85 research outputs found

    Chemical fingerprinting of wood sampled along a pith-to-bark gradient for individual comparison and provenance identification

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    Background and Objectives: The origin of traded timber is one of the main questions in the enforcement of regulations to combat the illegal timber trade. Substantial efforts are still needed to develop techniques that can determine the exact geographical provenance of timber and this is vital to counteract the destructive effects of illegal logging, ranging from economical loss to habitat destruction. The potential of chemical fingerprints from pith-to-bark growth rings for individual comparison and geographical provenance determination is explored. Materials and Methods: A wood sliver was sampled per growth ring from four stem disks from four individuals of Pericopsis elata (Democratic Republic of the Congo) and from 14 stem disks from 14 individuals of Terminalia superba (Cote d'Ivoire and Democratic Republic of the Congo). Chemical fingerprints were obtained by analyzing these wood slivers with Direct Analysis in Real Time Time-Of-Flight Mass Spectrometry (DART TOFMS). Results: Individual distinction for both species was achieved but the accuracy was dependent on the dataset size and number of individuals included. As this is still experimental, we can only speak of individual comparison and not individual distinction at this point. The prediction accuracy for the country of origin increases with increasing sample number and a random sample can be placed in the correct country. When a complete disk is removed from the training dataset, its rings (samples) are correctly attributed to the country with an accuracy ranging from 43% to 100%. Relative abundances of ions appear to contribute more to differentiation compared to frequency differences. Conclusions: DART TOFMS shows potential for geographical provenancing but is still experimental for individual distinction; more research is needed to make this an established method. Sampling campaigns should focus on sampling tree cores from pith-to-bark, paving the way towards a chemical fingerprint database for species provenance

    Comparison of species classification models of mass spectrometry data : kernel discriminant analysis vs. random forest : a case study of Afrormosia (Pericopsis elata (Harms) Meeuwen)

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    Rationale: The genus Pericopsis includes four tree species of which only Pericopsis elata (Harms) Meeuwen is of commercial interest. Enforcement officers might have difficulties discerning this CITES-listed species from some other tropical African timber species. Therefore, we tested several methods to separate and identify these species rapidly in order to enable customs officials to uncover illegal trade. In this study, two classification methods using Direct Analysis in Real Time (DART) ionization coupled with Time-of-Flight Mass Spectrometry (DART-TOFMS) data to discern between several species are presented. Methods: Metabolome profiles were collected using DART ionization coupled with TOFMS analysis of heartwood specimens of all four Pericopsis species and Haplormosia monophylla (Harms) Harms, Dalbergia melanoxylon Guill. & Perr. Harms, and Milicia excelsa (Welw.) C.C. Berg. In total, 95 specimens were analysed and the spectra evaluated. Kernel Discriminant Analysis (KDA) and Random Forest classification were used to discern the species. Results: DART-TOFMS spectra obtained from wood slivers and post-processing analysis using KDA and Random Forest classification separated Pericopsis elata from the other Pericopsis taxa and its lookalike timbers Haplormosia monophylla, Milicia excelsa, and Dalbergia melanoxylon. Only 50 ions were needed to achieve the highest accuracy. Conclusions: DART-TOFMS spectra of the taxa were reproducible and the results of the chemometric analysis provided comparable accuracy. Haplormosia monophylla was visually distinguished based on the heatmap and was excluded from further analysis. Both classification methods, KDA and Random Forest, were capable of distinguishing Pericopsis elata from the other Pericopsis taxa, Milicia excelsa, and Dalbergia melanoxylon, timbers that are commonly traded

    Pith-to-bark profiles of xylem vessel traits reveal unique information on tree performance in a tropical moist semi-deciduous forest of the Congo Basin

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    Xylem vessel features are the most investigated anatomical traits of Angiosperm wood. They are being analyzed in ecophysiological projects aiming at understanding sap flow and vulnerability to drought stress. Since long, size, grouping and density of vessels are also used as one of the first steps in timber identification, as they can easily be observed even with a hand lens. Vessels are also known to be related to tree height. The volumetric sap flow rate is inversely related to the length of the path, so that vessels need to widen at lower parts of the tree and taper towards the higher parts to assure optimal transport and a stable hydraulic resistance with progressing growth in height. Vessels are expected to narrow from roots to stem and further to the branches and the petioles. Accordingly it is also predictable that vessel features on pith-to-bark profiles are a proxy for height growth for individual trees. Since the functional groups of species of a tropical rainforest are based on height grow rate (related to light needs), it is expected that pith-to-bark profiles of vessels reveal information on temperament of the species. A methodology has been developed to establish pith-to-bark profiles of vessel features, based on long microtomic sections, image analysis and machine learning. Entandrophragma was used as a model genus. The differences between the four most common species of this genus have been explored. Wilcoxon signed rank test indicate that the difference in mean vessel size is significant between every species combination except between Entandrophragma candollei and Entandrophragma cylindricum. Interesting to note is the large vessel size range possible for Entandrophragma utile. Currently, pith-to-bark vessel trends are constructed that could help explaining difference in growth strategy. The approach offers appealing perspectives to find a formal way for sub setting tree species into functional groups and develop indexes for growing conditions of forest sites

    A Generalizable Deep Learning System for Cardiac MRI

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    Cardiac MRI allows for a comprehensive assessment of myocardial structure, function, and tissue characteristics. Here we describe a foundational vision system for cardiac MRI, capable of representing the breadth of human cardiovascular disease and health. Our deep learning model is trained via self-supervised contrastive learning, by which visual concepts in cine-sequence cardiac MRI scans are learned from the raw text of the accompanying radiology reports. We train and evaluate our model on data from four large academic clinical institutions in the United States. We additionally showcase the performance of our models on the UK BioBank, and two additional publicly available external datasets. We explore emergent zero-shot capabilities of our system, and demonstrate remarkable performance across a range of tasks; including the problem of left ventricular ejection fraction regression, and the diagnosis of 35 different conditions such as cardiac amyloidosis and hypertrophic cardiomyopathy. We show that our deep learning system is capable of not only understanding the staggering complexity of human cardiovascular disease, but can be directed towards clinical problems of interest yielding impressive, clinical grade diagnostic accuracy with a fraction of the training data typically required for such tasks.Comment: 21 page main manuscript, 4 figures. Supplementary Appendix and code will be made available on publicatio

    Perinatal asphyxia: current status and approaches towards neuroprotective strategies, with focus on sentinel proteins

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    Delivery is a stressful and risky event menacing the newborn. The mother-dependent respiration has to be replaced by autonomous pulmonary breathing immediately after delivery. If delayed, it may lead to deficient oxygen supply compromising survival and development of the central nervous system. Lack of oxygen availability gives rise to depletion of NAD+ tissue stores, decrease of ATP formation, weakening of the electron transport pump and anaerobic metabolism and acidosis, leading necessarily to death if oxygenation is not promptly re-established. Re-oxygenation triggers a cascade of compensatory biochemical events to restore function, which may be accompanied by improper homeostasis and oxidative stress. Consequences may be incomplete recovery, or excess reactions that worsen the biological outcome by disturbed metabolism and/or imbalance produced by over-expression of alternative metabolic pathways. Perinatal asphyxia has been associated with severe neurological and psychiatric sequelae with delayed clinical onset. No specific treatments have yet been established. In the clinical setting, after resuscitation of an infant with birth asphyxia, the emphasis is on supportive therapy. Several interventions have been proposed to attenuate secondary neuronal injuries elicited by asphyxia, including hypothermia. Although promising, the clinical efficacy of hypothermia has not been fully demonstrated. It is evident that new approaches are warranted. The purpose of this review is to discuss the concept of sentinel proteins as targets for neuroprotection. Several sentinel proteins have been described to protect the integrity of the genome (e.g. PARP-1; XRCC1; DNA ligase IIIα; DNA polymerase ÎČ, ERCC2, DNA-dependent protein kinases). They act by eliciting metabolic cascades leading to (i) activation of cell survival and neurotrophic pathways; (ii) early and delayed programmed cell death, and (iii) promotion of cell proliferation, differentiation, neuritogenesis and synaptogenesis. It is proposed that sentinel proteins can be used as markers for characterising long-term effects of perinatal asphyxia, and as targets for novel therapeutic development and innovative strategies for neonatal care

    NĂ­veis disfuncionais de ansiedade relacionada ao CoronavĂ­rus em estudantes de medicina: Dysfunctional levels of Coronavirus-related anxiety in medical students

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    As preocupaçÔes com a saĂșde mental das pessoas afetadas pela pandemia de coronavĂ­rus nĂŁo foram abordadas adequadamente. Isso Ă© surpreendente, uma vez que tragĂ©dias em massa, particularmente aquelas que envolvem doenças infecciosas, muitas vezes desencadeiam ondas de medo e ansiedade elevados que sĂŁo conhecidos por causar perturbaçÔes maciças no comportamento e no bem-estar psicolĂłgico de muitos na população. Assim, o objetivo desse trabalho Ă© demonstrar os nĂ­veis disfuncionais de ansiedade relacionada ao coronavĂ­rus em estudantes de medicina. Para isso, foi realizado uma revisĂŁo sistemĂĄtica sobre a temĂĄtica

    COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

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    Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≀ 18 years: 69, 48, 23; 85%), older adults (≄ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men
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