Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis.

One of the major problems in bioimaging, often highly underestimated, is whether features extracted for a discrimination or regression task will remain valid for a broader set of similar experiments or in the presence of unpredictable perturbations during the image acquisition process. Such an issue is even more important when it is addressed in the context of deep learning features due to the lack of a priori known relationship between the black-box descriptors (deep features) and the phenotypic properties of the biological entities under study. In this regard, the widespread use of descriptors, such as those coming from pre-trained Convolutional Neural Networks (CNNs), is hindered by the fact that they are devoid of apparent physical meaning and strongly subjected to unspecific biases, i.e., features that do not depend on the cell phenotypes, but rather on acquisition artifacts, such as brightness or texture changes, focus shifts, autofluorescence or photobleaching. The proposed Deep-Manager software platform offers the possibility to efficiently select those features having lower sensitivity to unspecific disturbances and, at the same time, a high discriminating power. Deep-Manager can be used in the context of both handcrafted and deep features. The unprecedented performances of the method are proven using five different case studies, ranging from selecting handcrafted green fluorescence protein intensity features in chemotherapy-related breast cancer cell death investigation to addressing problems related to the context of Deep Transfer Learning. Deep-Manager, freely available at https://github.com/BEEuniroma2/Deep-Manager , is suitable for use in many fields of bioimaging and is conceived to be constantly upgraded with novel image acquisition perturbations and modalities.

Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.

High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data and to the availability of dynamic models that link phenomena across levels: from genes to cells, from cells to organs, and through the whole organism. The combination of phenomics, deep learning, and machine learning represents a strong potential for the phenotypical investigation, leading the way to a more embracing approach, called machine learning phenomics (MLP). In particular, in this work we present a novel MLP platform for phenomics investigation of cancer-cells response to therapy, exploiting and combining the potential of time-lapse microscopy for cell behavior data acquisition and robust deep learning software architectures for the latent phenotypes extraction. A two-step proof of concepts is designed. First, we demonstrate a strict correlation among gene expression and cell phenotype with the aim to identify new biomarkers and targets for tailored therapy in human colorectal cancer onset and progression. Experiments were conducted on human colorectal adenocarcinoma cells (DLD-1) and their profile was compared with an isogenic line in which the expression of LOX-1 transcript was knocked down. In addition, we also evaluate the phenotypic impact of the administration of different doses of an antineoplastic drug over DLD-1 cells. Under the omics paradigm, proteomics results are used to confirm the findings of the experiments.

Carbon nanotube films as a platform to transduce molecular recognition events in metalloporphyrins.

Porphyrins have been widely used for many years as functional materials for chemical sensors. Their outstanding chemical features are balanced by some restrictions in terms of transduction techniques. In particular, porphyrin layers are barely conductive, with the consequence that the fabrication of porphyrin based chemiresistors is not possible, except in few rare cases. On the other hand, carbon nanotubes (CNTs) have superior electric properties ranging from metallic to semiconductor in character. Although the conductivity of CNTs is very sensitive to adsorbed molecules, it should be considered that the adsorption onto carbon structures is also scarcely selective and cannot be modified unless other molecular recognition systems are coupled with the CNTs. Following this approach, in this paper we investigated the sensing properties of hybrid CNT-porphyrin films to explore the possibility of transducing the adsorption events occurring in a porphyrin layer into resistance changes of the CNT layers. The results obtained indicate that the presence of the porphyrin films increases the sensitivity of the electric resistance of the CNTs to the concentration of volatile compounds. This enhancement is probably due to the catalytic effect of the metalloporphyrin in conveying the charge transfer from the adsorbate molecule to the CNTs substrate. This property of metalloporphyrins may introduce a further differentiation between porphyrin based sensors that could be positively utilized in sensor array configurations.

LOX-1 and cancer: an indissoluble liaison.

Recently, a strong correlation between metabolic disorders, tumor onset, and progression has been demonstrated, directing new therapeutic strategies on metabolic targets. OLR1 gene encodes the LOX-1 receptor protein, responsible for the recognition, binding, and internalization of ox-LDL. In the past, several studied, aimed to clarify the role of LOX-1 receptor in atherosclerosis, shed light on its role in the stimulation of the expression of adhesion molecules, pro-inflammatory signaling pathways, and pro-angiogenic proteins, including NF-kB and VEGF, in vascular endothelial cells and macrophages. In recent years, LOX-1 upregulation in different tumors evidenced its involvement in cancer onset, progression and metastasis. In this review, we outline the role of LOX-1 in tumor spreading and metastasis, evidencing its function in VEGF induction, HIF-1alpha activation, and MMP-9/MMP-2 expression, pushing up the neoangiogenic and the epithelial-mesenchymal transition process in glioblastoma, osteosarcoma prostate, colon, breast, lung, and pancreatic tumors. Moreover, our studies contributed to evidence its role in interacting with WNT/APC/ß-catenin axis, highlighting new pathways in sporadic colon cancer onset. The application of volatilome analysis in high expressing LOX-1 tumor-bearing mice correlates with the tumor evolution, suggesting a closed link between LOX-1 upregulation and metabolic changes in individual volatile compounds and thus providing a viable method for a simple, non-invasive alternative monitoring of tumor progression. These findings underline the role of LOX-1 as regulator of tumor progression, migration, invasion, metastasis formation, and tumor-related neo-angiogenesis, proposing this receptor as a promising therapeutic target and thus enhancing current antineoplastic strategies.

Accelerating the experimental responses on cell behaviors: a long-term prediction of cell trajectories using Social Generative Adversarial Network.

The incremented uptake provided by time-lapse microscopy in Organ-on-a-Chip (OoC) devices allowed increased attention to the dynamics of the co-cultured systems. However, the amount of information stored in long-time experiments may constitute a serious bottleneck of the experimental pipeline. Forward long-term prediction of cell trajectories may reduce the spatial-temporal burden of video sequences storage. Cell trajectory prediction becomes crucial especially to increase the trustworthiness in software tools designed to conduct a massive analysis of cell behavior under chemical stimuli. To address this task, we transpose here the exploitation of the presence of "social forces" from the human to the cellular level for motion prediction at microscale by adapting the potential of Social Generative Adversarial Network predictors to cell motility. To demonstrate the effectiveness of the approach, we consider here two case studies: one related to PC-3 prostate cancer cells cultured in 2D Petri dishes under control and treated conditions and one related to an OoC experiment of tumor-immune interaction in fibrosarcoma cells. The goodness of the proposed strategy has been verified by successfully comparing the distributions of common descriptors (kinematic descriptors and mean interaction time for the two scenarios respectively) from the trajectories obtained by video analysis and the predicted counterparts.

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

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 inspired by the recent successes in application of machine learning for style recognition in paintings and artistic style transfer. The originality of the method relies i) on the generation of atlas from the collection of single-cell trajectories in order to visually encode the multiple descriptors of cell motility, and ii) on the application of pre-trained Deep Learning Convolutional Neural Network architecture in order to extract relevant features to be used for classification tasks from this visual atlas. Validation tests were conducted on two different cell motility scenarios: 1) a 3D biomimetic gels of immune cells, co-cultured with breast cancer cells in organ-on-chip devices, upon treatment with an immunotherapy drug; 2) Petri dishes of clustered prostate cancer cells, upon treatment with a chemotherapy drug. For each scenario, single-cell trajectories are very accurately classified according to the presence or not of the drugs. This original approach demonstrates the existence of universal features in cell motility (a so called "motility style") which are identified by the DL approach in the rationale of discovering the unknown message in cell trajectories.

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

Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors' discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the computational models were experimentally confirmed by a series of video-microscopy acquisitions of co-cultures of unlabelled human cancer and immune cells embedded in 3D collagen gels within microfluidic devices. We argue that the experimental protocol of acquisition should be adapted to the specific kind of analysis involved and to the chosen descriptors in order to derive reliable conclusions and avoid biasing the interpretation of results.

Identification of melanoma with a gas sensor array.

BACKGROUND/PURPOSE: The relationship between diseases and alterations of the airborne chemicals emitted from the body has been found in many different pathologies and in particular for various forms of cancer. Metabolism of cancer cells is greatly altered during their lifetime; then, modification of chemicals is supposed to be large around cancer tissues. Positive hints in this direction were provided, as an example, on studying the breath composition of lung cancer-affected subjects. Besides the conventional analytical approaches, in recent years sensor arrays were also applied to these researches considering the chemical composition changes as those occurring in other applications such as for instance, those dealing with food quality measurements. METHODS: In this paper, the first application of sensor arrays to study the differentiation between melanomas and nevi, namely malignant and benign affection of melanocytary cells, respectively, is presented and discussed. The localization of lesions on the skin surface made possible the utilization of differential measurements aimed at capturing the differences between two adjacent skin regions. This approach strongly reduces the influence of skin headspace variability due to the peculiar subjective odour background and the skin odour variability. The measurement campaign involved 40 cases; 10 of these were diagnosed melanomas referred to surgical intervention. Nine of these diagnoses were further confirmed by histological examinations of the removed tissue and one was a false positive. RESULTS: The differences in the chemical composition of headspace were verified with a gas-chromatographic investigation, and the classification of electronic nose data provided an estimated cross-validated accuracy of the same order of magnitude as the currently used diagnostic instruments. CONCLUSION: Electronic nose sensors have been shown to have good sensitivity towards volatile organic compounds emitted by skin lesions, and the method seems to be effective for malign lesions identification. The results presented in this paper encourage a second experimental campaign with a larger number of participants and a systematic use of gas chromatography mass spectrometer technology in order to identify some possible melanoma biomarkers.

Structural investigation of nucleophosmin interaction with the tumor suppressor Fbw7γ.

Nucleophosmin (NPM1) is a multifunctional nucleolar protein implicated in ribogenesis, centrosome duplication, cell cycle control, regulation of DNA repair and apoptotic response to stress stimuli. The majority of these functions are played through the interactions with a variety of protein partners. NPM1 is frequently overexpressed in solid tumors of different histological origin. Furthermore NPM1 is the most frequently mutated protein in acute myeloid leukemia (AML) patients. Mutations map to the C-terminal domain and lead to the aberrant and stable localization of the protein in the cytoplasm of leukemic blasts. Among NPM1 protein partners, a pivotal role is played by the tumor suppressor Fbw7γ, an E3-ubiquitin ligase that degrades oncoproteins like c-MYC, cyclin E, Notch and c-jun. In AML with NPM1 mutations, Fbw7γ is degraded following its abnormal cytosolic delocalization by mutated NPM1. This mechanism also applies to other tumor suppressors and it has been suggested that it may play a key role in leukemogenesis. Here we analyse the interaction between NPM1 and Fbw7γ, by identifying the protein surfaces implicated in recognition and key aminoacids involved. Based on the results of computational methods, we propose a structural model for the interaction, which is substantiated by experimental findings on several site-directed mutants. We also extend the analysis to two other NPM1 partners (HIV Tat and CENP-W) and conclude that NPM1 uses the same molecular surface as a platform for recognizing different protein partners. We suggest that this region of NPM1 may be targeted for cancer treatment.

Systematic approach in Mg2+ ions analysis with a combination of tailored fluorophore design.

A systematic study of a series of diaza-18-crown-6 8-hydroxyquinoline (DCHQ) chemosensors, devoted to Mg(II) ion detection, was performed. Functionalization of DCHQ by peripheral substituents allowed the development of novel all-solid-state optodes via inclusion inside PVC-based polymeric films. The influence on the DCHQ-based optode response of the lipophilic sites functionalization and of the nature of the plasticizer, was investigated. Fluorimetric studies on optodes sensitivity towards a number of different metal cations (Ca2+, Na+, K+, Li+, Co2+, Cd2+, Pb2+, Cu2+, Hg2+, Zn2+) and NH4+ were carried out. The results demonstrated the suitability of the DCHQ optodes to perform fast monitoring (<10s) of magnesium (II) ions. Emission light signal was sufficiently brilliant to be captured by a low-cost computer webcam. The phenyl-substituted DCHQ-Ph derivative showed the best performance with a wide range for Mg(II) ion determination between 2.7 × 10-7 and 2.2 × 10-2 mol/L. It was possible, therefore, to determine the concentrations of Mg(II) in commercial fertilizer samples by DCHQ-Ph-based optodes with acceptable results: recoveries of 96.2-104.9% and relative standard deviation (RSD, n = 6) less than 5%. Moreover, in comparison to single sensors, the use of an array composed of five optodes (the ones showing the best performances in the preliminary tests) has allowed to reduce the RSD of magnesium determination in real samples (down to 3.7% with respect to 5.5% for single optodes) and to achieve a detection limit (estimated by s/n = 3 method) as low as 4.6 × 10-7 mol/L.

Electronic tongue for microcystin screening in waters.

The potentiometric E-tongue system was employed for water toxicity estimation in terms of cyanobacterial microcystin toxins (MCs) detection. The data obtained from E-tongue were correlated to the MCs content detected by the standard chromatographic technique UHPLC-DAD (Ultra High Performance Liquid Chromatography with Diode Array Detector), as far as by the colorimetric enzymatic approach. The prediction of MCs released by toxic Microcystis aeruginosa strains was possible with Root Mean Squared Error of Validation (RMSEV) lower or very close to 1µg/L, the provisional guideline value of WHO for MCs content in potable waters. The application of E-tongue system opens up a new perspective offset for fast and inexpensive analysis in the field of environmental monitoring, offering also the possibility to distinguish toxin producing and non-toxic M. aeruginosa strains present in potable water.

Vortexes tune the chirality of graphene oxide and its non-covalent hosts.

Graphene oxide (GO) is one of the most appealing bidimensional materials able to interact non-covalently with achiral molecules and to act as chiral inducers. Vortexes can tune chirality and, consequently transfer a specific handedness to non-covalent host molecules, either when dispersed in water or when deposited on a solid surface.

Self-organising sensory maps in odour classification mimicking.

A system for artificial olfaction is introduced, which is composed of a sensor array for gas sensing and a self-organising artificial neural network. A detailed reformulation of the most effective Self-Organising sensory Map (SOM)-based algorithms for odour classification and other applications is provided. An opto-electronic micromachined implementation of the neural network is introduced, which employs a novel hybrid mechanism for activating neural groups, avoiding fabricated cloning templates hardware.

Technologies and tools for mimicking olfaction: status of the Rome "Tor Vergata" electronic nose.

This paper shows recent results obtained in the field of artificial olfaction by an electronic nose based on quartz microbalances. The chemical interactive material responsible of the sensitivity is, in this case, porphyrin, whose performance and optical characterization will be presented and discussed. The design of the electronic nose and the kind of neural network that has been considered for these applications will be illustrated and commented. Future research and perspectives toward electronic nose miniaturization are also discussed as fundamental milestones for reaching closer biomimicking action.

Piezoelectric sensors for dioxins: a biomimetic approach.

The aim of this work was to design a fast, cheap and easy to use analytical system for dioxins. Piezoelectric sensors coupled with the pentapeptides as biomimetic traps (the receptors), selective for the dioxins, were used for the realisation of this analytical system. A methodology to select specific receptors among all possible pentapeptides randomly generated was represented by the use of molecular modelling software. Three peptides called later on A, B and C (A:[N]Asn-Phe-Gln-Gly-Ile[C]; B:[N]Asn-Phe-Gln-Gly-Gln[C]; C:[N]Asn-Phe-Gln-Gly-Phe[C]), were selected and evaluated for their potential usage as artificial receptors in solid-gas analysis by using a quartz crystal microbalance (QCM) sensors array. The peptide sequences were functionalised by two terminal cysteine residues in order to achieve a covalent interaction with the QCM gold surface. A manganese-porphyrin complex and two other pentapeptides, a pentaglutamine (pentapeptide D) and a pentalysine (pentapeptide E), were used as negative control sensors. The QCM sensors (A, B and C) gave a good linearity against different sample concentrations of the 2,3,7,8-tetrachlorinated dibenzo-p-dioxin (TCDD) and a mixture of dioxins. In particular, the selectivity against 2,3,7,8-TCDD was nicely correlated to the estimated binding energy of the receptors calculated by computational modelling. The cross-reactivity of the system was quantified using commercial polychlorinated biphenyls (PCBs) mixtures (dioxin-like compounds).

Biomedical application of an electronic nose.

The analysis of volatiles secreted outside the human body to get information on the health status of the individuals has been proposed several times in the past. This kind of analysis is complex both from the point of view of sample collection and data interpretation when, for instance, gas chromatography is utilized. In the recent years the advent of chemical sensors and chemical sensors systems (the so-called electronic noses) opened the way to the possibility of fast and simple analysis of odors in many fields, and, recently, among them, in medicine. In this paper some examples of these applications are illustrated. The results, although preliminary, encourage in pursuing these researches that can give rise to a better comprehension of the role of smell and odor in humans and, possibly in the near future, in novel diagnostic tools.

Biological qualification of blood units: considerations about the effects of sample's handling and storage on stability of nucleic acids.

BACKGROUND: In transfusional setting introduction of nucleic amplification technique (NAT) for HBV-DNA, HCV-RNA and HIV-RNA in biological qualification of blood units suggest some problems. At first the opportunity to operate on mini-pool, at second the need to store the samples at +4 degrees C. The authors therefore have tried to estimate the impact of these conditions on the operativity of NAT testing in the transfusional setting. METHODS: The following parameters has been estimated: distribution of viral-load in untreated subjects, stability of nucleic acids during storage at +4 degrees C, stability of nucleic acids after repeated cycles of freezing and defrosting, robustness of the test to the cross-contamination, definition of the detection-limit (95%). Quantitative tests has been performed by using the following kits: Cobas Amplicor HBV Monitor, Cobas Amplicor HCV Monitor, Cobas Amplicor HIV Monitor; the qualitative tests has been performed by using the following kits: Ampliscreen HBV, Ampliscreen HCV 2,0, Ampliscreen HIV 1,5 all supplied by Roche Molecular System (Brancburg, NJ). RESULTS: Viral load in untreated subjects showed wide variation for HBV, HCV and HIV. HBV has been demonstrated much stable to the conservation +4 degrees C also until 168 h while for HCV and HIV a greater decrease of the viral-load was observed. For all and three virus the conservation to +4 degrees C until 72 h does not seem to involve meaningful fall in the viral-load. A remarkable reduction of the viral-load has been observed after five cycles of freezing and defrosting. All the tests showed a good robustness to cross-contamination. The detection-limit (95%) was 8 U/ml for HBV, 21 U/ml for HCV and 27 copy/ml for HIV. CONCLUSIONS: Samples for NAT testing, can be stored until 72 h to +4 degrees C without appreciable lowering of the viral-load. Repeated cycles of changes of state should be avoided. The tests showed a good robustness to cross-contamination. NAT tests for biological qualification of blood units had a minimal sensibility around 50 (copy/unit/ml). In our experience the detection-limit (95%) was 21 U/ml for HCV, 27 copies/ml for HIV, 8 U/ml for HBV. The availability of NAT test for HBV-DNA, HCV-RNA e HIV-RNA, sensitive and reliable, together with epidemiological data, suggest the opportunity to place side by side, in the biological qualification of the blood units, to add the tests for HBV-DNA and HIV-RNA to the test for HCV-RNA mandatory by low, in Italy in the biological qualification of blood units.

Electronic nose analysis of urine samples containing blood.

In this paper the possible application of an electronic nose to the analysis of urine is presented. In contrast with the conventional applications of sensors and biosensors operating in liquid, the approach discussed here makes use of gas sensors performing an analysis of the headspace. The application deals with urine samples from patients affected by kidney diseases; some of the samples contained traces of blood. Results show the possibility of distinguishing the samples containing blood from the others, and a linear correlation between the first three principal components and the blood content was found. Furthermore, the electronic nose matched with a suitable neural network showed good performance in measuring the pH and the specific weight of the samples.

Conceptual problems of colon pathologies of surgical interest in the elderly.

Case reports of 151 patients above the age of 70 years, treated with colon diseases of surgical interest, have been compared to those of 220 patients treated with similar diagnoses, but in younger ages. The case reports were evaluated on the basis of the available literary data, and interpreted from the points of view of the geriatric pathology. It is concluded that a correct interpretation of surgical pathologies of the colon in the elderly cannot disregard the knowledge of the age-dependent involutive processes concerning particularly this part of the digestive tract, and also other organs and systems in global sense. Aging of the mucosa of colon, after all, represents a more or less expressed reduction of its barrier function against oncogenic factors and pathogenic microorganisms. The degenerative lesions involving continuously the micro- and macrocirculation of the splanchnic regions result in a more frequent occurrence of complications (ischemia, perforations). The instability of the bioimmunological equilibrium and the presence of accompanying diseases complicate further the clinical picture which displays usually a few symptoms even during the evolutive phases of the diseases. Once the diagnosis has been achieved, the therapeutic strategies should be modified individually without giving up the main principles, however, always considering the possible expectations as regards the quality of life of each patients for the remaining life.

Use of IgG Avidity test in case definitions of toxoplasmosis in pregnancy.

A survey network for congenital toxoplasmosis (TOXO-NET) was set up in December 1996 in Piedmont (Italy). Participants were asked to classify the infections in pregnant mothers and newborns by the criteria of the European Network on Congenital Toxoplasmosis published by Lebech in 1996. Because the IgG Avidity test is largely employed as a 2nd level test in toxoplasmosis diagnosis and it could be helpful to date infection, the co-ordinators of TOXO-NET suggested including it in the "case definition" of "probable" infection and "unlikely" infection. 117 cases of toxoplasmosis in pregnancy divided into the risk categories under Lebech's criteria were re-examined using the "new" case definitions. 77 out of 117 (65.8%) Toxoplasma gondii infections during pregnancy could be defined with only one serum sample using the IgG Avidity test. The IgG Avidity test proved a useful method to classify the Toxoplasma gondii infections in pregnancy, especially when we had only one serum sample.