A Hidden Markov Movement Model for rapidly identifying behavioral states from animal tracks

Electronic telemetry is frequently used to document animal movement through time. Methods that can identify underlying behaviors driving specific movement patterns can help us understand how and why animals use available space, thereby aiding conservation and management efforts. For aquatic animal tracking data with significant measurement error, a Bayesian state‐space model called the first‐Difference Correlated Random Walk with Switching (DCRWS) has often been used for this purpose. However, for aquatic animals, highly accurate tracking data are now becoming more common. We developed a new hidden Markov model (HMM) for identifying behavioral states from animal tracks with negligible error, called the hidden Markov movement model (HMMM). We implemented as the basis for the HMMM the process equation of the DCRWS, but we used the method of maximum likelihood and the R package TMB for rapid model fitting. The HMMM was compared to a modified version of the DCRWS for highly accurate tracks, the DCRWS [Formula: see text] , and to a common HMM for animal tracks fitted with the R package moveHMM. We show that the HMMM is both accurate and suitable for multiple species by fitting it to real tracks from a grey seal, lake trout, and blue shark, as well as to simulated data. The HMMM is a fast and reliable tool for making meaningful inference from animal movement data that is ideally suited for ecologists who want to use the popular DCRWS implementation and have highly accurate tracking data. It additionally provides a groundwork for development of more complex modeling of animal movement with TMB. To facilitate its uptake, we make it available through the R package swim

Patient-reported outcomes in patients with hematological relapse or progressive disease:a longitudinal observational study

Abstract Background Patients with hematological cancer who experience relapse or progressive disease often face yet another line of treatment and continued mortality risk that could increase their physical and emotional trauma and worsen their health-related quality of life. Healthcare professionals who use patient-reported outcomes to identify who will have specific sensitivities in particular health-related quality of life domains may be able to individualize and target treatment and supportive care, both features of precision medicine. Here, in a cohort of patients with relapsed or progressive hematological cancer, we sought to identify health-related quality of life domains in which they experienced deterioration after relapse treatment and to investigate health-related quality of life patterns. Method Patients were recruited in connection with a precision medicine study at the Department of Hematology, Aalborg University Hospital. They completed the European Organization for Research and Treatment of Cancer questionnaire and the Hospital Anxiety and Depression Scale at baseline and at 3, 6, 9, and 12 months after the relapse diagnosis or progressive cancer. Modes of completion were electronically or on paper. Clinically relevant changes from baseline to 12 months were interpreted according to Cocks’ guidelines. We quantified the number of patients with moderate or severe symptoms and functional problems and the number who experienced improvements or deterioration from baseline to 12 months. Results A total of 104 patients were included, of whom 90 (87%) completed baseline questionnaires and 50 (56%) completed the 12-month assessments. The three symptoms that patients most often reported as deteriorating were fatigue (18%), insomnia (18%), and diarrhea (18%). The three functions that patients most often reported as deteriorating were role (16%) and emotional (16%) and cognitive (16%) functioning. Conclusion In this study, patient-reported outcome data were useful for identifying negatively affected health-related quality of life domains in patients with relapsed or progressive hematological cancer. We identified patients experiencing deterioration in health-related quality of life during treatment and characterized a potential role for patient-reported outcomes in precision medicine to target treatment and supportive care in this patient group

Semaglutide treatment attenuates vessel remodelling in ApoE-/- mice following vascular injury and blood flow perturbation.

BACKGROUND AND AIMS Randomized clinical studies have shown a reduction in cardiovascular outcomes with glucagon-like peptide 1 receptor agonist (GLP-1RA) treatment with the hypothesized mechanisms being an underlying effect on atherosclerosis. Here, we aimed to assess the pharmacological effects of semaglutide in an atheroprone murine model that recapitulates central mechanisms related to vascular smooth muscle cell (VSMC) phenotypic switching and endothelial dysfunction known to operate within the atherosclerotic plaque. METHODS In study A, we employed an electrical current to the carotid artery in ApoE-/- mice to induce severe VSMC injury and death, after which the arteries were allowed to heal for 4 weeks. In study B, a constrictive cuff was added for 6 h at the site of the healed segment to induce a disturbance in blood flow. RESULTS Compared to vehicle, semaglutide treatment reduced the intimal and medial area by ∼66% (p = 0.007) and ∼11% (p = 0.0002), respectively. Following cuff placement, expression of the pro-inflammatory marker osteopontin and macrophage marker Mac-2 was reduced (p < 0.05) in the semaglutide-treated group compared to vehicle. GLP-1R were not expressed in murine carotid artery and human coronary vessels with and without atherosclerotic plaques, and semaglutide treatment did not affect proliferation of cultured primary human VSMCs. CONCLUSIONS Semaglutide treatment reduced vessel remodelling following electrical injury and blood flow perturbation in an atheroprone mouse model. This effect appears to be driven by anti-inflammatory and -proliferative mechanisms independent of GLP-1 receptor-mediated signalling in the resident vascular cells. This mechanism of action may be important for cardiovascular protection.This study was supported by a grant from the LifePharm Centre of In Vivo Pharmacology.S

Detection of solar-like oscillations from Kepler photometry of the open cluster NGC 6819

Asteroseismology of stars in clusters has been a long-sought goal because the assumption of a common age, distance and initial chemical composition allows strong tests of the theory of stellar evolution. We report results from the first 34 days of science data from the Kepler Mission for the open cluster NGC 6819 -- one of four clusters in the field of view. We obtain the first clear detections of solar-like oscillations in the cluster red giants and are able to measure the large frequency separation and the frequency of maximum oscillation power. We find that the asteroseismic parameters allow us to test cluster-membership of the stars, and even with the limited seismic data in hand, we can already identify four possible non-members despite their having a better than 80% membership probability from radial velocity measurements. We are also able to determine the oscillation amplitudes for stars that span about two orders of magnitude in luminosity and find good agreement with the prediction that oscillation amplitudes scale as the luminosity to the power of 0.7. These early results demonstrate the unique potential of asteroseismology of the stellar clusters observed by Kepler.Comment: 5 pages, 4 figures, accepted by ApJ (Lett.

SHREC2020 track:Multi-domain protein shape retrieval challenge

Proteins are natural modular objects usually composed of several domains, each domain bearing a specific function that is mediated through its surface, which is accessible to vicinal molecules. This draws attention to an understudied characteristic of protein structures: surface, that is mostly unexploited by protein structure comparison methods. In the present work, we evaluated the performance of six shape comparison methods, among which three are based on machine learning, to distinguish between 588 multi-domain proteins and to recreate the evolutionary relationships at the proteinand species levels of the SCOPe database. The six groups that participated in the challenge submitted a total of 15 sets of results. We observed that the performance of all the methods significantly decreases at the species level, suggesting that shape-only protein comparison is challenging for closely related proteins. Even if the dataset is limited in size (only 588 proteins are considered whereas more than 160,000 protein structures are experimentally solved), we think that this work provides useful insights into the current shape comparison methods performance, and highlights possible limitations to large-scale applications due to the computational cost

Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human Studies

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the HP 13C MRI Consensus Group as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality

Surface-based protein domains retrieval methods from a SHREC2021 challenge

publication dans une revue suite à la communication hal-03467479 (SHREC 2021: surface-based protein domains retrieval)International audienceProteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore of primary importance for their activity. In the present work, we assess the ability of different methods to detect such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone. Finally, the discussion permits to expose the results with respect to ones obtained in the previous contests for the extended method. The source codes of each presented method have been made available online

Seventeen Tidal Disruption Events from the First Half of ZTF Survey Observations: Entering a New Era of Population Studies

While tidal disruption events (TDEs) have long been heralded as laboratories for the study of quiescent black holes, the small number of known TDEs and uncertainties in their emission mechanism have hindered progress towards this promise. Here present 17 new TDEs that have been detected recently by the Zwicky Transient Facility along with Swift UV and X-ray follow-up observations. Our homogeneous analysis of the optical/UV light curves, including 22 previously known TDEs from the literature, reveals a clean separation of light curve properties with spectroscopic class. The TDEs with Bowen fluorescence features in their optical spectra have smaller blackbody radii, as well as longer rise times and higher disruption rates compared to the rest of the sample. The Bowen fluorescence mechanism requires a high density which can be reached at smaller radii, which in turn yields longer diffusion timescales. Thus, the difference in rise times suggests the pre-peak TDE light curves are governed not by the fallback timescale, but instead by the diffusion of photons through the tidal debris. The small subset of TDEs that show only helium emission lines in their spectra have the longest rise times, the highest luminosities and the lowest rates. We also report, for the first time, the detection of soft X-ray flares from a TDE on day timescales. Based on the fact the flares peak at a luminosity similar to the optical/UV blackbody luminosity, we attribute them to brief glimpses through a reprocessing layer that otherwise obscures the inner accretion flow