Repositorio Digital Ikiam (Univ. Regional Amazónica)
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Diseño de un proyecto artesanal semi-industrial para la repación de un jarabe de uso terapéutico, a partir de plantas medicinlaes tradicionales del Cantón Arajuno
Get PDFEn Ecuador, el Cantón Arajuno, provincia de Pastaza, las comunidades indígenas han utilizado un sistema agropastoril chakra para reactivar la economía del cantón a partir de la elaboración de jarabe terapéutico a base de 9 plantas medicinales como chuchuhuaso, bálsamo, amini, lispungo, challua kaspi, ajo de monte, matico, hierba luisa y ishpingo. Sin embargo, su uso no ha sido validado por estudios científicos, ni se ha estandarizado el proceso de elaboración de un jarabe con posible uso terapéutico contra enfermedades respiratorias. Con el objetivo de diseñar un proceso semi-industrial para la elaboración de jarabe terapéutico en el cantón Arajuno, se visitó las comunidades de Shiwa Kucha, Chulla Yaku y Nushino ishpingo para conocer la metodología de elaboración artesanal del jarabe. En la estandarización del proceso de obtención de jarabe se utilizaron las nueve plantas medicinales mencionadas, de las cuales tres plantas presentaron compuestos con propiedades bioactivas de interés. Se ejecutó una revisión bibliográfica de la fitoquímica de dichas plantas (ajo de monte, chuchuhuaso y matico). Además, se realizó el balance de masa y energía tomando como base los 100 L de jarabe terapéutico producido. Dicha cantidad de jarabe corresponde a 200 botellas de 500 mL con un costo de inversión aproximado de $ 9667,21. El estudio permitió la obtención de un producto a base de métodos estandarizados y respaldo científico que corrobora la fitoquímica de las plantas empleadas y su efectividad
Transformaciones del habitar amazónico, un enfoque sociocultural, comunitario y arquitectónico: análisis del equipamiento Punta de Ahuano - provincia de Napo. (Amazonic Inhabit Transformations, a Sociocultural,
Get PDFLa Amazonía es un territorio en constante transformación, motivada por procesos de extracción de recursos bajo modelos de desarrollo que colocan al capital sobre los pueblos y nacionalidades indígenas y la naturaleza. Dichas transformaciones se reflejan en los diferentes modos de ocupación y formas de habitar el espacio que se modifican con la implantación de infraestructura y equipamientos con lógicas urbanas occidentales. Este es el caso del equipamiento Punta de Ahuano, ubicado en la parroquia Ahuano a orillas del río Napo, una innovadora estructura de bambú financiada con fondos públicos en 2012 tras la construcción del aeropuerto Jumandy. El presente artículo se deriva de un proyecto de vinculación, gestionado por las asociaciones productivas de la parroquia, para recuperar el espacio tras múltiples intentos de ocuparlo sin éxito. El objetivo es destacar el conocimiento obtenido con la aplicación de una metodología con enfoque interdisciplinario que combina el trabajo de análisis de tipo sociocultural desde la interacción acción participativa, frente a la evaluación cuantitativa usando matrices de observación de espacios públicos basados en “Placemaking” como un diálogo para promover una mirada integral y complementaria a la valoración arquitectónica. Los principales hallazgos son las contradicciones entre planificación pública y el diálogo de saberes, formas de habitar y de concebir espacios amazónicos desde lo asociativo; y la falta de participación comunitaria en procesos de planificación y diseño
Machine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds
Get PDFAntibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of multidrug-resistant bacteria increase interest in understanding metabolic network (MN) mutations and the interaction of AD vs MN. In this study, we employed the IFPTML = Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) algorithm on a huge dataset from the ChEMBL database, which contains >155,000 AD assays vs >40 MNs of multiple bacteria species. We built a linear discriminant analysis (LDA) and 17 ML models centered on the linear index and based on atoms to predict antibacterial compounds. The IFPTML-LDA model presented the following results for the training subset: specificity (Sp) = 76% out of 70,000 cases, sensitivity (Sn) = 70%, and Accuracy (Acc) = 73%. The same model also presented the following results for the validation subsets: Sp = 76%, Sn = 70%, and Acc = 73.1%. Among the IFPTML nonlinear models, the k nearest neighbors (KNN) showed the best results with Sn = 99.2%, Sp = 95.5%, Acc = 97.4%, and Area Under Receiver Operating Characteristic (AUROC) = 0.998 in training sets. In the validation series, the Random Forest had the best results: Sn = 93.96% and Sp = 87.02% (AUROC = 0.945). The IFPTML linear and nonlinear models regarding the ADs vs MNs have good statistical parameters, and they could contribute toward finding new metabolic mutations in antibiotic resistance and reducing time/costs in antibacterial drug research
Repeated genetic adaptation to altitude in two tropical butterflies
Get PDFRepeated evolution can provide insight into the mechanisms that facilitate
adaptation to novel or changing environments. Here we study adaptation to
altitude in two tropical butterflies, Heliconius erato and H. melpomene, which
have repeatedly and independently adapted to montane habitats on either
side of the Andes. We sequenced 518 whole genomes from altitudinal transects
and found many regions differentiated between highland (~ 1200 m) and
lowland (~ 200 m) populations. We show repeated genetic differentiation
across replicate populations within species, including allopatric comparisons.
In contrast, there is little molecular parallelism between the two species. By
sampling five close relatives, we find that a large proportion of divergent
regions identified within species have arisen from standing variation and
putative adaptive introgression from high-altitude specialist species. Taken
together our study supports a role for both standing genetic variation and
gene flow from independently adapted species in promoting parallel local
adaptation to the environment
A Fuzzy System Classification Approach for QSAR Modeling of α- Amylase and α-Glucosidase Inhibitors
Get PDFIntroduction This report proposes the application of a new Machine Learning algorithm called Fuzzy Unordered Rules Induction Algorithm (FURIA)-C in the classification of drug-like compounds with antidiabetic inhibitory ability toward the main two pharmacological targets: α-amylase and α-glucosidase. Methods The two obtained QSAR models were tested for classification capability, achieving satisfactory accuracy scores of 94.5% and 96.5%, respectively. Another important outcome was to achieve various α-amylase and α-glucosidase fuzzy rules with high Certainty Factor values. Fuzzy-Rules derived from the training series and active classification rules were interpreted. An important external validation step, comparing our method with those previously reported, was also included. Results The Holm’s test comparison showed significant differences (p-value<0.05) between FURIA-C, Linear Discriminating Analysis (LDA), and Bayesian Networks, the former beating the two latter ones according to the relative ranking score of the Holm’s test. Conclusion From these results, the FURIA-C algorithm could be used as a cutting-edge technique to predict (classify or screen) the α-amylase and α-glucosidase inhibitory activity of new compounds and hence speed up the discovery of new potent multi-target antidiabetic agents
Level of acceptance of epistemically unwarranted beliefs in pre-service primary school teachers: influence of cognitive style, academic level and gender
Get PDFOne of the main objectives of scientific literacy is the development of rational skills and critical thinking in citizens. This is a central goal for teachers. However, beliefs that lack rational foundation and supporting evidence, named “epistemically unwarranted beliefs” (EUB), spread rapidly among the population. If teachers had some of these EUB, their work could be compromised. The aim of this research was to determine the level of acceptance of different EUB in Spanish pre-service primary school teachers and to analyze the influence of their cognitive style, gender, and academic level. Two hundred and fifty undergraduate students of Bachelor’s Degree in Primary Education participated in this study. Two questionnaires were used to collect data. ANOVA, ANCOVA, correlations, and linear regression analysis were used to quantify that influence. Results showed high levels of acceptance of some EUB in future teachers, with significant influences of gender and academic level, and a mediating role of cognitive styles. Experiential and rational cognitive styles, and academic level were significant predictors of EUB, being experiential thinking the most powerful one. Thus, pre-service teacher education should have an epistemological vigilance on future teachers’ scientific literacy and increase the presence of rational style among teacher
Size-dependent colouration balances conspicuous aposematism and camouflage
No full textColour is an important component of many different defensive strategies, but signal efficacy and detectability will also depend on the size of the coloured structures, and how pattern size interacts with the background. Consequently, size-dependent changes in colouration are common among many different species as juveniles and adults frequently use colour for different purposes in different environmental contexts. A widespread strategy in many species is switching from crypsis to conspicuous aposematic signalling as increasing body size can reduce the efficacy of camouflage, while other antipredator defences may strengthen. Curiously, despite being chemically defended, the gold-striped frog (Lithodytes lineatus, Leptodactylidae) appears to do the opposite, with bright yellow stripes found in smaller individuals, whereas larger frogs exhibit dull brown stripes. Here, we investigated whether size-dependent differences in colour support distinct defensive strategies. We first used visual modelling of potential predators to assess how colour contrast varied among frogs of different sizes. We found that contrast peaked in mid-sized individuals while the largest individuals had the least contrasting patterns. We then used two detection experiments with human participants to evaluate how colour and body size affected overall detectability. These experiments revealed that larger body sizes were easier to detect, but that the colours of smaller frogs were more detectable than those of larger frogs. Taken together our data support the hypothesis that the primary defensive strategy changes from conspicuous aposematism to camouflage with increasing size, implying size-dependent differences in the efficacy of defensive colouration. We discuss our data in relation to theories of size-dependent aposematism and evaluate the evidence for and against a possible size-dependent mimicry complex with sympatric poison frogs (Dendrobatidae)
Water table depth modulates productivity and biomass across Amazonian forests
Get PDFWater availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Lowland Amazonian forests. 1971–2019. We used 344 long‐term inventory plots distributed across Amazonia to analyse the effects of long‐term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil‐water and edaphic properties. Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth <5 m) had 18% less above‐ground woody productivity and 23% less biomass stock than forests with a deep water table. Forests in drier climates (maximum cumulative water deficit < −160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by the interaction between climatic water deficit and water table depth. On average, in drier climates the forests with a shallow water table had lower productivity than those with a deep water table, with this difference decreasing within wet climates, where lower productivity was confined to a very shallow water table. We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland (terra‐firme) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change
Traditional and Computational Screening of Non-Toxic Peptides and Approaches to Improving Selectivity
Get PDFPeptides have positively impacted the pharmaceutical industry as drugs, biomarkers, or
diagnostic tools of high therapeutic value. However, only a handful have progressed to the market.
Toxicity is one of the main obstacles to translating peptides into clinics. Hemolysis or hemotoxicity,
the principal source of toxicity, is a natural or disease-induced event leading to the death of vital red
blood cells. Initial screenings for toxicity have been widely evaluated using erythrocytes as the gold
standard. More recently, many online databases filled with peptide sequences and their biological
meta-data have paved the way toward hemolysis prediction using user-friendly, fast-access machine
learning-driven programs. This review details the growing contributions of in silico approaches
developed in the last decade for the large-scale prediction of erythrocyte lysis induced by peptides.
After an overview of the pharmaceutical landscape of peptide therapeutics, we highlighted the
relevance of early hemolysis studies in drug development. We emphasized the computational models
and algorithms used to this end in light of historical and recent findings in this promising field. We
benchmarked seven predictors using peptides from different data sets, having 7–35 amino acids in
length. According to our predictions, the models have scored an accuracy over 50.42% and a minimal
Matthew’s correlation coefficient over 0.11. The maximum values for these statistical parameters
achieved 100.0% and 1.00, respectively. Finally, strategies for optimizing peptide selectivity were
described, as well as prospects for future investigations. The development of in silico predictive
approaches to peptide toxicity has just started, but their important contributions clearly demonstrate
their potential for peptide science and computer-aided drug design. Methodology refinement and
increasing use will motivate the timely and accurate in silico identification of selective, non-toxic
peptide therapeutics
Analysis of energy future pathways for Ecuador facing the prospects of oil availability using a system dynamics model. Is degrowth inevitable?
Get PDFThe aim of this paper is to develop a system dynamics model to assess the energy future up to 2050 for Ecuador considering its condition of oil producing country. Three scenarios have been developed with different assumptions regarding national and global oil availability under a Business-As-Usual narrative.
Energy demand would have a 2.4-fold increase by 2050 with predominance of petroleum products in a BAU scenario with unlimited oil access. In constrained scenarios, restricted availability of oil might pressure final demand to be reduced in 31%–40% compared to BAU. Limited imports of oil and petroleum products might produce shortages in supply, causing a downfall in economic activity in sectors with high dependency on these fuels Electricity would partially substitute fossil fuels but is not enough to offset economy decay in constrained scenarios. Limiting oil exports would not have an important effect since the decline of Ecuador's oil wells is expected to be too fast. Oil exports would cease by 2030–2045. When BAU scenarios are evaluated considering limited fossil energy access in a decaying world oil production, arise the necessity to explore new strategies to deal with an energy/economic shock