An evaluation of antigen capture assays for detecting active filarial antigens

Lymphatic filariasis is a parasitic disease of tropical countries. This is a disfiguring and painful disease contracted in childhood, but the symptoms become apparent only in later years. Diagnosis of filarial infection is very crucial for the management of the disease. The main objective of this study was to develop a filarial antigen-based immunological assay for the diagnosis and surveillance of the disease. Monoclonal and polyclonal antibodies were raised to the recombinant protein Brugia malayi vespid allergen homologue (VAH). Capture enzyme-linked immunosorbent assay (ELISA) was standardized utilizing various combinations of antibodies and evaluated with serum samples of endemic normal (EN, n = 110), microfilaraemic (MF, n = 65), chronic pathology (CP, n = 45) and non-endemic normal (NEN, n = 10) individuals. Of the 230 samples tested, VAHcapture assay detected circulating antigen in 97.91% of bancroftian and 100% of brugian microfilaraemic individuals, and 5% of endemic normal individuals, comparable to the earlier reported SXP-1 antigen detection assay. However, the combination of VAH and SXP-1 (VS) capture ELISA was found to be more robust, detecting 100% of microfilaraemic individuals and with higher binding values. Thus an antigen capture immunoassay has been developed, which can differentiate active infection from chronic infection by detecting circulating filarial antigens in clinical groups of endemic areas.

Perceptual thresholds for detecting modifications applied to the acoustical properties of a violin

This study is the first step in the psychoacoustic exploration of perceptual differences between the sounds of different violins. A method was used which enabled the same performance to be replayed on different "virtual violins," so that the relationships between acoustical characteristics of violins and perceived qualities could be explored. Recordings of real performances were made using a bridge-mounted force transducer, giving an accurate representation of the signal from the violin string. These were then played through filters corresponding to the admittance curves of different violins. Initially, limits of listener performance in detecting changes in acoustical characteristics were characterized. These consisted of shifts in frequency or increases in amplitude of single modes or frequency bands that have been proposed previously to be significant in the perception of violin sound quality. Thresholds were significantly lower for musically trained than for nontrained subjects but were not significantly affected by the violin used as a baseline. Thresholds for the musicians typically ranged from 3 to 6 dB for amplitude changes and 1.5%-20% for frequency changes. interpretation of the results using excitation patterns showed that thresholds for the best subjects were quite well predicted by a multichannel model based on optimal processing. (c) 2007 Acoustical Society of America.

Application of Optical Protein-chip in Detecting Phage M13KO7

Abstract: Avidin layer was bound on the substrate surface of Silicon wafer modified with aldehyde. The interaction between avidin and biotin was adopted for the immobilization of mouse monoclonal biotin-anti-M13 (antibody GP3)-labeled biotin. The surface was incubated in a solution containing phage M13KO7, which was trapped by the antibody GP3 with the interaction between phage M13KO7 and antibody GP3, resulting in a variation of layer thickness that was detected by imaging ellipsometry. The results showed a saturated layer of antibody GP3 with a thickness about 6.9 nm on the surface of the silicon wafer. The specific interaction between phage M13KO7 and antibody GP3 resulted in a variation of layer thickness. The layer of phage M13KO7 bound with antibody GP3 was 17.5 nm in the concentration of 1.1×1010 pfu/mL. Each variation of the layer thickness corresponded to a concentration of phage M13KO7 in the range of 0.1×1010–2.5×1010 pfu/mL, with the sensitivity of 109 pfu/mL. Compared with other methods, the optical protein-chip, requiring only short measurement time, label free, is a quantitative test, and can be visualized. This study could be significant on the interactions between the antibody and the virus, showing potential in the early diagnosis of virosis.

Power analysis for detecting trends in juvenile spotted seatrout abundance in Florida Bay

The spotted seatrout (Cynoscion nebulosus) is considered a key species relative to the implementation of the Comprehensive Everglades Restoration Plan (CERP). One of the goals of the CERP is to increase freshwater flows to Florida Bay. Increased freshwater flows can have potential positive and negative impacts on spotted seatrout populations. At low salinities, the planktonic eggs of spotted seatrout sink to the bottom and are not viable (Alshuth and Gilmore, 1994; Holt and Holt, 2002). On the other hand, increased freshwater flows can alleviate hypersaline conditions that could result in an expansion of the distribution of the early life stages of spotted seatrout (Thayer et al., 1999; Florida Department of Environmental Protection1). Thus it would be useful to develop a monitoring program that can detect changes in seatrout abundance on time scales short enough to be useful to resource managers. The NOAA Center for Coastal Fisheries and Habitat Research (NOAA) has made sporadic collections of juvenile seatrout using otter trawls since 1984 (see Powell et al, 2004). The results suggest that it might be useful to sample for seatrout in as many as eight different areas or basins (Figure 1): Bradley Key, Sandy Key, Johnson Key, Palm Key, Snake Bight, Central, Whipray and Crocodile Dragover. Unfortunately, logistical constraints are likely to limit the number of tows to about 40 per month over a period of six months each year. Inasmuch as few seatrout are caught in any given tow and the proportion of tows with zero seatrout is often high, it is important to determine how best to allocate this limited sampling effort among the various basins so that any trends in abundance may be detected with sufficient statistical confidence. (PDF contains 16 pages)

Detecting fish aggregations from reef habitats mapped with high resolution side scan sonar imagery

As part of a multibeam and side scan sonar (SSS) benthic survey of the Marine Conservation District (MCD) south of St. Thomas, USVI and the seasonal closed areas in St. Croix—Lang Bank (LB) for red hind (Epinephelus guttatus) and the Mutton Snapper (MS) (Lutjanus analis) area—we extracted signals from water column targets that represent individual and aggregated fish over various benthic habitats encountered in the SSS imagery. The survey covered a total of 18 km2 throughout the federal jurisdiction fishery management areas. The complementary set of 28 habitat classification digital maps covered a total of 5,462.3 ha; MCDW (West) accounted for 45% of that area, and MCDE (East) 26%, LB 17%, and MS the remaining 13%. With the exception of MS, corals and gorgonians on consolidated habitats were significantly more abundant than submerged aquatic vegetation (SAV) on unconsolidated sediments or unconsolidated sediments. Continuous coral habitat was the most abundant consolidated habitat for both MCDW and MCDE (41% and 43% respectively). Consolidated habitats in LB and MS predominantly consisted of gorgonian plain habitat with 95% and 83% respectively. Coral limestone habitat was more abundant than coral patch habitat; it was found near the shelf break in MS, MCDW, and MCDE. Coral limestone and coral patch habitats only covered LB minimally. The high spatial resolution (0.15 m) of the acquired imagery allowed the detection of differing fish aggregation (FA) types. The largest FA densities were located at MCDW and MCDE over coral communities that occupy up to 70% of the bottom cover. Counts of unidentified swimming objects (USOs), likely representing individual fish, were similar among locations and occurred primarily over sand and shelf edge areas. Fish aggregation school sizes were significantly smaller at MS than the other three locations (MCDW, MCDE, and LB). This study shows the advantages of utilizing SSS in determining fish distributions and density.

ICGE: an R package for detecting relevant clusters and atypical units in gene expression

Background: Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample ... ) belongs to one of these previously identified clusters or to a new group. Results: ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions: We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

Detecting actions of fruit flies

In this thesis we describe a system that tracks fruit flies in video and automatically detects and classifies their actions. We introduce Caltech Fly-vs-Fly Interactions, a new dataset that contains hours of video showing pairs of fruit flies engaging in social interactions, and is published with complete expert annotations and articulated pose trajectory features. We compare experimentally the value of a frame-level feature representation with the more elaborate notion of bout features that capture the structure within actions. Similarly, we compare a simple sliding window classifier architecture with a more sophisticated structured output architecture, and find that window based detectors outperform the much slower structured counterparts, and approach human performance. In addition we test the top performing detector on the CRIM13 mouse dataset, finding that it matches the performance of the best published method.