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Abstract: Introduction: Primidone and propranolol are primary treatments for essential tremor, however the exact mechanisms underlying their efficacy are not fully elucidated. Understanding how these medications alleviate tremor may guide the development of additional pharmacologic treatments. Our prospective observational study employed transcranial magnetic stimulation (TMS) to explore mechanisms of primidone and propranolol effects in essential tremor. Eyeblink classical conditioning (EBCC) was tested as a potential predictor of treatment response. Methods: Patients with essential tremor underwent two evaluations: prior to commencing primidone or propranolol and following a minimum of three months of treatment. Tremor severity was assessed using accelerometry and clinically. TMS was employed to study changes in corticospinal excitability - resting and active motor thresholds, resting and active input/output curves and intracortical excitability - cortical silent period (CSP), short interval intracortical inhibition intensity curve (SICI), long interval intracortical inhibition (LICI), intracortical facilitation (ICF), and short afferent inhibition (SAI). EBCC, a marker of cerebellar function, was studied at baseline. Results: Of the 54 enrolled patients (28 primidone, 26 propranolol), 35 completed both visits. Primidone effect on decreasing hand tremor was associated with decreased corticospinal excitability, prolongation of CSP, increased LICI, increased SAI and decreased SICI. Propranolol effect on hand tremor was associated with decreased corticospinal excitability and increased SAI. Better EBCC at baseline predicted better response to primidone. Conclusions: Primidone exerts its therapeutic effects by blocking voltage-gated sodium channels and by modulating GABA-A and GABA-B intracortical circuits. Propranolol's central effects are likely mediated via noradrenergic modulation of GABA outflow
Keywords: essential tremor, primidone and propranolol treatments
Published in DiRROS: 03.12.2025; Views: 79; Downloads: 47
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Abstract: Bike commuters are regularly exposed to environmental stressors that impact their health and well-being. The Urban Cycling Lab in Ljubljana, developed within an Urban Living Lab and citizen science framework, engaged stakeholders in assessing exposure to particulate matter and noise, and in co-creating strategies to reduce it. This citizen science intervention combined sensor-enhanced ICT tools with behaviour change theory to assess both environmental and behavioural aspects of exposure. Exposure assessment included low-cost personal sensors as well as chemical analysis in biological samples to evaluate environmental exposure, while biochemical analysis of biological samples aimed to evaluate potential biological effects of exposure. Participants collected data using portable sensors and accessed real-time exposure comparisons via the Route Exposure Comparator web app. Biological samples (peripheral blood and spot urine) were collected from each participant at the end of data collection period. Data on sociodemographic characteristics, commuting habits, and environmental health literacy were collected via questionnaires. Ethnographic methods captured participants’ perceptions, route choices, and the intervention’s influence on commuting behaviour. This paper presents the methodology used to implement this intervention and provides a transferable model for participatory environmental exposure assessment. 1. Designed and implemented a citizen science intervention to assess cyclists’ exposure to air pollution and noise using sensor-enhanced ICT tools. 2. Promoted environmentally informed route choices through behaviour change strategies and digital feedback. 3. Applied survey and ethnographic methods to explore commuting behaviours and intervention impact.
Keywords: personal sensors, environmental exposure assessment
Published in DiRROS: 03.12.2025; Views: 107; Downloads: 49
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Abstract: Genetic markers can assist in the identification of the stock origin in different organisms. Comparative studies of forest tree provenances have demonstrated that forest tree populations differ in performance across environments and at multiple geographic levels: populations nested within regions nested within gene pools. These levels are critical for conservation and sustainable use of genetic resources: regions of provenance are key units for seed marketing, while populations guide reproductive material collection under most seed regulations. Despite their potential, genetic methods have rarely been applied to identify forest tree origins due to methodological (sufficient number of highly discriminatory markers) and practical (construction of a baseline composed of a representative selection of samples) challenges. In our study, we analyzed a genomic dataset comprising 10,185 SNPs from 1579 samples of Pinus pinaster, a species with strong population structure, across 86 populations, 45 regions of provenance, and 10 gene pools, to discriminate among these hierarchical levels and assign individuals to them. We used two software packages to evaluate the reliability of our baseline dataset (i.e., reference data) for genetic discrimination and assignment: RUBIAS, which performs genetic stock identification and associated tasks, and assignPOP, implementing a supervised machine-learning genetic-assignment framework. Using numerical validation analyses, we assessed their suitability and limitations for origin inference at each geographical level. Our results indicate that origin assignment is reliable in P. pinaster at the gene pool and region of provenance levels, but less so at the population level, provided that the 10 K SNP markers and a comprehensive genetic baseline are used. Incomplete baselines may result in wrong assignments at any hierarchical level, irrespective of sampling intensity for sampled candidate origins. We provide an extensive and publicly available baseline for P. pinaster, offering a useful tool for the management of forest genetic resources of this economically and ecologically important tree species.
Keywords: gene pool, genetic assignment, maritime pine, origin identification, region of provenance, SNP marker
Published in DiRROS: 03.12.2025; Views: 107; Downloads: 55
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Abstract: Participatory approaches are becoming paramount to harness the relationship between researchers, government, industry, and civil society to inform programs and policies. However, variability in implementation and limited standardized reporting hinder the systematic evaluation of their effectiveness. This study characterizes participatory methodologies in urban health research and proposes a framework for evaluating and reporting such approaches. Using an explanatory sequential design, this study evaluated 20 participatory pilot studies from the Urban Health Cluster (Horizon 2020 European Commission Programme), combining survey data and semi-structured interviews with project leads. The analysis identified four primary purposes for participatory methods: to assess health-environment correlations; raise awareness; co-create interventions; and assess health-related effects. Case studies exemplify each of these purposes. Findings informed a “purpose framework” nested within a theory-of-change model, which clarifies the rationale behind participatory approaches and maps their processes and intended impacts. The framework includes indicators for purpose, stakeholder involvement, participation mechanisms, facilitators, challenges, expected outcomes, and evaluation strategies, reported across all 20 projects. Public authorities (90 %) and civil society (85 %) are the most frequently engaged stakeholders, typically involved during project identification and deployment. Engagement was facilitated by shared motivation to address local needs, while long-term commitment posed challenges. Our results highlight the limited use of theory-of-change models in current practice and the value of structured frameworks for enhancing the reproducibility and transformative impact of participatory urban health research. The proposed framework can help align participatory methods with a theory of change and foster more effective urban health transformations.
Keywords: participatory research, public engagement, standardized reporting, urban health
Published in DiRROS: 03.12.2025; Views: 102; Downloads: 49
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Abstract: Mutual information between particle positions before and after mixing provides a universal assumption-free measure of mixing efficiency at low Reynolds number that accounts for the kinematic reversibility of the Stokes equation. For a generic planar shear flow with time-dependent shear rate, we derive a compact expression for the mutual information as a nonlinear functional of the shearing protocol and solve the associated extremization problem exactly to determine the optimal control under both linear and nonlinear constraints, specifically total shear and total dissipation per unit volume. Remarkably, optimal protocols turn out to be universal and time-reversal symmetric in both cases. Our results establish a minimum energetic cost of erasing information in a broad class of nonequilibrium drift-diffusive systems.
Keywords: information thermodynamics, mixing enhancement, nonequilibrium statistical mechanics, shear flows
Published in DiRROS: 03.12.2025; Views: 107; Downloads: 46
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