Analysis of the Horizontal Distribution of Sampling Points for Gas Concentrations Monitoring in an Open-Sided Dairy Barn

In the livestock sector, the monitoring of gas concentrations plays a relevant role in the implementation of mitigation strategies, as well as the improvement in the indoor air quality for both workers and animals in barns. In the present study, measurements of gas concentrations (NH3, CH4, and CO2) at different locations were carried out in an open dairy barn using a commercial photo-acoustic spectroscopy system. Measurement variability for different datasets was computed to contribute to the evaluation of the sampling strategy in the measurement campaign. The results showed that the position of sampling locations (SLs) significantly influenced (p < 0.001) the variability in the gas distribution. Specifically, the SLs located on the perimeter of the building had the highest variability. The number of SLs utilised for determining the mean value of gas concentration in the barn had a significant influence on NH3 (p < 0.001), CO2 (p < 0.001), and CH4 (p < 0.001) in both the central zone and the perimeter one. At least three SLs were necessary to obtain a mean value of gas concentration that reduced the variability to under the 10% in the central zone and 16% in the perimeter one. Moreover, the NH3 concentrations obtained as the mean value of the gas measurements at two SLs with a 10 m distance had a lower variability compared to those recorded at two SLs located at 5 m.

Measuring Estuarine Total Exchange Flow From Discrete Observations

The exchange between estuaries and the coastal ocean is a key dynamical driver impacting nutrient and phytoplankton concentrations and regulating estuarine residence time, hypoxia, and acidification. Estuarine exchange flows can be particularly challenging to monitor because many systems have strong vertical and lateral velocity shear and sharp gradients in water properties that vary over space and time, requiring high-resolution measurements in order to accurately constrain the flux. The total exchange flow (TEF) method provides detailed information about the salinity structure of the exchange, but requires observations (or model resolution) that resolve the time and spatial co-variability of salinity and currents. The goal of this analysis is to provide recommendations for measuring TEF with the most efficient spatial sampling resolution. Results from three realistic hydrodynamic models were investigated. These model domains included three estuary types: a bay (San Diego Bay), a salt-wedge (Columbia River), and a fjord (Salish Sea). Model fields were sampled using three different mooring strategies, varying the number of mooring locations (lateral resolution) and sample depths (vertical resolution) with each method. The exchange volume transport was more sensitive than salinity to the sampling resolution. Most (>90%) of the exchange flow magnitude was captured by three to four moorings evenly distributed across the estuarine channel with a minimum threshold of 1-5 sample depths, which varied depending on the vertical stratification. These results can improve our ability to observe and monitor the exchange and transport of water masses efficiently with limited resources.

Assessing land use influences on isotopic variability and stream water ages in urbanising rural catchments

Stable water isotopes are invaluable in helping understand catchment functioning and are widely used in experimental catchments, with higher frequency data becoming increasingly common. Such datasets incur substantial logistical costs, reducing their feasibility for use by decision makers needing to understand multi-catchment, landscape-scale functioning over a relatively short period to assess the impact of proposed land use change. Instead, reconnaissance style surveys (high spatial resolution across the landscape at a lower temporal frequency, over a relatively short period) offer an alternative, complementary approach. To test if such sampling could identify heterogeneities in hydrological functioning, and associated landscape controls, we sampled 27 stream sites fortnightly for one year within a peri-urban landscape undergoing land use change. Visual examination of raw data and application of mean transit time and young water fraction models indicated urbanisation, agriculture and responsive soils caused more rapid cycling of precipitation to stream water, whereas mature forestry provided attenuation. We were also able to identify contiguous catchments which functioned fundamentally differently, meaning their response to land use alteration would also be different. This study demonstrated how stable water isotopes can be a valuable, low-cost addition to tools available for environmental decision makers by providing local, process-based information.

Review of Scavenged Sampling for Sustainable Therapeutic Drug Monitoring: Do More With Less

PURPOSE

Innovative and sustainable sampling strategies for bioanalytical quantification of drugs and metabolites have gained considerable interest. Scavenging can be stratified as a sustainable sampling strategy using residual material because it aligns with the green principles of waste reduction and sampling optimization. Scavenged sampling includes all biological fluids' (eg, blood, liquor, and urine) leftover from standard clinical care. This review elaborates on the past and current landscape of sustainable sampling within therapeutic drug monitoring, with a focus on scavenged sampling.

METHODS

In February 2021, 4 databases were searched to assess the literature on the clinical use of innovative and sustainable sampling techniques without applying publication date restrictions. Studies reporting the clinical use of scavenged blood sampling and bridging studies of scavenged sampling and normal blood sampling were eligible for inclusion.

RESULTS

Overall, 19 eligible studies concerning scavenged sampling were identified from 1441 records. Scavenged sampling is mainly applied in the pediatric population, although other patient groups may benefit from this strategy. The infrastructure required for scavenged sampling encounters several challenges, including logistic hurdles, storage and handling conditions, and documentation errors. A workflow is proposed with identified opportunities that guide the implementation of scavenged sampling.

CONCLUSIONS

This review presents current evidence on the clinical use of scavenged sampling strategies. Scavenged sampling can be a suitable approach for drug quantification to improve dosage regimens, perform pharmacokinetic studies, and explore the value of therapeutic drug monitoring without additional sample collection.

On the acquisition of the water signal during water suppression: High-speed MR spectroscopic imaging with water referencing and concurrent functional MRI

This study evaluated the utility of concurrent water signal acquisition as part of the water suppression in MR spectroscopic imaging (MRSI), to allow simultaneous water referencing for metabolite quantification, and to concurrently acquire functional MRI (fMRI) data. We integrated a spatial-spectral binomial water excitation RF pulse and a short spatial-spectral echo-planar readout into the water suppression module of 2D and 3D proton-echo-planar-spectroscopic-imaging (PEPSI) with a voxel size as small as 4 x 4 x 6 mm³ . Metabolite quantification in reference to tissue water was validated in healthy controls for different prelocalization methods (spin-echo, PRESS and semi-LASER) and the clinical feasibility of a 3-minute 3D semi-Laser PEPSI scan (TR/TE: 1250/32 ms) with water referencing in patients with brain tumors was demonstrated. Spectral quality, SNR, Cramer-Rao-lower-bounds and water suppression efficiency were comparable with conventional PEPSI. Metabolite concentration values in reference to tissue water, using custom LCModel-based spectral fitting with relaxation correction, were in the range of previous studies and independent of the prelocalization method used. Next, we added a phase-encoding undersampled echo-volumar imaging (EVI) module during water suppression to concurrently acquire metabolite maps with water referencing and fMRI data during task execution and resting state in healthy controls. Integration of multimodal signal acquisition prolongated minimum TR by less than 50 ms on average. Visual and motor activation in concurrent fMRI/MRSI (TR: 1250-1500 ms, voxel size: 4 x 4 x 6 mm³ ) was readily detectable in single-task blocks with percent signal change comparable with conventional fMRI. Resting-state connectivity in sensory and motor networks was detectable in 4 minutes. This hybrid water suppression approach for multimodal imaging has the potential to significantly reduce scan time and extend neuroscience research and clinical applications through concurrent quantitative MRSI and fMRI acquisitions.

Ecological Specialization and Rarity of Arable Weeds: Insights from a Comprehensive Survey in France

The definition of “arable weeds” remains contentious. Although much attention has been devoted to specialized, segetal weeds, many taxa found in arable fields also commonly occur in other habitats. The extent to which adjacent habitats are favorable to the weed flora and act as potential sources of colonizers in arable fields remains unclear. In addition, weeds form assemblages with large spatiotemporal variability, so that many taxa in weed flora are rarely observed in plot-based surveys. We thus addressed the following questions: How often do weeds occur in other habitats than arable fields? How does including field edges extend the taxonomic and ecological diversity of weeds? How does the weed flora vary across surveys at different spatial and temporal scales? We built a comprehensive dataset of weed taxa in France by compiling weed flora, lists of specialized segetal weeds, and plot-based surveys in agricultural fields, with different spatial and temporal coverages. We informed life forms, biogeographical origins and conservation status of these weeds. We also defined a broader dataset of plants occupying open habitats in France and assessed habitat specialization of weeds and of other plant species absent from arable fields. Our results show that many arable weeds are frequently recorded in both arable fields and non-cultivated open habitats and are, on average, more generalist than species absent from arable fields. Surveys encompassing field edges included species also occurring in mesic grasslands and nitrophilous fringes, suggesting spill-over from surrounding habitats. A total of 71.5% of the French weed flora was not captured in plot-based surveys at regional and national scales, and many rare and declining taxa were of Mediterranean origin. This result underlines the importance of implementing conservation measures for specialist plant species that are particularly reliant on arable fields as a habitat, while also pointing out biotic homogenization of agricultural landscapes as a factor in the declining plant diversity of farmed landscapes. Our dataset provides a reference species pool for France, with associated ecological and biogeographical information.

Application of conditional robust calibration to ordinary differential equations models in computational systems biology: a comparison of two sampling strategies

Mathematical modelling is a widely used technique for describing the temporal behaviour of biological systems. One of the most challenging topics in computational systems biology is the calibration of non-linear models; i.e. the estimation of their unknown parameters. The state-of-the-art methods in this field are the frequentist and Bayesian approaches. For both of them, the performance and accuracy of results greatly depend on the sampling technique employed. Here, the authors test a novel Bayesian procedure for parameter estimation, called conditional robust calibration (CRC), comparing two different sampling techniques: uniform and logarithmic Latin hypercube sampling. CRC is an iterative algorithm based on parameter space sampling and on the estimation of parameter density functions. They apply CRC with both sampling strategies to the three ordinary differential equations (ODEs) models of increasing complexity. They obtain a more precise and reliable solution through logarithmically spaced samples.

T1ρ magnetic resonance fingerprinting

T_1ρ relaxation imaging is a quantitative imaging technique that has been used to assess cartilage integrity, liver fibrosis, tumors, cardiac infarction, and Alzheimer's disease. T₁ , T₂ , and T_1ρ relaxation time constants have each demonstrated different degrees of sensitivity to several markers of fibrosis and inflammation, allowing for a potential multi-parametric approach to tissue quantification. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T₁ and T₂ relaxation time constants. In this study, T_1ρ relaxation is added to the MRF framework using spin lock preparations. An MRF sequence involving an RF-spoiled sequence with T_R , flip angle, T_1ρ , and T₂ preparation variation is described. The sequence is then calibrated against conventional T₁ , T₂ , and T_1ρ relaxation mapping techniques in agar phantoms and the abdomens of four healthy volunteers. Strong intraclass correlation coefficients (ICC > 0.9) were found between conventional and MRF sequences in phantoms and also in healthy volunteers (ICC > 0.8). The highest ICC correlation values were seen in T₁ , followed by T_1ρ and then T₂ . In this study, T_1ρ relaxation has been incorporated into the MRF framework by using spin lock preparations, while still fitting for T₁ and T₂ relaxation time constants. The acquisition of these parameters within a single breath hold in the abdomen alleviates the issues of movement between breath holds in conventional techniques.

Pseudo-spiral sampling and compressed sensing reconstruction provides flexibility of temporal resolution in accelerated aortic 4D flow MRI: A comparison with k-t principal component analysis

INTRODUCTION

Time-resolved three-dimensional phase contrast MRI (4D flow) of aortic blood flow requires acceleration to reduce scan time. Two established techniques for highly accelerated 4D flow MRI are k-t principal component analysis (k-t PCA) and compressed sensing (CS), which employ either regular or random k-space undersampling. The goal of this study was to gain insights into the quantitative differences between k-t PCA- and CS-derived aortic blood flow, especially for high temporal resolution CS 4D flow MRI.

METHODS

The scan protocol consisted of both k-t PCA and CS accelerated 4D flow MRI, as well as a 2D flow reference scan through the ascending aorta acquired in 15 subjects. 4D flow scans were accelerated with factor R = 8. For CS accelerated scans, we used a pseudo-spiral Cartesian sampling scheme, which could additionally be reconstructed at higher temporal resolution, resulting in R = 13. 4D flow data were compared with the 2D flow scan in terms of flow, peak flow and stroke volume. A 3D peak systolic voxel-wise velocity and wall shear stress (WSS) comparison between k-t PCA and CS 4D flow was also performed.

RESULTS

The mean difference in flow/peak flow/stroke volume between the 2D flow scan and the 4D flow CS with R = 8 and R = 13 was 4.2%/9.1%/3.0% and 5.3%/7.1%/1.9%, respectively, whereas for k-t PCA with R = 8 the difference was 9.7%/25.8%/10.4%. In the voxel-by-voxel 4D flow comparison we found 13.6% and 3.5% lower velocity and WSS values of k-t PCA compared with CS with R = 8, and 15.9% and 5.5% lower velocity and WSS values of k-t PCA compared with CS with R = 13.

CONCLUSION

Pseudo-spiral accelerated 4D flow acquisitions in combination with CS reconstruction provides a flexible choice of temporal resolution. We showed that our proposed strategy achieves better agreement in flow values with 2D reference scans compared with using k-t PCA accelerated acquisitions.

Expostats: A Bayesian Toolkit to Aid the Interpretation of Occupational Exposure Measurements

INTRODUCTION

Interpretation of exposure measurements has evolved into a framework based on the lognormal distribution. Most available practical tools are based on traditional frequentist statistical procedures that do not satisfactorily account for censored data and are not amenable to simple probabilistic risk statements. Bayesian methods offer promising solutions to these challenges. Such methods have been proposed in the literature but are not widely and freely available to practitioners.

METHODS

A set of computer applications were developed aimed at answering typical inferential questions that are important to occupational health practitioners: Is a group of workers compliant with an occupational exposure limit? Are some individuals within this group likely to experience substantially higher exposure than its average member? How does an intervention influence the distribution of exposures? These questions were addressed using Bayesian models, simultaneously accounting for left, right, and interval-censored data with multiple censoring points. The models are estimated using the JAGS Gibbs sampler called through the R statistical package.

RESULTS

The Expostats toolkit is freely available from www.expostats.ca as four tools accessible through a Web application, an offline standalone application or algorithms. The tools include a variety of calculations and graphical outputs useful according to current practices in analysis and interpretation of exposure measurements collected by occupational hygienists. Tool1 and its simplified version Tool1 Express focus on inferences from data from a similarly exposed group. Tool2 evaluates within- and between-worker components of variability, as well as the probability that an individual worker might be overexposed. Tool3 compares exposure data across groups, e.g. evaluates the effect of an intervention. Uncertainty management includes the calculation of credible intervals and produces probabilistic statements about the exposure metrics (e.g. probability that over 5% of exposures are above a limit).

DISCUSSION

Expostats is the first freely available toolkit that leverages the flexibility of Bayesian analysis to perform an extensive list of calculations recommended in several international guidelines on the practice of occupational hygiene.

Unipolar MR elastography: Theory, numerical analysis and implementation

In MR elastography (MRE), zeroth moment balanced motion-encoding gradients (MEGs) are incorporated into MRI sequences to induce a phase shift proportional to the local displacement caused by external actuation. To maximize the signal-to-noise ratio (SNR), fractional encoding is employed, i.e., the MEG duration is reduced below the wave period. Here, gradients encode primarily the velocity of the motion-reducing encoding efficiency. Thus, in GRE-MRE, T₂ * decay and motion sensitivity have to be balanced, imposing a lower limit on repetition times (TRs). We propose to use a single trapezoidal gradient, a "unipolar gradient", to directly encode spin displacement. Such gradients cannot be used in conventional sequences as they exhibit a large zeroth moment and dephase magnetization. By time-reversing a spoiled SSFP sequence, the spoiling gradient becomes an efficient unipolar MEG. The proposed "unipolar MRE" technique benefits from this approach in three ways: first, displacement encoding is split over multiple TRs increasing motion sensitivity; second, spoiler and MEG coincide, allowing a reduction in TR; third, motion sensitivity of a typical unipolar lobe is of an order of magnitude higher than a bipolar MEG of equal duration. In this work, motion encoding using unipolar MRE is analyzed using the extended phase graph (EPG) formalism with a periodic motion propagator. As an approximation, the two-transverse TR approximation for diffusion-weighted SSFP is extended to incorporate cyclic motion. A complex encoding efficiency metric is introduced to compare the displacement fields of unipolar and conventional GRE-MRE sequences in both magnitude and phase. The derived theoretical encoding equations are used to characterize the proposed sequence using an extensive parameter study. Unipolar MRE is validated against conventional GRE-MRE in a phantom study showing excellent agreement between measured displacement fields. In addition, unipolar MRE yields significantly increased octahedral shear strain-SNR relative to conventional GRE-MRE and allows for the recovery of high stiffness inclusions, where conventional GRE-MRE fails.

Multi-parametric T2 * magnetic resonance fingerprinting using variable echo times

The use of quantitative imaging biomarkers in the imaging of various disease states, including cancer and neurodegenerative disease, has increased in recent years. T₁ , T₂ , and T₂ * relaxation time constants have been shown to be affected by tissue structure or contrast infusion. Acquiring these biomarkers simultaneously in a multi-parametric acquisition could provide more robust detection of tissue changes in various disease states including neurodegeneration and cancer. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T₁ and T₂ relaxation time constants. In this study, T₂ * relaxation is added to the MRF framework using variable echo times (TE). To demonstrate the feasibility of the method and compare incremental and golden angle spiral rotations, simulated phantom data was fit using the proposed method. Additionally, T₁ /T₂ /T₂ */δf MRF as well as conventional T₁ , T₂ , and T₂ * acquisitions were acquired in agar phantoms and the brains of three healthy volunteers. Golden angle spiral rotation was found to reduce inaccuracy resulting from off resonance effects. Strong correlations were found between conventional and MRF values in the T₁ , T₂ , and T₂ * relaxation time constants of the agar phantoms and healthy volunteers. In this study, T₂ * relaxation has been incorporated into the MRF framework by using variable echo times, while still fitting for T₁ and T₂ relaxation time constants. In addition to fitting these relaxation time constants, a novel method for fitting and correcting off resonance effects has been developed.

Design strategies from sexual exploitation and sex work studies among women and girls: Methodological considerations in a hidden and vulnerable population

The study of sex trafficking, prostitution, sex work, and sexual exploitation is associated with many methodological issues and challenges. Researchers' study designs must consider the many safety issues related to this vulnerable and hidden population. Community advisory boards and key stakeholder involvement are essential to study design to increase safety of participants, usefulness of study aims, and meaningfulness of conclusions. Nonrandomized sampling strategies are most often utilized when studying exploited women and girls, which have the capacity to provide rich data and require complex sampling and recruitment methods. This article reviews the current methodological issues when studying this marginalized population as well as strategies to address challenges while working with the community in order to bring about social change. The authors also discuss their own experiences in collaborating with community organizations to conduct research in this field.

Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research.

Methodology Series Module 5: Sampling Strategies

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ‘ Sampling Method’. There are essentially two types of sampling methods: 1) probability sampling – based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term ‘ random sample’ when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the ‘ generalizability’ of these results. In such a scenario, the researcher may want to use ‘ purposive sampling’ for the study.

Invited commentary: recruiting for epidemiologic studies using social media

Social media-based recruitment for epidemiologic studies has the potential to expand the demographic and geographic reach of investigators and identify potential participants more cost-effectively than traditional approaches. In fact, social media are particularly appealing for their ability to engage traditionally "hard-to-reach" populations, including young adults and low-income populations. Despite their great promise as a tool for epidemiologists, social media-based recruitment approaches do not currently compare favorably with gold-standard probability-based sampling approaches. Sparse data on the demographic characteristics of social media users, patterns of social media use, and appropriate sampling frames limit our ability to implement probability-based sampling strategies. In a well-conducted study, Harris et al. (Am J Epidemiol. 2015;181(10):737-746) examined the cost-effectiveness of social media-based recruitment (advertisements and promotion) in the Contraceptive Use, Pregnancy Intention, and Decisions (CUPID) Study, a cohort study of 3,799 young adult Australian women, and the approximate representativeness of the CUPID cohort. Implications for social media-based recruitment strategies for cohort assembly, data accuracy, implementation, and human subjects concerns are discussed.

Recent advances and applications of experimental technologies in marine natural product research

Marine natural products are a rich source of novel and biologically active compounds. The number of identified marine natural compounds has grown 20% over the last five years from 2009 to 2013. Several challenges, including sample collection and structure elucidation, have limited the development of this research field. Nonetheless, new approaches, such as sampling strategies for organisms from extreme ocean environments, nanoscale NMR and computational chemistry for structural determination, are now available to overcome the barriers. In this review, we highlight the experimental technology innovations in the field of marine natural products, which in our view will lead to the development of many new drugs in the future.

SElf-gated Non-Contrast-Enhanced FUnctional Lung imaging (SENCEFUL) using a quasi-random fast low-angle shot (FLASH) sequence and proton MRI

Obtaining functional information on the human lung is of tremendous interest in the characterization of lung defects and pathologies. However, pulmonary ventilation and perfusion maps usually require contrast agents and the application of electrocardiogram (ECG) triggering and breath holds to generate datasets free of motion artifacts. This work demonstrates the possibility of obtaining highly resolved perfusion-weighted and ventilation-weighted images of the human lung using proton MRI and the SElf-gated Non-Contrast-Enhanced FUnctional Lung imaging (SENCEFUL) technique. The SENCEFUL technique utilizes a two-dimensional fast low-angle shot (FLASH) sequence with quasi-random sampling of phase-encoding (PE) steps for data acquisition. After every readout, a short additional acquisition of the non-phase-encoded direct current (DC) signal necessary for self-gating was added. By sorting the quasi-randomly acquired data according to respiratory and cardiac phase derived from the DC signal, datasets of representative respiratory and cardiac cycles could be accurately reconstructed. By application of the Fourier transform along the temporal dimension, functional maps (perfusion and ventilation) were obtained. These maps were compared with dynamic contrast-enhanced (DCE, perfusion) as well as standard Fourier decomposition (FD, ventilation) reference datasets. All datasets were additionally scored by two experienced radiologists to quantify image quality. In addition, one initial patient examination using SENCEFUL was performed. Functional images of healthy volunteers and a patient diagnosed with hypoplasia of the left pulmonary artery and left-sided pulmonary fibrosis were successfully obtained. Perfusion-weighted images corresponded well to DCE-MRI data; ventilation-weighted images offered a significantly better depiction of the lung periphery compared with standard FD. Furthermore, the SENCEFUL technique hints at a potential clinical relevance by successfully detecting a perfusion defect in the patient scan. It can be concluded that SENCEFUL enables highly resolved ventilation- and perfusion-weighted maps of the human lung to be obtained using proton MRI, and might be interesting for further clinical evaluation.

A comparison of two common flight interception traps to survey tropical arthropods

Tropical forests are predicted to harbor most of the insect diversity on earth, but few studies have been conducted to characterize insect communities in tropical forests. One major limitation is the lack of consensus on methods for insect collection. Deciding which insect trap to use is an important consideration for ecologists and entomologists, yet to date few study has presented a quantitative comparison of the results generated by standardized methods in tropical insect communities. Here, we investigate the relative performance of two flight interception traps, the windowpane trap, and the more widely used malaise trap, across a broad gradient of lowland forest types in French Guiana. The windowpane trap consistently collected significantly more Coleoptera and Blattaria than the malaise trap, which proved most effective for Diptera, Hymenoptera, and Hemiptera. Orthoptera and Lepidoptera were not well represented using either trap, suggesting the need for additional methods such as bait traps and light traps. Our results of contrasting trap performance among insect orders underscore the need for complementary trapping strategies using multiple methods for community surveys in tropical forests.

Fine-scale genetic structure among genetic individuals of the clone-forming monotypic genus Echinosophora koreensis (Fabaceae)

BACKGROUND AND AIMS

For rare endemics or endangered plant species that reproduce both sexually and vegetatively it is critical to understand the extent of clonality because assessment of clonal extent and distribution has important ecological and evolutionary consequences with conservation implications. A survey was undertaken to understand clonal effects on fine-scale genetic structure (FSGS) in two populations (one from a disturbed and the other from an undisturbed locality) of Echinosophora koreensis, an endangered small shrub belonging to a monotypic genus in central Korea that reproduces both sexually and vegetatively via rhizomes.

METHODS

Using inter-simple sequence repeats (ISSRs) as genetic markers, the spatial distribution of individuals was evaluated using Ripley's L(d)-statistics and quantified the spatial scale of clonal spread and spatial distribution of ISSR genotypes using spatial autocorrelation analysis techniques (join-count statistics and kinship coefficient, F(ij)) for total samples and samples excluding clones.

KEY RESULTS

A high degree of differentiation between populations was observed (phi(ST(g)) = 0.184, P < 0.001). Ripley's L(d)-statistics revealed a near random distribution of individuals in a disturbed population, whereas significant aggregation of individuals was found in an undisturbed site. The join-count statistics revealed that most clones significantly aggregate at < or = 6-m interplant distance. The Sp statistic reflecting patterns of correlograms revealed a strong pattern of FSGS for all four data sets (Sp = 0.072-0.154), but these patterns were not significantly different from each other. At small interplant distances (< or = 2 m), however, jackknifed 95% CIs revealed that the total samples exhibited significantly higher F(ij) values than the same samples excluding clones.

CONCLUSION

The strong FSGS from genets is consistent with two biological and ecological traits of E. koreensis: bee-pollination and limited seed dispersal. Furthermore, potential clone mates over repeated generations would contribute to the observed high F(ij) values among genets at short distance. To ensure long-term ex situ genetic variability of the endangered E. koreensis, individuals located at distances of 10-12 m should be collected across entire populations of E. koreensis.

Clonal and fine-scale genetic structure in populations of a restricted Korean endemic, Hosta jonesii (Liliaceae) and the implications for conservation

BACKGROUND AND AIMS

In plant populations the magnitude of spatial genetic structure of apparent individuals (including clonal ramets) can be different from that of sexual individuals (genets). Thus, distinguishing the effects of clonal versus sexual individuals in population genetic analyses could provide important insights for evolutionary biology and conservation. To investigate the effects of clonal spread on the fine-scale spatial genetic structure within plant populations, Hosta jonesii (Liliaceae), an endemic species to Korea, was chosen as a study species.

METHODS

Using allozymes as genetic markers, spatial autocorrelation analysis of ramets and of genets was conducted to quantify the spatial scale of clonal spread and genotype distribution in two populations of H. jonesii.

KEY RESULTS

Join-count statistics revealed that most clones are significantly aggregated at < 3-m interplant distance. Spatial autocorrelation analysis of all individuals resulted in significantly higher Moran's I values at 0-3-m interplant distance than analyses of population samples in which clones were excluded. However, significant fine-scale genetic structure was still observed when clones were excluded.

CONCLUSIONS

These results suggest that clones enhance the magnitude of spatial autocorrelation due to localized clonal spread. The significant fine-scale genetic structure detected in samples excluding clones is consistent with the biological and ecological traits exhibited by H. jonesii including bee pollination and limited seed dispersal. For conservation purposes, genetic diversity would be maximized in local populations of H. jonesii by collecting or preserving individuals that are spaced at least 5 m apart.

Embracing the emerging precision agriculture technologies for site-specific management of yield-limiting factors

Precision agriculture (PA) is providing an information revolution using Global Positioning (GPS) and Geographic Information (GIS) systems and Remote Sensing (RS). These technologies allow better decision making in the management of crop yield-limiting biotic and abiotic factors and their interactions on a site-specific (SSM) basis in a wide range of production systems. Characterizing the nature of the problem(s) and public education are among the challenges that scientists, producers, and industry face when adapting PA technologies. To apply SSM, spatio-temporal characteristics of the problem(s) need to be determined and variations within a field demonstrated. Spatio-temporal characteristics of a given pathogen or pest problem may be known but may not be the only or primary cause of the problem. Hence, exact cause-and-effect relationships need to be established by incorporating GIS, GPS, and RS-generated data as well as possible interactions. Exploiting the potential of PA technologies in sustainable ways depends on whether or not we first ask ''Are we doing the right thing?'' (strategic) as opposed to ''Are we doing it right?'' (tactical).

Dependence of DNA-histograms on the sampling techniques in fine needle aspirates of the breast

48 fine needle aspiration biopsy (FNAB) samples from 25 breast cancer cases, originally used for cytodiagnosis were subjected to DNA cytometry. There were air dried smears stained with the MGG method, and samples stained with HE or PAP stain after 50% ethanol fixation and cytocentrifugation. Different sampling strategies were applied. Four methods were tested: method 1: cell groups measured, method 2: all cells measured, method 3: free cells measured, and method 4: atypical free cells measured. Method 4 showed most often DNA aneuploid histogram patterns, sampling method 1 had the highest number of DNA diploid histogram patterns. Diagnostic approaches may benefit from a sampling method detecting the hiding aneuploid cell population. Grading of neoplasm could potentially benefit from other approaches.