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826 results for “low level”
Data from: Fitness trade-offs explain low levels of persister cells in the opportunistic pathogen Pseudomonas aeruginosa
Microbial populations often contain a fraction of slow-growing persister cells that withstand antibiotics and other stress factors. Current theoretical models predict that persistence levels should reflect a stable state in which the survival advantage of persisters under adverse conditions is balanced with the direct growth cost impaired under favourable growth conditions, caused by the nonreplication of persister cells. Based on this direct growth cost alone, however, it remains challenging to explain the observed low levels of persistence (<<1%) seen in the populations of many species. Here, we present data from the opportunistic human pathogen Pseudomonas aeruginosa that can explain this discrepancy by revealing various previously unknown costs of persistence. In particular, we show that in the absence of antibiotic stress, increased persistence is traded off against a lengthened lag phase as well as a reduced survival ability during stationary phase. We argue that these pleiotropic costs contribute to the very low proportions of persister cells observed among natural P. aeruginosa isolates (3 × 10−8–3 × 10−4) and that they can explain why strains with higher proportions of persister cells lose out very quickly in competition assays under favourable growth conditions, despite a negligible difference in maximal growth rate. We discuss how incorporating these trade-offs could lead to models that can better explain the evolution of persistence in nature and facilitate the rational design of alternative therapeutic strategies for treating infectious diseases.
Data Supporting High-Level to Low-Level Requirements Coverage Reviewing with Large Language Models
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Figure 26 in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 26. Distribution of A, Pseudoanthidium kaspareki; B, P. rozeni.
Figure 15. Neotype Anthidium stigmaticorne. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 15. Neotype Anthidium stigmaticorne. A, dorsal view; B, labels; C, face; D, lateral view.
Figure 14. Lectotype Anthidium frontale. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 14. Lectotype Anthidium frontale. A, dorsal view; B, face; C, labels; D, lateral view.
Figure 5. Lectotype, Pseudoanthidium nanum. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 5. Lectotype, Pseudoanthidium nanum. A, lateral view; B, dorsal view; C, labels.
Figure 26 in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 26. Distribution of A, Pseudoanthidium kaspareki; B, P. rozeni.
Figure 15. Neotype Anthidium stigmaticorne. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 15. Neotype Anthidium stigmaticorne. A, dorsal view; B, labels; C, face; D, lateral view.
Figure 14. Lectotype Anthidium frontale. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 14. Lectotype Anthidium frontale. A, dorsal view; B, face; C, labels; D, lateral view.
Figure 5. Lectotype, Pseudoanthidium nanum. A in Paraphyly and low levels of genetic divergence in morphologically distinct taxa: revision of the Pseudoanthidium scapulare complex of carder bees (Apoidea: Megachilidae: Anthidiini)
Figure 5. Lectotype, Pseudoanthidium nanum. A, lateral view; B, dorsal view; C, labels.
Code - Effects of horizontal resolution and updated surface data on the simulated low-level winds over Incheon International Airport
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Single column 1D radiative transfer simulations for a case study of low-level-stratus clouds in the central Arctic during PS106
<p>The collection of datasets published contain the input parameters and output simulations from a single column 1D radiative transfer simulations using the <strong>R</strong>apid <strong>R</strong>adiative <strong>T</strong>ransfer <strong>M</strong>odel for <strong>G</strong>eneral Circulation Model (GCM) applications (RRTMG).</p> <p>The simulations are focused on a selected case study of low-level-stratus clouds during the PS106 research cruise conducted in 2017 in the Central Arctic. The simulations are based on remote sensing observations, which were synergistically used with the Cloudnet algorithm to derive macro and microphysical properties of clouds. The atmospheric profiles of temperature, pressure, and ozone are from ERA5 (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) and values of surface albedo from CERES (Clouds and the Earth's Radiant Energy System) SYN1deg Ed. 4.1.</p>
Low Level Laser Therapy for Radiation Induced Dermatitis in H & N Squamous Cell Carcinoma
ClinicalTrials.gov study NCT02384434. IPD Sharing: NO. Countries: 1. Publications: 0.
Low Level Diode Laser Versus Topical Chamomile in Management of Chemotherapy Induced Oral Mucositis
ClinicalTrials.gov study NCT06214273. IPD Sharing: NO. Countries: 0. Publications: 4.
High Level Pulsed Heat Versus Low Level Steady Heat in Subjects With Chronic Low Back Pain
ClinicalTrials.gov study NCT04109703. IPD Sharing: NO. Countries: 1. Publications: 0.
Assessment of Visual Performance in Patients With Low Levels of Astigmatism
ClinicalTrials.gov study NCT00842231. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study to Assess the Effectiveness of an Investigational Drug in Elderly Subjects With Low Vitamin D Levels (0822A-009)
ClinicalTrials.gov study NCT00242476. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Prognostic Value of Serum Erythropoietin Level,Ferritin Level and Fibrinogen in Adult Low Risk MDS
ClinicalTrials.gov study NCT04573686. IPD Sharing: Not stated. Countries: 0. Publications: 6.
Study of Over-The-Counter Use of Low Level Laser Light Therapy for Body Contouring of the Waist, Hips and Thighs
ClinicalTrials.gov study NCT02167867. IPD Sharing: NO. Countries: 1. Publications: 0.
Anxiety Level Among Patients With Chronic Low Back Pain
ClinicalTrials.gov study NCT06404788. IPD Sharing: NO. Countries: 0. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.