Multiple Abiotic Stresses Applied Simultaneously Elicit Distinct Responses in Two Contrasting Rice Cultivars

Rice crops are often subject to multiple abiotic stresses simultaneously in both natural and cultivated environments, resulting in yield reductions beyond those expected from single stress. We report physiological changes after a 4 day exposure to combined drought, salt and extreme temperature treatments, following a 2 day salinity pre-treatment in two rice genotypes—Nipponbare (a paddy rice) and IAC1131 (an upland landrace). Stomata closed after two days of combined stresses, causing intercellular CO2 concentrations and assimilation rates to diminish rapidly. Abscisic acid (ABA) levels increased at least five-fold but did not differ significantly between the genotypes. Tandem Mass Tag isotopic labelling quantitative proteomics revealed 6215 reproducibly identified proteins in mature leaves across the two genotypes and three time points (0, 2 and 4 days of stress). Of these, 987 were differentially expressed due to stress (cf. control plants), including 41 proteins that changed significantly in abundance in all stressed plants. Heat shock proteins, late embryogenesis abundant proteins and photosynthesis-related proteins were consistently responsive to stress in both Nipponbare and IAC1131. Remarkably, even after 2 days of stress there were almost six times fewer proteins differentially expressed in IAC1131 than Nipponbare. This contrast in the translational response to multiple stresses is consistent with the known tolerance of IAC1131 to dryland conditions.     

Atomistic insights into solvation dynamics and conformational transformation in thermo-sensitive and non-thermo-sensitive oligomers

Solvation dynamics and conformational transformation in oligomers with varying degree of temperature sensitivity is studied using molecular dynamics (MD) simulations. Conformational transformation in three model systems namely poly(N-isopropylacrylamide) (PNIPAM), poly(acrylamide) (PAA), and poly(ethylene glycol) (PEG) are compared and contrasted to understand the origin of a coil-to-globule transformations across the lower critical solution temperature (LCST) in thermo-sensitive oligomers. PNIPAM, PAA, and PEG are water-soluble oligomers. However, for the temperature range used in these simulations, PNIPAM shows an LCST whereas PAA and PEG are non-thermo-sensitive. Oligomers of PNIPAM, PAA, and PEG consisting of 30 monomer units (30-mer) each were simulated at 5 °C (278 K) and 37 °C (310 K). Conformational transformations in the oligomers are evaluated using structural and dynamical correlation functions such as radius of gyration, radial distribution function, residence time probabilities and hydrogen-bonding life-times. Our simulations suggest that the solubility, solvation dynamics, and conformation of the oligomers are dictated by two factors: (a) the local structure of proximal water and (b) the diffusion and exchange kinetics of proximal water with bulk water. In thermo-sensitive oligomer such as PNIPAM, we find that the coil-to-globule transition is closely related to the local ordering and solvation dynamics of PNIPAM. We have identified stable configurations of proximal water molecules for an oligomer undergoing conformational transition. The slow diffusional properties of proximal water molecules near PNIPAM oligomers suggests that water forms a stable network near hydrophilic groups of PNIPAM as compared to the hydrophilic groups of PAA and PEG. Thermal perturbation of this solvated structure results in significant reduction in local ordering of water, which contributes to the globular collapse and the reduced solubility of PNIPAM above its LCST. On the other hand, non-thermo-sensitive oligomers such as PAA and PEG are characterized by much faster diffusion and exchange kinetics of proximal water at the two simulated temperatures compared to PNIPAM. This faster exchange kinetics helps in maintaining higher hydration level of the oligomers and is responsible for the apparent hydrophilic character and thereby the observed solubility at the two simulated temperatures.     

Simultaneous segmentation of prostatic zones using Active Appearance Models with multiple coupled levelsets

In this work we present an improvement to the popular Active Appearance Model (AAM) algorithm, that we call the Multiple-Levelset AAM (MLA). The MLA can simultaneously segment multiple objects, and makes use of multiple levelsets, rather than anatomical landmarks, to define the shapes. AAMs traditionally define the shape of each object using a set of anatomical landmarks. However, landmarks can be difficult to identify, and AAMs traditionally only allow for segmentation of a single object of interest. The MLA, which is a landmark independent AAM, allows for levelsets of multiple objects to be determined and allows for them to be coupled with image intensities. This gives the MLA the flexibility to simulataneously segmentation multiple objects of interest in a new image.In this work we apply the MLA to segment the prostate capsule, the prostate peripheral zone (PZ), and the prostate central gland (CG), from a set of 40 endorectal, T2-weighted MRI images. The MLA system we employ in this work leverages a hierarchical segmentation framework, so constructed as to exploit domain specific attributes, by utilizing a given prostate segmentation to help drive the segmentations of the CG and PZ, which are embedded within the prostate. Our coupled MLA scheme yielded mean Dice accuracy values of .81, .79 and .68 for the prostate, CG, and PZ, respectively using a leave-one-out cross validation scheme over 40 patient studies. When only considering the midgland of the prostate, the mean DSC values were .89, .84, and .76 for the prostate, CG, and PZ respectively.     

Long‐Range Nanoparticle Surface‐Energy‐Transfer Ruler for Monitoring Photothermal Therapy Response

A recent gold nanotechnology‐driven approach opens up a new possibility for the destruction of cancer cells through photothermal therapy. Ultimately, photothermal therapy may enter into clinical therapy and, as a result, there is an urgent need for techniques to monitor the tumor response to therapy. Driven by this need, a nanoparticle surface‐energy‐transfer (NSET) approach to monitor the photothermal therapy process by measuring a simple fluorescence intensity change is reported. The fluorescence intensity change is due to the light‐controlled photothermal release of single‐stranded DNA/RNA via dehybridization during the therapy process. Time‐dependent results show that just by measuring the fluorescence intensity change, the photothermal therapy response during the therapy process can be monitored. The possible mechanism and operating principle of the NSET assay are discussed. Ultimately, this NSET assay could have enormous potential applications in rapid, on‐site monitoring of the photothermal therapy process, which is critical to providing effective treatment of cancer and multidrug‐resistant bacterial infections.     

Perturbation-Based Eigenvector Updates for On-Line Principal Components Analysis and Canonical Correlation Analysis

Principal components analysis is an important and well-studied subject in statistics and signal processing. Several algorithms for solving this problem exist, and could be mostly grouped into one of the following three approaches: adaptation based on Hebbian updates and deflation, optimization of a second order statistical criterion (like reconstruction error or output variance), and fixed point update rules with deflation. In this study, we propose an alternate approach that avoids deflation and gradient-search techniques. The proposed method is an on-line procedure based on recursively updating the eigenvector and eigenvalue matrices with every new sample such that the estimates approximately track their true values as would be calculated analytically from the current sample estimate of the data covariance matrix. The perturbation technique is theoretically shown to be applicable for recursive canonical correlation analysis, as well. The performance of this algorithm is compared with that of a structurally similar matrix perturbation-based method and also with a few other traditional methods like Sanger’s rule and APEX.

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Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions

Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality in women. In the last decade, ultrasound along with digital mammography has come to be regarded as the gold standard for breast cancer diagnosis. Automatically detecting tumors and extracting lesion boundaries in ultrasound images is difficult due to their specular nature and the variance in shape and appearance of sonographic lesions. Past work on automated ultrasonic breast lesion segmentation has not addressed important issues such as shadowing artifacts or dealing with similar tumor like structures in the sonogram. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. In this paper, we present a novel technique to automatically find lesion margins in ultrasound images, by combining intensity and texture with empirical domain specific knowledge along with directional gradient and a deformable shape-based model. The images are first filtered to remove speckle noise and then contrast enhanced to emphasize the tumor regions. For the first time, a mathematical formulation of the empirical rules used by radiologists in detecting ultrasonic breast lesions, popularly known as the "Stavros Criteria" is presented in this paper. We have applied this formulation to automatically determine a seed point within the image. Probabilistic classification of image pixels based on intensity and texture is followed by region growing using the automatically determined seed point to obtain an initial segmentation of the lesion. Boundary points are found on the directional gradient of the image. Outliers are removed by a process of recursive refinement. These boundary points are then supplied as an initial estimate to a deformable model. Incorporating empirical domain specific knowledge along with low and high-level knowledge makes it possible to avoid shadowing artifacts and lowers the chance of confusing similar tumor like structures for the lesion. The system was validated on a database of breast sonograms for 42 patients. The average mean boundary error between manual and automated segmentation was 6.6 pixels and the normalized true positive area overlap was 75.1%. The algorithm was found to be robust to 1) variations in system parameters, 2) number of training samples used, and 3) the position of the seed point within the tumor. Running time for segmenting a single sonogram was 18 s on a 1.8-GHz Pentium machine.     

Characterization and quantitation of aprepitant drug substance polymorphs by attenuated total reflectance fourier transform infrared spectroscopy

In this study, we report the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) for the identification and quantitation of two polymorphs of Aprepitant, a substance P antagonist for chemotherapy-induced emesis. Mixtures of the polymorph pair were prepared by weight and ATR-FT-IR spectra of the powdered samples were obtained over the wavelength range of 700-1500 cm(-1). Significant spectral differences between the two polymorphs at 1140 cm(-1) show that ATR-FT-IR can provide definitive identification of the polymorphs. To investigate the feasibility of ATR-FT-IR for quantitation of polymorphic forms of Aprepitant, a calibration plot was constructed with known mixtures of the two polymorphs by plotting the peak ratio of the second derivative of absorbance spectra against the weight percent of form II in the polymorphic mixture. Using this novel approach, 3 wt % of one crystal form could be detected in mixtures of the two polymorphs. The accuracy of ATR-FT-IR in determining polymorph purity of the drug substance was tested by comparing the results with those obtained by X-ray powder diffractometry (XRPD). Indeed, polymorphic purity results obtained by ATR-FT-IR were found to be in good agreement with the predictions made by XRPD and compared favorably with actual values in the known mixtures. The present study clearly demonstrates the potential of ATR-FT-IR as a quick, easy, and inexpensive alternative to XRPD for the determination of polymorphic identity and purity of solid drug substances. The technique is ideally suited for polymorph analysis, because it is precise, accurate, and requires minimal sample preparation.     

An integrated region-, boundary-, shape-based active contour for multiple object overlap resolution in histological imagery

Active contours and active shape models (ASM) have been widely employed in image segmentation. A major limitation of active contours, however, is in their 1) inability to resolve boundaries of intersecting objects and to 2) handle occlusion. Multiple overlapping objects are typically segmented out as a single object. On the other hand, ASMs are limited by point correspondence issues since object landmarks need to be identified across multiple objects for initial object alignment. ASMs are also are constrained in that they can usually only segment a single object in an image. In this paper, we present a novel synergistic boundary and region-based active contour model that incorporates shape priors in a level set formulation with automated initialization based on watershed. We demonstrate an application of these synergistic active contour models using multiple level sets to segment nuclear and glandular structures on digitized histopathology images of breast and prostate biopsy specimens. Unlike previous related approaches, our model is able to resolve object overlap and separate occluded boundaries of multiple objects simultaneously. The energy functional of the active contour is comprised of three terms. The first term is the prior shape term, modeled on the object of interest, thereby constraining the deformation achievable by the active contour. The second term, a boundary-based term detects object boundaries from image gradients. The third term drives the shape prior and the contour towards the object boundary based on region statistics. The results of qualitative and quantitative evaluation on 100 prostate and 14 breast cancer histology images for the task of detecting and segmenting nuclei and lymphocytes reveals that the model easily outperforms two state of the art segmentation schemes (geodesic active contour and Rousson shape-based model) and on average is able to resolve up to 91% of overlapping/occluded structures in the images.     

Effect of Heat Processing on IgE Reactivity and Cross‐Reactivity of Tropomyosin and Other Allergens of Asia‐Pacific Mollusc Species: Identification of Novel Sydney Rock Oyster Tropomyosin Sac g 1

1 Scope

Shellfish allergy is an increasing global health priority, frequently affecting adults. Molluscs are an important shellfish group causing food allergy but knowledge of their allergens and cross‐reactivity is limited. Optimal diagnosis of mollusc allergy enabling accurate advice on food avoidance is difficult. Allergens of four frequently ingested Asia‐Pacific molluscs are characterized: Sydney rock oyster (Saccostrea glomerata), blue mussel (Mytilus edulis), saucer scallop (Amusium balloti), and southern calamari (Sepioteuthis australis), examining cross‐reactivity between species and with blue swimmer crab tropomyosin, Por p 1.

2 Methods and results

IgE ELISA showed that cooking increased IgE reactivity of mollusc extracts and basophil activation confirmed biologically relevant IgE reactivity. Immunoblotting demonstrated strong IgE reactivity of several proteins including one corresponding to heat‐stable tropomyosin in all species (37–40 kDa). IgE‐reactive Sydney rock oyster proteins were identified by mass spectrometry, and the novel major oyster tropomyosin allergen was cloned, sequenced, and designated Sac g 1 by the IUIS. Oyster extracts showed highest IgE cross‐reactivity with other molluscs, while mussel cross‐reactivity was weakest. Inhibition immunoblotting demonstrated high cross‐reactivity between tropomyosins of mollusc and crustacean species.

3 Conclusion

These findings inform novel approaches for reliable diagnosis and improved management of mollusc allergy.