Biology subjects

Pappalardo, F.

Publications and source records attributed to Pappalardo, F..

4 recordsLinked to original sources

bioRxiv2021

Small Extracellular Vesicles Secreted by Region-specific Astrocytes Ameliorate the Mitochondrial Function in a Cellular Model of Parkinson's Disease

Extracellular vesicles (EVs) are emerging as powerful players in cell-to-cell communication both in health and diseased brain. In Parkinsons disease (PD) - characterized by selective dopaminergic (DAergic) neuron death in ventral midbrain (VMB) and degeneration of DAergic terminals in striatum (STR) - astrocytes (AS) exert dual harmful/protective functions. When activated by chemokine CCL3, AS promote a robust DAergic neuroprotection both in cellular and pre-clinical models of PD, with mechanisms not fully elucidated. Here we used a combination of techniques to characterize AS-EVs derived from VMB and STR, and investigated their potential to exert neuroprotection. First, we show that: (i) AS of both regions secrete small EVs of ~100 nm; (ii) VMB-AS release more EVs per cell than STR-AS under basal conditions; and (iii) only VMB-AS respond to CCL3 by producing more EVs, suggesting differential AS-EV secretion rate according to PD brain region. Next, addressing AS-EV potential against oxidative stress and mitochondrial toxicity, we found that AS-EVs, especially CCL3-AS-EVs, fully counteract H2O2-induced caspase-3 activation. Furthermore, using high resolution respirometry, we demonstrated that AS-EVs rescue the neuronal mitochondrial complex I function impaired by MPP+, with VMB-AS-EVs fully restoring ATP production in MPP+-injured neurons, highlighting a regional diversity of AS-EVs with neuroprotective implications for PD.

neuroscience↗

bioRxiv2020

Lysyl oxidase-like 2 (LOXL2) is Increased in Asthma and Contributes to Asthmatic Airway Remodelling

Airway smooth muscle cells (ASM) are fundamental to asthma pathogenesis, influencing bronchoconstriction, airway hyper-responsiveness, and airway remodelling. Extracellular matrix (ECM) can influence tissue remodelling pathways, however, to date no study has investigated the effect of ASM ECM stiffness and crosslinking on the development of asthmatic airway remodelling. We hypothesised that TGF{beta} activation by ASM is influenced by ECM in asthma and sought to investigate the mechanisms involved. This study combines in vitro and in vivo approaches: human ASM cells were used in vitro to investigate basal TGF{beta} activation and expression of ECM crosslinking enzymes. Human bronchial biopsies from asthmatic and non-asthmatic donors were used to confirm LOXL2 expression ASM. A chronic ovalbumin model of asthma was used to study the effect of LOXL2 inhibition on airway remodelling. We found that ASM cells from asthmatics activated more TGF{beta} basally than non-asthmatic controls and that diseased cell-derived ECM influences levels of TGF{beta} activated. Our data demonstrate that the ECM crosslinking enzyme LOXL2 is increased in asthmatic ASM cells and in bronchial biopsies. Crucially, we show that LOXL2 inhibition reduces ECM stiffness and TGF{beta} activation in vitro, and can reduce subepithelial collagen deposition and ASM thickness, two features of airway remodelling, in an ovalbumin mouse model of asthma. These data are the first to highlight a role for LOXL2 in the development of asthmatic airway remodelling and suggest that LOXL2 inhibition warrants further investigation as a potential therapy to reduce remodelling of the airways in severe asthma.

cell biology↗

bioRxiv2020

In Silico Trial to test COVID-19 candidate vaccines: a case study with UISS platform

SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. Here, we present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2.

bioinformatics↗

bioRxiv2020

Designing Topographically Textured Microparticles For Induction and Modulation of Osteogenesis in Mesenchymal Stem Cell Engineering

Mesenchymal stem cells have been the focus of intense research in bone development and regeneration. We demonstrate the potential of microparticles as modulating moieties of osteogenic response by utilizing their architectural features. Topographically textured microparticles of varying microscale features were produced by exploiting phase-separation of a readily-soluble sacrificial component from polylactic acid. The influence of varying topographical features on primary human mesenchymal stem cell attachment, proliferation and markers of osteogenesis was investigated. In the absence of osteoinductive supplements, cells cultured on textured microparticles exhibited notably increased expression of osteogenic markers relative to conventional smooth microparticles. They also exhibited varying morphological, attachment and proliferation responses. Significantly altered gene expression and metabolic profiles were observed, with varying histological characteristics in vivo. This study highlights how tailoring topographical design offers cell-instructive 3D microenvironments which allow manipulation of stem cell fate by eliciting the desired downstream response without use of exogenous osteoinductive factors.

bioengineering↗