Search Results (6)

Background/Objectives: Asprosin is the endogenous ligand of the olfactory Olfr734 receptor linked to MASLD and glucose metabolism. Despite the involvement of asprosin in these processes, little has been published on the specific role of Olfr734 in liver function. The aim of this work is therefore to study the specific role of the olfactory Olfr734 receptor in MASLD and glucose metabolism. Methods: To achieve this objective, we performed a genetic inhibition specifically to inhibit Olfr734 in the livers of male mice. We then studied the progression of MASLD in DIO mice. In addition, we studied the glucose metabolism in hypoglycemia states and postprandial glucose production in standard diet-fed mice. Finally, analyses of liver biopsies from patients with obesity and with or without T2DM were conducted. Results: We found that hepatic Olfr734 levels vary according to changes in nutritional status and its knockdown effect in the liver is to increase the hepatic lipid content in DIO mice. Our results also showed that OLFR734 expression is involved in the adaptive response in terms of glucose production to nutrient availability. Finally, the hepatic human Olfr734 ortholog named OR4M1 has been observed to be at significantly higher levels in male patients with T2DM. Conclusions: This study increases understanding of the mechanisms by which the modulation of Olfr734 expression affects liver function. Full article

Heart failure with preserved ejection fraction (HFpEF) represents a global health challenge, with limited therapies proven to enhance patient outcomes. This makes the elucidation of disease mechanisms and the identification of novel potential therapeutic targets a priority. Here, we performed RNA sequencing on ventricular myocardial biopsies from patients with HFpEF, prospecting to discover distinctive transcriptomic signatures. A total of 306 differentially expressed mRNAs (DEG) and 152 differentially expressed microRNAs (DEM) were identified and enriched in several biological processes involved in HF. Moreover, by integrating mRNA and microRNA expression data, we identified five potentially novel miRNA–mRNA relationships in HFpEF: the upregulated hsa-miR-25-3p, hsa-miR-26a-5p, and has-miR4429, targeting HAPLN1; and NPPB mRNA, targeted by hsa-miR-26a-5p and miR-140-3p. Exploring the predicted miRNA–mRNA interactions experimentally, we demonstrated that overexpression of the distinct miRNAs leads to the downregulation of their target genes. Interestingly, we also observed that microRNA signatures display a higher discriminative power to distinguish HFpEF sub-groups over mRNA signatures. Our results offer new mechanistic clues, which can potentially translate into new HFpEF therapies. Full article

In this research, we address the problem of evaluating physical stability (PS) to close tailings dams (TD) from medium-sized Chilean mining using artificial intelligence (AI) algorithms. The PS can be analyzed through the study of critical variables of the TD that allow estimating different potential failure mechanisms (PFM): seismic liquefaction, slope instability, static liquefaction, overtopping, and piping, which may occur in this type of tailings storage facilities in a seismically active country such as Chile. Thus, this article proposes the use of four machine learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural networks (ANN), and extreme gradient boosting (XGBoost), to estimate five possible PFM. In addition, due to the scarcity of data to train the algorithms, the use of generative adversarial networks (GAN) is proposed to create synthetic data and increase the database used. Therefore, the novelty of this article consists in estimating the PFM for TD and generating synthetic data through the GAN. The results show that, when using the GAN, the result obtained by the ML models increases the F1-score metric by 30 percentage points, obtaining results of 97.4%, 96.3%, 96.7%, and 97.3% for RF, SVM, ANN, and XGBoost, respectively. Full article

Coastal wetlands areas are heterogeneous, highly dynamic areas with complex interactions between terrestrial and marine ecosystems, making them essential for the biosphere and the development of human activities. Remote sensing offers a robust and cost-efficient mean to monitor coastal landscapes. In this paper, we evaluate the potential of using high resolution satellite imagery to classify land cover in a coastal area in Concepción, Chile, using a machine learning (ML) approach. Two machine learning algorithms, Support Vector Machine (SVM) and Random Forest (RF), were evaluated using four different scenarios: (I) using original spectral bands; (II) incorporating spectral indices; (III) adding texture metrics derived from the grey-level covariance co-occurrence matrix (GLCM); and (IV) including topographic variables derived from a digital terrain model. Both methods stand out for their excellent results, reaching an average overall accuracy of 88% for support vector machine and 90% for random forest. However, it is statistically shown that random forest performs better on this type of landscape. Furthermore, incorporating Digital Terrain Model (DTM)-derived metrics and texture measures was critical for the substantial improvement of SVM and RF. Although DTM did not increase the accuracy in SVM, this study makes a methodological contribution to the monitoring and mapping of water bodies’ landscapes in coastal cities with weak governance and data scarcity in coastal management. Full article

Newborn screening (NBS) has widely been utilized in developed countries as a cost-effective public health strategy that reduces morbidity and mortality. Developing countries, however, are new to the NBS scene and have their own unique challenges, both in instituting the program as well as effectively acting on the results. NBS offers numerous ethical issues on a global scale, however, here we argue that there are unique ethical issues surrounding the development and expansion of newborn screening in Latin America given its highly heterogenous population. Once a NBS program is effectively instated, ethical considerations continue when pursuing expansion of screening to include further conditions. While Latin America grapples with the ethics of expanded newborn screening (ENBS), some developed countries discuss utility of genomic sequencing technologies in the newborn population. When the ability to detect further pathology is expanded, one must know what to do with this information. As rare diseases are identified either on ENBS or via genome sequencing, access to treatments for these rare diseases can be a real challenge. If we consider newborn screening as a global initiative, then we need more than a deontology approach to analyze these challenges; we need an approach that considers the unique characteristics of each territory and tremendous heterogeneity that exists prior to the implementation of these programs. As genomic technology advances further in the developed world, while some developing countries still lack even basic newborn screening, there is a further widening of the gap in global health disparities. The question is posed as to who has responsibility for these newborns’ lives on an international level. Without an approach towards newborn screening that accounts for the diverse global population, we believe optimal outcomes for newborns and families across the world will not be achieved. Full article

In this work we develop a study of positive periodic solutions for a mathematical model of the dynamics of computer virus propagation. We propose a generalized compartment model of SEIR-KS type, since we consider that the population is partitioned in five classes: susceptible (S); exposed (E); infected (I); recovered (R); and kill signals (K), and assume that the rates of virus propagation are time dependent functions. Then, we introduce a sufficient condition for the existence of positive periodic solutions of the generalized SEIR-KS model. The proof of the main results are based on a priori estimates of the SEIR-KS system solutions and the application of coincidence degree theory. Moreover, we present an example of a generalized system satisfying the sufficient condition. Full article