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57 results for “SHERLOCK”
Sherlock
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Sherlock Camera Trap Dataset 9
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 7
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 8
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 6
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 4
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 5
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 3
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
Sherlock Camera Trap Dataset 2
<p>Part of the camera trap image dataset used for the 'main' Sherlock test. See the base dataset for links to the remaining data. </p>
The SHERLOCK PIPEline: Searching for Hints of Exoplanets fRom Lightcurves Of spaCe-based seeKers
<p>The arrival of space missions such as Kepler/K2 and TESS has revolutionized exoplanets' detection, producing a vast amount of data that scientists need to analyze. This situation will keep increasing shortly thanks to the ESA PLATO mission, mainly devoted to finding Earth-like planets orbiting Sun-like stars, which will be launched in 2025-2026 (Rauer et al. 2014). This poster presents SHERLOCK, a robust and easy-to-use end-to-end pipeline to search for planet candidates, vet signals, perform a statistical validation, bayesian fit, and compute observational windows from ground-based facilities to trigger a follow-up campaign. All these steps are executed with just a few lines of code, which makes SHERLOCK an optimal ready-to-use code for any planetary search program.</p>
Rapid and accurate species identification for ecological studies and monitoring using CRISPR-based SHERLOCK
<p>One of the most foundational aspects of ecological studies and monitoring is accurate species identification, but cryptic speciation and observer error can confound phenotype-based identification. The CRISPR-Cas toolkit has facilitated remarkable advances in many scientific disciplines, but the fields of ecology and conservation biology have yet to fully embrace this powerful technology. The recently developed CRISPR-Cas13a platform SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing) enables highly accurate taxonomic identification and has all the characteristics needed to transition to ecological and environmental disciplines. Here we conducted a series of proof of principle experiments to characterize SHERLOCK's ability to accurately, sensitively, and rapidly distinguished three fish species (two with protected status and one non-native) co-occurring in the San Francisco Estuary which are easily misidentified in the field. We improved SHERLOCK's ease of field deployment by combining its rapid isothermal amplification and CRISPR genetic identification with a minimally invasive and extraction-free DNA collection protocol as well as the option of instrument-free lateral flow detection. This approach opens the door for redefining how, where and by whom genetic identifications occur in the future.</p>
FIGURE 8. Bayesian inference consensus using a in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 8. Bayesian inference consensus using a Markov chain Monte Carlo algorithm applied to mitochondrial sequences of Cyt b fragments of 510 bp. The values over the nodes refer to bootstrap value by maximum parsimony. T. dimidiata and T. infestans were used as outgroup. Accession code of GenBank in the text.
FIGURE 7 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 7. Triatoma bahiensis (2n= 22 chromosomes), male meiosis, C-banding. (A) Early first meiotic prophase: several heterochromatic chromocenters spread in the nucleus (arrowheads). A large chromocenter consists of the association of sex chromosomes plus autosomal bivalents (arrow). (B) Diplotene stage: the association between two autosomal bivalents (arrowheads) with associated sex chromosomes (arrow) is observed. (C) Diakinesis or later diplotene: ten bivalents and both sex chromosomes (XY) are clearly identified. The Y chromosome is entirely C-heterochromatic (arrow) and the X chromosome is euchromatic.
FIGURE 6 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 6. Factorial maps in the plane of the two discriminant factors of wing shape variation (canonical variables 1 and 2, or CV1 and CV2) presenting the distribution of specimens of Triatoma bahiensis (Tba, dashed polygon, open symbols) and Triatoma lenti (Tle, black polygon, closed symbols). Males are represented by squares and females are represented by circles. Drawings to the right of the plot show the consensus conformation of the wings of the species (see landmarks in Fig. 2). Arrows indicate the differences in wings of both species (see text for details).
FIGURE 5 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 5. Ventral view of T. bahiensis: A—prothorax, B—mesothorax and C—metathorax; Ventral view of T. lenti: D—prothorax, E—mesothorax and F—metathorax
FIGURE 4 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 4. Egg exochorion detail via scanning electron microscopy in A—T. bahiensis and B—T. lenti. Scutellum detail via scanning electron microscopy in C—T. bahiensis and D—T. lenti.
FIGURE 3. A in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 3. A—Triatoma bahiensis female, dorsal view; B—Triatoma bahiensis female, ventral view; C—Triatoma lenti female, dorsal view; D—Triatoma lenti female, ventral view.
FIGURE 1 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 1. Type-material analyzed in the present study. A. Triatoma bahiensis Sherlock & Serafim, 1967, revalidated. B. Triatoma pessoai var. bahiensis Sherlock & Serafim (1972). C. Triatoma lenti.
FIGURE 2 in Revalidation of Triatoma bahiensis Sherlock & Serafim, 1967 (Hemiptera: Reduviidae) and phylogeny of the T. brasiliensis species complex
FIGURE 2. Right wing of Triatoma bahiensis with the seven landmarks used in morphometric analysis. Following Bookstein (1990), all points correspond to type I landmarks (venation intersections).
SHERLOCK 3CG vs. Fluoroscopy in Implantation of PICC-Line
ClinicalTrials.gov study NCT02929368. IPD Sharing: NO. Countries: 1. Publications: 1.
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