Using sniffing behavior to differentiate true negative from false negative responses in trained scent-detection dogs.

False negatives are recorded in every chemical detection system, but when animals are used as a scent detector, some false negatives can arise as a result of a failure in the link between detection and the trained alert response, or a failure of the handler to identify the positive alert. A false negative response can be critical in certain scenarios, such as searching for a live person or detecting explosives. In this study, we investigated whether the nature of sniffing behavior in trained detection dogs during a controlled scent-detection task differs in response to true positives, true negatives, false positives, and false negatives. A total of 200 videos of 10 working detection dogs were pseudorandomly selected and analyzed frame by frame to quantify sniffing duration and the number of sniffing episodes recorded in a Go/No-Go single scent-detection task using an eight-choice test apparatus. We found that the sniffing duration of true negatives is significantly shorter than false negatives, true positives, and false positives. Furthermore, dogs only ever performed one sniffing episode towards true negatives, but two sniffing episodes commonly occurred in the other situations. These results demonstrate how the nature of sniffing can be used to more effectively assess odor detection by dogs used as biological detection devices.

Differential growth and yield by canola (Brassica napus L.) and wheat (Triticum aestivum L.) arising from alterations in chemical properties of sandy soils due to additions of fly ash.

BACKGROUND: There is a need for field trials on testing agronomic potential of coal fly ash to engender routine use of this technology. Two field trials were undertaken with alkaline and acidic fly ashes supplied at between 3 and 6 Mg ha⁻¹ to acidic soils and sown to wheat and canola at Richmond (Eastern Australia) and to wheat only at Merredin (Western Australia). RESULTS: Ash addition marginally (P< 0.10) raised the pH in the top soil layers at both sites. The exceptionally dry season at both sites constrained yields and thwarted any likelihood of gaining yield benefits from ash-induced improvements in soil conditions. Yield improvements due to ash addition were absent at Merredin and only marginal at Richmond, where no elevated accumulation of B, Mo, Se, P or S in either the straw or seeds of wheat was observed; canola increased accumulation of Mo and Se in its shoot with acidic fly ash, but it was well below phyto toxic levels. Simulations of wheat using APSIM at Richmond over a 100-year period (1909-2008) predicted yield increases in 52% of years with addition of ash at 3.0 Mg ha⁻¹ compared with 24% of years with addition of ash at 6.0 Mg ha⁻¹. The simulated yield increases did not exceed 40% over the control with addition of 6 Mg ha⁻¹ ash, but was between 40% and 50% with an addition rate of 3 Mg ha⁻¹. CONCLUSION: We found no evidence of phytotoxicity in either crop in this unusually dry year and there is still a need for further field assessment in years with favourable rainfall to enable development of clear recommendations on fly ash rates for optimum yield benefits.

Deagglomeration of DNA nanomedicine carriers using controlled ultrasonication.

Control over the agglomeration state of manufactured particle systems for drug and oligonucleotide intracellular delivery is paramount to ensure reproducible and scalable therapeutic efficacy. Ultrasonication is a well-established mechanism for the deagglomeration of bulk powders in dispersion. Its use in manufacturing requires strict control of the uniformity and reproducibility of the cavitation field within the sample volume to minimise within-batch and batch-to-batch variability. In this work, we demonstrate the use of a reference cavitating vessel which provides stable and reproducible cavitation fields over litre-scale volumes to assist the controlled deagglomeration of a novel non-viral particle-based plasmid delivery system. The system is the Nuvec delivery platform, comprising polyethylenimine-coated spiky silica particles with diameters of âˆ¼ 200 nm. We evaluated the use of controlled cavitation at different input powers and stages of preparation, for example before and after plasmid loading. Plasmid loading was confirmed by X-ray photoelectron spectroscopy and gel electrophoresis. The latter was also used to assess plasmid integrity and the ability of the particles to protect plasmid from potential degradation caused by the deagglomeration process. We show the utility of laser diffraction and differential centrifugal sedimentation in quantifying the efficacy of product de-agglomeration in the microscale and nanoscale size range respectively. Transmission electron microscopy was used to assess potential damages to the silica particle structure due to the sonication process.

Synchronized firing among retinal ganglion cells signals motion reversal.

We show that when a moving object suddenly reverses direction, there is a brief, synchronous burst of firing within a population of retinal ganglion cells. This burst can be driven by either the leading or trailing edge of the object. The latency is constant for movement at different speeds, objects of different size, and bright versus dark contrasts. The same ganglion cells that signal a motion reversal also respond to smooth motion. We show that the brain can build a pure reversal detector using only a linear filter that reads out synchrony from a group of ganglion cells. These results indicate that not only can the retina anticipate the location of a smoothly moving object, but that it can also signal violations in its own prediction. We show that the reversal response cannot be explained by models of the classical receptive field and suggest that nonlinear receptive field subunits may be responsible.

Detection and prediction of periodic patterns by the retina.

A fundamental task of the brain is detecting patterns in the environment that enable predictions about the future. Here, we show that the salamander and mouse retinas can recognize a wide class of periodic temporal patterns, such that a subset of ganglion cells fire strongly and specifically in response to a violation of the periodicity. This sophisticated retinal processing may provide a substrate for hierarchical pattern detection in subsequent circuits.

Feasibility of integrating canine olfaction with chemical and microbial profiling of urine to detect lethal prostate cancer.

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs' diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

A Lesson in Standardization - Subtle Aspects of the Processing of Samples Can Greatly Affect Dogs' Learning.

Training new medical odors presents challenges in procuring sufficient target samples, and suitably matched controls. Organizations are often forced to choose between using fewer samples and risking dogs learning individuals or using differently sourced samples. Even when aiming to standardize all aspects of collection, processing, storage and presentation, this risks there being subtle differences which dogs use to discriminate, leading to artificially high performance, not replicable when novel samples are presented. We describe lessons learnt during early training of dogs to detect prostate cancer from urine. Initially, six dogs were trained to discriminate between hospital-sourced target and externally-sourced controls believed to be processed and stored the same way. Dogs performed well: mean sensitivity 93.5% (92.2-94.5) and specificity 87.9% (78.2-91.9). When training progressed to include hospital-sourced controls, dogs greatly decreased in specificity 67.3% (43.2-83.3). Alerted to a potential issue, we carried out a methodical, investigation. We presented new strategically chosen samples to the dogs and conducted a logistic regression analysis to ascertain which factor most affected specificity. We discovered the two sets of samples varied in a critical aspect, hospital-processed samples were tested by dipping the urinalysis stick into the sample, whilst for externally sourced samples a small amount of urine was poured onto the stick. Dogs had learnt to distinguish target aided by the odor of this stick. This highlights the importance of considering every aspect of sample processing even when using urine, often believed to be less susceptible to contamination than media like breath.

Canine Olfactory Thresholds to Amyl Acetate in a Biomedical Detection Scenario.

Dogs' abilities to respond to concentrations of odorant molecules are generally deemed superior to electronic sensors. This sensitivity has been used traditionally in many areas; but is a more recent innovation within the medical field. As a bio-detection sensor for human diseases such as cancer and infections, dogs often need to detect volatile organic compounds in bodily fluids such as urine and blood. Although the limits of olfactory sensitivity in dogs have been studied since the 1960s, there is a gap in our knowledge concerning these limits in relation to the concentration of odorants presented in a fluid phase. Therefore, the aim of this study was to estimate olfactory detection thresholds to an inert substance, amyl acetate presented in a liquid phase. Ten dogs were trained in a "Go/No go" single scent-detection task using an eight-choice carousel apparatus. They were trained to respond to the presence of solutions of amyl acetate diluted to varying degrees in mineral oil by sitting in front of the positive sample, and not responding to the 7 other control samples. Training and testing took place in an indoor room with the same handler throughout using a food reward. After 30 weeks of training, using a forward chaining technique, dogs were tested for their sensitivity. The handler did not assist the dog during the search and was blind to the concentration of amyl acetate tested and the position of the target in the carousel. The global olfactory threshold trend for each dog was estimated by fitting a least-squares logistic curve to the association between the proportion of true positives and amyl acetate concentration. Results show an olfactory detection threshold for fluid mixtures ranging from 40 parts per billion to 1.5 parts per trillion. There was considerable inter-dog difference in sensitivity, even though all dogs were trained in the same way and worked without the assistance of the handler. This variation highlights factors to be considered in future work assessing olfactory detection performance by dogs.

A cumulant analysis for non-Gaussian displacement distributions in Newtonian and non-Newtonian flows through porous media.

We use displacement encoding pulsed field gradient (PFG) nuclear magnetic resonance to measure Fourier components S(q) of flow displacement distributions P(zeta) with mean displacement (zeta) for Newtonian and non-Newtonian flows through rocks and bead packs. Displacement distributions are non-Gaussian; hence, there are finite terms above second order in the cumulant expansion of ln(S(q)). We describe an algorithm for an optimal self-consistent cumulant analysis of data, which can be used to obtain the first three (central) moments of a non-Gaussian P(zeta), with error bars. The analysis is applied to Newtonian and non-Newtonian flows in rocks and beads. Flow with shear-thinning xanthan solution produces a 15.6+/-2.3% enhancement of the variance sigma(2) of displacement distributions when compared to flow experiments with water.

Volatile organic compounds as biomarkers of bladder cancer: Sensitivity and specificity using trained sniffer dogs.

In a previous canine study, we demonstrated that volatile organic compounds specific to bladder cancer are present in urine headspace, subsequently showing that up to 70% of tumours can be correctly classified using an electronic nose. This study aimed to evaluate the sensitivity and specificity which can be achieved by a group of four trained dogs. In a series of 30 double-blind test runs, each consisting of one bladder cancer urine sample placed alongside six controls, the highest sensitivity achieved by the best performing dog was 73% (95% CI 55-86%), with the group as a whole correctly identifying the cancer samples 64% (95% CI 55-73%) of the time. Specificity of the dogs individually ranged from 92% (95% CI 82-97%) for urine samples obtained from healthy, young volunteers down to 56% (95% CI 42-68%) for those taken from older patients with non-cancerous urological disease. Odds ratio comparisons confirmed a significant decrease in performance as the extent of urine dipstick abnormality and/or pathology amongst the control population increased. Importantly, however, statistical analysis indicated that covariates such as smoking, gender and age, as well as blood, protein and /or leucocytes in the urine did not significantly alter the odds of response to the cancer samples. Our results provide further evidence that volatile biomarkers for bladder cancer exist in urine headspace, and that these have the potential to be exploited for diagnosis.

Incorporating movement into models of grey seal population dynamics.

1. One of the most difficult problems in developing spatially explicit models of population dynamics is the validation and parameterization of the movement process. We show how movement models derived from capture-recapture analysis can be improved by incorporating them into a spatially explicit metapopulation model that is fitted to a time series of abundance data. 2. We applied multisite capture-recapture analysis techniques to photo-identification data collected from female grey seals at the four main breeding colonies in the North Sea between 1999 and 2001. The best-fitting movement models were then incorporated into state-space metapopulation models that explicitly accounted for demographic and observational stochasticity. 3. These metapopulation models were fitted to a 20-year time series of pup production data for each colony using a Bayesian approach. The best-fitting model, based on the Akaike Information Criterion (AIC), had only a single movement parameter, whose confidence interval was 82% less than that obtained from the capture-recapture study, but there was some support for a model that included an effect of distance between colonies. 4. The state-space modelling provided improved estimates of other demographic parameters. 5. The incorporation of movement, and the way in which it was modelled, affected both local and regional dynamics. These differences were most evident as colonies approached their carrying capacities, suggesting that our ability to discriminate between models should improve as the length of the grey seal time series increases.