Learning cancer-related drug efficacy exploiting consensus in coordinated motility within cell clusters

D Di Giuseppe, F Corsi, A Mencattini… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Objective: The ability of cells to collectively move is essential in various biological contexts
including cancer metastasis. In this paper, we propose an automatic video analysis tool to …

A camera sensors-based system to study drug effects on in vitro motility: The case of PC-3 prostate cancer cells

MC Comes, A Mencattini, D Di Giuseppe, J Filippi… - Sensors, 2020 - mdpi.com
Cell motility is the brilliant result of cell status and its interaction with close environments. Its
detection is now possible, thanks to the synergy of high-resolution camera sensors, time …

The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications

MC Comes, P Casti, A Mencattini, D Di Giuseppe… - Scientific reports, 2019 - nature.com
Cell-cell interactions are an observable manifestation of underlying complex biological
processes occurring in response to diversified biochemical stimuli. Recent experiments with …

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments

A Mencattini, D Di Giuseppe, MC Comes, P Casti… - Scientific reports, 2020 - nature.com
We describe a novel method to achieve a universal, massive, and fully automated analysis
of cell motility behaviours, starting from time-lapse microscopy images. The approach was …

Deciphering cancer cell behavior from motility and shape features: Peer prediction and dynamic selection to support cancer diagnosis and therapy

M D'Orazio, F Corsi, A Mencattini, D Di Giuseppe… - Frontiers in …, 2020 - frontiersin.org
Cell motility varies according to intrinsic features and microenvironmental stimuli, being a
signature of underlying biological phenomena. The heterogeneity in cell response, due to …

Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system

J Huth, M Buchholz, JM Kraus, M Schmucker… - BMC cell biology, 2010 - Springer
Background Cell motility is a critical parameter in many physiological as well as
pathophysiological processes. In time-lapse video microscopy, manual cell tracking remains …

A new method to address unmet needs for extracting individual cell migration features from a large number of cells embedded in 3D volumes

I Adanja, V Megalizzi, O Debeir, C Decaestecker - PloS one, 2011 - journals.plos.org
Background In vitro cell observation has been widely used by biologists and
pharmacologists for screening molecule-induced effects on cancer cells. Computer-assisted …

Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning

Y Goldstein, OT Cohen, O Wald, D Bavli, T Kaplan… - Science …, 2024 - science.org
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools,
capable of classifying cancer cells based on their functions, may substantially enhance …

Quantitative characterization of cell behaviors through cell cycle progression via automated cell tracking

Y Wang, Y Jeong, SM Jhiang, L Yu, CH Menq - PloS one, 2014 - journals.plos.org
Cell behaviors are reflections of intracellular tension dynamics and play important roles in
many cellular processes. In this study, temporal variations in cell geometry and cell motion …

CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation

Q Jiang, P Sudalagunta, MC Silva… - …, 2022 - academic.oup.com
Motivation Time-lapse microscopy is a powerful technique that relies on images of live cells
cultured ex vivo that are captured at regular intervals of time to describe and quantify their …