Biology subjects

Lopez-Hernandez, A.

Publications and source records attributed to Lopez-Hernandez, A..

3 recordsLinked to original sources

bioRxiv2025

Mitochondrial Responses to Conventional and Ultra-high Dose Rate (FLASH) Radiation

PurposeUltra-high dose rate (>40 Gy/s, FLASH) radiation therapy (RT) provides equivalent tumor control while reducing normal tissue toxicity relative to conventional dose rate (CONV) RT. However, the mechanisms underlying the observed FLASH effect are unknown. We hypothesized that the preservation of mitochondrial integrity in nontumorigenic cells by FLASH RT could be a key factor in reducing normal tissue toxicity and improving overall treatment outcomes. MethodsWe examined mitochondrial health and function after CONV and FLASH in vitro, ex vivo, and in vivo through assays of metabolic flux, mitochondrial membrane potential, mitochondrial reactive oxygen species (ROS), mitochondrial DNA damage and copy number, mitochondrial morphology, and tumor growth and survival. ResultsIn in vitro assays, murine pancreatic cancer (PDAC) cells showed evidence of equal mitochondrial damage in response to CONV and FLASH, but nontumorigenic pancreatic cells were spared by FLASH. These results were recapitulated ex vivo, and mice treated with FLASH showed higher response rates and longer survival time than mice treated with CONV in an in vivo tumor model. ConclusionsCollectively, these results suggest that FLASH spares mitochondrial function in nontumorigenic cells, but not in PDAC cells, relative to CONV. The preservation of mitochondrial integrity in nontumorigenic cells may be a key mechanism underlying the reduced normal tissue toxicity observed with FLASH RT.

cancer biology↗

bioRxiv2023

A data-driven evaluation of Arabidopsis-centric research and the model species concept

The selection of Arabidopsis as a model organism played a pivotal role in advancing genomic science, firmly establishing the cornerstone of today s plant molecular biology. Competing frameworks to select an agricultural- or ecological-based model species, or to decentralize plant science and study a multitude of diverse species, were selected against in favor of building core knowledge in a species that would facilitate genome-enabled research that could assumedly be transferred to other plants. Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plant species. Comparing different machine learning algorithms, models trained and tested on Arabidopsis data achieved near perfect precision and recall values using the K-Nearest Neighbor method, whereas when tissue identity is predicted across the flowering plants using models trained on Arabidopsis data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64, depending on the algorithm used. Below-ground tissue is more predictable than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from Arabidopsis. This suggests that gene expression signatures rather than marker genes are more valuable to create models for tissue and cell type prediction in plants. Our data-driven results highlight that, in hindsight, the assertion that knowledge from Arabidopsis is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data and computational resources, it may be prudent to reevaluate the scientific emphasis on Arabidopsis and to prioritize the exploration of plant diversity.

plant biology↗

bioRxiv2019

Comprehensive analysis of the internal structure and firmness in American cranberry (Vaccinium macrocarpon Ait.) fruit

Cranberry (Vaccinium macrocarpon Ait.) fruit quality traits encompass many properties. Among these, fruit firmness has become a quality standard due to the recent demand increase for sweetened and dried cranberries (SDC). Traditionally, this trait has been measured by the cranberry industry using compression tests; however, it is poorly understood how fruit firmness is influenced by other characteristics. In this study, we developed a high-throughput computer-vision method to measure the internal structure of cranberry fruit, which may in turn influence cranberry fruit firmness. We measured the internal structure of 16 cranberry cultivars measured over a 40-day period. Internal structure data paired with fruit firmness values at each evaluation period allowed us to explore the correlations between firmness and internal morphological characteristics.

plant biology↗