Biology subjects

Farina, S.

Publications and source records attributed to Farina, S..

7 recordsLinked to original sources

bioRxiv2026

Graph-Based Classification of Penetrating Arteries and Veins in Whole-Mouse Vasculature Datasets

Advances in whole-brain imaging have produced large-scale vascular datasets, yet most lack artery-vein annotations. However, this is essential for quantitative analysis of whole brain vascular structure, blood flow simulation and translational cerebrovascular research. For unlabelled datasets, manual labelling is infeasible at network scale, and surface-vessel tracing is hampered by reconstruction artefacts, limiting the insights that can be gained from these datasets. Here, we focus on penetrating vessel trees, i.e. descending arteries (A) and ascending veins (V). A supervised Random Forest classifier is trained on graph-derived morphological and topological tree features, including persistent homology. Training uses datasets from two imaging modalities: Light sheet (LS) microscopy with arterial staining and two-photon (TP) micrscopy with manual labelling in smaller samples. Classification reached 96% balanced accuracy on independent TP dataset and 93% on LS datasets. Topological features alone achieved competitive accuracy without relying on diameter measurements, demonstrating cross-modality portability. Arteries exhibit larger diameters and longer inter-bifurcation segments, likely facilitating their functional task of directed blood delivery. The veins show greater branching complexity, allowing low-pressure drainage. These signatures are stable across modalities, supporting their physological relevance. The framework enables A-V label transfer to unlabelled whole-brain TP graph datasets, validated through the V:A ratio as a function of middle cerebral artery (MCA) distance. Operating on graph representations derived from any volumetric imaging modality and requiring no retraining, the approach is applicable to LS, TP, and likely other imaging platforms, providing a scalable foundation for A-V quantification, vascular topological analysis, and haemodynamic modelling.

neuroscience↗

bioRxiv2024

A multiscale electro-metabolic model of a rat neocortical circuit reveals the impact of ageing on central cortical layers

The high energetic demands of the brain arise primarily from neuronal activity. Neurons consume substantial energy to transmit information as electrical signals and maintain their resting membrane potential. These energetic requirements are met by the neuro-glial-vascular (NGV) ensemble, which generates energy in a coupled metabolic process. In ageing, metabolic function becomes impaired, producing less energy and, consequently, the system is unable to sustain the neuronal energetic needs. We propose a multiscale model of electro-metabolic coupling in a reconstructed rat neocortex. This combines an electro-morphologically reconstructed electrophysiological model with a detailed NGV metabolic model. Our results demonstrate that the large-scale model effectively captures electro-metabolic processes at the circuit level, highlighting the importance of heterogeneity within the circuit, where energetic demands vary according to neuronal characteristics. Finally, in metabolic ageing, our model indicates that the middle cortical layers are particularly vulnerable to energy impairment.

neuroscience↗

bioRxiv2024

Machine Learning-based Predictions of Spatial Metabolic Profiles Demonstrate the Impact of Morphology on Astrocytic Energy Metabolism

This work introduces a machine learning framework that allows the investigation of the influence of reaction centers on the metabolic state of astrocyte cells. The proposed ML framework takes advantage of spatial astrocyte metabolic data stemming from numerical simulations for different reaction center configurations and allows for the following: (i) Discovery of cell groups of similar metabolic states and investigation of the reaction center configuration within each group. This approach allows for an analysis of the importance of the specific location of the reaction centers for a potentially critical metabolic state of the cell. (ii) Qualitative prediction of the energetic state of the cell (based on [ATP]: [ADP]) and quantitative prediction of the metabolic state of the cell by predicting the spatial average concentration of the metabolites or the complete spatial metabolic profile within the cell. (iii) Finally, the framework allows for the post hoc analysis of the developed quantitative predictive models using a SHAP approach to investigate the influence of the reaction center positions for further support of the insights drawn in steps (i)-(iii). Following the implementation of the framework, we observe that a uniform mitochondrial distribution within the cell results in the most robust energetic cell state. On the contrary, realizations of polarized mitochondrial distributions exhibit the worst overall cell health. Furthermore, we can make accurate qualitative predictions regarding cell health (accuracy = 0.9515, recall = 0.9753) and satisfactory predictions for the spatial average concentration and spatial concentration profiles of most of the metabolites involved. The techniques proposed in this study are not restricted to the dataset used. They can be easily used in other datasets that include findings from various metabolic computational models.

systems biology↗

bioRxiv2024

DNA damage response defects induced by the formation of TDP-43 and mutant FUS cytoplasmic inclusions and their pharmacological rescue.

Formation of cytoplasmic inclusions (CIs) of TDP-43 and FUS, along with DNA damage accumulation, is a hallmark of affected motor neurons in Amyotrophic Lateral Sclerosis (ALS). However, the impact of CIs on DNA damage response (DDR) and repair in this pathology remains unprobed. Here, we show that CIs of TDP-43 and FUSP525L, co-localizing with stress granules, lead to a dysfunctional DDR activation associated with physical DNA breakage. Inhibition of the activity of the DDR kinase ATM, but not of ATR, abolishes DDR signaling, indicating that DNA double-strand breaks (DSBs) are the primary source of DDR activation. In addition, cells with TDP-43 and FUSP525L CIs exhibit reduced DNA damage-induced RNA synthesis at DSBs. We previously showed that the two endoribonucleases DROSHA and DICER, also known to interact with TDP-43 and FUS during small RNA processing, contribute to DDR signaling at DSBs. Treatment with enoxacin, which stimulates DDR and repair by boosting the enzymatic activity of DICER, restores a proficient DDR and reduces DNA damage accumulation in cultured cells with CIs and in vivo in a murine model of ALS. In Drosophila melanogaster, Dicer-2 overexpression rescues TDP-43-mediated retinal degeneration. In summary, our results indicate that the harmful effects caused by TDP-43 and FUS proteinopathies include genotoxic stress and that the pharmacological stimulation of the DNA damage signaling and repair counteracts it.

molecular biology↗

bioRxiv2023

Orthogonal analysis of mitochondrial function in Parkinson's disease patients

The etiopathology of Parkinsons disease has been associated with mitochondrial defects at genetic, laboratory, epidemiological, and clinical level. These converging lines of evidence suggest that mitochondrial defects are systemic and causative factors in the pathophysiology of PD, rather than being mere correlates. Understanding mitochondrial biology in PD at granular level is therefore crucial from both basic science and translational perspectives. In a recent study, we investigated mitochondrial alterations in fibroblasts obtained from PD patients assessing mitochondrial function in relation to clinical measures. Our findings demonstrated that the magnitude of mitochondrial alterations parallels disease severity. In this study, we extend these investigations to blood cells and dopamine neurons derived from induced pluripotent stem cells reprogrammed from PD patients. To overcome the inherent metabolic heterogeneity of blood cells, we focused our analyses on metabolically homogeneous, accessible, and expandable erythroblasts. Our results confirm the presence of mitochondrial anomalies in erythroblasts and induced dopamine neurons. Consistent with our previous findings in fibroblasts, we observed that mitochondrial alterations are reversible, as evidenced by enhanced mitochondrial respiration when PD erythroblasts were cultured in a galactose medium that restricts glycolysis. This observation indicates that suppression of mitochondrial respiration may constitute a protective, adaptive response in PD pathogenesis. Notably, this effect was not observed in induced dopamine neurons, suggesting their distinct bioenergetic behavior. In summary, we provide additional evidence for the involvement of mitochondria in the disease process by demonstrating mitochondrial abnormalities in additional cell types relevant to PD. These findings contribute to our understanding of PD pathophysiology and may have implications for the development of novel biomarkers and therapeutic strategies.

neuroscience↗

bioRxiv2022

Mechanistic multiscale modelling of energy metabolism in human astrocytes indicates morphological effects in Alzheimer's Disease

Astrocytes with their specialized morphology are essential for brain homeostasis as metabolic mediators between blood vessels and neurons. In neurodegenerative diseases such as Alzheimers disease (AD), astrocytes adopt reactive profiles with molecular and morphological changes that could lead to the impairment of their metabolic support and impact disease progres-sion. However, the underlying mechanisms how metabolic function of human astrocytes is impaired by their morphological changes in AD is still elusive. To address this challenge, we developed and applied a metabolic multiscale modelling approach integrating the dynamics of metabolic energy pathways and physiological astrocyte morphologies acquired in human AD and age-matched control brain samples. The results demonstrate that the complex cell shape and intracellular organization of energetic pathways determine the metabolic profile and support capacity of astrocytes in health and AD conditions. Thus, our mechanistic approach indicates the importance of spatial orchestration in metabolism and allows for the identification of protective mechanisms against disease-associated metabolic impairments.

systems biology↗

bioRxiv2021

"How do we do this at a distance?!" A descriptive study of remote undergraduate research programs during COVID-19

The COVID-19 pandemic shut down undergraduate research programs across the U.S. Twenty-three sites offered remote undergraduate research programs in the life sciences during summer 2020. Given the unprecedented offering of remote research experiences, we carried out a study to describe and evaluate these programs. Using structured templates, we documented how programs were designed and implemented, including who participated. Through focus groups and surveys, we identified programmatic strengths and shortcomings as well as recommendations for improvements from the perspectives of participating students. Strengths included the quality of mentorship, opportunities for learning and professional development, and development of a sense of community. Weaknesses included limited cohort building, challenges with insufficient structure, and issues with technology. Although all programs had one or more activities related to diversity, equity, inclusion, and justice, these topics were largely absent from student reports even though programs coincided with a peak in national consciousness about racial inequities and structural racism. Our results provide evidence for designing remote REUs that are experienced favorably by students. Our results also indicate that remote REUs are sufficiently positive to further investigate their affordances and constraints, including the potential to scale up offerings, with minimal concern about disenfranchising students.

scientific communication and education↗