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Displaying 11 of 11 results for "TSC22D3"
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Title Date Issued Date Released Description
Cost effectiveness of the NZ DIP guideline screening recommendations FINAL
05-18-2015 05-18-2015
This is the decision analytic model designed to compare the cost effectiveness of the 2-step and 3-step screening strategies described in the article.
individual dip sampling data for mosquito larvae in Ethiopia
05-05-2016 05-05-2016
Site: sites visited labelled from A-Z (with 2 meaning second visit). Sample: count of individual samples taken at each site. Depth: depth in cm at the point of each individual dip sample. Area: area of the water body being sampled. Mean_depth: mean of depth measures from site. ph: ph at each site. Tall_rip: percentage estimate of tall (>20cm) riparian vegetation around the water body. Temp: temperature in degrees celsius at the sampling point. Anoph10: yes/no variable for whether Anopheles larvae were found in an individual dip sample. Algae: whether algae were visibly present in the water body. Sunny: if it was sunny on the surface of the water body at the time of collection.
Data from: Decline in new drug launches: myth or reality? Retrospective observational study using 30 years of data from the UK
02-20-2013 08-21-2015
Objective: To describe trends in new drugs launched in the UK from 1982 to 2011 and test the hypothesis that the rate of new drug introductions has declined over the study period. There is wide concern that pharmaceutical innovation is declining. Reported trends suggest that fewer new drugs have been launched over recent decades, despite increasing investment into research and development. Design: Retrospective observational study. Setting and data source: Database of new preparations added annually to the British National Formulary (BNF). Main outcome measures: The number of new drugs entered each year, including new chemical entities(NCEs) and new biological drugs, based on first appearance in the BNF. Results: There was no significant linear trend in the number of new drugs introduced into the UK from 1982 to 2011. Following a dip in the mid-1980s (11–12 NCEs/new biologics introduced annually from 1985 to 1987), there was a variable increase in the numbers of new drugs introduced annually to a peak of 34 in 1997. This peak was followed by a decline to approximately 20 new drugs/year between 2003 and 2006, and another peak in 2010. Extending the timeline further back with existing published data shows an overall slight increase in new drug introductions of 0.16/year over the entire 1971 to 2011 period. Conclusions: The purported ‘innovation dip’ is an artefact of the time periods previously studied. Reports of declining innovation need to be considered in the context of their timescale and perspective.
Data from: The importance of accounting for larval detectability in mosquito habitat-association studies
05-04-2016 05-05-2016
Background: Mosquito habitat-association studies are an important basis for disease control programmes and/or vector distribution models. However, studies do not explicitly account for incomplete detection during larval presence and abundance surveys, with potential for significant biases because of environmental influences on larval behaviour and sampling efficiency. Methods: Data were used from a dip-sampling study for Anopheles larvae in Ethiopia to evaluate the effect of six factors previously associated with larval sampling (riparian vegetation, direct sunshine, algae, water depth, pH and temperature) on larval presence and detectability. Comparisons were made between: (i) a presence-absence logistic regression where samples were pooled at the site level and detectability ignored, (ii) a success versus trials binomial model, and (iii) a presence-detection mixture model that separately estimated presence and detection, and fitted different explanatory variables to these estimations. Results: Riparian vegetation was consistently highlighted as important, strongly suggesting it explains larval presence (−). However, depending on how larval detectability was estimated, the other factors showed large variations in their statistical importance. The presence-detection mixture model provided strong evidence that larval detectability was influenced by sunshine and water temperature (+), with weaker evidence for algae (+) and water depth (−). For larval presence, there was also some evidence that water depth (−) and pH (+) influenced site occupation. The number of dip-samples needed to determine if larvae were likely present at a site was condition dependent: with sunshine and warm water requiring only two dips, while cooler water and cloud cover required 11. Conclusions: Environmental factors influence true larval presence and larval detectability differentially when sampling in field conditions. Researchers need to be more aware of the limitations and possible biases in different analytical approaches used to associate larval presence or abundance with local environmental conditions. These effects can be disentangled using data that are routinely collected (i.e., multiple dip samples at each site) by employing a modelling approach that separates presence from detectability.
Bonanza Creek Experimental Forest Precipitation (Water Buckets/Rain Gauges) at BCEF LTER sites: Weekly
04-26-2011 04-26-2011
Three (in clearings) or four (under canopies) Weather Bureau standard rain gauges have been placed on stands at a height of approximately 1 m at each site with meteorological measurements. Rainfall is measured each week during the summer with a dip stick. Measurements are entered into the computer and averaged by site and date. Prior to 1991 measurements were in inches. These data have been converted to mm.
Data from: Systematic study of the surface plasmon resonance signals generated by cells for sensors with different characteristic lengths
10-23-2014 11-11-2014
The objectives of this study were to establish an in-depth understanding of the signals induced by mammalian cells in surface plasmon resonance (SPR) sensing. To this end, two plasmonic structures with different propagation and penetration distances were used: conventional surface plasmon resonance and long-range surface plasmon resonance. Long-range SPR showed a lesser sensitivity to the absolute number of round cells but a greater resolution due to its very narrow spectral dip. The effect of cell spreading was also investigated and the resonance angle of long-range SPR was mostly insensitive unlike in the conventional SPR counterpart. Experimental data was compared with suitable models used in the SPR literature. Although these simple averaging models could be used to describe some of the experimental data, important deviations were observed which could be related to the fact that they do not take into consideration critical parameters such as plasmon scattering losses, which is particularly crucial in the case of long-range SPR structures. The comparison between conventional and long-range SPR for cellular schemes revealed important fundamental differences in their responses to the presence of cells, opening new horizons for SPR-based cell assays. From this study, long-range SPR is expected to be more sensitive towards both the detection of intracellular events resulting from biological stimulation and the detection of microorganisms captured from complex biological samples.
Offspring outcomes
05-13-2016 05-13-2016
Block refers to experimental block. Weight refers to weight at offspring infection. Family refers to family identity. Date mated refers to the date the mother was mated. Maternal egg refers to how many eggs the mother laid. Gender refers to the gender of the offspring. Date infected refers to the date of infection of the offspring (coded as a factor). Food refers to the diet quality of the offspring where "g" = good, 10:1:1 wheat bran to brewers' yeast to glycerol and "b" = bad 20:1:1 ratio. "infected" refers to the infection status of the offspring where "bt" = infected with LD33 Bt, "fu" = infected with LD33 Bb, "co" = coinfection with both pathogens. Trt refers to maternal treatment where "nai" = naive only handling treatment, "cdip" = control dip treatment in distilled water, "cdrop" = fed a control droplet of sugar water and food dye, "fungi" = LD05 dose of Bb, "btp" = LD05 dose of Bt, "cop" = coinfection with both pathogens. adstatus refers to whether the offspring outcome is either "a" = alive or "d" = dead. bt refers to the infection status of the mother with regard to bt, where "bt" = infected with either Bt or coinfection, and "nbt" = infected with fungus or any of the control treatments. fu refers to the infection status of the mother with regard to Bb where "fu" = infected with either Bb or coinfection, and "nfu" = infected with Bt or any of the control treatments.
Data from: Switching among natal and auxiliary hosts increases vulnerability of Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae) to insecticides
03-20-2017 04-19-2017
The role of insecticidal application and host plant resistance in managing Spodoptera exigua has been well documented, but the effect of different host plants, on which the pest cycles its population in the field, has seldom been investigated. Therefore, we have studied the vulnerability of S. exigua against commonly used insecticides (cypermethrin, chlorpyrifos, lufenuron, and emamectin benzoate) with different mode of actions when it switches its generations from natal to auxiliary hosts and vice versa. Different field populations being established on different host plants including castor, cauliflower, cotton, okra, and spinach were collected and reared in the laboratory before insecticidal bioassays. The role of larval diet and host plant switching on their response to tolerate applied insecticides was studied using leaf-dip bioassay methods. Host switching demonstrated a significant role in altering the vulnerability of S. exigua populations to tested insecticides. Spodoptera exigua sourced from castor, when switched host to okra and spinach, exhibited 50% higher mortality when treated with emamectin benzoate. This trend in mortality was consistent upon complete host switch cycle (natal—auxiliary—natal host). However, the highest increase (92%) in vulnerability was recorded when the larvae were shifted to spinach from cotton. In general, chlorpyrifos and lufenuron had highest efficacies in terms of larval mortality. The findings of present studies provide insights to a better understanding the behavior of polyphagous pests and the role of different host plants in altering the susceptibility of these pests against applied insecticides. Ultimately the results warrant that due consideration should be given to cropping patterns and time of host switching by pest population during planning and executing chemical control.
Space use by mottled sculpin and prey patch dynamics in a southern Appalachian stream.
04-21-2011 05-30-2016
We examined the effects of competitive interactions and prey patch dynamics on patch selection by a predatory benthic stream fish. Using mark-recapture techniques, we characterized the movements and space use behaviors of juvenile and adult mottled sculpin in a southern Appalachian stream. We then related these behaviors to spatial variation in benthic invertebrate colonization rates and small scale changes in local prey abundance. Observations made on the individual movements of sculpin indicated two distinct behavioral patterns: 1)despotic patch use, and 2)periodic patch abandonment. Our results on prey patch dynamics indicated that these behaviors were mediated by spatio-temporal variation in invertebrate distribution and dispersal. Adult sculpin maintained activities within patches of high prey abundance and exhibited persistent use of patches characterized by high invertebrate colonization rates. In addition, we found that patch abandonment by adult sculpin was induced by changes in the local abundance of invertebrate prey. In contrast to adults, patch use by juveniles appeared to be controlled primarilly by size-dependent competitive interactions. These results indicate that the dynamics of patch use by sculpin are controlled simultaneously by the dynamics of their patchily distributed prey and age/size dependent competitive interactions.1.We sampled sculpin population seasonally (Spring, Early and Late Summer, Autumn) in each of four years (1994, 1995, 1996, 1997). Within each season we made a series of four sampling passes. During each pass we snorkeled the study site and capture individual sculpin with dip nets. Individuals were weighed (nearest .01g) and measured (nearest 1mm) and given a unique mark using acrylic paints injected subcutaneously. We mapped the location of each individual using triangulation procedures. Individual movements were characterized as the distance between subsequent captures of the same individual over time. We measured microhabitat variables at each location (depth, current velocity, and substrate composition). We quantified invertebrate abundances within patches occupied by sculpin. We related movements by sculpin to changes in prey abundance and we quantified invertebrate colonization rates in areas used persistently by sculpin.
MODIS Leaf Area Index estimates for Alaska: 2002
04-26-2011 04-26-2011
The MODIS Leaf Area Index (LAI) Product is a global product produced every 8 days. The Leaf Area Index is estimated by a radiative transfer model assuming a given distribution of biome types within each pixel. The LAI Product was evaluated for the period of May 2002 to September 2002. The temporal pattern of spring greenup and fall senescence appeared reasonable across a large latitudinal transect from the Kenai Peninsula to the Arctic Coastal Plain. The temporal pattern also appeared reasonable across an elevational transect from Bonanza Creek Experimental Forest to Caribou Poker Creek Research Watershed to Eagle Summit. The positional accuracy and spatial pattern LAI was judged excellent by comparing the M2002 maximum LAI for the Survey Line Burn with a Landsat ETM+ image. However, there were two consistent problems with the LAI index at all spatial scales. First, a dip in maximum LAI during the green-up period most likely indicated cloud contamination of pixels. Second, the maximum 2002 LAI estimate was unrealistically high (>6.5) in many areas of Alaska. The accuracy of global estimates of leaf area and vegetation indices are suspect for high latitude areas due to several factors: 1) There is no tundra or taiga biome used in the leaf area index radiative transfer model. 2) Although a cloud-screen algorithm is applied on the front-end of processing, sub-pixel cloud contamination may occur over much of Alaska. 3) Subpixel broadleaf shrubs may lead to an overestimate of leaf area index and inflate vegetation indices.This dataset contains MOD15 leaf area index (LAI) and fraction of photosynthetically absorbed radiation (FPAR) for most of Alaska during the 2002 growing season. The data are in hdf format, with one file for each MODIS tile, for each 8-day composite period. The original quality control bits are included in each hdf file. The data are in the integerized sinusoidal projection with approzimately 1-km pixel size. The files were submitted in winzip format. The naming convention is For example: MOD15A2.A2002065.h10v02 is product MOD15A2, composite period starting at 2002065, for tile h10v02. More metadata about each file is embedded in each hdf file and can be read using any hdf browser. This dataset contains MOD15 leaf area index (LAI) and fraction of photosynthetically absorbed radiation (FPAR) for most of Alaska during the 2002 growing season. The data are in hdf format, with one file for each MODIS tile, for each 8-day composite period. The original quality control bits are included in each hdf file. The data are in the integerized sinusoidal projection with approzimately 1-km pixel size. The files were submitted in winzip format. The naming convention is For example: MOD15A2.A2002065.h10v02 is product MOD15A2, composite period starting at 2002065, for tile h10v02. More metadata about each file is embedded in each hdf file and can be read using any hdf browser.
Landscape and stream ecosystem trajectories in the southern Blue Ridge.
04-27-2011 04-27-2011
Aquatic ecosystems in medium sized watersheds (10-40 sq. km) in the southern Blue Ridge tend to have low productivity due to low light, low temperature, high gradient, and low nutrient levels. Human activities can alter each of these important drivers of ecosystem structure. Historic land use carries important implications for present and future biological and physical conditions. We assessed current conditions at sites whose watersheds were in (1) reference conditions, (2) forested land use, and (3) agricultural land use. The latter are projected to move toward second home development and suburban land uses, respectively. This study will document watershed land cover and land use as well as in-stream biological and physical changes as they are projected to occur over a 20-year period. Land use projections were derived from regression models base on past and present land cover and terrain information.Hazard Site Sampling Protocol and Methods || Sediment cores | Sediment core samples were collected at each site using a 60 cm (height) x 25 cm (diameter) stainless steel stovepipe corer. Sediment cores were located haphazardly in three riffles and three pools at each site. The coring device was inserted approximately 10 cm into the streambed. All substrate was removed to a depth of 10 cm. Large substrate (> 64 mm) was removed first and weighed in the field. All remaining substrate was removed, placed in plastic bags and transported to a lab at UGA for processing. Samples were dried in the lab at 105?C for three weeks, or until completely dry. Samples were then sieved into three size fractions: gravel (2 64 mm), sand (0.063 2 mm) and silt-clay (< 0.063 mm). Size fractions were then weighed to the nearest 0.1 gram. Percent fines (< 2 mm) and percent coarse material (> 2 mm) were determined using sediment core data. || TSS | Total suspended solids (TSS) samples were collected at baseflow at each site. Three 125 ml water samples, to be used for determining water chemistry, were collected from the thalweg of run habitat. Using a hand pump, water samples were filtered in the field onto a pre-ashed, pre-weighed 47 mm, 0.45 m Whatman glass fiber filter. Filters were placed in aluminium envelopes, transported to the lab, dried in a 105 C oven for 24 hours and weighed. Water sample filtrate was placed on ice and transported to lab for water chemistry analysis. || Pebble Count | Pebble counts were conducted to determine the particle size distribution of the bed substrate. One hundred particles were picked up and measured while traversing a zig-zag pattern at each site. Particles were measured in riffle-run habitat, while pool habitat was avoided. This affords direct comparison of similar habitat among sites. Medial axes of particles were measured to the nearest millimeter. Measurements were then converted to phi size (i.e. the negative log, base two), and average phi was determined. Some studies have suggested average phi as a good predictor of fish and macroinvertebrate measures (pers. comm., D. Walters, University of Georgia). || Temperature | Stream temperature data was collected in late summer 2000, from August 3rd to September 15th. Temperature was measured every 2 hours during this period, using a Hobo data logger contained in a waterproof PVC housing. Mean temperature and daily temperature flux were determined for each site. || Algae Standing Stock | Benthic algal biomass samples were collected at each site using a custom made suction apparatus. The apparatus consisted of a 20 cm long plexiglass cylinder with a 4.3 cm diameter. A rubber gasket was fitted to the end of the sampler which was pressed against the substrate to ensure a water tight seal between the sampler and substrate. Inside the sampler was a round scrub-brush, which was used to dislodge the algae from the substrate. Three algae samples were collected haphazardly and composited at each of 10 evenly spaced transects per site. Composite samples were placed on ice and transported to lab for processing. Algae samples were sub-sampled for determination of chlorophyll a concentration, ash-free dry mass and species identification. Chlorophll a concentration was determined from sub-samples using standard pigment analysis methods (Wetzel and Likens 1991). Pigments were extracted using 90% acetone buffered with ammonium hydroxide. Chlorophyll a was measured using standard fluorometric methods.Ash-free dry mass (AFDM) was also measured. Sub-samples were filtered through pre-weighed 47 mm, 0.45 ?m Whatman? glass fiber filters. Filters were then dried in a 105 C oven for 24 hours and weighed. || Fish | Fish were collected between April 16th and July 6th 2000 using a backpack electroshocker, seines and dip nets. At each site a quantitative sample was taken during one thorough pass within a representative 50 m reach. To ensure comparable catch per unit effort, an attempt was made to equalize electroshocking time per area sampled. After each quantitative collection, a larger area was randomly searched to determine community species richness. One individual from each species (except the federally threatened Cyprinella (Erimonax) monacha) was kept for museum specimens. Remaining fish were identified in the field, counted, and returned to the stream. || Energy Grade Line and Channel Cross Section Surveys | Standard survey techniques were used to survey three channel cross sections along the 100m study reach at each site. Energy grade line was also recorded by measuring water depth in the thalweg and channel elevation along the 100m reach. Pools and riffles were noted to allow calculation of pool to pool and riffle to riffle gradients. Point bar elevations were recorded separately, as were elevations of the flood plain. || Benthic Macroinvertebrates | Benthic macroinvertebrates were collected in riffle habitat by disturbing substrate inside a 0.4-sq. meter frame to a depth of 10 cm for 2 minutes. Material was collected in a net (353 micron mesh) held downstream of the sampling area and fixed in 3% formalin. Samples were rinsed in the laboratory in a 125 micron sieve and preserved in 80% ethanol. Macroinvertebrates were separated from other materials (sand, detritus) and identified to genus.