We applaud Kakad et al. for their convincing analysis of melatonin’s potential as a treatment for long-term COVID-19 (LC19), emphasizing its pleiotropic effects. Due to oxidative stress and chronic inflammation, LC19 has caused millions of people to suffer from cardiovascular problems such myocarditis and thrombosis. Even while corticosteroids are still a mainstay of treatment, long-term usage of them can have serious adverse effects, such as disruption of metabolism and disturbed sleep. In this letter, we present a novel chronotherapeutic strategy that combines evening melatonin supplementation with morning corticosteroid delivery that is timed to coincide with natural cortisol peaks. This approach seeks to minimize side effects brought on by corticosteroids while maximizing the anti-inflammatory and cardioprotective benefits of both drugs. The cardioprotective, anti-inflammatory, and antioxidant qualities of melatonin enhance corticosteroid treatment, potentially lowering dosages and improving patient results. In order to continue this strategy through coordinated, multi-center trials and guarantee thorough assessment and application of this potential therapeutic paradigm, we also support the creation of a Global LC19 Chronotherapy Consortium.

This paper introduces a novel nonlinear model predictive control (NMPC) framework that incorporates a lifting technique to enhance control performance for nonlinear systems. While the lifting technique has been widely employed in linear systems to capture intersample behaviour, their application to nonlinear systems remains unexplored. We address this gap by formulating an NMPC scheme that combines fast-sample fast-hold (FSFH) approximations and numerical methods to approximate system dynamics and cost functions. The proposed approach is validated through two case studies: the Van der Pol oscillator and the inverted pendulum on a cart. Simulation results demonstrate that the lifted NMPC outperforms conventional NMPC in terms of reduced settling time and improved control accuracy. These findings underscore the potential of the lifting-based NMPC for efficient control of nonlinear systems, offering a practical solution for real-time applications.

In our rapidly changing world, evolution is likely to play an important role in facilitating the resilience of wildlife populations. The mountain yellow-legged frog (Rana muscosa/Rana sierrae) provides a rare example of recovery following severe declines caused by the amphibian chytrid fungus (Batrachochytrium dendrobatidis). However, the role of evolution in facilitating this recovery remains circumstantial. In this study, we sought to gain insights into the potential role of evolution by comparing genomes of frogs from naïve and recovering populations located in relatively close proximity. Using multiple methods to scan frog genomes for signatures of selection, our study reveals several genomic variants associated with frog recovery. Specifically, we identify gene variants in interferon-related genes and genes associated with the complement system and major histocompatibility complex (MHC). Additionally, we identify a recovery-associated variant in RIN3, a gene that may play a critical role in disease defense and wound healing. Finally, we report no differences in genetic diversity between naïve and recovering populations. We provide a rare example from natural populations that suggests that evolution can produce individuals that harbor adaptive alleles and allow population recovery in a novel environment. These findings complement recent research on amphibian immune evolution and provide mechanistic hypotheses for how individuals from populations can recover from disease.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that leads to dementia. Many cases are diagnosed annually and there is no currently available cure. Understanding the underlying disease biology of AD through the study of molecular networks, particularly by mapping clinical variants to tissue-specific interactomes and regulatory macromolecular assemblies, offers a promising avenue to elucidate altered disease pathways. This, in turn, could provide valuable insights for drug discovery. In this study, we leverage our manually curated AD-specific dataset from the IMEx consortium, which provides detailed interaction data, including the relationship between interacting partners, detection in specific host tissues and cell lines, and the impact of variants on interaction outcomes. By integrating these data with information on protein complex composition taken from the Complex Portal, we have identified relevant macromolecular assemblies enriched in AD networks. Further pathway enrichment analysis is conducted using Reactome, enabling a comprehensive exploration of disease mechanisms and potential therapeutic targets.

BACKGROUND: Glucagon-like Peptide 1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) risk, but it is unclear which populations benefit most. Recent pharmacoepidemiologic studies have employed iterative causal forest (iCF), a machine learning (ML) algorithm to identify subgroups with heterogeneous treatment effects. While iCF do not rely on prior knowledge of treatment-variable interactions, it may be constrained by missing or misdefined variables in pharmacepidemiology studies. METHODS: We applied the high-dimensional iterative causal forest (hdiCF), a causal ML algorithm that does not reply on predefined variables, to MarketScan 2016-2020 claims data to identify populations with asthma that might benefit most from GLP1RA in reducing AE risk. We built a GLP1RA vs sulfonylurea new-user cohort with ≥ 1 inpatient or 2 outpatient asthma encounters, excluding patients with non-asthma indications for systemic steroids. Using 599 high-dimensional features from inpatient/outpatient services and pharmacy claims, patients were followed for 6 months from their second prescription. The outcome was acute AE (hospital admission or emergency department visit for asthma). RESULTS: In the overall population, GLP1RA decreased AE risk relative to sulfonylurea: aRD -1.4% (-2.0%, -0.8%). hdiCF identified 3 subgroups based on systemic steroid prescription fills (0, 1, and ≥2): patients with ≥2 systemic steroid prescriptions (GLP1RA: 34 events/1367 individuals; sulfonylurea: 53/1013) benefited most from GLP1RA: aRD -3.8% (-5.3%, -2.2%). CONCLUSIONS: This study demonstrates how automated feature identification can pinpoint clinically relevant subgroups with varying treatment effects. Systemic steroid use, as a proxy for severe asthma, may guide personalized predictions of GLP1RA’s short-term benefits on acute AE.

A major goal in marine ecology is to understand patterns of larval dispersal and population connectivity. Dispersal plasticity allows for adaptive variation in dispersal phenotypes in response to variation in environmental conditions and may help to explain intraspecific variation in dispersal distances. However, this phenomenon has not yet been investigated in marine fishes. Here, we test the hypothesis that parents produce larvae with different dispersal-related traits in response to variation in environmental quality using the orange anemonefish, Amphiprion percula. By experimentally manipulating food rations, we show that parents produce larger offspring on low-food rations than on high-food rations. However, there was no effect of parental diet on larval critical swimming speed. We also found an effect on larval otolith core size which, in combination with parentage analyses, may provide a way to test the dispersal plasticity hypothesis in the field. This study shows that parents can produce different larval phenotypes in response to variation in environmental conditions, demonstrating plasticity in a dispersal-related trait which may help to explain observed variation in A. percula larval dispersal distances. Incorporating dispersal plasticity into our understanding of marine dispersal patterns may enhance our understanding of marine metapopulation ecology, fisheries management, and conservation.

Age information is fundamental in population biology. In fisheries management, robust and effective stock assessment models rely on fecundity and survival rates, and other life history traits that are generally age specific. Current aging methods for most fish species are based on the number of otolith growth rings, a time intensive method that requires lethal sampling and highly specialized expertise. To supplement current otolith-based aging efforts, here we develop a DNA methylation approach for aging Atlantic Halibut. We conducted whole-genome methylation sequencing on 66 wild caught individuals with otolith-derived age estimates. The resulting 14,588 CpG sites were evaluated as predictors of age in an elastic net model. We found a strong positive linear correlation between otolith age and predictions using a subset of 87 CpG sites selected by the elastic net model that had a mean absolute error of less than one year. The enzymatic treatment required for methylation sequencing with short-read technology like Illumina is still cost-prohibitive for routine application of large numbers of individuals. Accordingly, we conducted a successful pilot test to use adaptive nanopore sequencing for rapid, large-scale aging, and developed a framework to process the data for use in an aging framework. Our technique can be used to age Atlantic halibut when non-lethal sampling is needed (e.g., tagging studies) and to supplement otolith aging data for lethally sampled fish.

Background: In HPV-primary screening, sample quality significantly influences test accuracy. Unlike cytology-based screening, no consensus guidelines exist for sample quality assessment in HPV testing. This study aims to evaluate the impact of sample cellularity on HPV testing. Methods: A total of 37,592 liquid-based cytology (LBC) samples from women undergoing screening (aged 30-64, mean 47.8±9 years) were analyzed using Cobas®4800 HPV Test (Roche). Sample adequacy was assessed by the assay’s β-globin internal control and by an independent quantitative cellularity assessment (OncoPredict HPV, Hiantis). HPV positivity rates (PR) were stratified according to β-globin Ct values. Results: Overall HPV-PR was 7.7%. PR reached 9.7% in samples with β-globin ≤ 28Ct, decreasing markedly to 1.4% for β-globin > 34 Ct (p < 0.001). Quantitative analysis showed that Cobas®4800 β-globin Ct = 34 corresponds to approximately 1,5x10^3 nucleated cells/rxn. A subset of 195 HPV-negative samples with β-globin Ct ≥34 was evaluated by LBC: 19% had inadequate cellularity according to LBC guidelines, 8% ≥ ASC-US and 73% NILMs, of which 65% showed cellular atrophy. Conclusion: These findings emphasize the importance of assessing cellularity in HPV-screening in order to avoid potentially false-negative results due to inadequate samples. Future research should focus on establishing standardized cellularity thresholds to improve screening accuracy.

Background: Non-ischemic cardiomyopathies can be primary (p-NICM) which involves mainly the heart muscle or caused by systemic disease with heart muscle involvement as it is seen in systemic infiltrative diseases (i-NICM). There is limited data on the safety and in-hospital outcomes of ventricular tachycardia (VT) ablation in i-NICM. Methods: We identified patients who underwent VT ablation between 2018-2021 using the National Inpatient Sample Database. i-NICM include amyloidosis, hemochromatosis, or sarcoidosis. In-hospital complications include mortality, acute kidney injury (AKI), acute heart failure (AHF), bleeding, vasopressor use, blood transfusion and cardiac tamponade. Multivariate logistic regression analyses were performed. Results: There were 7,420 VT ablations, 7,235 had P-NICM and 185 had i-NICM. A multivariable analysis did not reveal any difference in mortality (adjusted odds ratio [aOR]: 0.81; 95% confidence interval 0.32-1.98; p=0.62), AHF aOR: 0.88 (0.41-1.81; p=0.69, AKI aOR:1.17 (0.83-1.65); p=0.36, blood transfusion aOR: 0.63 (0.25-1.59); p=0.33, vasopressor aOR: 0.86( 0.51-1.49); p=0.61 or pericardial effusion/ tamponade aOR: 1.16 (0.67-2.1); p=0.58 Figure Conclusion: Patients with i-NICM had similar in-hospital complications compared to P-NICM further supporting the safety of VT ablation in managing recurrent VT in patients with i-NICM.

Understanding population response to disturbance is critical to both ecological theory and wildlife conservation. The current framework for quantifying demographic resilience assumes that resilience is static. Yet, survival and fecundity, two key components of demography, change over time. Here, we assessed how incorporating time affects the estimates of demographic resilience of two spotted hyena (Crocuta crocuta) populations with 55 years of combined longitudinal data. We developed an approach based on mark-recapture data, matrix population models and transient analyses to calculate five resilience metrics. We found strong evidence that incorporating time improves the assessment of inertia (long-term population response) and maximum attenuation (greatest reduction in population size). Resilience estimates were also highly sensitive to population structure, the proportion of individuals in different life states. Considering variation over time in assessing demographic resilience will make resilience estimates more accurate, thereby extending their utility for both ecological theory and conservation.

Coloration and patterning have been implicated in lineage diversification across various taxa, as color traits are heavily influenced by sexual and natural selection. Investigating the biochemical and genomic foundations of these traits therefore provides deeper insights into the interplay between genetics, ecology, and social interactions in shaping the diversity of life. In this study, we assessed the pigment chemistries and genomic underpinnings of carotenoid color variation in naturally hybridizing Dinopium flamebacks. We employed reflectance spectrometric analysis to quantify species-specific plumage coloration, High-Performance Liquid Chromatography (HPLC) to elucidate the feather carotenoids of flamebacks across the hybrid zone, and Genome-Wide Association Study (GWAS) using next-generation sequencing data to uncover the genetic factors underlying carotenoid color variation in flamebacks. Our analysis revealed that the red mantle feathers of D. psarodes primarily contain astaxanthin, with small amounts of other 4-keto-carotenoids. In contrast, the yellow mantle feathers of D. benghalense predominantly contained lutein and 3’-dehydro-lutein, alongside minor amounts of zeaxanthin, β-cryptoxanthin, and canary-xanthophylls A and B. Hybrids with an intermediate, orange, coloration deposited all of these pigments in their mantle feathers, with notably higher concentrations of carotenoids with ε-end rings. The GWAS analysis identified the CYP2J2 gene, which plays a role in carotenoid ketolation, as co-varying with color. This gene exhibited significant allele variation and evidence of multiple copies across species. These findings contribute to the growing knowledge on avian carotenoid metabolism and highlight how genomic architecture can influence phenotypic diversity.

Contemporary work environments require humans to process audiovisual information displays whilst moving around the world. The attentional demands associated with using devices such as in-ear headphones and head-mounted displays may be significantly influenced by varying locomotor demands, yet this relationship remains poorly understood. This study investigates the interplay of information presentation modality, movement state, and cognitive task difficulty. In a virtual reality laboratory, 22 participants performed a cued task-switch paradigm with two difficulty levels while standing, walking, or walking with perturbations on a treadmill. We used a questionnaire, behavioral and mobile EEG data to investigate cognitive-motor interference. We find that locomotion interfered with cognitive task performance, and that the presentation modality of task-switch notification modified the nature of this interference. While auditory cue presentation resulted in faster responses under low cognitive load conditions, visual information presentation was less impaired by higher cognitive and locomotor demands. A detailed analysis of the EEG response to cues addressed these differences in terms of multi-modal attentional mechanisms. Hence, wearable information presentation should be tailored to the specific needs, particularly for cognitively demanding information in mobile work settings.

We present a novel method utilizing in-situ video data of fish locomotion to calculate thrust. This methodology was applied to several large elasmobranch species, which are typically challenging to measure. Using motion tracking software, we analyzed video footage of both wild and captive sharks to track their position and speed. In order to estimate the total force output, we used the tail/body motion in respect to the surrounding medium assuming equilibrium conditions. The force output for each shark was converted into scaled thrust, enabling comparisons independent of size. This scaled thrust was then analyzed across swimming modes and caudal fin morphology, serving as a proxy for each species’ behavioral ecology. Through PCA analysis we demonstrate the coupling between morphological traits and hydrodynamic forces. The ratio of the upper to lower lobe of the caudal fin (CLAR) emerged as a strong predictor of scaled thrust, accounting for over 80% of observed variation. These morphological traits, a proxy for behavioral ecology, appear to be the most suitable predictor of hydrodynamic forces given the quantitative nature of the variable compared to the categorical classifications of swimming mode. Our findings indicate that coastal pelagic species exhibited similar but significantly lower scaled thrust values than benthic species, suggesting that benthic species may be less efficient, expending more energy to remain aloft or compensate for drag relative to generating forward motion. Our findings demonstrate how morphological traits have evolved to optimize energy expenditure based on behavioral ecology, highlighting a tradeoff between benthic and coastal pelagic species. We propose that the unique ecological niches of these species drive behavioral changes that result in morphological adaptations to optimize performance. Given the relatedness between morphology/behavioral ecology and swim mode, selected pressure overtime could also explain the ecological need of different swim modes.

Background: Hemophagocytic lymphohistiocytosis (HLH) is a potentially fatal condition. Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) overlaps with HLH. Human-herpesvirus 6 (HHV6) is a common childhood infection that rarely causes neurological complications. HHV6-related HLH/DRESS has only been described in case reports . Procedure: From all admissions to Children’s Minnesota with positive HHV6 the records of a subgroup and additional patients from Israel formed a cohort of patients with HHV6-rlated HLH using HLH-2004 criteria. Results: Of 50 consecutive HHV-6 patients, five (10%) developed HLH/DRESS and with two from other centers a cohort of seven is described (six with HLH and one with DRESS). Four had concurrent viruses as possible pathogenic factors. All had thrombocytopenia, elevated soluble IL2 receptor (CD25), and fever; 6/7 had elevated ferritin, and all 5 evaluated had bone marrow hemophagocytosis. Most (6/7) had CNS involvement, all had liver abnormalities, and most had coagulopathy. One patient with Kabuki syndrome was on gammaglobulin replacement therapy, whereas none of the other patients had immune deficiency. One patient had a heterozygous pathogenic variant of TNFSF13B, with no immunodeficiency. Four required etoposide and dexamethasone therapy, while three were also treated with ganciclovir/valganciclovir. The outcome was excellent (median follow-up almost 6 years) with no neurologic sequelae, recurrent HLH, or need for hematopoietic stem cell transplantation. Conclusions: The high incidence of HHV6-related HLH in admitted patients indicates a strong need for vigilance regarding this condition. HHV6-related HLH has a high rate of CNS manifestations, but the outcome in this group of patients was excellent.

Given scarce data on childhood cancer outcomes in Colombia and discrepancies among hospital-based, population-based, and government registries, we implemented VIGICANCER, a childhood cancer clinical outcomes surveillance system to collect, analyze, and disseminate valid, reliable, and timely data. VIGICANCER has expanded to ten Colombian cities, achieving inclusion of 55-60% of children nationwide. VIGICANCER yields key, exhaustive, and actionable population-based information, guides multilevel interventions, and informs public policy while providing timely feedback to participating institutions. VIGICANCER’s systematic results have positioned our childhood cancer surveillance system as a successful model in Latin America, reproducible in other low–and middle-income countries with similar contexts.

The use of additive manufacturing has increased significantly in recent years, particularly in the aerospace industry. However, AM materials often exhibit defects that adversely impact fatigue performance. This study examines the geometric and morphological features of critical defects observed in Ti-6Al-4V specimens. A framework for automatic fatigue failure analysis through computer vision is proposed. An AI-based tool was trained to identify critical defects, measure their proximity to the surface, and quantify 14 geometric and morphological features. The findings indicate that surface proximity is the most influential factor in fatigue life classification, with defects near the surface exerting a negative impact on performance. No clear trend was observed in defect morphology beyond a certain surface distance. For lack-of-fusion defects classified as critical, the X-parameter model was applied and a correlation of R 2 = 0 . 9 1 with the measured CTF was obtained.

The achievement of optimal lifetime and efficiency in stationary battery energy storage systems (BESS) is crucial and may require custom-made operational strategies for each grid application. This work focuses on addressing one of the key operational challenges: power distribution among the sub-units of a BESS, which leads to uneven aging and affects the overall usable capacity of a multi-pack battery system. While adjusting power setpoints of these sub-units can improve efficiency and aging performance, it can inherently introduce challenges of state of charge (SOC) imbalance within the system. This imbalance, coupled with temperature inhomogeneities in the battery packs, significantly affect the aging rate and further exacerbate system imbalances. To mitigate imbalances, a model predictive control (MPC)-based optimizer for SOC balancing is developed and evaluated against conventional and literature-derived rule-based control (RBC) strategies. Mixed-integer linear programming (MILP) is incorporated into the MPC optimizer to account for non-linear inverter losses during operation. A 1D thermal simulation, developed in this study, is used to analyze the temperature imbalances caused by these control strategies. The simulation estimates the spatial temperature distribution within each pack at the end of the operation, considering internal dissipative losses in the battery modules under fixed boundary conditions for passive air cooling. The comparative case study conducted in this work focuses on key performance metrics such as availability index (AI), fulfilment factor (FF), inverter and battery efficiencies, and state of health (SOH). These metrics are computed by coupling the power split control strategies with 1D thermal and aging estimation models through an equivalent circuit model (ECM). It suggests that due to the delayed balance of the SOC and non-uniform power distribution in RBC strategies, the availability and energy throughput of the system is lower than the desired 100% achieved using MPC. In addition, higher battery pack temperatures of up to 314 K in one of the RBC strategies were estimated, while MPC control induced a maximum temperature of up to 300 K thereby also achieving more balanced temperatures across packs. With the help of the SOC and temperature profiles during their operation, these control strategies are compared for their aging. MPC control strategy exhibited the lowest drop in state of health due to maintaining lower temperatures and mean SOC levels.

Vegetation stability is vulnerable to climate change in Central Asia. However, how future climate variations and extremes influence the vegetation stability in Central Asia has not been well understood. In this study, we investigated future vegetation stability quantified by the variability of vegetation productivity and attribution to climatic variation and negative extremes in Central Asia under four Shared Socioeconomic Pathways scenarios (SSPs) during 2021-2100, using Coupled Model Intercomparison Project phase 6 simulations. We found that the interannual variability (IAV) of Net Primary Production (NPP) would be larger under higher anthropogenic emissions scenarios. The standard deviation of NPP IAV increases from 64.55 Tg C yr -1 under SSP1-2.6 to 78.01 Tg C y r -1 under SSP5-8.5. The north of Central Asia accounts for the largest contribution (48% -53%) to Central Asia’s NPP IAV under SSP1-2.6 to SSP5-8.5. Compared to temperature IAV, precipitation IAV exerts a larger contribution to NPP IAV in Central Asia, due to the higher sensitivity of NPP IAV to precipitation IAV. Dry conditions are the main climate extremes causing negative NPP extremes in Central Asia, especially in the north and southeast of Central Asia. Our findings identify the northern and southeastern regions with higher instability posed by future climate changes in Central Asia, and provide scientific guidance for regional water management to mitigate ecosystem instability.