Biology subjects

Garcia, J. J.

Publications and source records attributed to Garcia, J. J..

3 recordsLinked to original sources

bioRxiv2026

A Novel ILP Framework to Identify Compensatory Pathways in Genetic Interaction Networks with GIDEON

In Bakers yeast, there exists a comprehensive collection of pairwise epistasis experiments that, for nearly every pair of non-essential genes, measures the growth of the double-knockout strain as compared to its component single knockouts. This data can be represented as a weighted signed graph termed the genetic interaction network, and we introduce a new ILP-based method named GIDEON to search for a diverse collection of Between-Pathway Models (BPMs) in this network, where BPMs are a graph motif signature that indicates potential compensatory pathways in the genetic interaction network. With both an improved distribution-informed edge weighting scheme and an improved ILP method, GIDEON produces BPM collections that are substantially larger and with better functional enrichment compared to previous methods. We find some interesting new BPM gene sets including one with potential insights into antifungal drug targets through ties between ergosterol and aromatic amino acid biosynthesis.

bioinformatics↗

bioRxiv2026

Environmental and biotic drivers of Aedes albopictus spatiotemporal distribution in the Argentina-Brasil-Paraguay subtropical triple border: The key role of periurban and disturbed wild environments

There is empirical evidence that biophysical factors determine the spatio-temporal distribution of mosquito vectors, and identifying the variables that shape their ecology allows decision-makers to design effective surveillance and control strategies. This study evaluated the spatiotemporal distribution of Aedes albopictus in relation to environmental and biotic variables in the Iguazu Department, Misiones Province, Argentina, within the tri-border region shared with Brazil and Paraguay. Environmental characterization integrated field data and remotely sensed biophysical variables, and vector occurrence was analyzed at micro- and meso-spatial scales using generalized linear mixed models. Eleven sampling sessions were conducted between April 2019 and February 2020 at 81 sites representing urban, periurban, and wild environments. A total of 1,614 Ae. albopictus and 4,358 Ae. aegypti specimens were identified. Rainfall, minimum temperature, exposure days, and land cover were the main predictors of Ae. albopictus presence, showing nonlinear responses to precipitation and vegetation. The selected model explained 67% of the variance. The species exhibited clear spatiotemporal stratification, with periurban and disturbed wild areas functioning as ecotones favorable to its establishment. These findings provide key insights to guide preventive actions and strengthen integrated vector management strategies in the region.

ecology↗

bioRxiv2023

Integrative Spatial Analysis of H&E and IHC Images Identifies Prognostic Immune Subtypes Correlated with Progression-Free Survival in HPV-Related Oropharyngeal Squamous Cell Carcinoma

PurposeDeep learning techniques excel at identifying tumor-infiltrating lymphocytes (TILs) and immune phenotypes in hematoxylin and eosin (H&E)-stained slides. However, their ability to elucidate detailed functional characteristics of diverse cellular phenotypes within tumor immune microenvironment (TME) is limited. We aimed to enhance our understanding of cellular composition and functional characteristics across TME regions and improve patient stratification by integrating H&E with adjacent immunohistochemistry (IHC) images. MethodsA retrospective study was conducted on patients with HPV(+) oropharyngeal squamous cell carcinoma (OPSCC). Using paired H&E and IHC slides for 11 proteins, a DL pipeline was used to quantify tumor, stroma, and TILs in the TME. Patients were classified into immune inflamed (IN), immune excluded (IE), or immune desert (ID) phenotypes. By registering the IHC and H&E slides, we integrated IHC data to capture protein expression in the corresponding tumor regions. We further stratified patients into specific immune subtypes, such as IN, with increased or reduced CD8+ cells, based on the abundance of these proteins. This characterization provided functional insight into the H&E-based subtypes. ResultsAnalysis of 88 primary tumors and 70 involved lymph node tissue images revealed an improved prognosis in patients classified as IN in primary tumors with high CD8 and low CD163 expression (p = 0.007). Multivariate Cox regression analysis confirmed a significantly better prognosis for these subtypes. ConclusionsIntegrating H&E and IHC data enhances the functional characterization of immune phenotypes of the TME with biological interpretability, and improves patient stratification in HPV(+) OPSCC.

cancer biology↗