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Detecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decision-making processes in the treatment of this malignancy. Though several machine learning models analyzing both clinical and histopathological information have been developed in literature to address this task, these approaches turned out to be unsuitable for describing this problem. In this study, we designed a novel artificial intelligence-based approach which converts clinical information into an image-form to be analyzed through Convolutional Neural Networks. Specifically, we predicted the occurrence of an Invasive Disease Event at both 5-year and 10-year follow-ups of 696 female patients with a first invasive breast cancer diagnosis enrolled at IRCCS \"Giovanni Paolo II\" in Bari, Italy. After transforming each patient, represented by a vector of clinical information, to an image form, we extracted low-level quantitative imaging features by means of a pre-trained Convolutional Neural Network, namely, AlexNET. Then, we classified breast cancer patients in the two classes, namely, Invasive Disease Event and non-Invasive Disease Event, via a Support Vector Machine classifier trained on a subset of significative features previously identified. Both 5-year and 10-year models resulted particularly accurate in predicting breast cancer recurrence event, achieving an AUC value of 92.07% and 92.84%, an accuracy of 88.71% and 88.82%, a sensitivity of 86.83% and 88.06%, a specificity of 89.55% and 89.3%, a precision of 71.93% and 84.82%, respectively. This is the first study proposing an approach which converts clinical information into an image-form to develop a decision support system for identifying patients at high risk of occurrence of an Invasive Disease Event, and then defining personalized oncological therapeutic treatments for breast cancer patients.

Background About 15%–20% of breast cancer (BC) cases is classified as Human Epidermal growth factor Receptor type 2 (HER2) positive. The Neoadjuvant chemotherapy (NAC) was initially introduced for locally advanced and inflammatory BC patients to allow a less extensive surgical resection, whereas now it represents the current standard for early‐stage and operable BC. However, only 20%–40% of patients achieve pathologic complete response (pCR). According to the results of practice‐changing clinical trials, the addition of trastuzumab to NAC brings improvements to pCR, and recently, the use of pertuzumab plus trastuzumab has registered further statistically significant and clinically meaningful improvements in terms of pCR. The goal of our work is to propose a machine learning model to predict the pCR to NAC in HER2‐positive patients based on a subset of clinical features. Method First, we evaluated the significant association of clinical features with pCR on the retrospectively collected data referred to 67 patients afferent to Istituto Tumori “Giovanni Paolo II.” Then, we performed a feature selection procedure to identify a subset of features to be used for training a machine learning‐based classification algorithm. As a result, pCR to NAC was associated with ER status, Pgr status, and HER2 score. Results The machine learning model trained on a subgroup of essential features reached an AUC of 73.27% (72.44%–73.66%) and an accuracy of 71.67% (71.64%–73.13%). According to our results, the clinical features alone are not enough to define a support system useful for clinical pathway. Conclusion Our results seem worthy of further investigation in large validation studies and this work could be the basis of future study that will also involve radiomics analysis of biomedical images.

Organic materials have revolutionized optoelectronics by their processability, flexibility and low cost, with application to light-emitting devices for full-colour screens 1 , solar cells 2 and lasers 3 , 4 . Some low-dimensional organic semiconductor structures exhibit properties resembling those of inorganics, such as polarized emission 5 and enhanced electroluminescence 6 . One-dimensional metallic, III–V and II–VI nanostructures have also been the subject of intense investigation 7 , 8 as building blocks for nanoelectronics and photonics. Given that one-dimensional polymer nanostructures, such as polymer nanofibres, are compatible with sub-micrometre patterning capability 9 and electromagnetic confinement within subwavelength volumes 8 , they can offer the benefits of organic light sources to nanoscale optics. Here we report on the optical properties of fully conjugated, electrospun polymer nanofibres. We assess their waveguiding performance and emission tuneability in the whole visible range. We demonstrate the enhancement of the fibre forward emission through imprinting periodic nanostructures using room-temperature nanoimprint lithography, and investigate the angular dispersion of differently polarized emitted light. Conjugated polymer fibres offer many advantages over other photonic materials, such as tunable properties and easy processability, making them attractive for optoelectronic applications. The waveguiding performance and emission tunability of fully conjugated, electrospun polymer nanofibres have been assessed and their forward emission shown to improve after periodic structures are imprinted using nanoimprint lithography.

A straight synthetic route to fabricate hybrid nanocomposite films of well-dispersed CdS nanocrystals (NCs) in poly[2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) is reported. A soluble cadmium complex [Cd(SBz) 2 ] 2 ·MI, obtained by incorporating a Lewis base (1-methylimidazole, MI) on the cadmium bis(benzyl)thiol, is used as starting reagent in an in situ thermolytic process. CdS NCs with spherical shape nucleate and grow well below 200°C in a relatively short time (30 min). Photoluminescence spectroscopy measurements performed on CdS/MEH-PPV nanocomposites show that CdS photoluminescence peaks are totally quenched inside MEH-PPV, if compared to CdS/PMMA nanocomposites, as expected due to overlapping of the polymer absorption and CdS emission spectra. The CdS NCs are well-dispersed in size and homogeneously distributed within MEH-PPV matrix as proved by transmission electron microscopy. Nanocomposites with different precursor/polymer weight ratios were prepared in the range from 1:4 to 4:1. Highly dense materials, without NCs clustering, were obtained for a weight/weight ratio of 2:3 between precursor and polymer, making these nanocomposites particularly suitable for optoelectronic and solar energy conversion applications.

This chapter provides introductory background information and state‐of‐the‐art progress in the field of nanocomposite materials, films, and patterns realized by the exploitation of in situ methodologies based on thermal, photon, and electron‐beam‐assisted synthesis. It introduces the most widely used precursor molecules and processes accounting for precursor decomposition and nanoparticles (NPs) nucleation, mainly during thermal‐assisted experiments. Several pathways can be used to induce NPs nucleation inside a polymer matrix, such as chemical reduction, photoreduction, or thermal decomposition. One of the most extensively used energy source for the in situ synthesis of NPs is the heat. An overview on the most extensive techniques used for the nanocomposite microstructural characterization (X‐ray diffraction (XRD), and Transmission Electron Microscopy (TEM)) and optical spectroscopy is reported. The chapter defines the most promising in situ synthesis and patterning methods also in combined approaches, based on photon‐ and electron‐beam‐assisted procedures.

No commercial vaccine is yet available against Group A Streptococcus (GAS), major cause of pharyngitis and impetigo, with a high frequency of serious sequelae in low- and middle-income countries. Group A Carbohydrate (GAC), conjugated to an appropriate carrier protein, has been proposed as an attractive vaccine candidate. Here, we explored the possibility to use GAS Streptolysin O (SLO), SpyCEP and SpyAD protein antigens with dual role of antigen and carrier, to enhance the efficacy of the final vaccine and reduce its complexity. All protein antigens resulted good carrier for GAC, inducing similar anti-GAC IgG response to the more traditional CRM197 conjugate in mice. However, conjugation to the polysaccharide had a negative impact on the anti-protein responses, especially in terms of functionality as evaluated by an IL-8 cleavage assay for SpyCEP and a hemolysis assay for SLO. After selecting CRM197 as carrier, optimal conditions for its conjugation to GAC were identified through a Design of Experiment approach, improving process robustness and yield This work supports the development of a vaccine against GAS and shows how novel statistical tools and recent advancements in the field of conjugation can lead to improved design of glycoconjugate vaccines.

Cancer stem cells (CSCs) are a subpopulation of cancer cells endowed with high tumorigenic, chemoresistant and metastatic potential. Nongenetic mechanisms of acquired resistance are increasingly being discovered, but molecular insights into the evolutionary process of CSCs are limited. Here, we show that type I interferons (IFNs-I) function as molecular hubs of resistance during immunogenic chemotherapy, triggering the epigenetic regulator demethylase 1B (KDM1B) to promote an adaptive, yet reversible, transcriptional rewiring of cancer cells towards stemness and immune escape. Accordingly, KDM1B inhibition prevents the appearance of IFN-I-induced CSCs, both in vitro and in vivo. Notably, IFN-I-induced CSCs are heterogeneous in terms of multidrug resistance, plasticity, invasiveness and immunogenicity. Moreover, in breast cancer (BC) patients receiving anthracycline-based chemotherapy, KDM1B positively correlated with CSC signatures. Our study identifies an IFN-I → KDM1B axis as a potent engine of cancer cell reprogramming, supporting KDM1B targeting as an attractive adjunctive to immunogenic drugs to prevent CSC expansion and increase the long-term benefit of therapy.Type I interferons have been described to have protumor or antitumor functions depending on context. Here the authors show a protumor function for type I interferons in that they promote cancer stem cells by upregulating the chromatin remodeling factor KDM1B.

Outer Membrane Vesicles (OMV) constitute a promising platform for the development of efficient vaccines. OMV can be decorated with heterologous antigens (proteins or polysaccharides), becoming attractive novel carriers for the development of multicomponent vaccines. Chemical conjugation represents a tool for linking antigens, also from phylogenetically distant pathogens, to OMV. Here we develop two simple and widely applicable conjugation chemistries targeting proteins or lipopolysaccharides on the surface of Generalized Modules for Membrane Antigens (GMMA), OMV spontaneously released from Gram-negative bacteria mutated to increase vesicle yield and reduce potential reactogenicity. A Design of Experiment approach was used to identify optimal conditions for GMMA activation before conjugation, resulting in consistent processes and ensuring conjugation efficiency. Conjugates produced by both chemistries induced strong humoral response against the heterologous antigen and GMMA. Additionally, the use of the two orthogonal chemistries allowed to control the linkage of two different antigens on the same GMMA particle. This work supports the further advancement of this novel platform with great potential for the design of effective vaccines.

Technology platforms are an important strategy to facilitate the design, development and implementation of vaccines to combat high-burden diseases that are still a threat for human populations, especially in low- and middle-income countries, and to address the increasing number and global distribution of pathogens resistant to antimicrobial drugs. Generalized Modules for Membrane Antigens (GMMA), outer membrane vesicles derived from engineered Gram-negative bacteria, represent an attractive technology to design affordable vaccines. Here, we show that GMMA, decorated with heterologous polysaccharide or protein antigens, leads to a strong and effective antigen-specific humoral immune response in mice. Importantly, GMMA promote enhanced immunogenicity compared to traditional formulations (e.g., recombinant proteins and glycoconjugate vaccines), without negative impact to the anti-GMMA immune response. Our findings support the use of GMMA as a “plug and play” technology for the development of effective combination vaccines targeting different bugs at the same time.

Autophagy is a highly regulated degradative process crucial for maintaining cell homeostasis. This important catabolic mechanism can be nonspecific, but usually occurs with fine spatial selectivity (compartmentalization), engaging only specific subcellular sites. While the molecular machines driving autophagy are well understood, the involvement of localized signaling events in this process is not well defined. Among the pathways that regulate autophagy, the cyclic AMP (cAMP)/protein kinase A (PKA) cascade can be compartmentalized in distinct functional units called microdomains. However, while it is well established that, depending on the cell type, cAMP can inhibit or promote autophagy, the role of cAMP/PKA microdomains has not been tested. Here we show not only that the effects on autophagy of the same cAMP elevation differ in different cell types, but that they depend on a highly complex sub-compartmentalization of the signaling cascade. We show in addition that, in HT-29 cells, in which autophagy is modulated by cAMP rising treatments, PKA activity is strictly regulated in space and time by phosphatases, which largely prevent the phosphorylation of soluble substrates, while membrane-bound targets are less sensitive to the action of these enzymes. Interestingly, we also found that the subcellular distribution of PKA type-II regulatory PKA subunits hinders the effect of PKA on autophagy, while displacement of type-I regulatory PKA subunits has no effect. Our data demonstrate that local PKA activity can occur independently of local cAMP concentrations and provide strong evidence for a link between localized PKA signaling events and autophagy.