@SysBioGroup

We are an interdisciplinary group working in Systems Biology. We participate in interdisciplinary projects with theoretical and experimental groups

 La Plata, Argentina
Joined April 2018
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Osvaldo Chara and Juan Fernández were interviewed (in Spanish) on the CONICET website regarding SysBio’s new article on cardiac syncrhony. Here you can find the interview: conicet.gov.ar/disenan-una-h…

Diseñan una herramienta para predecir qué pacientes cardíacos responderán mejor a un tratamiento

Un equipo del CONICET creó un método para indicar con mayor precisión la terapia de resincronización cardíaca.

conicet.gov.ar
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We have recently implemented this method through a custom device and software. This study has been performed with the support from @SysBioGroup, @CONICETDialoga, @agenciaidiar y @Htal_Britanico.
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Since it is solely based on the patient´s surface electrocardiogram, our method can be easily implemented in any scenario where cardiac synchrony needs to be assessed. This is of particular interest during CRT candidate selection, device implant and post implant optimization.
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We tested our dyssynchrony index against mechanical dyssynchrony (assessed by strain echocardiography): It proved useful in predicting mechanical dyssynchrony. We also verified its efficacy in identifying the most efficient activation sequence.
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We found a cut-off value for the dyssynchrony index, separating synchronous from dyssynchronous populations.
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When tested in patients with abnormal conduction patterns, our index reflected the magnitude of the dyssynchrony commonly associated to these types of conduction.
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We found a correlation between voltage and speed in control subjects. From this observation we built a “dyssynchrony index” quantifying the deviation from the expected behavior.
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Impairment of the electrical synchrony of the heart results in mechanical dysfunction. There is still no reliable, universal method to assess cardiac electrical synchrony. We developed a pipeline for the automated reconstruction of the vectorcardiogram from a single surface ECG.
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Optimizing heart sisto-diastolic function: Is there a way to improve the work of a dysfunctional heart? Check out this article from Chara’s lab in collaboration with @Htal_Britanico by @Osvaldo_Chara, @damiosp and @Juan08319226. nature.com/articles/s41598-0…

Vectorcardiography-derived index allows a robust quantification of ventricular electrical synchrony

Scientific Reports - Vectorcardiography-derived index allows a robust quantification of ventricular electrical synchrony

nature.com
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Ultimately, our study gives a simple criterion (based on the Crossover Length) to select a finite or infinite approximation when modelling Reaction-Diffusion systems to study tissue morphogenesis. (9/9)
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The analytical solution of the finite-domain reaction-diffusion model and its extensions could improve the efficiency of computational multi-scale algorithms involving a signalling scale. (8/9)
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By recreating a FRAP experiment in silico, we found that the infinite-domain model wrongly estimates diffusion coefficients when the domain is smaller than the Crossover length. (7/9)
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We evaluated whether the infinite-domain model gives an accurate estimation of diffusion coefficients when fitted to finite spatial profiles, a procedure typically followed in Fluorescence Recovery After Photobleaching (FRAP) experiments. (6/9)
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Moreover, we found that the time it takes to reach the steady state (and its Standard deviation!) differs between small and large tissues. (5/9)
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We propose an observable accounting for the shape of the morphogen spatial distributions. By comparing a finite tissue with an infinite domain, this shape factor allowed us to define a Crossover length of ~3 morphogen characteristic lengths. (4/9)
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We found a Crossover length in a Reaction-Diffusion model. While above the crossover, assuming an infinite domain renders a good approximation; below the crossover, a finite domain should be used. (3/9)
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We analytically investigated the spatiotemporal distributions of morphogens predicted by the well-known reaction–diffusion model in a finite one-dimensional domain, as a proxy for a biological tissue, and compared it with the solution of the infinite-domain model. (2/9)
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When is it OK to assume a tissue as infinite? Read the last article from Chara's lab by @CeccarelliAS , @borgesaugust and @Osvaldo_Chara about spatiotemporal distribution of morphogens! royalsocietypublishing.org/d… (1/9)

Size matters: tissue size as a marker for a transition between reaction–diffusion regimes in...

Abstract. The reaction–diffusion model constitutes one of the most influential mathematical models to study distribution of morphogens in tissues. Despite

royalsocietypublishing.org
Royal Society Publishing
@RSocPublishing27 Jan 2022
Size matters - tissue size as a marker for a transition between reaction–diffusion regimes in spatio-temporal distribution of morphogens: ow.ly/lHS350HFrzc #RSOS #OpenAccess #ComputationalBiology #biophysics
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When is it OK to assume a tissue as infinite? Read the last preprint from Chara's lab by @CeccarelliAS @fiisau and @Osvaldo_Chara about spatiotemporal distribution of morphogens! biorxiv.org/content/10.1101/…

Size matters: An analytical study on the role of tissue size in spatiotemporal distribution of...

The reaction-diffusion model constitutes one of the most influential mathematical models to study the distribution of morphogens spreading within tissues. Despite its widespread appearance, the role...

biorxiv.org
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Curious about how cell proliferation and cell recruitment interact? Check out our new modelling and experimental adventure in Drosophila wing development by @Osvaldo_Chara and @H_Ariel_Alvarez in collaboration with Nahmad´s Lab published in @Dev_Bio_Journal !
H. Ariel Alvarez@H_Ariel_Alvarez21 May 2020
A dynamic cell recruitment process drives growth of the Drosophila wing by overscaling the vestigial expression pattern. @Osvaldo_Chara @SysBioGroup Our work with Nahmad´s Lab sciencedirect.com/science/ar…
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