Since their inception, DNA aptamers were regarded as the turning point for biochemical sensing in real samples; however up to now their promises are far from being fulfilled. Especially aptamers for small molecules pose a challenge for both selection and characterization. The lack of a universally accepted and robust quality control protocol for the characterization of aptamer performances coupled with the observation of inconsistent data sets in literature, prompted us to address the issue comparing different analytical methodologies to validate (or disprove) the binding capabilities of aptamer sequences. We chose three aptamers for ampicillin, a β-Lactam antibiotic; used several detection strategies described in literature. The colorimetric gold nanoparticles (AuNPs) assay used in the original paper describing the aptamer sequences was repeated with conflicting results. The three sequences were then tested with three different instrumental techniques to assess their Kd and binding mechanism in homogeneous solutions. Coupling the thermodynamic data obtained with Isothermal Titration Calorimetry (ITC) with the structural information on the binding event given by Native Electro Spray Ionization Mass spectrometry (Native ESI-MS) and 1H-NMR it was possible to verify that the three sequences do not show any specific binding with the target ampicillin. To verify the influence of the AuNPs on the binding event, the experiments were repeated in presence of AuNPs both with ITC and 1H-NMR, again without any results. By offering a cross-referenced and robust analitycal approach to aptamer characterization we aim at elucidating the potentialities of aptamer for small organic molecules, especially when ultrasensitive analytical application are involved

proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decisionmaking, from oncology and respiratory medicine to pharmacological and genotyping studies.

A nanostructured electrochemical biosensor for detecting proteins of interest in work of art, in particular in tempera paintings, is presented. To determine egg yolk we focus here on the determination of immunoglobulin IgY. The transducers are nanoelectrode ensembles (NEEs), prepared via membrane templated electroless deposition of gold. Because of their geometrical and diffusion characteristics, NEEs are characterized by significantly low detection limits, moreover they display the capability of capturing proteins by interaction with the polycarbonate membrane of the NEE. At first, the proteic component of the paint is extracted by ultrasonication in an aqueous buffer, then IgY is captured by incubation on the NEE. The immunoglobulin is detected by treatment with anti-IgY labeled with horse radish peroxidase (Anti-IgY-HRP). The binding of the Anti-IgY-HRP is detected by recording the electrocatalytic signal caused by addition of H2O2 and methylene blue. The sensor detection capabilities are tested by analyzing both paint models, prepared in the lab, and real samples, from paintings of the XVIII-XX century. Multivariate exploratory analysis is applied to classify the voltammetric patterns, confirming the capability to differentiate egg-yolk tempera from other kind of tempera binders as well as from acrylic or oil paints.

A joint action of ssDNA aptamers and electrochemistry is a key element in developing successful biosensing platforms, since aptamers are capable of binding various targets with high specificity, and electrochemistry is one of the most sensitive techniques for on-site detections. A continuous search for improved immobilization and sensing strategies of aptamers on transducer surfaces resulted in the strategy presented in this article. The strategy is based on the covalent attachment of gold nanoparticles on the surface of glassy carbon electrodes through sulfhydryl-terminated monolayer, acting as a glue to connect AuNPs on the electrode. The covalently attached gold nanoparticles modified glassy carbon electrodes have been applied for the efficient immobilization of thiolated ssDNA probes, with a surface coverage of about 8.54×10 13 molecules cm −2 which was 7-fold higher than that on the electrochemically deposited gold nanoparticles. Consequently, improved sensitivity, good reproducibility and stability are achieved for electrochemical aptasensor. Combined with the high affinity and specificity of an aptamer, a simple, novel, rapid, sensitive and label-free electrochemical aptasensor was successfully fabricated for ofloxacin (OFL) detection. The linear dynamic range of the sensor varies between 5×10 -8 to 2×10 -5 M OFL with a detection limit of 1×10 -9 M OFL. A potential application in environmental monitoring was demonstrated by using this sensing strategy for the determination of OFL in (experimentally spiked) real samples such as tap water and effluent of sewage treatment plant. The proposed nanoaptasensor combines the advantages of the covalent attachment of neatly arranged AuNPs (enlarged active surface area and strengthened electrochemical signal) and the elimination of labels for the amplified detection of OFL, with the covalent attachment of highly specific aptamers to the surface of the modified electrode.

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Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50 years. As modern medicine is evolving towards precision medicine, offering personalized patient care and treatment, the requirement for robust imaging biomarkers has gradually increased. Radiomics, a specific method generating high-throughput extraction of a tremendous amount of quantitative imaging data using data-characterization algorithms, has shown great potential in individuating imaging biomarkers. Radiomic analysis can be implemented through the following two methods: hand-crafted radiomic features extraction or deep learning algorithm. Its application in lung diseases can be used in clinical decision support systems, regarding its ability to develop descriptive and predictive models in many respiratory pathologies. The aim of this article is to review the recent literature on the topic, and briefly summarize the interest of radiomics in chest Computed Tomography (CT) and its pertinence in the field of pulmonary diseases, from a clinician’s perspective.

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