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PubMed2026

Sexual selection purges mutation load, but not overall genetic diversity, decreasing vulnerability to extinction.

Theory suggests sexual selection will enhance population viability by purging deleterious alleles. However, direct genomic evidence for this fundamental idea is scarce and contradictory. We combined long-term experimental evolution with whole-genome resequencing to directly test how sexual selection affects mutation load, genomic divergence, and extinction risk in small populations (maximum Ne = 40) of Tribolium castaneum. After 156 generations, populations evolving under strong sexual selection carried substantially fewer deleterious alleles than populations under weak sexual selection, based on both individual-level estimates of missense and nonsense variants and population-level Rxy analyses, indicating more efficient purging of deleterious alleles. In contrast, nucleotide diversity and runs of homozygosity were similar across treatments, indicating that purging acted most strongly on deleterious variation, and that reduced mutation load in these small populations under strong sexual selection was not explained by demographic effects. Importantly, population-level mutation load estimates best explained extinction risk under inbreeding, directly linking sexual selection to purging and population viability. Genome scans of high and low sexual selection populations revealed peaks of divergence, which included genes involved in courtship, sex discrimination, and seminal fluid proteins. Our results provide direct genomic evidence that sexual selection can reduce mutation load without eroding standing genetic diversity and thus adaptive potential, while driving adaptive divergence in reproductive traits. This beneficial purging may help explain the widespread prevalence of sexual reproduction in nature despite inherent costs and have important ramifications as to how we manage populations of conservation concern.

Animals↗

PubMed2026

Phylogenomics and female reproductive morphology reframe the classification of the Halymeniales (Rhodophyta).

The red algal order Halymeniales (Rhodophyta) exhibits remarkable morphological and taxonomic diversity but its higher-level relationships remain poorly resolved. Here, we present a comprehensive phylogenomic analysis based on newly generated plastid (170 protein-coding genes), mitochondrial (23 genes), and complete nuclear ribosomal cistron sequences from 56 taxa, complemented with an expanded rbcL dataset encompassing 334 sequences. Our results provide a robust phylogenomic framework for the Halymeniales, offering a taxonomic backbone for future systematic studies. The analyses consistently recover six early-diverging lineages (Acrodiscus, Isabbottia, Norrissia, Pachymenia, Zymurgia, and Tsengia) and two strongly supported larger clades (Halymenia s.l. and Grateloupia s.l.). While most small and recently described genera are monophyletic, several traditional genera (e.g., Halymenia, Cryptonemia, Grateloupia) are poly- or paraphyletic, requiring considerable taxonomic revision. At the family level, the data indicate that reinstatement of the Grateloupiaceae sensu Kim et al. (2021) would entail a revised circumscription of the Halymeniaceae and the recognition of at least five small families to accommodate the early-diverging lineages. Although such a revised classification would result in monophyletic families, it is not supported by morpho-anatomical characters. Instead, we propose a more stable two-family system, recognizing a broadly circumscribed Halymeniaceae that is sister to the Tsengiaceae. Female reproductive characters, particularly the structure of carpogonial and auxiliary cell ampullae, support this two-family system and further characterize many genus-level clades, although substantial convergence across lineages exists.

Phylogeny↗

PubMed2026

Empagliflozin and functional aerobic capacity in individuals with increased risk of heart failure: The Empire Prevent Cardiac trial.

BACKGROUND: Higher maximal oxygen consumption (VO₂ max) is associated with lower risk of developing heart failure (HF). Empagliflozin improves VO2 max in HF with reduced ejection fraction, but the effect on VO2 max in individuals at risk of HF remain unknown. OBJECTIVE: This study aimed to evaluate the effect of 180 days treatment with empagliflozin compared to placebo on VO2 max, daily physical activity level, and quality of life (QoL) in individuals with overweight or obesity and risk of HF. METHOD: This investigator-initiated, double-blinded, randomized, placebo-controlled, multicenter trial included elderly individuals with body mass index >28 kg/m2 and at least one additional risk factor for HF, including hypertension, ischemic heart disease, stroke, or chronic kidney disease. Individuals with HF or type 2 diabetes mellitus were excluded. The primary endpoint was the mean difference in change of VO2 max. The secondary outcome was objectively measured physical activity level. QoL was an explorative outcome. RESULTS: Among 191 randomized individuals (94 empagliflozin, 97 placebo), 89% had hypertension and 66% ischemic heart disease. At baseline, 69% were male, median age was 68 years, median body mass index 31.9 kg/m², mean left ventricular ejection fraction 65 ± 9%, and mean VO₂ max 18.1 ± 4.3 mL/min/kg. Empagliflozin did not change VO2 max with an estimated treatment difference of -0.2 mL/min/kg (97.5% confidence interval -1.2 to 0.8), adjusted P = 1.00. No significant treatment differences were observed for neither daily physical activity nor QoL. CONCLUSIONS: Empagliflozin did not affect VO2 max, physical activity level, or QoL in elderly individuals with overweight or obesity and risk of HF.

Humans↗

PubMed2026

ATF4-histone 2-hydroxyisobutyrylation feedback loop drives sepsis-induced inflammation.

BACKGROUND AND PURPOSE: The role and mechanisms of lysine 2-hydroxyisobutyrylation (Khib) in the acute inflammatory phase of sepsis remain unclear. We investigated the function and underlying mechanisms of histone H4 lysine 5 2-hydroxyisobutyrylation (H4K5-hib) in sepsis-induced inflammation in vivo and in vitro. EXPERIMENTAL APPROACH: Acute sepsis was induced by caecal ligation and puncture (CLP) in mice, and inflammatory responses were modelled in lipopolysaccharide (LPS)-stimulated macrophages. CUT&Tag-seq was used to identify genomic targets associated with H4K5-hib and activating transcription factor 4 (ATF4). Immunofluorescence, Western blotting, qPCR, dual-luciferase assays, and ELISA were performed to investigate the underlying mechanisms. KEY RESULTS: H4K5-hib levels were increased in macrophages during the acute inflammatory phase of sepsis. LPS stimulation enhanced H4K5-hib enrichment at the ATF4 promoter, thereby promoting ATF4 transcription. Inhibition of EP300-mediated 2-hydroxyisobutyrylation or mutation of H4K5 abolished ATF4 activation. Increased H4K5-hib activated the ATF4/NLRP3 signalling axis, promoting inflammasome assembly and amplifying inflammatory responses. ATF4 directly bound to the EP300 promoter and enhanced its transcription, forming a positive feedback loop that further increased H4K5-hib levels. In CLP-induced sepsis, pharmacological inhibition of EP300 or ATF4 reduced H4K5-hib levels and suppressed NLRP3 inflammasome activation. CONCLUSION AND IMPLICATIONS: These findings reveal a previously unrecognized epigenetic mechanism underlying sepsis-induced inflammation and identify the EP300/ATF4/H4K5-hib positive feedback loop as a potential therapeutic target for sepsis.

Animals↗

PubMed2026

Metabolomic Signatures of Inflammation in Chronic Kidney Disease.

RATIONALE & OBJECTIVE: Inflammation is associated with adverse kidney, cardiovascular, and mortality outcomes. Investigation of the metabolic milieu as it relates to inflammation may provide important insights into these disease processes. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: African American Study of Kidney Disease and Hypertension (AASK), Atherosclerosis Risk in Communities (ARIC) study, and Boston Kidney Biopsy Cohort (BKBC) participants with available metabolomics and inflammatory protein data. PREDICTORS: Baseline blood levels of 718 metabolites. OUTCOMES: Baseline and longitudinal changes in blood levels of tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), interleukins 6, 8, and 10 (IL-6, IL-8, IL-10), uromodulin (UMOD), and epidermal growth factor (EGF). ANALYTICAL APPROACH: Multivariable linear regression and linear mixed-effects models. RESULTS: Among 491 AASK participants (mean age 54 years; 37% women; mean glomerular filtration rate, 45 mL/min/1.73 m2), 367 cross-sectional associations between metabolites and inflammatory proteins were significant after correction for multiple comparisons. The direction of association was mostly positive for TNFR1 (97%), TNFR2 (97%), IL-8 (77%), and IL-10 (100%); negative for UMOD (80%) and EGF (97%); and variable for TNF-⍺, IFN-γ, and IL-6. Pathways were distinct for several inflammatory proteins (eg, tryptophan metabolism for TNFR2). Forty-five associations between metabolites and longitudinal change in inflammatory proteins were identified. Notable metabolites included tigylcarnitine and N 2,N 5-diacetylornithine, which were associated with 2-year increases in TNFR1 and/or TNFR2, and 1,5-anhydroglucitol, where lower levels were associated with decreases in UMOD. In ARIC (n = 3,773) and BKBC (n = 413), replication of cross-sectional associations was excellent for TNFR1 (ARIC 83%; BKBC 85%) and TNFR2 (ARIC 64%; BKBC 79%) but poor for IL-8 (ARIC 3%; BKBC 3%). LIMITATIONS: Metabolite data limited to baseline visit; potential for residual confounding. CONCLUSIONS: Using an untargeted approach, multiple metabolites were cross-sectionally and longitudinally associated with inflammatory proteins in persons with chronic kidney disease.

Chronic kidney disease↗

PubMed2026

Investing in Canada's nursing workforce: a comprehensive review to inform policy innovations and directions.

BACKGROUND: Health systems worldwide face persistent health workers challenges including nursing shortages, workforce strain, and inequities. In Canada, these challenges have prompted renewed national and provincial reforms to strengthen recruitment, retention, leadership, and sustainability. This paper compares nursing workforce policy directions across Canada, and international jurisdictions to inform policy and planning. METHODS: A cross-country comparative analysis of policies building on a comprehensive national funded review that included an umbrella review of 69 systematic reviews, a comparative policy review of nursing workforce strategies in five jurisdictions, and validation through national horizon-scanning and policy dialogues (n >100). Evidence was analyzed across system, organizational, and individual levels. RESULTS: At the system level, international jurisdictions demonstrate comprehensive, legislated approaches integrating data, governance, and multi-year funding have advanced key nursing strategies. In Canada, the advances show the importance of strategies to have national and provincial/territorial alignment emphasizing leadership, flexibility, and inclusion as key levers. Organizational and individual-level reforms such as mentorship, leadership development, and wellness initiatives are expanding but remain variably evaluated. Experts identified national workforce data strategies and policy integration with embedded evaluation as key enablers to inform scalability and sustainability of implemented strategies. CONCLUSIONS: Canada's nursing workforce reforms are advancing toward coordinated, equity-driven, and evidence-informed strategies. Continued investment in evaluation, leadership, and national integrated data systems along with integrating nursing workforce planning within broader intersectoral planning will consolidate these gains and position Canada as an international leader in sustainable nursing workforce policy.

Canada↗

PubMed2025

The effects of haptonomy and virtual reality, anxiety, prenatal attachment and acceptance of pregnancy in unplanned pregnancy.

AIM: Unplanned pregnancies are an important public health problem that negatively affects the health of women and babies. This study aimed to determine the effects of haptonomy and virtual reality on anxiety, prenatal attachment and acceptance of pregnancy in unplanned pregnancies. Haptonomy, a touch-based bonding technique, and virtual reality, an immersive fetal visualisation tool, were used as interventions. METHODS: The sample of this randomised controlled study consisted of 217 pregnant women (haptonomy: 73, virtual reality: 72 and control: 72) who applied to the Obstetrics and Gynaecology outpatient clinics of a public hospital in eastern Turkey between July 2020 and April 2021. For both experimental groups, four interviews were conducted with the pregnant women between the 24thand32nd gestational weeks at intervals of 7-10 days. Data were collected on pregnancy-related anxiety, prenatal attachment and pregnancy acceptance. Group differences were analysed using appropriate statistical comparisons. RESULTS: Pregnancy-related anxiety was lower, and acceptance of pregnancy was higher in the experimental groups compared to the control group (p < .001). Prenatal attachment level was higher in the haptonomy and virtual reality groups compared to the control group (p < .001). Notably, prenatal attachment scores were significantly higher in the haptonomy group compared to the virtual reality group (p < .001). CONCLUSION: In unplanned pregnancies, imagining the baby through haptonomy and imagining the baby through virtual reality are techniques that reduce the level of anxiety related to pregnancy and increase the level of prenatal attachment and acceptance of pregnancy. Especially haptonomy showed a higher effect on prenatal attachment.

Humans↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗

PubMed2026

Barriers to physical activity in patients with systemic lupus erythematosus in the UK.

INTRODUCTION: Physical activity (PA) may play an important role as a non-pharmacological addition to the management of SLE for disease control and reduction of cardiovascular risk factors. Those with SLE have been reported to engage in PA less than the general population. OBJECTIVE: To describe PA patterns and patient-reported barriers to PA for people with SLE in the UK. METHODS: An online survey was conducted of adults aged ≥ 18 years. Participants were recruited from posters in outpatient clinics, newsletters and Lupus UK social media platforms. Survey questions included demographic information, perception of disease activity, the International Physical Activity Questionnaire (IPAQ) and specific leisure time questions. RESULTS: Two hundred sixty-eight patients participated, with a median (IQR) age of 51 (39-59) years and SLE disease duration of 10 (4-20) years were included. SLE-diagnosis was collected by self-report. In those with complete IPAQ data, 178/228 (79.1%) were in a moderate/high activity group. Participants in this group were more likely to be in employment and had lower levels of fatigue and pain. Fatigue was the most reported barrier to PA, irrespective of activity levels. Participants in the low PA group were more likely to have SLE-specific barriers such as higher disease activity and higher pain scores. CONCLUSIONS: Perceptions and preferences in relation to PA differ greatly between individuals with SLE. The most common self-reported barrier to PA was fatigue. Exploration of individual perceptions of PA should form part of consultations, to address perceived barriers. Key Points • Some patients with self-reported SLE can meet WHO physical activity targets, especially those who remain in work. • Fatigue is the most frequently reported barrier to physical activity for patients, irrespective of their activity levels. • People are less likely to engage in PA if they believe it will negatively affect their SLE.

Humans↗

PubMed2026

Intraskeletal Variation in Cortical Bone Quantity in a Medieval Italian Sample: A Multivariate Exploratory Approach.

Bioarcheologists interpret skeletal health by examining variability within and between individuals. Studies of bone loss have generated contradictory and conflicting results regarding the onset and severity of age-related bone loss on a global and temporal scale, perhaps due to mismatched methodologies. Intraskeletal comparisons of bone tissue prove challenging precisely because of heterogeneous baselines in quantity and remodeling of cortical bone throughout the skeleton, as well as evolutionary histories and environmental impacts on growth and development. Here we analyze cortical bone indicators from the rib, metacarpal, and femoral cortical bone in a subset of individuals (n = 72) regions from the medieval Italian archaeological site of Pieve di Pava. To facilitate intraskeletal comparisons across elements with different biological baselines, we standardize cortical bone parameters using z-scores. Variation in relative intraskeletal cortical bone was assessed using accessible multivariate methods (principal component analysis and hierarchical cluster analysis). Results suggest an association between femoral and metacarpal cortical bone values, with stochastic trends in metacarpal and femoral relative bone quantity in relation to the rib bone quantity at the sample level. Our study demonstrates that while intraskeletal analyses are challenging, they are made more robust by synthesizing multivariate methods alongside exploratory data analysis (EDA) methods to tack between sample-level and individual-level scales and variability. Ultimately, we advocate for leveraging multivariate techniques not as a final step, but rather as a means of generating new hypotheses and challenging tendencies to a priori establish typological groups in the research process.

Skeleton↗

PubMed2026

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.  Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans↗

PubMed2026

Variability and ozone formation potential of ambient non-methane hydrocarbons in a tropical semi-arid atmosphere of northwest India.

We present first-time measurements of twenty-six ambient non-methane hydrocarbons (NMHCs; C2-C8), including isoprene (C5H8), at a semi-arid site in northwest India (Ajmer; 26.45°N, 74.64°E), during January 2022-December 2023. Ambient samples were analyzed using a thermal desorption gas chromatography system equipped with dual flame ionization detectors. Daily total NMHC levels ranged from 6 ppbV to >100 ppbV. Most NMHCs, except isoprene, toluene, ethylbenzene, m-xylene and o-xylene, exhibited the highest levels in winter and the lowest in the monsoon. In contrast, others were highest in the pre-monsoon and toluene was highest during monsoon. These variations reflect the combined influence of emissions, chemistry and meteorology. Toluene and o-xylene were the dominant NMHCs (25 %-67 %). Correlation analyses indicated major contributions from liquefied petroleum gas (LPG) and vehicular emissions, with additional influence from urban and oil and natural gas activities. Compared with other Indian sites, NMHCs levels at Ajmer were 2-5 times lower than Ahmedabad and Udaipur and 10 times lower than Delhi. The total ozone formation potential was highest in the monsoon (about 175 ppbV) and lowest in the post-monsoon (about 55 ppbV), with dominance of o-xylene (24 %-33 %) and toluene (8 %-37 %). Propylene-equivalent concentrations were highest in the pre-monsoon (30.23 ppb C) and lowest in the post-monsoon (7.28 ppb C). Similarly, OH reactivity was highest in the pre-monsoon (19.58 s⁻¹) and lowest in the post-monsoon (4.71 s⁻¹), dominated by benzene and toluene. These findings emphasize the importance of NMHC chemistry in a climatically sensitive region and highlight the need for their continuous monitoring.

India↗

PubMed2026

Effects of lavender oil preparation silexan on different symptoms of major depression - results from a randomized, controlled trial.

BACKGROUND: Major depressive disorder (MDD) is characterized by depressed mood, anhedonia, and loss of energy, which can be accompanied by associated symptoms and co-morbidities. Psychiatric scales such as the Montgomery Åsberg Depression Rating Scale (MADRS) must account for the complex nature of depression. METHODS: The MADRS total score change between baseline and week 8 was the primary outcome measure in a randomized, double-blind clinical trial investigating the antidepressant efficacy of 8 weeks' treatment with silexan compared to sertraline and placebo in patients with mild or moderate MDD. We report on a pre-planned, exploratory analysis of the individual MADRS items. Treatment effects were assessed using analyses of covariance with baseline adjustment, based on an estimand strategy. RESULTS: 498 subjects (silexan 170, sertraline 171, placebo 157) were treated and analyzed. After 8 weeks, silexan was superior to placebo for 5 out of the 9 MADRS items analyzed ("apparent sadness", "reported sadness", "reduced appetite", "concentration difficulties", "lassitude"; P < .05) and showed clinically important adjusted mean value differences >0.2 points for 7 out of the 9 items. Item-level results for silexan and sertraline were mainly comparable. CONCLUSIONS: Silexan had a strong over-all antidepressant effect, with the most pronounced improvements affecting the cardinal symptoms of depression. TRIAL REGISTRATION: EudraCT2020-000688-22 first entered on 12/08/2020. Significance statement Patients with depressive disorders can show many different symptoms. To better characterize the clinical action of an antidepressant, it is therefore important to analyze not only the overall value of a depression scale but also the individual items that describe these symptoms. Silexan is a preparation from lavender oil whose antidepressant effect has been proven in a randomized, double-blind, placebo-controlled 8-week study in patients with mild or moderate major depressive disorder. Based on the individual items of the Montgomery Åsberg Depression Rating Scale that was used as the main outcome for efficacy, we found in an exploratory, hypothesis-generating analysis that silexan had a rather broad antidepressant effect in the participants of our study, with potentially clinically meaningful advantages over placebo for 7 out of the 9 individual items investigated. This applied in particular to the main symptoms of depression, namely sadness and lassitude. Our single-item analysis thus helps to understand the antidepressant effects of silexan in more detail. Significant outcomes In patients with mild to moderate major depressive disorder, lavender oil preparation silexan has a clinical profile similar to that of the selective serotonin re-uptake inhibitor sertraline based on an item-level analysis of the Montgomery-Åsberg Depression Rating Scale (MADRS). Silexan has a significant antidepressant effect that includes an alleviation of depressed mood, anhedonia, and loss of energy, the cardinal symptoms of depression. The broad improvement of symptoms of depression could not be explained by the proven anxiolytic efficacy silexan alone but indicates an independent, direct antidepressant effect. The present item-level analysis provides valuable and detailed additional insights into the therapeutic profiles of silexan and sertraline and may help clinicians to tailor antidepressant treatment to the specific symptoms of a patient. Limitations For item-level analyses of the MADRS, no validated thresholds for the assessment of the clinical importance of changes over time have been defined, taking into account that different items may have different thresholds. Even though our analyses were pre-defined, they were exploratory and did not include studywise type I error level control. Their generalizability beyond the study population is therefore limited.

Humans↗

PubMed2026

Animal-assisted therapy in pediatric urodynamics.

INTRODUCTION/BACKGROUND: Urodynamics (UDS) is associated with high levels of patient anxiety/discomfort. Children are often unable to complete UDS, with anesthesia needed to place catheters. Animal-assisted therapy (AAT) has been used in a variety of settings, but it has not been studied for UDS before. OBJECTIVE: To determine if AAT can increase success of completing UDS testing without anesthesia in children who were previously unable to perform UDS, along with decreasing distress levels. STUDY DESIGN: We performed a pilot case series of 7 patients (2 female, 5 male) aged 4-16 (mean 9.7) years who previously were unable to complete UDS awake, with AAT prior to and during the UDS procedure. A visual analog scale (VAS) was used to measure patient stress levels before and after AAT. RESULTS: We were able to successfully complete UDS testing with AAT in 6 of the 7 patients (85.7%) without the need for anesthesia. VAS scores decreased from before to after AAT (5.4-3.6, p = 0.020) but with discrepancy when compared to UDS success. DISCUSSION: Our study was the first to describe AAT during UDS. Our preliminary data found AAT to be feasible in UDS. Subjective distress may not correlate with procedural success. AAT in UDS may be more beneficial in certain populations, such as anxious children who previously were unable to tolerate UDS, and not in others such as severe neurodevelopmental conditions. Our study was limited by the small sample size, a single provider, single center, single therapy dog, inclusion of a specific population of patients, and no control group due to this being a pilot study. CONCLUSION: AAT for certain children undergoing UDS testing could help improve the ability to complete the testing without anesthesia. Further studies are needed to fully demonstrate its usefulness in UDS.

Humans↗

PubMed2026

RR-interval-based atrial fibrillation detection and burden estimation: cross-dataset validation and calibration-aware probability analysis.

Objective.Atrial fibrillation (AF) burden has become an increasingly important endpoint in long-duration rhythm monitoring, but reliable burden estimation requires more than accurate AF detection alone. In particular, when burden is derived by aggregating predicted AF probabilities over time, probability calibration may directly affect burden validity under external dataset shift.Approach.This study developed an interpretable-interval feature model for AF detection and evaluated it using record-wise cross-validation on a development cohort and independent cross-dataset external validation on public Holter electrocardiographic databases. Window-level performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (PR-AUC), Brier score, expected calibration error (ECE), and calibration intercept and calibration slope. Recording-level AF burden was estimated using both probability-based and hard-label aggregation and evaluated using mean absolute error (MAE) and agreement analyses.Main results.The model showed high discrimination in both development and external evaluation, with external ROC-AUC ofand PR-AUC of. However, external calibration deteriorated despite preserved ranking performance, with Brier score of, ECE(15) of, calibration intercept of, and calibration slope of. In the external cohort, probability-based burden estimation preserved strong association with reference burden but showed weaker raw agreement than hard-label aggregation, with MAE ofversus, consistent with systematic probability underprediction. Repeated external recalibration across record-level splits substantially improved probability quality and probability-based burden estimation. Median probability-burden MAE decreased fromwithout recalibration toafter Platt recalibration andafter isotonic recalibration, while median ECE(15) decreased fromtoand, respectively.Significance.These findings indicate that-interval-based AF detection maintained strong ranking performance in the tested external cohort, but probability calibration should be evaluated explicitly when predicted probabilities are aggregated into AF-burden estimates.

Atrial Fibrillation↗

PubMed2026

Wedge tarsectomy using patient specific instrumentation for complex multiplanar foot deformity Reconstruction: A prospective case series.

BACKGROUND: Bony correction in complex cavovarus deformities is often multiplanar. We examine our results following wedge tarsectomy (WT) using patient-specific instrumentation (PSI). METHODS: This single-centre, prospective case series evaluated noncorrectable cavovarus feet undergoing PSI-guided WT. Accuracy of PSI guides/plans, operative duration, and adjunctive procedures were recorded. Weightbearing CT (WBCT) measurements and PROM scores were recorded preoperatively and postoperatively, with 1 year follow-up. Data was then statistically analysed. RESULTS: Eleven patients were included. Planned correction was achieved (two required minor intraoperative adjustments to the initial osteotomy and nine required adjunctive procedures). Mean operative time was 135 min. Postoperative improvements were significant radiologically and in MOxFW walking distance. All fused by 3 months, with no significant complications. CONCLUSION: PSI-guided wedge tarsectomy safely achieves predictable multiplanar corrections. Our unit's experience has been excellent, with improvement in patients' walking, particularly with larger deformity corrections. LEVEL OF EVIDENCE: Level IV, prospective case series.

Humans↗