University of Puerto Rico at Mayagüez Institutional Repository
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Publication Restricted Characterization of the habitat suitability of the atmosphere of Venus(2026-06-11)This study pursued two objectives: analyzing data from the Arecibo Observatory to determine Venus’s brightness temperature and search for biologically relevant molecules, and assessing atmospheric habitability using habitat suitability models. Observations were performed using Arecibo’s 12 m and 305 m radio telescopes. Analysis of these yielded an average brightness temperature of 626.5 ± 167.7 K (1σ standard deviation), consistent with previous studies. No spectral lines of the evaluated species were detected, likely due to instrumental sensitivity and limited observation times. Modeling results showed that potential habitability peaks between 53–58 km, within Venus’s cloud decks, but overall habitability was extremely low due to limited water activity and scarcity of biogenic elements. These results reinforce that Venus’s atmosphere is highly inhospitable to terrestrial life while demonstrating the value of observational data and modeling approaches for astrobiological investigations.Publication Restricted Remote sensing of floating Sargassum biomass in coastal zones(2026-06-11)In the last decade, intensified coastal inundations of pelagic Sargassum across the tropical Atlantic and Caribbean have deteriorated coastal water quality and triggered mortality events – creating an urgent need for quantitative biomass assessments that focus beyond surface coverage to support forecasting and management efforts. However, existing satellite-based biomass models were developed for thin, pelagic mats and do not represent the vertically stacked, wave-compressed accumulations common in coastal zones. Here we developed and evaluated a model to predict Sargassum biomass from hyperspectral data using controlled mesocosms and in situ observations designed to capture a broad density range of nearshore mats. Our model generally agreed with the previously established pelagic model but diverged at higher index values, where dense, vertically stacked mats saturated reflectance and produced nonlinear relationships. We improved quantitative Sargassum biomass estimation in nearshore environments to provide a foundation for operational coastal monitoring and the development of early-warning systems.Publication Restricted Genome-wide SNP analysis reveals high genetic connectivity in the pelagic wahoo (Acanthocybium solandri) around Puerto Rico(2026-06-11)Understanding population connectivity is essential for sustainable management of pelagic fishes, particularly for wahoo (Acanthocybium solandri), which supports economically important fisheries. Here, we present the first population genomic assessment of wahoo in the Caribbean Sea, focused around Puerto Rico (PR), evaluating genetic connectivity using genome-wide single nucleotide polymorphisms (SNPs) data generated through Restriction site-Associated DNA Sequencing (RAD-Seq). We analyzed 47,775 high-quality SNPs from 46 individuals sampled across four coastal regions in PR. Various complementary approaches, including pairwise FST, principal component analysis (PCA), discriminant principal component analysis (DPCA), and analysis of molecular variance (AMOVA), consistently revealed weak genetic differentiation and high genetic connectivity among regions. Most genetic variation was distributed within individuals, with only a very small proportion attributable to differences among regions. No loci under divergent selection were detected, indicating neutral population structure. Results suggest wahoo around PR represent a single local population which supports fishery management as a single management unit, although this does not preclude the risk of stock depletion under uneven fishing pressure across the region. Our use of SNPs and RAD-Seq warrants additional research throughout the region to further define the regional population structure of wahoo to enhance management and conservation of the species.Publication Embargo Analysis of gene expression data by BioOptimatics to investigate association between Systemic Lupus Erythematosus and SARS- CoV-2 infection(2026-06-11)Systemic lupus erythematosus (SLE) is a chronic autoimmune condition of multifactorial origin, involving genetic, environmental, and hormonal factors, and is known to have a higher prevalence in women than in men. Genetic factors play an important role in the initiation and progression of SLE by influencing immune system responses. Nevertheless, the specific mechanisms through which certain genes contribute to SLE pathogenesis remain insufficiently studied. In a related context, several literature reviews suggest that viral infections may act as triggers or amplifiers of autoimmune processes; however, the shared biological signaling mechanisms between viral infections and SLE have not yet been fully characterized. SARS-CoV-2 infection is a viral disease caused by the SARS-CoV-2 coronavirus, identified as the agent responsible for the COVID-19 pandemic in 2019. This virus primarily affects the respiratory system and can compromise other organs and systems of the body due to its ability to induce an intense inflammatory and immune response. In addition to the acute phase, symptoms known as Long COVID can develop months after the initial infection. This is associated with prolonged dysregulation of the immune system, persistent activation of inflammatory pathways, and alterations in the production of type I interferons (IFN-I) and is frequently observed in men. This study explores the relationship between SARS-CoV-2 infection and SLE by analyzing changes in the expression of selected genes and their association with sex-related hormonal factors and immunological profiles characteristic of both conditions. To this end, the BioOptimatics methodology is employed with the objective of finding genes that change their expression the most for each condition and their expression changes correlations. Gene expression datasets were analyzed to identify maximal correlation patterns associated with type I interferon signaling, JAK– STAT pathway activation, antiviral effector modules, and CD8⁺ T cell–related immune responses, particular emphasis was placed on sex-stratified expression profiles to explore potential hormone- associated immune response. The list of genes with the most expression changes between the groups analyzed for SLE comparison groups were: DEFA3, IFI27, IFI44, IFI44L, and IFIT3. The genes selected by the analysis related to SARS-CoV-2 infection were HLA_DQA1, HLA_DQB1, LAMP3, and IFI35, and the genes that change their expression in both conditions and provide a link between both pathologies were MX1, OASL, ISG15, CD8A, IFIT2, BTS2, LTF, and CEACAM6. After reviewing the previous literature, this work proposes a connection pathway for the changes in gene expression that link SLE and the immune response to SARS-CoV-2 infection, confirming that the strongest genetic link between the two processes described is associated with sex. Systemic lupus erythematosus (SLE) predominantly affects women due to sex-linked immunological and genetic factors; however, this study reveals that certain key genetic markers are also expressed in men. This finding is crucial, as it connects two diseases with opposing epidemiological trends: the high prevalence of SLE in women versus the higher incidence of long COVID in men. This result suggests the existence of common immunogenetic mechanisms that operate beyond traditional biological differences between sexes.Publication Restricted Modelando decisiones de desalojo en respuesta a alertas de inundación(2026-06-11)Esta investigación desarrolló un modelo para estimar el comportamiento de evacuación de residentes en zonas inundables de Puerto Rico ante la recepción de alertas de inundación basadas en aplicaciones móviles. Para ello, se diseñó una encuesta de preferencias declaradas, en la que 189 participantes respondieron ocho escenarios hipotéticos de alerta, definidos según tres atributos: canal de comunicación, confiabilidad de la alerta y tiempo de anticipación. Las alternativas de respuesta fueron evacuar inmediatamente, evacuar más tarde o no evacuar. A partir de estas respuestas, se estimó un modelo logit multinomial, consistente con el marco del modelado de elección discreta. Los resultados mostraron que la confiabilidad de la alerta es el factor con mayor influencia sobre la decisión de evacuación, ya que aumenta significativamente la probabilidad de evacuar inmediatamente y reduce la probabilidad de no evacuar. También se observó que tiempos de anticipación mayores tienden a disminuir la urgencia percibida, mientras que el canal de difusión presentó un efecto menor y menos estable. En conjunto, los hallazgos evidencian que la efectividad de una alerta móvil depende más de la credibilidad del mensaje y de cómo comunica la inmediatez del riesgo que del medio específico por el cual se transmite. La investigación aporta evidencia aplicada al contexto puertorriqueño y ofrece una base útil para el diseño de sistemas de alerta temprana más efectivos y adaptados a comunidades vulnerables ante inundaciones.
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