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Pancreatic cystic lesions (PCLs) are increasingly detected because of the widespread use of imaging techniques. Among them, mucinous PCLs carry a higher malignancy risk, with intraductal papillary mucinous neoplasms (IPMNs) being the most frequent subtype. Accurate stratification based on the degree of dysplasia-low-grade dysplasia (LGD) versus high-grade dysplasia or carcinoma (HGD/C)-is essential to guide clinical management and avoid unnecessary surgical interventions. This study aimed to develop and evaluate a deep learning model for stratifying IPMNs into HGD/C and LGD using endoscopic ultrasound (EUS) images. This multicenter study included EUS images collected from 5 centers across Spain, Brazil, and the United States. Ground truth classification of IPMNs was established through cytologic and biochemical analysis of cyst fluid, EUS-guided through-the-needle biopsy, or surgical specimens. A deep learning model was trained to distinguish LGD from HGD/C. Model performance was assessed on the basis of sensitivity, specificity, accuracy, and area under the precision-recall curve. A total of 51,046 EUS images were extracted from 30 examinations performed at 5 centers in Portugal, Spain, Brazil, and the United States. The model distinguished IPMNs with HGD/C from those with LGD with a sensitivity of 95.7%, a specificity of 88.7%, and an overall accuracy of 87.2%. The area under the receiver operating characteristic curve was 0.951. To our knowledge, this is one of the first studies to evaluate the potential of an artificial intelligence model for dysplasia grading of IPMNs. Prospective validation of our model is necessary to ensure clinical benefit.

This roadmap reviews CARDIO4Cities, a whole-of-city approach designed to reduce cardiovascular risk and disease at population level. As urbanization accelerates globally - with 68% of the global population projected to live in cities by 2050 - cities across income settings face a growing burden of cardiovascular disease, yet often lack operational models that translate evidence into scalable action. CARDIO4Cities responds to this gap by combining a simple, standardized population-health framework with locally adaptable implementation pathways that can be embedded within existing city systems. The approach is organized around six reinforcing pillars: quality and coordination of Care, Access to early diagnosis and management of cardiovascular risk factors, policy Reform, Data and technology, Intersectoral collaboration, and local Ownership. Rather than relying on new parallel infrastructures, CARDIO4Cities integrates evidence-based interventions into routine health services and leverages non-traditional community and private-sector actors, enabling replication across cities with varying levels of health-system maturity and resources. This document provides city health officials and their partners with a step-by-step implementation pathway, including governance structures, target-setting frameworks, intervention design processes, monitoring systems, and scaling strategies. Evaluations from the first three implementation cities-São Paulo (Brazil), Dakar (Senegal), and Ulaanbaatar (Mongolia)-demonstrated significant improvements in hypertension control and reductions in acute cardiovascular events within one to two years. Modeling projected that, without further CARDIO4Cities interventions, 2.7-7.9% of premature deaths would be averted over the subsequent decade, at costs meeting WHO-CHOICE cost-effectiveness thresholds. These results, achieved in diverse geographic, economic, and health-system contexts, illustrate the transferability of the model across income settings. Since standardization of the approach, CARDIO4Cities has expanded to more than 40 cities worldwide, including major cities in Europe and the Americas, equipping city leaders with operational guidance to implement evidence-based cardiovascular population health programs adapted to local contexts and resources. We position CARDIO4Cities as a replicable and scalable model for improving cardiovascular population health across diverse urban contexts, from resource-constrained cities initiating basic risk-factor detection to data-rich cities advancing toward precision population health.

Rare-earth elements are strategic materials essential for renewable energy, electronics, and electric mobility. The growing demand emphasizes the need for a sustainable and efficient supply, considering environmental and economic aspects. Among their main applications are neodymium-iron-boron (Nd-Fe-B) permanent magnets, whose production chain presents significant environmental impactsfrom mining to final manufacturing. This study assesses the life cycle of Nd-Fe-B magnets in the Brazilian context, following ISO 14040 and ISO 14044 standards. System modeling was performed in Sankey software, and environmental impacts were calculated using SimaPro 9.1 with data from the EcoInvent database and literature sources. Results indicate that mining is highly impactful, particularly during the roasting stage, due to high energy consumption and emissions of particulate matter and greenhouse gases. In oxide production, leaching and preseparation steps stand out for their use of hydrochloric acid, contributing to marine eutrophication and ionizing radiation. Magnet manufacturing, especially machining, shows major impacts on global warming, ozone depletion, and water use. The study highlights the need for mitigation strategies, such as stricter regulations, circular economy initiatives, and cleaner technologies. Incorporating renewable energy and improving ore processing efficiency can significantly reduce the carbon footprint of Nd-Fe-B magnets.

Oropouche virus (OROV) spread across the Americas in 2024, yet Panama's Darién migration corridor saw no outbreak until nearly a year after Brazil's January 2024 peak, raising two hypotheses: cryptic circulation masked by diagnostic gaps, or recent introduction under permissive climatic conditions. Here we resolve this paradox using integrated clinical, genomic, and climate-informed surveillance. Among 1,040 individuals tested, 43% were OROV-positive and showed a clinical signature distinct from co-circulating arboviruses, including headache more frequent than in dengue (RR 2.38, 95% CI 1.74-3.24). The household secondary attack rate was 56%, and waste burning independently predicted infection. Phylogeographic reconstruction identified a single recent introduction in October 2024 with no evidence of adaptive evolution, excluding prolonged cryptic persistence. Climate-informed models indicate broad outbreak susceptibility across Panama, with Bocas del Toro and Los Santos as the next highest-risk provinces. These findings identify a Central American foothold for OROV with potential for further northward spread.

Morphological studies, as well as comparisons and phylogenetic analyses of sequences of the 45S (= 18S-ITS-28S) nuc rDNA region and the largest subunit of the RNA polymerase II (rpb1) gene of two specimens, preliminarily named Isolate 527 and Isolate 530, showed that they are undescribed species in a newly proposed genus of the family Rhizoglomeraceae and in the genus Dominikia in Dominikiaceae (order Glomerales, phylum Glomeromycota), respectively. Consequently, Isolate 527 was described as Durabilispora carpatica sp. nov. in Durabilispora gen. nov., and Isolate 530 as Dominikia tatrensis sp. nov. Durabilispora was previously identified as an undescribed genus informally named "gen21" by other researchers. Both new species produced glomoid glomerospores in glomerocarps, which were extracted from trap cultures inoculated with mixtures of rhizosphere soils and root fragments of meadow plants from the Tatra Mountains, southern Poland. The morphological identity of Du. carpatica to the previously found Isolate 299, which was not provided with genetic data, indicated that Du. carpatica also inhabited dunes of the Baltic Sea in northern Poland.

This study explores the sustainable valorization of grape pomace digestate as a biofertilizer for the cultivation of Calendula officinalis L., a medicinal and edible flower with significant functional potential. Grape pomace, a major byproduct of winemaking, was subjected to anaerobic digestion to produce a nutrient-rich digestate applied at 0, 10, 20, and 30% concentrations under four irrigation regimes (57-232 mL day-1). Two seasonal greenhouse experiments evaluated agronomic performance, flower yield, and biochemical composition. Moderate to high digestate applications (20-30%) markedly enhanced flower yield and aerial biomass, while promoting the accumulation of proteins, lipids, soluble sugars, carotenoids, and phenolic compounds. Flowers grown under these conditions exhibited elevated β-carotene levels (80.97 mg 100 g-1) and strong antioxidant activity (>1300 μmol TEAC 100 g-1), supporting their potential in functional foods, nutraceuticals, and natural colorants. Seasonal variation influenced metabolic responses, with summer enhancing sugar and carotenoid synthesis and winter favoring pigment stability. The digestate was free from toxic elements and improved substrate fertility, confirming its agronomic safety and efficiency. A sustainability evaluation yielded an EcoScale score of 89.8, substantially higher than values reported in comparable literature, underscoring the high environmental performance and process greenness of this approach. Overall, this work presents a scalable, eco-efficient strategy to convert winery residues into high-value floral biomass, advancing circular bioeconomy principles and sustainable agricultural practices.

Covalent organic frameworks (COFs) have emerged as promising porous organic semiconductors for chemical sensing, owing to their structurally tunable electronic properties and accessible pores. A key challenge for the rational design of these materials is establishing a clear understanding of how molecular-level functionalization dictates their optoelectronic response. Here, we address this challenge through a computational investigation of TBQP-based COFs, combining density functional theory and molecular dynamics to investigate the impact of edge functionalization on their electronic structure, optical properties, and adsorption reactivity toward Cl2, ClF3, and SO2. Using representative molecular models and fragments derived from the TBQP architecture, our results demonstrate that the Frontier orbital energies and band gap of the extended framework are primarily governed by the electronic character of the constitutive building blocks. This enables systematic property modulation through targeted substituent effects. We establish quantitative correlations between experimental Hammett parameters, DFT-based reactivity indices, and analyte-induced electronic perturbations, providing descriptors that link chemical modification to optoelectronic behavior. Furthermore, we find that analyte adsorption can introduce midgap states, revealing a general electronic sensing mechanism for π-conjugated COFs. These findings not only offer practical guidelines for tailoring the electronic and reactive properties of TBQP frameworks but also underscore the critical role of molecular functionalization in governing the sensing performance of porous organic semiconductors. The identified structure-property relationships provide useful guidelines for the rational design of COF-based sensors.

Bard, Keller, and Leavens' call for a WILD psychology is timely. This commentary argues that moving beyond WEIRD bias requires accountability and structural transformation, not just awareness or inclusivity. We must challenge the aspiration to universality, embrace multiplicity, and engage in anticolonial praxis to dismantle systemic inequities in knowledge production and achieve genuine epistemic justice in the developmental sciences.

When multiple vaccines are simultaneously recommended, a statistical method to monitor adverse events accounting for multiple combinations of vaccine exposure rather than each vaccine individually is preferred. We introduce an adaptive multiple hypotheses test method for rapidly detecting increased risks of adverse events from one or more combinations of simultaneous vaccine exposure, for example, exposed to influenza vaccination only; exposed to COVID and influenza vaccinations; exposed to COVID, influenza, and respiratory syncytial virus (RSV) vaccinations. We do this by extending the binomial maximized sequential probability ratio test (MaxSPRT) method to a multinomial probability model. With an exact analytical alpha spending approach, the computationally feasible limit of multiple exposures is likely limited to two vaccines. For more complex situations with three or more vaccines and multiple adverse event endpoints, we demonstrate a valid Monte Carlo approach. Illustrative examples and simulation studies were performed with the R Sequential package.

Cardiorespiratory fitness (CRF) is a strong predictor of mortality and noncommunicable disease risk, but its underlying molecular mechanisms are poorly understood. In this study, we identified 2 signatures of CRF (1 metabolomic and 1 proteomic) from UK Biobank participants who completed a risk-stratified submaximal cycle ergometer test, with CRF estimated from the heart rate response to incremental workload. These signatures were validated in an independent sample of UK participants with data on metabolomics (n=354 222) and proteomics (n=29 961) to investigate prospective associations with all-cause mortality and noncommunicable diseases. Prospective associations were evaluated using Cox proportional hazards models adjusted for age, sex, ethnicity, socioeconomic status, lifestyle factors (including smoking, alcohol intake, diet, and body mass index), and relevant medical history. Our findings reveal that higher CRF is characterized by downregulation of pathways related to inflammation, triglyceride metabolism, glycolysis, and vascular dysfunction, and upregulation of pathways related to cholesterol transport, apolipoprotein particle size, and cytoskeletal remodeling. Leveraging these insights, we developed 2 novel signatures of CRF (1 metabolomic and 1 proteomic) that robustly reflect CRF levels (R2: 0.50-0.60). Over an average of 9 years of follow-up, we observed 27 659 cases of all-cause mortality. Across the discovery and validation cohorts, we found that the metabolomic signature of CRF was strongly associated with a 39% to 54% lower risk of all-cause mortality and markedly reduced risk of type 2 diabetes (90% in both), cardiovascular disease (42%-47%), and colorectal cancer (33%-39%). Additionally, the proteomic signature of CRF was associated with a 17% lower risk of all-cause mortality, and with a 22% to 39% lower risk of type 2 diabetes and cardiovascular disease. Together, these findings indicate that circulating metabolites and proteins are associated with CRF and with subsequent risk of mortality and noncommunicable diseases.

Duchenne muscular dystrophy (DMD) is a progressive neuromuscular disorder caused by DMD pathogenic variants, leading to dystrophin deficiency, muscle degeneration, loss of ambulation, respiratory failure, and reduced life expectancy. Current treatments, such as corticosteroids and supportive care, offer limited long-term benefits. Delandistrogene moxeparvovec is a promising gene therapy developed to restore dystrophin expression and deliver microdystrophin to skeletal and cardiac muscles. This systematic review and meta-analysis evaluate the efficacy of this treatment in ambulatory pediatric patients with DMD. A systematic search of Cochrane, PubMed, and Embase identified randomized controlled trials (RCTs) and cohort studies on delandistrogene moxeparvovec in ambulatory male children (&#x2265;4 to <8 years) with DMD. Primary outcomes included NSAA score changes, a 10-meter walk/run test (10MWR), time to rise (TTR), and dystrophin expression. Study selection followed PRISMA guidelines, and statistical analyses were conducted using R software. The study was registered in PROSPERO (CRD42025635605). We included 302 participants from 4 studies (2 RCTs). Follow-up ranged from 48 weeks to 5 years, with results analyzed at 1 year. Delandistrogene moxeparvovec was administered to 107 affected individuals, while 195 were in the control group. At 1 year, the therapy significantly improved NSAA scores (MD = 2.48, p = 0.04) and TTR (MD = -0.85, p < 0.01). Sensitivity analysis demonstrated improved 10MWR (MD = -0.71, p = 0.02). Muscle dystrophin content significantly increased (MD = 28.39, p < 0.01). Delandistrogene moxeparvovec, despite high heterogeneity for the analysis, improved functional outcomes in ambulatory pediatric patients with DMD. Further long-term RCTs are needed to confirm its safety and efficacy.

Alkali-metal niobates MNbO3 (M = Na, Li) decorated with platinum (Pt) nanoparticles (NPs) are innovatively utilized as catalytic supports for hydrogen (H2) evolution from sodium borohydride (NaBH4). Notably, a direct comparison between sodium niobate (NaNbO3) and lithium niobate (LiNbO3) in their efficiency for H2 evolution from NaBH4 was conducted for the first time, highlighting the distinct catalytic performance of these materials. The synthesis was confirmed by X-ray diffraction (XRD), scanning electron microscopy (SEM), and high-resolution transmission electron microscopy (HRTEM). The deposited Pt nanoparticles remain below 10 nm. In this study, different transition-metal nanoparticles (M = Co, Ni, Pd, Pt) supported on NaNbO3 and LiNbO3 were evaluated as catalysts. The Pt NPs/NaNbO3 and Pt NPs/LiNbO3 catalysts demonstrated optimized performance, producing H2 at similar rates of 2044.9 and 2303.7 mL min-1 gcat -1 at 293.15 K. Arrhenius plots indicate activation energies (E a) of 35.54 &#xb1; 1.32 kJ mol-1 for Pt NPs/NaNbO3 and 35.04 &#xb1; 1.32 kJ&#xb7;mol-1 for Pt NPs/LiNbO3. Additionally, the materials exhibited consistent stability, with an efficiency loss of less than 20% after the 10th cycle of use. These results underscore the potential of these catalysts for H2 generation applications.

This commentary explores the shift from WEIRD to WILD psychologies, showing how a focus on cultural diversity and meaning-making aligns with this movement. Using examples, we argue that the epistemic recognition of Global South realities is an urgent act of justice - one that frees psychology from its colonial imagination and opens space for many ways of knowing, caring, and becoming human.

Candidozyma aurisauris (formerly Candida auris) is an emerging, multidrug-resistant fungal pathogen that is difficult to identify and has become an increasing challenge for global public health. In recent years, its detection in wastewater has raised concerns regarding the potential environmental dimensions of its dissemination and the associated public health implications. This study examines the current evidence on the occurrence of C. auris in wastewater, with an emphasis on the concentration, isolation, and identification methodologies employed in recent investigations. Framed within a One Health perspective, the analysis discusses potential pathways of environmental dissemination through wastewater effluents and biosolids, particularly in the context of the expanding reuse of treated wastewater and the land application of sewage sludge. The review also highlights existing regulatory gaps, including the absence of specific guidelines addressing pathogenic fungi in wastewater treatment plant byproducts as well as the lack of standardization in reported data, which hinders more in-depth analyses. Overall, this work identifies important knowledge gaps and emphasizes the need for further studies and interdisciplinary surveillance strategies to better understand the environmental circulation of C. auris. Additionally, a conceptual workflow is proposed to advance the standardization of analytical approaches and data reporting, contributing to strengthening public health, environmental protection, and sanitary policies.

Polygenic risk scores (PRSs) are increasingly being considered as tools to refine risk stratification in cardiovascular and cardiometabolic disease, but their clinical translation remains constrained by a central limitation: most currently available PRSs were derived in predominantly European-ancestry datasets and perform less well in admixed and underrepresented populations. This limitation reflects differences in allele frequencies, linkage disequilibrium structure, imputation performance, ancestry-specific effect sizes, and environmental context, and is especially consequential in recently admixed populations, in whom local ancestry and internal heterogeneity further complicate prediction. In this review, we examine recent methodological and translational advances in PRS development across diverse populations, with emphasis on coronary artery disease (CAD), blood pressure and hypertension, type 2 diabetes, obesity, and atrial fibrillation. We highlight the transition from single-ancestry prediction to multi-ancestry frameworks, as well as emerging approaches tailored to admixed genomes, including ancestry deconvolution-based and local-ancestry-aware models. Across traits, broader discovery resources and ancestry-aware methods have improved predictive performance beyond naive European transfer, but progress remains uneven. CAD currently represents the most mature phenotype, with the strongest evidence for clinically relevant gains from multi-ancestry PRS development and validation. Blood pressure and hypertension, as well as type 2 diabetes, show substantial methodological progress but remain limited by calibration, context dependence, and incomplete evidence for implementation. Obesity and atrial fibrillation are advancing rapidly, but their translational readiness remains less developed. We argue that admixed and underrepresented populations should not be viewed only as settings in which PRSs underperform, but as essential contexts for building more robust and clinically generalizable models. The next phase of precision cardiovascular medicine will depend not simply on improving prediction, but on demonstrating that PRS-informed risk assessment can be calibrated, interpretable, and clinically useful across the diverse populations in whom it is intended to guide care.

Several studies have revealed that polycarboxylate superplasticizers (PCEs) with shorter side chains and higher anionicities can overcome challenges posed by the high alkaline environment and disperse alkali-activated slags (AASs). However, how adsorption-dispersion translates into macroscopic setting behavior and early hydration remains insufficiently understood. Here, a series of isoprenyl oxy poly-(ethylene glycol) ether (TPEG) PCEs were synthesized with an identical side-chain length (n EO = 10) but different anionicities by varying the feeding molar ratio of acrylic acid (AA:TPEG = 3, 4.5, and 7), enabling the isolated investigation of anionicity effects. A comprehensive analysis was conducted on NaOH-activated slag using adsorption measurements, &#x3b6;-potential analysis, isothermal calorimetry, setting time determination, compressive strength testing, and XRD characterization. It was found that an increase in PCE anionicity could enhance adsorption by stronger Ca2+ complexation, providing not only better dispersion but also a longer setting time and slightly delayed and reduced heat flow peak. However, these drawbacks did not compromise early strength development because the high-anionicity PCE can promote better particle stabilization. It was proposed that the more effectively dispersed the system is, the more prolonged the dissolution process may become, leading to delayed local precipitation. Consequently, hydration progression may be sustained, resulting in a higher compressive strength. These findings provide insight into the role of polymer charge density in influencing hydration and strength evolution in the NaOH-activated slag.

Obstructive sleep apnea (OSA) exhibits substantial phenotypic heterogeneity, but its prognostic relevance in patients with coronary artery disease (CAD) undergoing revascularization remains uncertain. We pooled data from two prospective cohorts of CAD patients undergoing percutaneous coronary intervention or coronary artery bypass grafting (n = 2318). Major adverse cardiac and cerebrovascular events (MACCE; cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, and unplanned revascularization) were assessed over a mean follow-up of 1.9 &#xb1; 1.1 years. Latent class analysis using nine clinical variables identified phenogroups. Associations between OSA (apnea-hypopnea index &#x2265;15) and MACCE were evaluated using Cox regression. Three phenogroups were identified: (1) Younger-Sleepy-Hypoxia (42.2%), (2) Cardiorenal-Metabolic (30.9%), and (3) Old-Lean-Chinese (26.9%). OSA prevalence was similar across groups (45.5%, 50.7%, and 47.8%). The overall incidence of MACCE was 11.4% and did not differ significantly across phenogroups (p = 0.127). OSA was associated with increased MACCE risk in the overall cohort (adjusted HR 1.55, 95% CI 1.20-2.00; p < 0.001). In phenogroup analyses, this association was significant in phenogroup 1 (adjusted HR 1.57, 95% CI 1.04-2.36; p = 0.030), borderline in phenogroup 2 (adjusted HR 1.55, 95% CI 0.98-2.43; p = 0.059), and not significant in phenogroup 3 (adjusted HR 1.32, 95% CI 0.81-2.16; p = 0.263). In revascularized CAD patients, OSA was associated with increased cardiovascular risk in the overall cohort, with heterogeneity across phenogroups. These findings support phenogroup-based risk stratification, pending external validation.

In this paper, we report simulations of the water dimer under a uniform external electric field carried out within the framework of density functional theory (DFT). By gradually increasing the field intensity, we identify a structural transition characterized by an abrupt change in the orientation of the molecular dipole moments relative to the applied field. Below a critical field strength, the system remains in a conventional water dimer configuration. Above this limit, the dimer undergoes a reorientation, leading to a cis-like arrangement associated with a unilateral movement of the donor hydrogen. Vibrational analysis confirms that this field-induced cis configuration corresponds to a stable local minimum. We further analyze the structural and electronic properties of this configuration and propose a semiclassical interpretation of the transition based on the interaction between dipole-dipole interactions and the torque exerted by the external electric field within a classical electrodynamic structure. Hysteresis analysis reveals that the electric field drives the system between distinct local minima on the potential-energy surface, stabilizing a high-dipole structure even after the external field is removed.

Macauba seed cake, a carbohydrate-rich biomass from seed mechanical oil extraction, is a promising feedstock for sustainable biorefinery applications. In this study, seed cake polysaccharides were characterized, and a mechanochemical pretreatment using planetary ball milling was applied as a chemical-free strategy to overcome biomass recalcitrance. The effects of dry grinding at different times (30, 60, 120, 180, and 240 min) were evaluated through 13C solid-state nuclear magnetic resonance, X-ray diffraction, and mid-infrared FTIR spectroscopy. The characterization of macauba seed cake confirmed it to be a rich source of d-mannose (44%). Solid-state 13C CPMAS NMR proved to be highly sensitive for monitoring mannan I polymorphs and revealed progressive amorphization during the pretreatment. Ball milling significantly reduced mannan crystallinity (from 26.6% in untreated biomass to 1.2% after 120 min and 2.4% after 180 min of pretreatment), promoted polymorphic transformations, and induced structural modifications in the polysaccharide functional groups. These structural changes improved polysaccharide bioavailability, leading to improved enzymatic hydrolysis by mannanases produced from Aspergillus niger. Saccharification yields, using 20 IU of mannanases per gram of dry biomass, reached up to 76.8% mannose release after 120 min of milling, confirming the strong correlation among crystallinity reduction, amorphization of mannan I, and enzymatic digestibility. Overall, macauba seed cake was validated as a promising feedstock for mannose recovery and other reducing sugars. To our knowledge, this is the first report of mannose production from macauba seed cake via ball milling and enzymatic hydrolysis and the first to demonstrate solid-state NMR as a tool to track amorphization in mannan-rich biomasses.