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Publikationer

ForskningsartiklarEdstorp, J., Wei, Y., Ahlqvist, E., Alfredsson, L., Grill, V., Groop, L., Rasouli, B., Sørgjerd, E. P., Thorsby, P. M., Tuomi, T., Åsvold, B. O., & Carlsson, S. (2023). Smoking, use of smokeless tobacco, HLA genotypes and incidence of latent autoimmune diabetes in adults. Diabetologia, 66(1), 70–81. https://doi.org/10.1007/s00125-022-05763-wChristensen DH, Nicolaisen SK, Ahlqvist

https://www.andis.lu.se/publikationer - 2025-07-05

2023

Rättsfallsseminarium om Foxhouse-domen i Högsta domstolenOnsdagen 5 december kl. 11.00-12.15Advokatfirman Vinge, MalmöHögsta domstolen meddelade den 2 november 2023 dom i mål T 8042-21 (Foxhouse). I avgörandet behandlar Högsta domstolen förutsättningarna för vinstutdelning, återbäringsskyldighet och bristtäckningsansvar enligt aktiebolagslagen samt vissa bestämmelser om återvinning i konkurs. Doms

https://www.aclu.lu.se/evenemang/genomforda-evenemang/2023 - 2025-07-05

Björn Eriksson

Researcher Contact details Email: bjorn [dot] eriksson [at] ekh [dot] lu [dot] se Phone: +46 46 222 08 86Organisation Department of Economic History Visiting address: Scheelevägen 15 B, Lund Room number: Alfa 1:2007 Service point: HS10 WebpageBjörn Erikssons profile in Lund University research portalOther affiliations Researcher Historical labour markets Researcher Growth, technological change, an

https://www.lusem.lu.se/bjorn-eriksson - 2025-07-06

Signalling to Activation of Cytosolic Phospholipase A2 and Arachidonate Release in Macrophages

Eicosanoids include prostaglandins, thromboxanes and leukotrienes, which are arachidonic acid oxygenation products. These lipids make important contributions to the signs and symptoms of inflammatory diseases. The level of free arachidonic acid seems to be a rate-limiting factor in the synthesis of eicosanoids and the enzyme cytosolic phospholipase A2 (cPLA2) has been shown to preferentially liber

Analyzing Vegetation Trends with Sensor Data from Earth Observation Satellites

Abstract This thesis aims to advance the analysis of nonlinear trends in time series of vegetation data from Earth observation satellite sensors. This is accomplished by developing fast, efficient methods suitable for large volumes of data. A set of methods, tools, and a framework are developed and verified using data from regions containing vegetation change hotspots. First, a polynomial-fittin