Humoral immune response to SARS-CoV-2 in five different groups of individuals at different environmental and professional risk of infection

It is partially unknown whether the immune response to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection persists with time. To address this issue, we detected the presence of SARS-CoV-2 antibodies in different groups of individuals previously diagnosed with COVID-19 disease (group 1 and 2), or potentially exposed to SARS-CoV-2 infection (group 3 and 4), and in a representative group of individuals with limited environmental exposure to the virus due to lockdown restrictions (group 5). The primary outcome was specific anti-SARS-CoV-2 antibodies in the different groups assessed by qualitative and quantitative analysis at baseline, 3 and 6 months follow-up. The seroconversion rate at baseline test was 95% in group 1, 61% in group 2, 40% in group 3, 17% in group 4 and 3% in group 5. Multivariate logistic regression analysis revealed male gender, close COVID-19 contact and presence of COVID-19 related symptoms strongly associated with serological positivity. The percentage of positive individuals as assessed by the qualitative and quantitative tests was superimposable. At the quantitative test, the median level of SARS-CoV-2 antibody levels measured in positive cases retested at 6-months increased significantly from baseline. The study indicates that assessing antibody response to SARS-CoV-2 through qualitative and quantitative testing is a reliable disease surveillance tool

Challenges and Recommendations for Magnetic Hyperthermia Characterization Measurements

The localized heating of magnetic nanoparticles (MNPs) via the application of time-varying magnetic fields – a process known as magnetic field hyperthermia (MFH) – can greatly enhance existing options for cancer treatment; but for broad clinical uptake its optimization, reproducibility and safety must be comprehensively proven. As part of this effort, the quantification of MNP heating – characterized by the specific loss power (SLP), measured in W/g, or by the intrinsic loss power (ILP), in nHm2/kg – is frequently reported. However, in SLP/ILP measurements to date, the apparatus, the analysis techniques and the field conditions used by different researchers have varied greatly, leading to questions as to the reproducibility of the measurements. To address this, we report here on an interlaboratory study (across N = 21 European sites) of calorimetry measurements that constitutes a snapshot of the current state-of-the-art within the MFH community. The data show that although there is very good intralaboratory repeatability, the overall interlaboratory measurement accuracy is poor, with the consolidated ILP data having standard deviations on the mean of ca. ± 30% to ± 40%. There is a strong systematic component to the uncertainties, and a clear rank correlation between the measuring laboratory and the ILP. Both of these are indications of a current lack of normalization in this field. A number of possible sources of systematic uncertainties are identified, and means determined to alleviate or minimize them. However, no single dominant factor was identified, and significant work remains to ascertain and remove the remaining uncertainty sources. We conclude that the study reveals a current lack of harmonization in MFH characterization of MNPs, and highlights the growing need for standardized, quantitative characterization techniques for this emerging medical technology.Multifunctional Nanoparticles for Magnetic Hyperthermia and Indirect Radiation Therap

Nanomaterials in Cancer Diagnosis and Therapy

Currently, the most commonly used treatments for cancer are surgery, radiotherapy, and chemotherapy [...

Multifunctional modalities of iron oxide magnetic nanoparticles: applications in diagnostics and magnetic fluid hyperthermia.

This PhD thesis, Multifunctional modalities of iron oxide magnetic nanoparticles: applications in diagnostics and magnetic fluid hyperthermia, has two major purposes. The first goal is to assess the anti-tumor efficacy and the potential of combining Hadron Therapy and Magnetic Fluid Hyperthermia (MFH) against pancreatic tumor cells; this is carried out with a perspective to establishing solid protocols for desirable future clinical applications. The second goal is to evaluate the Magnetic Resonance Imaging (MRI) image contrast efficiency of magnetic nanoparticles. This is accomplished by means of 1H Nuclear Magnetic Resonance relaxometry, magnetometry and morpho-dimensional characterization techniques, with a particular focus on the effect of size and coating. Data for this research were collected thanks to cross-collaborations between national and international research groups and hospital structures. For the MFH therapy, the properties of the magnetic nanoparticles that were employed have been optimized in order to maximize their heat release, and, at the same time, to give the patient an amount of magnetic material as low as possible, thus reducing any risk of detrimental side effects to his health. Cell culture conditions and hyperthermic treatment (partly of magnetic origin) were optimized to maximize the efficacy of the therapy, with the aim of decreasing the survival of cancer cells. Given the advantages of hadron therapy over conventional radiotherapy, it was decided to combine the hyperthermic treatment with the first one. This was possible thanks to the fact that Pavia, where most of the work behind this thesis was performed, hosts a state-of-the-art hadron therapy center, the CNAO foundation. This center is the only one in Italy where cancer patients can be treated with both protons and carbon ions. Two main results can be highlighted from the clonogenic survival data collected at 15 days after the combined therapeutic treatment. Firstly, at all hadrons/photon irradiation doses, an additional killing effect – i.e toxicity - of about 50-60% can be ascribed to the cellular uptake of the nanoparticles, with respect to simple irradiation of culture cells. Secondly, a significant killing effect of hyperthermia was observed for both irradiation protocols, consisting in an additional 15-30% of total survival decrease. The enhanced efficacy of Hadron Therapy applied immediately after hyperthermia lays the foundations for future preclinical studies. Furthermore, these encouraging results point in the direction of further investigating this combination, with a view to finally translating it to clinical applications. As to the second goal - i.e. the investigation of the properties of magnetic nanoparticles by means of nuclear magnetic resonance relaxometry and magnetometry - this thesis specifically concerned the influence of coating on the nuclear relaxation times. Two sets of samples, each consisting of four samples with different coatings, were obtained by means of the same synthesis procedure, while the nanoparticles coating has been realized with different polymers. A heuristic model for the field dependence of the NMR relaxivity curves allowed us to evaluate several parameters: among them, the saturation magnetization, the minimum approach distance, etc. Moreover, through the acquisition and analysis of experimental NMR dispersion curves, we observed that the relaxivities r1 and r2 of the four samples analyzed, for both sets, did not show significant differences in the whole range of frequencies investigated, at least within the experimental errors. Thus, we concluded that the four different coatings we analyzed on our spherical MNPs give essentially similar magnetic and relaxometric behavior.This PhD thesis, Multifunctional modalities of iron oxide magnetic nanoparticles: applications in diagnostics and magnetic fluid hyperthermia, has two major purposes. The first goal is to assess the anti-tumor efficacy and the potential of combining Hadron Therapy and Magnetic Fluid Hyperthermia (MFH) against pancreatic tumor cells; this is carried out with a perspective to establishing solid protocols for desirable future clinical applications. The second goal is to evaluate the Magnetic Resonance Imaging (MRI) image contrast efficiency of magnetic nanoparticles. This is accomplished by means of 1H Nuclear Magnetic Resonance relaxometry, magnetometry and morpho-dimensional characterization techniques, with a particular focus on the effect of size and coating. Data for this research were collected thanks to cross-collaborations between national and international research groups and hospital structures. For the MFH therapy, the properties of the magnetic nanoparticles that were employed have been optimized in order to maximize their heat release, and, at the same time, to give the patient an amount of magnetic material as low as possible, thus reducing any risk of detrimental side effects to his health. Cell culture conditions and hyperthermic treatment (partly of magnetic origin) were optimized to maximize the efficacy of the therapy, with the aim of decreasing the survival of cancer cells. Given the advantages of hadron therapy over conventional radiotherapy, it was decided to combine the hyperthermic treatment with the first one. This was possible thanks to the fact that Pavia, where most of the work behind this thesis was performed, hosts a state-of-the-art hadron therapy center, the CNAO foundation. This center is the only one in Italy where cancer patients can be treated with both protons and carbon ions. Two main results can be highlighted from the clonogenic survival data collected at 15 days after the combined therapeutic treatment. Firstly, at all hadrons/photon irradiation doses, an additional killing effect – i.e toxicity - of about 50-60% can be ascribed to the cellular uptake of the nanoparticles, with respect to simple irradiation of culture cells. Secondly, a significant killing effect of hyperthermia was observed for both irradiation protocols, consisting in an additional 15-30% of total survival decrease. The enhanced efficacy of Hadron Therapy applied immediately after hyperthermia lays the foundations for future preclinical studies. Furthermore, these encouraging results point in the direction of further investigating this combination, with a view to finally translating it to clinical applications. As to the second goal - i.e. the investigation of the properties of magnetic nanoparticles by means of nuclear magnetic resonance relaxometry and magnetometry - this thesis specifically concerned the influence of coating on the nuclear relaxation times. Two sets of samples, each consisting of four samples with different coatings, were obtained by means of the same synthesis procedure, while the nanoparticles coating has been realized with different polymers. A heuristic model for the field dependence of the NMR relaxivity curves allowed us to evaluate several parameters: among them, the saturation magnetization, the minimum approach distance, etc. Moreover, through the acquisition and analysis of experimental NMR dispersion curves, we observed that the relaxivities r1 and r2 of the four samples analyzed, for both sets, did not show significant differences in the whole range of frequencies investigated, at least within the experimental errors. Thus, we concluded that the four different coatings we analyzed on our spherical MNPs give essentially similar magnetic and relaxometric behavior

LungQuant

LungQuant is a software for the quantification of lesions in CT scans of COVID-19 patients. Its functioning is based on a cascade of three Convolutional Neural Networks (CNN): 1) the first one is used to produce a bounding box enclosing the lungs; 2) the second CNN is used to segment the lungs; 3) the third CNN is devoted to lesion segmentation. The system takes in input Computed Tomography (CT) scans in nifti format. The system returns in output: the lungs and lesion masks and other information that can be useful to describe the infection

Quantification of pulmonary involvement in COVID-19 pneumonia: an upgrade of the LungQuant software for lung CT segmentation

Computed tomography (CT) scans are used to evaluate the severity of lung involvement in patients affected by COVID-19 pneumonia. Here, we present an improved version of the LungQuant automatic segmentation software (LungQuant v(2)), which implements a cascade of three deep neural networks (DNNs) to segment the lungs and the lung lesions associated with COVID-19 pneumonia. The first network (BB-net) defines a bounding box enclosing the lungs, the second one (U-net(1)) outputs the mask of the lungs, and the final one (U-net(2)) generates the mask of the COVID-19 lesions. With respect to the previous version (LungQuant v1), three main improvements are introduced: the BB-net, a new term in the loss function in the U-net for lesion segmentation and a post-processing procedure to separate the right and left lungs. The three DNNs were optimized, trained and tested on publicly available CT scans. We evaluated the system segmentation capability on an independent test set consisting of ten fully annotated CT scans, the COVID-19-CT-Seg benchmark dataset. The test performances are reported by means of the volumetric dice similarity coefficient (vDSC) and the surface dice similarity coefficient (sDSC) between the reference and the segmented objects. LungQuant v2 achieves a vDSC (sDSC) equal to 0.96 +/- 0.01 (0.97 +/- 0.01) and 0.69 +/- 0.08 (0.83 +/- 0.07) for the lung and lesion segmentations, respectively. The output of the segmentation software was then used to assess the percentage of infected lungs, obtaining a Mean Absolute Error (MAE) equal to 2%

Integration of a Deep Learning-Based Module for the Quantification of Imaging Features into the Filling-in Process of the Radiological Structured Report

The role of Computed Tomography (CT) in the characterization of COVID-19 pneumonia has been widely recognized. The aim of this work is to present the idea of integrating a Deep Learning (DL)-based software, able to automatically quantify qualitative information typically describing COVID-19 lesions on chest CT scans, into a structured report-filling pipeline. Different studies have highlighted the value of introducing the use of structured reports in clinical practice, as a reproducible instrument for diagnosis and follow-up rather than the commonly used free-text radiological report. Structured data are fundamental to helping clinical decision support systems and fostering precision medicine. We developed a Deep Learning based software that segments both the lungs and the lesions associated with COVID-19 pneumonia on chest CT scans and quantifies some indexes describing qualitative characteristics used to assess COVID-19 lesions clinically. Once assessed the robustness of the system by means of a multicenter clinical evaluation made by clinical experts, it can be used for the first stratification of patients, supporting radiologists with a computer-aided quantification, and the derived quantities, immediately intelligible for the clinicians, are suitable to be inserted in a structured report in COVID-19 pneumonia and then exploited as explainable features to build predictive models

Tailoring the magnetic and structural properties of manganese/zinc doped iron oxide nanoparticles through microwaves-assisted polyol synthesis

Tuning the fundamental properties of iron oxide magnetic nanoparticles (MNPs) according to the required biomedical application is an unsolved challenge, as the MNPs’ properties are affected by their composition, their size, the synthesis process, and so on. In this work, we studied the effect of zinc and manganese doping on the magnetic and structural properties of MNPs synthesized by the microwave-assisted polyol process, using diethylene glycol (DEG) and tetraethylene glycol (TEG) as polyols. The detailed morpho-structural and magnetic characterization showed a correspondence between the higher amounts of Mn and smaller crystal sizes of the MNPs. Such size reduction was compensated by an increase in the global magnetic moment so that it resulted in an increase of the saturation magnetization. Saturation magnetization MS values up to 91.5 emu/g and NMR transverse relaxivities r2 of 294 s−1mM−1 were obtained for Zn and Mn- doped ferrites having diameters around 10 nm, whereas Zn ferrites with diameters around 15 nm reached values of MS∼ 97.2 emu/g and of r2∼ 467 s−1mM−1, respectively. Both kinds of nanoparticles were synthesized by a simple, reproducible, and more sustainable method that makes them very interesting for diagnostic applications as MRI contrast agents.This work was funded by the European Commission through the HOTZYMES Project (H2020-FETOPEN-RIA 829162) and European Research Council (ERC) through the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 853468). It was also funded by by the Spanish Ministry of Science and Innovation (AEI/FEDER, UE) through PID2020-113480RB-I00 project, and by the Comunidad de Madrid I+D+i grant program Atracción de Talento project 2018-T1/IND-1005, AECC Ideas Semilla 2019 and SEV-2016-0686 projects. It was also funded by the EU project NESTOR (101007629).Peer reviewe