Axonal T₂ estimation using the spherical variance of the strongly diffusion-weighted MRI signal.

In magnetic resonance imaging, the application of a strong diffusion weighting suppresses the signal contributions from the less diffusion-restricted constituents of the brain's white matter, thus enabling the estimation of the transverse relaxation time T <sub>2</sub> that arises from the more diffusion-restricted constituents such as the axons. However, the presence of cell nuclei and vacuoles can confound the estimation of the axonal T <sub>2</sub> , as diffusion within those structures is also restricted, causing the corresponding signal to survive the strong diffusion weighting. We devise an estimator of the axonal T <sub>2</sub> based on the directional spherical variance of the strongly diffusion-weighted signal. The spherical variance T <sub>2</sub> estimates are insensitive to the presence of isotropic contributions to the signal like those provided by cell nuclei and vacuoles. We show that with a strong diffusion weighting these estimates differ from those obtained using the directional spherical mean of the signal which contains both axonal and isotropically-restricted contributions. Our findings hint at the presence of an MRI-visible isotropically-restricted contribution to the signal in the white matter ex vivo fixed tissue (monkey) at 7T, and do not allow us to discard such a possibility also for in vivo human data collected with a clinical 3T system

Asistencia farmacéutica a la prescripción para aproximar la práctica clínica a la evidencia científica

ObjetivoEl objetivo del presente estudio es valorar la utilidad de un programa de asistencia farmacéutica a la prescripción (AFP) en cuanto a la detección de problemas relacionados con los medicamentos.DiseñoRealizamos un estudio descriptivo de los hallazgos de este programa al cabo de 6 meses de rodaje.EmplazamientoEl trabajo fue realizado en 5 centros del Distrito Bahía-Cádiz de Atención Primaria.PacientesSe estudian todos los pacientes (499) incluidos a petición y criterio de su médico, que solicita asesoramiento sobre su farmacoterapia.IntervenciónImplantamos el programa de AFP en pacientes crónicos con dos finalidades básicas:1. Asistencial: detectar problemas relacionados con medicamentos y proponer soluciones individualizadas.2. Docente: aproximar los conocimientos en farmacoterapia aplicados en la práctica clínica a la evidencia científica disponible.Mediciones y resultadosNos centramos en la detección de aquellos problemas relacionados con medicamentos más frecuentes, con incidencia directa y relevante sobre la morbimortalidad. Detectamos 236 casos (47%) de posible mejora terapéutica con implicaciones importantes sobre morbilidad asociada, de los cuales 114 (23%) tenían también implicaciones sobre mortalidad. Un 56% de los pacientes recibía más de 4 medicamentos, polimedicación que podía reducirse fácilmente en un 43,5% de ellos, evitando la utilización de medicamentos de valor intrínseco no elevado.ConclusionesLa utilidad del programa resulta muy elevada al detectar numerosos problemas de gran relevancia clínica y aportar información que puede ser útil al médico para aproximar la farmacoterapia a la evidencia científica disponible.ObjectiveThe objective of this study is to assess the usefulness of a programme of attention to pharmaceutical prescriptions (APP) so as to detect medicine-related problems.DesignA descriptive study of the findings after six months operation of this programme.SettingFive primary care centres in the Bahía-Cádiz Area.PatientsAll the patients (499) who requested advice on their drug therapy and were included at the request and on the criterion of their doctor were studied.InterventionWe introduced the APP programme for chronic patients, with two basic aims:1. Care: to detect medicine-related problems and propose individual solutions.2. Teaching: to bring drug-therapy skills used in clinical practice into line with the scientific evidence available.Measurements and resultsWe focused on the detection of problems related to the most common medicines, with direct and relevant incidence on morbidity and mortality. We detected 236 cases (47%) of possible therapeutic improvement that had important implications for associated morbidity, of which 114 (23%) also had implications for mortality. 56% of the patients took more than 4 medicines, multiple medication that could easily be reduced in 43.5% of cases, so avoiding the use of medicines of low intrinsic value.ConclusionsThe programme was very useful, as numerous very clinically relevant problems were detected and information was gained that the doctor can use to bring drug therapy into line with the available scientific evidence

Revisiting the T₂ spectrum imaging inverse problem: Bayesian regularized non-negative least squares.

Multi-echo T <sub>2</sub> magnetic resonance images contain information about the distribution of T <sub>2</sub> relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-negative least squares (NNLS) is the tool of choice for estimating non-parametric T <sub>2</sub> spectra. However, the estimation is ill-conditioned, sensitive to noise, and highly affected by the employed regularization weight. The purpose of this study is threefold: first, we want to underline that the apparently innocuous use of two alternative parameterizations for solving the inverse problem, which we called the standard and alternative regularization forms, leads to different solutions; second, to assess the performance of both parameterizations; and third, to propose a new Bayesian regularized NNLS method (BayesReg). The performance of BayesReg was compared with that of two conventional approaches (L-curve and Chi-square (X <sup>2</sup> ) fitting) using both regularization forms. We generated a large dataset of synthetic data, acquired in vivo human brain data in healthy participants for conducting a scan-rescan analysis, and correlated the myelin content derived from histology with the MWF estimated from ex vivo data. Results from synthetic data indicate that BayesReg provides accurate MWF estimates, comparable to those from L-curve and X <sup>2</sup> , and with better overall stability across a wider signal-to-noise range. Notably, we obtained superior results by using the alternative regularization form. The correlations reported in this study are higher than those reported in previous studies employing the same ex vivo and histological data. In human brain data, the estimated maps from L-curve and BayesReg were more reproducible. However, the T <sub>2</sub> spectra produced by BayesReg were less affected by over-smoothing than those from L-curve. These findings suggest that BayesReg is a good alternative for estimating T <sub>2</sub> distributions and MWF maps

A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data

High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots nested in genotypes, and genotypes nested in populations. For selection of genotypes in a plant breeding context, we show how to extract new phenotypes, like growth rates, from the estimated genotypic growth curves and their first-order derivatives. We illustrate our approach on HTP data from the PhenoArch greenhouse platform at INRAE Montpellier and the outdoor Field Phenotyping platform at ETH Zürich.BERC 2018-2021 BCAM Severo Ochoa accreditation SEV-2017-0718) EU H2020 grant agreement ID 731013 (EPPN2020) PhenoCOOL (project no. 169542)

Homoeologous chromosomal location of the genes encoding thionins in wheat and rye

Thionins are high sulphur basic polypeptides present in the endosperm of Gramineae. In wheat there are three thionins encoded by genes located in the long arms of chromosomes 1A, 1B and 1D. Rye has one thionin encoded by a gene which has been assigned to chromosome 1R after analysis of the Imperial-Chinese Spring rye-wheat disomic addition lines. Commercial varieties and experimental stocks with a 1B/1R substitution carry the thionin from rye ( R) instead of the B thionin from wheat. The R thionin gene is not located in the large chromosomal segment representing most of the short arm of chromosome 1R

Model-informed machine learning for multi-component T₂ relaxometry.

Recovering the T <sub>2</sub> distribution from multi-echo T <sub>2</sub> magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to combine machine learning and aspects of parametric (fitting from the MRI signal using biophysical models) and non-parametric (model-free fitting of the T <sub>2</sub> distribution from the signal) approaches to T <sub>2</sub> relaxometry in brain tissue by using a multi-layer perceptron (MLP) for the distribution reconstruction. For training our network, we construct an extensive synthetic dataset derived from biophysical models in order to constrain the outputs with a priori knowledge of in vivo distributions. The proposed approach, called Model-Informed Machine Learning (MIML), takes as input the MR signal and directly outputs the associated T <sub>2</sub> distribution. We evaluate MIML in comparison to a Gaussian Mixture Fitting (parametric) and Regularized Non-Negative Least Squares algorithms (non-parametric) on synthetic data, an ex vivo scan, and high-resolution scans of healthy subjects and a subject with Multiple Sclerosis. In synthetic data, MIML provides more accurate and noise-robust distributions. In real data, MWF maps derived from MIML exhibit the greatest conformity to anatomical scans, have the highest correlation to a histological map of myelin volume, and the best unambiguous lesion visualization and localization, with superior contrast between lesions and normal appearing tissue. In whole-brain analysis, MIML is 22 to 4980 times faster than the non-parametric and parametric methods, respectively

Distinctive phehotypes of Bradyrhizobium diazoefficiens transcriptional regulator (phaR) mutants grown on different carbon sources.

Resumen del poster presentado en: XVII Congreso Argentino de Microbiología General (SAMIGE). Córdoba, Argentina, 25-28 octubre 2022

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro

A fast sparse block circulant matrix vector product

In the context of computed tomography (CT), iterative image reconstruction techniques are gaining attention because high-quality images are becoming computationally feasible. They involve the solution of large systems of equations, whose cost is dominated by the sparse matrix vector product (SpMV). Our work considers the case of the sparse matrices being block circulant, which arises when taking advantage of the rotational symmetry in the tomographic system. Besides the straightforward storage saving, we exploit the circulant structure to rewrite the poor-performance SpMVs into a high-performance product between sparse and dense matrices. This paper describes the implementations developed for multi-core CPUs and GPUs, and presents experimental results with typical CT matrices. The presented approach is up to ten times faster than without exploiting the circulant structure.Romero Alcalde, E.; Tomás Domínguez, AE.; Soriano Asensi, A.; Blanquer Espert, I. (2014). 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Parasitism by the Endoparasitoid, Cotesia flavipes Induces Cellular Immunosuppression and Enhances Susceptibility of the Sugar Cane Borer, Diatraea saccharalis to Bacillus thuringiensis

Cotesia flavipes Cameron (Hymenoptera: Braconidae), is a gregarious larval endoparasitoid of the sugarcane borer, Diatraea saccharalis Fabricius (Lepidoptera: Crambidae). The aim of this research was to analyze cellular immunosuppression of D. saccharalis parasitized by C. flavipes in terms of encapsulation, melanization, and hemocyte nodule formation. The encapsulation assay was done 1 and 6 days after parasitoid oviposition. In addition, the susceptibility of parasitized and nonparasitzed larvae to Bacillus thuringiensis HD 73 strain was assessed. 3, 12, and 24 h after bead injection; the percentages of encapsulation were significantly higher in unparasitized larvae compared to larvae parasitized 1 and 6 days after oviposition. Interestingly, there was a significant reduction in numbers of beads encapsulated at 1 day after oviposition compared to 6 days, and unparasitized larvae. The percentage of melanized beads decreased significantly in parasitized larvae compared to control. There was a reduction in the number of nodules in parasitized larvae compared to unparasitized controls. Larvae that were injected with polyndavirus 24 h before beads were injected showed significantly reduced encapsulation responses relative to control larvae. The D. saccharalis parasitized by C. flavipes exhibited higher susceptibility to B. thuringiensis. These results suggest that parasitization induced host immunosuppression, and the immunosuppression factors could impair the defense capacity against microbial pathogens - causing an increase in pathogen susceptibility