A Model for QCD at High Density and Large Quark Mass

We study the high density region of QCD within an effective model obtained in the frame of the hopping parameter expansion and choosing Polyakov type of loops as the main dynamical variables representing the fermionic matter. To get a first idea of the phase structure, the model is analyzed in strong coupling expansion and using a mean field approximation. In numerical simulations, the model still shows the so-called sign problem, a difficulty peculiar to non-zero chemical potential, but it permits the development of algorithms which ensure a good overlap of the Monte Carlo ensemble with the true one. We review the main features of the model and present calculations concerning the dependence of various observables on the chemical potential and on the temperature, in particular of the charge density and the diquark susceptibility, which may be used to characterize the various phases expected at high baryonic density. We obtain in this way information about the phase structure of the model and the corresponding phase transitions and cross over regions, which can be considered as hints for the behaviour of non-zero density QCD.Comment: 21 pages, 29 figure

Phase diagram of the lattice Wess-Zumino model from rigorous lower bounds on the energy

We study the lattice N=1 Wess-Zumino model in two dimensions and we construct a sequence $\rho^{(L)}$ of exact lower bounds on its ground state energy density $\rho$, converging to $\rho$ in the limit $L\to\infty$. The bounds $\rho^{(L)}$ can be computed numerically on a finite lattice with $L$ sites and can be exploited to discuss dynamical symmetry breaking. The transition point is determined and compared with recent results based on large-scale Green Function Monte Carlo simulations with good agreement.Comment: 32 pages, 12 figure

Role of PET gamma detection in radioguided surgery: a systematic review

Purpose This systematic review aimed to collect published studies concerning intraoperative gamma detection of positronemitting tracers for radioguided surgery (RGS) applications. Methods A systematic literature search of studies published until October 2022 was performed in Pubmed, Web Of Science, Central (Cochrane Library) and Scopus databases, including the following keywords: “Positron Emission Tomography” OR “PET” AND “Gamma” OR “γ” AND “Probe” AND “Radioguided Surgery” OR “RGS”. The included studies had to concern RGS procedures performed in at least 3 patients, regardless of the administered radiopharmaceutical and the field of application. Results Among to the 17 selected studies, all published between 2000 and 2022, only 2 investigations were conducted with gallium-68 (68Ga)-labeled somatostatin analogues, with fluorine-18-fluoro-2-deoxyglucose ([ 18F]FDG) being the most commonly used agent for RGS applications. Almost all studies were performed in oncologic patients, with only one paper also including inflammatory and infectious findings. The analysis showed that the largest part of procedures was performed through the intraoperative use of conventional gamma probes, not specifically designed for the detection of annihilation photons (n = 9), followed by PET gamma probes (n = 5) and with only three studies involving electronic collimation. Conclusions Regardless of the intraoperative devices, RGS with positron emitters seems to lead to significant improvements in surgeons’ ability to obtain a complete resection of tumors, even if the nature of photons resulting from positron–electron collision still remains extremely challenging and requires further technical advances

A brief overview on valorization of industrial tomato by-products using the biorefinery cascade approach

The industrial processing of tomato leads to substantial amounts of residues, typically known as tomato pomace or by-products, which can represent as much as 10% by weight of fresh tomatoes. At present, these residues are either used as feedstock for animals or, in the worst case, disposed of in landfills. This represents a significant waste because tomato pomace contains high-value compounds like lycopene, a powerful antioxidant, cutin, which can be used as a starting material for biopolymers, and pectin, a gelling agent. This article presents an overview of technologies that valorize tomato by-products by recovering added-value compounds as well as generating fuel for energy production. These technologies include operations for extraction, separation, and exploitation of lycopene, cutin and pectin, as well as the processes for conversion of the solid residues to fuels. Data collected from the review has been used to develop a biorefinery scheme with the related mass flow balance, for a scenario involving the tomato supply chain of Regione Campania in Italy, using tomato by-products as feedstock

Apparent diffusion coefficient assessment of brain development in normal fetuses and ventriculomegaly

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19–38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values = 50, 200, 700 s/mm2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing, and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC between normal and VM cases and between second and third trimester in different brain regions. Correlation between ADC and GA was assessed with linear and quadratic regression analysis. Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains (p ≤ 0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p ≤ 0.02). ADC values in centrum semiovale, thalamus, cerebellum and pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA was found in basal ganglia and occipital white matter of normal brains and in frontal white matter of VM (p ≤ 0.02). ADC values in all fetal brain regions were lower than those reported in literature where DWI with b = 0 was performed. Conversely, they were in agreement with the results of other authors who measured perfusion and diffusion contributions separately. By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities associated with VM

18F-fluorodeoxyglucose (18F-FDG) functionalized gold nanoparticles (GNPs) for plasmonic photothermal ablation of cancer. A review

The meeting and merging between innovative nanotechnological systems, such as nanoparticles, and the persistent need to outperform diagnostic-therapeutic approaches to fighting cancer are revolutionizing the medical research scenario, leading us into the world of nanomedicine. Photothermal therapy (PTT) is a non-invasive thermo-ablative treatment in which cellular hyperthermia is generated through the interaction of near-infrared light with light-to-heat converter entities, such as gold nanoparticles (GNPs). GNPs have great potential to improve recovery time, cure complexity, and time spent on the treatment of specific types of cancer. The development of gold nanostructures for photothermal efficacy and target selectivity ensures effective and deep tissue-penetrating PTT with fewer worries about adverse effects from nonspecific distributions. Regardless of the thriving research recorded in the last decade regarding the multiple biomedical applications of nanoparticles and, in particular, their conjugation with drugs, few works have been completed regarding the possibility of combining GNPs with the cancer-targeted pharmaceutical fluorodeoxyglucose (FDG). This review aims to provide an actual scenario on the application of functionalized GNP-mediated PTT for cancer ablation purposes, regarding the opportunity given by the 18F-fluorodeoxyglucose (18F-FDG) functionalization

Basil essential oil: Composition, antimicrobial properties, and microencapsulation to produce active chitosan films for food packaging

The essential oil (EO) from basil—Ocimum basilicum—was characterized, microencapsu-lated by vibration technology, and used to prepare a new type of packaging system designed to extend the food shelf life. The basil essential oil (BEO) chemical composition and antimicrobial activity were analyzed, as well as the morphological and biological properties of the derived BEO microcapsules (BEOMC). Analysis of BEO by gas chromatography demonstrated that the main component was linalool, whereas the study of its antimicrobial activity showed a significant inhibitory effect against all the microorganisms tested, mostly Gram-positive bacteria. Moreover, the prepared BEOMC showed a spheroidal shape and retained the EO antimicrobial activity. Finally, chitosan-based edible films were produced, grafted with BEOMC, and characterized for their physicochemical and biological properties. Since their effective antimicrobial activity was demonstrated, these films were tested as packaging system by wrapping cooked ham samples during 10 days of storage, with the aim of their possible use to extend the shelf life of the product. It was demonstrated that the obtained active film can both control the bacterial growth of the cooked ham and markedly inhibit the pH increase of the packaged food

Automated joint skull-stripping and segmentation with Multi-Task U-Net in large mouse brain MRI databases

Skull-stripping and region segmentation are fundamental steps in preclinical magnetic resonance imaging (MRI) studies, and these common procedures are usually performed manually. We present Multi-task U-Net (MU-Net), a convolutional neural network designed to accomplish both tasks simultaneously. MU-Net achieved higher segmentation accuracy than state-of-the-art multi-atlas segmentation methods with an inference time of 0.35 s and no pre-processing requirements. We trained and validated MU-Net on 128 T2-weighted mouse MRI volumes as well as on the publicly available MRM NeAT dataset of 10 MRI volumes. We tested MU-Net with an unusually large dataset combining several independent studies consisting of 1782 mouse brain MRI volumes of both healthy and Huntington animals, and measured average Dice scores of 0.906 (striati), 0.937 (cortex), and 0.978 (brain mask). Further, we explored the effectiveness of our network in the presence of different architectural features, including skip connections and recently proposed framing connections, and the effects of the age range of the training set animals. These high evaluation scores demonstrate that MU-Net is a powerful tool for segmentation and skull-stripping, decreasing inter and intra-rater variability of manual segmentation. The MU-Net code and the trained model are publicly available at https://github.com/Hierakonpolis/MU-Net

Apparent Diffusion Coefficient Assessment of Brain Development in Normal Fetuses and Ventriculomegaly

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19–38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values = 50, 200, 700 s/mm2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing, and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC between normal and VM cases and between second and third trimester in different brain regions. Correlation between ADC and GA was assessed with linear and quadratic regression analysis. Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains (p ≤ 0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p ≤ 0.02). ADC values in centrum semiovale, thalamus, cerebellum and pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA was found in basal ganglia and occipital white matter of normal brains and in frontal white matter of VM (p ≤ 0.02). ADC values in all fetal brain regions were lower than those reported in literature where DWI with b = 0 was performed. Conversely, they were in agreement with the results of other authors who measured perfusion and diffusion contributions separately. By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities associated with VM