Confined cell migration along extracellular matrix space in vivo.

Collective migration of cancer cells is often interpreted using concepts derived from the physics of active matter, but the experimental evidence is mostly restricted to observations made in vitro. Here, we study collective invasion of metastatic cancer cells injected into the mouse deep dermis using intravital multiphoton microscopy combined with a skin window technique and three-dimensional quantitative image analysis. We observe a multicellular but low-cohesive migration mode characterized by rotational patterns which self-organize into antiparallel persistent tracks with orientational nematic order.

Health and income inequality: a comparative analysis of USA and Italy.

Introduction: Socio-economic background is often an important determinant for health with low income households having higher exposure to risk factors and diminished access to healthcare and prevention, in a way that is specific to each country.

Methods: Here, we perform a comparative analysis of the relations between health and income inequality in two developed countries, USA and Italy, using longitudinal and cross-sectional data from surveys.

Results And Discussion: We show that the income class determines the incidence of chronic pathologies, associated risk-factors and psychiatric conditions, but find striking differences in health inequality between the two countries.

Urban Scaling Functions: Emission, Pollution and Health.

Urban scaling is widely used to characterize the population dependence of city indicators including greenhouse gas emission. Here we analyze the population dependence of CO and PM2.5 emissions and concentrations across all European cities.

Regional evaluation of glyphosate pollution in the minor irrigation network.

Due to its low cost, its ease of use and to the "mild action" declared for long time by the Control and Approval Agencies towards it, the herbicide Glyphosate, is one of the currently best-selling and most-used agricultural products worldwide. In this work, we evaluated the presence and spread of Glyphosate in the Po River Basin (Northern Italy), one of the regions with the most intensified agriculture in Europe and where, by now for decades, a strong and general loss of aquatic biodiversity is observed. In order to carry out a more precise study of the real presence of this herbicide in the waters, samples were collected from the minor water network for two consecutive years, starting in 2022, at an interval time coinciding with those of the spring and summer crop treatments.

Artificial Intelligence for Precision Oncology of Triple-Negative Breast Cancer: Learning from Melanoma.

Thanks to new technologies using artificial intelligence (AI) and machine learning, it is possible to use large amounts of data to try to extract information that can be used for personalized medicine. The great challenge of the future is, on the one hand, to acquire masses of biological data that nowadays are still limited and, on the other hand, to develop innovative strategies to extract information that can then be used for the development of predictive models. From this perspective, we discuss these aspects in the context of triple-negative breast cancer, a tumor where a specific treatment is still lacking and new therapies, such as immunotherapy, are under investigation.

Harnessing deep learning to forecast local microclimate using global climate data.

Microclimate is a complex non-linear phenomenon influenced by both global and local processes. Its understanding holds a pivotal role in the management of natural resources and the optimization of agricultural procedures. This phenomenon can be effectively monitored in local areas by employing models that integrate physical laws and data-driven algorithms relying on climate data and terrain conformation.

Interrogating colorectal cancer metastasis to liver: a search for clinically viable compounds and mechanistic insights in colorectal cancer Patient Derived Organoids.

Background: Approximately 20-50% of patients presenting with localized colorectal cancer progress to stage IV metastatic disease (mCRC) following initial treatment and this is a major prognostic determinant. Here, we have interrogated a heterogeneous set of primary colorectal cancer (CRC), liver CRC metastases and adjacent liver tissue to identify molecular determinants of the colon to liver spreading. Screening Food and Drug Administration (FDA) approved drugs for their ability to interfere with an identified colon to liver metastasis signature may help filling an unmet therapeutic need.

Infiltration of tumor spheroids by activated immune cells.

Recent years have seen a tremendous growth of interest in understanding the role that the adaptive immune system could play in interdicting tumor progression. In this context, it has been shown that the density of adaptive immune cells inside a solid tumor serves as a favorable prognostic marker across different types of cancer. The exact mechanisms underlying the degree of immune cell infiltration is largely unknown.

A Pipeline to Investigate Fungal-Fungal Interactions: Isolates against Plant-Associated Fungi.

Soil fungi play essential roles in ecosystems, forming complex interaction networks with bacteria, yeasts, other fungi, or plants. In the framework of biocontrol strategies, -based fungicides are at the forefront of research as an alternative to synthetic ones. However, the impact of introducing new microbial strain(s) on the soil microbiome of a habitat is not well-explored.

The Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy and the Epithelial-Mesenchymal Transition.

It would be highly desirable to find prognostic and predictive markers for triple-negative breast cancer (TNBC), a strongly heterogeneous and invasive breast cancer subtype often characterized by a high recurrence rate and a poor outcome. Here, we investigated the prognostic and predictive capabilities of ARIADNE, a recently developed transcriptomic test focusing on the epithelial-mesenchymal transition. We first compared the stratification of TNBC patients obtained by ARIADNE with that based on other common pathological indicators, such as grade, stage and nodal status, and found that ARIADNE was more effective than the other methods in dividing patients into groups with different disease-free survival statistics.

Quantitative analysis of disease-related metabolic dysregulation of human microbiota.

The metabolic activity of all the micro-organism composing the human microbiome interacts with the host metabolism contributing to human health and disease in a way that is not fully understood. Here, we introduce STELLA, a computational method to derive the spectrum of metabolites associated with the microbiome of an individual. STELLA integrates known information on metabolic pathways associated with each bacterial species and extracts from these the list of metabolic products of each singular reaction by means of automatic text analysis.

A pipeline for monitoring water pollution: The example of heavy metals in Lombardy waters.

Time-dependent geolocalized analysis of pollution data allows to better understand their dynamics over time and could suggest strategies to restore a good ecological status of contaminated area. This research analyzes concentrations of pollutants in surface waters and groundwater monitored by the Regional Environment Protection Agency of Lombardy from 2017 to 2020. Lombardy is one of the richest and populous region of Europe, providing an interesting example of the impact of environmental pollutants due to anthropogenic and industrial activities, not only for Italy but also for all Europe.

Artificial intelligence in breast cancer diagnostics.

Since breast cancer deaths are mainly due to metastasis, predicting the risk that a primary tumor will develop metastasis after a first diagnosis is a central issue that could be addressed by artificial intelligence. To overcome the problem posed by limited availability of standardized datasets, algorithms should include biological insight.

Nuclear Biophysical Changes during Human Melanoma Plasticity.

Tumor plasticity is an emerging property of tumor cells which allows them to change their phenotype in dependence on the environment. The epithelial-mesenchymal transition plays a crucial role in helping cells acquire a more aggressive phenotype when they are in the mesenchymal state. Herein, we investigated the biophysical changes occurring during phenotypic switching in human melanoma cells, considering the blebbiness of the nuclei, their stiffness, and the involvement of polycombs with lamins.

FLIM-FRET Investigation of Heterogeneous Huntingtin Aggregation in HeLa Cells.

Fluorescence lifetime imaging microscopy-fluorescence resonance energy transfer (FLIM-FRET) technique is a novel tool to study protein-protein interaction combining FRET detection, lifetime measurements, and high-resolution imaging. This chapter describes a FLIM-FRET protocol for the detection and quantification of heterogeneous huntingtin aggregates in HeLa cells co-transfected with huntingtin variants containing polyglutamine tracts of different lengths.

Classification of triple negative breast cancer by epithelial mesenchymal transition and the tumor immune microenvironment.

Triple-negative breast cancer (TNBC) accounts for about 15-20% of all breast cancers and differs from other invasive breast cancer types because it grows and spreads rapidly, it has limited treatment options and typically worse prognosis. Since TNBC does not express estrogen or progesterone receptors and little or no human epidermal growth factor receptor (HER2) proteins are present, hormone therapy and drugs targeting HER2 are not helpful, leaving chemotherapy only as the main systemic treatment option. In this context, it would be important to find molecular signatures able to stratify patients into high and low risk groups.

Evidence of a SARS-CoV-2 double Spike mutation D614G/S939F potentially affecting immune response of infected subjects.

Objectives: Despite extensive efforts to monitor the diffusion of COVID-19, the actual wave of infection is worldwide characterized by the presence of emerging SARS-CoV-2 variants. The present study aims to describe the presence of yet undiscovered SARS-CoV-2 variants in Italy.

Methods: Next Generation Sequencing was performed on 16 respiratory samples from occasionally employed within the Bangladeshi community present in Ostia and Fiumicino towns.

Immune Profile of SARS-CoV-2 Variants of Concern.

The spread of the current Sars-Cov-2 pandemics leads to the development of mutations that are constantly monitored because they could affect the efficacy of vaccines. Three recently identified mutated strains, known as variants of concern, are rapidly spreading worldwide. Here, we study possible effects of these mutations on the immune response to Sars-Cov-2 infection using NetTepi a computational method based on artificial neural networks that considers binding and stability of peptides obtained by proteasome degradation for widely represented HLA class I alleles present in human populations as well as the T-cell propensity of viral peptides that measures their immune response.

Information Optimized Multilayer Network Representation of High Density Electroencephalogram Recordings.

High-density electroencephalography (hd-EEG) provides an accessible indirect method to record spatio-temporal brain activity with potential for disease diagnosis and monitoring. Due to their highly multidimensional nature, extracting useful information from hd-EEG recordings is a complex task. Network representations have been shown to provide an intuitive picture of the spatial connectivity underlying an electroencephalogram recording, although some information is lost in the projection.

TRPM2 Oxidation Activates Two Distinct Potassium Channels in Melanoma Cells through Intracellular Calcium Increase.

Tumor microenvironments are often characterized by an increase in oxidative stress levels. We studied the response to oxidative stimulation in human primary (IGR39) or metastatic (IGR37) cell lines obtained from the same patient, performing patch-clamp recordings, intracellular calcium ([Ca]) imaging, and RT-qPCR gene expression analysis. In IGR39 cells, chloramine-T (Chl-T) activated large K currents (KROS) that were partially sensitive to tetraethylammonium (TEA).

Role of body temperature variations in bat immune response to viral infections.

The ability of bats to coexist with viruses without being harmed is an interesting issue that is still under investigation. Here we use a mathematical model to show that the pattern of body temperature variations observed in bats between day and night is responsible for their ability to keep viruses in check. From the dynamical systems point of view, our model displays an intriguing quasi-periodic behaviour that might be relevant in making the system robust by avoiding viral escape due to perturbations in the body temperature cycle.

Synergistic effects of contaminants in Lombardy waters.

Quantifying synergistic environmental effects in water contamination is still an open issue. Here, we have analyzed geolocalized data of pollutants recorded in 2018 in surface and groundwater of Lombardy, one of the areas with the highest agricultural production rates, not only in Italy, but also in Europe. Both herbicides and insecticides are present at concentration levels above the legal limit, mainly in surface waters.

Classification of triple-negative breast cancers through a Boolean network model of the epithelial-mesenchymal transition.

Predicting the metastasis risk in patients with a primary breast cancer tumor is of fundamental importance to decide the best therapeutic strategy in the framework of personalized medicine. Here, we present ARIADNE, a general algorithmic strategy to assess the risk of metastasis from transcriptomic data of patients with triple-negative breast cancer, a subtype of breast cancer with poorer prognosis with respect to the other subtypes. ARIADNE identifies hybrid epithelial/mesenchymal phenotypes by mapping gene expression data into the states of a Boolean network model of the epithelial-mesenchymal pathway.

Oral mucositis: the hidden side of cancer therapy.

Inflammation response of epithelial mucosa to chemo- radiotherapy cytotoxic effects leads to mucositis, a painful side effect of antineoplastic treatments. About 40% of the patients treated with chemotherapy develop mucositis; this percentage rises to about 90% for head and neck cancer patients (HNC) treated with both chemo- and radiotherapy. 19% of the latter will be hospitalized and will experience a delay in antineoplastic treatment for high-grade mucositis management, resulting in a reduction of the quality of life, a worse prognosis and an increase in patient management costs.

Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I exposes viral peptides in all nucleated cells and is involved in the susceptibility to many human diseases. Here, we use artificial neural networks to analyze the binding of SARS-CoV-2 peptides with polymorphic human MHC class I molecules.