Assessing a novel modelling approach with high resolution UAV imagery for monitoring health status in priority riparian forests

ResearchBackground: Black alder (Alnus glutinosa) forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex (class Oomycetes), “alder Phytopththora”. Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity. Data obtained by unmanned aerial vehicles (UAVs) may be particularly useful for such tasks due to the high resolution, flexibility of acquisition and cost efficiency of this type of data. In this study, A. glutinosa decline was assessed by considering four categories of tree health status in the field: asymptomatic, dead and defoliation above and below a 50% threshold. A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles -red green blue (RGB) data were analysed using classical random forest (RF) and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony. A total of 34 remote sensing variables were considered, including a set of vegetation indices, texture features from the normalized difference vegetation index (NDVI) and a digital surface model (DSM), topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level. Results: The four categories identified by the RF yielded an overall accuracy of 67%, while aggregation of the legend to three classes (asymptomatic, defoliated, dead) and to two classes (alive, dead) improved the overall accuracy to 72% and 91% respectively. On the other hand, the confusion matrix, computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%, 80% and 94% for four-, three- and two-level classifications, respectively. Discussion: The study findings provide forest managers with an alternative robust classification method for the rapid, effective assessment of areas affected and non-affected by the disease, thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forestsinfo:eu-repo/semantics/publishedVersio

Machine Learning Improves Risk Stratification in Myelodysplastic Neoplasms: An Analysis of the Spanish Group of Myelodysplastic Syndromes

Machine learning; Risk stratification; Myelodysplastic neoplasmsAprendizaje automático; Estratificación del riesgo; Neoplasias mielodisplásicasAprenentatge automàtic; Estratificació del risc; Neoplàsies mielodisplàstiquesMyelodysplastic neoplasms (MDS) are a heterogeneous group of hematological stem cell disorders characterized by dysplasia, cytopenias, and increased risk of acute leukemia. As prognosis differs widely between patients, and treatment options vary from observation to allogeneic stem cell transplantation, accurate and precise disease risk prognostication is critical for decision making. With this aim, we retrieved registry data from MDS patients from 90 Spanish institutions. A total of 7202 patients were included, which were divided into a training (80%) and a test (20%) set. A machine learning technique (random survival forests) was used to model overall survival (OS) and leukemia-free survival (LFS). The optimal model was based on 8 variables (age, gender, hemoglobin, leukocyte count, platelet count, neutrophil percentage, bone marrow blast, and cytogenetic risk group). This model achieved high accuracy in predicting OS (c-indexes; 0.759 and 0.776) and LFS (c-indexes; 0.812 and 0.845). Importantly, the model was superior to the revised International Prognostic Scoring System (IPSS-R) and the age-adjusted IPSS-R. This difference persisted in different age ranges and in all evaluated disease subgroups. Finally, we validated our results in an external cohort, confirming the superiority of the Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS) over the IPSS-R, and achieving a similar performance as the molecular IPSS. In conclusion, the AIPSS-MDS score is a new prognostic model based exclusively on traditional clinical, hematological, and cytogenetic variables. AIPSS-MDS has a high prognostic accuracy in predicting survival in MDS patients, outperforming other well-established risk-scoring systems

Drug Delivery to the Posterior Segment of the Eye: Biopharmaceutic and Pharmacokinetic Considerations

The treatment of the posterior-segment ocular diseases, such as age-related eye diseases (AMD) or diabetic retinopathy (DR), present a challenge for ophthalmologists due to the complex anatomy and physiology of the eye. This specialized organ is composed of various static and dynamic barriers that restrict drug delivery into the target site of action. Despite numerous efforts, effective intraocular drug delivery remains unresolved and, therefore, it is highly desirable to improve the current treatments of diseases affecting the posterior cavity. This review article gives an overview of pharmacokinetic and biopharmaceutics aspects for the most commonly-used ocular administration routes (intravitreal, topical, systemic, and periocular), including information of the absorption, distribution, and elimination, as well as the benefits and limitations of each one. This article also encompasses different conventional and novel drug delivery systems designed and developed to improve drug pharmacokinetics intended for the posterior ocular segment treatment

Prediction of the yield of grains through artificial intelligence

Grass turns out to be an appropriate food for cattle, mainly in tropical climate countries such as Latin American countries. This is due to the high number of species that can be used, the possibility of growing them year-round, the ability of the ruminant to use fibrous supplies and be an economic source (Sánchez et al., Data mining and big data. DMBD 2018. Lecture notes in computer science, vol 10943. Springer, Cham, 2018, [1]). In this work, an application of neural networks was carried out in the forecasting of more accurate values of production and quality of grasslands

Optogenetic Peripheral Nerve Immunogenicity

Optogenetic technologies have been the subject of great excitement within the scientific community for their ability to demystify complex neurophysiological pathways in the central (CNS) and peripheral nervous systems (PNS). The excitement surrounding optogenetics has also extended to the clinic with a trial for ChR2 in the treatment of retinitis pigmentosa currently underway and additional trials anticipated for the near future. In this work, we identify the cause of loss-of-expression in response to transdermal illumination of an optogenetically active peroneal nerve following an anterior compartment (AC) injection of AAV6-hSyn-ChR2(H134R) with and without a fluorescent reporter. Using Sprague Dawley Rag2−/− rats and appropriate controls, we discover optogenetic loss-of-expression is chiefly elicited by ChR2-mediated immunogenicity in the spinal cord, resulting in both CNS motor neuron death and ipsilateral muscle atrophy in both low and high Adeno-Associated Virus (AAV) dosages. We further employ pharmacological immunosuppression using a slow-release tacrolimus pellet to demonstrate sustained transdermal optogenetic expression up to 12 weeks. These results suggest that all dosages of AAV-mediated optogenetic expression within the PNS may be unsafe. Clinical optogenetics for both PNS and CNS applications should take extreme caution when employing opsins to treat disease and may require concurrent immunosuppression. Future work in optogenetics should focus on designing opsins with lesser immunogenicity.MIT Media Lab Consortiu

Spleen-Dependent Immune Protection Elicited by CpG Adjuvanted Reticulocyte-Derived Exosomes from Malaria Infection Is Associated with Changes in T cell Subsets' Distribution

Added corrigendum published in 2017-01-17 https://doi.org/10.3389/fcell.2016.00153Reticulocyte-derived exosomes (rex) are 30-100 nm membrane vesicles of endocytic origin released during the maturation of reticulocytes to erythrocytes upon fusion of multivesicular bodies with the plasma membrane. Combination of CpG-ODN with rex obtained from BALB/c mice infected with the reticulocyte-prone non-lethal P. yoelii 17X malaria strain (rexPy), had been shown to induce survival and long lasting protection. Here, we show that splenectomized mice are not protected upon rexPy+CpG inmunizations and that protection is restored upon passive transfer of splenocytes obtained from animals immunized with rexPy+CpG. Notably, rexPy immunization of mice induced changes in PD1- memory T cells with effector phenotype. Proteomics analysis of rexPy confirmed their reticulocyte origin and demonstrated the presence of parasite antigens. Our studies thus prove, for what we believe is the first time, that rex from reticulocyte-prone malarial infections are associated with splenic long-lasting memory responses. To try extrapolating these data to human infections, in vitro experiments with spleen cells of human transplantation donors were performed. Plasma-derived exosomes from vivax malaria patients (exPv) were actively uptaken by human splenocytes and stimulated spleen cells leading to changes in T cell subsets

Two-neutron transfer reaction mechanisms in 12^{12}C(6^6He,4^{4}He)14^{14}C using a realistic three-body 6^{6}He model

The reaction mechanisms of the two-neutron transfer reaction $^{12}$C($^6$He,$^4$He) have been studied at 30 MeV at the TRIUMF ISAC-II facility using the SHARC charged-particle detector array. Optical potential parameters have been extracted from the analysis of the elastic scattering angular distribution. The new potential has been applied to the study of the transfer angular distribution to the 2$^+_2$ 8.32 MeV state in $^{14}$C, using a realistic 3-body $^6$He model and advanced shell model calculations for the carbon structure, allowing to calculate the relative contributions of the simultaneous and sequential two-neutron transfer. The reaction model provides a good description of the 30 MeV data set and shows that the simultaneous process is the dominant transfer mechanism. Sensitivity tests of optical potential parameters show that the final results can be considerably affected by the choice of optical potentials. A reanalysis of data measured previously at 18 MeV however, is not as well described by the same reaction model, suggesting that one needs to include higher order effects in the reaction mechanism.Comment: 9 pages, 9 figure

Direct reactions for nuclear structure required for fundamental symmetry tests

A program of nuclear structure studies to support fundamental symmetry tests has been initiated. Motivated by the search for an electric dipole moment in Hg-199, the structure in the vicinity has been explored via direct reaction studies. To date, these have included the Hg-198,Hg-200(d, d') inelastic scattering reactions, with the aim to obtain information on the E2 and E3 strength distributions, and the Hg-198(d, p) and Hg-200(d, t) reactions to obtain information on the single-particle states in 199Hg. The studies using the 200Hg targets have been fully analyzed using the FRESCO reaction code yielding the E2 and E3 strength distribution to 4 MeV in excitation energy, and the (d, t) single-particle strength to over 3 MeV in excitation energy

Direct reactions for nuclear structure required for fundamental symmetry tests

A program of nuclear structure studies to support fundamental symmetry tests has been initiated. Motivated by the search for an electric dipole moment in Hg-199, the structure in the vicinity has been explored via direct reaction studies. To date, these have included the Hg-198,Hg-200(d, d') inelastic scattering reactions, with the aim to obtain information on the E2 and E3 strength distributions, and the Hg-198(d, p) and Hg-200(d, t) reactions to obtain information on the single-particle states in 199Hg. The studies using the 200Hg targets have been fully analyzed using the FRESCO reaction code yielding the E2 and E3 strength distribution to 4 MeV in excitation energy, and the (d, t) single-particle strength to over 3 MeV in excitation energy