386 research outputs found

    Slocum gliders provide accurate near real-time estimates of baleen whale presence from human-reviewed passive acoustic detection information

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Baumgartner, M. F., Bonnell, J., Corkeron, P. J., Van Parijs, S. M., Hotchkin, C., Hodges, B. A., Thornton, J. B., Mensi, B. L., & Bruner, S. M. Slocum gliders provide accurate near real-time estimates of baleen whale presence from human-reviewed passive acoustic detection information. Frontiers in Marine Science, 7, (2020):100, doi:10.3389/fmars.2020.00100.Mitigating the effects of human activities on marine mammals often depends on monitoring animal occurrence over long time scales, large spatial scales, and in real time. Passive acoustics, particularly from autonomous vehicles, is a promising approach to meeting this need. We have previously developed the capability to record, detect, classify, and transmit to shore information about the tonal sounds of baleen whales in near real time from long-endurance ocean gliders. We have recently developed a protocol by which a human analyst reviews this information to determine the presence of marine mammals, and the results of this review are automatically posted to a publicly accessible website, sent directly to interested parties via email or text, and made available to stakeholders via a number of public and private digital applications. We evaluated the performance of this system during two 3.75-month Slocum glider deployments in the southwestern Gulf of Maine during the spring seasons of 2015 and 2016. Near real-time detections of humpback, fin, sei, and North Atlantic right whales were compared to detections of these species from simultaneously recorded audio. Data from another 2016 glider deployment in the same area were also used to compare results between three different analysts to determine repeatability of results both among and within analysts. False detection (occurrence) rates on daily time scales were 0% for all species. Daily missed detection rates ranged from 17 to 24%. Agreement between two trained novice analysts and an experienced analyst was greater than 95% for fin, sei, and right whales, while agreement was 83–89% for humpback whales owing to the more subjective process for detecting this species. Our results indicate that the presence of baleen whales can be accurately determined using information about tonal sounds transmitted in near real-time from Slocum gliders. The system is being used operationally to monitor baleen whales in United States, Canadian, and Chilean waters, and has been particularly useful for monitoring the critically endangered North Atlantic right whale throughout the northwestern Atlantic Ocean.Funding for this project was provided by the Environmental Security Technology Certification Program of the U.S. Department of Defense and the U.S. Navy’s Living Marine Resources Program

    Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin

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    Population structure and genome-wide linkage disequilibrium (LD) were investigated in 192 Hordeum vulgare accessions providing a comprehensive coverage of past and present barley breeding in the Mediterranean basin, using 50 nuclear microsatellite and 1,130 DArT® markers. Both clustering and principal coordinate analyses clearly sub-divided the sample into five distinct groups centred on key ancestors and regions of origin of the germplasm. For given genetic distances, large variation in LD values was observed, ranging from closely linked markers completely at equilibrium to marker pairs at 50 cM separation still showing significant LD. Mean LD values across the whole population sample decayed below r 2 of 0.15 after 3.2 cM. By assaying 1,130 genome-wide DArT® markers, we demonstrated that, after accounting for population substructure, current genome coverage of 1 marker per 1.5 cM except for chromosome 4H with 1 marker per 3.62 cM is sufficient for whole genome association scans. We show, by identifying associations with powdery mildew that map in genomic regions known to have resistance loci, that associations can be detected in strongly stratified samples provided population structure is effectively controlled in the analysis. The population we describe is, therefore, shown to be a valuable resource, which can be used in basic and applied research in barle

    Mapping adaptation of barley to droughted environments

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    Identifying barley genomic regions influencing the response of yield and its components to water deficits will aid in our understanding of the genetics of drought tolerance and the development of more drought tolerant cultivars. We assembled a population of 192 genotypes that represented landraces, old, and contemporary cultivars sampling key regions around the Mediterranean basin and the rest of Europe. The population was genotyped with a stratified set of 50 genomic and EST derived molecular markers, 49 of which were Simple Sequence Repeats (SSRs), which revealed an underlying population sub-structure that corresponded closely to the geographic regions in which the genotypes were grown. A more dense whole genome scan was generated by using Diversity Array Technology (DArT®) to generate 1130 biallelic markers for the population. The population was grown at two contrasting sites in each of seven Mediterranean countries for harvest 2004 and 2005 and grain yield data collected. Mean yield levels ranged from 0.3 to 6.2 t/ha, with highly significant genetic variation in low-yielding environments. Associations of yield with barley genomic regions were then detected by combining the DArT marker data with the yield data in mixed model analyses for the individual trials, followed by multiple regression of yield on markers to identify a multi-locus subset of significant markers/QTLs. QTLs exhibiting a pre-defined consistency across environments were detected in bins 4, 6, 6 and 7 on barley chromosomes 3H, 4H, 5H and 7H respectivel

    Targeting AMP-activated kinase impacts hepatocellular cancer stem cells induced by long-term treatment with sorafenib

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    Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. HCC treatment is hindered by the frequent emergence of chemoresistance to the multikinase inhibitor sorafenib, which has been related to the presence of cancer stem cells (CSCs) that self‐renew and often escape therapy. The key metabolic sensor AMP‐activated kinase (AMPK) has recently been recognized as a tumour growth regulator. In this study, we aimed to elucidate the role of AMPK in the development of a stem cell phenotype in HCC cells. To this end, we enriched the CSC population in HCC cell lines that showed increased expression of drug resistance (ALDH1A1, ABCB1A) and stem cell (CD133, Nanog, Oct4, alpha fetoprotein) markers and demonstrated their stemness phenotype. These cells were refractory to sorafenib‐induced cell death. We report that sorafenib‐resistant cells had lower levels of total and phosphorylated AMPK as well as its downstream substrate, ACC, compared with the parental cells. Interestingly, AMPK knockdown with siRNA or inhibition with dorsomorphin increased the expression of stem cell markers in parental cells and blocked sorafenib‐induced cell death. Conversely, the upregulation of AMPK, either by transfection or by pharmacological activation with A‐769662, decreased the expression of ALDH1A1, ABCB1A, CD133, Nanog, Oct4, and alpha fetoprotein, and restored sensitivity to sorafenib. Analysis of the underlying mechanism points to hypoxia‐inducible factor HIF‐1α as a regulator of stemness. In vivo studies in a xenograft mouse model demonstrated that stem‐like cells have greater tumourigenic capacity. AMPK activation reduced xenograft tumour growth and decreased the expression of stem cell markers. Taken together, these results indicate that AMPK may serve as a novel target to overcome chemoresistance in HCC

    Effects of JWH015 in cytokine secretion in primary human keratinocytes and fibroblasts and its suitability for topical/transdermal delivery

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    BACKGROUND: JWH015 is a cannabinoid (CB) receptor type 2 agonist that produces immunomodulatory effects. Since skin cells play a key role in inflammatory conditions and tissue repair, we investigated the ability of JWH015 to promote an anti-inflammatory and pro-wound healing phenotype in human primary skin cells. METHODS: Human primary keratinocytes and fibroblasts were stimulated with lipopolysaccharide. The mRNA expression of cannabinoid receptors was determined using RT-PCR. The effects of JWH015 (0.05, 0.1, 0.5, and 1 µM) in pro- and anti-inflammatory factors were tested in lipopolysaccharide-stimulated cells. A scratch assay, using a co-culture of keratinocytes and fibroblasts, was used to test the effects of JWH015 in wound healing. In addition, the topical and transdermal penetration of JWH015 was studied in Franz diffusion cells using porcine skin and LC-MS. RESULTS: The expression of CB1 and CB2 receptors (mRNA) and the production of pro- and anti-inflammatory factors enhanced in keratinocytes and fibroblasts following lipopolysaccharide stimulation. JWH015 reduced the concentration of major pro-inflammatory factors (IL-6 and MCP-1) and increased the concentration of a major anti-inflammatory factor (TGF-β) in lipopolysaccharide-stimulated cells. JWH015 induced a faster scratch gap closure. These JWH015’seffects were mainly modulated through both CB1 and CB2 receptors. Topically administered JWH015 was mostly retained in the skin and displayed a sustained and low level of transdermal permeation. CONCLUSIONS: Our findings suggest that targeting keratinocytes and fibroblasts with cannabinoid drugs could represent a therapeutic strategy to resolve peripheral inflammation and promote tissue repair

    Three dimensional reconstruction to visualize atrial fibrillation activation patterns on curved atrial geometry

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    Background: The rotational activation created by spiral waves may be a mechanism for atrial fibrillation (AF), yet it is unclear how activation patterns obtained from endocardial baskets are influenced by the 3D geometric curvature of the atrium or 'unfolding' into 2D maps. We develop algorithms that can visualize spiral waves and their tip locations on curved atrial geometries. We use these algorithms to quantify differences in AF maps and spiral tip locations between 3D basket reconstructions, projection onto 3D anatomical shells and unfolded 2D surfaces. Methods: We tested our algorithms in N = 20 patients in whom AF was recorded from 64-pole baskets (Abbott, CA). Phase maps were generated by non-proprietary software to identify the tips of spiral waves, indicated by phase singularities. The number and density of spiral tips were compared in patient-specific 3D shells constructed from the basket, as well as 3D maps from clinical electroanatomic mapping systems and 2D maps. Results: Patients (59.4±12.7 yrs, 60% M) showed 1.7±0.8 phase singularities/patient, in whom ablation terminated AF in 11/20 patients (55%). There was no difference in the location of phase singularities, between 3D curved surfaces and 2D unfolded surfaces, with a median correlation coefficient between phase singularity density maps of 0.985 (0.978-0.990). No significant impact was noted by phase singularities location in more curved regions or relative to the basket location (p>0.1). Conclusions: AF maps and phase singularities mapped by endocardial baskets are qualitatively and quantitatively similar whether calculated by 3D phase maps on patient-specific curved atrial geometries or in 2D. Phase maps on patient-specific geometries may be easier to interpret relative to critical structures for ablation planning

    Atrial fibrillation signatures on intracardiac electrograms identified by deep learning

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    Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events'. This may delay or misdirect therapy. Objective: We hypothesized that deep learning (DL) can accurately classify AF from AT by revealing electrogram (EGM) signatures. Methods: We studied 86 patients in whom the diagnosis of AF or AT was established at electrophysiological study (25 female, 65 ± 11 years). Custom DL architectures were trained to identify AF using N = 29,340 unipolar and N = 23,760 bipolar EGM segments. We compared DL to traditional classifiers based on rate or regularity. We explained DL using computer models to assess the impact of controlled variations in shape, rate and timing on AF/AT classification in 246,067 EGMs reconstructed from clinical data. Results: DL identified AF with AUC of 0.97 ± 0.04 (unipolar) and 0.92 ± 0.09 (bipolar). Rule-based classifiers misclassified ∼10-12% of cases. DL classification was explained by regularity in EGM shape (13%) or timing (26%), and rate (60%; p 15% timing variation, <0.48 correlation in beat-to-beat EGM shapes and CL < 190 ms (p < 0.001). Conclusions: Deep learning of intracardiac EGMs can identify AF or AT via signatures of rate, regularity in timing or shape, and specific EGM shapes. Future work should examine if these signatures differ between different clinical subpopulations with AF
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