Biology subjects

Palumbo, A.

Publications and source records attributed to Palumbo, A..

3 recordsLinked to original sources

bioRxiv2024

Longitudinal Prediction of Drug Response in High-Grade Serous Ovarian Cancer Organoid Cultures Aligning with Clinical Responses

High-grade serous ovarian cancer (HGSOC) ranks among the most aggressive gynecological malignancies. Its high mortality stems from frequent recurrence post-primary treatments and development of platinum resistance. Since, traditional drug development via animal models is time-consuming and lacks reproducibility, in precision cancer medicine, primary patient-derived organoids (PDOs) offer a solution by replicating disease pathophysiology and expediting drug screening. We developed an expandable HGSOC organoid platform for rapid drug screening and resistance testing. Our study aimed to validate the stability of seven PDO pairs in predicting drug responses over time. Organoids underwent low- and high-passage drug screenings over nine months, involving 21 conventional and FDA-approved drugs and proteomic analyses. Comparison of in vitro outcomes with clinical data confirmed the platforms predictive capacity. Notably, a PDO with BRCA1 mutation exhibited resistance to Carboplatin and PARP inhibitors, highlighting organoid models clinical relevance for novel targeted therapies such as the Peptidylprolyl Cis/Trans Isomerase, NIMA-Interacting 1 (Pin1), a valuable target for HGSOC patients.

cancer biology↗

bioRxiv2023

Improvisation and Live Accompaniment Increase Motor Response and Reward During a Music Playing Task

Music provides an abstract reward that can enhance learning and motivation in humans. While music is often combined with exercise to improve performance and to upregulate mood, the relationship between music-induced reward and motor output is poorly understood. Here, we study music reward and motor output at the same time by capitalizing on music playing. Specifically, we investigate the effects of music improvisation and live accompaniment on motor, autonomic, and affective responses. Thirty adults performed a rhythm tapping task while (i) improvising or maintaining the beat and (ii) with live or recorded accompaniment. Motor response was characterized by acceleration of hand movements (accelerometry), wrist flexor and extensor muscle activation (electromyography), and the number of beats played. Autonomic arousal was measured by tonic response of electrodermal activity (EDA) and heart rate (HR). Affective responses were measured by a 12-item Likert scale. The combination of improvisation and live accompaniment, as compared to all other conditions, significantly increased acceleration of hand movements and muscle activation, as well as participant reports of enjoyment during music-playing. Improvisation, regardless of type of accompaniment, increased the number of beats played and autonomic arousal (including tonic EDA responses and several measures of HR), as well as participant reports of challenge. Importantly, increased motor response was associated with increased enjoyment during music improvisation only and not while participants were maintaining the beat. The increased motor responses achieved with improvisation and live accompaniment have important implications for enhancing dose of movement during music-based interventions for stroke rehabilitation. Significance StatementMusic provides a rewarding stimulus and improves motor performance and learning. However, the relationship between music reward and motor output is poorly understood. Here, we show that music improvisation with live accompaniment increased acceleration and muscle activation during movement, and that this increase in motor response was associated with increased enjoyment only when improvising. These findings are important for developing music interventions that target improved motor performance and learning in exercise and physical rehabilitation.

physiology↗

bioRxiv2020

EntireAxon: Deep learning deciphers four distinct patterns of axonal degeneration

BackgroundAxonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and to develop effective therapeutic interventions. Here, we evaluated the progression of AxD in cortical neurons using a novel microfluidic device in combination with a deep learning tool, the EntireAxon, that we developed for the enhanced-throughput analysis of AxD on microscopic images. ResultsThe EntireAxon convolutional neural network sensitively and specifically segmented the features of AxD, including axons, axonal swellings, and axonal fragments, and its performance exceeded that of human expert raters. In an in vitro model of AxD in hemorrhagic stroke induced by the hemolysis product hemin, we detected the concentration- and time-dependent degeneration of axons leading to a decrease in axon area, while the axonal swelling and axonal fragment area increased. Time course analysis revealed that axonal swellings preceded axon fragmentation, suggesting that swellings may be reliable predictors of AxD. Using a recurrent neural network, we further identified four morphological patterns of AxD (granular, retraction, swelling, and transport degeneration) in cortical axons subjected to hemin. ConclusionsThese findings indicate a morphological heterogeneity of AxD under pathophysiologic conditions. The combination of the microfluidic device with the EntireAxon deep learning tool enable the systematic analysis of AxD but also unravel a so far unknown intricacy in which AxD can occur in a disease context.

neuroscience↗