1,586 research outputs found
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 of exact lower bounds on its ground state energy
density , converging to in the limit . The bounds
can be computed numerically on a finite lattice with 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
Higher retransplantation rate following extended right split-liver transplantation: An analysis from the eurotransplant liver follow-up registry
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: âPositron Emission Tomographyâ
OR âPETâ AND âGammaâ OR âÎłâ AND âProbeâ AND âRadioguided Surgeryâ OR âRGSâ. 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 surgeonsâ ability to obtain a complete resection of tumors, even if the nature of photons resulting from positronâelectron
collision still remains extremely challenging and requires further technical advances
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: 19â38w) 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
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: 19â38w) 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
Prognostic and theranostic applications of positron emission tomography for a personalized approach to metastatic castrationâresistant prostate cancer
Metastatic castrationâresistant prostate cancer (mCRPC) represents a condition of pro-gressive disease in spite of androgen deprivation therapy (ADT), with a broad spectrum of mani-festations ranging from no symptoms to severe debilitation due to bone or visceral metastatization. The management of mCRPC has been profoundly modified by introducing novel therapeutic tools such as antiandrogen drugs (i.e., abiraterone acetate and enzalutamide), immunotherapy through sipuleucelâT, and targeted alpha therapy (TAT). This variety of approaches calls for unmet need of biomarkers suitable for patientsâ preâtreatment selection and prognostic stratification. In this sce-nario, imaging with positron emission computed tomography (PET/CT) presents great and still unexplored potential to detect specific molecular and metabolic signatures, some of whom, such as the prostate specific membrane antigen (PSMA), can also be exploited as therapeutic targets, thus combining diagnosis and therapy in the soâcalled âtheranosticâ approach. In this review, we per-formed a webâbased and desktop literature research to investigate the prognostic and theranostic potential of several PET imaging probes, such as18FâFDG,18Fâcholine and68GaâPSMAâ11, also covering the emerging tracers still in a preâclinical phase (e.g., PARPâinhibitorsâ analogs and the radioligands binding to gastrin releasing peptide receptors/GRPR), highlighting their potential for defining personalized care pathways in mCRPC
Compositional study and antioxidant potential of Ipomoea hederacea Jacq. and Lepidium sativum L. seeds
The present investigation has been carried out to find the proximate composition, amino acids, metal contents, oil composition as well as the antioxidant capacity of the seeds of Ipomoea hederacea Jacq. and Lepidium sativum L. Proximate composition indicated a great difference in oil (14.09\ub10.66, 28.03\ub11.05) and fibre (16.55\ub10.31, 6.75\ub11.20) contents for I. hederacea and L. sativum, respectively. Fatty acid profile indicated that oleic acid (19.50 \ub1 0.37, 30.50 \ub1 0.16) and linoleic acid (52.09 \ub1 0.48, 8.60 \ub1 0.38) are major fatty acids. \u3b3-Tocopheol and alfa-tocopheol (28.70 \ub1 0.14, 111.56 \ub1 0.37) were the most abundant in the seed oil of I. hederacea and L. sativum, respectively. Results of antioxidant assays like TEAC, FRAP and TRAP indicated that L. sativum has much greater antioxidant potential than I. hederacea
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