Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) allows a fast and reliable bacterial identification from culture plates. Direct analysis of clinical ...samples may increase its usefulness in samples in which a fast identification of microorganisms can guide empirical treatment, such as blood cultures (BC). Three hundred and thirty BC, reported as positive by the automated BC incubation device, were processed by conventional methods for BC processing, and by a fast method based on direct MALDI-TOF MS. Three hundred and eighteen of them yield growth on culture plates, and 12 were false positive. The MALDI-TOF MS-based method reported that no peaks were found, or the absence of a reliable identification profile, in all these false positive BC. No mixed cultures were found. Among these 318 BC, we isolated 61 Gram-negatives (GN), 239 Gram-positives (GP) and 18 fungi. Microorganism identifications in GN were coincident with conventional identification, at the species level, in 83.3% of BC and, at the genus level, in 96.6%. In GP, identifications were coincident with conventional identification in 31.8% of BC at the species level, and in 64.8% at the genus level. Fungaemia was not reliably detected by MALDI-TOF. In 18 BC positive for Candida species (eight C. albicans, nine C. parapsilosis and one C. tropicalis), no microorganisms were identified at the species level, and only one (5.6%) was detected at the genus level. The results of the present study show that this fast, MALDI-TOF MS-based method allows bacterial identification directly from presumptively positive BC in a short time (<30 min), with a high accuracy, especially when GN bacteria are involved.
Background and purpose
Specific respiratory tract infections, including COVID‐19, may cause smell and/or taste disorders (STDs) with increased frequency. The aim was to determine whether new‐onset ...STDs are more frequent amongst COVID‐19 patients than influenza patients.
Method
This was a case–control study including hospitalized patients of two tertiary care centres. Consecutive patients positive for COVID‐19 polymerase chain reaction (cases) and patients positive for influenza polymerase chain reaction (historical control sample) were assessed during specific periods, employing a self‐reported STD questionnaire.
Results
Seventy‐nine cases and 40 controls were included. No significant differences were found in basal features between the two groups. New‐onset STDs were significantly more frequent amongst cases (31, 39.2%) than in the control group (5, 12.5 %) adjusted odds ratio 21.4 (2.77–165.4, P = 0.003). COVID‐19 patients with new‐onset STDs were significantly younger than COVID‐19 patients without STDs (52.6 ± 17.2 vs. 67.4 ± 15.1, P < 0.001). Amongst COVID‐19 patients who presented STDs, 22 (70.9%) recalled an acute onset and it was an initial manifestation in 11 (35.5%). Twenty‐five (80.6%) presented smell disorders (mostly anosmia, 14, 45.2%) and 28 (90.3%) taste disorders (mostly ageusia, 14, 45.2%). Only four (12.9 %) reported concomitant nasal obstruction. The mean duration of STD was 7.5 ± 3.2 days and 12 patients (40%) manifested complete recovery after 7.4 ± 2.3 days of onset.
Conclusion
New‐onset STDs were significantly more frequent amongst COVID‐19 patients than influenza patients; they usually had an acute onset and were commonly an initial manifestation. The use of STD assessment in anamnesis as a hint for COVID‐19 and to support individuals’ self‐isolation in the current epidemic context is suggested.
Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT (Computed ...Tomography) scanners and RT-PCR testing are not available in most medical centers and hence in many cases CXR images become the most time/cost effective tool for assisting clinicians in making decisions. Deep learning neural networks have a great potential for building COVID-19 triage systems and detecting COVID-19 patients, especially patients with low severity. Unfortunately, current databases do not allow building such systems as they are highly heterogeneous and biased towards severe cases. This article is threefold: (i) we demystify the high sensitivities achieved by most recent COVID-19 classification models, (ii) under a close collaboration with Hospital Universitario Clínico San Cecilio, Granada, Spain, we built COVIDGR-1.0, a homogeneous and balanced database that includes all levelsof severity, from normal with Positive RT-PCR, Mild, Moderate to Severe. COVIDGR-1.0 contains 426 positive and 426 negative PA (PosteroAnterior) CXR views and (iii) we propose COVID Smart Data based Network (COVID-SDNet) methodology for improving the generalization capacity of COVID-classification models. Our approach reaches good and stable results with an accuracy of 97.72% ± 0.95%, 86.90% ± 3.20%, 61.80% ± 5.49% in severe, moderate and mild COVID-19 severity levels. Our approach could help in the early detection of COVID-19. COVIDGR-1.0 along with the severity level labels are available to the scientific community through this link https://dasci.es/es/transferencia/ open-data/covidgr/.
The study of lightmatter interaction has led to important advances in quantum optics and enabled numerous technologies. Over recent decades, progress has been made in increasing the strength of this ...interaction at the single-photon level. More recently, a major achievement has been the demonstration of the so-called strong coupling regime1,2, a key advancement enabling progress in quantum information science. Here, we demonstrate lightmatter interaction over an order of magnitude stronger than previously reported, reaching the nonperturbative regime of ultrastrong coupling (USC). We achieve this using a superconducting articial atom tunably coupled to the electromagnetic continuum of a one-dimensional waveguide. For the largest coupling, the spontaneous emission rate of the atom exceeds its transition frequency. In this USC regime, the description of atom and light as distinct entities breaks down, and a new description in terms of hybrid states is required3,4. Beyond lightmatter interaction itself, the tunability of our system makes it a promising tool to study a number of important physical systems, such as the well-known spin-boson5 and Kondo models6.
Frugivores are highly variable in their contribution to fruit removal in plant populations. However, data are lacking on species-specific variation in two central aspects of seed dispersal, distance ...of dispersal and probability of dispersal among populations through long-distance transport. We used DNA-based genotyping techniques on Prunus mahaleb seeds dispersed by birds (small- and medium-sized passerines) and carnivorous mammals to infer each seed's source tree, dispersal distance, and the probability of having originated from outside the study population. Small passerines dispersed most seeds short distances (50% dispersed <51 m from source trees) and into covered microhabitats. Mammals and medium-sized birds dispersed seeds long distances (50% of mammals dispersed seeds >495 m, and 50% of medium-sized birds dispersed seeds to > 110 m) and mostly into open microhabitats. Thus, dispersal distance and microhabitat of seed deposition were linked through the contrasting behaviors of different frugivores. When the quantitative contribution to fruit removal was accounted for, mammals were responsible for introducing two-thirds of the immigrant seeds into the population, whereas birds accounted for one-third. Our results demonstrate that frugivores differ widely in their effects on seed-mediated gene flow. Despite highly diverse coteries of mutualistic frugivores dispersing seeds, critical long-distance dispersal events might rely on a small subset of large species. Population declines of these key frugivore species may seriously impair seed-mediated gene flow in fragmented landscapes by truncating the long-distance events and collapsing seed arrival to a restricted subset of available microsites.
Although ferromagnets have many applications, their large magnetization and the resulting energy cost for switching magnetic moments bring into question their suitability for reliable low-power ...spintronic devices. Non-collinear antiferromagnetic systems do not suffer from this problem, and often have extra functionalities: non-collinear spin order may break space-inversion symmetry and thus allow electric-field control of magnetism, or may produce emergent spin-orbit effects that enable efficient spin-charge interconversion. To harness these traits for next-generation spintronics, the nanoscale control and imaging capabilities that are now routine for ferromagnets must be developed for antiferromagnetic systems. Here, using a non-invasive, scanning single-spin magnetometer based on a nitrogen-vacancy defect in diamond, we demonstrate real-space visualization of non-collinear antiferromagnetic order in a magnetic thin film at room temperature. We image the spin cycloid of a multiferroic bismuth ferrite (BiFeO
) thin film and extract a period of about 70 nanometres, consistent with values determined by macroscopic diffraction. In addition, we take advantage of the magnetoelectric coupling present in BiFeO
to manipulate the cycloid propagation direction by an electric field. Besides highlighting the potential of nitrogen-vacancy magnetometry for imaging complex antiferromagnetic orders at the nanoscale, these results demonstrate how BiFeO
can be used in the design of reconfigurable nanoscale spin textures.
Organic electronics is emerging for large-area applications such as photovoltaic cells, rollable displays or electronic paper. Its future development and integration will require a simple, low-power ...organic memory, that can be written, erased and readout electrically. Here we demonstrate a non-volatile memory in which the ferroelectric polarisation state of an organic tunnel barrier encodes the stored information and sets the readout tunnel current. We use high-sensitivity piezoresponse force microscopy to show that films as thin as one or two layers of ferroelectric poly(vinylidene fluoride) remain switchable with low voltages. Submicron junctions based on these films display tunnel electroresistance reaching 1,000% at room temperature that is driven by ferroelectric switching and explained by electrostatic effects in a direct tunnelling regime. Our findings provide a path to develop low-cost, large-scale arrays of organic ferroelectric tunnel junctions on silicon or flexible substrates.
The capacity to propagate magnetic domain walls with spin-polarized currents underpins several schemes for information storage and processing using spintronic devices. A key question involves the ...internal structure of the domain walls, which governs their response to certain current-driven torques such as the spin Hall effect. Here we show that magnetic microscopy based on a single nitrogen-vacancy defect in diamond can provide a direct determination of the internal wall structure in ultrathin ferromagnetic films under ambient conditions. We find pure Bloch walls in Ta/CoFeB(1 nm)/MgO, while left-handed Néel walls are observed in Pt/Co(0.6 nm)/AlOx. The latter indicates the presence of a sizable interfacial Dzyaloshinskii-Moriya interaction, which has strong bearing on the feasibility of exploiting novel chiral states such as skyrmions for information technologies.
Most epistemic uncertainty within data-driven landslide susceptibility assessment results from errors in landslide inventories, difficulty in identifying and mapping landslide causes and decisions ...related with the modelling procedure. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from: (i) the selection of the statistical method; (ii) the selection of the terrain mapping unit; and (iii) the selection of the feature type to represent landslides in the model (polygon versus point). The work is performed in a single study area (Silveira Basin - 18.2km2 - Lisbon Region, Portugal) using a unique database of geo-environmental landslide predisposing factors and an inventory of 82 shallow translational slides.
The logistic regression, the discriminant analysis and two versions of the information value were used and we conclude that multivariate statistical methods perform better when computed over heterogeneous terrain units and should be selected to assess landslide susceptibility based on slope terrain units, geo-hydrological terrain units or census terrain units. However, evidence was found that the chosen terrain mapping unit can produce greater differences on final susceptibility results than those resulting from the chosen statistical method for modelling.
The landslide susceptibility should be assessed over grid cell terrain units whenever the spatial accuracy of landslide inventory is good. In addition, a single point per landslide proved to be efficient to generate accurate landslide susceptibility maps, providing the landslides are of small size, thus minimizing the possible existence of heterogeneities of predisposing factors within the landslide boundary.
Although during last years the ROC curves have been preferred to evaluate the susceptibility model's performance, evidence was found that the model with the highest AUC ROC is not necessarily the best landslide susceptibility model, namely when terrain mapping units are heterogeneous in size and reduced in number.
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•Multivariate statistical methods perform better when computed over heterogeneous terrain mapping units.•Landslide susceptibility should be assessed over grid cells when the spatial accuracy of landslide inventory is good.•A single point per landslide proved to be efficient to generate accurate landslide susceptibility maps•The model with the highest AUC ROC is not necessarily the best landslide susceptibility model.
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