| 1. |
- Valiente-Dobon, J. J., et al.
(författare)
-
Conceptual design of the AGATA 2 pi array at LNL
- 2023
-
Ingår i: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 1049
-
Tidskriftsartikel (refereegranskat)abstract
- The Advanced GAmma Tracking Array (AGATA) has been installed at Laboratori Nazionali di Legnaro (LNL), Italy. In this installation, AGATA will consist, at the beginning, of 13 AGATA triple clusters (ATCs) with an angular coverage of 1n,and progressively the number of ATCs will increase up to a 2 pi angular coverage. This setup will exploit both stable and radioactive ion beams delivered by the Tandem-PIAVE-ALPI accelerator complex and the SPES facility. The new implementation of AGATA at LNL will be used in two different configurations, firstly one coupled to the PRISMA large-acceptance magnetic spectrometer and lately a second one at Zero Degrees, along the beam line. These two configurations will allow us to cover a broad physics program, using different reaction mechanisms, such as Coulomb excitation, fusion-evaporation, transfer and fission at energies close to the Coulomb barrier. These setups have been designed to be coupled with a large variety of complementary detectors such as charged particle detectors, neutron detectors, heavy-ion detectors, high-energy gamma-ray arrays, cryogenic and gasjet targets and the plunger device for lifetime measurements. We present in this paper the conceptual design, characteristics and performance figures of this implementation of AGATA at LNL.
|
|
| 2. |
- Solmi, M, et al.
(författare)
-
- 2022
-
Ingår i: Journal of affective disorders. - : Elsevier BV. - 1573-2517 .- 0165-0327. ; 299, s. 367-376
-
Tidskriftsartikel (refereegranskat)
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Sala, A, et al.
(författare)
-
Molecular connectivity: A review of tools
- 2022
-
Ingår i: JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM. - 0271-678X. ; 42:1_SUPPL, s. 66-67
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)
|
|
| 7. |
|
|
| 8. |
- Brusaferri, L., et al.
(författare)
-
The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic
- 2022
-
Ingår i: Brain, Behavior, and Immunity. - : Elsevier BV. - 0889-1591. ; 102, s. 89-97
-
Tidskriftsartikel (refereegranskat)abstract
- While COVID-19 research has seen an explosion in the literature, the impact of pandemic-related societal and lifestyle disruptions on brain health among the uninfected remains underexplored. However, a global increase in the prevalence of fatigue, brain fog, depression and other “sickness behavior”-like symptoms implicates a possible dysregulation in neuroimmune mechanisms even among those never infected by the virus. We compared fifty-seven ‘Pre-Pandemic’ and fifteen ‘Pandemic’ datasets from individuals originally enrolled as control subjects for various completed, or ongoing, research studies available in our records, with a confirmed negative test for SARS-CoV-2 antibodies. We used a combination of multimodal molecular brain imaging (simultaneous positron emission tomography / magnetic resonance spectroscopy), behavioral measurements, imaging transcriptomics and serum testing to uncover links between pandemic-related stressors and neuroinflammation. Healthy individuals examined after the enforcement of 2020 lockdown/stay-at-home measures demonstrated elevated brain levels of two independent neuroinflammatory markers (the 18 kDa translocator protein, TSPO, and myoinositol) compared to pre-lockdown subjects. The serum levels of two inflammatory markers (interleukin-16 and monocyte chemoattractant protein-1) were also elevated, although these effects did not reach statistical significance after correcting for multiple comparisons. Subjects endorsing higher symptom burden showed higher TSPO signal in the hippocampus (mood alteration, mental fatigue), intraparietal sulcus and precuneus (physical fatigue), compared to those reporting little/no symptoms. Post-lockdown TSPO signal changes were spatially aligned with the constitutive expression of several genes involved in immune/neuroimmune functions. This work implicates neuroimmune activation as a possible mechanism underlying the non-virally-mediated symptoms experienced by many during the COVID-19 pandemic. Future studies will be needed to corroborate and further interpret these preliminary findings. © 2022 Elsevier Inc.
|
|
| 9. |
|
|
| 10. |
- Knudsen, Gitte M, et al.
(författare)
-
Guidelines for the content and format of PET brain data in publications and archives : A consensus paper
- 2020
-
Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : SAGE Publications. - 0271-678X .- 1559-7016. ; 40:8, s. 1576-1585
-
Tidskriftsartikel (refereegranskat)abstract
- It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.
|
|
