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BACKGROUND: Bacterial translocation from the gut has been suggested to induce a systemic inflammatory response syndrome (SIRS) and organ dysfunction. The liver has a pivotal role in eliminating circulating bacteria entering from the gut. We investigated whether pre-existing inflammation affects hepatic bacterial elimination.

METHODS: Fifteen anaesthetised piglets were infused with E. coli in the portal vein for 3 h. The naive group (n = 6) received the bacterial infusion without endotoxin exposure. SIRS (SIRS group, n = 6) was induced by endotoxin infusion 24 h before the bacterial infusion. For effects of anaesthesia, controls (n = 3) received saline instead of endotoxin for 24 h. Bacterial counts and endotoxin levels in the portal and hepatic veins were analysed during bacterial infusion.

RESULTS: The bacterial killing rate was higher in the naive group compared with the SIRS group (p = 0.001). The ratio of hepatic to portal venous bacterial counts, i.e. the median bacterial influx from the splanchnic circulation, was 0.06 (IQR 0.01-0.11) in the naive group and 0.71 (0.03-1.77) in the SIRS group at 3 h, and a magnitude lower in the naive group during bacteraemia (p = 0.03). Similar results were seen for hepatic endotoxin elimination. Peak log tumour necrosis factor alpha was higher in the naive 4.84 (4.77-4.89) vs. the SIRS group 3.27 (3.26-3.32) mg/L (p < 0.001).

CONCLUSIONS: Our results suggest that hepatic bacterial and endotoxin elimination is impaired in pigs with pre-existing SIRS while the inflammatory response to bacterial infusion is diminished. If similar mechanisms operate in human critical illness, the hepatic elimination of bacteria from the gut could be impaired by SIRS.

BACKGROUND: Sepsis-induced immunosuppression impairs bacterial clearance and increases mortality. Liver and spleen macrophages are an essential part of the mononuclear phagocyte system and crucial for bacterial elimination. Systemic inflammation hampers bacterial clearance in the liver. We hypothesized that immunosuppression due to systemic inflammation might lead to decreased bacterial clearance by the spleen.

METHODS: Anesthetized pigs were subjected to an E. coli infusion for three hours in an intensive care setting. The Naive group only received the bacterial infusion (n = 10). The ETX group (n = 10) received an endotoxin infusion for 24 h, inducing systemic inflammation before the E. coli infusion. The Control group (n = 3) received saline instead of endotoxin for 24 h to study the effects of anesthesia alone. Bacterial counts and endotoxin levels were analyzed during the E. coli infusion. The levels of IL-6 and TNF were analyzed, and the piglets' physiological response was evaluated.

RESULTS: There was no difference in the bacterial counts in the artery, splenic vein or hepatic vein. However, the splenic venous to arterial bacterial counts ratio at 1-3 h was lower in Naive compared to ETX group (0.54 (0.34-1.07), 0.54 (0.20-0.85), 0.52 (0.21-0.64) vs. 0.77 (0.61-1.06), 0.85 (0.63-0.89), 0.74 (0.53-0.88); p < 0.01), but there was no difference in the animals' blood ex vivo bactericidal capacity. There was no difference in endotoxin clearance in the spleen between the groups. The peak log IL-6 and TNF levels in response to the E. coli infusion were higher in the Naive compared to the ETX group (3.40 ± 0.41 vs. 2.94 ± 0.43 pg × mL^-1 and 3.78 ± 0.68 vs. 2.23 ± 0.36 pg × mL^-1; p < 0.05 and p < 0.001, respectively). The respiratory, circulatory and metabolic response to the E. coli infusion was dampened in the animals pre-exposed to endotoxin.

CONCLUSION: The splenic bacterial clearance is impaired by pre-existing systemic inflammation, while differences in endotoxin elimination were not detected. The inflammatory and physiological response to bacteremia is diminished during ongoing inflammation. Since the animals' ex vivo bactericidal capacity was not affected by pre-existing inflammation, our results suggest that inherent mechanisms in the spleen were involved.

Introduction

The liver is essential for bacterial elimination, preventing intestinal bacteria from entering the systemic circulation, and for producing inflammatory cytokines. Glucocorticoids have been reported to exert heterogeneous effects on bacterial clearance in sepsis. Using a porcine model of gram-negative abdominal sepsis, we investigated how portal venous administration of budesonide, a glucocorticoid with extensive hepatic first-pass metabolism, affects hepatic bacterial and endotoxin elimination as well as the systemic inflammatory response, in comparison with systemic administration and no treatment.

Methods

The Portal Steroid-Sepsis (Sep-Port, n = 8) and Systemic Steroid-Sepsis (Sep-Syst, n = 8) groups were administered budesonide in the portal vein or systemically, followed by an E. coli infusion for 3 h in the portal vein. The Septic Controls (Sep-Ctrl, n = 8) received saline instead of budesonide. Non-septic Controls (NSep-Port, n = 3) were treated only with portal budesonide. Portal, arterial, and hepatic venous bacterial counts were analyzed hourly during the bacterial infusion. The levels of endotoxin and inflammatory cytokines were measured.

Results

There was no difference in hepatic/portal venous bacterial count ratios. However, the arterial and hepatic venous bacterial counts were higher in the Sep-Syst compared to Sep-Port group (p < 0.001 and p < 0.01, respectively), while microbiological findings were similar in the Sep-Port and Sep-Ctrl groups. Hepatic endotoxin elimination did not differ between the groups. IL-10 levels were higher in the Sep-Port compared to the Sep-Syst group at 1 h (p < 0.01), and IL-6 levels were lower in the Sep-Port compared to the Sep-Ctrl after the bacterial infusion (p < 0.05).

Conclusions

In this experimental sepsis model, hepatic bacterial elimination was unaffected by portal or systemic budesonide, whereas systemic administration was associated with increased systemic bacterial levels. Endotoxin clearance was unaffected by budesonide. Portal budesonide elicited a more pronounced anti-inflammatory response compared to systemic administration. These findings suggest that hepatic exposure to budesonide may modulate the inflammatory response while limiting adverse effects on systemic bacterial clearance.

Editorial Comment

Glucocorticoids are widely used in sepsis management, yet their effects on bacterial clearance is incompletely understood. In this porcine model of gram-negative abdominal sepsis, portal venous delivery of budesonide (which has ~90% hepatic first-pass metabolism) preserved bacterial elimination and enhanced the early anti-inflammatory response, without the increase in systemic bacterial levels seen with systemic administration. These results demonstrate that route of delivery as a potentially important determinant of the risk-benefit balance of glucocorticoid therapy in sepsis, and support further investigation of hepatic-targeting strategies.

Background: Tachycardia associated with active tuberculosis (TB) often diminishes when patients recover from TB. Elevated heart rate (HR) may lead to suboptimal correction, complicating the assessment of QT prolongation when using standard correction factors (CFs), such as Fridericia's formula (QTcF). Olliaro has proposed a CF for QT interval correction in pretreatment TB patients. However, the QT-HR correlation changes as HR decreases during treatment, indicating the need for time-varying correction.

Methods: We developed an HR model to capture the HR normalisation during successful treatment. Subsequently, a time-varying CF was constructed using the estimated HR change rate. The performance of CFs to make corrected QT (QTc) independent from HR was evaluated by linear regression analyses of QTc versus HR within defined time bins.

Results: The final HR model included asymptotic change in HR attributed to time on treatment, circadian rhythm cycles, M2 (bedaquiline-metabolite) concentration, and patient covariates. The time-varying CF decreased from 0.4081 to 0.33, with a half-life of 7.74 weeks. The slope (QTc/HR vs. Time) derived from the time-varying correction was not significantly different from 0 (95% CI -0.003 to 0.002), and the intercept was not significantly different from 0 (95% CI -0.089 to 0.006), demonstrating successful QT correction from pretreatment to the end of treatment.

Conclusion: The time-varying CF effectively captures the dynamic QT-HR relationship during TB treatment, reducing the risk of misdiagnosing QT prolongation or unnecessary discontinuation of treatment. By addressing underestimation and overestimation issues in QT interval assessment, this method enhances drug evaluation in clinical trials and supports improved treatment decisions for TB patients. (c) 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Evaluating QT prolongation induced by anti-tuberculosis (TB) drugs in patients with active TB, who often experience tachycardia, is challenging due to the limitations of Fridericia's correction factor (QTcF) in decorrelating QTc from heart rate (HR). Previous exposure-QTcF analyses in patients with active TB were able to alleviate the limitation of QTcF but required advanced model-based methodologies, incorporating a non-drug-related, "secular" trend in the model to dissociate drug and non-drug-related effects on QT. Recently, we developed and validated a time-varying QT correction method (QTcTBT) that more accurately accounts for the HR changes during TB treatment. In the present work, using data from 429 patients with multidrug-resistant TB across two Phase IIb trials, we re-evaluated the exposure-QTc relationship for bedaquiline by applying QTcTBT instead of QTcF. Our analysis showed that when HR changes were accounted for using QTcTBT, a typical maximum M2 (bedaquiline metabolite) concentration (326 ng/mL, mean maximal concentration (Cmax) at the end of 2-week loading phase) was associated with a 7 ms QTc interval prolongation (90% CI: 5.9-8.2). This estimate closely aligns with the previously reported M2 effect of 7.9 ms (90% CI: 6.8-9.3), derived from the exposure-QTcF model. The consistency between the two methodologies further supports the use of QTcTBT for estimating the QTc prolongation effects of anti-TB drugs.

Background and Objectives

The use of the 12-dose, once-weekly, rifapentine-based (3HP), short-course tuberculosis preventive treatment (TPT) in children has been limited due to a lack of child-friendly rifapentine formulations. In this study, we compared the relative bioavailability of rifapentine and isoniazid when suspended in water versus whole tablets, using generic adult formulations.

Methods

We assessed the relative bioavailability of non-dispersible rifapentine and isoniazid adult tablets suspended in water compared with whole tablets. Adults with a positive tuberculosis infection test were randomized 1:1:1 to receive two of three rifapentine/isoniazid formulations in separate treatment sequences, including two generic brands of fixed-dose combinations and standalone tablets of rifapentine and isoniazid. Participants received either whole tablets swallowed or tablets suspended in water at a dose of 900 mg for each drug once weekly over 12 weeks with intensive pharmacokinetic sampling up to 48 h post-dose. Nonlinear mixed-effects modelling was used to compare the relative bioavailability of suspended versus whole tablets, with 90% confidence intervals (CI) evaluated against the standard bioequivalence range (80–125%).

Results

In 24 participants, a one-compartment model described rifapentine data well. A two-compartment model with a mixture component for fast/intermediate and slow acetylators best described isoniazid. Rifapentine and isoniazid demonstrated similar bioavailability across all dosing forms, meeting formal bioequivalence criteria. The absorption rates for suspended tablets were faster than those for whole tablets by 22.2% (90% CI 12.4–30.8) for rifapentine and 35% (90% CI 26.1–42.6) for isoniazid.

Conclusion

Both rifapentine and isoniazid, whether in fixed-dose combinations or as standalone, showed similar bioavailability when administered as whole tablets or suspended in water. These findings support dosing in children and other populations without the need to adjust rifapentine or isoniazid doses, thereby supporting broader access to the 3HP regimen.

Pan African Clinical Trials Registry

PACTR202306775627089, registration date June 15, 2023.

Hybrid inviability is an important post-zygotic reproductive barrier between species, but emerging signs of reduced viability can be difficult to study across the lifespan of natural hybrids. We use a combination of long-term monitoring, extra-pair paternity, and mitochondrial DNA identification in a natural hybrid zone of Ficedula flycatchers to detect emerging signs of intrinsic hybrid inviability across their entire lifespan. We evaluate possible evidence of Darwin's corollary to Haldane's rule, predicting asymmetries in inviability between hybrids resulting from reciprocal crosses, due to incompatible genetic factors with sex-specific inheritance patterns. We found higher hatching failure among mixed-species pairs, possibly indicating early developmental impairments associated with specific parental genetic combinations. Adult hybrids had a higher basal mortality rate than both parental species and different age-specific mortality trajectories. There were signs of differences in age-independent mortality rates between the reciprocal hybrid crosses: hybrids with a pied flycatcher mother experienced slightly increased mortality later in life. Using an exceptional dataset with many natural hybrids tracked across life stages, we provide evidence for several emerging signs of reduced hybrid viability. Incompatibilities between alleles located on autosomes and uniparentally inherited factors such as Z-linked and/or mitochondrial genes are strong candidates underlying intrinsic hybrid dysfunction in this system.

Background:Healthcare-associated infections (HCAIs) have a large negative impact onmorbidity, mortality, and quality of life. Approximately 9% of all patients hospitalized inSweden suffer from HCAI. Hand hygiene plays a key role and is considered the single mostimportant measure to reduce HCAI. The hospital organization works actively to reduceHCAI. Implementing electronic systems to remind and/or notify healthcare workers raisesawareness of and adherence to hand hygiene. However, there is a paucity of studiesaddressing individuals’ perceptions of having such a system and how the organizationworks.

Aim:To investigate healthcare workers’ perceptions of infection prevention in thehealthcare organization and perceptions and acceptance of an electronic reminder systemthat encourages good hand hygiene.

Methods:Qualitative descriptive design with data collected in eight focus group inter-views including assistant nurses, nurses, and physicians (N¼38). Content analysis wasapplied and data were related to the Theory of Planned Behaviour.

Findings:Healthcare workers perceive lack of feedback from the hospital organizationand are positive towards an electronic reminder system to increase adherence to handhygiene. The electronic reminder system should not register data at an individual levelsince it could be used as an instrument for control by the management that could bestressful for staff.

Conclusion:In general, there is positive acceptance of the electronic reminder system,and the respondents perceived it as having the ability to change behaviour. However, theconcept has to be further developed to protect the individual’s integrity and needs to beused with feedback on a group level

Aim

To determine the level of knowledge and explore the difference of hand hygiene between nursing students and nurses.

Background

Annually, 3.8 million people in Europe acquire healthcare-associated infections, highlighting the importance of hand hygiene. Despite WHO's emphasis on the fact that greater hand hygiene knowledge correlates with improved hand hygiene compliance, several studies have shown knowledge gaps among nurses and nursing students regarding hand hygiene.

Design

Descriptive cross-sectional comparative survey.

Methods

A version of the WHO “Hand Hygiene Knowledge Questionnaire”, translated into Swedish, was used for data collection among nursing students in the first and last semester, and registered nurses from a university and associated hospital. Data were analyzed by descriptive statistics, and comparison between groups with Fisher's exact test, one-way ANOVA, and post-hoc tests (Pairwise Z-Tests, Tukey HSD).

Results

The survey, conducted between December 2020 and January 2021, received responses from 201 participants, including 71 first semester students, 46 last semester students and 84 registered nurses, showing moderate (55.7% [50–74% correct answers]) to good (43.8% [75–100% correct answers]) knowledge levels. First-semester students scored lower (17.0 ± 2.1) than last-semester students (18.8 ± 1.8) and registered nurses (18.3 ± 2.1) out of 25 questions.

Discussion

It is necessary for all groups to receive proper education on hand hygiene knowledge and to have an educational program that does not separate the groups but combines them with continuing education, since the students will someday be influencing future hand hygiene knowledge as a peer, together with the nurse.

AimTo describe and compare attitudes toward hand hygiene and the perceived effectiveness of prevention methods among nursing students and registered nurses at a university and its affiliated university hospital.DesignA descriptive cross-sectional comparative survey.MethodsA total of 201 first- and final-semester nursing students and registered nurses completed the World Health Organisation's 'Perceptions Survey for Health-Care Workers'. The survey examined perceptions on hand hygiene, patient safety and the usefulness of improvement measures. Responses were analysed using descriptive statistics.ResultsNursing students consistently rated the importance of hand hygiene and related interventions higher than registered nurses. Students particularly emphasised the availability of hand disinfectants, ongoing education and supportive leadership. Both groups acknowledged the role of management support, regular feedback and organisational policies in reinforcing optimal hand hygiene.ConclusionDifferences in attitudes between nursing students and registered nurses underscore the need for ongoing education, strong managerial involvement and supportive policies to sustain adherence. Strengthening these factors can help maintain positive perceptions formed during training and enhance patient safety in clinical practice.Implications for the Profession and/or Patient CareEducational curricula and workplace strategies that prioritise hand hygiene may help lower healthcare-associated infections. Management-led feedback, continuous training and accessible hand hygiene resources offer additional support for safe patient care.ImpactWhat problem did the study address? Low adherence to hand hygiene is a key driver of preventable infections. What were the main findings? Nursing students rated hand hygiene and improvement measures more highly than registered nurses, highlighting a need for strategies that sustain positive attitudes during the transition from education to clinical practice. Who will benefit? Nurse educators, clinical leaders and healthcare workers can use these findings to improve infection prevention across educational and practice settings.Reporting MethodWe adhered to STROBE guidelines for cross-sectional research.Patient or Public ContributionNo patients or members of the public were involved in designing or conducting this study, which focused on perceptions of nursing students and registered nurses.

Background: Hand hygiene is a cornerstone of infection prevention and control and plays a critical role in preventing healthcare-associated infections. During the COVID-19 pandemic, hand hygiene awareness and adherence increased across healthcare systems, but evidence on whether these improvements were sustained as pandemic pressures subsided remains limited. Nursing students and registered nurses are key groups for understanding long-term behavioural changes, as their knowledge, perceptions, and workplace experiences influence patient safety practices.

Objective: To compare nursing students' and registered nurses' knowledge and perceptions of hand hygiene at two time points: during the peak of the COVID-19 pandemic in 2020 and in the post-pandemic period in 2023.

Design: Comparative cross-sectional survey study conducted at two time points (2020 and 2023).

Setting: A Swedish university and its affiliated university hospital. Participants: A total of 376 individuals: first-semester nursing students, final-semester nursing students, and registered nurses surveyed in 2020 (n = 201) and 2023 (n = 175).

Methods: This study employed a two-time point, independent-sample design. Data were collected online using two validated World Health Organization instruments: the Hand Hygiene Knowledge Questionnaire for Health Care Workers and the Perception Survey for Health Care Workers. Descriptive statistics were computed for all variables. Comparisons between 2020 and 2023 were performed using the Mann-Whitney U test for ordinal variables and Fisher's exact test for categorical variables.

Results: Total knowledge scores did not differ significantly between time points. However, first-semester students had lower knowledge of transmission routes and preventive actions in 2023. Perceptions of hand hygiene differed between time points. The mean score for perceived importance of hand hygiene as a patient safety measure was significantly lower in 2023 than in 2020 for first-semester students (3.77 vs 3.30, p < 0.001), final-semester students (3.61 vs 2.89, p < 0.001), and registered nurses (3.39 vs 3.19, p = 0.041). Perceived patient expectations about hand hygiene were also lower among nursing students, and registered nurses rated perceived hand hygiene adherence among healthcare workers lower in 2023. By contrast, first-semester students reported higher ratings of educational support and tolerance of alcohol-based hand rubs in 2023.

Conclusions: The findings indicate group-level differences in hand hygiene perceptions between the pandemic-period and post-pandemic samples, while total knowledge scores did not differ significantly within any participant group. Given the independent-sample design, these findings should not be interpreted as individual-level changes over time. Lower perceived importance of hand hygiene suggests a need for continued educational reinforcement and organisational support to maintain hand hygiene practices.

Transient permeation enhancers (PEs) have been widely used to improve the oral absorption of macromolecules. During pharmaceutical development, the correct selection of the macromolecule, PE, and the combination needs to be made to maximize oral bioavailability and ensure successful clinical development. Various in vitro and in vivo methods have been investigated to optimize this selection. In vitro methods are generally preferred by the pharmaceutical industry to reduce the use of animals according to the "replacement, reduction, and refinement" principle commonly termed "3Rs," and in vitro methods typically have a higher throughput. This paper compares two in vitro methods that are commonly used within the pharmaceutical industry, being Caco-2 and an Ussing chamber, to two in vivo models, being in situ intestinal instillation to rats and in vivo administration via an endoscope to pigs. All studies use solution formulation of sodium caprate, which has been widely used as a PE, and two macromolecules, being FITC-dextran 4000 Da and MEDI7219, a GLP-1 receptor agonist peptide. The paper shares our experiences of using these models and the challenges with the in vitro models in mimicking the processes occurring in vivo. The paper highlights the need to consider these differences when translating data generated using these in vitro models for evaluating macromolecules, PE, and combinations thereof for enabling oral delivery.

Oral delivery of therapeutic peptides is limited by degradation by digestive proteases and poor gastrointestinal permeability. We have investigated how physicochemical properties, including degree of lipidation and degree of amino acid sequence modification, along with formulation with a permeation enhancer (PE), influence the enzymatic stability and intestinal absorption of glucagon-like peptide-1(GLP-1) receptor agonists. We compared four peptides: J211 (non-lipidated; modified), J229 (mono-lipidated; modified), MEDI7219 (bis-lipidated; modified), and semaglutide (mono-lipidated control; least modified). J211, J229 and MEDI7219 have similar amino acid modifications in the peptide sequence to reduce the number of labile proteolytic sites. An in vitro head-to-head comparison between MEDI7219 and semaglutide showed that MEDI7219 was more proteolytically stable (% remaining after 90 min) than semaglutide, which was degraded completely within 10 min. Notably, co-formulation with sodium caprate (C10) improved semaglutide stability, and at least doubled its half-life. Results from in vivo studies in rats following intraduodenal bolus administration, showed that in the absence of C10, the absorption of all the peptides was minimal, with cumulative fractions absorbed below 1 % for all four compounds. Co-formulation with C10 increased the bioavailability of the modified peptides by 35-40-fold, with J211, J229, and MEDI7219 reaching 7.5 %, 4 %, and 17.3 % respectively. Semaglutide's bioavailability improved by similar to 200-fold, however bioavailability did not exceed 2 %. These results demonstrate that C10 enhances peptide absorption primarily by increasing intestinal permeability but also likely by improving enzymatic stability of a labile peptide like semaglutide. Furthermore, when comparing the three modified peptides, the degree of lipidation positively correlated with increased intestinal absorption in both the presence and absence of C10.

Oral peptide delivery increasingly relies on permeation enhancers (PEs), but how enhancer self-assembly couples to peptide self-assembly and co-assembly remains poorly understood. Here, we investigated the interactions between glucagon-like peptide-1 (GLP-1) analogues and the permeation enhancer sodium caprate (C10), with emphasis on how peptide lipidation and enhancer self-assembly control peptide availability for absorption. A non-lipidated analogue (J211), two mono-lipidated analogues (J229 and semaglutide), and a bis-lipidated analogue (MEDI7219) were characterized by 1H NMR spectroscopy, diffusion NMR, small-angle X-ray scattering (SAXS), circular dichroism (CD) and all-atom molecular dynamics (MD) simulations. In deuterated buffer, the peptides formed distinct oligomeric states with the size ranking semaglutide > J211 > J229 ≈ MEDI7219, while retaining predominantly α-helical secondary structure. C10 underwent a marked colloidal transition with the formulation conditions, forming non-spherical micelles at pD 8.5 and vesicular aggregates at pD 7.4 in fasted-state simulated intestinal fluid (FaSSIF-V2). Under alkaline micellar conditions, C10 associated with all peptides and remodeled the larger oligomers, J211 and semaglutide, by loosening peptide-peptide packing without major changes in global dimensions or helicity. Under near-neutral biorelevant conditions, peptide-C10 co-assembly became strongly peptide dependent. MEDI7219 showed the weakest association with C10 aggregates and retained the largest unbound fraction, whereas semaglutide and J229 had the most bound fraction. This ranking correlated to previously observed intestinal absorption ranking in vivo. These results show that peptide absorption is impacted by the coupled equilibria between peptide self-assembly, enhancer colloidal state, and peptide bound versus unbound fractions.

Lipidation is widely used to improve peptide pharmacokinetics; however, its influence on peptide–membrane interactions relevant to oral delivery requires further investigation. Here, we investigated how lipidation pattern, amino acid sequence, and peptide oligomeric state influence the interactions of four GLP-1 analogues with a model membrane composed of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC). The analogues comprised non-lipidated J211; mono-lipidated, acid-terminated J229 and semaglutide; and bis-lipidated, methyl-terminated MEDI7219. Quartz crystal microbalance with dissipation monitoring (QCM-D) was combined with molecular dynamics (MD) simulations to characterise peptide–membrane interactions.

QCM-D revealed distinct analogue-dependent interfacial responses, indicating that lipidation alone did not determine peptide–bilayer interactions. The non-lipidated analogue J211 produced the largest transient decrease in frequency and the greatest increase in dissipation, consistent with formation of a hydrated, mechanically soft, and largely reversible membrane-associated state. Interestingly, the mono-lipidated J229 produced a weaker and reversible response. In contrast, semaglutide and bis-lipidated MEDI7219 induced only small changes in frequency and dissipation, consistent with weak interactions but the membrane perturbation was retained under the studied conditions. In the presence of 2.5 mM sodium caprate (C10), peptide-specific responses were generally attenuated and shifted towards a C10-dominated membrane-perturbation profile, although analogue-dependent differences still remained.

MD simulations showed analogue-dependent membrane engagement, where interaction depth and interaction stability were influenced by lipidation and peptide sequence. MEDI7219 was found to insert itself deepest into the membrane leaflet with stable interactions between the peptide and the lipid bilayer. The lipid tail of semaglutide remained persistently inserted although not as deep as MEDI7219, whereas (the similarly monolipidated) J229 engaged more transiently and reversibly. The non-lipidated J211 only associated with the bilayer surface through aromatic and charged residues. Overall, the lipidated peptides perturbed the local membrane structure the most, providing a molecular-level context for the distinct experimental QCM-D responses.

Together, these findings demonstrate that peptide–membrane interactions are governed not by lipidation alone, but by the combined effects of lipidation pattern, backbone sequence, peptide association state, and formulation conditions. This work provides mechanistic insight relevant to the developability of orally delivered peptides.

Word embeddings have become an increasingly important class of models for analysis of textual data. We introduce probabilistic embeddings using Laplacian graph priors (PELP). The proposed model enables incorporating graph side-information into static word embeddings. We theoretically show that the model unifies several previously proposed embedding methods under one umbrella, such as graph-enhanced, group, dynamic, and cross-lingual static word embeddings.  Furthermore, we empirically show that our model matches or improves the performance of previous models that are special cases of the PELP model. PELP also enables any combination of these previous models in a  straightforward fashion for flexible modeling of textual data in a Bayesian fashion. We demonstrate the flexibility of using the graph-prior for embeddings by applying it to the comparison of political sociolects over time. Finally, we provide code as a TensorFlow implementation, enabling flexible and scalable estimation for settings with millions of documents.

We study Bayesian inference for probabilistic word embedding models, including skip-gram with negative sampling (SGNS) and continuous bag-of-words (CBoW). These models are widely used for inference, but their posteriors are non-identifiable under general linear transformations, which prevents meaningful Bayesian uncertainty quantification. We provide a simple and principled identifiability constraint that yields a well-defined posterior without altering the data model. Building on this, we develop scalable, fully Bayesian posterior sampling algorithms for SGNS and CBoW using Pólya–Gamma augmentation. Our block Gibbs samplers yield exact samples from the posterior and scale well to large corpora due to their straightforward parallelisation. We discuss the efficient implementation of the Gibbs sampler, and provide a fast TensorFlow reference implementation. In a combination of simulations and empirical experiments, we demonstrate that the sampler is both accurate and computationally efficient. It matches the accuracy of NUTS-HMC at a fraction of the computational cost and avoids the variance underestimation of mean-field variational inference. On large real datasets, we show that posterior means yield improved predictive performance, while posterior credible intervals provide meaningful uncertainty quantification for semantic similarity.

Data accuracy is crucial for reliable research, accurate decision-making, and high-performance machine learning.However, maintaining and improving data accuracy, especially at scale, is challenging and difficult to verify. By combining statistical quality control and branching process theory, we formalize an iterative data curation framework that scales well to large data sets. The framework is agnostic to the source and reliability of proposed data edits, allowing human annotators, automated rules, machine learning models, large language models, and external data sources to be combined within a common statistical process. We prove that under mild assumptions, the proposed iterative approach asymptotically eliminates all errors with probability one for both tabular and textual data.Additionally, we provide guarantees that data accuracy testing further accelerates error reduction. We corroborate these results through simulations on text and tabular data, as well as a real-world application, demonstrating the framework's effectiveness in improving the accuracy of data at scale.

The Swedish parliamentary records are an important source material for social science and humanities researchers. We introduce a new research corpus, the Swedish Parliament Corpus, which is larger and more developed than previously available research corpora for the Swedish parliament. The corpus contains annotated and structured parliamentary records over more than 150 years, through the bicameral parliament (1867–1970) and the unicameral parliament (1971–). In addition to the records, which contain all speeches in the parliament, we also provide a database of all members of parliament over the same period. Along with the corpus, we describe procedures to ensure data quality. The corpus facilitates detailed analysis of parliamentary speeches in several research fields.

In spiking neural networks (SNNs), the main unit of information processing is the neuron with an internal state. The internal state generates an output spike based on its component associated with the membrane potential. This spike is then communicated to other neurons in the network. Here, we propose a general multiple-input multiple-output (MIMO) spiking neuron model that goes beyond this traditional single-input single-output (SISO) model in the SNN literature. Our proposed framework is based on interpreting the neurons as state-space models (SSMs) with linear state evolutions and non-linear spiking activation functions. We illustrate the trade-offs among various parameters of the proposed SSM-inspired neuron model, such as the number of hidden neuron states, the number of input and output channels, including single-input multiple-output (SIMO) and multiple-input single-output (MISO) models. We show that for SNNs with a small number of neurons with large internal state spaces, significant performance gains may be obtained by increasing the number of output channels of a neuron. In particular, a network with spiking neurons with multiple-output channels may achieve the same level of accuracy with the baseline with the continuous-valued communications on the same reference network architecture.

Neuromorphic computing is an emerging technology enabling low-latency and energy-efficient signal processing. A key algorithmic tool in neuromorphic computing is spiking neural networks (SNNs). SNNs are biologically inspired neural networks which utilize stateful neurons, and provide low-bit data processing by encoding and decoding information using spikes. Similar to SNNs, deep state-space models (SSMs) utilize stateful building blocks. However, deep SSMs, which recently achieved competitive performance in various temporal modeling tasks, are typically designed with high-precision activation functions and no reset mechanisms. To bridge the gains offered by SNNs and the recent deep SSM models, we propose a novel multiple-output spiking neuron model that combines a linear, general SSM state transition with a non-linear feedback mechanism through reset. Compared to the existing neuron models for SNNs, our proposed model clearly conceptualizes the differences between the spiking function, the reset condition and the reset action. The experimental results on various tasks, i.e., a keyword spotting task, an event-based vision task and a sequential pattern recognition task, show that our proposed model achieves performance comparable to existing benchmarks in the SNN literature. Our results illustrate how the proposed reset mechanism can overcome instability and enable learning even when the linear part of neuron dynamics is unstable, allowing us to go beyond the strictly enforced stability of linear dynamics in recent deep SSM models.

Spiking neural networks (SNNs) are biologically inspired, event-driven models suited for temporal data processing and energy-efficient neuromorphic computing. In SNNs, richer neuronal dynamic allows capturing more complex temporal dependencies, with delays playing a crucial role by allowing past inputs to directly influence present spiking behavior. We propose a general framework for incorporating delays into SNNs through additional state variables. The proposed mechanism enables each neuron to access a finite temporal input history. The framework is agnostic to neuron models and hence can be seamlessly integrated into standard spiking neuron models such as Leaky Integrate-and-Fire (LIF) and Adaptive LIF (adLIF). We analyze how the duration of the delays and the learnable parameters associated with them affect the performance. We investigate the trade-offs in the network architecture due to additional state variables introduced by the delay mechanism. Experiments on the Spiking Heidelberg Digits (SHD) dataset show that the proposed mechanism matches existing delay-based SNNs in performance while remaining computationally efficient, with particular gains in smaller networks.

The identification and modeling of time-varying systems is a fundamental challenge in signal processing and system identification. To address this challenge, we propose a class of time-varying state-space model (SSM) based neural networks in which the neurons' states are governed by time-varying dynamics. The proposed model provides the learnable time-varying dynamics through a dictionary of basis functions, where each basis function evolves differently over time. We evaluate the proposed approach on both synthetic data from switching systems and a speech denoising task where real audio is corrupted with switching dynamics noise. The results show that the proposed time-varying model consistently outperforms its time-invariant counterparts while maintaining comparable computational complexity. Our investigations also reveal which aspects of the time-varying dynamics of the data most need to be captured by the proposed time-invariant models, how the additional freedom provided by time-varying basis functions should be allocated across model components, and to what extent larger models can compensate for time-invariant limitations.

Spiking Neural Networks (SNNs) are biologically-inspired deep neural networks that efficiently extract temporal information while offering promising gains in terms of energy efficiency and latency when deployed on neuromorphic devices. SNN parameters are sensitive to temporal resolution, leading to significant performance drops when the temporal resolution of target data during deployment is not the same as that of the source data used for training, especially when fine-tuning with the target data is not possible during deployment. To address this challenge, we propose three novel domain adaptation methods for adapting neuron parameters to account for the change in time resolution without re-training on target time resolution. The proposed methods are based on a mapping between neuron dynamics in SNNs and State Space Models (SSMs) and are applicable to general neuron models. We evaluate the proposed methods under spatio-temporal data tasks, namely the audio keyword spotting datasets SHD and MSWC, and the neuromorphic image NMINST dataset. Our methods provide an alternative to-and in most cases significantly outperform-the existing reference method that consists of scaling only the time constant. Notably, when the temporal resolution of the target data is double that of the source data, applying one of our proposed methods instead of the benchmark achieves classification accuracy of 89.5% instead of 53.0% on SHD, 93.6% instead of 38.8% on MSWC and 98.5% instead of 97.2% on NMNIST. Moreover, our results show that high accuracy on high temporal resolution data can be obtained by time-efficient training on lower temporal resolution data.

Rapid processing of tactile information is essential to human haptic exploration and dexterous object manipulation. Conventional electronic skins generate frames of tactile signals upon interaction with objects. Unfortunately, they are generally ill-suited for efficient coding of temporal information and rapid feature extraction. In this work, we report a neuromorphic tactile system that uses spike timing, especially the first-spike timing, to code dynamic tactile information about touch and grasp. This strategy enables the system to seamlessly code highly dynamic information with millisecond temporal resolution on par with the biological nervous system, yielding dynamic extraction of tactile features. Upon interaction with objects, the system rapidly classifies them in the initial phase of touch and grasp, thus paving the way to fast tactile feedback desired for neuro-robotics and neuro-prosthetics. 

Freshwater systems are shaped by hydrological connectivity, yet distinct microbial communities persist between lotic and lentic habitats. While bacterial biogeography across aquatic habitats has been widely explored, less is known about the spatiotemporal links of microeukaryotes to bacterial communities. Here, we investigated microbial diversity, rRNA-based activity and community assembly within a stream-lake network in Sweden under contrasting hydrological regimes. Using amplicon sequencing of both rRNA genes and transcripts, we found parallel patterns in bacterial and microeukaryotic alpha and beta diversity, with lower richness in lakes than in inlet streams. Bacterial phenotypic diversity, assessed by flow cytometry, captured biogeographic trends comparable to sequencing-based methods. Bacteria and microeukaryotes also appeared to be structured by similar assembly mechanisms, with environmental selection having a higher relative importance in lakes compared to streams. During low-flow periods, the catchment outlet became increasingly distinct from upstream communities, demonstrating dispersal limitation from lakes. Finally, phantom taxa, undetected in rRNA genes, were predominantly rare and exhibited disproportionately high RNA: DNA ratios compared to active taxa, underscoring the need for their careful handling. Our findings revealed habitat-driven microbial dynamics, despite pronounced seasonal shifts in hydrology. Combined RNA- and DNA-based 16S and 18S rRNA amplicon sequencing revealed covarying bacterial and microeukaryotic diversity and community assembly dynamics across an aquatic network in central Sweden.

Community coalescence occurs when entire microbial communities are introduced into new environments. In aquatic ecosystems, inflowing streams represent major pathways for microbial dispersal into lakes, where stream bacteria encounter and mix with resident lake communities. Tolerating novel environmental conditions is critical for establishment success, yet direct experimental evidence on how dispersed bacterial communities respond to lake abiotic conditions remains limited. Here, we conducted in vitro transplant experiments across three distinct hydrological contexts to test whether abiotic conditions constrain the establishment of stream bacteria following introduction into pelagic environments. Bacterial communities from five inlet streams were incubated in water from two downstream lakes, using dialysis bags that exposed communities to ambient lake conditions while preventing interactions with resident bacteria. Following incubation in lake water, bacterial abundance and protein production of stream communities were comparable to those of lake controls, indicating functional plasticity at the community level. High‑throughput sequencing of both 16S rRNA genes and transcripts revealed that transplanted stream communities shifted towards a more lake‑like composition. Despite higher taxonomic richness in streams, a substantial proportion of stream community abundance prior to transplantation (typically >50% of reads) consisted of taxa shared between stream and lake habitats. These generalist taxa increased markedly during incubation, dominating community composition (up to 99% of reads), whereas the diverse assemblage of stream‑specific taxa contributed little to overall abundance. Nevertheless, some rare stream specialists remained active in lake water, suggesting persistence within the local seed bank. Collectively, we demonstrate that environmental filtering alone can restructure stream bacterial communities upon entering lakes, driven by an abundant pool of taxa already shared across aquatic habitats. More broadly, our findings suggest that dispersal from streams may contribute little to taxonomic diversity in recipient communities, yet we speculate that it nonetheless may introduce novel genes in lakes through the repeated seeding of bacterial generalists.

Hydrological connectivity shapes aquatic microbial communities by facilitating taxon dispersal and modulating local selection. Microbial community composition and assembly remain understudied in aquatic networks with alternating river and lake connections, particularly regarding the roles of inflowing and outflowing rivers associated with lakes. Here, we investigated bacterial biogeography across an oligotrophic boreal river–lake network comprising three lake chains. Integrating 16S rRNA gene amplicon sequencing and genome‑resolved metagenomics, we examined diversity patterns across inlet rivers, lakes and outlet habitats. Inlet rivers harbored the highest alpha and beta diversity, likely reflecting mass effects from sediment-derived microbial inputs. In contrast, lake communities were comparatively similar across the network, indicating a stronger influence of species sorting than in inlet rivers. Outlet communities closely resembled lake community structure and suggested downstream dispersal of lake-selected taxa. Although inlet habitats contained the highest richness of habitat‑specific taxa, the dominant fraction of the metacommunity consisted of taxa shared among inlets, lakes and outlets. A strong upstream imprint was also maintained on downstream communities, with 99% of taxa detected at the catchment outlet already present in upstream sites. Furthermore, ultra‑small bacteria from the phylum Patescibacteria were highly abundant across all habitats, accounting for up to 42% of amplicon reads. Beyond differences in community composition, pangenome analyses revealed two lineages of a widespread freshwater species that differed in accessory gene content, potentially related to the acquisition of dissolved organic compounds or stress response. The two lineages co-occurred across the network, exhibiting variable abundance patterns across sampling sites, but showed no consistent association with habitat type. Together, our results provide a multiscale view of bacterial biogeography, revealing how hydrological connectivity and habitat filtering jointly shape diversity from communities to within‑species microdiversity.

Bacterivorous protists are central to aquatic food webs, mediating the transfer of carbon and nutrients to higher trophic levels through the microbial loop. In natural communities, a major challenge remains in linking protist grazing activity to environmental sequences and identifying which taxa are actively feeding at the community level. Here, we present the first application of quantitative stable isotope probing (qSIP) in a grazing experiment. By combining qSIP with 18S rRNA gene amplicon sequencing, we linked prey assimilation to the identity of active protist predators at the operational taxonomic unit (OTU) level. In a replicated 36 h bottle experiment, live ¹³C,¹⁵N-labeled Limnohabitans planktonicus cells were added to natural samples from a lake pelagic site and its main inlet stream. Although hydrologically connected, protist richness was higher in the inlet than in the lake, yet a similar number of taxa incorporated prey biomass, comprising 108 OTUs in the inlet and 107 OTUs in the lake, including both rare and abundant taxa. Of these, 26 OTUs were labeled at both sites. The most strongly labeled protist in the inlet was a putative phago-mixotrophic prasinophyte, whereas in the lake it was a chrysophyte. Across sites, prey incorporation occurred in a broad range of taxa, including heterotrophs (e.g., choanoflagellates, cercozoans, ciliates, centrohelids), putative mixotrophs (e.g., cryptophytes, chrysophytes, dictyochophytes), parasitic protists and fungi. These results demonstrate the potential of qSIP to resolve trophic interactions at fine taxonomic resolution in natural communities and highlight new opportunities to study complex microbial food webs across environmental systems.

Background: Technological constraints limit 3D printing of collagen structures with complex trabecular shapes. However, the Freeform Reversible Embedding of Suspended Hydrogels (FRESH) method may allow for precise 3D printing of porous collagen scaffolds that carry the potential for repairing critical size bone defects.

Methods: Collagen type I scaffolds mimicking trabecular bone were fabricated through FRESH 3D printing and compared either with 2D collagen coatings or with 3D-printed polyethylene glycol diacrylate (PEGDA) scaffolds. The porosity of the printed scaffolds was visualized by confocal microscopy, the surface geometry of the scaffolds was investigated by scanning electron microscopy (SEM), and their mechanical properties were assessed with a rheometer. The osteoconductive properties of the different scaffolds were evaluated for up to four weeks by seeding and propagation of primary human osteoblasts (hOBs) or SaOS-2 cells. Intracellular alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) activities were measured, and cells colonizing scaffolds were stained for osteocalcin (OCN).

Results: The FRESH technique enables printing of constructs at the millimetre scale using highly concentrated collagen, and the creation of stable trabecular structures that can support the growth osteogenic cells. FRESH-printed collagen scaffolds displayed an intricate and fibrous 3D network, as visualized by SEM, whereas the PEGDA scaffolds had a smooth surface. Amplitude sweep analyses revealed that the collagen scaffolds exhibited predominantly elastic behaviour, as indicated by higher storage modulus values relative to loss modulus values, while the degradation rate of collagen scaffolds was greater than PEGDA. The osteoconductive properties of collagen scaffolds were similar to those of PEGDA scaffolds but superior to 2D collagen, as verified by cell culture followed by analysis of ALP/LDH activity and OCN immunostaining.

Conclusions: Our findings suggest that FRESH-printed collagen scaffolds exhibit favourable mechanical, degradation and osteoconductive properties, potentially outperforming synthetic polymers such as PEGDA in bone tissue engineering applications.

Artificial intelligence is revolutionizing protein structure prediction, providing unprecedented opportunities for drug design. To assess the potential impact on ligand discovery, we compared virtual screens using protein structures generated by the AlphaFold machine learning method and traditional homology modeling. More than 16 million compounds were docked to models of the trace amine-associated receptor 1 (TAAR1), a G protein-coupled receptor of unknown structure and target for treating neuropsychiatric disorders. Sets of 30 and 32 highly ranked compounds from the AlphaFold and homology model screens, respectively, were experimentally evaluated. Of these, 25 were TAAR1 agonists with potencies ranging from 12 to 0.03 mu M. The AlphaFold screen yielded a more than twofold higher hit rate (60%) than the homology model and discovered the most potent agonists. A TAAR1 agonist with a promising selectivity profile and drug-like properties showed physiological and antipsychotic-like effects in wild-type but not in TAAR1 knockout mice. These results demonstrate that AlphaFold structures can accelerate drug discovery.

Artificial intelligence has transformed protein structure prediction, with AlphaFold2 (AF2) generating models with near-experimental accuracy. However, as AF2 was trained to generate a single structural model, this method does not capture the conformational flexibility of proteins, limiting its utility for structure-based drug design. Here, we explore strategies to generate diverse ensembles of binding-site models suitable for structure-based virtual screening against G protein-coupled receptors (GPCRs), a major class of drug targets. Our AFsample2T approach uses multiple sequence alignment column masking in the receptor binding site to reduce coevolutionary signals, leading to greater structural heterogeneity in the generated models. We demonstrate that ensembles of AFsample2T models capture multiple relevant binding-site conformations and reproduce experimentally observed conformational variability. Evaluation of AF2-based models in structure-based virtual screening using docking of actives and decoys shows that considering ensembles of diverse binding-site models substantially improves ligand enrichment. Our results provide guidelines for using AF2-based models in structure-based ligand discovery for GPCRs, and the AFsample2T approach can readily be applied to other protein classes.

Activation of G protein-coupled receptors (GPCRs) by extracellular ligands is crucial for cellular communication and modulates numerous physiological processes. Despite sharing highly similar orthosteric binding sites, catecholamine GPCRs exhibit exquisite selectivity for their native agonists, even among nearly identical chemical messengers. However, the molecular basis and evolution of receptor selectivity remain poorly understood. To elucidate the structural mechanisms of GPCR selectivity, we focus on the prototypical human β₂-adrenergic and D₁ dopaminergic receptors, which are important drug targets and respond to the catecholamines adrenaline/noradrenaline and dopamine, respectively. Guided by structural and sequence data, we identify a small set of residues responsible for ligand selectivity. By exchanging residues at four positions in the β-adrenergic receptors and seven in the D₁-like dopaminergic receptors, we swap the pharmacological profiles of the two subfamilies. Unexpectedly, the switch in selectivity not only involves residues interacting with the ligand, but is also controlled by regions outside the orthosteric binding site. Cryo-electron microscopy structures and computational models of the mutant receptors identify distinct molecular mechanisms contributing to selectivity in a concerted manner. Our findings provide insights into GPCR evolution and highlight strategies for protein engineering and drug design.

Predicting how chemical modifications affect drug binding is central to rational drug design. Free energy perturbation (FEP) calculations provide accurate estimates of these binding affinity changes, but existing methods often require substantial computational resources and expert knowledge. Here, we present QligFEP v2.1.0, a flexible open-source workflow based on a graphical and command-line interface for calculating relative binding free energies using spherical boundary conditions, which dramatically reduces simulation system size by confining simulations to a focused region around the binding site. QligFEP features a configurable restraint algorithm that automatically handles diverse chemical transformations, streamlined setup procedures, and enhanced analysis tools. We validated the method using industry benchmarks comprising 16 protein targets and 639 ligand transformations. Statistical analysis demonstrates that QligFEP achieves comparable accuracy to established commercial and open-source alternatives while requiring only a fraction of the computational resources. The perturbation protocol simulates ∼6250 atoms per perturbation leg and completes transformation replicates in under 2 h on standard computational clusters. Unlike full-system simulations, QligFEP's modest computational requirements make FEP accessible for less than $1 on current AWS spot instances. The combination of accuracy, flexibility, and computational efficiency positions QligFEP as a practical solution for accelerating compound optimization in drug discovery, making rigorous binding affinity predictions accessible for large scale applications and to research groups with limited computational infrastructure.

The modulation of the A_2B adenosine receptor is a promising strategy in cancer (immuno) therapy, with A_2BAR antagonists emerging as immune checkpoint inhibitors. Herein, we report a systematic assessment of the impact of (di- and mono-)halogenation at positions 7 and/or 8 on both A_2BAR affinity and pharmacokinetic properties of a collection of A_2BAR antagonists and its study with structure-based free energy perturbation simulations. Monohalogenation at position 8 produced potent A_2BAR ligands irrespective of the nature of the halogen. In contrast, halogenation at position 7 and dihalogenation produced a halogen-size-dependent decay in affinity. Eight novel A_2BAR ligands exhibited remarkable affinity (K_i < 10 nM), exquisite subtype selectivity, and enantioselective recognition, with some eutomers eliciting sub-nanomolar affinity. The pharmacokinetic profile of representative derivatives showed enhanced solubility and microsomal stability. Finally, two compounds showed the capacity of reversing the antiproliferative effect of adenosine in activated primary human peripheral blood mononuclear cells.

We herein document a large collection of 108 2-amino-4,6-disubstituted-pyrimidine derivatives as potent, structurally simple, and highly selective A(1)AR ligands. The most attractive ligands were confirmed as antagonists of the canonical cyclic adenosine monophosphate pathway, and some pharmacokinetic parameters were preliminarily evaluated. The library, built through a reliable and efficient three-component reaction, comprehensively explored the chemical space allowing the identification of the most prominent features of the structure-activity and structure-selectivity relationships around this scaffold. These included the influence on the selectivity profile of the aromatic residues at positions R-4 and R-6 of the pyrimidine core but most importantly the prominent role to the unprecedented A(1)AR selectivity profile exerted by the methyl group introduced at the exocyclic amino group. The structure-activity relationship trends on both A(1) and A(2A)ARs were conveniently interpreted with rigorous free energy perturbation simulations, which started from the receptor-driven docking model that guided the design of these series.

BACKGROUND: Tumor response and survival varies in patients treated with transarterial chemoembolization (TACE) for intermediate stage hepatocellular carcinoma (HCC) and may be associated with several factors.

PURPOSE: To evaluate safety and efficacy of TACE in patients with intermediate stage HCC and to identify factors related to tumor response and survival.

MATERIAL AND METHODS: Consecutive patients with HCC treated with TACE between September 2008 and September 2018 were retrospectively reviewed.

RESULTS: In 87 patients (71 men; mean age = 68 ± 9 years), 327 TACE treatments were performed (mean = 3/patient; range = 1-12). Mean and median overall survival were 32 and 19 months, respectively. Survival rates at 30 days, one, three, and five years were 99%, 71%, 19%, and 8%, respectively. Objective response (OR) was seen in 84% and disease control (DC) was seen in 92% of the patients. Patients in whom peritumoral portal lipiodol enhancement (PPLE) was seen during TACE had better OR (97 vs. 73%; P = 0.007) and DC (100 vs. 85%; P = 0.024), and a reduced risk of death (hazard ratio [HR] = 0.52; 95% confidence interval = 0.32-0.86) compared to those without PPLE. Severe adverse events were rare (15%) and occurred more often in patients with a larger tumor size.

CONCLUSIONS: TACE was effective and safe in patients with intermediate stage HCC. Patients with PPLE during TACE had better tumor response and longer survival than those without PPLE. Severe adverse events occurred more often in patients with larger tumors.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a common cause of cancer-related death, often detected in the intermediate stage. The standard of care for intermediate-stage HCC is transarterial chemoembolisation (TACE), where idarubicin (IDA) is a promising drug. Despite the fact that TACE has been used for several decades, treatment success is unpredictable. This clinical trial has been designed believing that further improvement might be achieved by increasing the understanding of interactions between local pharmacology, tumour targeting, HCC pathophysiology, metabolomics and molecular mechanisms of drug resistance.

METHODS AND ANALYSIS: The study population of this single-centre clinical trial consists of adults with intermediate-stage HCC. Each tumour site will receive TACE with two different IDA doses, 10 and 15 mg, on separate occasions. Before and after each patient's first TACE blood samples, tissue and liquid biopsies, and positron emission tomography (PET)/MRI will be performed. Blood samples will be used for pharmacokinetics (PK) and liver function evaluation. Tissue biopsies will be used for histopathology analyses, and culturing of primary organoids of tumour and non-tumour tissue to measure cell viability, drug response, multiomics and gene expression. Multiomics analyses will also be performed on liquid biopsies. PET/MRI will be used to evaluate tumour viability and liver metabolism. The two doses of IDA will be compared regarding PK, antitumour effects and safety. Imaging, molecular biology and multiomics data will be used to identify HCC phenotypes and their relation to drug uptake and metabolism, treatment response and survival.

ETHICS AND DISSEMINATION: Participants give informed consent. Personal data are deidentified. A patient will be withdrawn from the study if considered medically necessary, or if it is the wish of the patient. The study has been approved by the Swedish Ethical Review Authority (Dnr. 2021-01928) and by the Medical Product Agency, Uppsala, Sweden.

TRIAL REGISTRATION NUMBER: EudraCT number: 2021-001257-31.

Introduction Despite progress in reducing Uganda’s unmet need for family planning (FP), particularly in urban areas, it remains high with notable intraurban disparities. FP services in urban settings are delivered in a complex health system, which impacts service delivery and utilisation. Acknowledging the complexity of FP utilisation in these contexts, this study adopted a systems thinking approach, using causal loop diagrams (CLDs), to examine the interrelationships between the factors influencing FP uptake in urban east central Uganda.

Methods This qualitative study, conducted in Jinja city and Iganga municipality, used community-based system dynamic modelling to create CLDs to visualise the interrelationships between the different factors. The CLDs were developed through two group model building workshops, involving 14 community members and other key stakeholders. Initial model building was based on themes derived from analysis of data from eight focus group discussions, eight key informant interviews and four indepth interviews. The resulting CLDs were subsequently validated in a separate meeting with the participants.

Results The study identified 30 key factors influencing FP utilisation mediated through five mechanisms: reproductive autonomy, service access, client satisfaction, perceptions of FP as important and perceived susceptibility to sexually transmitted infections among women. It highlighted the role of self-regulating feedback loops related to side effects, commodity and supply availability and provider workload, which moderate FP use. Additionally, the study emphasised the positive reinforcing effects of enhanced access to FP information on service access and uptake.

Conclusion Effective FP intervention designs should account for the complex interplay of factors affecting utilisation. Key leverage points include addressing the underlying negative religious and sociocultural beliefs that shape system behaviour, improving information flow and data use for better commodity management and human resource sustainability, enhancing contraceptive pharmacovigilance systems, improving the management of side effects and increasing access to FP information.

Background

Health facility readiness is essential for realizing voluntary, rights-based family planning. However, many countries, including rapidly urbanizing Uganda, face challenges in ensuring their health facilities are sufficiently equipped to meet the growing demand for these services. This study assessed readiness and associated factors across public, private-not-for-profit (PNFP), and private-for-profit (PFP) health facilities in urban east-central Uganda to guide strategies for improving service delivery.

Methods

The study used secondary data from a cross-sectional study done in Jinja City and Iganga Municipality, including a health facility assessment and health worker survey. Readiness was measured using the Service Availability and Readiness Assessment methodology, and health worker knowledge and biases were assessed through the Situation Analysis approach. Sample weights adjusted for facility and health worker representation, and linear regression examined associations between readiness scores and various factors.

Results

Among 152 health facilities, 94.2% offered family planning services, with an average readiness score of 46.7% (standard deviation +/- 17.0). Short-acting methods had high availability (99.0%), while long-acting reversible contraceptives (34.2%) and permanent options (8.9%) were less available, compounded by prevalent stock-outs. Additionally, staff refresher training was inadequate, particularly in PFP facilities (50.4%), and health worker knowledge, confidence and willingness to provide some methods, particularly long-acting options and natural family planning counselling, were low. Notably, out of 261 health workers, 97.7% imposed at least one restriction to service access based on either age, parity, marital status, or spousal consent, more pronounced in PNFP facilities. Readiness was significantly associated with facility level (health centre level II facilities: beta = -9.42, p = 0.036; drug shops: beta = -11.00, p = 0.022), external supervision (beta = 9.04, p = 0.009), holding administrative meetings (beta = 9.72, p = 0.017), and imposing marital status (beta = -9.42, p = 0.017) and spousal consent access barriers (beta = 6.24, p = 0.023).

Conclusions

This study found sub-optimal facility readiness, highlighting the need to strengthen governance of services across both public and private sectors, implement comprehensive training for health workers in both sectors, and align policies to ensure equitable access to a full range of services for all clients.

Many women in Uganda face barriers to using family planning in ways that are safe and responsive to their needs. This study explored the experiences of women in urban east-central Uganda to understand how they access, use, and navigate family planning services to identify opportunities for service improvement. Ten women participated in a three-month photovoice process combining photography with bi-monthly group discussions. Data were analysed using reflexive thematic analysis. Five themes were generated: (1) Services that do not serve: a disconnect between the promise of free, accessible care and the reality of stockouts, hidden costs, poor provider attitudes, and poor infrastructure; (2) Disputed and constrained decision-making power: reproductive choices were restricted by male partners, providers, and age-based stigma; (3) Living with side effects in exchange for protection: women reported several physical and psychological effects, often self-managed with little healthcare system support; (4) Community Health Workers (CHWs) as trusted and flexible providers: CHWs filled gaps left by formal healthcare services through accessible, discreet, and personalised care; and (5) Quiet acts of reproductive agency: despite the barriers, women maintained control over their fertility through covert use or reliance on unevidenced alternatives when modern methods were inaccessible or perceived unsafe. These findings offer distinct visual and narrative evidence of a disconnect between policy commitments and women's realities. To strengthen family planning programs, approaches must shift from a narrow focus on uptake to prioritising women's agency and well-being. This requires user-centred strategies that address structural, interpersonal, and method-related barriers while strengthening community-based service provision.

Introduction: Horse allergens are less studied than allergens from other furry animals and these allergens must be evaluated to understand the complexity of allergy to horses. The aims of this study were to develop assays for the horse allergens Equ c 1 and Equ c 2 in dander and saliva and to determine their levels in ten horse breeds. The study also included a comparison of these findings with previous results on the levels of Equ c 4 performed on the same study population. Method: The study population included 170 horses from 10 horse breeds including American Curly and Russian Bashkir horse, which have been suggested to be hypoallergenic. Competitive ELISA assays were developed, with polyclonal antibodies as capture antibodies, for the detection of Equ c 1 and Equ c 2 in dander and saliva samples. Results: The horse allergens Equ c 1 and Equ c 2 were found in all dander and saliva samples from the ten horse breeds. The GM level (ng/mu g protein) of Equ c 1 in dander was 470 (range 129-2,569) and in saliva samples, 40 (range 6-160). The GM level of Equ c 2 in dander was 138 (range 18-1,650) and in saliva samples, 0.8 (range 0.03-17). In dander, there were no significant differences in Equ c 1 and Equ c 2 GM levels between stallions, mares, and geldings. Conclusion: Our results show high intra- and inter-breed variability. Neither the American Curly horse nor the Russian Bashkir horse, earlier categorized as hypoallergenic breeds, was associated with lower allergen levels of Equ c 1, Equ c 2, or Equ c 4 than the other horse breeds investigated.

Background: Horses are an important source of allergens, but the distribution of horse allergens is poorly understood. Five horse allergens have been identified, Equ c 1-4 and 6. Equ c 4 seems to be an important allergen, with an IgE-binding frequency of 77% in horse-sensitized individuals.0000 Objectives: The aim of this study was to investigate levels of horse allergen Equ c 4 in dander, saliva and urine from ten horse breeds. Method: The study population included 170 horses (87 mares, 27 stallions, 56 geldings) from ten breeds. Horse dander, saliva and urine samples were collected. Levels of horse allergen Equ c 4 were quantified using a two-site sandwich ELISA (mAb 103 and 14G4) and were expressed as Equ c 4 U/mu g protein. Results: The horse allergen Equ c 4 was present in all dander and saliva samples from ten horse breeds, with high within-breed and inter-breed variations; GM values were 639 Equ c 4 U/mu g protein (range 5-15 264) for dander and 39.5 (4-263) for saliva. Equ c 4 was found in 19/21 urine samples. Adjusted for age, sex and changes over time, no differences between breeds could be seen in dander, while in saliva the North Swedish horse showed lower levels of Equ c 4 than any other breed. The levels of Equ c 4 protein in dander and saliva were significantly higher in samples from stallions compared to mares and geldings, independent of breed. Conclusions and Clinical Relevance: The results show a high variability in allergen levels of Equ c 4 in dander and saliva both within and between breeds. Significantly higher levels were found in stallions compared to mares and geldings, independent of breed. Results suggest that none of the horse breeds studied can be recommended for individuals allergic to Equ c 4.

Marine energy resources could be crucial in meeting the increased demand for clean electricity. To enable the use of marine energy resources, developing efficient and durable offshore electrical systems is vital. Currently, there are no large-scale commercial projects with marine energy resources, and the question of how to design such electrical systems is still not settled. A natural starting point in investigating this is to draw on experiences and research from offshore wind power. This article reviews different collection grid topologies and key components for AC and DC grid structures. The review covers aspects such as the type of components, operation and estimated costs of commercially available components. A DC collection grid can be especially suitable for offshore marine energy resources, since the transmission losses are expected to be lower, and the electrical components could possibly be made smaller. Therefore, five DC collection grid topologies are proposed and qualitatively evaluated for marine energy resources using submerged and non-submerged marine energy converters. The properties, advantages and disadvantages of the proposed topologies are discussed, and it is concluded that a suitable electrical system for a marine energy farm will most surely be based on a site-specific techno-economic analysis.

This paper discusses the article "Assessing temporal complementarity between three variable energy sources through correlation and compromise programming." The discussed paper proposes a novel method of assessing comple-mentarity between three energy sources using correlation, compromise programming, and normalization. The method is then used to calculate a complementarity index which is applied to a case study in Poland. However, upon inspection, the normalization of the index overestimates the complementarity potential. This issue is dis-cussed in detail in this paper, and an alternative way of calculating the index is proposed, eliminating the issue of overestimating complementarity.

An important aspect in designing co-located wind and solar photovoltaic hybrid power plants is the sizing of the energy converters to achieve as efficient power smoothening as possible. In this study, the ratio of wind- and photovoltaic energy converters in a hybrid power plant is determined by minimizing the overall stored energy that is needed to facilitate constant power output. Using Fourier transform the variability is isolated at predefined time scales that are relevant for grid integration. For the investigated time scales, energy and power ratings for energy storages are determined to counteract the variability. The resulting configuration is the one that is able to achieve constant power output with minimum stored energy. It is shown that co-locating wind- and photovoltaic energy converters smoothen seasonal energy generation, and reduce the energy storage need in both the diurnal and seasonal time scales. A case study for south-eastern Sweden is presented where the wind- \& solar hybrid plant configuration that minimizes the energy storage need and therefore most closely resembles constant output power is determined. It is found that a ratio of approximately 40-45\% wind power in the hybrid power plant yields the lowest need for energy storage. The presented method is valid for any number of co-located energy sources, and can also be extended to sizing of hybrid power systems.

Co-locating renewable energy sources such aswave power, solar photovoltaic and wind power, forminga hybrid power plant, may reduce the overall variability,increase the utilization of the transmission system, and reduce the needed physical area. An important topic to address regarding the formation of hybrid power plants is which energy sources to co-locate, and to what proportions these energy sources should be included in the hybrid power plant. In this study, offshore hybrid power plants are analyzed in the North Sea region. By minimizing the plant variability the proportions of each energy source are found, forming the plant with minimal need for energy storage for constant power output operation. The added grid value of such plants is analyzed in terms of electrical infrastructure utilization and power production ramping. It is found that in conditions suitable for the wave energy converter used in the study, a plant configuration of 23% wave power, 22% wind power and 55% solar minimizes the need for energy storage. It is shown that the inclusion of wave power in a hybrid power plant lowers ramping of power generation, increases the capacity factor and provides an overall higher grid value compared to stand-alone installations.

As the share of renewable energy sources in the energy mix increases, weather-dependent variations in several time scales will have a significant impact on the power system. One way of mitigating these variations is to co-locate complementary energy sources at the same location. In this study, the complementarity between offshore floating photovoltaics, wave, and wind power is analyzed and the grid impact of such co-located energy sources is addressed using capacity credit. Additionally, the possibility of installing supplementary generation capacity within existing offshore wind power farms is investigated. It is found that co-locating wave power with offshore wind results in increased capacity credit compared to stand-alone wind power farms and that in all analyzed cases, the capacity credit of the co-located energy sources exceeds the capacity credit contribution of the separate energy sources. Co-locating photovoltaics with offshore wind brings little benefit to the capacity credit, but shows potential in increasing the utilization of the transmission cable.

One of the key problems with integrating renewable energy in the power grid is the inherent variability and uncertainty. One way of mitigating this issue is using complementary energy sources, that when combined reduce variability and increase system reliability or optimize resource utilization. In this paper, various metrics for renewable energy complementarity are reviewed. Definitions, methodologies and interpretations of the metrics are provided.

A particular focus is placed on the implications of the metrics for wave energy. The temporal characteristics of wave energy is often similar to that of wind power, with a time delay. Therefore, combining wave energy with wind energy as well as other energy sources offer opportunities for synergetic co-location strategies.

The paper acts as a reference map for when to use which complementarity metric, and what the metric means. Our finding underscores the importance of leveraging energy complementarity, and aids to avoid pitfalls in wrongly assessing complementarity.

With larger shares of renewable energy sources in the generation mix, their inherent variability and intermittency increasingly challenge power system stability. One strategy to mitigate the variability of renewable energy sources is to co-locate complementary energy sources. This article reviews the concept of renewable energy complementarity, with a particular focus on metrics for complementarity assessment. Twelve distinct metrics are identified and classified into four groups: statistical, fluctuation-based, event-based, and effectiveness metrics. Of the reviewed articles, approximately one-third employed the Pearson correlation coefficient, and more than half focused on wind-photovoltaic (PV) combinations. The identified metrics are compared in this study using both synthetic test data and meteorological reanalysis data. Our analysis reveals that metrics designed for more than two sources tend to overestimate complementarity, and no single metric consistently captures all relevant aspects. We recommend the combined use of multiple metrics, chosen for the intended application, to ensure a robust and transparent assessment.

In this study, the impact of data time resolution on long-term voltage stability assessment of a power grid with high penetration of wind-solar hybrid power plants is investigated. Historical and synthetic wind data as well as solar irradiance are used to calculate power output from hypothetical offshore wind-solar hybrid power plants, geographically located off the coast of Massachusetts, USA. The results show that using hourly input data can overestimate the long-term voltage stability, compared with using minute data. However, the relative difference in terms of voltage mean value and standard deviation is marginal whilst the most significant difference is the intensity of the voltage fluctuations. The main drawback of using high-resolution data is the execution time, increasing proportionally with the number of time steps. Thus, it is argued that the choice of da ta time resolution should be based on the aspects of long-term voltage stability and the size of the power grid to be studied.

The Nordic synchronous area strives to achieve a fossil-free energy system, requiring significant expansion of renewable electricity generation. While onshore wind power is technologically mature, offshore wind, particularly floating installations, offers access to stronger and more consistent wind resources in deeper waters. In this study, the potential of floating offshore wind power in the Nordic synchronous area is evaluated through a 21-year (2004-2024) wind resource analysis using ERA5 reanalysis data for 11 geographically distributed sites across several seas. A MATLAB-based model was developed to simulate the wind power generation. Simulating local compressed air energy storage at each site and centralized hydropower storage, the total losses and curtailments of the proposed system are determined. A system with both local and centralized storage demonstrates greater reliability in providing a baseload to the grid than a system with only local storage. Additionally, the geographical smoothing significantly reduces variability, with correlation between sites decaying exponentially with distance. The system has the potential to provide 187.3 TWh annually. Furthermore, the seasonal variation in the Nordic synchronous area was integrated into the model. It showed higher demand during the winter and lower demand during the summer, and demonstrated reliability in providing a baseload to the grid, with an annual output of 189.5 TWh. Floating offshore wind, combined with local storage and existing hydropower flexibility, can contribute to the Nordic synchronous area for baseload supply and enhance system reliability while expanding generation and supporting the region's decarbonization goals.

The large-scale deployment of renewable energy at sea offers an opportunity to combine complementary resources within shared offshore infrastructure. While co-location of wind, wave, and solar energy has been proposed as a means to reduce variability and costs, the global conditions under which hybrid offshore power parks are economically preferable remain poorly understood. This study performs a global, temporally high-resolved, techno-economic assessment of offshore wind, wave, and floating solar power, both as stand-alone and co-located systems. Using hourly ERA5 reanalysis data for the period 2020–2024, energy generation from each technology is modelled, and the levelized cost of energy (LCOE) for hybrid parks is minimized subject to shared grid infrastructure and curtailment. The optimization is performed for two cost scenarios representing present-day and near-future capital expenditure levels. Results show that LCOE ranges from 0.04–0.16 €/kWh under present-day conditions and 0.02–0.09 €/kWh under near-future scenarios. Co-location is rarely cost-optimal in regions with excellent single-resource conditions, but can yield lower LCOE than single-technology deployment in locations with moderate and complementary resources. Negative correlations between hourly energy profiles, even when weak (−0.3 to −0.2), are shown to systematically reduce LCOE in mixed systems. While the optimal technology mix is sensitive to assumed cost levels, the underlying drivers (solar capacity factor, resource availability and intersource correlation) for co-location remain robust. These findings provide a global perspective on where and why hybrid offshore energy systems can contribute to a cost-efficient and resilient future energy supply.

Ex vivo drug response profiling is emerging as a valuable tool for identifying drug resistance mechanisms and advancing precision medicine in hematological cancers. However, the functional impact of dysregulation of the epigenome and transcriptome in this context remains poorly understood. In this study, we combined ex vivo drug sensitivity profiling with transcriptomic and epigenomic analyses in diagnostic samples from 597 pediatric B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients. Ex vivo resistance to antimetabolites (e.g., cytarabine, thioguanine), glucocorticoids (e.g., dexamethasone, prednisolone), and doxorubicin was independently associated with reduced relapse-free survival (P < 0.05). Molecular profiling identified pretreatment DNA methylation and gene expression patterns distinguishing resistant from sensitive cases, revealing key drug resistance signatures. These included aberrant expression of genes related to heme metabolism (e.g., ATPV06A) and KRAS signaling (e.g., GS02). Notably, we also observed atypical expression of genes usually restricted to T cells and other immune cells (e.g., ITK) in resistant BCP-ALL cells. Our findings demonstrate that ex vivo drug response patterns are predictive of clinical outcomes and reflect intrinsic molecular states associated with drug tolerance. This integrative multi-omics approach highlights potential therapeutic targets and underscores the value of functional precision medicine in identifying treatment vulnerabilities in pediatric ALL.

Functional precision medicine (FPM) aims to optimize patient-specific drug selection based on the unique characteristics of their cancer cells. Recent advancements in high throughput ex vivo drug profiling have accelerated interest in FPM. Here, we present a proof-of-concept study for an integrated experimental system that incorporates ex vivo treatment response with a single-cell gene expression output enabling barcoding of several drug conditions in one single-cell sequencing experiment. We demonstrate this through a proof-of-concept investigation focusing on the glucocorticoid-resistant acute lymphoblastic leukemia (ALL) E/R+ Reh cell line. Three different single-cell transcriptome sequencing (scRNA-seq) approaches were evaluated, each exhibiting high cell recovery and accurate tagging of distinct drug conditions. Notably, our comprehensive analysis revealed variations in library complexity, sensitivity (gene detection), and differential gene expression detection across the methods. Despite these differences, we identified a substantial transcriptional response to fludarabine, a highly relevant drug for treating high-risk ALL, which was consistently recapitulated by all three methods. These findings highlight the potential of our integrated approach for studying drug responses at the single-cell level and emphasize the importance of method selection in scRNA-seq studies. Finally, our data encompassing 27 327 cells are freely available to extend to future scRNA-seq methodological comparisons.

Implementing a computationally efficient numerical model for a single streamer discharge is essential to understand the complex processes such as lightning initiation and electrical discharges in high voltage systems. In this paper, we present a streamer discharge simulation in air, by solving one-dimensional (1D) drift diffusion reaction (DDR) equations for charged species with the disc approximation for electric field. A recently developed fourth-order space and time-centered implicit finite difference method (FDM) with a flux-corrected transport (FCT) method is applied to solve the DDR equations, followed by a comparative simulation using the well-established explicit FDM with FCT. The results demonstrate good agreement between implicit and explicit FDMs, verifying their reliability for streamer modeling. The total electrons, total charge, streamer position, and hence the streamer bridging time obtained using the FDMs with FCT agree with the same streamer computed in the literature using different numerical methods and dimensions. The electric field is obtained with good accuracy due to the inclusion of image charges representing the electrodes in the disc method. This accuracy can be further improved by introducing more image charges. Both implicit and explicit FDMs effectively capture the key streamer behavior, including the variations in charged particle densities and electric field. However, the implicit FDM is computationally more efficient.

Lightning involves complex physical processes in atmospheric discharges, beginning with the development of streamer discharges. Therefore, to understand the mechanism of streamer discharges, it is important to develop a computationally efficient and an accurate numerical model. In this paper, we present the results of a 1.5-dimensional (1.5D) streamer discharge simulation using the well-established explicit finite difference method (FD) with flux-corrected transport (FCT) method. The method was applied to a streamer propagating in a 1.25cm plane-plane air gap in standard atmos-pheric pressure and temperature. We compared our results to those from a previously published two-dimensional (2D) axisymmetric streamer paper which is focused on the same air gap but using different numerical approaches. One can observe that the electric field is obtained with good accuracy in this 1.5D numerical simulation. The streamer position and the streamer bridging time agree with 2D results. This model has the potential to deal with moving non-uniform meshes.