Silver-doped Calcium Phosphate bone cements with antibacterial properties

Calcium phosphate bone cements (CPCs) with antibacterial properties are demanded for clinical applications. In this study, we demonstrated the use of a relatively simple processing route based on preparation of silver-doped CPCs (CPCs-Ag) through the preparation of solid dispersed active powder phase. Real-time monitoring of structural transformations and kinetics of several CPCs-Ag formulations (Ag = 0 wt %, 0.6 wt % and 1.0 wt %) was performed by the Energy Dispersive X-ray Diffraction technique. The partial conversion of β-tricalcium phosphate (TCP) phase into the dicalcium phosphate dihydrate (DCPD) took place in all the investigated cement systems. In the pristine cement powders, Ag in its metallic form was found, whereas for CPC-Ag 0.6 wt % and CPC-Ag 1.0 wt % cements, CaAg(PO₃)₃ was detected and Ag (met.) was no longer present. The CPC-Ag 0 wt % cement exhibited a compressive strength of 6.5 ± 1.0 MPa, whereas for the doped cements (CPC-Ag 0.6 wt % and CPC-Ag 1.0 wt %) the reduced values of the compressive strength 4.0 ± 1.0 and 1.5 ± 1.0 MPa, respectively, were detected. Silver-ion release from CPC-Ag 0.6 wt % and CPC-Ag 1.0 wt % cements, measured by the Atomic Emission Spectroscopy, corresponds to the average values of 25 µg/L and 43 µg/L, respectively, rising a plateau after 15 days. The results of the antibacterial test proved the inhibitory effect towards pathogenic Escherichia coli for both CPC-Ag 0.6 wt % and CPC-Ag 1.0 wt % cements, better performances being observed for the cement with a higher Ag-content

Tiles: an online algorithm for community discovery in dynamic social networks

Community discovery has emerged during the last decade as one of the most challenging problems in social network analysis. Many algorithms have been proposed to find communities on static networks, i.e. networks which do not change in time. However, social networks are dynamic realities (e.g. call graphs, online social networks): in such scenarios static community discovery fails to identify a partition of the graph that is semantically consistent with the temporal information expressed by the data. In this work we propose Tiles, an algorithm that extracts overlapping communities and tracks their evolution in time following an online iterative procedure. Our algorithm operates following a domino effect strategy, dynamically recomputing nodes community memberships whenever a new interaction takes place. We compare Tiles with state-of-the-art community detection algorithms on both synthetic and real world networks having annotated community structure: our experiments show that the proposed approach is able to guarantee lower execution times and better correspondence with the ground truth communities than its competitors. Moreover, we illustrate the specifics of the proposed approach by discussing the properties of identified communities it is able to identify

Machine Learning Aided Molecular Modelling of Taste to Identify Food Fingerprints

Nature has developed fascinating mechanisms for selecting and monitoring nutrients through refined systems for food intake and uptake. One of the most important is the sense of taste. Taste is an emergent property involving a complex network of multilevel biological interactions beginning with the activation of specific protein receptors as a consequence of interaction with food molecules. In this context, crucial information about the mechanisms underlying the functioning of taste can be obtained by using molecular mechanistic modelling and machine learning tools borrowed from the field of drug design and the study of structural biology and protein biophysics. The ultimate goal is to develop predictive models capable of studying the intricate connection of molecular, sub-cellular and cellular phenomena underlying the complex biological mechanisms that regulate the relationships between food constituents and perceived taste. Artificial intelligence-driven digital tools for taste prediction and the study of molecular features of the interaction between food molecules and taste receptors have been recently developed by our group. Such tools are the operating engines of the decision support tool developed during the VIRTUOUS project (https://virtuoush2020.com). In this work, these tools were used to generate molecular fingerprints of coffee starting from its chemical composition. Through methods that integrate molecular modelling techniques and machine learning, molecules extracted from coffee were characterized in terms of binding affinity, specificity, and selectivity toward bitter receptors. The targeting ability of coffee-extracted molecules for human TAS2Rs was studied with an atomistic resolution to obtain a virtual fingerprint that links the molecular structure of food ingredients with their bitter profile. The study fits within the digital transition vision that leverages modelling and computational approaches to develop decision-supporting tools for developing solutions in the areas of nutrition, health and the modern food industry

Proof-of-concept Raman spectroscopy study aimed to differentiate thyroid follicular patterned lesions.

Inter-observer variability and cancer over-diagnosis are emerging clinical problems, especially for follicular patterned thyroid lesions. This challenge strongly calls for a new clinical tool to reliably identify neoplastic lesions and to improve the efficiency of differentiation between benign and malignant neoplasms, especially considering the increased diagnosis of small carcinomas and the growing number of thyroid nodules. In this study, we employed a Raman spectroscopy (RS) microscope to investigate frozen thyroid tissues from fourteen patients with thyroid nodules. To generate tissue classification models, a supervised statistical analysis of the Raman spectra was performed. The results obtained demonstrate an accuracy of 78% for RS based diagnosis to discriminate between normal parenchyma and follicular patterned thyroid nodules, and 89% accuracy - for very challenging follicular lesions (carcinoma versus adenoma). RS translation into intraoperative diagnosis of frozen sections and in preoperative analysis of biopsies can be very helpful to reduce unnecessary surgery in patients with indeterminate cytological reports

Desorption of hot molecules from photon irradiated interstellar ices

We present experimental measurements of photodesorption from ices of astrophysical relevance. Layers of benzene and water ice were irradiated with a laser tuned to an electronic transition in the benzene molecule. The translational energy of desorbed molecules was measured by time-of-flight (ToF) mass spectrometry. Three distinct photodesorption processes were identified - a direct adsorbate-mediated desorption producing benzene molecules with a translational temperature of around 1200 K, an indirect adsorbate-mediated desorption resulting in water molecules with a translational temperature of around 450 K, and a substrate-mediated desorption of both benzene and water producing molecules with translational temperatures of around 530 K and 450 K respectively. The translational temperature of each population of desorbed molecules is well above the temperature of the ice matrix. The implications for gas-phase chemistry in the interstellar medium are discussed.Comment: 23 pages, including 4 figures; submitted to Ap

Strontium Substituted Tricalcium Phosphate Bone Cement: Short and Long‐Term Time‐Resolved Studies and In Vitro Properties

Due to a significant influence of strontium (Sr) on bone regeneration, Sr substituted beta-tricalcium phosphate (Sr-TCP) cement is prepared and investigated by short- and long-term time-resolved techniques. For short-term investigations, energy-dispersive X-ray diffraction, infrared spectroscopy, and, for the first time, terahertz time-domain spectroscopy techniques are applied. For long-term time-resolved studies, angular dispersive X-ray diffraction, scanning electron microscopy, mechanical tests, and behavior in Ringer solution are carried out. After 45 min of the cement setting, the Sr-TCP phase is no longer detectable. During this time period, an appearance and constant increase of the final brushite phase are registered. The compressive strength of the Sr-TCP cement increases from 4.5 MPa after 2 h of setting and reaches maximum at 13.3 MPa after 21 d. After cement soaking for 21 d in Ringer solution, apatite final product, with an admixture of brushite and TCP phases is detected. The cytotoxicity aspects of the prepared cement are investigated using NCTC 3T3 fibroblast cell line, and the cytocompatibility-by human dental pulp mesenchymal stem cells. The obtained results allow to conclude that the developed Sr-TCP cement is promising for biomedical applications for bone tissue

Saints and lovers: myths of the avant-garde in Michel Georges-Michel's Les Montparnos

This article examines Michel Georges-Michel’s 1924 novel Les Montparnos as a study of the myths circulating around the Montparnasse avant-garde of the 1920s, and their function in relation to art. Key amongst these myths is the idea of art as a religion, according to which avant-garde artists are conceived as secular saints and martyrs. While this notion of artist as saint is strongly present in early-twentieth-century biographies of Van Gogh, Georges-Michel explicitly relates his fictionalized version of Modigliani’s life not to such recent models but rather to the Renaissance masters, and especially to Raphael, a link which is explained in terms of the post-war ‘retour à l’ordre’ in French artistic culture. The novel’s references to Raphael as archetypal painter-lover are also related to its construction of a myth of the artist as virile and sexually prolific, and to its identification of creative and sexual impulses