Sampling tissue for DNA analysis of trees: Trunk cambium as an alternative to canopy leaves

The number of studies of tropical tree species that use molecular tools is increasing, most of which collect leaf tissue for genomic DNA extraction. In tropical trees the canopy is not only frequently inaccessible, but also, once reached, the leaf tissue is often heavily defended against herbivory by high concentrations of anti-predation compounds, which may inhibit downstream applications, particularly PCR. Cambium tissue, accessed directly from the tree trunk at ground level, offers a readily accessible resource that is less hampered by the presence of defensive chemicals than leaf tissue. Here we describe a simple method for obtaining tissue from the cambial zone for DNA extraction and test the applicability of the method in a range of tropical tree species. The method was used successfully to extract DNA from 11 species in nine families. A subset of the DNA extracts was tested in more detail and proved to be highly suitable for AFLP analysis.

A Method for Capturing Dugongs (Dugong dugon) in Open Water

We developed a method to rapidly and safely live capture wild dugongs based on the “rodeo method” employed to catch marine turtles. This method entails close pursuit of a dugong by boat until it is fatigued. The dugong is then caught around the peduncle region by a catcher leaping off the boat, and the dugong is restrained at the water surface by several people while data are collected. Our sampling protocol involves a short restraint time, typically < 5 min. No ropes or nets were attached to the dugong to avoid the risk of entanglement and subsequent drowning. This method is suitable for shallow, open-water captures when weather and water conditions are fair, and may be adapted for deeper waters.

Coherence imaging by use of a Newton rings sampling function

We show that, with suitable optics in the arm of a Michelson interferometer, orthogonal galvo-scanning mirrors build a sampling function in the form of Newton rings when the two interferometer arms are matched. Using a low-coherence source, one can obtain transversal depth-resolved images. A fast display procedure using a storage oscilloscope was devised based on this method.

Coherence imaging by use of a Newton rings sampling function

We show that, with suitable optics in the arm of a Michelson interferometer, orthogonal galvo-scanning mirrors build a sampling function in the form of Newton rings when the two interferometer arms are matched. Using a low-coherence source, one can obtain transversal depth-resolved images. A fast display procedure using a storage oscilloscope was devised based on this method.

A novel dried blood spot-LCMS method for the quantification of methotrexate polyglutamates as a potential marker for methotrexate use in children

Objective: Development and validation of a selective and sensitive LCMS method for the determination of methotrexate polyglutamates in dried blood spots (DBS). Methods: DBS samples [spiked or patient samples] were prepared by applying blood to Guthrie cards which was then dried at room temperature. The method utilised 6-mm disks punched from the DBS samples (equivalent to approximately 12 μl of whole blood). The simple treatment procedure was based on protein precipitation using perchloric acid followed by solid phase extraction using MAX cartridges. The extracted sample was chromatographed using a reversed phase system involving an Atlantis T3-C18 column (3 μm, 2.1x150 mm) preceded by Atlantis guard column of matching chemistry. Analytes were subjected to LCMS analysis using positive electrospray ionization. Key Results: The method was linear over the range 5-400 nmol/L. The limits of detection and quantification were 1.6 and 5 nmol/L for individual polyglutamates and 1.5 and 4.5 nmol/L for total polyglutamates, respectively. The method has been applied successfully to the determination of DBS finger-prick samples from 47 paediatric patients and results confirmed with concentrations measured in matched RBC samples using conventional HPLC-UV technique. Conclusions and Clinical Relevance: The methodology has a potential for application in a range of clinical studies (e.g. pharmacokinetic evaluations or medication adherence assessment) since it is minimally invasive and easy to perform, potentially allowing parents to take blood samples at home. The feasibility of using DBS sampling can be of major value for future clinical trials or clinical care in paediatric rheumatology. © 2014 Hawwa et al.

A simple bioanalytical method for the quantification of antiepileptic drugs in dried blood spots

An increasing number of publications on the dried blood spot (DBS) sampling approach for the quantification of drugs and metabolites have been spurred on by the inherent advantages of this sampling technique. In the present research, a selective and sensitive high-performance liquid chromatography method for the concurrent determination of multiple antiepileptic drugs (AEDs) [levetiracetam (LVT), lamotrigine (LTG), phenobarbital (PHB)], carbamazepine (CBZ) and its active metabolite carbamazepine-10,11 epoxide (CBZE)] in a single DBS has been developed and validated. Whole blood was spotted onto Guthrie cards and dried. Using a standard punch (6 mm diameter), a circular disc was punched from the card and extracted with methanol: acetonitrile (3:1, v/v) containing hexobarbital (Internal Standard) and sonicated prior to evaporation. The extract was then dissolved in water and vortex mixed before undergoing solid phase extraction using HLB cartridges. Chromatographic separation of the AEDs was achieved using Waters XBridge™ C18 column with a gradient system. The developed method was linear over the concentration ranges studied with r ≥ 0.995 for all compounds. The lower limits of quantification (LLOQs) were 2, 1, 2, 0.5 and 1 μg/mL for LVT, LTG, PHB, CBZE and CBZ, respectively. Accuracy (%RE) and precision (%CV) values for within and between day were <20% at the LLOQs and <15% at all other concentrations tested. This method was successfully applied to the analysis of the AEDs in DBS samples taken from children with epilepsy for the assessment of their adherence to prescribed treatments.

Development of a dynamic headspace concentration technique for the non-contact sampling of human odor samples and the creation of canine training aids

Human scent and human remains detection canines are used to locate living or deceased humans under many circumstances. Human scent canines locate individual humans on the basis of their unique scent profile, while human remains detection canines locate the general scent of decomposing human remains. Scent evidence is often collected by law enforcement agencies using a Scent Transfer Unit, a dynamic headspace concentration device. The goals of this research were to evaluate the STU-100 for the collection of human scent samples, and to apply this method to the collection of living and deceased human samples, and to the creation of canine training aids. The airflow rate and collection material used with the STU-100 were evaluated using a novel scent delivery method. Controlled Odor Mimic Permeation Systems were created containing representative standard compounds delivered at known rates, improving the reproducibility of optimization experiments. Flow rates and collection materials were compared. Higher air flow rates usually yielded significantly less total volatile compounds due to compound breakthrough through the collection material. Collection from polymer and cellulose-based materials demonstrated that the molecular backbone of the material is a factor in the trapping and releasing of compounds. The weave of the material also affects compound collection, as those materials with a tighter weave demonstrated enhanced collection efficiencies. Using the optimized method, volatiles were efficiently collected from living and deceased humans. Replicates of the living human samples showed good reproducibility; however, the odor profiles from individuals were not always distinguishable from one another. Analysis of the human remains samples revealed similarity in the type and ratio of compounds. Two types of prototype training aids were developed utilizing combinations of pure compounds as well as volatiles from actual human samples concentrated onto sorbents, which were subsequently used in field tests. The pseudo scent aids had moderate success in field tests, and the Odor pad aids had significant success. This research demonstrates that the STU-100 is a valuable tool for dog handlers and as a field instrument; however, modifications are warranted in order to improve its performance as a method for instrumental detection.

Empirical aspects of a mixed method approach to economic network analysis

We discuss the interactions among the various phases of network research design in the context of our current work using Mixed Methods and SNA on networks and rural economic development. We claim that there are very intricate inter-dependencies among the various phases of network research design - from theory and formulation of research questions right through to modes of analysis and interpretation. Through examples drawn from our work we illustrate how choices about methods for Sampling and Data Collection are influenced by these interdependencies.

Leveraging Stratification in Twitter Sampling

With Tweet volumes reaching 500 million a day, sampling is inevitable for any application using Twitter data. Realizing this, data providers such as Twitter, Gnip and Boardreader license sampled data streams priced in accordance with the sample size. Big Data applications working with sampled data would be interested in working with a large enough sample that is representative of the universal dataset. Previous work focusing on the representativeness issue has considered ensuring the global occurrence rates of key terms, be reliably estimated from the sample. Present technology allows sample size estimation in accordance with probabilistic bounds on occurrence rates for the case of uniform random sampling. In this paper, we consider the problem of further improving sample size estimates by leveraging stratification in Twitter data. We analyze our estimates through an extensive study using simulations and real-world data, establishing the superiority of our method over uniform random sampling. Our work provides the technical know-how for data providers to expand their portfolio to include stratified sampled datasets, whereas applications are benefited by being able to monitor more topics/events at the same data and computing cost.

Finite Sampling Exponential Bounds

Thesis (Ph.D.)--University of Washington, 2016-08

Quantifying nitrous oxide emissions from sugarcane cropping systems : Optimum sampling time and frequency

Nitrous oxide (N2O) emissions from soil are often measured using the manual static chamber method. Manual gas sampling is labour intensive, so a minimal sampling frequency that maintains the accuracy of measurements would be desirable. However, the high temporal (diurnal, daily and seasonal) variabilities of N2O emissions can compromise the accuracy of measurements if not addressed adequately when formulating a sampling schedule. Assessments of sampling strategies to date have focussed on relatively low emission systems with high episodicity, where a small number of the highest emission peaks can be critically important in the measurement of whole season cumulative emissions. Using year-long, automated sub-daily N2O measurements from three fertilised sugarcane fields, we undertook an evaluation of the optimum gas sampling strategies in high emission systems with relatively long emission episodes. The results indicated that sampling in the morning between 09:00–12:00, when soil temperature was generally close to the daily average, best approximated the daily mean N2O emission within 4–7% of the ‘actual’ daily emissions measured by automated sampling. Weekly sampling with biweekly sampling for one week after >20 mm of rainfall was the recommended sampling regime. It resulted in no extreme (>20%) deviations from the ‘actuals’, had a high probability of estimating the annual cumulative emissions within 10% precision, with practicable sampling numbers in comparison to other sampling regimes. This provides robust and useful guidance for manual gas sampling in sugarcane cropping systems, although further adjustments by the operators in terms of expected measurement accuracy and resource availability are encouraged. By implementing these sampling strategies together, labour inputs and errors in measured cumulative N2O emissions can be minimised. Further research is needed to quantify the spatial variability of N2O emissions within sugarcane cropping and to develop techniques for effectively addressing both spatial and temporal variabilities simultaneously.

Identification, diversity and distribution patterns of fish larvae in Khark & Kharko Coralline Islands ecosystem – Persian Gulf, by GIS method

Khark & Kharko Islands are the last Northern point for fringing coral reefs in Iranian side of the Persian Gulf. These Coralline habitats are the Protected Area and Wildlife Refugees with the total area of 2400 ha which located in the territory of Bushehr Province. This research carried out during 2006-2007 with monthly sampling from 12 stations, which selected around Islands and inshore waters with maximum depth of 20 meter. Sampling was conducted using by Bongo-Net plankton sampler with 500μ of mesh size. Totally, 1808 specimen from 45 family fish larvae was identified in studied area, including: 21 coralline fish larva families and 24 shore fish larvae such as pelagic and demersal fishes which some of them known as indicator, sentinel or endemic species for coral reef ecosystems. The results was shown that coral reef diversity in coral reefs (Khark & Kharko Islands) is more than other habitats such as estuary and river mouth, creeks, mangrove forest sites, and off shore water of the Persian Gulf and Oman Sea Iranian side. Among Identified families, Clupeidae, Blenniidae, Sillaginidae, Atherinidae and Tripterygiidae; with more abundance were dominant families in studied area. The pick of fish larvae abundance family were estimated in spring. There were significant differences between seasonally abundance and sub areas, but there were not significant differences in diversity indexes between Khark and Kharko stations with coastal stations (p< 0.05). The mean abundance of fish larvae were estimated 18.7083 larvae under 10m² of sea surface, and the mean diversity indexes and evenness were estimated 0.7135 and 0.565342 consequently, that was showed the area is under ecological stress for fish larvae, and wasn’t stable. Therefore, from the ecological point of view, only some of the fish larvae groups as like Clupeidae were dominant. Thus, they were the main cause of the fish larvae abundance change in studied area. Due to geographical location of Khark and Kharko Islands and among the environmental parameters, Its seems that the condition of sea current is the main cause for present or absent and distribution patterns of fish larvae in area. Abundance of fish larvae in west of Islands was higher than eastern parts in the spring. But this condition will be reversed in eastern part of Island and several coastal stations, so that the Islands surrounding clock wise current to cause fish larvae distribution patterns.

Starch analysis as a method to discover subsistence strategies in prehistoric Finland and Estonia

Ancient starch analysis is a microbotanical method in which starch granules are extracted from archaeological residues and the botanical source is identified. The method is an important addition to established palaeoethnobotanical research, as it can reveal ancient microremains of starchy staples such as cereal grains and seeds. In addition, starch analysis can detect starch originating from underground storage organs, which are rarely discovered using other methods. Because starch is tolerant of acidic soils, unlike most organic matter, starch analysis can be successful in northern boreal regions. Starch analysis has potential in the study of cultivation, plant domestication, wild plant usage and tool function, as well as in locating activity areas at sites and discovering human impact on the environment. The aim of this study was to experiment with the starch analysis method in Finnish and Estonian archaeology by building a starch reference collection from cultivated and native plant species, by developing sampling, measuring and analysis protocols, by extracting starch residues from archaeological artefacts and soils, and by identifying their origin. The purpose of this experiment was to evaluate the suitability of the method for the study of subsistence strategies in prehistoric Finland and Estonia. A total of 64 archaeological samples were analysed from four Late Neolithic sites in Finland and Estonia, with radiocarbon dates ranging between 2904 calBC and 1770 calBC. The samples yielded starch granules, which were compared with the starch reference collection and descriptions in the literature. Cereal-type starch was identified from the Finnish Kiukainen culture site and from the Estonian Corded Ware site. The samples from the Finnish Corded Ware site yielded underground storage organ starch, which may be the first evidence of the use of rhizomes as food in Finland. No cereal-type starch was observed. Although the sample sets were limited, the experiment confirmed that starch granules have been preserved well in the archaeological material of Finland and Estonia, and that differences between subsistence patterns, as well as evidence of cultivation and wild plant gathering, can be discovered using starch analysis. By collecting large sample sets and addressing the three most important issues – preventing contamination, collecting adequate references and understanding taphonomic processes – starch analysis can substantially contribute to research on ancient subsistence in Finland and Estonia.

Risk Factors for Neonatal Sepsis and Method for Reduction of Blood Culture Contamination

Background False-positive blood cultures findings may lead to a falsely increased morbidity and increased hospital costs. Method The survey was conducted as retrospective - prospective study and included 239 preterm infants (born before 37 weeks of gestation) who were treated in Neonatal Intensive Care Unit (NICU) in Institute for Child and Youth Health Care of Vojvodina during one year (January 1st, 2012 to December 31st, 2012). The retrospective part of the study focused on examination of incidence of neonatal sepsis and determination of risk factors. In the prospective part of the study infants were sub-divided into two groups: Group 1- infants hospitalized in NICU during the first 6 months of the study; blood cultures were taken by the ‘’clean technique’’ and checklists for this procedure were not taken. Group 2- neonates hospitalized in NICU during last 6 months of the study; blood cultures were taken by ‘’sterile technique’’ and checklists for this procedure were taken. Results The main risk factors for sepsis were prelabor rupture of membranes, low gestational age, low birth weight, mechanical ventilation, umbilical venous catheter placement, and abdominal drainage. Staphylococcus aureus and coagulase negative Staphylococcus were the most frequently isolated microorganisms in false-positive blood samples. Conclusions Education of employees, use of checklists and sterile sets for blood sampling, permanent control of false positive blood cultures, as well as regular and routine monthly reports are crucial for successful reduction of contamination rates.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.