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"Beltran, Felipe"
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A simple solution for antibody signal enhancement in immunofluorescence and triple immunogold assays
Immunolocalization techniques are standard in biomedical research. Tissue fixation with aldehydes and cell membrane permeabilization with detergents can distort the specific binding of antibodies to their high affinity epitopes. In immunofluorescence protocols, it is desirable to quench the sample’s autofluorescence without reduction of the antibody-dependent signal. Here we show that adding glycine to the blocking buffer and diluting the antibodies in a phosphate saline solution containing glycine, Triton X-100, Tween20 and hydrogen peroxide increase the specific antibody signal in tissue immunofluorescence and immunogold electron microscopy. This defined antibody signal enhancer (ASE) solution gives similar results to the commercially available Pierce Immunostain Enhancer (PIE). Furthermore, prolonged tissue incubation in resin and fixative and application of ASE or PIE are described in an improved protocol for triple immunogold electron microscopy that is used to show co-localization of GABA-A ρ2 and dopamine D2 receptors in GFAP-positive astrocytes in the mouse striatum. The addition of glycine, Triton X-100, Tween20 and hydrogen peroxide during antibody incubation steps is recommended in immunohistochemistry methods.
Journal Article
Dealing with Negative Inflows in the Long-Term Hydrothermal Scheduling Problem
The long-term hydrothermal scheduling (LTHS) problem seeks to obtain an operational policy that optimizes water resource management. The most employed strategy to obtain such a policy is stochastic dual dynamic programming (SDDP). The primary source of uncertainty in predominant hydropower systems is the reservoirs inflow, usually a linear time series model (TSM) based on the order-p periodic autoregressive [PAR(p)] model. Although the linear PAR(p) can represent the seasonality and autocorrelation of the inflow datasets, negative inflows may appear during SDDP iterations, leading to water balance infeasibilities in the LTHS problem. Different from other works, the focus of this paper is not avoiding negative inflows but instead dealing with the negative values that cause infeasibilities. Hence, three strategies are discussed: (i) inclusion of a slack variable penalized in the objective function, (ii) negative inflow truncation to zero, and (iii) optimal inflow truncation, among which the latter is a novel approach. The strategies are compared individually and combined. Methodological conditions and evidence of the algorithm convergence are presented. Out-of-sample simulations show that the choice of negative inflow strategy significantly impacts the performance of the resultant operational policy. The combination of strategy (i) and (iii) reduces the expected operation cost by 15%.
Journal Article
Old Things New View: Ascorbic Acid Protects the Brain in Neurodegenerative Disorders
Ascorbic acid is a key antioxidant of the Central Nervous System (CNS). Under brain activity, ascorbic acid is released from glial reservoirs to the synaptic cleft, where it is taken up by neurons. In neurons, ascorbic acid scavenges reactive oxygen species (ROS) generated during synaptic activity and neuronal metabolism where it is then oxidized to dehydroascorbic acid and released into the extracellular space, where it can be recycled by astrocytes. Other intrinsic properties of ascorbic acid, beyond acting as an antioxidant, are important in its role as a key molecule of the CNS. Ascorbic acid can switch neuronal metabolism from glucose consumption to uptake and use of lactate as a metabolic substrate to sustain synaptic activity. Multiple evidence links oxidative stress with neurodegeneration, positioning redox imbalance and ROS as a cause of neurodegeneration. In this review, we focus on ascorbic acid homeostasis, its functions, how it is used by neurons and recycled to ensure antioxidant supply during synaptic activity and how this antioxidant is dysregulated in neurodegenerative disorders.
Journal Article
Host-microbiome protein-protein interactions capture disease-relevant pathways
Background
Host-microbe interactions are crucial for normal physiological and immune system development and are implicated in a variety of diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), obesity, and type 2 diabetes (T2D). Despite large-scale case-control studies aimed at identifying microbial taxa or genes involved in pathogeneses, the mechanisms linking them to disease have thus far remained elusive.
Results
To identify potential pathways through which human-associated bacteria impact host health, we leverage publicly-available interspecies protein-protein interaction (PPI) data to find clusters of microbiome-derived proteins with high sequence identity to known human-protein interactors. We observe differential targeting of putative human-interacting bacterial genes in nine independent metagenomic studies, finding evidence that the microbiome broadly targets human proteins involved in immune, oncogenic, apoptotic, and endocrine signaling pathways in relation to IBD, CRC, obesity, and T2D diagnoses.
Conclusions
This host-centric analysis provides a mechanistic hypothesis-generating platform and extensively adds human functional annotation to commensal bacterial proteins.
Journal Article
Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer’s Disease Neuroimaging (ADNI) database
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on subjects at various stage of symptomatic severity due to Alzheimer's disease. As expected, magnetic resonance imaging is a major component of the project. Full brain images are obtained at every 6-month visit. A range of cognitive tests studying executive function and memory are employed less frequently. Two blood draws (baseline, 6 months) provide samples to measure concentrations of approximately 145 plasma biomarkers. In addition, other diagnostic measurements are performed including PET imaging, cerebral spinal fluid measurements of amyloid-beta and tau peptides, as well as genetic tests, demographics, and vital signs. ADNI data is available upon review of an application. There have been numerous reports of how various processes evolve during AD progression, including alterations in metabolic and neuroendocrine activity, cell survival, and cognitive behavior. Lacking an analytic model at the onset, we leveraged recent advances in machine learning, which allow us to deal with large, non-linear systems with many variables. Of particular note was examining how well binary predictions of future disease states could be learned from simple, non-invasive measurements like those dependent on blood samples. Such measurements make relatively little demands on the time and effort of medical staff or patient. We report findings with recall/precision/area under the receiver operator curve after application of CART, Random Forest, Gradient Boosting, and Support Vector Machines, Our results show (i) Random Forests and Gradient Boosting work very well with such data, (ii) Prediction quality when applied to relatively easily obtained measurements (Cognitive scores, Genetic Risk and plasma biomarkers) achieve results that are competitive with magnetic resonance techniques. This is by no means an exhaustive study, but instead an exploration of the plausibility of defining a series of relatively inexpensive, broad population based tests.
Journal Article
A failure in energy metabolism and antioxidant uptake precede symptoms of Huntington’s disease in mice
Huntington’s disease has been associated with a failure in energy metabolism and oxidative damage. Ascorbic acid is a powerful antioxidant highly concentrated in the brain where it acts as a messenger, modulating neuronal metabolism. Using an electrophysiological approach in R6/2 HD slices, we observe an abnormal ascorbic acid flux from astrocytes to neurons, which is responsible for alterations in neuronal metabolic substrate preferences. Here using striatal neurons derived from knock-in mice expressing mutant huntingtin (STHdhQ cells), we study ascorbic acid transport. When extracellular ascorbic acid concentration increases, as occurs during synaptic activity, ascorbic acid transporter 2 (SVCT2) translocates to the plasma membrane, ensuring optimal ascorbic acid uptake for neurons. In contrast, SVCT2 from cells that mimic HD symptoms (dubbed HD cells) fails to reach the plasma membrane under the same conditions. We reason that an early impairment of ascorbic acid uptake in HD neurons could lead to early metabolic failure promoting neuronal death.
Defective ascorbic acid flux is a sign of metabolic failure associated with Huntington’s disease. Here, Acuña
et al.
show that reduction in ascorbic acid flux from astrocytes precedes the symptoms of Huntington’s disease in mice and impairs ascorbic acid uptake in neurons.
Journal Article
Impact of the COVID-19 Pandemic on Export Survival from Latin American Countries
This study analyzes the impact of mobility, as a proxy for social distancing measures, on exports to the United States of America (USA). A mobility index based on Google mobility indicators was constructed using Principal Component Analysis (PCA), and an Accelerated Failure Time (AFT) model was fitted to the data on export survival from a group of Latin American countries (LATAM). Higher mobility levels are associated with an acceleration of the risk of interruption of exports. On average, LATAM shows higher export survival levels compared to other countries. Higher innovation and market concentration favored export survival, while higher levels of Real Effective Exchange Rate (REER) are associated with a lower probability of survival. Differences in survival were found between export sectors with regard to machinery and transportation equipment.
Journal Article