A socially interdependent choice framework for social influences in healthcare decision-making:a study protocol

OBJECTIVES: Current choice models in healthcare (and beyond) can provide suboptimal predictions of healthcare users' decisions. One reason for such inaccuracy is that standard microeconomic theory assumes that decisions of healthcare users are made in a social vacuum. Healthcare choices, however, can in fact be (entirely) socially determined. To achieve more accurate choice predictions within healthcare and therefore better policy decisions, the social influences that affect healthcare user decision-making need to be identified and explicitly integrated into choice models. The purpose of this study is to develop a socially interdependent choice framework of healthcare user decision-making.DESIGN: A mixed-methods approach will be used. A systematic literature review will be conducted that identifies the social influences on healthcare user decision-making. Based on the outcomes of a systematic literature review, an interview guide will be developed that assesses which, and how, social influences affect healthcare user decision-making in four different medical fields. This guide will be used during two exploratory focus groups to assess the engagement of participants and clarity of questions and probes. The refined interview guide will be used to conduct the semistructured interviews with healthcare professionals and users. These interviews will explore in detail which, and how, social influences affect healthcare user decision-making. Focus group and interview transcripts will be analysed iteratively using a constant comparative approach based on a mix of inductive and deductive coding. Based on the outcomes, a social influence independent choice framework for healthcare user decision-making will be drafted. Finally, the Delphi technique will be employed to achieve consensus about the final version of this choice framework.ETHICS AND DISSEMINATION: This study was approved by the Erasmus School of Health Policy and Management Research Ethics Review Committee (ESHPM, Rotterdam, The Netherlands; reference ETH2122-0666).</p

Optimizing Agricultural Supply Chains with Machine Learning Algorithms

Agricultural supply chains serve as the vital link between producers and consumers, ensuring the efficient flow of agricultural products. Their optimization is essential to address challenges like seasonal variations, transportation complexities, and quality control. Machine learning, with its predictive modeling, demand forecasting, route optimization, inventory management, quality control, and risk management capabilities, offers a promising solution to revolutionize the agricultural industry. These supply chains consist of various components, including producers, distributors, retailers, and consumers, each contributing to the network that delivers agricultural products. To enhance efficiency and product quality, innovative solutions are required to overcome challenges such as seasonal fluctuations and quality concerns. Machine learning empowers supply chain stakeholders to make data-driven decisions, automate processes, and optimize various aspects of the supply chain. This technology enhances the resilience and efficiency of agricultural supply chains, ensuring the delivery of fresh and safe products to consumers. Effective data collection and preprocessing are essential for leveraging machine learning's potential. Through sourcing, cleaning, and structuring data from diverse sources, stakeholders enable machine learning algorithms to make informed recommendations and predictions. Machine learning's application in agricultural supply chains, exemplified by predictive modeling for crop yield through weather data analysis and disease detection, illustrates the power of data-driven technologies in enhancing crop production, reducing losses, and ensuring a secure global food supply

The Barents area changes – How will Finland adapt? (Barentsin alue muuttuu – miten Suomi sopeutuu?)

The cumulative impacts of environmental, climatic and societal changes and their consequences will affect the development of the Arctic region in the coming decades. Adaptation to these changes will require measures of all the actors in the region. Finland, part of the Euro-Arctic region, will adapt to these changes in a variety of ways. The Barents area is unique in the Arctic in being a multicultural, relatively densely populated area with well-developed industries and infrastructure. This report examines adaptation to changes and their consequences in the Barents area in terms of governance and Finland’s capacities to adapt. The aim has been to produce comprehensive information from the Finnish perspective for local and national decision-makers about long-term changes in the region, their expected impacts and adaptation options, and to support decision-making that will advance adaptation. The report includes recommendations. This report is based on the contribution of Finnish experts to an Arctic Council and Arctic Monitoring and Assessment Programme (AMAP) project titled ”Adaptation Actions for a Changing Arctic” (AACA). The project has prepared a pilot report by Nordic and Russian experts on the Barents area in English on changes, their impacts and adaptation options. The report will be published in 2017 (AMAP 2017)

HUWE1 E3 ligase promotes PINK1/PARKINindependent mitophagy by regulating AMBRA1 activation via IKKa

The selective removal of undesired or damaged mitochondria by autophagy, known as mitophagy, is crucial for cellular homoeostasis, and prevents tumour diffusion, neurodegeneration and ageing. The pro-autophagic molecule AMBRA1 (autophagy/beclin-1 regulator-1) has been defined as a novel regulator of mitophagy in both PINK1/PARKIN-dependent and -independent systems. Here, we identified the E3 ubiquitin ligase HUWE1 as a key inducing factor in AMBRA1-mediated mitophagy, a process that takes place independently of the main mitophagy receptors. Furthermore, we show that mitophagy function of AMBRA1 is post-translationally controlled, upon HUWE1 activity, by a positive phosphorylation on its serine 1014. This modification is mediated by the IKKα kinase and induces structural changes in AMBRA1, thus promoting its interaction with LC3/GABARAP (mATG8) proteins and its mitophagic activity. Altogether, these results demonstrate that AMBRA1 regulates mitophagy through a novel pathway, in which HUWE1 and IKKα are key factors, shedding new lights on the regulation of mitochondrial quality control and homoeostasis in mammalian cells

Clinical course, therapeutic responses and outcomes in relapsing MOG antibody-associated demyelination.

Abstract OBJECTIVE: We characterised the clinical course, treatment and outcomes in 59 patients with relapsing myelin oligodendrocyte glycoprotein (MOG) antibody-associated demyelination. METHODS: We evaluated clinical phenotypes, annualised relapse rates (ARR) prior and on immunotherapy and Expanded Disability Status Scale (EDSS), in 218 demyelinating episodes from 33 paediatric and 26 adult patients. RESULTS: The most common initial presentation in the cohort was optic neuritis (ON) in 54% (bilateral (BON) 32%, unilateral (UON) 22%), followed by acute disseminated encephalomyelitis (ADEM) (20%), which occurred exclusively in children. ON was the dominant phenotype (UON 35%, BON 19%) of all clinical episodes. 109/226 (48%) MRIs had no brain lesions. Patients were steroid responsive, but 70% of episodes treated with oral prednisone relapsed, particularly at doses <10\u2009mg daily or within 2 months of cessation. Immunotherapy, including maintenance prednisone (P=0.0004), intravenous immunoglobulin, rituximab and mycophenolate, all reduced median ARRs on-treatment. Treatment failure rates were lower in patients on maintenance steroids (5%) compared with non-steroidal maintenance immunotherapy (38%) (P=0.016). 58% of patients experienced residual disability (average follow-up 61 months, visual loss in 24%). Patients with ON were less likely to have sustained disability defined by a final EDSS of 652 (OR 0.15, P=0.032), while those who had any myelitis were more likely to have sustained residual deficits (OR 3.56, P=0.077). CONCLUSION: Relapsing MOG antibody-associated demyelination is strongly associated with ON across all age groups and ADEM in children. Patients are highly responsive to steroids, but vulnerable to relapse on steroid reduction and cessation

Sää- ja ilmastoriskit Suomessa - Kansallinen arvio

Tähän raporttiin on koottu ajantasainen arvio sään ja ilmaston aiheuttamista riskeistä eri toimialoille Suomessa. Arviossa otettiin huomioon sekä muuttuvan ilmaston että yhteiskunnallisen kehityksen vaikutus riskin muodostumiseen nykyhetkessä ja tulevaisuudessa. Sää- ja ilmastoriskejä pyrittiin hahmottamaan vaaratekijän (riskiä aiheuttava sääilmiö), altistumisen (riskin kohteen sijainti) ja haavoittuvuuden (riskin kohteen ominaisuudet) yhdistelmänä. Sääilmiöt aiheuttavat Suomessa riskejä jo nykyilmastossa. Muun muassa rajuilmat, helleaallot ja rankkasateet aiheuttavat taloudellisia ja terveydellisiä vaikutuksia sekä yleistä haittaa. Tulevaisuudessa riskit muuttuvat ilmastonmuutoksen muuttaessa haitallisia sääilmiöitä. Ilmastonmuutos tuo vähitellen kasvavia riskejä erityisesti ekosysteemeille ja infrastruktuurille. Muualla maailmalla tapahtuvat ilmastonmuutoksen vaikutukset voivat heijastua epäsuorasti Suomeen globaalien tavara-, energia-, raha- ja ihmisvirtojen kautta. Näiden riskien systemaattinen arviointi on vasta aloitettu. Raportin tavoitteena on tukea yhteiskunnan riskeihin varautumista ja ilmastonmuutokseen sopeutumista eri hallinnon tasoilla ja toimialoilla. Arvio perustuu pääosin kirjallisuudesta löytyviin tutkimuksiin ja selvityksiin sekä asiantuntija-arvioihin. Työ tehtiin “Sää- ja ilmastoriskien arviointi ja toimintamallit” (SIETO)- hankkeessa vuosina 2017–2018

The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990-2018

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990-2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011-2015, the CO2 land sources and sinks from NGHGI estimates report-90 Tg C yr-1 ± 30 Tg C yr-1 while all other BU approaches report a mean sink of-98 Tg C yr-1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr-1 ± 400 Tg C yr-1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of "CO2 flux"obtained from different approaches. The referenced datasets related to figures are visualized. © 2021 Ana Maria Roxana Petrescu et al

Species-specific, pan-European diameter increment models based on data of 2.3 million trees

ResearchBackground: Over the last decades, many forest simulators have been developed for the forests of individual European countries. The underlying growth models are usually based on national datasets of varying size, obtained from National Forest Inventories or from long-term research plots. Many of these models include country- and location-specific predictors, such as site quality indices that may aggregate climate, soil properties and topography effects. Consequently, it is not sensible to compare such models among countries, and it is often impossible to apply models outside the region or country they were developed for. However, there is a clear need for more generically applicable but still locally accurate and climate sensitive simulators at the European scale, which requires the development of models that are applicable across the European continent. The purpose of this study is to develop tree diameter increment models that are applicable at the European scale, but still locally accurate. We compiled and used a dataset of diameter increment observations of over 2.3 million trees from 10 National Forest Inventories in Europe and a set of 99 potential explanatory variables covering forest structure, weather, climate, soil and nutrient deposition. Results: Diameter increment models are presented for 20 species/species groups. Selection of explanatory variables was done using a combination of forward and backward selection methods. The explained variance ranged from 10% to 53% depending on the species. Variables related to forest structure (basal area of the stand and relative size of the tree) contributed most to the explained variance, but environmental variables were important to account for spatial patterns. The type of environmental variables included differed greatly among species. Conclusions: The presented diameter increment models are the first of their kind that are applicable at the European scale. This is an important step towards the development of a new generation of forest development simulators that can be applied at the European scale, but that are sensitive to variations in growing conditions and applicable to a wider range of management systems than before. This allows European scale but detailed analyses concerning topics like CO2 sequestration, wood mobilisation, long term impact of management, etcinfo:eu-repo/semantics/publishedVersio

Probing Chemical Space with Alkaloid-Inspired Libraries

Screening of small molecule libraries is an important aspect of probe and drug discovery science. Numerous authors have suggested that bioactive natural products are attractive starting points for such libraries, due to their structural complexity and sp3-rich character. Here, we describe the construction of a screening library based on representative members of four families of biologically active alkaloids (Stemonaceae, the structurally related cyclindricine and lepadiformine families, lupin, and Amaryllidaceae). In each case, scaffolds were based on structures of the naturally occurring compounds or a close derivative. Scaffold preparation was pursued following the development of appropriate enabling chemical methods. Diversification provided 686 new compounds suitable for screening. The libraries thus prepared had structural characteristics, including sp3 content, comparable to a basis set of representative natural products and were highly rule-of-five compliant