Studies on the transmission of WSSV (white spot syndrome virus) in juvenile Marsupenaeus japonicus via marine microalgae

We studied the possible role that marine microalgae may play during the outbreaks of WSS (white spot syndrome). In order to elucidate the possibility of marine microalgae carrying WSSV (white spot syndrome virus), six marine microallgae (Isochr.vsis galbana, Skeletonema costatum, Chlorella sp., Heterosigma akashiwo, Scrippsiella trochoidea, Dunaliella salina) were co-cultured with adult Marsupenaeus japollicus infected with WSSV and were assayed daily by nested-PCR to study whether they could carry WSSV. Further experiments were conducted to investigate whether the virus carried by microalgae could re-infect juvenile M. japonicus. Results showed that all of the experimental microalgae, except H. akashiwo could carry WSSV, and among them, Chlorella sp. and S. trochoidea had the strongest WSSV-carrying ability. Unlike other invertebrate carriers of WSSV, the WSSV detections in microalgae, which were positive after I and 3 days, were negative after 10 days of incubation. WSSV detection results in juvenile M. japonicus showed that the juvenile shrimp were re-infected by co-cultured Chlorella sp., although the juvenile M. japonicus carried so small an amount of WSSV that it could only be detected by nested-PCR. The results of this experiment suggest that microalgae might be one possible horizontal transmission pathway for WSSV. Further research, however, is required to better understand the factors behind the different carrying abilities and virus-carrying mechanisms of different microalgae. (c) 2007 Elsevier Inc. All rights reserved.

Studies on nitric oxide synthase activity in haemocytes of shrimps Fenneropenaeus chinensis and Marsupenaeus japonicus after white spot syndrome virus infection

The nitric oxide synthase (NOS) activity in the haemocytes of shrimps Fenneropenaeus chinensis (Osbeck) and Marsupenaeus japonicus (Bate) was Studied after white spot syndrome virus (WSSV) infection to determine its characteristics in response to virus infection. First, the NOS activity in haemocytes of shrimps was determined by the means of NBT reduction and changes in cell conformation. And the variations of NOS activity in shrimps after challenge with WSSV intramuscularly were evaluated through the analysis Of L-citrulline and total nitrite/nitrate (both as NO derivates) concentrations. The result showed that NOS activity in the haemocytes of F chinensis increased slightly from 0 to 12 h postchallenge, indicated by the variations Of L-Citrulline (from 11.15 +/- 0.10 to 12.08 +/- 0.64 mu M) and total nitrite/nitrate concentrations (from 10.45 +/- 0.65 to 12.67 +/- 0.52 mu M). Then it decreased sharply till the end of the experiment (84 h postchallenge), the concentrations Of L-Citrulline and total nitrite/nitrate at 84 It were 1.58 +/- 0.24 and 2.69 +/- 0.70 mu M, respectively. The LPS-stimulated NOS activity kept constant during the experiment. However, in M. japonicus, the NOS activity kept increasing during the first 72 It postchallenge, the concentrations Of L-Citrulline and total nitrite/nitrate increased from 7.82 +/- 0.77 at 0 h to 10.79 +/- 0.50 mu M at 72 h, and from 8.98 +/- 0.43 at 0 h to 11.20 +/- 0.37 mu M at 72 h, respectively. Then it decreased till the end of the experiment (216 h postchallenge), and the concentrations of L-Citrulline and total nitrite/nitrate at 216 h were 5.66 +/- 0.27 and 4.68 +/- 0.16 mu M, respectively. More importantly, an apparent increase of I-PS-stimulated NOS activity was observed in M japonicus at 48 h postchallenge, which was about 4 times higher than that in the control group of health shrimps. In correspondence with the difference of NOS activity between the two species of shrimps, the Cumulative mortalities of the shrimps were also different. All shrimps of F. chinensis in the mortality experiment died in 66 h, much more quickly than M. japonicus, Whose accumulative mortality reached 100% after 240 h. Data here reported let us hypothesize that NOS activity in the haemocytes of shrimps F chinensis and M. japonicus responses to WSSV infection differently, and this might be one of the reasons for the different susceptibility of F chinensis and M. japonicus to WSSV infection. (c) 2005 Elsevier Inc. All rights reserved.

The effect of acute salinity change on white spot syndrome (WSS) outbreaks in Fenneropenaeus chinensis

In order to observe the effect of salinity on disease resistance and white spot syndrome virus (WSSV) proliferation in Fenneropenaeus chinensis, shrimps with latent WSSV were subjected to two acute salinity changes from the original salinity of 22 ppt to 18 and 14 ppt in an hour, respectively. The total haemocyte count (THC) of the challenged group showed no evident change under salinity adjustments, but the phenoloxidase (PO) index declined significantly (P<0.05) corresponding to continuing acute salinity changes from the 24th to the 72nd hour. According to the WSSV load detected by quantitative real-time PCR method, it was found that WSSV carried by the challenged group and control group were significantly different (P<0.05); acute salinity change from 22 to 14 ppt led to the WSSV carried in the challenged group being significantly higher (P<0.05) than that of those surviving in 22 ppt, but salinity change from 22 to 18 ppt had no such effect. At the end of the 72-h experiment, the challenged group subjected to salinity change from 22 to 14 ppt had nearly 3 times the WSSV load as the control group with no salinity change. Therefore, salinity changes over a particular range could result in a decrease of immunocompetence and obvious WSSV proliferation in the shrimps, leading to white spot syndrome developing from a latent infection to an acute outbreak. (C) 2005 Elsevier B.V All rights reserved.

Tan spot disease of wheat: race characterization.

2007

On the Relationship Between File Sizes, Transport Protocols, and Self-Similar Network Traffic

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits variability at a wide range of scales self-similarity. In this paper, we examine a mechanism that gives rise to self-similar network traffic and present some of its performance implications. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. We examine its effects through detailed transport-level simulations of multiple TCP streams in an internetwork. First, we show that in a "realistic" client/server network environment i.e., one with bounded resources and coupling among traffic sources competing for resources the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. We show that this causal relationship is not significantly affected by changes in network resources (bottleneck bandwidth and buffer capacity), network topology, the influence of cross-traffic, or the distribution of interarrival times. Second, we show that properties of the transport layer play an important role in preserving and modulating this relationship. In particular, the reliable transmission and flow control mechanisms of TCP (Reno, Tahoe, or Vegas) serve to maintain the long-range dependency structure induced by heavy-tailed file size distributions. In contrast, if a non-flow-controlled and unreliable (UDP-based) transport protocol is used, the resulting traffic shows little self-similar characteristics: although still bursty at short time scales, it has little long-range dependence. If flow-controlled, unreliable transport is employed, the degree of traffic self-similarity is positively correlated with the degree of throttling at the source. Third, in exploring the relationship between file sizes, transport protocols, and self-similarity, we are also able to show some of the performance implications of self-similarity. We present data on the relationship between traffic self-similarity and network performance as captured by performance measures including packet loss rate, retransmission rate, and queueing delay. Increased self-similarity, as expected, results in degradation of performance. Queueing delay, in particular, exhibits a drastic increase with increasing self-similarity. Throughput-related measures such as packet loss and retransmission rate, however, increase only gradually with increasing traffic self-similarity as long as reliable, flow-controlled transport protocol is used.

Scheduling Flows with Unknown Sizes: Approximate Analysis

Previous studies have shown that giving preferential treatment to short jobs helps reduce the average system response time, especially when the job size distribution possesses the heavy-tailed property. Since it has been shown that the TCP flow length distribution also has the same property, it is natural to let short TCP flows enjoy better service inside the network. Analyzing such discriminatory system requires modification to traditional job scheduling models since usually network traffic managers do not have detailed knowledge about individual flows such as their lengths. The Multi-Level (ML) queue, proposed by Kleinrock, can b e used to characterize such system. In an ML queueing system, the priority of a flow is reduced as the flow stays longer. We present an approximate analysis of the ML queueing system to obtain a closed-form solution of the average system response time function for general flow size distributions. We show that the response time of short flows can be significantly reduced without penalizing long flows.

Integrated spot size converters for InP based photonic systems

The ever increasing demand for broadband communications requires sophisticated devices. Photonic integrated circuits (PICs) are an approach that fulfills those requirements. PICs enable the integration of different optical modules on a single chip. Low loss fiber coupling and simplified packaging are key issues in keeping the price of PICs at a low level. Integrated spot size converters (SSC) offer an opportunity to accomplish this. Design, fabrication and characterization of SSCs based on an asymmetric twin waveguide (ATG) at a wavelength of 1.55 μm are the main elements of this dissertation. It is theoretically and experimentally shown that a passive ATG facilitates a polarization filter mechanism. A reproducible InP process guideline is developed that achieves vertical waveguides with smooth sidewalls. Birefringence and resonant coupling are used in an ATG to enable a polarization filtering and splitting mechanism. For the first time such a filter is experimentally shown. At a wavelength of 1610 nm a power extinction ratio of (1.6 ± 0.2) dB was measured for the TE- polarization in a single approximately 372 μm long TM- pass polarizer. A TE-pass polarizer with a similar length was demonstrated with a TM/TE-power extinction ratio of (0.7 ± 0.2) dB at 1610 nm. The refractive indices of two different InGaAsP compositions, required for a SSC, are measured by the reflection spectroscopy technique. A SSC layout for dielectric-free fabricated compact photodetectors is adjusted to those index values. The development and the results of the final fabrication procedure for the ATG concept are outlined. The etch rate, sidewall roughness and selectivity of a Cl2/CH4/H2 based inductively coupled plasma (ICP) etch are investigated by a design of experiment approach. The passivation effect of CH4 is illustrated for the first time. Conditions are determined for etching smooth and vertical sidewalls up to a depth of 5 μm.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Optoelectronic packaging interfaces for submicron alignment (OPISA) and the dynamics of laser spot weld formation

The work presented in this paper is part of the OPISA project. This is a collaborative research project between the University of Greenwich and Bookham Technology. This report describes some of the initial work undertaken towards the goal of investigating optoelectronic packaging where alignment issues between optical sources and fibers can arise as part of the fabrication process. The focus of this study is on charting the dynamics of laser spot weld formation. This paper introduces some of the initial simulation work that has been undertaken and presents a model describing a transient heat source applied from a laser pulse to weld a stainless steel sleeve and ferrule and the resulting weld formation