1. Same, but different: similar states of forest structure in temperate mountain regions of Europe despite different social-ecological forest disturbance regimes 

   Stritih, Ana; Senf, Cornelius; Kuemmerle, Tobias; et al. (2024)

   Landscape Ecology

   Context Ecosystem services provided by mountain forests are critically linked to forest structure. Social-ecological disturbance regimes (i.e., the rate, frequency, and patch size distribution of disturbances driven by interacting natural and anthropogenic processes) and land use affect forest structure, but their specific impacts are not fully understood. Objectives We examine how differences in disturbance regimes affect patterns of ...

   Journal Article

2. Microvascular dysfunction in heart transplantation is associated with altered cardiomyocyte mitochondrial structure and unimpaired excitation-contraction coupling 

   Hohendanner, Felix; Boegner, Markus; Huettemeister, Judith; et al. (2024)

   PLoS ONE

   Introduction Microvascular dysfunction (MVD) is a hallmark feature of chronic graft dysfunction in patients that underwent orthotopic heart transplantation (OHT) and is the main contributor to impaired long-term graft survival. The aim of this study was to determine the effect of MVD on functional and structural properties of cardiomyocytes isolated from ventricular biopsies of OHT patients. Methods We included 14 patients post-OHT, who ...

   Journal Article

3. Predicting mortality after transcatheter aortic valve replacement using preprocedural CT 

   Brüggemann, David; Kuzo, Nazar; Anwer, Shehab; et al. (2024)

   Scientific Reports

   Transcatheter aortic valve replacement (TAVR) is a widely used intervention for patients with severe aortic stenosis. Identifying high-risk patients is crucial due to potential postprocedural complications. Currently, this involves manual clinical assessment and time-consuming radiological assessment of preprocedural computed tomography (CT) images by an expert radiologist. In this study, we introduce a probabilistic model that predicts ...

   Journal Article

4. A Bayesian Take on Gaussian Process Networks 

   Giudice, Enrico; Kuipers, Jack; Moffa, Giusi (2023)

   Advances in Neural Information Processing Systems

   Gaussian Process Networks (GPNs) are a class of directed graphical models which employ Gaussian processes as priors for the conditional expectation of each variable given its parents in the network. The model allows the description of continuous joint distributions in a compact but flexible manner with minimal parametric assumptions on the dependencies between variables. Bayesian structure learning of GPNs requires computing the posterior ...

   Conference Paper

5. Search for dark matter particles in W⁺W⁻ events with transverse momentum imbalance in proton-proton collisions at s = 13 TeV 

   Hayrapetyan A.; Tumasyan A.; Adam W.; et al. (2024)

   Journal of High Energy Physics

   A search for dark matter particles is performed using events with a pair of W bosons and large missing transverse momentum. Candidate events are selected by requiring one or two leptons (ℓ = electrons or muons). The analysis is based on proton-proton collision data collected at a center-of-mass energy of 13 TeV by the CMS experiment at the LHC and corresponding to an integrated luminosity of 138 fb−1. No significant excess over the expected ...

   Journal Article

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