Climate change integration in the multilevel governance of Italy and Austria: the key role of vertical and horizontal coordination

Climate change represents a global problem and a challenge with manifold responses, which requires coordinated action at different levels. In this context, subnational governments play a significant – yet still understudied – role in the fight against climate change; they exercise powers in policy sectors that may have an impact on climate mitigation and adaptation objectives, such as transport, energy and water, and spatial planning. The research project “Climate change integration in the multilevel governance of Italy and Austria” (Research Südtirol/Alto Adige 2019) compares the Italian and Austrian legal systems with a particular focus on how climate change policy integration (CPI) is realized in the Autonomous Province of Bolzano and Trento in Italy and Länder Tyrol and Vorarlberg in Austria. The project hypothesizes that five factors play a particularly significant role in realizing CPI, namely coordination, participation, information, leadership and funding. In this contribution, we will focus on the dimension of coordination. Also in light of the different decentralization arrangements in Italy and Austria, coordination in the study areas analysed unfolds differently concerning both the type and the employed instruments of coordination, although certain common tendencies can also be observed. Drawing from the results of the empirical research (interviews) conducted in the study areas, this article argues that coordination is affected by the federal vs regional organization of the State only when it comes to vertical coordination. Furthermore, since climate change in not a unitary policy field, improving horizontal coordination among policy fields seems to be more crucial than improving vertical coordination

First Responders to Hyperosmotic Stress in Murine Astrocytes: Connexin 43 Gap Junctions Are Subject to an Immediate Ultrastructural Reorganization

In a short-term model of hyperosmotic stress, primary murine astrocytes were stimulated with a hyperosmolar sucrose solution for five minutes. Astrocytic gap junctions, which are mainly composed of Connexin (Cx) 43, displayed immediate ultrastructural changes, demonstrated by freeze– fracture replica immunogold labeling: their area, perimeter, and distance of intramembrane particles increased, whereas particle numbers per area decreased. Ultrastructural changes were, however, not accompanied by changes in Cx43 mRNA expression. In contrast, transcription of the gap junction regulator zonula occludens (ZO) protein 1 significantly increased, whereas its protein expression was unaffected. Phosphorylation of Serine (S) 368 of the Cx43 C–terminus has previously been associated with gap junction disassembly and reduction in gap junction communication. Hyperosmolar sucrose treatment led to enhanced phosphorylation of Cx43S368 and was accompanied by inhibition of gap junctional intercellular communication, demonstrated by a scrape loading-dye transfer assay. Taken together, Cx43 gap junctions are fast reacting elements in response to hyperosmolar challenges and can therefore be considered as one of the first responders to hyperosmolarity. In this process, phosphorylation of Cx43S368 was associated with disassembly of gap junctions and inhibition of their function. Thus, modulation of the gap junction assembly might represent a target in the treatment of brain edema or trauma

Modelagem no GeoGebra e o desenvolvimento do pensamento geométrico no ensino fundamental

Uma modelagem geométrica é uma representação, na linguagem da matemática, de um mecanismo no qual as formas geométricas estão em movimento. Com os recursos do software GeoGebra podemos implementar tal tipo de modelagem. Esta é uma atividade interessante, pois exige um domínio de procedimentos de construção que podem ajudar no desenvolvimento de habilidades e atitudes características do pensamento geométrico: conjeturar, relacionar, refinar suposições. É através da apresentação de um experimento didático desenvolvido com alunos do oitavo ano do ensino fundamental, que vamos ilustrar o potencial deste tipo de atividade

Recording of Chronic Diseases and Adverse Obstetric Outcomes during Hospitalizations for a Delivery in the National Swiss Hospital Medical Statistics Dataset between 2012 and 2018: An Observational Cross-Sectional Study.

The prevalence of chronic diseases during pregnancy and adverse maternal obstetric outcomes in Switzerland has been insufficiently studied. Data sources, which reliably capture these events, are scarce. We conducted a nationwide observational cross-sectional study (2012-2018) using data from the Swiss Hospital Medical Statistics (MS) dataset. To quantify the recording of chronic diseases and adverse maternal obstetric outcomes during delivery in hospitals or birthing centers (delivery hospitalization), we identified women who delivered a singleton live-born infant. We quantified the prevalence of 23 maternal chronic diseases (ICD-10-GM) and compared results to a nationwide Danish registry study. We further quantified the prevalence of adverse maternal obstetric outcomes (ICD-10-GM/CHOP) during the delivery hospitalization and compared the results to existing literature from Western Europe. We identified 577,220 delivery hospitalizations, of which 4.99% had a record for ≥1 diagnosis of a chronic disease (versus 15.49% in Denmark). Moreover, 13 of 23 chronic diseases seemed to be substantially under-recorded (8 of those were >10-fold more frequent in the Danish study). The prevalence of three of the chronic diseases was similar in the two studies. The prevalence of adverse maternal obstetric outcomes was comparable to other European countries. Our results suggest that chronic diseases are under-recorded during delivery hospitalizations in the MS dataset, which may be due to specific coding guidelines and aspects regarding whether a disease generates billable effort for a hospital. Adverse maternal obstetric outcomes seemed to be more completely captured

Prescription Trends in Hospice Care: A Longitudinal Retrospective and Descriptive Medication Analysis.

BACKGROUND In hospice and palliative care, drug therapy is essential for symptom control. However, drug regimens are complex and prone to drug-related problems. Drug regimens must be simplified to improve quality of life and reduce risks associated with drug-related problems, particularly at end-of-life. To support clinical guidance towards a safe and effective drug therapy in hospice care, it is important to understand prescription trends. OBJECTIVES To explore prescription trends and describe changes to drug regimens in inpatient hospice care. DESIGN We performed a retrospective longitudinal and descriptive analysis of prescriptions for regular and as-needed (PRN) medication at three timepoints in deceased patients of one Swiss hospice. SETTING/SUBJECTS Prescription records of all patients ( 18 years) with an inpatient stay of three days and longer (admission and time of death in 2020) were considered eligible for inclusion. RESULTS Prescription records of 58 inpatients (average age 71.7 ± 12.8 [37-95] years) were analyzed. The medication analysis showed that polypharmacy prevalence decreased from 74.1% at admission to 13.8% on the day of death. For regular medication, overall numbers of prescriptions decreased over the patient stay while PRN medication decreased after the first consultation by the attending physician and increased slightly towards death. CONCLUSIONS Prescription records at admission revealed high initial rates of polypharmacy that were reduced steadily until time of death. These findings emphasize the importance of deprescribing at end-of-life and suggest pursuing further research on the contribution of clinical guidance towards optimizing drug therapy and deprescribing in inpatient hospice care

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

LocTree3 prediction of localization

The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria and in three for archaea. The method outputs a score that reflects the reliability of each prediction. LocTree2 has performed on par with or better than any other state-of-the-art method. Here, we report the availability of LocTree3 as a public web server. The server includes the machine learning-based LocTree2 and improves over it through the addition of homology-based inference. Assessed on sequence-unique data, LocTree3 reached an 18-state accuracy Q18 = 80 ± 3% for eukaryotes and a six-state accuracy Q6 = 89 ± 4% for bacteria. The server accepts submissions ranging from single protein sequences to entire proteomes. Response time of the unloaded server is about 90 s for a 300-residue eukaryotic protein and a few hours for an entire eukaryotic proteome not considering the generation of the alignments. For over 1000 entirely sequenced organisms, the predictions are directly available as downloads. The web server is available at http://www.rostlab.org/services/loctree3