Logo: to the web site of Uppsala University

Suppose sender-receiver transmission links in a downlink network at a given data rate are subject to fading, path loss, and inter -cell interference, and that transmissions either pass, suffer loss, or incur retransmission delay. We introduce a method to obtain the average activity level of the system required for handling the buffered work and from this derive the resulting coverage probability and key performance measures. The technique involves a family of stationary buffer distributions which is used to solve iteratively a nonlinear balance equation for the unknown busy -link probability and then identify throughput, loss probability, and delay. The results allow for a straightforward numerical investigation of performance indicators, are in special cases explicit and may be easily used to study the trade-off between reliability, latency, and data rate.

We consider a cellular network equipped with aretransmission mechanism where the signal transmissions in asingle cell depends on interference with simultaneous traffic insurrounding cells. In this framework where failed signals areeither retransmitted or lost we study the channel capacity per-formance of a single-tier model with downlink or uplink traffic.For this purpose, a tractable model that allows for a precisetheoretical analysis of coverage probability and coverage rate isdeveloped further. Specifically, we obtain the Shannon capacity inthe model and introduce relevant performance measures to guidein the identification of those systems which in a precise sense areable to process all incoming work. To emphasize the genericpatterns that arise we extend and simplify the results under ascaling regime of balanced densification, which highlights thatperformance essentially falls into three categories, for pure-loss,buffered, and no-loss systems.

Multi-tier cellular networks able to handle multiple classes of base stations with varying transmission power and coverage area offer a promising approach to meet increasing traffic demands by properly balancing the input load. This paper investigates the performance of buffered multi-tier networks with randomly placed transmission nodes . Under simplifying model assumptions of Rayleigh fading and unbounded attenuation, we propose an approach to derive the multi-tier coverage probability and Shannon capacity of typical cells. The goal is to study the trade-off between base station density and interference effects in multitier compared to single-tier networks by assessing the system performance under varying policies. We also use stochastic simulation to verify the theoretical results and visualize the system behavior under different parameter settings.

In this work we consider an uplink cellular network with the focus on a typical cell rather than the whole network. The base stations (BSs) and the users are distributed according to Poisson point processes (PPP) and the signals are transmitted at random power. The BSs’ serving area is formed according to the Voronoi diagram and the users are associated with a serving BS based on the shortest distance. One of the features of the system is that we primarily take into account the interference inside a d-dimensional ball of the average size of a typical Voronoi cell. In this work we mainly focus on the system stability and discuss a necessary stability condition, which is then studied by using stochastic simulation. We also discuss some properties of the network that can affect the stability and appear to be interesting and promising for the performance analysis of the system.

We consider an uplink cellular network with static users and unlimited retransmissions. The users are assigned to the base stations (BSs) using the shortest distance association policy. The network cells are formed according to the Voronoi tessellation, and we study stability of this model with focus on a single cell. In particular, we consider a model with non-homogeneous users where the buffer size of each user depends on the number and locations of the active users at each time slot. We obtain a basic relation between input and output rate (coverage probability) of each user in steady-state regime. Moreover, we use stochastic simulation to verify sufficient stability conditions (obtained in the paper [8] for a more general system) which are reformulated in terms of the model under consideration. In particular, we find that these conditions turn out to be quite close to stability criteria in the most realistic case of the heavily loaded cell. In this regard and because of analytical unavailability of some metrics, we empirically study the convergence of the stability zone of the lightly-loaded cell to the zone defined by the sufficient stability conditions, when the load increases.

In this work, we investigate the stability of a class of n-dimensional discrete-time Markov chains with state space Nn and monotonic drift conditions. While exact stability criteria are well understood for one- and two-dimensional cases, extending these results to higher dimensions remains an open problem. To address this, we present an analytical approach to establish upper and lower bounds for the stability region for n ≥ 2. A key feature of the considered Markov chain is the monotonicity of the drift vector, which not only reduces the analytical complexity but also reflects realistic dynamics observed in practical applications, such as communication networks. Our analysis uses the Foster–Lyapunov criterion and generalizes the existing stability results to higher-dimensional settings. To illustrate the bounds obtained, we also provide numerical examples. 

This paper proposes a mean-field multi-agent reinforcement learning (MARL) framework for optimizing transmission control in buffered cellular networks. Each base station is modeled as an autonomous agent with finite queuing capacity, interacting with neighboring stations through interference on a Voronoi-based network topology. To address scalability issues in dense networks, a mean-field approximation is used so that agents respond to the average behavior of their neighbors rather than to full global states. A mean-field Q-learning algorithm and a corresponding reward function are derived to jointly balance Shannon capacity, buffer occupancy, and delay. Convergence of the learning dynamics is formally proved, and performance is evaluated via greedy,  tabular, and deep Q-network (DQN) approaches. Simulation results show that the proposed implementation significantly lowers delays and signal losses, and hence achieves better overall performance.

Both genetic and environmental influences have been proposed to contribute to the variance of gender identity and development of gender dysphoria (GD), but the magnitude of the effect of each component remains unclear. We aimed to examine the prevalence of GD among twins and non-twin siblings of individuals with GD, using data derived from a large register-based population in Sweden over the period 2001-2016. Register data was collected from the Statistics Sweden and the National Board of Health and Welfare. The outcome of interest was defined as at least four diagnoses of GD or at least one diagnosis followed by gender-affirming treatment. A total of 2592 full siblings to GD cases were registered, of which 67 were twins; age at first GD diagnosis for the probands ranged from 11.2 to 64.2 years. No same-sex twins that both presented with GD were identified during the study period. The proportion of different-sex twins both presenting with GD (37%) was higher than that in same-sex twins (0%, Fisher's exact test p-value < 0.001) and in non-twin sibling pairs (0.16%). The present findings suggest that familial factors, mainly confined to shared environmental influences during the intrauterine period, seem to contribute to the development of GD.

Background: Allergic disease is common. The aim of this study was to look at the change in asthma and rhinitis over time and to characterise factors contributing to remission and persistence of disease.

Methods: This cohort study included 255 individuals with or without asthma and or rhinitis that participated in a population survey and a follow-up 10 years later. The participants were tested for allergic sensitisation, total IgE, multiplex allergen component analysis and type-2 inflammatory markers: exhaled nitric oxide (FENO), eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN).

Results: Of the 132 healthy individuals, 112 remained healthy, 16 developed rhinitis, 4 asthma and rhinitis over the 10 years. Out of 82 subjects with rhinitis, 26 went into remission, 53 remained unchanged and 3 developed asthma in addition to rhinitis. None of the 41 participants with asthma and rhinitis went into remission. Subjects with persistent rhinitis and asthma had higher levels of total IgE (odds ratio [OR] 95% confidence interval [CI]: 6.16 [3.05-12.5]) at baseline and after 10 years, and FENO and ECP at baseline (OR per log unit increase, 95% CI 5.21 [1.20-22.7] and 6.32 [1.52-26.4], respectively), compared with those that remained healthy. Subjects with persistent rhinitis were more likely to be sensitised to grass pollen and had higher total IgE levels than those that went into remission. Individuals with persistent asthma were more likely to be sensitised to tree pollen and furry animals than those with only persistent rhinitis (OR 95% CI: 3.50 [1.29-9.49] and 6.73 [2.00-22.6], respectively).

Conclusion: IgE sensitisation and total IgE levels are associated with the persistence of rhinitis and asthma. Participants with persistent allergic disease had higher levels of allergen sensitisation and type 2 inflammation markers at baseline than those who remained healthy.

Background Rhinitis is a common problem within the population. Many subjects with rhinitis also have atopic multimorbidity, such as asthma and eczema. The purpose of this investigation was to compare subjects with only rhinitis to those that have rhinitis, asthma and/or eczema in relation to immunoglobulin E (IgE) sensitization, inflammatory markers, family history, lung function and body mass index (BMI). Methods A total of 216 adult subjects with rhinitis from the European Community Respiratory Health Survey II were investigated with multiplex component allergen analysis (103 allergen components), total IgE, C-reactive protein, eosinophilic cationic protein, fractional exhaled nitric oxide and spirometry. Rhinitis, eczema, asthma and parental allergy were questionnaire-assessed. Results Of the 216 participants with rhinitis, 89 also had asthma and/or eczema. Participants with rhinitis that also had asthma or eczema were more likely to be IgE-sensitized (3.44, odds ratio, OR: 95% CI 1.62-7.30, adjusted for sex, age, mother's allergy, total IgE and forced expiratory volume (FEV1)). The number of IgE-positive components was independently associated with atopic multimorbidity (1.11, OR: 95% Cl 1.01-1.21) adjusted for sex, age, mother's allergy, total IgE and FEV1. When analysing different types of sensitization, the strongest association with atopic multimorbidity was found in participants that were IgE-sensitized both to perennial and seasonal allergens (4.50, OR: 95% CI 1.61-12.5). Maternal allergy (2.75, OR: 95% CI 1.15-4.46), high total IgE (2.38, OR: 95% CI 1.21-4.67) and lower FEV1 (0.73, OR: 95% CI 0.58-0.93) were also independently associated with atopic multimorbidity, while no association was found with any of the other inflammatory markers. Conclusion IgE polysensitization, to perennial and seasonal allergens, and levels of total IgE seem to be the main determinants of atopic multimorbidity in subjects with rhinitis. This indicates that disease-modifying treatment that targets IgE sensitization may be of value when decreasing the risk of developing atopic multimorbidity.

BACKGROUND: Asthma is common worldwide and a large part of subjects with asthma have concomitant allergic multimorbidity in the form of rhinitis and/or eczema.

OBJECTIVE: The aim of this study is to investigate whether the presence of allergic multimorbidity in asthma relates to allergic sensitization, allergic and respiratory symptoms, quality of life, inflammatory markers, lung function, use of medication and background factors.

METHODS: A total of 437 asthmatics from the (GA² LEN) cross-sectional survey in Sweden were grouped depending on the presence of rhinitis and/or eczema. The impact of allergic multimorbidity was assessed in terms of allergic sensitization, allergic and respiratory symptoms, quality of life, type-2 inflammatory markers (exhaled nitric oxide, eosinophil activation markers, periostin), lung function, use of medication and background factors.

RESULTS: Subjects with asthma, rhinitis and eczema were more likely to be sensitized to seasonal allergens (67% vs 32%, P < .001), food allergens (54% vs 18%, P < .001) and to have a higher degree of sensitization than subjects with only asthma (23% vs 10%, P < .001). Subjects with allergic multimorbidity more often had allergic reactions to food (28% vs 10%, P = .002), more respiratory symptoms and anxiety/depression (40% vs, 14%, P < .001) than subjects with only asthma, despite having similar levels of type 2 inflammatory markers. Individuals with allergic multimorbidity were more likely to be diagnosed with asthma before the age of 12 (48% vs 27%, P = .016) and to have maternal heredity for allergy (53% vs 33%, P = .011) than subjects with only asthma.

CONCLUSION AND CLINICAL RELEVANCE: Asthmatics with allergic multimorbidity are more likely to be sensitized to seasonal aeroallergens, food allergens and they have a higher degree of sensitization compared with those with only asthma. Allergic multimorbidity is associated with respiratory and allergy symptoms, anxiety and/or depression.

Viral infections and reactivations have been linked to several pregnancy complications. Antiviral medications are often prescribed as a prophylactic measure to prevent infant infection. This study examines associations between antiviral medication use during pregnancy and preeclampsia, thereby exploring links between viruses and such pregnancy complication. We analyzed data from 618,814 first-time mothers in Sweden (2007-2019) using four national registers. Of these 27,135 (4.4%) developed preeclampsia and 18,004 (2.9%) filled an antiviral medication prescription. Adjusted logistic regression with inverse probability of treatment weighting was used to evaluate associations between use of antiviral medication and preeclampsia. Antiviral medication use was associated with a reduced likelihood of preeclampsia (aOR 0.88; 95% CI, 0.81-0.96). Particularly, antiviral medication use was associated with a reduced likelihood of developing preeclampsia with delivery before 34 weeks gestation (aOR 0.66; 95% CI, 0.48-0.92) and preeclampsia with a small for gestational age infant (aOR, 0.74; 95% CI, 0.57-0.96). Timing of antiviral prescription filling was also investigated. Antiviral medication use in the third trimester was associated with a reduced likelihood of preeclampsia (aOR 0.77; 95% CI, 0.67-0.90), but not when used during the first two trimesters. Our study suggests that viral infections or reactivation might play a role in the etiology of preeclampsia, highlighting the need to further explore viral infections' role in preeclampsia development.

Sequence-specific binding of proteins to DNA is essential for accessing genetic information. We derive a model that predicts an anticorrelation between the macroscopic association and dissociation rates of DNA binding proteins. We tested the model for thousands of different lac operator sequences with a protein binding microarray and by observing kinetics for individual lac repressor molecules in single-molecule experiments. We found that sequence specificity is mainly governed by the efficiency with which the protein recognizes different targets. The variation in probability of recognizing different targets is at least 1.7 times as large as the variation in microscopic dissociation rates. Modulating the rate of binding instead of the rate of dissociation effectively reduces the risk of the protein being retained on nontarget sequences while searching.

We seek to build an optical pooled screening platform with single-molecule readouts to quantify transcription factor(TF)-DNA binding kinetics across thousands of TF variants in live cells. As a step toward this goal, this pilot study tackles the frontline challenge of scaling optical pooled screening (OPS) with chromosomal barcodes, previously demonstrated for ~10² chromosomal genotypes in Escherichia coli (E. coli) (Soares et al., 2025), to 10³–10⁴ genotypes. We implemented a dual-barcode in situ genotyping and pooled λ-Red recombineering workflow to enable high-throughput single-molecule phenotyping of LacI–mVenus variants. In a six-genotype pilot library (WT, Q18M, V52A, Q55N, G58A and a negative control lacking a specific genomic Lac operator), in situ genotyping correctly identified 5/6 strains, and live-cell imaging recovered expected phenotypes for identified strains. This pilot establishes OPS as a practical foundation for single-molecule phenotyping with large TF variants library and identifies below design constraints to address before scaling : dual-barcode decoding efficiency, rare inter-donor recombination, and instability of long LacO arrays.

Transcription factors (TFs) efficiently locate their target DNA sequences by combining three-dimensional diffusion and one-dimensional sliding on nonspecific DNA. To balance rapid sliding with strong specific binding, TFs were proposed to switch between search and recognition conformations. For E. coli lac repressor (LacI), the folding of the hinge helices has been implicated in the conformational switch. Here, we tested how mutations in the hinge region impact the search speed and binding stability. Based on molecular dynamics simulations, we selected two LacI mutants favoring either search or recognition conformation. We measured the binding kinetics of the mutants both in vitro on DNA microarrays with 2,479 different Lac operators and in vivo via single-molecule experiments. We conclude that a hinge region mutation causing less helix propensity enhances the specificity but reduces binding strength globally, while a hinge region mutation causing higher helix propensity has opposite effects. However, altered specificity impacts the search time less than expected. Instead, the major effect was impaired dissociation in response to IPTG induction for the strongly binding mutant. Together with earlier reports of affinity–inducibility trade-offs in LacI, our data support the model in which the hinge region governs a trade-off between binding stability and inducibility rather than between speed and binding stability. 

Background: A major challenge in management of traumatic brain injury (TBI) is to assess the heterogeneity of TBI pathology and outcome prediction. A reliable outcome prediction would have both great value for the healthcare provider, but also for the patients and their relatives. A well-known prediction model is the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) prognostic calculator. The aim of this study was to externally validate all three modules of the IMPACT calculator on TBI patients admitted to Uppsala University hospital (UUH).

Method: TBI patients admitted to UUH are continuously enrolled into the Uppsala neurointensive care unit (NICU) TBI Uppsala Clinical Research (UCR) quality register. The register contains both clinical and demographic data, radiological evaluations, and outcome assessments based on the extended Glasgow outcome scale extended (GOSE) performed at 6 months to 1 year. In this study, we included 635 patients with severe TBI admitted during 2008–2020. We used IMPACT core parameters: age, motor score, and pupillary reaction.

Results: The patients had a median age of 56 (range 18–93), 142 female and 478 male. Using the IMPACT Core model to predict outcome resulted in an AUC of 0.85 for mortality and 0.79 for unfavorable outcome. The CT module did not increase AUC for mortality and slightly decreased AUC for unfavorable outcome to 0.78. However, the lab module increased AUC for mortality to 0.89 but slightly decreased for unfavorable outcome to 0.76. Comparing the predicted risk to actual outcomes, we found that all three models correctly predicted low risk of mortality in the surviving group of GOSE 2–8. However, it produced a greater variance of predicted risk in the GOSE 1 group, denoting general underprediction of risk. Regarding unfavorable outcome, all models once again underestimated the risk in the GOSE 3–4 groups, but correctly predicts low risk in GOSE 5–8.

Conclusions: The results of our study are in line with previous findings from centers with modern TBI care using the IMPACT model, in that the model provides adequate prediction for mortality and unfavorable outcome. However, it should be noted that the prediction is limited to 6 months outcome and not longer time interval.

Outcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3–0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.

This study aimed to evaluate the predictive value and clinical impact of a clinically implemented artificial neural network software model. The software detects intracranial hemorrhage (ICH) from head computed tomography (CT) scans and artificial intelligence (AI)-identified positive cases are then annotated in the work list for early radiologist evaluation. The index test was AI detection by the program Zebra Medical Vision-HealthICH+. Radiologist-confirmed ICH was the reference standard. The study compared whether time benefits from using the AI model led to faster escalation of patient care or surgery within the first 24 h. A total of 2,306 patients were evaluated by the software, and 288 AI-positive cases were included. The AI tool had a positive predictive value of 0.823. There was, however, no significant time reduction when comparing the patients who required escalation of care and those who did not. There was also no significant time reduction in those who required acute surgery compared with those who did not. Among the individual patients with reduced time delay, no cases with evident clinical benefit were identified. Although the clinically implemented AI-based decision support system showed adequate predictive value in identifying ICH, there was no significant clinical benefit for the patients in our setting. While AI-assisted detection of ICH shows great promise from a technical perspective, there remains a need to evaluate the clinical impact and perform external validation across different settings.

Ice phenology has shifted with anthropogenic warming such that many lakes are experiencing a shorter ice season. However, changes to ice quality - the ratio of black and white ice layers - remain little explored, despite relevance to lake physics, ecological function, human recreation and transportation. In this Review, we outline how ice quality is changing and discuss knock-on ecosystem service impacts. Although direct evidence is sparse, there are suggestions that ice quality is diminishing across the Northern Hemisphere, encompassing declining ice thickness, decreasing black ice and increasing white ice. These changes are projected to continue in the future, scaling with global temperature increases, and driving considerable impacts to related ecosystem services. Rising proportions of white ice will markedly reduce bearing strength, implying more dangerous conditions for transportation (limiting operational use of many winter roads) and recreation (increasing the risk of fatal spring-time drownings). Shifts from black to white ice conditions will further reduce the amount of light reaching the water column, minimizing primary production, and altering community composition to favour motile and mixotrophic species; these changes will affect higher trophic levels, including diminished food quantity for zooplankton and fish, with potential developmental consequences. Reliable and translatable in situ sampling methods to assess and predict spatiotemporal variations in ice quality are urgently needed. Lake ice has witnessed considerable changes in its phenology, but less is known about ice quality - the ratio of black ice to white ice. This Review assesses the changes in lake ice quality and its ecosystem services, noting diminished ice quality in observations and projections.

Ice and snow cover on lakes plays a fundamental role for under-ice ecology by reducing water column mixing and light availability. Previous studies have shown that such reductions can significantly influence the growth and reproduction of phytoplankton, primarily focusing on changes in ice-on and ice-off dates in a warming climate. This study goes beyond studying the effects of ice phenology on phytoplankton by addressing two fundamental questions: (1) how does a snow cover on ice influence below-ice phytoplankton chlorophyll-a and community composition and (2) how do variations in ice phenology influence spring phytoplankton chlorophyll-a and community composition after ice-off? To address these two questions, we assessed long-term monitoring data collected at least monthly on phytoplankton chlorophyll-a and community composition. We combined the phytoplankton data with annual ice phenology and nearby meteorological data on daily snow depth between 1997 and 2019 in a mesotrophic lake (Erken) in Sweden. Snow cover resulted in an exponential decrease of phytoplankton chlorophyll-a, with detectable effects during all 3 months studied (January-March). Deeper snow cover changed the community dominance from autotrophs to mixotrophs in two of the months studied (January and March), which we explain by reduced light availability caused by snow cover. In spring, phytoplankton chlorophyll-a increased with longer ice periods and delayed ice-off dates. A wide range of taxa in the spring community increased with delayed ice-off dates, while delayed ice-on dates mainly promoted diatoms. Convective mixing is important to keep non-motile taxa in the photic zone and could explain the increased phytoplankton growth with longer ice duration. Our results highlight seasonal ice and snow cover as key regulators for the timing of growth and reproduction of primary producers below ice, with effects of the ice cover period lasting after ice-off. Snow on ice causes light constraints, which commonly result in reduced under-ice primary production and a higher proportion of mixotrophs in the phytoplankton community. Losing high nutritional phytoplankton groups such as mixotrophs following changes in ice phenology and snow cover can have consequences for the trophic transfer and the biogeochemical cycling in lakes.

Single-particle imaging (SPI) using X-ray free-electron Lasers (XFELs) offers the potential to determine protein structures at high spatial and temporal resolutions without the need for crystallization or vitrification. However, the technique faces challenges due to weak diffraction signals from single proteins and significant background scattering from gases used for sample delivery. A recent observation of a diffraction pattern from an isolated GroEL protein complex Ekeberg T et al. (Light Sci Appl 13:15, 2024. https://doi.org/10.1038/274s41377-023-01352-7) had similar numbers of signal and background photons. Ongoing efforts aim to reduce the background created by sample delivery, with one approach replacing most of the used gas with helium Yenupuri T et al. (Sci Rep 14:4401, 2024. https://doi.org/10.1038/s41598-024-54605-9). In this study, we investigate the effects of a reduced background on the resolution limits for SPI of isolated proteins under different experiment conditions. As a test case, we used GroEL, and we used experimentally derived parameters for our simulations. We observe that background significantly impacts the achievable resolution, particularly when the signal strength is comparable to the background. This is best exemplified at 6.0 keV, where a background reduction by a factor of 10 leads to a resolution improvement from 1.9 to 1.2 nm, for a dataset of 10⁴ patterns.

The feasibility of Single Particle Imaging on a protein complex in solution is investigated. We leverage two recent experimental results: the ability to generate stable nano-scale thin liquid sheets, and the availability of a nanometer-sized X-ray focus with unprecedented photon densities. Combining these advances, we show that it is in principle possible to solve for the three-dimensional electron density of a single isolated protein despite significant background scattering due to the water layer. With the 15 nm diameter GroEL protein, a resolution of 0.85 nm was achieved using 10⁶ diffraction patterns. The diffraction patterns were simulated using 9.0 keV hard X-rays with a 7 nm beam radius. 

The study of ultrafine particle aerosols, those with particle diameters of 100 nm or less, is important due to their impact on our health and environment. However, given their small sizes, such particles can be difficult to measure and trace. Most common optical methods are unable to reach this size range. Other methods exist but incur other limitations, such as the need for electrically charged particles. Here we show how light scattering can be used to detect and measure the size and location of single viruses and protein complexes forming an aerosol beam, as well as trace their path. We were able to detect individual particles down to 16 nm in diameter. The primary purpose of our instrument is to monitor the delivery of single bioparticles to the focus of an X-ray laser to image those particles, but it has the potential to study any other aerosols such as those resulting from ultrafine sea spray, with important consequences for cloud formation and climate modeling, or from combustion, responsible for most air pollution and resulting health impacts.

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility.

Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based early bactericidal activity analysis workflow and determine sample sizes needed to detect early bactericidal activity or a difference between treatment arms.

Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based early bactericidal activity analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect early bactericidal activity given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated.

Results: The presented early bactericidal activity analysis approach incorporates estimate of early bactericidal activity with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect early bactericidal activity with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA(0-14) as low as 11 h when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% [coefficient of variation (CV)] and 22%, respectively. Higher sample sizes are required for smaller early bactericidal activity and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered.

Conclusion: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting early bactericidal activity for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.

Background

In vitro, meropenem is shown to restore the activity of rifampicin in rifampicin-resistant Mycobacterium tuberculosis strains. This phase 2a trial aimed to determine if addition of rifampicin increases the early bactericidal activity (EBA) of meropenem plus amoxicillin/clavulanate in patients with rifampicin-resistant tuberculosis (RR-TB).

Methods

Individuals with RR-TB were randomized to either 2 g meropenem infusion 3 times daily plus amoxicillin/clavulanate 500 mg/125 mg orally 3 times daily with 20 mg/kg rifampicin orally once daily (M-AC-R arm) or the same treatment without rifampicin (M-AC). Sputum samples were collected at baseline and throughout the 14-day treatment. Colony-forming unit (CFU) and time-to-positivity (TTP) data were analyzed using nonlinear mixed-effects modeling. Plasma samples at day 13 were used to derive rifampicin and meropenem pharmacokinetic parameters using noncompartmental analysis. Rifampicin minimum inhibitory concentrations (MICs) were determined from baseline sputum isolates with and without meropenem.

Results

Of the 52 participants enrolled, 38 participants completed the trial. The majority (67%) were male, and the median age was 37 years. The median (95% prediction interval) predicted 14-day EBA in CFU was 1.33 (−0.15 to 3.64) and 1.20 (0.05–2.66) log₁₀ CFU/mL, and TTP increased by 0.220 (0.098–0.551) and 0.216 (0.126–0.505) log₁₀ hours for the M-AC-R and M-AC arms, respectively. No statistically significant difference was found between the 2 arms. Meropenem pharmacokinetics were similar in both arms, and rifampicin MICs were not meaningfully reduced by meropenem.

Conclusions

Adding rifampicin to meropenem plus amoxicillin/clavulanate did not enhance short-term antibacterial activity in patients with RR-TB.

Linezolid is an efficacious medication for the treatment of drug-resistant tuberculosis but has been associated with serious safety issues that can result in treatment interruption. The objectives of this study were thus to build a population pharmacokinetic model and to use the developed model to establish a model-informed precision dosing (MIPD) algorithm enabling safe and efficacious dosing in patients with multidrug- and extensively drug-resistant tuberculosis. Routine hospital therapeutic drug monitoring data, collected from 70 tuberculosis patients receiving linezolid, was used for model development. Efficacy and safety targets for MIPD were the ratio of unbound area under the concentration versus time curve between 0 and 24 h over minimal inhibitory concentration (fAUC(0-24h)/MIC) above 119 and unbound plasma trough concentration (fC(min)) below 1.38 mg/L, respectively. Model building was performed in NONMEM 7.4.3. The final population pharmacokinetic model consisted of a one-compartment model with transit absorption and concentration- and time-dependent auto-inhibition of elimination. A flat dose of 600 mg once daily was appropriate in 67.2% of the simulated patients from an efficacy and safety perspective. Using the here developed MIPD algorithm, the proportion of patients reaching the efficacy and safety target increased to 81.5% and 88.2% using information from two and three pharmacokinetic sampling occasions, respectively. This work proposes an MIPD approach for linezolid and suggests using three sampling occasions to derive an individualized dose that results in adequate efficacy and fewer safety concerns compared to flat dosing.

Long-term usage of linezolid can result in adverse events such as peripheral neuropathy, anemia and thrombocytopenia. Therapeutic drug monitoring data from 75 drug-resistant tuberculosis patients treated with linezolid were analyzed using a time-to-event (TTE) approach for peripheral neuropathy and anemia and indirect response modelling for thrombocytopenia. Different time-varying linezolid pharmacokinetic exposure indices (AUC0-24h,ss, Cav, Cmax and Cmin) and patient characteristics were investigated as risk factors. A treatment duration shorter than 3 months was considered dropout and was modelled using a TTE approach. An exposure-response relationship between linezolid Cmin and both peripheral neuropathy and anemia was found. The exposure index which best described the development of thrombocytopenia was AUC0-24h. The final TTE dropout model indicated an association between linezolid Cmin and dropout. New safety targets for each adverse event were proposed which can be used for individualized linezolid dosing. According to the model predictions at 6 months of treatment, a Cmin of 0.11 mg/L and 1.4 mg/L should not be exceeded to keep the cumulative probability to develop anemia and peripheral neuropathy below 20%. The AUC0-24h should be below 111 h center dot mg/L or 270 h center dot mg/L to prevent thrombocytopenia and severe thrombocytopenia, respectively. A clinical utility assessment showed that the currently recommended dose of 600 mg once daily is safer compared to a 300 mg BID dosing strategy considering all four safety endpoints.

Large clinical trials often generate complex and large datasets which need to be presented frequently throughout the trial for interim analysis or to inform a data safety monitory board (DSMB). In addition, reliable and traceability are required to ensure reproducibility in pharmacometric data analysis. A reproducible pharmacometric analysis workflow was developed during a large clinical trial involving 1000 participants over one year testing Bacillus Calmette-Guerin (BCG) (re)vaccination in coronavirus disease 2019 (COVID-19) morbidity and mortality in frontline health care workers. The workflow was designed to review data iteratively during the trial, compile frequent reports to the DSMB, and prepare for rapid pharmacometric analysis. Clinical trial datasets (n = 41) were transferred iteratively throughout the trial for review. An RMarkdown based pharmacometric processing script was written to automatically generate reports for evaluation by the DSMB. Reports were compiled, reviewed, and sent to the DSMB on average three days after the data cut-off, reflecting the trial progress in real-time. The script was also utilized to prepare for the trial pharmacometric analyses. The same source data was used to create analysis datasets in NONMEM format and to support model script development. The primary endpoint analysis was completed three days after data lock and unblinding, and the secondary endpoint analyses two weeks later. The constructive collaboration between clinical, data management, and pharmacometric teams enabled this efficient, timely, and reproducible pharmacometrics workflow.

(1) Background: Some individuals are more susceptible to developing respiratory tract infections (RTIs) or coronavirus disease (COVID-19) than others. The aim of this work was to identify risk factors for symptomatic RTIs including COVID-19 and symptomatic COVID-19 during the coronavirus pandemic by using infection incidence, participant baseline, and regional COVID-19 burden data. (2) Methods: Data from a prospective study of 1000 frontline healthcare workers randomized to Bacillus Calmette-Gu & eacute;rin vaccination or placebo, and followed for one year, was analyzed. Parametric time-to-event analysis was performed to identify the risk factors associated with (a) non-specific symptomatic respiratory tract infections including COVID-19 (RTIs+COVID-19) and (b) symptomatic RTIs confirmed as COVID-19 using a polymerase chain reaction or antigen test (COVID-19). (3) Results: Job description of doctor or nurse (median hazard ratio [HR] 1.541 and 95% confidence interval [CI] 1.299-1.822), the reported COVID-19 burden (median HR 1.361 and 95% CI 1.260-1.469 for 1.4 COVID-19 cases per 10,000 capita), or a BMI > 30 kg/m(2) (median HR 1.238 and 95% CI 1.132-1.336 for BMI of 35.4 kg/m(2)) increased the probability of RTIs+COVID-19, while positive SARS-CoV-2 serology at enrollment (median HR 0.583 and 95% CI 0.449-0.764) had the opposite effect. The reported COVID-19 burden (median HR 2.372 and 95% CI 2.116-2.662 for 1.4 COVID-19 cases per 10,000 capita) and a job description of doctor or nurse (median HR 1.679 and 95% CI 1.253-2.256) increased the probability of developing COVID-19, while smoking (median HR 0.428 and 95% CI 0.284-0.648) and positive SARS-CoV-2 serology at enrollment (median HR 0.076 and 95% CI 0.026-0.212) decreased it. (4) Conclusions: Nurses and doctors with obesity had the highest probability of developing RTIs including COVID-19. Non-smoking nurses and doctors had the highest probability of developing COVID-19 specifically. The reported COVID-19 burden increased the event probability, while positive SARS-CoV-2 IgG serology at enrollment decreased the probability of RTIs including COVID-19, and COVID-19 specifically.

Heteroresistance (HR) is an enigmatic phenotype where, in a main population of susceptible cells, small subpopulations of resistant cells exist. This is a cause for concern, as this small subpopulation is difficult to detect by standard antibiotic susceptibility tests, and upon antibiotic exposure the resistant subpopulation may increase in frequency and potentially lead to treatment complications or failure. Here, we determined the prevalence and mechanisms of HR for 40 clinical Staphylococcus aureus isolates, against 6 clinically important antibiotics: daptomycin, gentamicin, linezolid, oxacillin, teicoplanin, and vancomycin. High frequencies of HR were observed for gentamicin (69.2%), oxacillin (27%), daptomycin (25.6%), and teicoplanin (15.4%) while none of the isolates showed HR toward linezolid or vancomycin. Point mutations in various chromosomal core genes, including those involved in membrane and peptidoglycan/teichoic acid biosynthesis and transport, tRNA charging, menaquinone and chorismite biosynthesis and cyclic-di-AMP biosynthesis, were the mechanisms responsible for generating the resistant subpopulations. This finding is in contrast to gram-negative bacteria, where increased copy number of bona fide resistance genes via tandem gene amplification is the most prevalent mechanism. This difference can be explained by the observation that S. aureus has a low content of resistance genes and absence of the repeat sequences that allow tandem gene amplification of these genes as compared to gram-negative species.

Heteroresistance (HR), the coexistence of a minor resistant subpopulation within a predominantly susceptible bacterial population, is a clinically relevant problem. The resistant subpopulation often escapes detection by standard susceptibility testing, which can lead to treatment failure. To investigate HR in Enterococcus faecalis, we performed population analysis profiling (PAP) on 40 clinical isolates against five clinically important antibiotics and whole-genome sequencing (WGS) on the resistant subpopulation. HR was identified for daptomycin (20.0%), gentamicin (13.2%), and tigecycline (35.9%), but not for linezolid, and vancomycin. Genomic analysis revealed that daptomycin resistance was primarily caused by mutations affecting cell envelope integrity and stress-response pathways. Gentamicin resistance was linked to alterations in efflux regulation, ribosomal proteins synthesis, and transcriptional control. Tigecycline resistance involved deletions in the tet(M) leader peptide, resulting in a ±25-fold increased tet(M) expression, as well as transposition of the transposon Tn916 carrying tet(M) to multiple chromosomal sites, likely contributing to increased gene dosage. These findings highlight the role of chromosomal mutations and mobile genetic elements in driving HR in E. faecalis, consistent with previously observed mechanisms in Staphylococcus aureus.

Heteroresistance is a transient resistance phenotype characterized by the presence of small subpopulations of bacterial cells with elevated antibiotic resistance within a susceptible main population. In Gram-negative pathogens, heteroresistance is frequently caused by tandem amplification of genes encoding resistance proteins with low activity towards the antibiotic, a process commonly mediated by homologous recombination between flanking repeated sequences. However, the specific roles of individual recombination proteins in this mechanism remain largely undefined. In this study, we systematically evaluated the contribution of 19 recombination-associated genes to tandem amplification-driven heteroresistance in Escherichia coli. A clinical plasmid causing tobramycin heteroresistance by tandem amplification of aac(3)-IId gene was conjugated into recombination gene deficient mutants and the wild-type parental strain. While heteroresistance was observed with all mutants, the frequency of resistant subpopulations was decreased in recA and recB mutants, and a shift in resistance mechanism towards increased plasmid copy number and resistance mutations was observed. Partially reduced frequencies of tandem amplifications and a shift towards other heteroresistance mechanisms were also observed with recC, recJ, ruvA, and ruvC mutants, whereas other deletions of recombination genes had no or little impact on tandem amplifications. These findings identify RecABC as a key pathway in heteroresistance via tandem amplification, but even when these genes are deleted resistant subpopulations can still be generated by other mechanisms. 

Sterile inflammation after injury is important for tissue restoration. In injured human and mouse tissues, macrophages were recently found to accumulate perivascularly. This study investigates if macrophages adopt a mural cell phenotype important for restoration after ischemic injury. Single-cell RNA sequencing of fate-mapped macrophages from ischemic mouse muscles demonstrates a macrophage-toward-mural cell switch of a subpopulation of macrophages with downregulated myeloid cell genes and upregulated mural cell genes, including PDGFRβ. This observation was further strengthened when including unspliced transcripts in the analysis. The macrophage switch was proven functionally relevant, as induction of macrophage-specific PDGFRβ deficiency prevented their perivascular macrophage phenotype, impaired vessel maturation and increased vessel leakiness, which ultimately reduced limb function. In conclusion, macrophages in adult ischemic tissue were demonstrated to undergo a cellular program to morphologically, transcriptomically and functionally resemble mural cells while weakening their macrophage identity. The macrophage-to-mural cell-like phenotypic switch is crucial for restoring tissue function and warrants further exploration as a potential target for immunotherapies to enhance healing.

X-ray photoelectron spectroscopy (PES) has been widely applied in the field of battery studies. However, the lack of knowledge regarding the inelastic mean free path (IMFP) for studied systems limits the interpretation of spectroscopic results. In this work, the IMFP of poly(trimethylene carbonate) (PTMC), poly( epsilon-caprolactone) (PCL), and the solid polymer electrolytes consisting of lithium bis(oxalate)borate (LiBOB) together with PTMC or PCL has been determined using PES at a photoelectron kinetic energy of 8.7 keV. Additionally, the surface roughness of these films was investigated by atomic force microscopy and correlated with calculated IMFP values. Our studies reveal that the IMFP of solid polymer electrolytes is higher than that of pure polymers. The presented IMFPs provide references for future spectroscopic studies involving these materials.

Implementation of fluorine-free electrolytes that are safer and more sustainable than the state-of-the-art highly fluorinated electrolytes requires a thorough understanding of the interphase formation process. This work investigates the effects of LiPF₆- and lithium bis(oxalato)borate (LiBOB)-based electrolytes on the electrochemical performance and surface chemistry of graphite, silicon, and silicon-graphite composite electrodes. The LiBOB-based electrolyte degrades more with the presence of silicon in the electrode, and tends to form a thicker solid electrolyte interphase (SEI) layer compared to the LiPF₆-based electrolyte. Different degradation distributions were also found in the graphite-silicon composite electrode: The LiPF₆ degradation products tend to form on silicon, while the LiBOB degradation products preferentially form on carbon species. These results provide insights into the relationship between electrolytes and electrodes in terms of electrochemical performance, as well as SEI composition and morphology.

A limiting factor for solid polymer electrolyte (SPE)-based Li-batteries is the functionality of the electrolyte decomposition layer that is spontaneously formed at the Li metal anode. A deeper understanding of this layer will facilitate its improvement. This study investigates three SPEs – polyethylene oxide:lithium tetrafluoroborate (PEO:LiBF₄), polyethylene oxide:lithium bis(oxalate)borate (PEO:LiBOB), and polyethylene oxide:lithium difluoro(oxalato)borate (PEO:LiDFOB) – using a combination of electrochemical impedance spectroscopy (EIS), galvanostatic cycling, in situ Li deposition photoelectron spectroscopy (PES), and ab initio molecular dynamics (AIMD) simulations. Through this combination, the cell performance of PEO:LiDFOB can be connected to the initial SPE decomposition at the anode interface. It is found that PEO:LiDFOB had the highest capacity retention, which is correlated to having the least decomposition at the interface. This indicates that the lower SPE decomposition at the interface still creates a more effective decomposition layer, which is capable of preventing further electrolyte decomposition. Moreover, the PES results indicate formation of polyethylene in the SEI in cells based on PEO electrolytes. This is supported by AIMD that shows a polyethylene formation pathway through free-radical polymerization of ethylene.

We present the development and validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantification of clonidine, dexmedetomidine, fentanyl, ketamine, ketobemidone, midazolam and morphine in whole blood. These are drugs predominately used in intensive care units (ICUs) but they are also encountered in forensic investigations. The analytes were recovered from 0.25 g of blood by protein precipitation with a mixture of acetonitrile and ethanol. Separation was performed on a BEH phenyl column. Mobile phases consisted of 0.05% formic acid in 10 mM ammonium formate and 0.05% formic acid in methanol, respectively, and the flow rate was 600 mu L/min. The mass spectrometer was operated in positive electrospray ionization mode with multiple reaction monitoring. Validation included selectivity, qualitative matrix effects, calibration model, limit of detection, lower limit of quantification, within- and between-day accuracy and precision, process efficiency, dilution integrity, carry over and stability. Selectivity was high and no ion suppression or enhancementwas observed in the areas were the analytes eluted. Calibration curves were linear over arange of 0.25-50 ng/g for dexmedetomidine, 0.05-50 ng/g for fentanyl and 5.0-500 ng/g formorphine and quadratic over a range of 0.5-50 ng/g for clonidine, 50-5000 ng/g for ketamine, 5.0-500 ng/g for ketobemidone and midazolam. The method showed acceptable within- and betweenday accuracies and precisions. All analytes were stable in whole blood for three weeksat 4. C. Concentrations in patient samples ranged between 42-760 ng/g for midazolam (n = 15), 0.3-1.5 ng/g for dexmedetomidine (n = 13), 0.6-6.4 ng/g for clonidine (n = 13), 8-62 ng/g for morphine (n = 16), 5-19 ng/g for ketobemidone (n = 5), 0.07-3.1 ng/g for fentanyl (n = 43), and 562000 ng/g for ketamine (n = 10). We conclude that the method was successfully validatedand applied to ante-mortem and post-mortem blood samples from critically ill adult patientsin a general ICU.

Background: Standard dosages of analgesic and sedative drugs are given to intensive care patients. The resulting range of blood concentrations and corresponding clinical responses need to be better examined. The purpose of this study was to describe daily dosages, measured blood concentrations, and clinical responses in critically ill patients. The purpose was also to contribute to establishing whole blood concentration reference values of the drugs investigated.

Methods: A descriptive study of prospectively collected data from 302 admissions to a general intensive care unit (ICU) at a university hospital. Ten drugs (clonidine, fentanyl, morphine, dexmedetomidine, ketamine, ketobemidone, midazolam, paracetamol, propofol, and thiopental) were investigated, and daily dosages recorded. Blood samples were collected twice daily, and drug concentrations were measured. Clinical responses were registered using Richmond agitation-sedation scale (RASS) and Numeric rating scale (NRS).

Results: Drug dosages were within recommended dose ranges. Blood concentrations for all 10 drugs showed a wide variation within the cohort, but only 3% were above therapeutic interval where clonidine (57 of 122) and midazolam (38 of 122) dominated. RASS and NRS were not correlated to drug concentrations.

Conclusion: Using recommended dose intervals for analgesic and sedative drugs in the ICU setting combined with regular monitoring of clinical responses such as RASS and NRS leads to 97% of concentrations being below the upper limit in the therapeutic interval. This study contributes to whole blood drug concentration reference values regarding these 10 drugs.

Background: Patients in the intensive care unit (ICU) often receive analgesic and sedative drugs. There is limited knowledge about the resulting drug concentrations in blood in the critically ill patient, and how these concentrations change after death. In this single-centre prospective study of deceased patients from a general ICU, the aim was to describe blood concentrations and post-mortem redistribution for ten common analgesic and sedative drugs.

Methods: We included 46 patients who died during intensive care. Blood samples were collected pre-mortem (before death), peri-mortem (within one hour after death) and post-mortem (through aortic arch sampling at the morgue or during clinical or forensic autopsy). Samples were analysed for clonidine, dexmedetomidine, fentanyl, ketamine, ketobemidone, morphine, midazolam, paracetamol, propofol and thiopental.

Results: Post-mortem redistribution was significant for fentanyl, with a mean concentration increase from 3.1 ng/ g to 5.2 ng/g (p = 0.002). There was no correlation between neither cumulative fentanyl dose nor post-mortem interval and post-mortem concentration changes. For the other drugs, the changes during the post-mortem interval were not significant. Median peri-mortem concentrations were 2.3-9 times higher than observed concentrations in a larger cohort of living ICU patients.

Conclusion: In conclusion, of the investigated drugs, only fentanyl showed a predominant positive post-mortem redistribution, whereas for the other drugs, post-mortem changes were unpredictable. We also conclude that concentrations from the living may not be comparable to those obtained even shortly after death. These concentration differences, as well as the observed post-mortem changes, can influence toxicological interpretation.

Claudin-5 (CLDN5) is an endothelial tight junction protein essential for blood-brain barrier (BBB) formation. Abnormal CLDN5 expression is common in brain disease, and knockdown of Cldn5 at the BBB has been proposed to facilitate drug delivery to the brain. To study the consequences of CLDN5 loss in the mature brain, we induced mosaic endothelial-specific Cldn5 gene ablation in adult mice (Cldn5^iECKO). These mice displayed increased BBB permeability to tracers up to 10 kDa in size from 6 days post induction (dpi) and ensuing lethality from 10 dpi. Single-cell RNA sequencing at 11 dpi revealed profound transcriptomic differences in brain endothelial cells regardless of their Cldn5 status in mosaic mice, suggesting major non-cell-autonomous responses. Reactive microglia and astrocytes suggested rapid cellular responses to BBB leakage. Our study demonstrates a critical role for CLDN5 in the adult BBB and provides molecular insight into the consequences and risks associated with CLDN5 inhibition.

Rationale: Pericytes are capillary mural cells playing a role in stabilizing newly formed blood vessels during development and tissue repair. Loss of pericytes has been described in several brain disorders, and genetically induced pericyte deficiency in the brain leads to increased macromolecular leakage across the blood-brain barrier (BBB). However, the molecular details of the endothelial response to pericyte deficiency remain elusive.

Objective: To map the transcriptional changes in brain endothelial cells resulting from lack of pericyte contact at single-cell level and to correlate them with regional heterogeneities in BBB function and vascular phenotype.

Methods and Results: We reveal transcriptional, morphological, and functional consequences of pericyte absence for brain endothelial cells using a combination of methodologies, including single-cell RNA sequencing, tracer analyses, and immunofluorescent detection of protein expression in pericyte-deficient adult Pdgfb(ret/ret) mice. We find that endothelial cells without pericyte contact retain a general BBB-specific gene expression profile, however, they acquire a venous-shifted molecular pattern and become transformed regarding the expression of numerous growth factors and regulatory proteins. Adult Pdgfb(ret/ret) brains display ongoing angiogenic sprouting without concomitant cell proliferation providing unique insights into the endothelial tip cell transcriptome. We also reveal heterogeneous modes of pericyte-deficient BBB impairment, where hotspot leakage sites display arteriolar-shifted identity and pinpoint putative BBB regulators. By testing the causal involvement of some of these using reverse genetics, we uncover a reinforcing role for angiopoietin 2 at the BBB.

Conclusions: By elucidating the complexity of endothelial response to pericyte deficiency at cellular resolution, our study provides insight into the importance of brain pericytes for endothelial arterio-venous zonation, angiogenic quiescence, and a limited set of BBB functions. The BBB-reinforcing role of ANGPT2 (angiopoietin 2) is paradoxical given its wider role as TIE2 (TEK receptor tyrosine kinase) receptor antagonist and may suggest a unique and context-dependent function of ANGPT2 in the brain.

Platelet-derived growth factor B (PDGFB) released from endothelial cells is indispensable for pericyte recruitment during angiogenesis in embryonic and postnatal organ growth. Constitutive genetic loss-of-function of PDGFB leads to pericyte hypoplasia and the formation of a sparse, dilated and venous-shifted brain microvasculature with dysfunctional blood-brain barrier (BBB) in mice, as well as the formation of microvascular calcification in both mice and humans. Endothelial PDGFB is also expressed in the adult quiescent microvasculature, but here its importance is unknown. We show that deletion of Pdgfb in endothelial cells in 2-months-old mice causes a slowly progressing pericyte loss leading, at 12–18 months of age, to ≈50% decrease in endothelial:pericyte cell ratio, ≈60% decrease in pericyte longitudinal capillary coverage and >70% decrease in pericyte marker expression. Similar to constitutive loss of Pdgfb, this correlates with increased BBB permeability. However, in contrast to the constitutive loss of Pdgfb, adult-induced loss does not lead to vessel dilation, impaired arterio-venous zonation or the formation of microvascular calcifications. We conclude that PDFGB expression in quiescent adult microvascular brain endothelium is critical for the maintenance of pericyte coverage and normal BBB function, but that microvessel dilation, rarefaction, arterio-venous skewing and calcification reflect developmental roles of PDGFB.

Background: The burden caused by chronic pain is significant, affecting at least 10 percent of the world ' s population. While internet-based treatments based on cognitive behavioral therapy (CBT) have been shown to be promising in this area, attrition levels vary significantly. The purpose of this study was to investigate predictor variables for participants' adherence to an internet-based CBT treatment for individuals with chronic pain as well as to investigate associations between adherence and treatment outcome.

Methods: Data for this study was retrieved from a randomized controlled trial including 95 individuals with chronic pain who received internet-based CBT. Treatment adherence was studied through three outcome variables: treatment progress, treatment completion and exercise completion. The predictor variables were grouped into four clusters: background variables (age, gender, marital status, level of education, and typical computer usage); the second cluster included health status variables (sick leave, current psychiatric diagnosis, previous psychotherapy for pain, current pharmacological treatment, previous depression, current depression, and current depressive symptoms); the third cluster included pain-related variables (opioid medication, history of pain, and pain symptoms) and the fourth cluster included motivation variables (measured with treatment preference, treatment credibility, compliance to the treatment schedule and contact with the therapists).

Results: Findings showed that treatment progress was predicted by higher treatment credibility at baseline, whereas participants who were behind schedule in the second week of the program finished fewer treatment modules. When analyzing each cluster of predictor variables separately, current depressive symptoms also predicted fewer completed treatment modules. Among the pain-related variables, higher pain acceptance was the only predictor for completing more treatment modules. Treatment completion (which in this study was defined as having completed at least 75% of treatment modules) was predicted by higher treatment credibility and fewer depressive symptoms at baseline, and was thus similar to the results regarding treatment progress. Finally, all adherence variables predicted the treatment outcome pain interference.

Conclusions: Low treatment credibility, depressive symptoms and falling behind the treatment schedule early on were the most important predictor variables for low treatment adherence, while a number of demographical and pain-related variables were not related to adherence. The results from this study may help clinicians identify patients who are less likely to complete, and thus benefit from, their pain treatment. Trial registration ClinicalTrials.gov NTC03316846.

Comorbid psychological problems are commonly related to chronic pain but addressing heterogeneous comorbidities in traditional settings is often difficult. Delivering individually tailored treatment using the internet could be a viable alternative. The present study investigates whether a guided, individually tailored and internet-delivered cognitive behavioral therapy (ICBT) could improve mood and reduce disability in individuals suffering from chronic pain and comorbid psychological distress. Participants were recruited from a pain clinic and randomized to either ICBT or waiting list. The participants (n = 187) individually tailored treatments included 6-13 modules targeting different types of psychological distress. Modules were designed to be completed weekly, and feedback was provided by clinicians. Participants completed an average of 5.1 (49.7%) modules, with 22.9% completing all assigned modules. Intention-to-treat analyses showed significantly larger improvements in depression, disability, pain acceptance, catastrophizing, and quality of life in the ICBT-group compared to the control group. Between-group effect sizes were very small or small at post for the primary outcomes depression (d = 0.18) and pain interference (d = 0.22). Other effect sizes ranged from very small to small, with the largest effect being improvements in pain acceptance (d = 0.3). All significant changes were stable at 12-month follow up.

The integration of single-layer graphene with diamond substrates offers a promising platform for highperformance electronic devices by utilizing the exceptional properties of both materials. This study describes a fabrication process and transport measurements of single-layer graphene devices on diamond substrates featuring two surface terminations: hydrogen (H-terminated, thermal process) and oxygen (O-terminated, plasma treatment). The carrier transport properties were investigated using Hall effect measurements over a broad temperature range (80-400 K) under high-vacuum conditions (1 x 10^-4 mbar). Our findings reveal that thermal annealing significantly improves the graphene-diamond interface quality, causing a notable increase in carrier mobility for devices on both H- and O-terminated from 1439 to 1644 cm²/Vs and from 1238 to 1340 cm²/Vs, respectively. We also found that the effect of remote interfacial phonon scattering on high-temperature mobility is affected by the termination type. These findings highlight the importance of substrate surface engineering and offer a pathway for optimizing graphene-diamond heterostructures for advanced electronic applications.

This study investigates the impact of temperature variations on the photoelectrical detection ofmagnetic resonances (PDMR) in nitrogen-vacancy (NV) ensembles within single-crystalline, CVD-grown diamond, spanning temperatures from 77 K to 395 K. It is demonstrated that the chargecollection efficiency is sufficient for performing PDMR across this temperature range. Recognizingthe influence of defect states on the photoelectric detection, we utilize a 561-nm laser to reducephotoionization of P1 defects, thereby optimizing sensitivity. Our findings indicate that PDMR isa promising alternative to optically detected magnetic resonance, which can meet the requirementsfor miniaturization and high sensitivity in quantum sensing applications over a wide temperaturerange.

Graphene on diamond has emerged as a promising platform for various electronic applications. This brief review article explores the recent advancements and the potential of graphene on diamond for electronic applications with a focus on single-crystal (SC) chemically vapor-deposited and high-pressure and high-temperature diamond. Device fabrication techniques, properties, and performance of single-layer graphene on diamond in various electronic devices are discussed. This hybrid system's challenges and prospects are also analyzed. A particular emphasis is placed on the unique benefits of diamond as a substrate for graphene and its growth, including its high thermal conductivity, mechanical strength, high optical phonon energy, and the importance of achieving high-quality single-layer graphene on SC diamond.

The high current-carrying capacity of graphene is essential for its use as an interconnect in electronic and spintronic circuits. At the same time, knowing the breakdown limits and mechanism under high fields can enable new device design strategies. In this work, we push the current carrying capacity of the scalable form of chemical vapor deposited (CVD) graphene employing a high-thermal conducting single crystalline diamond substrate. Our experiments on CVD graphene reveal extremely high current densities > 10⁹ A/cm² in graphene on the diamond with both ohmic (low-resistive) and tunneling tunnel (high-resistive) contacts. Measurements on ferromagnetic (TiO_x/Co) and metallic (Ti/Au) contacts demonstrate current densities of ∼1.16×10⁹ A/cm² and ∼1.7×10⁹ A/cm², respectively. The tunnel (high-resistive) contacts exhibit a shunting of graphene under high currents via the bottom graphitized diamond, resulting in dielectric breakdown and via alternative conducting paths. Electrical measurements show a distinct threshold for conducting paths of graphitized diamond, in tune accordance with Middleton-Wingreen's theory. Our results of high current densities achieved in CVD graphene, with distinct dependence on ohmic and tunneling, contact resistance, and the observed breakdown mechanism, provide new insights for enabling high-current all carbon circuits.

The outstanding electronic properties of graphene make this material a candidate for many applications, for instance, ultra-fast transistors. However, self-heating and especially the detrimental influence of available supporting substrates have impeded progress in this field. In this study, we fabricate graphene-diamond heterostructures by transferring graphene to an ultra-pure single-crystalline diamond substrate. Hall-effect measurements were conducted at 80 to 300 K on graphene Hall bars to investigate the charge transport properties in these devices. Enhanced hole mobility of 2750 cm(2) V-1 s(-1) could be observed at room-temperature when using diamond with reduced nitrogen (N-s(0)) impurity concentration. In addition, by electrostatically varying the carrier concentration, an upper limit for mobility is determined in the devices. The results are promising for enabling carbon-carbon (C-C) devices for room-temperature applications.

Although theoretical investigations indicate that the successful combination of graphene and diamond would give interesting properties, only a limited number of reports dealing with the subject have been published. Here, we present a rapid thermal process (RTP) which involves nickel (Ni) as metal catalyst for a direct growth of graphene on diamond at a temperature of 1073 K for 60 s. This process operates with a combination of a lower temperature and for a shorter duration than what has previously been reported. Thin Ni films of different thicknesses were deposited on top of (100) single-crystalline diamond. After RTP, the coverage of monolayer graphene was found to be around 20% shown by the intensity ratio between the 2D- and G-peak using Raman spectroscopy on 50 nm thick Ni films. In addition, x-ray photoelectron spectroscopy and atomic force microscopy analysis were conducted. For electrical characterization, Hall-effect measurements were performed at temperatures between 80 and 360 K.

As the world transitions to renewable electrification to reduce CO2 emissions, remote island electrification remains a challenge. Although some islands are connected to the grid, many still rely on fossil fuels for electricity generation. Several studies indicate that renewable energy sources, such as wave energy, have the potential to make these islands self-reliant because of their substantial power potential. However, research on the control of power electronics converters for these systems remains limited. This paper proposes isolated grid-forming control for island electrification to address this gap using a wave energy converter and an energy storage system. Resistive loading control is implemented to optimize the power absorption of the generator. The result illustrates the establishment of the required AC voltage and 50 Hz frequency in the island load, ensuring harmonics compliance with the recommended standards. Experiments were conducted to test and validate the operation of different converter controls. The results also demonstrate the converter's ability to black-start the island load and automatically transition the load current with varying loads in a few milliseconds. Furthermore, the power quality produced by the wave energy converter presents one of its significant challenges. Therefore, the performance of two distinct converter technologies was compared. The performance of the IGBT converter was evaluated against that of the SiC-based converter in terms of power quality. The study demonstrates that the use of SiC enhances power quality in all switching frequencies tested, achieving the most significant reduction of 78% in current THD and 92% in voltage THD at the 25 kHz switching frequency, thus validating its advantages for wave energy converter applications.

Understanding the electrically active defects and impurities in semiconductors, especially in intrinsic or unintentionally doped wide bandgap materials, still remains a challenge. Here, time-of-flight (ToF) measurement using a solid state light source (355 and 213 nm) was performed on intrinsic silicon carbide and single-crystalline diamond. The charge transient spectroscopy (QTS) and the inverse Laplace (IL) QTS methods were applied to analyze the ToF results. Using these methods, we were able to trace the existing impurities in both materials. However, ILQTS proved to be more sensitive, with higher resolution for detection of existing multiple defects. The results suggest that this system can successfully be employed to investigate electrically active impurities at different energy states in highly resistive and undoped materials.

Mosquito larvae of the genus Anopheles develop entirely in water, frequently visiting the surface for air. The aquatic environment plays a key role in shaping their microbiota, but the connection between environmental characteristics of breeding sites and larval microbiota remains underexplored. This study focuses on Anopheles arabiensis, which inhabits the surface microlayer (SML) of breeding sites, a zone with high particle density. We hypothesized that the SML could allow us to capture the diversity of the surrounding environment, and in turn its influence on the larval microbial communities. To test this, we collected A. arabiensis larvae and SML samples from various breeding sites categorized by environmental features. Our results confirm that breeding site characteristics are significant drivers of the bacterial species present in mosquito larvae. Additionally, we found that the larval micro-environment selectively shapes its microbiota, highlighting a dynamic interplay between environmental and internal factors. Interestingly, specific bacterial families were associated with the presence or absence of larvae in breeding sites, suggesting potential ecological roles. These findings expand our understanding of vector-mosquito microbiota, emphasizing the importance of breeding site features in shaping larval microbial communities and providing a foundation for future research on mosquito ecology and control strategies. Environmental characteristics of the breeding site are an important factor in shaping the microbiota of mosquitoes of the genus Anopheles.

Mosquito behavior is a major aspect of vector ecology. Their host seeking is tightly linked to their capacity to interact with different hosts and act as vectors of etiological agents. Evidence suggests that host seeking is determined by genetic factors, such as olfactory genes re-arrangements. Simultaneously, mosquito-associated microbiota is increasingly recognized as a particularly sensitive descriptor of ecological variation. In this study, we investigated microbial communities of host-seeking females of the malaria vector, Anopheles arabiensis, linked to their host preference, and whether mosquitoes attracted to the same host display more similar microbiota profiles. Beta-diversity analysis showed no clear clustering of microbial communities by host choice, collection site, or time of collection. However, alpha-diversity measures revealed that cattle-seeking mosquitoes from one of the two villages consistently displayed higher richness and evenness than human-seeking ones. This difference was associated with the presence of several unique taxa, suggesting that environmental factors, such as livestock abundance, can shape microbial profiles of adult host-seeking mosquitoes. We hypothesize a possible mechanism to explain our observations, namely that repeated feeding on cattle increases exposure to a broader microbial reservoir, which may be transiently acquired at first and their presence be reinforced through processes, such as accumulation in breeding habitats. Overall, our findings highlight, consistently with existing literature, that mosquito microbiota is structured by a hierarchy of influences. Conserved core taxa, and localized and specific environmental-related factors all converge into creating microbial communities, which carry traces of the recent life-history of a whole mosquito population.

Leafhoppers (Hemiptera: Cicadellidae) are important vectors of plant pathogens in agricultural systems. Biological control via parasitisation is a key management strategy, but little is known about how microbial symbionts mediate host-parasitoid interactions. Here, we characterise the bacterial communities of six Cambodian leafhopper species (Cofana spectra, Exitianus sp., Goniagnathus punctifer, Maiestas dorsalis, Nephotettix virescens, and Stirellus sp.) and their parasitoids from the families Dryinidae (Hymenoptera) and Halictophagidae (Strepsiptera). We found that the bacterial symbiont Sulcia dominates cicadellid microbiotas, often coexisting with secondary symbionts. For example, Nasuia is present alongside Sulcia in Nephotettix, while Wolbachia is prevalent in Exitianus and Goniagnathus. Parasitoids exhibited distinct microbiotas with greater diversity; Rhodobacteraceae and Comamonadaceae were in dryinids, while Wolbachia was common in Halictophagidae. We analysed the microbiota of individual pairs of host-parasitoid and although parasitism did not significantly alter cicadellid overall microbiotas, some secondary symbionts (e.g., Arsenophonus, Wolbachia, Rickettsia, and Sodalis) were detected in both hosts and parasitoids, suggesting possible microbial transmission that warrants further investigation. These findings improve our understanding of host-parasitoid microbial interactions and highlight the relationship between primary and secondary symbiont communities.

Normalizing 16S amplicon data for library size variation is a crucial step to ensure unbiased results. While rarefaction is widely used and considered an acceptable way of normalizing data, it does however require choosing a threshold at which to rarefy the data. Our aim is to provide an effective tool to allow users to consistently select the best threshold for their data, evaluating sample inclusion to not discard useful data. To do that, the Sibyl package was developed. It provides a convenient way of selecting a range of rarefaction thresholds according to accumulation curves, and evaluating their effect on ordination results. Clustering according to variables of interest is evaluated through the Calinski-Harabasz Index allowing to discern degradation of ordination patterns. The package can be used to analyze data across a wide range of conditions.

Background and aims:

Fibromyalgia (FM) is characterized by chronic widespread pain and affects approximately 1-3% of the general population. Respiratory function has not been given much consideration in people with FM. Few studies have been published concerning FM and respiratory function and conflicting data still exist. The aim of this study was to compare differences in forced expiration, but also to investigate chest expansion, spinal mobility and segmental pain intensity between a group with fibromyalgia and heal thy controls.

Methods:

Forty-one women with diagnosed FM based on American College of Rheumatology 1990 criteria and forty-one controls without pain matched for age and gender participated in this cross-sectional study. For evaluation of forced expiration, a Wright peak expiratory flow rate meter was used. A tape measure was used to measure the mobility of the thorax at maximum inhalation and exhalation known as chest expansion. Spinal mobility was measured with the Cervico-thoracic ratio method. The spinal mobility was measured as range of motion from C7 to 15 cm below in flexion and manual palpation was conducted between C7-T5. For differences in pain intensity a palpation-index was defined for each level, respectively; C7-T1, T1-2, T2-3, T3-4 and T4-5 by calculating the mean value for the four different palpation points for each motion segment. A combined measure of expiration and thoracic mobility (expiratory/inspiratory ratio) was calculated by dividing peak expiratory flow rate (L/min) with chest expansion (cm). Statistical analyses included descriptive statistics to describe subjects and controls, means and standard deviation to compare differences between groups and student-t and Chi-square (chi(2)) tests, using SPSS 22 software. Confidence interval was set to 95%.

Results:

In the FM group 17 had the diagnosis for more than 5 years and 24 less than 5 years. The FM group demonstrated significantly lower forced expiration (p < 0.018), less thoracic expansion (p < 0.001), reduced spinal mobility (p < 0.029), higher expiratory-inspiratory ratio value (p < 0.001) and increased palpation pain over C7-T5 (p < 0.001) compared to healthy controls. There were more smokers in the FM group (n = 9) compared to the controls (n = 5) though this difference was not statistically significant (p < 0.24) and excluding the few smokers yielded similar result. No significant correlations for manual palpation, chest expansion, peak expiratory flow rate and spinal mobility were found in the FM group.

Conclusions:

Women with FM demonstrated significantly lower forced expiration and thoracic mobility compared to healthy controls.

Implications:

The results of this study point to a plausible restriction of respiratory function which in turn may have effect on physical endurance and work capacity in people with FM.

Objectives: The purpose of this study was to investigate whether people with fibromyalgia (FM) have dysfunctional breathing by examining acid-base balance and comparing it with healthy controls.

Methods: Thirty-six women diagnosed with FM and 36 healthy controls matched for age and gender participated in this cross-sectional study. To evaluate acid-base balance, arterial blood was sampled from the radial artery. Carbon dioxide, oxygen, bicarbonate, base excess, pH and lactate were analysed for between-group differences. Blood gas analyses were performed stepwise on each individual to detect acid-base disturbance, which was categorized as primary respiratory and possible compensation indicating chronicity. A three-step approach was employed to evaluate pH, carbon dioxide and bicarbonate in this order.

Results: Women with FM had significantly lower carbon dioxide pressure (p = 0.013) and higher lactate (p = 0.038) compared to healthy controls at the group level. There were no significant differences in oxygen pressure, bicarbonate, pH and base excess. Employing a three-step acid-base analysis, 11 individuals in the FM group had a possible renally compensated mild chronic hyperventilation, compared to only 4 among the healthy controls (p = 0.042).

Conclusions: In this study, we could identify a subgroup of individuals with FM who may be characterized as mild chronic hyperventilators. The results might point to a plausible dysfunctional breathing in some women with FM.

The objective of this study was to investigate respiratory parameters, including minute ventilation, tidal volume,and respiratory rate, and the role of thoracic mobility in women with FM compared to healthy controls. Thiscase-control study included 38 women with fibromyalgia and 44 age-matched healthy women. Respiratory ratewas measured using a portable monitor and tidal volume was assessed through spirometry. The minute venti-lation was calculated by multiplying tidal volume by respiratory rate. Thoracic mobility was evaluated bymeasuring chest expansion. Pressure pain threshold was assessed over paraspinal muscles between C7-T7 byalgometry to evaluate pain sensitivity. Perceived stress was assessed using the questionnaire Perceived StressScale  10. Women with fibromyalgia exhibited significantly higher minute ventilation (p<0.032), respiratoryrate (p<0.001), and lower tidal volume (p<0.001) compared to healthy controls. Thoracic mobility was reducedin participants with fibromyalgia. Group differences in minute ventilation disappeared when adjusting forperceived stress, suggesting a psychological influence on respiratory parameters. However, differences in res-piratory rate and tidal volume were still significant. Fibromyalgia is associated with altered breathing function,including higher respiratory rate and lower tidal volume. Thoracic mobility and stress may contribute to thesechanges.Perspective: Compared to healthy controls, women with fibromyalgia exhibit an altered breathing pattern whichconsists of higher minute ventilation due to increased respiratory rate. Reduced thoracic mobility and perceivedstress may contribute to this condition. Including the respiratory system in the evaluation and treatment mayoptimize the effects of rehabilitation.Trial registration number: ClinicalTrials.gov: NCT04098731.

Reaching sub-millisecond 3D tracking of individual molecules in living cells would enable direct measurements of diffusion-limited macromolecular interactions under physiological conditions. Here, we present a 3D tracking principle that approaches the relevant regime. The method is based on the true excitation point spread function and cross-entropy minimization for position localization of moving fluorescent reporters. Tests on beads moving on a stage reaches 67 nm lateral and 109 nm axial precision with a time resolution of 0.84 ms at a photon count rate of 60 kHz; the measurements agree with the theoretical and simulated predictions. Our implementation also features a method for microsecond 3D PSF positioning and an estimator for diffusion analysis of tracking data. Finally, we successfully apply these methods to track the Trigger Factor protein in living bacterial cells. Overall, our results show that while it is possible to reach sub-millisecond live-cell single-molecule tracking, it is still hard to resolve state transitions based on diffusivity at this time scale.

The bacterial chaperone Trigger factor (TF) binds to ribosome-nascent chain complexes (RNCs) and cotranslationally aids the folding of proteins in bacteria. Decades of studies have given a broad, but often conflicting, description of the substrate specificity of TF, its RNC-binding dynamics, and competition with other RNC-binding factors, such as the Signal Recognition Particle (SRP). Previous RNC-binding kinetics experiments were commonly conducted on stalled RNCs in reconstituted systems, and consequently, may not be representative of the interaction of TF with ribosomes translating mRNA in the cytoplasm of the cell. Here, we used single-particle tracking (SPT) to measure TF binding to actively translating ribosomes inside living Escherichia coli. In cells, TF displays distinct binding modes—longer (ca 1 s) and shorter (ca 50 ms) RNC bindings. Consequently, we conclude that TF, on average, stays bound to the RNC for only a fraction of the translation cycle. Further, binding events are interrupted only by transient excursions to a freely diffusing state (ca 40 ms), suggesting a highly dynamic binding and unbinding cycle of TF in vivo. We also show that TF competes with SRP for RNC binding, and in doing so, tunes the binding selectivity of SRP.

Outer-membrane proteins (OMPs) embedded in the outer membrane (OM) of gram-negative bacteria are important for the rigidity, mobility, pathogenicity, and the selective permeability of the cell. Most OMPs share a common structure and biogenesis pathway, where the unfolded OMP is post-translationally translocated from the cytoplasm to the periplasm, with subsequent folding and insertion into the OM. In vitro studies on the targeting, translocation and folding of OMPs have proven challenging due to difficulties in reconstituting the physical and biological complexity of the biogenesis network, while commonly used in vivo methods suffer from low temporal resolution. Here, we investigate the possibility of using single-molecule FRET to directly observe the folded state of Outer-membrane protein A (OmpA) in live cells. In vitro double-labeled Cy3Cy5-OmpA was incorporated into Escherichia coli by electroporation. Using single-molecule tracking (SMT), we observed both cytosolic and immobilized, membrane-associated particles. On rare occasion, immobile particles displayed FRET, indicative of successful folding and OM incorporation of Cy3Cy5-OmpA. This work lays the foundation for combining SMT and smFRET for direct measurements of the complete targeting, translocation and folding pathway of OMPs at high spatiotemporal resolution in their native environment.

In this article we study the properties of preprojective algebras of representation finite species. To understand the structure of a preprojective algebra, one often studies its Nakayama automorphism. A complete description of the Nakayama automorphism is given by Brenner, Butler and King when the algebra is given by a path algebra. We partially generalize this result to the species case, i.e. we manage to describe the Nakayama automorphism up to an unknown constant.

We show that the preprojective algebra of a representation finite species is an almost Koszul algebra. With this we know that almost Koszul complexes exist. It turns out that the almost Koszul complex for a representation finite species is given by a mapping cone of a certain chain map. We also study a higher dimensional analogue of representation finite hereditary algebras called d-representation finite algebras. One source of $d$-representation finite algebras comes from taking tensor products. By introducing a functor called the Segre product, we manage to give a complete description of the almost Koszul complex of the preprojective algebra of a tensor product of two species with relations with certain properties, in terms of the knowledge of the given species with relations. This allows us to compute the almost Koszul complex explicitly for certain species with relations more easily.