Biology subjects

Tovar, H.

Publications and source records attributed to Tovar, H..

6 recordsLinked to original sources

bioRxiv2026

Metabolic cost sets the shear stress profile of optimal vascular trees

Vascular remodeling responds to local wall shear stress, but transport efficiency belongs to the network as a whole. We connect these scales by minimizing dissipation under a fixed maintenance budget, with vessel cost proportional to mass raised to an exponent b. At an optimum, dissipated power is proportional to vessel cost. This yields the shear set point |{tau} | {propto} r^(b-1){ell}^(b-1)/2 for radius r and length {ell}, with uniform shear recovered at b = 1. The associated local adaptation rule decreases the global functional, although the topology it reaches retains a memory of development. Simulations with 400 and 700 sinks show that staged growth improves transport mainly by allowing pruned connections to regrow. Fluctuating demand sustains loops without increasing the maintenance budget. The local condition fixes allocation on a given support, whereas growth and variable demand shape the topology that survives.

biophysics↗

bioRxiv2024

Transcriptomic signatures and network-based methods uncover new Senescent Cell Anti-Apoptotic Pathways and Senolytics

Cellular senescence is an irreversible cell cycle arrest caused by various stressors that damage cells. Over time, senescent cells accumulate and contribute to the progression of multiple age-related degenerative diseases. It is believed that these cells accumulate partly due to their ability to evade programmed cell death through the development and activation of survival and anti-apoptotic resistance mechanisms; however, many aspects of how these survival mechanisms develop and activate are still unknown. By analyzing transcriptomic signature profiles generated by the LINCS L1000 project and using network-based methods, we identified various genes that could represent new senescence-related survival mechanisms. Additionally, employing the same methodology, we identified over 600 molecules with potential senolytic activity. Experimental validation of our computational findings confirmed the senolytic activity of Fluorouracil, whose activity would be mediated by a multi-target mechanism, revealing that its targets AURKA, EGFR, IRS1, SMAD4, and KRAS are new senescence-associated survival and anti-apoptotic resistance pathways. The development of these pathways could depend on the stimulus that induces cellular senescence. The SCAPs development and activation mechanisms proposed in this work offer new insights into how senescent cells survive. Identifying new anti-apoptotic resistance targets and drugs with potential senolytic activity paves the way for developing new pharmacological therapies to eliminate senescent cells selectively. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/596326v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@137c0d4org.highwire.dtl.DTLVardef@154af55org.highwire.dtl.DTLVardef@c32030org.highwire.dtl.DTLVardef@765ee4_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Prediction of myeloid malignant cells in Fanconi anemia using machine learning

Fanconi anemia (FA) is an inherited bone marrow failure syndrome with cancer predisposition. Most FA patients develop aplastic anemia during childhood and have an extremely high cumulative risk to develop cancer during their lifespan. Myeloid malignancy is one of the main tumor risks for patients with FA, including high-risk myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Although bone marrow transplantation is the treatment of choice for FA patients that develop aplastic anemia, patients with a more stable bone marrow remain at a high risk of presenting MDS/AML and should be monitored for appearance of myeloid malignant clones. Markers for an as-early-as-possible identification of emerging myeloid malignant cells are needed for the monitoring of patients with FA, since quick medical action after detection of neoplastic transformation is needed. In this work we have leveraged publicly available single cell RNA seq (scRNAseq) datasets of patients with MDS and AML for training deep neural networks (DNN). We have generated two machine learning models aimed to identify myeloid malignant transcriptional profiles in scRNAseq datasets from the bone marrow of patients with FA, one for detection of MDS and a second one for AML. Both predictors displayed high sensitivity, specificity, and accuracy for detection of single cell resolution myeloid malignant transcriptional profiles. Multiple tools for analysis of single cell transcriptional data were implemented to characterize the predicted MDS and AML cells. Our analysis suggests that the predicted MDS and AML cells from FA patients are enriched in the lympho-myeloid-primed progenitor (LMPP) and the granulocyte-monocyte progenitor (GMP) populations. The predicted MDS and AML cells have gene expression and master transcriptional factor profiles that suggest malignant transformation and that differ from the rest of FA cells. Also cues of immune evasion were detected using single cell pathway analysis (SCPA) and cell-cell communication profiles. Next work will be aimed to find potential cell surface markers on the predicted MDS and AML cells as well as to assess our predictions in primary samples from FA patients.

cancer biology↗

bioRxiv2020

Determining which mechanisms underlie facilitation by tussocks in tropical high mountains and their relative importance

Facilitation by tussocks is common in high-altitude tropical environments. It is thought that facilitation results from stress amelioration, but it is unclear which of the many stressors acting in these environments is ameliorated. We aimed at determining the relative importance of different stressors as drivers of facilitation by the tussock Festuca tolucensis in Mexico. We manipulated five stressors in the field: minimum temperatures by using electric radiators that kept plants warm; maximum temperatures by means of reflective sand that precluded temperature build-up during the day; UV radiation by using screens opaque to UV; poor soil properties by comparing soils from beneath tussocks and from bare ground; and low water availability by adding vermiculite to the soil. The performance (survival and growth) of Mexerion sarmentosum (a plant usually associated with Festuca) in these treatments was compared to that recorded under tussocks and in bare ground. Amelioration of extreme temperatures had the largest positive effects on Mexerion survival. UV radiation and increased soil humidity did not affect survival, although humidity increased growth rates. Nevertheless, tussocks reduced the growth of Mexerion, which is consistent with observations of competition between plants and soil microorganisms favoured by tussocks. Our results highlight the importance of the extreme daily fluctuations in temperature that characterise tropical mountains as fundamental drivers of their dynamics.

ecology↗

bioRxiv2018

ExtendAlign: a computational algorithm for delivering multiple global alignment results originated from local alignments.

In this work, we evaluated several tools used for the alignment of short sequences and found that most aligners execute reasonably well for identical sequences, whereas a variety of alignment errors emerge for dissimilar ones. Since alignments are essential in computational biology, we developed ExtendAlign, a post-analysis tool that corrects these errors and improves the alignment of dissimilar short sequences. We used simulated and biological data to show that ExtendAlign outperforms the other aligners in most metrics tested. ExtendAlign is useful for pinpointing the identity percentage for alignments of short sequences in the range of [~]35-50% similarity.

bioinformatics↗

bioRxiv2018

Master regulators of signaling pathways coordinate key processes of embryonic development in breast cancer

Signal transduction pathways allow cells to respond to environmental cues and can induce intracellular changes. In some contexts, like embryonic development, signal transduction plays crucial roles in cell fate determination and differentiation, while in developed organisms some of this processes contribute in the maintenance of the structural integrity of tissues.\n\nTumor cells are recognized as having deregulated signaling which leads to a series of abnormal behaviors known as the hallmarks of cancer. Although gene regulation is often viewed as the last step in signal transduction, transcriptional regulation of the components of a pathway may impact in the long term deregulation observed in tumors. The study of gene regulatory networks centered around genes of the signal transduction pathways allows the identification of transcriptional regulators with the greatest influence over the signal transduction gene signature, also denominated Master Regulators.\n\nIn this work we identify, the master regulators that regulate the expression of genes of 25 relevant pathways grouped in KEGG within the category of signal transduction in a breast cancer dataset. For this purpose we implemented a modified MARINa algorithm that identifies, from a network of regulons, those that possess more differentially expressed genes related to the process to be studied. We identified CLOCK, TSHZ2, HOXA2, MEIS2, HOXA3, HAND2, HOXA5, TBX18, PEG3 and GLI2 as the top 10 master regulators of signaling pathways in breast cancer. Nine of them are recognized for taking part in embryonic development associated processes.\n\nIndividual enrichment GO biological function for each TMR regulons showed to be significantly enriched in embryonic development related processes. Hedgehog signaling pathway was shown as enriched and also highly deregulated. The genes of the HOXA family are shared among most of the TMRs. Overall, this suggests the importance of the aberrant reprogramming of mechanisms present during embryonic development, being coopted in favor of tumor development.

systems biology↗