Logotyp: till Uppsala universitets webbplats

A 1056-membered fragment library has been screened against SMYD3 using a novel multiplexed experimental design implemented in a grating coupled interferometry (GCI)-based biosensor. SMYD3 is a prospective target for anticancer drugs and the focus has initially been on discovery of inhibitors of its lysine methyl transferase activity. However, it has multiple protein interaction partners and several potential roles in carcinogenesis. It therefore remains unclear what mode of action ligands targeting the protein should have. Our goal was therefore to identify new ligands and discriminate hits that interact with the active site and those that interact with other sites. In addition, we were interested in selecting hits based on kinetic features rather than affinity. Screening was done in parallel against SMYD3 alone or SMYD3 with the active site blocked by a tight binding inhibitor. Hit selection was primarily based on dissociation rates. In total, 20 fragments were selected as hits, of which half apparently targeted the active site and half targeted other sites. Twelve of the hits were selected for structural analysis using X-ray crystallography in order to identify binding sites and modes of binding. Four of the hits were successfully identified in crystal structures with SMYD3; the others did not show any electron densities for ligands in the crystals. Although it might be possible to optimize the crystallography approach for a better success rate, it was clear that the sensitivity and time resolution of the biosensor assay was exceptional and enabled kinetic rate constants to be estimated for fragments. Fragments are typically considered to interact too rapidly for such quantification to be possible. This approach consequently represents a paradigm shift. In addition, the multiplexed approach allows ligands targeting different sites to be rationally selected already in the fragment library screening stage.

Background and objectives: Spatially resolved techniques for exploring the molecular landscape of tissue samples, such as spatial transcriptomics, often result in millions of data points and images too large to view on a regular desktop computer, limiting the possibilities in visual interactive data exploration. TissUUmaps is a free, open-source browser-based tool for GPU-accelerated visualization and interactive exploration of 107+ data points overlaying tissue samples.

Methods: Herein we describe how TissUUmaps 3 provides instant multiresolution image viewing and can be customized, shared, and also integrated into Jupyter Notebooks. We introduce new modules where users can visualize markers and regions, explore spatial statistics, perform quantitative analyses of tissue morphology, and assess the quality of decoding in situ transcriptomics data.

Results: We show that thanks to targeted optimizations the time and cost associated with interactive data exploration were reduced, enabling TissUUmaps 3 to handle the scale of today's spatial transcriptomics methods.

Conclusion: TissUUmaps 3 provides significantly improved performance for large multiplex datasets as compared to previous versions. We envision TissUUmaps to contribute to broader dissemination and flexible sharing of largescale spatial omics data.

The locations of different mRNA molecules can be revealed by multiplexed in situ RNA detection. By assigning detected mRNA molecules to individual cells, it is possible to identify many different cell types in parallel. This in turn enables investigation of the spatial cellular architecture in tissue, which is crucial for furthering our understanding of biological processes and diseases. However, cell typing typically depends on the segmentation of cell nuclei, which is often done based on images of a DNA stain, such as DAPI. Limiting cell definition to a nuclear stain makes it fundamentally difficult to determine accurate cell borders, and thereby also difficult to assign mRNA molecules to the correct cell. As such, we have developed a computational tool that segments cells solely based on the local composition of mRNA molecules. First, a small neural network is trained to compute attractive and repulsive edges between pairs of mRNA molecules. The signed graph is then partitioned by a mutex watershed into components corresponding to different cells. We evaluated our method on two publicly available datasets and compared it against the current state-of-the-art and older baselines. We conclude that combining neural networks with combinatorial optimization is a promising approach for cell segmentation of in situ transcriptomics data. The tool is open-source and publicly available for use at https://github.com/wahlby-lab/IS3G.

Imaging-based spatial transcriptomics techniques generate image data that, once processed, results in a set of spatial points with categorical labels for different mRNA species. A crucial part of analyzing downstream data involves the analysis of these point patterns. Here, biologically interesting patterns can be explored at different spatial scales. Molecular patterns on a cellular level would correspond to cell types, whereas patterns on a millimeter scale would correspond to tissue-level structures. Often, clustering methods are employed to identify and segment regions with distinct point-patterns. Traditional clustering techniques for such data are constrained by reliance on complementary data or extensive machine learning, limiting their applicability to tasks on a particular scale. This paper introduces 'Points2Regions', a practical tool for clustering spatial points with categorical labels. Its flexible and computationally efficient clustering approach enables pattern discovery across multiple scales, making it a powerful tool for exploratory analysis. Points2Regions has demonstrated efficient performance in various datasets, adeptly defining biologically relevant regions similar to those found by scale-specific methods. As a Python package integrated into TissUUmaps and a Napari plugin, it offers interactive clustering and visualization, significantly enhancing user experience in data exploration. In essence, Points2Regions presents a user-friendly and simple tool for exploratory analysis of spatial points with categorical labels. 

Interpreting tissue architecture plays an important role in gaining a better understanding of healthy tissue development and disease. Novel molecular detection and imaging techniques make it possible to locate many different types of objects, such as cells and/or mRNAs, and map their location across the tissue space. In this review, we present several methods that provide quantification and statistical verification of observed patterns in the tissue architecture. We categorize these methods into three main groups: Spatial statistics on a single type of object, two types of objects, and multiple types of objects. We discuss the methods in relation to four hypotheses regarding the methods' capability to distinguish random and non-random distributions of objects across a tissue sample, and present a number of openly available tools where these methods are provided. We also discuss other spatial statistics methods compatible with other types of input data.

Research on healthy aging commonly concerns problems related to loneliness and food intake. These are not independent aspects of health since eating, beyond its biological necessity, is a central part of social life. This scoping review aimed to map scientific articles on eating alone or together among community-living older people, and to identify relevant research gaps. Four databases were searched, 989 articles were identified and 98 fulfilled the inclusion criteria. In the first theme, eating alone or together are treated as central topics of interest, isolated from adjoining, broader concepts such as social participation. In the second, eating alone or together are one aspect of the findings, e.g., one of several risk factors for malnutrition. Findings confirm the significance of commensality in older peoples’ life. We recommend future research designs allowing identification of causal relationships, using refined ways of measuring meals alone or together, and qualitative methods adding complexity.

The practice of eating together, commensality, is often considered as something positive in later life, particularly regarding peoples' nutritional status and psychosocial well-being. Eating alone, in contrast, is treated as a risk factor, although literature indicates that it is not necessarily something negative. Still, analyses that specifically target older peoples' varied experiences and notions of eating alone are scarce. This study has explored perceptions and experiences of eating alone among older people in Sweden, a country considered highly individualistic, yet with relatively low levels of loneliness in the older population. Semi-structured interviews were conducted with 20 community-living and retired Swedes, 70-90 years of age. A thematic analysis identified three themes: i) 'Eating alone as a manifestation of loss'; ii) 'Eating alone as an everyday routine'; and iii) 'Eating alone as independence and contentment'. General perceptions of eating alone were often related to the current living situation (e.g., cohabiting or single-living). One key finding was an identified tension between the idea of eating alone as something problematic among those living and eating with a partner and the practical experience of an uncomplicated routine among those living and eating alone. Eating together is discussed as a possible social need for many, but perhaps not for all. Some can feel content with eating alone or even enjoy it. Future studies should approach potential disadvantages of eating alone among older people as an open empirical question that is likely to depend on both the individual and the cultural context.

Background

Eating is fundamental not only to survival and health, but also to how humans organise their social lives. Eating together with others is often seen as the healthy ideal, while eating alone is highlighted as a risk factor for negative health outcomes, especially among older adults. This paper, therefore, investigates the relationship between the frequency and subjective experience of eating alone and food-related outcomes among 70- to 75-year-olds in Sweden.

Methods

A survey was distributed to a nationally representative random sample of 1500 community-living in Sweden, aged 70–75 years. Two different constructs of eating alone (objective and subjective) were measured, along with the following food-related outcomes: a food index, intake of food groups, consumption of ready-made meals, number of main meals per day, and body mass index (BMI).

Results

In total, 695 respondents were included in the final sample. A quarter of the respondents were categorised as eating alone, of which a small proportion reported that doing so bothered them. There were no associations between eating alone and food index scores, BMI, or intake frequencies of fruits and berries, or fish and shellfish. However, people eating alone were less likely to report eating three meals per day (OR: 0.53, CI: 0.37–0.76, p = 0.006), less likely to report higher intake frequencies of vegetables and snacks, sugary foods, and sweet drinks (adjusted OR: 0.68, CI: 0.48–0.95, p = 0.023 resp. OR: 0.59, CI: 0.43–0.81, p = 0.001), and more likely to report higher intake frequencies of ready-made meals (adjusted OR: 3.71, CI: 2.02–6.84, p < 0.001) compared to those eating together with others. The subjective experience of eating alone did not have an impact on food-related outcomes.

Conclusion

Eating alone or with others played a role in participants’ food intake, and seemed to influence aspects of the organisation of everyday eating routines rather than overall dietary healthiness or weight status. Our findings add to the previous body of research on commensality, eating alone, and health among the older population, providing insights into the development of future health policies and research.

Objectives: To investigate whether eating alone (measured objectively and subjectively) and engagement in social activities are associated with loneliness and self-rated health, independently or through interaction effects among community-living adults in Sweden. Methods: Data from a national cross-sectional survey of 695 adults aged 70 to 75 years were used to assess both the subjective experience and frequency of eating alone and engagement in social activities and their associations with loneliness, and self-rated health using logistic regression and interaction analysis. Results: Eating alone and being bothered by eating alone were both associated with loneliness, but no interaction between the two was identified, meaning that the association between eating alone and loneliness was not dependent on whether eating alone was perceived as bothersome or not. Lower engagement in social activities was also associated with loneliness. However, no interaction effect was identified between eating alone and social activities. Lower engagement in social activities was associated with lower self-rated health, but no associations between eating alone or being bothered by eating alone and self-rated health were observed. Discussion: In this sample, eating alone was associated with loneliness but not lower self-rated health. The proportion of loneliness was high in groups that were bothered by eating alone, indicating specific subgroups for whom eating alone can be problematic. More research is needed to understand the issue of eating alone – and who it affects. This will allow effective policies to be developed and implemented among groups vulnerable to loneliness and poor health.

PURPOSE: To characterise the pharmacokinetics and associated variability of cefotaxime in adult intensive care unit (ICU) patients and to assess the impact of patient covariates.

METHODS: This work was based on data from cefotaxime-treated patients included in the ACCIS (Antibiotic Concentrations in Critical Ill ICU Patients in Sweden) study. Clinical data from 51 patients at seven different ICUs in Sweden, given cefotaxime (1000-3000 mg given 2-6 times daily), were collected from the first day of treatment for up to three consecutive days. In total, 263 cefotaxime samples were included in the population pharmacokinetic analysis.

RESULTS: A two-compartment model with linear elimination, proportional residual error and inter-individual variability (IIV) on clearance and central volume of distribution best described the data. The typical individual was 64 years, with body weight at ICU admission of 92 kg and estimated creatinine clearance of 94 mL/min. The resulting typical value of clearance was 11.1 L/h, central volume of distribution 5.1 L, peripheral volume of distribution 18.2 L and inter-compartmental clearance 14.5 L/h. The estimated creatinine clearance proved to be a significant covariate on clearance (p < 0.001), reducing IIV from 68 to 49%.

CONCLUSION: A population pharmacokinetic model was developed to describe cefotaxime pharmacokinetics and associated variability in adult ICU patients. The estimated creatinine clearance partly explained the IIV in cefotaxime clearance. However, the remaining unexplained IIV is high and suggests a need for dose individualisation using therapeutic drug monitoring where the developed model, after evaluation of predictive performance, may provide support.

Objectives: To illustrate the impact of errors in documented dose administration time on therapeutic drug monitoring (TDM)-based target attainment evaluation for vancomycin and meropenem, and to explore the influence of drug and patient characteristics, and TDM sampling strategies.

Methods: Bedside observations of errors in documented dose administration times were collected. Population pharmacokinetic simulations were performed for vancomycin and meropenem, evaluating different one- and two-sampling strategies for populations with estimated creatinine clearance (CLcr) of 30, 80 or 130 mL/min. The impact of errors was evaluated as the proportion of individuals incorrectly considered to have reached the target.

Results: Of 143 observed dose administrations, 97% of doses were given within ±30 min of the documented time. For vancomycin, a +30 min error was predicted to result in a 0.1-3.9 percentage point increase of cases incorrectly evaluated as reaching area under the concentration-time curve during a 24-hour period (AUC₂₄)/minimum inhibitory concentration (MIC) >400, with the largest increase for patients with augmented renal clearance and peak and trough sampling. For meropenem, a +30 min error resulted in a 1.3-6.4 and 0-20 percentage point increase of cases incorrectly evaluated as reaching 100% T_>MIC, and 50% T_>MIC, respectively. Overall, mid-dose and trough sampling was most favourable for both antibiotics.

Conclusions: For vancomycin, simulations indicate that TDM-based target attainment evaluation is robust with respect to the observed errors in dose administration time of ±30 min; however, the errors had a potentially clinically important impact in patients with augmented renal clearance. For meropenem, extra measures to promote correct documentation are warranted when using TDM, as the impact of errors was evident even in patients with normal renal function.

BACKGROUND: Current guidelines recommend dosing vancomycin based on the area under the concentration time curve (AUC) to maximise efficacy and minimise the risk of nephrotoxicity. The preferred approach to AUC-guided therapy is to apply model-informed precision dosing (MIPD). However, the adoption in clinical practice has been slow.

AIM: We aimed to develop an intervention, including a standardised MIPD workflow and an implementation plan for vancomycin AUC-guided dosing, in a Swedish tertiary hospital.

METHOD: The intervention was developed in a framework-guided process. The design phase included stakeholder feedback (nurses, pharmacists, physicians), local data collection and feasibility testing of intervention components with parallel consideration of implementation aspects. The hypothesised relationships between the different components, implementation strategies and the mechanism of action resulting in expected outcomes were represented by a logic model.

RESULTS: The final intervention consisted of a workflow for MIPD, with defined roles and responsibilities, as well as processes for data and information transfer. Details were provided in supportive documents; an instruction on therapeutic drug monitoring (TDM) sampling and documentation for nurses, and a detailed dosing software instruction for MIPD consultants and clinical pharmacists. Activities to facilitate implementation included the development of a local clinical routine for vancomycin dosing, staff training and recurring MIPD rounds.

CONCLUSION: An intervention for MIPD, with an implementation plan for AUC-guided dosing of vancomycin, was developed for a tertiary hospital setting. The process can be used as guidance for other institutions with similar context wishing to initiate MIPD.

Prostate cancer is a common cancer type in men, yet some of its traits are still under-explored. One reason for this is high molecular and morphological heterogeneity. The purpose of this study was to develop a method to gain new insights into the connection between morphological changes and underlying molecular patterns. We used artificial intelligence (AI) to analyze the morphology of seven hematoxylin and eosin (H & E)-stained prostatectomy slides from a patient with multi-focal prostate cancer. We also paired the slides with spatially resolved expression for thousands of genes obtained by a novel spatial transcriptomics (ST) technique. As both spaces are highly dimensional, we focused on dimensionality reduction before seeking associations between them. Consequently, we extracted morphological features from H & E images using an ensemble of pre-trained convolutional neural networks and proposed a workflow for dimensionality reduction. To summarize the ST data into genetic profiles, we used a previously proposed factor analysis. We found that the regions were automatically defined, outlined by unsupervised clustering, associated with independent manual annotations, in some cases, finding further relevant subdivisions. The morphological patterns were also correlated with molecular profiles and could predict the spatial variation of individual genes. This novel approach enables flexible unsupervised studies relating morphological and genetic heterogeneity using AI to be carried out.

Automatic segmentation of histopathology whole -slide images (WSI) usually involves supervised training of deep learning models with pixel -level labels to classify each pixel of the WSI into tissue regions such as benign or cancerous. However, fully supervised segmentation requires large-scale data manually annotated by experts, which can be expensive and time-consuming to obtain. Non -fully supervised methods, ranging from semi -supervised to unsupervised, have been proposed to address this issue and have been successful in WSI segmentation tasks. But these methods have mainly been focused on technical advancements in algorithmic performance rather than on the development of practical tools that could be used by pathologists or researchers in real -world scenarios. In contrast, we present DEPICTER (Deep rEPresentatIon ClusTERing), an interactive segmentation tool for histopathology annotation that produces a patch -wise dense segmentation map at WSI level. The interactive nature of DEPICTER leverages self- and semi -supervised learning approaches to allow the user to participate in the segmentation producing reliable results while reducing the workload. DEPICTER consists of three steps: first, a pretrained model is used to compute embeddings from image patches. Next, the user selects a number of benign and cancerous patches from the multi -resolution image. Finally, guided by the deep representations, label propagation is achieved using our novel seeded iterative clustering method or by directly interacting with the embedding space via feature space gating. We report both real-time interaction results with three pathologists and evaluate the performance on three public cancer classification dataset benchmarks through simulations. The code and demos of DEPICTER are publicly available at https://github.com/eduardchelebian/depicter.

Layered Ni-rich transition metal oxide materials are considered the most promising cathodes for use in commercial Li-ion batteries. Due to their instability in air, an impurity layer forms during storage under ambient conditions, and this layer increases electrochemical polarization during charging and discharging, which ultimately leads to a lower cycling capacity. In this work, we found that storage of the LiNi_0.8Mn_0.1Co_0.1O₂ (NMC 811) material in ultrahigh vacuum (UHV) can restore the surface by reducing the amount of native carbonate species in the impurity layer. In this work, in situ soft X-ray ambient pressure photoelectron spectroscopy is used to directly follow the interaction between common gases found in air and the NMC 811 surface. During gas exposure of the NMC 811 surface to pure CO₂, O₂, and a mixture of both pure gases, surface-adsorbed CO₂ or/and O₂ were detected; however, permanent changes could not be identified under UHV after the gas exposure. In contrast, a permanent increase in metal hydroxide species was observed on the sample surface following H₂O vapor exposure, and an increased intensity in the carboxylate peak was observed after exposure to a mixture of CO₂/O₂/H₂O. Thus, the irreversible degradation reaction with CO₂ is triggered in the presence of H₂O (on relevant time scales defined by the experiment). Additional measurements revealed that X-ray irradiation induces the formation of metal carbonate species on the NMC 811 surface under CO₂ and H₂O vapor pressure.

Traditionally, Ni-rich-layered oxide cathodes for lithium-ion batteries are produced utilizing N-methyl-2-pyrrolidone (NMP)-processed casting. However, to avoid using the reprotoxic solvent NMP, aqueous processing becomes one of the options. In this study, H2O-processed LiNi0.8Mn0.1Co0.1O2 (NMC811) electrodes have been prepared to compare with the NMP-processed counterparts to investigate the degradation mechanism. The thick cathode-electrolyte interphase (CEI), NiO-like phase formation, and the growth of electrochemically inactive NMC particles after long-term cycling lead to capacity decay. In addition, phosphoric acid (H3PO4) was utilized to lower the pH value during the water-processed electrode preparation, to avoid corrosion of the aluminium current collector. The use of H3PO4 enhanced the capacity retention of NMC811 electrodes, likely owing to the formation of a LiF-rich CEI layer in the initial cycle(s) and the alleviated formation of electrochemically inactive NMC particles. Additionally, reaction inhomogeneity is present in H3PO4-modified electrodes, which is attributed to various Li-ion reinsertion resistances throughout the porous electrode during long-term cycling. Although the performance of the water-processed NMC811 electrode is not reaching the level of NMP-processed electrodes, this study provides key insights into the involved degradation mechanisms and demonstrates a viable pathway for the development of sustainable battery manufacturing processes. A slightly thinner CEI layer and lower charge transfer resistance were achieved by H3OP4 modification during the water processing of Ni-rich cathodes, compared to non-treated counterparts.

High heterogeneity in the membrane protein expression of small extracellular vesicles (sEVs) means that bulk methods relying on antibody-based capture for expression analysis have a drawback that each type of antibody may capture a different sub-population. An improved approach is to capture a representative sEV population, without any bias, and then perform a multiplexed protein expression analysis on this population. However, such a possibility has been largely limited to fluorescence-based methods. Here, we present a novel electrostatic labelling strategy and a microchip-based all-electric method for membrane protein analysis of sEVs. The method allows us to profile multiple surface proteins on the captured sEVs using alternating charge labels. It also permits the comparison of expression levels in different sEV-subtypes. The proof of concept was tested by capturing sEVs both non-specifically (unbiased) as well as via anti-CD9 capture probes (biased), and then profiling the expression levels of various surface proteins using the charge labelled antibodies. The method is the first of its kind, demonstrating an all-electrical and microchip based method that allows for unbiased analysis of sEV membrane protein expression, comparison of expression levels in different sEV subsets, and fractional estimation of different sEV sub-populations. These results were also validated in parallel using a single-sEV fluorescence technique.

Detection of analytes using streaming current has previously been explored using both experimental approaches and theoretical analyses of such data. However, further developments are needed for establishing a viable microchip that can be exploited to deliver a sensitive, robust, and scalable biosensor device. In this study, we demonstrated the fabrication of such a device on silicon wafer using a scalable silicon microfabrication technology followed by characterization and optimization of this sensor for detection of small extracellular vesicles (sEVs) with sizes in the range of 30 to 200 nm, as determined by nanoparticle tracking analyses. We showed that the sensitivity of the devices, assessed by a common protein–ligand pair and sEVs, significantly outperforms previous approaches using the same principle. Two versions of the microchips, denoted as enclosed and removable-top microchips, were developed and compared, aiming to discern the importance of high-pressure measurement versus easier and better surface preparation capacity. A custom-built chip manifold allowing easy interfacing with standard microfluidic connections was also constructed. By investigating different electrical, fluidic, morphological, and fluorescence measurements, we show that while the enclosed microchip with its robust glass-silicon bonding can withstand higher pressure and thus generate higher streaming current, the removable-top configuration offers several practical benefits, including easy surface preparation, uniform probe conjugation, and improvement in the limit of detection (LoD). We further compared two common surface functionalization strategies and showed that the developed microchip can achieve both high sensitivity for membrane protein profiling and low LoD for detection of sEV detection. At the optimum working condition, we demonstrated that the microchip could detect sEVs reaching an LoD of 104 sEVs/mL (when captured by membrane-sensing peptide (MSP) probes), which is among the lowest in the so far reported microchip-based methods.

Wood branches subjected to bending develop reaction wood to accommodate both tensile and compressive stresses. For softwood, such as Norway spruce and Scots pine, compression wood (CW) develops in the lower parts, while opposite wood (OW) develops on the upper parts of the branch. It is likely that the ratio of CW to OW is optimised for mechanical load bearing by nature. This hypothesis was tested with an analytical beam model using experimental data of stiffness and strength of CW and OW at CW fractions from 0 to 100%. It was found that there is indeed a maximum bending moment capacity around 35% CW, like literature values of CW content in softwood branches. For all compositions, compressive or tensile strength of OW was governing the behaviour.

The differential swelling seen between softwood opposite wood (OW) and its neighbouring compression wood (CW) developed in branches prompts several engineering issues such as dimensional instability and cracking. For a more efficient use of resources, the inevitable CW and OW should not be discarded or used as fuel, but incorporated into engineered wood products. Swelling is a hygroelastic phenomenon, where both the swelling and elastic properties of CW and OW are needed in order to make proper structural predictions. In this paper, swelling coefficients and moisture dependent elastic moduli for both CW and OW in the three principal material directions are provided along with measurements of moisture content, density, and microfibril angle. The small deformations necessitate the use of precise X-ray micro-computed tomography for measurements. The results indicate that CW and OW from Norway spruce branches differ in swelling, especially in longitudinal direction at low moisture content. It is noted that CW is a wood type with less pronounced anisotropic behaviour than both OW and normal wood from the stem, with the elastic moduli less sensitive to moisture changes in both longitudinal and transverse directions.

Softwood branches develop compression wood (CW) in the lower parts of thebranch, while opposite wood (OW) develops on the upper. These wood typesdiffer in structure at several length scales, among others in the chemical composition of their lignin matrix. While OW mostly contains guaiacyl (G) units, CW is known to contain a substantial fraction of 4-hydroxyphenyl (H) lignin.In this study, the impact this difference has on lignin hygroexpansion and inter-action with water is studied by the means of atomistic models and moleculardynamics computer simulations of lignin systems at different levels of hydration. It was found that, despite the minor difference in chemical composition, thereare differences in swelling, structure and water dynamics. CW lignin is found tohave a higher uniaxial swelling coefficient, since the phase separation between lignin and water is more pronounced. This behavior is linked to structural differ-ences, where intermolecular π−π stacking is more common in CW lignin andhydrogen bonding to water more pronounced in OW lignin. These findings are of interest for understanding the role of lignin in CW, and general understanding of moisture interaction with lignin inside wood cell walls.

The use of branch wood as a raw material in refined wood products has been limited. Compared with normal wood, this is due to the difference in structure from the tissue to molecular level, especially for compression wood found in conifers, resulting in different material behavior. To provide more insight into the underlying reasons for the difference in moisture induced swelling of compression and opposite wood, a simplified finite element model of the predominant S2 layer has been used to estimate the cell wall swelling based on previous and more recent findings of the composition and properties of the cell wall bio-polymers. Parametric investigations were carried out to determine the overall cell wall swelling of the three-phase composite, composed of cellulose, hemicellulose and lignin. Within reasonable bounds, it was found that the microfibril angle plays a significantly larger role in the swelling behavior of opposite and compression wood, than the relative composition of the cell wall bio-polymers and the hygroexpansion coefficient of lignin, of which the latter is known to be chemically different between compression and opposite wood.

Most tree species underwent cycles of contraction and expansion during the Quaternary. These cycles led to an ancient and complex genetic structure that has since been affected by extensive gene flow and by strong local adaptation. The extent to which hybridization played a role in this multi-layered genetic structure is important to be investigated. To study the effect of hybridization on the joint population genetic structure of two dominant species of the Eurasian boreal forest, Picea abies and P. obovata, we used targeted resequencing and obtained around 480 K nuclear SNPs and 87 chloroplast SNPs in 542 individuals sampled across most of their distribution ranges. Despite extensive gene flow and a clear pattern of Isolation-by-Distance, distinct genetic clusters emerged, indicating the presence of barriers and corridors to migration. Two cryptic refugia located in the large hybrid zone between the two species played a critical role in shaping their current distributions. The two species repeatedly hybridized during the Pleistocene and the direction of introgression depended on latitude. Our study suggests that hybridization helped both species to overcome main shifts in their distribution ranges during glacial cycles and highlights the importance of considering whole species complex instead of separate entities to retrieve complex demographic histories.

Current global climate change is expected to affect biodiversity negatively at all scales leading to mass biodiversity loss. Many studies have shown that the distribution of allele frequencies across a species' range is often influenced by specific genetic loci associated with local environmental variables. This association reflects local adaptation and allele changes at those loci could thereby contribute to the evolutionary response to climate change. However, predicting how species will adapt to climate change from this type of data alone remains challenging. In the present study, we combined exome capture sequences and environmental niche reconstruction, to test multiple methods for assessing local adaptation and climate resilience in two widely distributed conifers, Norway spruce and Siberian spruce. Both species are keystone species of the boreal forest and share a vast hybrid zone. We show that local adaptation in conifers can be detected through allele frequency variation, population-level ecological preferences, and historical niche movement. Moreover, we integrated genetic and ecological information into genetic offset predictive models to show that hybridization plays a central role in expanding the niche breadth of the two conifer species and may help both species to cope better with future changing climates. This joint genetic and ecological analysis also identified spruce populations that are at risk under current climate change. Cycles of glaciation have induced phases of species expansion and contraction, occasionally occurring at continental scales. Our study, employing both ecological and genetic approaches, indicates that hybridization between Norway and Siberian spruce aided both species in adapting to climate change.

Gene copy number variations (gCNVs) are structural genomic alterations involving duplications or deletions that influence gene dosage and represent a significant source of genetic variation. While single nucleotide polymorphisms (SNPs) have constituted the primary focus of population genomics, recent studies indicate that gCNVs play an equally pivotal role in adaptation. In this study, we examine the contribution of gCNVs to local adaptation along environmental gradients in Norway spruce (Picea abies) and Siberian spruce (Picea obovata), utilizing comprehensive genomic datasets derived from exome capture sequencing. A robust pipeline for the detection and quantifying of gCNVs from short-read data is developed, employing haploid samples for validation purposes. The results of our analysis demonstrate that gCNVs are pervasive, representing approximately 12% of targeted genes, with enrichment of functional genes, particularly associated with environmental stress, such as temperature tolerance, immune response, and metal ion regulation. Furthermore, they exhibit a correlation with the population structure identified through the analysis of SNPs, while also displaying distinctive adaptive signatures. Genome scans and genotype-environment association (GEA) analyses demonstrate that gCNVs contribute disproportionately to local adaptation in comparison to SNPs. These findings emphasize the multiallelic and quantitative nature of gCNVs as a crucial factor in adaptive evolution. By integrating SNPs and gCNVs, we demonstrate that gCNVs are capable of capturing patterns of selection that are not evident when using SNPs alone. This highlights the necessity of incorporating structural variation into evolutionary genomics. This study demonstrates the feasibility and importance of studying gCNVs in non-model species and provides a framework for their integration into population and quantitative genomics.

Recent studies have highlighted the significant role of copy number variants (CNVs) in phenotypic diversity, environmental adaptation and species divergence across eukaryotes. The presence of CNVs also has the potential to introduce genotyping biases, which can pose challenges to accurate population and quantitative genetic analyses. However, detecting CNVs in genomes, particularly in non-model organisms, presents a formidable challenge. To address this issue, we have developed a statistical framework and an accompanying r software package that leverage allelic-read depth from single nucleotide polymorphism (SNP) data for accurate CNV detection. Our framework capitalises on two key principles. First, it exploits the distribution of allelic-read depth ratios in heterozygotes for individual SNPs by comparing it against an expected distribution based on binomial sampling. Second, it identifies SNPs exhibiting an apparent excess of heterozygotes under Hardy–Weinberg equilibrium. By employing multiple statistical tests, our method not only enhances sensitivity to sampling effects but also effectively addresses reference biases, resulting in optimised SNP classification. Our framework is compatible with various NGS technologies (e.g. RADseq, Exome-capture). This versatility enables CNV calling from genomes of diverse complexities. To streamline the analysis process, we have implemented our framework in the user-friendly r package ‘rCNV’, which automates the entire workflow seamlessly. We trained our models using simulated data and validated their performance on four datasets derived from different sequencing technologies, including RADseq (Chinook salmon—Oncorhynchus tshawytscha), Rapture (American lobster—Homarus americanus), Exome-capture (Norway spruce—Picea abies) and WGS (Malaria mosquito—Anopheles gambiae).

Copy number variations (CNVs) have been revealed prevalent in natural populations. CNVs show significant potential to contribute to phenotypic variation and local adaptation, but can introduce bias in single nucleotide polymorphism (SNP)-based analyses if not properly accounted for. However, the limitations of using existing next-generation sequencing (NGS) data to identify CNVs hinder exploring the evolutionary significance of CNVs in population and quantitative genomic studies. Traditional CNV detection methods often rely on single features such as coverage depth, making them prone to false positives due to confounding factors. In this study, we present a flexible composite likelihood ratio (CLR) method that integrates multiple signatures, including depth of coverage, allele depth ratio deviations, and excess of observed heterozygosity, to improve the accuracy of CNV detection from SNP data. Our approach enables both SNP- and window-based CNV detection at the individual and population level, and is designed to be versatile across sequencing technologies, including whole-genome and exome capture data. Simulations and validation on real-world datasets demonstrated improved sensitivity and accuracy of CNV detection. This approach will be implemented in the rCNV R package, which we are benchmarking against established CNV detection tools across different datasets. 

IntroductionThis study investigates factors related to long-term and short-term adoption of video consultations (VCs) and reasons for discontinuing use among primary care patients.MethodsA sample of primary care patients using VCs with healthcare providers were invited to take a survey in a cross-sectional study. Participants were asked about their intention to continue to have video consultations in the future, and those indicating no intention to use VCs in the future (short-term adopters) were asked about their reasons for this. Prevalence and statistical differences between long-term and short-term adopters were investigated.ResultsThere were several statistically significant differences between long-term and short-term adopters (76% vs. 24%). Long-term adopters consisted of more middle-aged individuals (35?54 years) and the majority worked full-time (56%). They had more positive opinions of VCs and used VCs and video meetings for other purposes to a larger extent. They chose VCs because of the lack of time to go to the healthcare centre and because their provider offered them. The most common reason for discontinuing use was a preference for face-to-face consultations, with the youngest age group (16?34 years) reporting this to a larger extent.DiscussionYounger and older age groups may be less likely to continue the use of VCs, potentially preserving the digital divide. Additionally, disparities in using similar technologies might contribute to the digital divide. Moreover, convenience, positive opinions of VCs, and experience with VCs were related to long-term adoption. Further studies are needed to explore non-use, age?s influence, and address usability issues.

The rapid shift to digital healthcare, accelerated by the COVID-19 pandemic, holds promise for sustainable healthcare delivery and climate change mitigation. This study evaluates the Alltid öppet application through the lens of usability and patient satisfaction and their correlation with the intention for continued use. A cross-sectional analysis of primary care patients revealed that alignment with user needs significantly predicts long-term adoption, while frustration during use discourages it. Ease of use did not significantly affect the intention to continue, suggesting that usability alone is insufficient to drive sustained engagement. These findings highlight user-centred design's importance in digital healthcare solutions, suggesting that enduring adoption hinges on value perception and reducing user frustration. As the healthcare sector navigates its digital future, this study offers crucial insights into the design and implementation strategies that could underpin the environmental sustainability and resilience of healthcare systems.

Implementation and adoption of video consultations (VCs) in healthcare are not straightforward. Experiences of initiating a VC could increase our understanding of adoption by patients. This study aims to report patients' experiences of installing and booking a VC in primary care. Most people found it easy to find and install the VC application. Those with a higher self-reported ability and habit of using digital services and the internet found it easier than those reporting lower ability and habit. About half of our respondents had booked their recent VC themselves, most of whom had done so through a telephone call or the application "Alltid Öppet". The booking process was perceived to be easy by most but more difficult compared to installation. The easy installation process might have led to higher adoption by older people. Nevertheless, during implementation more support should be provided to people with lower digital service and internet use abilities and habits as they might find VC set-up more difficult. More attention should be given to the booking process as it may be a barrier potentially influencing adoption.

ObjectivePatient-accessible electronic health records (PAEHR) were implemented in the Stockholm region of Sweden seven years ago. This study examines socio-demographic and psychographic factors associated with reading/not reading these records, as well as the common reasons for such behaviours.MethodsPatients or guardians of minors seeking face-to-face or digital primary healthcare in the Stockholm region responded to a questionnaire about whether they were aware that they could read their PAEHR, and if so, if they had read it and reasons for reading or not reading. We conducted a comparative analysis of readers and non-readers and a stepwise multiple logistic regression.ResultsThe majority of participants were aware that they could read the PAEHR (86%) and among those aware, 77% had read it. The odds of reading decreased with increased age, unfavourable opinion of PAEHR, low information literacy and being single. Access to a smartphone increased the probability of reading. Participants who had read their PAEHR had commonly read it to get an overview of their health and care (65%) and to follow up on a healthcare visit (55%). Participants who had not read their PAEHR stated generally that they did not need to (63%) and/or had received sufficient information from their providers (38%).ConclusionsWhile most people were aware they could read the PAEHR and many had read it, a digital divide and several barriers to reading the PAEHR were identified. Efforts to increase PAEHR reading may be targeted at older people, people needing more informal support, those who may be excluded due to limited information literacy, and towards improving the patient portals’ usability.

Background: Video consultations (VCs) are effective and beneficial, yet there is a noticeable discontinuation of their use and a preference for face-to-face consultations. This study investigates the dual perspectives of patients and healthcare professionals (HCPs) on patients’ introduction to VCs, perceptions of who the users of VCs are, and the drivers of VC use in the Swedish healthcare context.

Methods: Six focus group interviews with HCPs and 13 individual interviews with patients in primary care were conducted. The interviews examined VC implementation and use, and were analyzed using rapid assessment procedures.

Results: Patients’ introductions were described as challenging, and both HCPs and patients as unprepared. Use or non-use was perceived to be related to patients’ different characteristics, needs and circumstances. The drivers of use were related to patients’ preferences and opportunities; HCPs’ choice, judgement, type of care; and societal and organizational factors.

Conclusion: The challenging introduction of VCs could have been avoided and might explain the observed discontinuation of VC use and preference for face-to-face consultations. Additionally, the perception of users’ characteristics may have negatively impacted VC use. Preference also emerged as a key driver of VC use, which was positively and negatively influenced by a range of different factors. Another significant driver of VC use was the judgement of suitability, which was greatly influenced by preferences. Furthermore, infrastructure, organisation, sociodemographics, the service’s usability and the application’s owner, in addition to the pandemic, may have further negatively influenced VC use.

Background: Patients are increasingly being offered online record access (ORA) through Patient Accessible Electronic Health Records (PAEHR), yet implementation is often met with resistance from healthcare professionals (HCPs). Experiences from previous implementations may provide important insights into potential barriers and facilitators.  

Objective: To investigate factors influencing implementation of the Swedish PAEHR in primary care from HCPs’ perspective.

Methods: We conducted 14 semi-structured interviews with a diverse group of HCPs shortly after the implementation of the Swedish PAEHR. The interviews were analysed using the Consolidated Framework for Implementation Research (CFIR) and content analysis, identifying key themes related to PAEHR implementation.

Results: Several potential barriers and facilitators were identified. According to HCPs, the PAEHR had shortcomings but offered some flexibility. HCPs described working in a complex and challenging organisation, which nonetheless had an existing structure, support, and established communication with patients. They also described using EHR system for other purposes than documentation. Moreover, they reported dealing with a complicated patient group with varying needs and high expectations. HCPs expressed that they worked in a patient-centred way and with patient engagement. The HCPs could see both advantages and disadvantages with PAEHR and had some concerns. There were mixed views of the extent of the change, where some felt patient ORA would not affect their work at all and others expected a substantial impact. Some had experiences using PAEHR themselves, while some lacked knowledge or interest. Furthermore, the implementation process was perceived as long and uneventful, with fragmented communication, where existing communication activities were utilized. They also reported receiving some information and education about PAEHR outside the organisation. HCPs had limited awareness of how patients were introduced to the PAEHR.

Conclusions: Shortcomings with the EHR system and within the organisation must be addressed for optimal implementation where patients’ and HCPs’ benefits and risks are mitigated. Moreover, improved information and education for patients and HCPs is a potential solution to address many concerns and perceived disadvantages of PAEHR.

Herein we report the first high turnover photocatalytic hydrogen formation reaction based on an earth-abundant Fe-III-NHC photosensitiser. The reaction occurs via reductive quenching of the (LMCT)-L-2 excited state that can be directly excited with green light and employs either Pt-colloids or [Co(dmgH)(2)pyCl] as proton reduction catalysts and [HNEt3][BF4] and triethanolamine/triethylamine as proton and electron donors. The outstanding photostability of the Fe-III-NHC complex enables turnover numbers >1000 without degradation.

The α-functionalisation of N-containing compounds is an area of broad interest in synthetic chemistry due to their presence in biologically active substances among others. Visible light-induced generation of nucleophilic α-aminoalkyl radicals as reactive intermediates that can be trapped by electron-deficient alkenes presents an attractive and mild approach to achieve said functionalisation. In this work, [Fe(III)(phtmeimb)₂]PF₆ (phtmeimb = phenyl(tris(3-methylimidazol-2-ylidene))borate), an N-heterocyclic carbene (NHC) complex based on Earth-abundant iron, was used as photoredox catalyst to efficiently drive the formation of α-aminoalkyl radicals from a range of different α-trimethylsilylamines and their subsequent addition to a number of electron-deficient alkenes under green light irradiation. Mechanistic investigations elucidated the different reaction steps of the complete photocatalytic cycle. In terms of yields and substrate scope, we show that [Fe(III)(phtmeimb)₂]PF₆ can compete with noble metal photoredox catalysts, for instance outcompeting archetypal [Ru(bpy)₃]Cl₂ under comparable reaction conditions, illustrating that iron photocatalysts can efficiently facilitate photoredox reactions of synthetic value.

Fe-N-heterocyclic carbene (NHC) complexes attract increasing attention as photosensitisers and photoredox catalysts. Such applications generally rely on sufficiently long excited state lifetimes and efficient bimolecular quenching, which leads to there being few examples of successful usage of Fe-NHC complexes to date. Here, we have employed [Fe(iii)(btz)(3)](3+) (btz = (3,3 '-dimethyl-1,1 '-bis(p-tolyl)-4,4 '-bis(1,2,3-triazol-5-ylidene))) in the addition of alkyl halides to alkenes and alkynes via visible light-mediated atom transfer radical addition (ATRA). Unlike other Fe-NHC complexes, [Fe(iii/ii)(btz)(3)](3+/2+) benefits from sizable charge transfer excited state lifetimes >= 0.1 ns in both oxidation states, and the Fe(iii) (LMCT)-L-2 and Fe(ii) (MLCT)-M-3 states are strong oxidants and reductants, respectively. The combined reactivity of both excited states enables efficient one-electron reduction of the alkyl halide substrate under green light irradiation. The two-photon mechanism proceeds via reductive quenching of the Fe(iii) (LMCT)-L-2 state by a sacrificial electron donor and subsequent excitation of the Fe(ii) product to its highly reducing (MLCT)-M-3 state. This route is shown to be more efficient than the alternative, where oxidative quenching of the less reducing Fe(iii) (LMCT)-L-2 state by the alkyl halide drives the reaction, in the absence of a sacrificial electron donor.

Iron N-heterocyclic carbene (FeNHC) complexes with long-lived charge transfer states are emerging as a promising class of photoactive materials. We have synthesized [Fe-II(ImP)(2)] (ImP = bis(2,6-bis(3-methylimidazol-2-ylidene-1-yl)phenylene)) that combines carbene ligands with cyclometalation for additionally improved ligand field strength. The 9 ps lifetime of its (MLCT)-M-3 (metal-to-ligand charge transfer) state however reveals no benefit from cyclometalation compared to Fe(II) complexes with NHC/pyridine or pure NHC ligand sets. In acetonitrile solution, the Fe(II) complex forms a photoproduct that features emission characteristics (450 nm, 5.1 ns) that were previously attributed to a higher ((MLCT)-M-2) state of its Fe(III) analogue [Fe-III(ImP)(2)](+), which led to a claim of dual (MLCT and LMCT) emission. Revisiting the photophysics of [Fe-III(ImP)(2)](+), we confirmed however that higher ((MLCT)-M-2) states of [Fe-III(ImP)(2)](+) are short-lived (<10 ps) and therefore, in contrast to the previous interpretation, cannot give rise to emission on the nanosecond timescale. Accordingly, pristine [Fe-III(ImP)(2)](+) prepared by us only shows red emission from its lower (LMCT)-L-2 state (740 nm, 240 ps). The long-lived, higher energy emission previously reported for [Fe-III(ImP)(2)](+) is instead attributed to an impurity, most probably a photoproduct of the Fe(II) precursor. The previously reported emission quenching on the nanosecond time scale hence does not support any excited state reactivity of [Fe-III(ImP)(2)](+) itself.