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This study uniquely combines advanced continental-scale data from two distinct sources: pollen-based past land cover (paleoecology) and ancient DNA (aDNA), developing a novel statistical model for spatiotemporal reconstructions of past land use across Europe. This groundbreaking approach integrates paleo-pollen and aDNA data, providing unprecedented insights into the environmental impacts of Holoc
This study examines how one may detect Parkinson’s disease (PD) by analyzing voice recordings made with a mobile phone. The key objectives include creating a model that ensures fair and unbiased predictions while maintaining interpretability that is consistent with the existing literature on PD. We introduce a novel group-wise scaling method to address typical age and biological sex biases in the
Digitalization is shaping the discipline and practice of marketing. Not only does digitalization shape how we shop and consume everything from music to food and mobility services (Cochoy, Hagberg, McIntyre, & Sörum, 2017; Fuentes, Hagberg, & Kjellberg, 2019; Guyader, 2018; Schneider & Eli, 2022), but it has also fundamentally transformed the practices of marketing. Digitalization has c
Collagen VII is an essential anchoring protein in the basement membrane zone, maintaining the attachment of stratified and pseudostratified epithelia to the underlying interstitial matrix. However, collagen VII is largely unexplored in normal lungs and idiopathic pulmonary fibrosis (IPF), a disease characterized by excessive accumulation of extracellular matrix (ECM) and aberrant re-epithelializat
Background: Recurrent coarctation of the aorta (re-CoA) is a well-known although not fully understood complication after surgical repair, typically occurring in 10%–20% of cases within months after discharge. Objectives: To (1) characterize geometry of the aortic arch and blood flow from pre-discharge magnetic resonance imaging (MRI) in neonates after CoA repair; and (2) compare these measures bet
Lung transplantation is limited by a scarcity of suitable donors resulting in high waiting list mortality. Ex vivo lung perfusion (EVLP) allows the evaluation and reconditioning of marginal donor lungs for use in transplantation. This study aimed to compare clinical outcome of patients transplanted with marginal organs by means of EVLP with a standard lung transplant cohort through a multicenter o
By using large scale numerical simulations, we obtain fractal structure, which develops at originally planar flame fronts due to the hydrodynamic Darrieus-Landau (DL) instability bending the fronts. We clarify some important issues regarding the DL fractal flames, which have been debated for a long time. We demonstrate an increase of the flame propagation speed with the hypothetic channel width, w
Biennial sugar beet (Beta vulgaris spp. vulgaris) is a Caryophyllidae that has adapted its growth cycle to the seasonal temperature and day length variation of temperate regions. This is the first time a holistic study of the expression pattern of non-symbiotic hemoglobins (nsHbs) is being carried out in a member of this group and under two essential environmental conditions for flowering, namely
Large Language Models (LLMs) such as GPT, BART, and Gemini stand at the forefront of Generative Artificial Intelligence, showcasing remarkable prowess in natural language comprehension and task execution. This paper proposes a novel framework developed on the foundation of Llama 2, aiming to bridge the gap between natural language queries and executable code for geospatial analyses within the PyQG
We compared manual lymph drainage (MLD) with sequential pneumatic compression (SPC) for treatment of unilateral arm lymphedema in 28 women previously treated for breast cancer. After 2 weeks of therapy with a standard compression sleeve (Part I) with maintenance of a steady arm volume, each patient was randomly assigned to either one of two treatment regimens (Part II). MLD was performed according
In this study, we use a data assimilation framework based on the adaptive Markov chain Monte Carlo (MCMC) algorithm to constrain process parameters in LPJ-GUESS model using CH4 eddy-covariance flux observations from 14 different natural boreal, temperate, and arctic wetlands. The objective is to derive a single set of calibrated parameter values. The calibrated parameter values are then used in th
We propose a methodology to enhance local CO2 monitoring by integrating satellite data from the Orbiting Carbon Observatories (OCO-2 and OCO-3) with ground-level observations from the Integrated Carbon Observation System (ICOS) and weather data from the ECMWF Reanalysis v5 (ERA5). Unlike traditional methods that downsample national data, our approach uses multimodal data fusion for high-resolution
Climate change calls for adaptive strategies to manage land system across governance levels, as differing multi-level policies distinctly shape land system and long-term ecosystem resilience. This study proposes an iterative approach for optimizing land-use pathways that balance competing policy objectives across national, provincial, and local levels without compromising ecosystem integrity in a
Background: Creatinine-based estimated glomerular filtration rate (eGFR) equations are widely used in clinical practice but exhibit inherent limitations. On the other side, measuring GFR is time consuming and not available in routine clinical practice. We developed and validated machine learning models to assess the trustworthiness (i.e. the ability of equations to estimate measured GFR (mGFR) wit
Cell replacement therapies using human pluripotent stem cell-derived ventral midbrain (VM) dopaminergic (DA) progenitors are currently in clinical trials for treatment of Parkinson’s disease (PD). Recapitulating developmental patterning cues, such as fibroblast growth factor 8 (FGF8), secreted at the midbrain-hindbrain boundary (MHB), is critical for the in vitro production of authentic VM DA prog
BACKGROUND: The global prevalence of dementia is rapidly expanding and is expected to triple by 2050. Approximately 45 % of dementia cases are estimated to be attributable to potentially modifiable risk factors. Identifying how these factors contribute to specific brain pathologies may improve strategies to reduce dementia incidence.OBJECTIVES, DESIGN, SETTING: The aim of this study was to identif
