we established a link between N-terminal to C-terminal contacts and RBSX thermostability. Our study reveals that augmenting N-terminal to C-terminal noncovalent interactions is associated with enhancement of the stability of the enzyme. In addition, we discuss several lines of evidence supporting a connection between N-terminal to C-terminal noncovalent interactions and protein stability in different proteins. We propose that the strategy of mutations at the termini could be exploited with a view to modulate stability without compromising enzymatic activity, or in general, protein function in diverse folds where N and C termini are in close proximity. Database The coordinates of RBSX, V1A and V1L have been deposited in the PDB database under the accession numbers 4QCE, 4QCF, and 4QDM, respectively
Resumo:
(p) ppGpp, a secondary messenger, is induced under stress and shows pleiotropic response. It binds to RNA polymerase and regulates transcription in Escherichia coli. More than 25 years have passed since the first discovery was made on the direct interaction of ppGpp with E. coli RNA polymerase. Several lines of evidence suggest different modes of ppGpp binding to the enzyme. Earlier cross-linking experiments suggested that the beta-subunit of RNA polymerase is the preferred site for ppGpp, whereas recent crystallographic studies pinpoint the interface of beta'/omega-subunits as the site of action. With an aim to validate the binding domain and to follow whether tetra-and pentaphosphate guanosines have different location on RNA polymerase, this work was initiated. RNA polymerase was photo-labeled with 8-azido-ppGpp/8-azido-pppGpp, and the product was digested with trypsin and subjected to mass spectrometry analysis. We observed three new peptides in the trypsin digest of the RNA polymerase labeled with 8-azido-ppGpp, of which two peptides correspond to the same pocket on beta'-subunit as predicted by X-ray structural analysis, whereas the third peptide was mapped on the beta-subunit. In the case of 8-azido-pppGpp-labeled RNA polymerase, we have found only one cross-linked peptide from the beta'-subunit. However, we were unable to identify any binding site of pppGpp on the beta-subunit. Interestingly, we observed that pppGpp at high concentration competes out ppGpp bound to RNA polymerase more efficiently, whereas ppGpp cannot titrate out pppGpp. The competition between tetraphosphate guanosine and pentaphosphate guanosine for E. coli RNA polymerase was followed by gel-based assay as well as by a new method known as DRaCALA assay.
Resumo:
Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.