Biology subjects

Camps, J.

Publications and source records attributed to Camps, J..

11 recordsLinked to original sources

bioRxiv2025

MonoAlg3D: Enabling Cardiac Electrophysiology Digital Twins with an Efficient Open Source Scalable Solver on GPU Clusters

Modelling and simulation are essential in biomedicine, and specifically in computational cardiology. Reliable, efficient and accurate solvers are critical. This study presents an open source, GPU-based cardiac electrophysiology solver for scalable digital twin multiscale simulations (MO_SCPLOWONOC_SCPLOWAO_SCPLOWLGC_SCPLOW3D), incorporating conduction system calibration and performance optimization. The solver employs the monodomain equation coupled with the Purkinje network, solved via the finite volume method, featuring a GPU-based linear solver and concurrent simulation dispatch with MPI. We demonstrate a 10.94x speedup over a CPU-based solution and scalability by running 512 simulations on 128 compute nodes, completing all coarse-mesh simulations in less than 24 minutes and fine-mesh simulations in 303 minutes. We also demonstrate integration into a cardiac digital twin pipeline for personalisation based on clinical data. The proposed open source solver enhances computational efficiency and physiological fidelity, enabling large-scale, high-speed cardiac simulations. This work marks a significant step toward fast and scalable cardiac simulations on GPU architectures, with integration in a Digital Twin personalisation pipeline including the conduction system.

bioengineering↗

bioRxiv2025

Sex-specific human electromechanical multiscale in-silico models for virtual therapy evaluation

Background and AimWomen are significantly under-represented in cardiovascular research and in the evaluation of treatment safety and efficacy, leading to poorer patient outcomes. Quantification and investigation of sex differences in human electromechanical function and underlying mechanisms is crucial. To address this, we present sex-specific human cellular and biventricular electromechanical models for mechanistic investigations into sex-differences in therapy evaluation through simulations. MethodsProtein genomic expression data from healthy human myocytes were used to calibrate sex-specific models of human cellular electrophysiology, subsequently integrated in biventricular electromechanical models with male and female anatomies. A validation, verification and uncertainty evaluation were implemented at the cellular and biventricular level, including validation using sex-specific datasets from randomised controlled trials for Dofetilide and Verapamil, with known sex-differences. Ionic mechanisms underlying sex-differences in drug response were mechanistically investigated. ResultsSex-specific electromechanical models recapitulate sex-differences from ionic currents to ECG biomarkers including QTc interval (Male: 312ms; Female: 339ms; 9% difference), T-wave amplitude (6-9% difference) and ST-steepness through electrophysiological changes alone. Sex-specific simulations demonstrate both ECG biomarkers and mechanical biomarkers (Female LVEF: 68%, Male LVEF: 50%) within healthy ranges in clinical data for male and female population in the UK Biobank (n= 806, 46% Male). ECGs sex-differences are primarily explained by ionic currents, whereas mechanical sex-differences are driven by anatomical differences, and secondarily through more robust calcium function in females. Under Dofetilide, simulations show exacerbated QT prolongation in women compared to men (54-78% increase in effect), and a T-wave amplitude decrease in males (up to 0.25 mV), consistent with clinical data. This is explained in simulations by lower repolarisation reserve in women (due to low potassium and high calcium currents) than men. Verapamil shows no effect on simulated QT in either sex, and divergent T-wave modulation (increased amplitude in females, decreased in males) consistent with clinical trial data. Simulations identify enhanced contractile reservoir in female compared to male, with lesser decreases to ejection fraction with calcium current block. ConclusionSimulations using novel, sex-specific cellular and biventricular electromechanical models reveal the primary role of ionic currents sex-differences in ECG and drug response, whereas mechanical sex-differences are also underpinned by anatomical differences. Main ContributionsO_LIDevelopment, calibration and validation of sex-specific human ventricular electromechanical, multiscale models. C_LIO_LIAn analysis of clinical randomised trial data in the context of sex-specific effects of multi-channel blockers on the ECG by dosage, where previous analysis focused on pharmacokinetics. C_LIO_LIConsideration of both sex-specific electrophysiology and anatomy explains sex-specific differences on the impact of drugs on ECG and mechanics. C_LIO_LISimulations demonstrate that the reduced repolarisation reserve in females increases the susceptibility to QTc prolongation via potassium channel block compared to males, and more robust calcium dynamics protect against t-wave amplitude reduction and the more severe contractility loss through L-type calcium inhibition observed in males. C_LI

physiology↗

bioRxiv2025

Calibration and validation strategy for electromechanical cardiac digital twins

State-of-the-art cardiac electromechanical modelling and simulation form the basis for recent developments in cardiac Digital Twin technologies. However, a comprehensive evaluation of electromechanical models at cellular, tissue, and organ level has yet to be performed that addresses both ECG and pressure-volume biomarkers. Such an evaluation would build credibility for applications of cardiac Digital Twins in clinical research and therapy development. We aimed to follow ASME V&V40 standards for calibration, validation, and sensitivity analysis of ventricular electromechanical models under healthy conditions, to progress towards the Digital Twin vision. We performed a multi-scaled review of ventricular electromechanics and compiled a dataset for calibration and validation incorporating ECG, pressure-volume, displacement, and strain biomarkers. When applied to a biventricular multiscale model, we achieved healthy calibrated values for the QRS duration (89 ms), QT interval (360 ms), left ventricular ejection fraction (LVEF) (51 %), peak systolic pressure (14 kPa), end diastolic (105 mL) and end systolic volumes (51 mL), peak ejection flow rate (180 mL/ms). Model validation was performed by comparison to displacement and strain biomarkers including systolic atrioventricular plane displacement (1.5 cm), systolic fibre strain (-0.18) and longitudinal strain (-0.15). Sensitivity analysis of model parameters at cellular and ventricular scales was also performed to inform model calibration and as a first step towards uncertainty quantification. We quantified the effects of variability in ionic conductance, mechanical stiffness, cross-bridge cycling dynamics, and systemic circulation on action potential and active tension dynamics at the cellular scale, and on ECG, pressure-volume, displacement, and strain biomarkers at the ventricular scale. Simulations showed that the relationship between healthy LVEF and T wave biomarkers was primarily underpinned by variability in L-type calcium channel conductance and SERCA activity through multi-scale effects. In this study, we provide a systematic framework for credibility assessment of cardiac electromechanical models based on both ECG and mechanical biomarkers, as a foundational step towards the cardiac Digital Twin vision.

bioengineering↗

bioRxiv2023

In Silico Evaluation of Cell Therapy in Acute versus Chronic Infarction: Role of Automaticity, Heterogeneity and Purkinje in Human

Human-based modelling and simulation offer an ideal testbed for novel medical therapies to guide experimental and clinical studies. Myocardial infarction (MI) is a common cause of heart failure and mortality, for which novel therapies are urgently needed. Although cell therapy offers promise, electrophysiological heterogeneity raises pro-arrhythmic safety concerns, where underlying complex spatio-temporal dynamics cannot be investigated experimentally. After demonstrating credibility of the modelling and simulation framework, we investigate cell therapy in acute versus chronic MI, and the role of cell heterogeneity, scar size and the Purkinje system. Simulations agreed with experimental and clinical recordings from ionic to ECG dynamics in acute and chronic infarction. Following cell delivery, spontaneous beats were facilitated by heterogeneity in cell populations, chronic MI due to tissue depolarisation, and slow sinus rhythm. Subsequent re-entrant arrhythmias occurred, in some instances with Purkinje involvement, and their susceptibility was enhanced by impaired Purkinje-myocardium coupling, large scars, and acute infarction. We conclude that homogeneity in injected cell populations minimises their spontaneous beating, which is enhanced by chronic MI, whereas a healthy Purkinje-myocardium coupling is key to prevent subsequent re-entrant arrhythmias, particularly for large scars.

bioengineering↗

bioRxiv2022

Ionic remodelling following myocardial infarction explains phenotypic variability in ECG and arrhythmic substrate but not in ejection fraction

AimsSudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic remodelling, which are reflected as variable phenotypes. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with the post-MI pro-arrhythmic heterogeneities are unknown. We aim to provide a mechanistic explanation of clinical phenotypes in acute and chronic MI, from ionic remodeling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. Methods and ResultsA human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets. Abnormalities caused by scar and border zone ionic remodeling are introduced in varying degrees as reported in experimental data obtained in acute and chronic infarction. Simulations enabled reproducing and explaining clinical phenotypes post-MI, from ionic remodelling to ECGs and pressure-volume loops. In acute MI, T-wave inversion and Brugada phenocopy were explained by up to 57 ms of local APD prolongation and activation failure due to the inhibition of potassium, sodium and calcium channels in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion caused by uneven potassium channel expression in border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI ionic remodelling reduced EF by up to 10% through inhibition of calcium transient amplitude due to weaker calcium currents or SERCA activity, but the EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. ConclusionsMulti-scale modelling and simulation coherently integrates experimental and clinical data at subcellular, tissue, and organ scales to unravel electromechanical disease mechanisms in MI. In acute post-MI, ionic remodelling and its effect on refractoriness and propagation failure in the BZ have a strong impact on phenotypic ECG variability, whereas in chronic post-MI, the repolarisation dispersion across the BZ is crucial. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.

bioengineering↗

bioRxiv2021

Targeting the mitochondrial RNA methyltransferase TRMT61B reveals new therapeutic opportunities in aneuploid cancer cells

Chromosomal instability (CIN) is an important source of genetic and phenotypic variation that has been extensively reported as a critical cancer related property that improves tumor cell adaptation and survival. CIN and its immediate consequence, aneuploidy, provoke adverse effects on cellular homeostasis that need to be overcome by developing efficient anti-stress mechanisms. Perturbations in these safeguard responses might be detrimental for cancer cells and represent an important tumor specific Achilles heel since CIN and aneuploidy are very rare events in normal cells. On the other hand, epitranscriptomic marks catalyzed by different RNA modifying enzymes have been found to change under several stress insults. Although CIN and aneuploidy are important intracellular stressors, their biological connection with RNA modifications is pending to be determined. In an in silico search for new cancer biomarkers, we have identified TRMT61B, a mitochondrial RNA methyltransferase enzyme, to be associated with high levels of aneuploidy. In the present work, we study the connection of this molecule with cancer and aneuploidy. First, we show increased protein amounts of TRMT61B in tumor cell lines with imbalanced karyotype as well as in different tumor types compared to unaffected control tissues. In addition, we demonstrate that depletion of TRMT61B in melanoma cells reduces cell proliferation either by fostering apoptosis and inhibiting autophagy in high-aneuploid (ANEhigh) cells or by inducing senescence in the case of low-aneuploid (ANElow) cell lines. Further, TRMT61B elimination compromises mitochondrial function and reduces the expression of several mitochondrial encoded proteins that are part of the electron transport chain. Finally, transwell and xenograft experiments revealed a reduced invasive and tumorigenic capacity upon TRMT61B depletion that strengthen the therapeutic value of this aneuploidy-associated biomarker. These results, which connect tumorigenesis, aneuploidy and mitochondrial RNA methylation, bring to the cancer field a new putative strategy to specifically target high aneuploid tumors.

cancer biology↗

bioRxiv2021

Copy-number intratumor heterogeneity contributes to predict relapse in chemotherapy-naive stage II colon cancer

Optimal selection of high-risk patients with stage II colon cancer is crucial to ensure clinical benefit of adjuvant chemotherapy after surgery. Here, we investigate the prognostic and predictive value of genomic intratumor heterogeneity and aneuploidy for disease recurrence. We combined SNP arrays, targeted next-generation sequencing, fluorescence in situ hybridization and inmunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the subclonality of copy-number alterations (CNAs) and mutations, CD8+ lymphocyte infiltration and their association with time to recurrence (TTR). Prognostic factors were included in machine learning analysis to evaluate their ability to predict individual relapse risk. Tumors from recurrent patients (N = 38) exhibited greater proportion of CNAs compared with non-recurrent (N = 46) (mean 31.3% vs. 23%, respectively; P = 0.014), which was confirmed in an independent cohort. Candidate chromosome-specific aberrations included the gain of the chromosome arm 13q (P = 0.02; HR, 2.67) and loss of heterozygosity at 17q22-q24.3 (P = 0.05; HR, 2.69), both associated with shorter TTR. CNA load positively correlated with intratumor heterogeneity (R = 0.52; P < 0.0001), indicating ongoing chromosomal instability. Consistently, subclonal copy-number heterogeneity was associated with elevated risk of relapse (P = 0.028; HR, 2.20), which we did not observe for subclonal mutations. The clinico-genomic model rated an area under the curve of 0.83, achieving a 10% incremental gain compared to clinicopathological markers. In conclusion, tumor aneuploidy and copy-number heterogeneity were predictive of a poor outcome in early-stage colon cancer, and improved discriminative performance in comparison to clinicopathological data.

genomics↗

bioRxiv2020

Risk factors associated with mortality in hospitalized patients with SARS-CoV-2 infection. A prospective, longitudinal, unicenter study in Reus, Spain

Spain is one of the countries that has suffered the most from the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the strain that causes coronavirus disease 2019 (COVID-19). However, there is a lack of information on the characteristics of this disease in the Spanish population. The objective of this study has been to characterize our patients from an epidemiological point of view and to identify the risk factors associated with mortality in our geographical area. We performed a prospective, longitudinal study on 188 hospitalized cases of SARS-Cov-2 infection in Hospital Universitari de Sant Joan, in Reus, Spain, admitted between 15th March 2020 and 30th April 2020. We recorded demographic data, signs and symptoms and comorbidities. We also calculated the Charlson and McCabe indices. A total of 43 deaths occurred during the study period. Deceased patients were older than the survivors (77.7 {+/-} 13.1 vs. 62.8 {+/-} 18.4 years; p < 0.001). Logistic regression analyses showed that fever, pneumonia, acute respiratory distress syndrome, diabetes mellitus and cancer were the variables that showed independent and statistically significant associations with mortality. The Charlson index was more efficient than the McCabe index in discriminating between deceased and survivors. This is one of the first studies to describe the factors associated with mortality in patients infected with SARS-CoV-2 in Spain, and one of the few in the Mediterranean area. We identified the main factors independently associated with mortality in our population. Further studies in are needed to complete and confirm our findings.

microbiology↗

bioRxiv2019

Cancer-type specific aneuploidies hard-wire chromosome-wide gene expression patterns of their tissue of origin

Most carcinomas have characteristic chromosomal aneuploidies specific to the tissue of tumor origin. The reason for this specificity is unknown. As aneuploidies directly affect gene expression, we hypothesized that cancer-type specific aneuploidies, which emerge at early stages of tumor evolution, confer adaptive advantages to the physiological requirements of the tissue of origin. To test this hypothesis, we compared chromosomal aneuploidies reported in the TCGA database to chromosome arm-wide gene expression levels of normal tissues from the GTEx database. We find that cancer-type specific chromosomal aneuploidies mirror differential gene expression levels specific to the respective normal tissues which cannot be explained by copy number alterations of resident cancer driver genes. We propose that cancer-type specific aneuploidies "hard-wire" chromosome arm-wide gene expression levels present in normal tissues, favoring clonal expansion and tumorigenesis. One sentence summaryThe clonal evolution of cancer is initiated by tissue-specific transcriptional requirements

cancer biology↗

bioRxiv2018

CNApp: a web-based tool for integrative analysis of genomic copy number alterations in cancer

Somatic copy number alterations (CNAs) are a hallmark of cancer. Although CNA profiles have been established for most human tumor types, their precise role in tumorigenesis as well as their clinical and therapeutic relevance remain largely unclear. Thus, computational and statistical approaches are required to thoroughly define the interplay between CNAs and tumor phenotypes. Here we developed CNApp, a user-friendly web tool that offers sample- and cohort-level computational analyses, allowing a comprehensive and integrative exploration of CNAs with clinical and molecular variables. By using purity-corrected segmented data from multiple genomic platforms, CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to a pan-cancer dataset of 10,635 genomes from TCGA showing that CNA patterns classify cancer types according to their tissue-of-origin, and that broad and focal CNA scores positively correlate in samples with low amounts of whole-chromosome and chromosomal arm-level imbalances. Moreover, using the hepatocellular carcinoma cohort from the TCGA repository, we demonstrate the reliability of the tool in identifying recurrent CNAs, confirming previous results. Finally, we establish machine learning-based models to predict colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and specific genomic imbalances. In summary, CNApp facilitates data-driven research and provides a unique framework for the first time to comprehensively assess CNAs and perform integrative analyses that enable the identification of relevant clinical implications. CNApp is hosted at http://cnapp.bsc.es.

genomics↗

bioRxiv2017

Colorectal cancer susceptibility loci as predictive markers of rectal cancer prognosis after surgery

BackgroundColorectal cancer (CRC) is among the leading causes of cancer death. Rectal cancers account for one third of CRC cases. The role and significance of colorectal cancer risk loci in rectal cancer progression has not been investigated.\n\nMethodsWe generated and explored a dataset from 230 rectal cancer patients by gene expression microarray analysis of cancer samples and matched controls, and SNP arrays of germline DNA.\n\nResults8q24 (upstream of MYC) and 18q21 (in the intron of SMAD7), two of the loci most strongly linked with colorectal cancer risk, as well as 20q13 (in the intron of LAMA5), are tightly associated with the prognosis of rectal cancer patients. For SNPs on 18q21 (rs12953717 and rs4464148) and 20q13 (rs4925386), alleles that correlate with higher risk for the development of colorectal cancer are associated with shorter disease free survival. However, for rs6983267 on 8q24, the low risk allele is associated with a higher risk for recurrence and metastasis after surgery, and importantly, is strongly correlated with the resistance of colorectal cancer cell lines to chemoradiotherapy. We also found that although MYC expression is dramatically increased in cancer, patients with higher levels of MYC have a better prognosis. The expression of SMAD7 is weakly correlated with disease free time. Notably, the presence of the 8q24 and 18q21 SNP alleles is not correlated with a change of expression of MYC and SMAD7. rs4464148, and probably rs6983267 and rs4925386, are linked with overall survival time of patients.\n\nConclusionsSNPs at three colorectal cancer risk loci detect subpopulations of rectal cancer patients with poor prognosis. rs6983267 probably affects prognosis through interfering with the resistance of cancer cells to chemoradiotherapy.

cancer biology↗