A5073056076- Cell Image Analysis Techniques
- 3D Printing in Biomedical Research
- Microfluidic and Bio-sensing Technologies
- Image Processing Techniques and Applications
- Electrohydrodynamics and Fluid Dynamics
- Microfluidic and Capillary Electrophoresis Applications
- Cancer Cells and Metastasis
- Innovative Microfluidic and Catalytic Techniques Innovation
- Microbial Inactivation Methods
- Biosensors and Analytical Detection
- AI in cancer detection
- Cutaneous Melanoma Detection and Management
- Analytical Chemistry and Sensors
- Advanced Sensor and Energy Harvesting Materials
- Integrated Circuits and Semiconductor Failure Analysis
- Advanced Fluorescence Microscopy Techniques
- Magnetic and Electromagnetic Effects
- Cellular Mechanics and Interactions
- Emotion and Mood Recognition
- Pain Mechanisms and Treatments
- Generative Adversarial Networks and Image Synthesis
- Neuroscience and Neural Engineering
- S100 Proteins and Annexins
- Advanced Proteomics Techniques and Applications
- Single-cell and spatial transcriptomics
University of Rome Tor Vergata
2020-2025
Université Côte d'Azur
2014
There is a compelling need for approaches to predict the efficacy of immunotherapy drugs. Tumor-on-chip technology exploits microfluidics generate 3D cell co-cultures embedded in hydrogels that recapitulate simplified tumor ecosystems. Here, we present development and validation lung tumor-on-chip platforms quickly precisely measure ex vivo effects immune checkpoint inhibitors on T cell-mediated cancer death by exploiting power live imaging advanced image analysis algorithms. The integration...
High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data availability dynamic models link phenomena across levels: from genes cells, cells organs, through whole organism. The combination phenomics, deep learning, machine learning represents a strong potential for phenotypical investigation, leading way more embracing approach, called phenomics (MLP). In particular, in this work we...
One of the major problems in bioimaging, often highly underestimated, is whether features extracted for a discrimination or regression task will remain valid broader set similar experiments presence unpredictable perturbations during image acquisition process. Such an issue even more important when it addressed context deep learning due to lack priori known relationship between black-box descriptors (deep features) and phenotypic properties biological entities under study. In this regard,...
Abstract 3D hydrogel‐based cell cultures provide models for studying behavior and can efficiently replicate the physiologic environment. Hydrogels be tailored to mimic mechanical biochemical properties of specific tissues allow produce gel‐in‐gel models. In this system, microspheres encapsulating cells are embedded in an outer hydrogel matrix, where able migrate. To enhance efficiency such studies, a lab‐on‐a‐chip named migration‐chip (3DCM‐chip) is designed, which offers substantial...
Recent advances in microfluidic technology and biomaterial science have augmented the use of organ-on-chip (OoC) to closely mimic human pathophysiology. Thus, it is now established that pericellular micro-environment plays a key role on cell behaviour, such as response drug compounds. OoC been shown enable fabrication micro-physiological systems recapitulating features vivo tissues including, mechanical forces (matrix stiffness, fluid shear stress, compressive/tensile stress), gradients...
More than two decades ago, the advent of Nanotechnology has marked onset a new and critical field in science technology, highlighting importance multidisciplinary approaches to assess model potential human hazard newly developed advanced materials nanoscale, nanomaterials (NMs). is, by definition, field, that integrates knowledge techniques from physics, chemistry, biology, science, engineering manipulate matter at defined as anything comprised between 1 100 nm. The emergence nanotechnology...
Cell motility varies according to intrinsic features and microenvironmental stimuli, being a signature of underlying biological phenomena. The heterogeneity in cell response, due multilevel diversity especially relevant cancer, poses challenge identifying the scenario from trajectories. We propose here novel peer prediction strategy among trajectories, deciphering state (tumor vs. non-tumor), tumor stage response anti-cancer drug etoposide, based on morphology features, solving strong...
Abstract The incremented uptake provided by time-lapse microscopy in Organ-on-a-Chip (OoC) devices allowed increased attention to the dynamics of co-cultured systems. However, amount information stored long-time experiments may constitute a serious bottleneck experimental pipeline. Forward long-term prediction cell trajectories reduce spatial–temporal burden video sequences storage. Cell trajectory becomes crucial especially increase trustworthiness software tools designed conduct massive...
In aquaculture, the density of fish stock, use feeding, and surrounding environmental conditions can easily result in an excessive concentration harmful compounds that require continuous monitoring. Chemical sensors are available for most these compounds, however, operative monitoring water make development suitable long unattended deployments difficult. A possible solution is engineered automatic labs where uptake sample contact with reduced a minimal quantity reagents enables...
This paper introduces an epidermal antenna made of Laser-Induced Graphene (LIG) that is designed for hosting sensors within the UHF-RFID band (860-960 MHz). The upper bound performance identified through numerical simulations and it just 4 dB lower than a copper counterpart. Comparative assessments reveal significantly wider trace width necessary to mitigate intrinsic power loss LIG. Furthermore, offers first experimental demonstration LIG-based wireless flexible plaster, integrating...
One of the most challenging frontiers in biological systems understanding is fluorescent label-free imaging. We present here NeuriTES platform that revisits standard paradigms video analysis to detect unlabeled objects and adapt dynamic evolution phenomenon under observation. Object segmentation reformulated using robust algorithms assure regular cell detection transfer entropy measures are used study inter-relationship among parameters related evolving system. applied automatic neurites...
Cell motility is the brilliant result of cell status and its interaction with close environments. Its detection now possible, thanks to synergy high-resolution camera sensors, time-lapse microscopy devices, dedicated software tools for video data analysis. In this scenario, we formulated a novel paradigm in which considered individual cells as sort sensitive element sensor, exploits transducer returning movement an output signal. way, allows us retrieve information about chemical composition...
In computer vision systems, the final measurement result can be a digital output provided by software, i.e., diagnostic value along with an uncertainty interval. line previous work on melanoma disease, we present here platform for image analysis based Variational Auto-Encoders (VAE), category of deep learning generative models that learns how to reproduce in encoder/decoder strategy. Latent variables extracted from VAE architecture are compact representations appearance objects and used as...
Pain is an alert state of the human body that can be conveyed to external world through different modalities. A possible communication channel for pain represented by facial expressions, whose role in social interactions has been well established. In this work, link between and transfer entropy (TE), passing investigated. new approach vision-based measurement (VBM) presented, which based on TE among time-series landmarks positions. The system composed three main blocks: VBM block automatic...
Pain is a health problem of vast dimension that requires prompt diagnosis. However, the evaluation criteria currently used in clinical settings are based on self-rating scales, which subjective and prone to error. This may cause administering improper analgesic treatments, either dosage or duration. For scope providing objective measures pain help devising effective therapeutic choices, we designed personalized platform for sensing monitoring pain. As input platform, visual, speech...
The advances in the deep learning field have paved way to novel strategies represent digital image data form of synthetic descriptors. Variational Auto-Encoders (VAE) architectures are generative powerful tools not only reconstruct input images but also extract meaningful information for task pattern classification. first part VAE network, called encoder, aims condense into a reduced set low-level descriptors, latent variables. second part, decoder, use variable reverse process that...
Detecting circulating tumor cells (CTCs) is a challenge in cancer research. Their dissemination into the blood stream represents crucial event formation of metastases from primary tumor. For this reason, targeting CTCs human liquid biopsies warning for invasiveness, progression, and prognosis. In regard, by means optically induced dielectrophoresis (ODEP) technique, we investigated response to electric field, at different frequencies, prostatic carcinoma PC3 cells, which mimic derived...
A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction 2D multi-frequency cell trajectories. Like in a "ping-pong" match, two virtual electrode barriers an alternate mode with varying frequencies the input voltage. The so-derived motions are characterized via time-lapse microscopy, tracking, state-of-the-art machine learning algorithms, like wavelet scattering transform (WST). As...