Publikationer från Uppsala Universitet
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Electrocatalytic Hydrogen Generation from Seawater at Neutral pH on a Corrosion-Resistant MoO3/Ti-Felt Electrode
No full textUsing seawater can reduce the dependence on freshwater resources to generate hydrogen by electrocatalytic water splitting. However, the stability and activity of hydrogen evolution reaction (HER) electrocatalysts are highly influenced by the pH of seawater. In this regard, the development of the practical application of HER depends on the creation of highly active non-noble metal electrocatalysts. Here, we propose a technique to optimize the electrocatalytic activity and stability of MoO3 by utilizing titanium felt as the substrate. We show an HER overpotential as low as 83 mV at -10 mA cm-2 in neutral pH conditions. The present results show that electrocatalysts based on earth-abundant metals can perform well in saltwater HER, especially at a near-neutral pH (pH similar to 7). In a neutral saltwater electrolyte (0.55 M PBS + 0.5 M NaCl), this electrocatalyst showed stable performance for 250 h at a constant current density of -100 mA cm-2, indicating its promising application in seawater-based hydrogen generation. Compared with noble metals, this electrocatalyst provides a cost-effective option for economic seawater hydrogen generation, promoting the potential of seawater electrolysis
Tissue-specific and whole-body insulin sensitivity by integrated imaging and hyperinsulinemic euglycemic clamp : A repeatability study in people with T2DM and overweight/obesity
No full textBackground: Assessment of glucose uptake by PET imaging under hyperinsulinemic euglycemic clamp (HEC) is an insightful tool for quantification of insulin resistance, a hallmark of diabetes and an area of interest in drug development. To enable the use of the method in metabolic trials, the repeatability of dynamic whole-body PET/MRI assessments of the tissue-specific glucose uptake and the total body glucose utilisation were investigated. The study included participants with type 2 diabetes mellitus (T2DM) and overweight/obesity, for two repeated examinations in standardised conditions. All participants signed informed consent, and the study plan was approved by the Swedish Ethical Review Authority (#2020-04140). After an overnight fast, HEC was established and a series of [18F]FDG-PET/MRI scans were performed. Total body glucose utilisation (M-value) was calculated for the duration of the scan and the tissue-specific metabolic rates of glucose uptake (MRGlu) were calculated using Patlak model. The repeatability was assessed by calculating the intraclass correlation coefficient (ICC). Results: Repeatability was assessed in per protocol set of 12 participants (PPS, defined by a consistent HEC) and in full analysis set (FAS n = 16). The measured M-values and tissue MRGlu demonstrated varying levels of insulin resistance. M-value ICC was 0.95 (95% CI 0.86-0.99) for PPS, indicating excellent repeatability. Tissue-specific MRGlu repeatability was excellent for skeletal muscle (ICC 0.94), and good to at least fair for SAT, VAT, myocardium, and brain. The FAS had lower, but at least fair repeatability, emphasising the importance of standardisation in metabolic assessments. Conclusion: Dynamic [18F]FDG-PET/MRI provides quantitative information on tissue-specific insulin sensitivity during hyperinsulinemic euglycemic clamp with a reliability comparable to total body glucose utilisation assessment. The method has potential to add value in monitoring and evaluating T2DM treatment effects on glucose uptake and insulin resistance in interventional trials
MODENA project : decay heat prediction using non-destructive assay
No full textThe long-term safety of nuclear waste disposal is a major challenge for countries with nuclear energy programs. Across Europe, (deep) geological repositories have been identified as the best solution for the permanent isolation of spent nuclear fuel (SNF) and high-level radioactive waste. These repositories use multi-barrier systems, including both engineered and geological barriers, to ensure that radioactive materials are isolated from the biosphere for thousands of years. A critical factor for the safety of geological repositories is managing the decay heat, which is the thermal energy produced by radioactive decay in SNFs. Although heat generation decreases over time, significant amounts are emitted for many years after the SNF is removed from a reactor. Improper management of decay heat can compromise the integrity of the repository barriers. Calorimetric measurements can directly measure the decay heat, but they are time-consuming and resource-intensive. To address this, the MODENA project is focused on developing a fast method to estimate decay heat that relies on measurements that will be performed on every SNF before its encapsulation to verify calculated fuel properties to fulfil international safeguards regulations. These measurements are non-destructive gamma and neutron measurements. The model uses only key radionuclides such as Cs-137 and Eu-154, along with neutron emissions, which allows the prediction of decay heat without the need for additional measurements. The strength of the methodology developed in the MODENA project is its flexibility. The model is based on measurement data from radionuclides that are expected to be measurable at encapsulation and can be adapted to well-known measurement instruments, which makes it easy to apply this model in different countries. Improving decay heat prediction could lead to a more efficient use of available resources, ultimately ensuring optimized sustainability of the repository
Genomic Erosion by Structural Variation in Island and Mainland Birds : From short-reads to comparative pangenomics
No full textOnly recently has the field of conservation genomics begun to turn its focus to the interaction of deleterious variation and demographic history in contributing to genomic erosion, especially with regards to the response of larger deleterious mutations beyond single base-pair changes; e.g. structural variants (SVs). By improving protocols to rapidly curate short-read discovered SVs in the House Sparrow (Passer domesticus), I find that even a single lenient curator can substantially reduce the incidence of putative false positive SVs. High-confidence SVs recapture population structure inferred with single nucleotide polymorphisms (SNPs), but those rejected by quality filtering and/or manual curation do not. Next, I apply this protocol to examine the role of distinct demographic histories in the accumulation of deleterious SVs relative to SNPs by manually curating > 35,000 SVs in 12 island and continental populations of the Rock / Willow Ptarmigan superspecies (Lagopus spp.) from across the North Atlantic and Arctic Ocean. Both diversity ratios for non-neutral to neutral SNPs and SVs suggest that slightly deleterious SVs (<30 Kb) detectable with short-reads accumulate nearly-neutrally as a function of decreasing effective population size (Ne). Many pre-existing reference assemblies and linkage maps lack the full set of chromosomes, particularly for e.g. avian and reptilian genomes partially comprised of microchromosomes. I assemble a highly contiguous, chromosomally-complete reference genome for the House Sparrow (Passer domesticus; Passeridae) enriched for previously unresolved repeat-rich regions, such as segmental duplications (SDs) covering 11% of the autosomal genome. By leveraging this new reference and 26 contig-level assemblies, I apply a comparative pangenomic approach to contrast relative densities of distinct variant classes between two deeply diverged human-commensal songbirds (Passeriformes); the House Sparrow and House Finch (Haemorhous mexicanus; Fringillidae). Microchromosomes were enriched for highly and mildly deleterious SVs in both species, likely reflecting a unique genomic background such as higher gene densities, recombination rates, segmental duplication and satellite densities conducive to SV formation. Finally, I assess differences in genetic load imposed by pangenome-inferred SVs versus SNPs in two parallel founder events ca. 1940, with distinct outcomes in sparrows versus finches. Notwithstanding the recent timing of the bottlenecks, genetic drift and inbreeding may inform consistent shifts in relative proportions of SV-associated realised load and masked load in post-founder populations. Underscoring their promise for the field of conservation genomics, chromosomally-complete reference assemblies and population pangenomes reveal that deleterious SVs are overrepresented on avian microchromosomes and may contribute disproportionately to genomic erosion.
Development of a Heuristic Machine Analogy Method for Model Simplification With an Application to a Large-Scale Model of Gi/Gs Signaling
No full textModel simplification is a process to simplify large-scale mathematical models to enable easy applications such as simulation and parameter estimation. A novel heuristic machine analogy method of model simplification was developed and applied to a motivating example of a model for cAMP signaling switch induced by Gi/Gs pathway competition for the CB1 receptor (consisting of 31 species and 76 parameters) to enable its use in estimation. The method first acquired an understanding of the mechanism by full model simulation, and then the mechanism was abstracted to a machine analogy. The machine analogy included signal start, signal mode selector, signal size regulator, and final effector, representing functions of different parts of the full model. The simplified minimal model (consisting of 11 species and 13 estimated parameters) was used for parameter estimation for Gi/Gs signaling of six CB1 agonists. The results of the minimal model suggested that six CB1 agonists have similar ratios of Gi/Gs activation, indicating Gi/Gs preference was more of a system effect rather than a ligand-specific effect. In conclusion, the novel machine analogy method can be used to heuristically simplify a larger-scale model while maintaining the important mechanisms. In the example here, the full Gi/Gs model of CB1 was successfully simplified, and the results indicated Gi/Gs preference is a system-dependent effect
Patientdelaktighet i teammöten för personer med kognitiva kommunikationsnedsättningar (CCD) efter förvärvad hjärnskada : en kvalitativ studie
No full textCognitive communication disorder (CCD) is a communication disorder caused by underlying cognitive impairment, and is highly prevalent after acquired brain injury. Communication challenges in this population include initiating or paying attention to a conversation, follow instructions and remembering information. Patient participation is a key aspect of person-centered care. In rehabilitation settings, team meetings where the patient, rehabilitation team and significant others gather to discuss individual goals, progress and planning, are an important tool to achieve patient participation. However, such meetings may represent a considerable challenge for a person with CCD. This study aimed to explore the experiences of participation in team meetings among individuals with CCD. Semi-structured interviews were conducted with a purposive sample of 13 participants with CCD (8 women and 5 men; mean age: 44) undergoing their rehabilitation at an outpatient clinic. Data were transcribed verbatim, and analyzed using Qualitative content analysis. The analysis yielded four categories; a) Defining patient participation for oneself, b) Overload disrupts communication c) Factors facilitating communication, and d) Making the journey easier- recommendations for the future. Results indicate a mismatch between participants’ communication abilities and the complexity and cognitive load at the meeting, particularly early in the rehabilitation process. An overarching theme was identified, capturing that patient participation is not present from start, but can be developed over time as insights, skills, and adaptations gradually evolve during the rehabilitation process for both the person with CCD and the team members. Merely attending a meeting does not ensure patient participation. Participation is an evolving process. Understanding and addressing the individual communication challenges faced by individuals with CCD are key factors in improving patient participation in team meetings. The results offer insights about how team meetings could be arranged to meet the needs of individuals with CCD
Additive manufacturing of drugs in Sweden : Barriers and facilitators for implementation of additive manufacturing to produce drugs
No full textThis study applies the Consolidated Framework for Implementation Research (CFIR) to explore factors perceived to influence the implementation of 3D printing for compounding medicines in Swedish healthcare, how they affect the implementation process, and what potential tensions or synergies exist among these factors. Using a qualitative approach, thirteen semi-structured interviews was conducted with diverse stakeholders. These stakeholders are connected to technology development, healthcare practice, and regulatory policy. The interviews were thematically analyzed using CFIR constructs. Participants acknowledged 3D printing’s promise for personalized medicine but also identified numerous barriers. These barriers included: regulatory uncertainty, economic and reimbursement challenges, technical and workflow complexity, and coordination gaps. In contrast to these barriers, key facilitators were seen as clear strategic planning, pilot testing (trialability), and shared learning to build confidence in adoption and implementation. Synergies were observed when the innovation’s advantages aligned with a supportive context, whereas tensions arose when regulatory demands, misaligned incentives, or lack of organizational readiness hindered implementation. Successful implementation of 3D printing in drug compounding requires more than technical efficiency; it demands an enabling environment that addresses multi-level barriers and leverages facilitators. This study herein offers insights to help healthcare organizations, pharmacies and policymakers plan and support the integration of 3D printing technologies, bridging the gap between laboratory innovation and clinical practice
Unsupervised Microfluidic Chip Anomaly Detection in Image Data : Leveraging Methods Based on Machine Learning Features: PatchCore, PaDim
No full textIn industrial productions, anomaly detection has always been important to maintain quality consistency. Medical industrial production requires rigid production standards, as each item serves diagnostic purposes for patients. Anomalous products slipped into passed ones, can be detrimental. Quality assurance which applies at the end of production is meant to detect and discard anomalous products. As production processes are not fuly deterministic, production variants can be decided pass or fail under different circumstances. Subtle defects, can be overlooked, while new unprecedented anomalies remain undiscovered. Based on these observations, we apply unsupervised machine learning techniques to combat this tricky and challenging issue. This work leverages the state of the art unsupervised machine learning methods including PaDim, PatchCore, and optimizes these methods under real-time industrial production settings. Anomaly scores predicted by both models are evaluated against the image labels, where PatchCore achieved 0.7691 in AUCROC and PaDim achieved 0.5734. Further, we developed a detailed rule sorting mechanism on PatchCore's heatmap predictions, and managed to sort out 21% chips(401 chips) from the full testing set of 1904 images. The sorting mechanism on this subset of chips achieved 88.78% accuracy(159 true positives, 197 true negatives, 42 false positives and 3 false negatives). Processing 21% of the manual examination workload in only 7 seconds per image, the proposed solution accurately detects subtle defects and has strong potential to boost efficiency
A FHE-based Outsourcing Service Framework with Circuit Privacy and Conditional Control
No full textThis thesis presents a framework for outsourcing computations while hiding data using Fully homomorphic encryption, and hiding the Circuit, with the use of matrix obusification, combined with a focus on exploring methods for circuit privacy and conditional control specifically within the CKKS encryption scheme. The matrix-based operation obfuscation technique enables addition and multiplication to be expressed as indistinguishable matrix products, offering operator privacy in isolation. This thesis also constructs a polynomial-based comparison mechanism using rational function approximations of the sign function, enabling encrypted conditional control logic. Although the framework does not fully achieve combined circuit and data privacy in a unified execution path, it demonstrates the feasibility of independently implementing these privacy layers. An encrypted machine learning example, AND gate approximation with gradient descent, is provided to illustrate practical application of the techniques.
Structural uncertainty in mapping Euro-Atlantic atmospheric rivers obscures understanding of associated meteorological extremes
No full textUnderstanding uncertainties in meteorological extremes induced by Atmospheric river (AR) structural uncertainties can help to develop effective strategies to mitigate AR induced hazards and adapt to changing climate conditions. As a first step, this study examines the statistical relationship between AR structural uncertainty and the characterisation of associated meteorological extremes over the Euro-Atlantic region, using long-term historical data from ECMWF Reanalysis v5 (ERA5) during 1940 to 2022. Leveraging the Bayesian AR detection (BARD), a form of statistical machine learning model in the Toolkit for Extreme Climate Analysis (TECA), we examine the impact of structural uncertainties in AR dimensions on daily precipitation (wet), wind speeds (windy), and temperature (warm/cold) anomalies and extremes over Europe, the UK and Scandinavia. A large spread in the aggregated detected AR probabilities (ARP) spatially and temporally led to differences in ARs’ attributes, such as frequency, integrated water vapour transport (IVT; intensity), and their impact on weather parameters, anomalies and extremes at selected probability thresholds across space and time. The magnitude of AR impacts and associated meteorological phenomena over land varies based on the chosen deciles (dividing ARP into ten equal parts with a 0.1 increase) of ARPs, along with the default threshold from the model (ARP≥0.67). AR intensities and landfalling area are increasing over the study period, irrespective of the selected ARP. The effects of AR structural uncertainties are more prominent over inland Europe and Scandinavia than over coastal Europe and the UK. The physical and meteorological phenomena underlying these results require further exploration to understand the impact of landfalling ARs on land