| 1. |
|
|
| 2. |
- Collste, K., et al.
(författare)
-
Lower levels of the glial cell marker TSPO in drug-naive first-episode psychosis patients as measured using PET and [C-11]PBR28
- 2017
-
Ingår i: Molecular Psychiatry. - : NATURE PUBLISHING GROUP. - 1359-4184 .- 1476-5578. ; 22:6, s. 850-856
-
Tidskriftsartikel (refereegranskat)abstract
- Several lines of evidence are indicative of a role for immune activation in the pathophysiology of schizophrenia. Nevertheless, studies using positron emission tomography (PET) and radioligands for the translocator protein (TSPO), a marker for glial activation, have yielded inconsistent results. Whereas early studies using a radioligand with low signal-to-noise in small samples showed increases in patients, more recent studies with improved methodology have shown no differences or trend-level decreases. Importantly, all patients investigated thus far have been on antipsychotic medication, and as these compounds may dampen immune cell activity, this factor limits the conclusions that can be drawn. Here, we examined 16 drug-naive, first-episode psychosis patients and 16 healthy controls using PET and the TSPO radioligand [C-11]PBR28. Gray matter (GM) volume of distribution (V-T) derived from a two-tissue compartmental analysis with arterial input function was the main outcome measure. Statistical analyses were performed controlling for both TSPO genotype, which is known to affect [C-11]PBR28 binding, and gender. There was a significant reduction of [C-11]PBR28 V-T in patients compared with healthy controls in GM as well as in secondary regions of interest. No correlation was observed between GM V-T and clinical or cognitive measures after correction for multiple comparisons. The observed decrease in TSPO binding suggests reduced numbers or altered function of immune cells in brain in early-stage schizophrenia.
|
|
| 3. |
|
|
| 4. |
- Jalkanen, J. P., et al.
(författare)
-
Modelling of ships as a source of underwater noise
- 2018
-
Ingår i: Ocean Science. - : Copernicus GmbH. - 1812-0792 .- 1812-0784. ; 14:6, s. 1373-1383
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, a methodology is presented for modelling underwater noise emissions from ships based on realistic vessel activity in the Baltic Sea region. This paper combines the Wittekind noise source model with the Ship Traffic Emission Assessment Model (STEAM) in order to produce regular updates for underwater noise from ships. This approach allows the construction of noise source maps, but requires parameters which are not commonly available from commercial ship technical databases. For this reason, alternative methods were necessary to fill in the required information. Most of the parameters needed contain information that is available during the STEAM model runs, but features describing propeller cavitation are not easily recovered for the world fleet. Baltic Sea ship activity data were used to generate noise source maps for commercial shipping. Container ships were recognized as the most significant source of underwater noise, and the significant potential for an increase in their contribution to future noise emissions was identified.
|
|
| 5. |
- Karasalo, I., et al.
(författare)
-
Estimates of source spectra of ships from long term recordings in the Baltic sea
- 2017
-
Ingår i: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 4:JUN
-
Tidskriftsartikel (refereegranskat)abstract
- © 2017 Karasalo, östberg, Sigray, Jalkanen, Johansson, Liefvendahl and Bensow. Estimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the island öland. Data from over 2,000 close-by passages were recorded during a 3 month period from October to December 2014. For each passage, ship-to-hydrophone transmission loss (TL) spectra were computed by sound propagation modeling using 1. bathymetry data from the Baltic Sea Bathymetry Database (BSBD), 2. sound speed profiles from the HIROMB oceanographic model, 3. seabed parameters obtained by acoustic inversion of data from a calibrated source, and 4. AIS data providing information on each ship's position. These TL spectra were then subtracted from the received noise spectra to estimate the free field source level (SL) spectra for each passage. The SL were compared to predictions by some existing models of noise emission from ships. Input parameters to the models, including e.g., ship length, width, speed, displacement, and engine mass, were obtained from AIS (Automatic Identification System) data and the STEAM database of the Finnish Metereological Institute (FMI).
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
|
|
