A preliminary timeline of the midbrain development in the Monodelphis Domestica animal model

Introduction: The Brazilian short-tailed opossum (Monodelphis Domestica) is an understudied animal model compared to the Mus musculus that has been identified as a perfect candidate to study neurodevelopment (Baggott, L. & Moore, H., 1990). What makes the Monodelphis Domestica a perfect specimen for neurodevelopment is that the embryo develops outside the pouch of the mother providing easy noninvasive access to track changes across different developmental stages (Mate et al., 1994). Objective: The objective of the study is to compare the area and volume in the development of the Monodelphis’s midbrain across three different developmental stages. Our research is beneficial because it facilitates the study of neurodevelopmental mental health disorders and its impact in the brain. Methods: We utilized ImageJ and Zen software to perform the volumetric and area analysis of these stages. To conduct a volumetric analysis a Volume Macro code was used in ImageJ software. The area analysis was completed using Zen software. A descriptive analysis was used to compare the differences in area and volume across the developmental stages

Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence.

Recent developments allowed generating multiple high-quality \u27omics\u27 data that could increase the predictive performance of genomic prediction for phenotypes and genetic merit in animals and plants. Here, we have assessed the performance of parametric and nonparametric models that leverage transcriptomics in genomic prediction for 13 complex traits recorded in 478 animals from an outbred mouse population. Parametric models were implemented using the best linear unbiased prediction, while nonparametric models were implemented using the gradient boosting machine algorithm. We also propose a new model named GTCBLUP that aims to remove between-omics-layer covariance from predictors, whereas its counterpart GTBLUP does not do that. While gradient boosting machine models captured more phenotypic variation, their predictive performance did not exceed the best linear unbiased prediction models for most traits. Models leveraging gene transcripts captured higher proportions of the phenotypic variance for almost all traits when these were measured closer to the moment of measuring gene transcripts in the liver. In most cases, the combination of layers was not able to outperform the best single-omics models to predict phenotypes. Using only gene transcripts, the gradient boosting machine model was able to outperform best linear unbiased prediction for most traits except body weight, but the same pattern was not observed when using both single nucleotide polymorphism genotypes and gene transcripts. Although the GTCBLUP model was not able to produce the most accurate phenotypic predictions, it showed the highest accuracies for breeding values for 9 out of 13 traits. We recommend using the GTBLUP model for prediction of phenotypes and using the GTCBLUP for prediction of breeding values

Prediction performance of linear models and gradient boosting machine on complex phenotypes in outbred mice.

We compared the performance of linear (GBLUP, BayesB, and elastic net) methods to a nonparametric tree-based ensemble (gradient boosting machine) method for genomic prediction of complex traits in mice. The dataset used contained genotypes for 50,112 SNP markers and phenotypes for 835 animals from 6 generations. Traits analyzed were bone mineral density, body weight at 10, 15, and 20 weeks, fat percentage, circulating cholesterol, glucose, insulin, triglycerides, and urine creatinine. The youngest generation was used as a validation subset, and predictions were based on all older generations. Model performance was evaluated by comparing predictions for animals in the validation subset against their adjusted phenotypes. Linear models outperformed gradient boosting machine for 7 out of 10 traits. For bone mineral density, cholesterol, and glucose, the gradient boosting machine model showed better prediction accuracy and lower relative root mean squared error than the linear models. Interestingly, for these 3 traits, there is evidence of a relevant portion of phenotypic variance being explained by epistatic effects. Using a subset of top markers selected from a gradient boosting machine model helped for some of the traits to improve the accuracy of prediction when these were fitted into linear and gradient boosting machine models. Our results indicate that gradient boosting machine is more strongly affected by data size and decreased connectedness between reference and validation sets than the linear models. Although the linear models outperformed gradient boosting machine for the polygenic traits, our results suggest that gradient boosting machine is a competitive method to predict complex traits with assumed epistatic effects

The impact of biological sex on motor function and responses to novel environments in the gray short-tailed opossum (Monodelphis domestica)

Background: Understanding the different stress reactions in different environments can help us understand stress factors. Studying animal behavior is important for translational research for mental health improvement. Previous literature has shown that stress is a risk factor for higher cancer incidence and poorer cancer survival. (Klejbor & Turlejski., 2012), as well as mental health outcomes. Understanding of how stress is related to cancer can help improve therapeutic outcomes as preventive measures (Glaser et al., 1987). Methods: Using the Rota Rod apparatus, 12 animals (3 males, 9 females) were tested at 36 rpm for a maximum of 400 seconds (Madroñal et al., 2010). Open field apparatus was used to test 8 animals (4males, 4 females), their locomotor and non-locomotor behaviors were recorded using AnyMaze. Data collected from both experiments were analyzed with SPSS software. Results: The preliminary results showed sex differences, female’s average number of revolutions (44.54) was higher than their male counterparts (26.15). Results from the open field showed females exhibit less immobile episodes (f(1)=6.000. p Conclusions: Previous literature has shown stress is a risk factor and a major contributor to mental and physical health problems. Preliminary results support the hypothesis that there is a biological component in stress reactivity to novel environments in the Monodelphis, and that animal models are a good alternative to study sex differences in stress responses and motor function. Further research is needed to test housing effects in the short-tailed opossums

Comportamiento de cultivares de maní alto oleico frente a “Thecaphora Frezii” en distintas condiciones hídricas

El carbón del maní (Thecaphora frezii) es una de las enfermedades más importantes que presenta el cultivo. Desde el año 2012, su prevalencia es del 100% en la región manisera de Córdoba (Rago et al., 2017), y al ser una enfermedad poliética, los registros de incidencia son crecientes año tras año agravando la situación. Una de las causas del incremento en la incidencia de la enfermedad es la falta de implementación de medidas contundentes para mitigar la infección, reproducción y dispersión del patógeno. Actualmente, los principales cultivares utilizados son altamente susceptibles a esta enfermedad, lo que conduce a perdidas de rendimiento y calidad de grano. Adicionalmente, estudios previos indican que en condiciones de sequía la enfermedad aumenta considerablemente (Paredes et al., 2018). En este sentido y teniendo en cuenta el mejoramiento genético como herramienta para mitigar la enfermedad, se planteó como objetivo evaluar el comportamiento de diferentes cultivares comerciales tolerantes y susceptibles frente al carbón en distintas condiciones hídricas (riego y secano).Centro de Investigaciones AgropecuariasFil: Pérez, I.A. Fundación ArgenINTA. Delegación CIAP; ArgentinaFil: Paredes, Juan Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Paredes, Juan Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Brichi, L. Prodeman; ArgentinaFil: Monguillot, Joaquín Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Monguillot, Joaquín Humberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Rago, Alejandro Mario. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigaciones Agropecuarias (CIAP); ArgentinaFil: Rago, Alejandro Mario. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentin

Efficacy of the Combination of Pinaverium Bromide 100mg Plus Simethicone 300mg in Abdominal Pain and Bloating in Irritable Bowel Syndrome: A Randomized, Placebo-controlled Trial

Goals: We aimed to evaluate the efficacy and safety of PB+S (pinaverium bromide 100 mg plus simethicone 300 mg) in patients with irritable bowel syndrome (IBS). Background: IBS is a multifactorial disorder; thus, combination therapy with different mechanisms of action is expected to be useful. PB+S has shown effectiveness in an open-label clinical study in IBS. However, there are no placebo-controlled trials. Materials and Methods: IBS-Rome III patients with abdominal pain/discomfort for at least 2 days within the week prior to baseline assessment were included in this 12-week, randomized, doubleblind, placebo-controlled study of PB+S versus placebo, bid. The primary endpoint was overall symptom improvement, evaluated weekly by the patient (Likert Scale). Secondary endpoints included the weekly improvement in the severity of abdominal pain and bloating assessed both by patients (10-cm Visual Analogue Scale) and investigators (Likert Scale); frequency of Bristol Scale stool types (consistency) evaluated by patients and the IBS Quality of Life scores. Results: A total of 285 patients (female: 83%; 36.5±8.9 y old) received at least 1 dose of PB+S (n=140) or placebo (n=145). No difference was observed in overall symptom improvement between the groups (P=0.13). However, PB+S was superior in abdominal pain (effect size: 31%, P=0.038) and bloating (33%, P=0.019). Patients with IBS-C and IBS-M showed the best improvement in the frequency of stool types with PB+S. No differences were observed in IBS Quality of Life scores and adverse events

18F-FDG-PET Imaging Patterns in Autoimmune Encephalitis: Impact of Image Analysis on the Results

Brain positron emission tomography imaging with 18Fluorine-fluorodeoxyglucose (FDG-PET) has demonstrated utility in suspected autoimmune encephalitis. Visual and/or assisted image reading is not well established to evaluate hypometabolism/hypermetabolism. We retrospectively evaluated patients with autoimmune encephalitis between 2003 and 2018. Patients underwent EEG, brain magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) sampling and autoantibodies testing. Individual FDG-PET images were evaluated by standard visual reading and assisted by voxel-based analyses, compared to a normal database. For the latter, three different methods were performed: two based on statistical surface projections (Siemens syngo.via Database Comparison, and 3D-SSP Neurostat) and one based on statistical parametric mapping (SPM12). Hypometabolic and hypermetabolic findings were grouped to identify specific patterns. We found six cases with definite diagnosis of autoimmune encephalitis. Two cases had anti-LGI1, one had anti-NMDA-R and two anti-CASPR2 antibodies, and one was seronegative. 18F-FDG-PET metabolic abnormalities were present in all cases, regardless of the method of analysis. Medial–temporal and extra-limbic hypermetabolism were more clearly depicted by voxel-based analyses. We found autoantibody-specific patterns in line with the literature. Statistical surface projection (SSP) methods (Neurostat and syngo.via Database Comparison) were more sensitive and localized larger hypermetabolic areas. As it may lead to comparable and accurate results, visual analysis of FDG-PET studies for the diagnosis of autoimmune encephalitis benefits from voxel-based analysis, beyond the approach based on MRI, CSF sample and EEG