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PubMed2026

In situ product monitoring in heterogeneous reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3: Effect of environmental factor and particle property.

Gas-particle reactions represent an important atmospheric heterogeneous transformation process for organic amines (OAs). Environmental factors and particle properties may impact the gas-particle reaction products. Although the products from gas-particle reactions can be monitored by various in situ techniques, related data remain scarce. Here, the interfacial and gaseous products from the reaction of trimethylamine on Fe2O3/Fe(NO3)3 particles under light irradiation with mixed NO2, O2, SO2 and H2O were monitored using in-situ diffuse reflectance Fourier transform infrared spectroscopy and proton transfer reaction time-of-flight mass spectrometry. Dark reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3 generated two interfacial products types: N-containing ones (CH3NCH2, CH3NO2, (CH3)2NCHO, and CH3N(OH)CHO) and N-free ones (alcohols, aldehydes and acids), both accumulating with reaction progression. Light irradiation and O2 oxidation enhanced formation of these products, while NO2 promoted the production of CH3NO2 and (CH3)2NCHO. H2O and SO2 occupied the active sites of particles to inhibit the formation of all products. Compared to Fe(NO3)3, Fe2O3 showed absolute dominance in contribution to the formation of products. Considering the smaller particle size of Fe2O3 and excess Fe(NO3)3, the physical mixing of them reduced the generation of interfacial products. Furthermore, gaseous products of CH3OH, HCHO, CH3CHO, HCOOH and CH3COOH detection clarified the N-free interfacial products. The presence of Fe(NO3)3 inhibited the formation of HCOOH and favored the formation of CH3CHO in the gas phase. By combining product information with thermodynamic calculations, the heterogeneous reaction pathways of trimethylamine were tentatively proposed. These findings provide a guiding significance for the migration of OAs in real atmospheric environment.

Methylamines↗

PubMed2026

Seed-derived mucilage polysaccharides as biomaterials for in vivo tissue regeneration: A systematic review.

Chronic wounds, bone defects, and cartilage injuries represent persistent clinical challenges requiring biomaterial platforms that actively regulate inflammation, oxidative stress, angiogenesis, and extracellular matrix remodeling. Conventional synthetic dressings often provide limited biological activity in these contexts. Seed-derived mucilages - polysaccharide-rich hydrocolloids obtained from chia (Salvia hispanica), flaxseed (Linum usitatissimum), fenugreek (Trigonella foenum-graecum), psyllium (Plantago ovata), guar (Cyamopsis tetragonoloba), quince (Cydonia oblonga) etc. - have emerged as biocompatible, biodegradable, and chemically versatile platforms for tissue engineering. This systematic review, conducted according to PRISMA 2020 guidelines, synthesized in vivo evidence on seed-derived mucilage-based biomaterials across wound healing, bone repair, cartilage regeneration, and related applications. PubMed, Scopus, and Web of Science Core Collection were searched for original in vivo experimental studies published in English between 2020 and 2026. Eligible studies reported at least one measurable regenerative outcome. Data were extracted independently by two reviewers, and methodological quality was assessed using the SYRCLE Risk of Bias tool. Forty-three studies were included. Hydrogels were the dominant biomaterial format, followed by films, scaffolds, sponges, nanoparticle systems, and bilayer or Janus composites. Included systems generally improved wound closure, re-epithelialization, collagen deposition, angiogenesis, antioxidant defense, and inflammatory regulation. However, most studies used small animals with short follow-up periods, and many incorporated nanoparticles or bioactive agents, limiting attribution of efficacy to the mucilage matrix alone. Risk of bias was predominantly unclear due to insufficient reporting of randomization and blinding. Blank mucilage controls, standardized characterization, long-term biosafety data, and clinically relevant models are essential prerequisites for translational progress.

Humans↗

PubMed2026

Oxygen-controlled gamma-irradiation and annealing enable terminal processing of collagen-based biomaterials.

Gamma irradiation is a widely adopted method for terminal sterilization of medical devices; however, its application to collagen-based extracellular matrix (ECM) materials remains limited due to radiation-induced degradation of structural integrity and mechanical performance. Here, we present an engineered terminal-processing strategy that combines oxygen controlled gamma irradiation (25-30 kGy) with post-irradiation dry-heat annealing to preserve ECM functionality while achieving effective sterilization. By modulating oxygen availability during irradiation, this approach alters radical reaction pathways, suppresses oxygen-mediated oxidative degradation, and generates a metastable radical-containing intermediate, which is subsequently converted into a structurally stabilized collagen network through thermal annealing. As a result, the treated matrices preserved ECM integrity and recovered clinically relevant mechanical properties. Furthermore, the process achieved cumulative viral reductions exceeding 6 log10 across a representative panel including enveloped and non-enveloped DNA and RNA viruses, demonstrating compatibility with sterility assurance and viral safety requirements for biologically derived medical devices. Notably, preliminary observations indicate that mechanical integrity can be partially preserved even at elevated irradiation doses up to 50 kGy, suggesting potential applicability to sterilization validation frameworks requiring higher assurance levels. Overall, this work establishes a mechanistically grounded terminal-processing paradigm that enables control of radical fate, decouples sterilization efficacy from material degradation, and integrates sterilization, viral safety, and functional preservation into a unified and scalable framework for collagen-based biomaterials. This concept repositions gamma-irradiation from a purely degradative process to a controllable tool for tuning collagen structure and performance.

Gamma Rays↗

PubMed2026

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

Animals↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans↗

PubMed2026

Identification and formation pathways of oxidation products of chlorinated paraffins during ozonation in municipal wastewater.

Chlorinated paraffins (CPs) cannot be efficiently removed by conventional water treatment processes and are continually discharged into the aqueous environment. Ozonation can effectively remove lipophilic and persistent pollutants. However, the degradation behaviors of short-chain CPs (SCCPs), medium-chain CPs (MCCPs), and long-chain CPs (LCCPs) in wastewater during the ozonation process remained unknown. In this study, ozonation treatment achieved removal efficiencies of 61 % for SCCPs, 66 % for MCCPs, and 51 % for LCCPs from wastewater within 30 min. Approximately 147 oxidative products of SCCPs, MCCPs, and LCCPs were non-targeted identified through Ph4PCl-enhanced ionization with ultra-high performance liquid chromatography-Orbitrap mass spectrometry. These oxidation products were structurally classified into three categories: carbon chain breakage (53 products), HCl-elimination (27 products), and hydroxylation (67 products). Twenty-three di-hydroxylated CPs were newly identified among the products. Hydroxylation was the predominant pathway for SCCPs, producing di-hydroxylated SCCPs ((OH)₂-SCCPs) with a higher generation rate constant (KG = 22.28 × 10⁻² min⁻¹) compared to other products. MCCPs and LCCPs mainly underwent carbon chain breakage and hydroxylation, generating shorter carbon chain congeners, (OH)2-SCCPs, and di-hydroxylated MCCPs ((OH)2-MCCPs). The KG values of (OH)2-SCCPs (10.56 × 10-2 min-1) and (OH)2-MCCPs (12.05 × 10-2 min-1) generated from the MCCPs were the highest, and the KG values of MCCPs (6.49 × 10-2 min-1), SCCPs (6.27 × 10-2 min-1), and (OH)2-SCCPs (4.74 × 10-2 min-1) generated from the LCCPs were higher than those of other products. These results comprehensively clarify the oxidation efficiencies and pathways of CPs during ozonation. Future studies must explore the potential risks associated with the oxidation products.

Water Pollutants, Chemical↗

PubMed2026

Therapeutic approaches for the treatment of bovine metritis: a systematic review of clinical, reproductive and productive outcomes.

Bovine metritis is a complex multifactorial disease associated with substantial clinical and economic impact due to reduced milk production, subfertility, and increased culling rates. Considerable uncertainty remains regarding the comparative efficacy of the many therapeutic strategies used to manage it. This systematic review aimed to summarize and critically evaluate the available evidence on therapeutic approaches for bovine metritis, with respect to clinical cure, reproductive performance, productive performance, and culling. A literature search conducted in PubMed, Web of Science and CABI Digital Library (2010-2025) identified 18 randomized controlled clinical trials eligible for inclusion. Risk of bias was assessed independently by two reviewers using the Cochrane RoB 2 tool. Given substantial clinical and methodological heterogeneity across studies, findings were synthesized narratively by outcome, without meta-analytic pooling, and the certainty of evidence was assessed using GRADE for the comparisons supported by more than one study. Overall, systemic antimicrobial therapies consistently improved short-term clinical cure rates, although their effects on long-term reproductive and productive performance remained inconsistent. In selected cases, nonsteroidal anti-inflammatory drugs (NSAIDs) showed clinical outcomes comparable to antimicrobial treatments, allowing reductions in antimicrobial use ranging from 50% to 92%. Alternative approaches, such as intrauterine flavonoid, chitosan or dextrose-based therapies, produced inconsistent results that appeared to correlate with disease severity and treatment protocol. The evidence base is limited by substantial heterogeneity in disease definitions, postpartum timing of diagnosis, and cure criteria across studies, and by the near-universal absence of allocation concealment in the primary literature; these limitations restrict the certainty of most conclusions to low or moderate. Therefore, effective metritis control should move beyond symptom resolution and incorporate integrated and preventive strategies targeting inflammatory and metabolic dysregulation during the transition period.

Animals↗

PubMed2026

Systematic modular engineering of genome-integrated Escherichia coli MG1655 for high-level 2'-fucosyllactose production.

2'-Fucosyllactose (2'-FL), the most abundant human milk oligosaccharide (HMO), has attracted considerable interest for its prebiotic and immunomodulatory functions, with broad applications in infant nutrition. In this study, we report the development of a high-yield, genome-integrated 2'-FL-producing strain based on Escherichia coli MG1655 through systematic modular optimization. Starting from a single-copy BKHT strain (MGC06), we first optimized the copy number of the α-1,2-fucosyltransferase (α-1,2-FT) gene BKHT. Subsequently, the GDP-L-fucose supply was enhanced through coordinated genomic integration of the gene clusters cpsG-cpsB and gmd-fcl, while the multidrug efflux transporter gene mdfA was integrated to improve product export and strain robustness. BKHT copy number was then re-evaluated in the optimized background, with four copies yielding the highest production. The final engineered strain, harboring all genetic modifications stably integrated into the chromosome, produced 17.18 g/L 2'-FL in shake-flask culture. In fed-batch fermentation using a 5-L bioreactor, this strain achieved a titer of 154.12 g/L after 60 h, with a productivity of 2.57 g/L/h. Notably, throughout the entire fermentation process, no antibiotics or inducers were supplemented, underscoring the genetic stability and regulatory compliance of this plasmid-free system. To our knowledge, this represents the highest 2'-FL titer reported to date, positioning our engineered strain as a promising candidate for commercial 2'-FL production.

Escherichia coli↗

PubMed2026

Innovation-related perception as a key driver of alternative protein acceptance: evidence from an early-stage model for cultivated meat and algae-/microalgae-based alternative protein products in Italy.

Alternative proteins are increasingly considered part of the transition toward more sustainable food systems, yet their diffusion depends critically on consumer acceptance. This study investigates the early-stage acceptance of two alternative protein categories in Italy-cultivated meat and algae-/microalgae-based alternative protein products. Focusing on the first three phases of acceptance, the analysis examines how innovation-related perception (IRP) shapes consumer perceived value (CPV), consumer perceived risk (CPR), and subsequent affective (AFF), cognitive (COG), and conative (CON) responses. Data were collected through an online survey administered to 238 Italian respondents and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that IRP is the main upstream driver of early-stage acceptance in both product domains: more favourable perceptions strongly increase perceived value and reduce perceived risk. In turn, CPV exerts a much stronger influence than CPR on both affective and cognitive attitudes. A tentative cross-model comparison suggests only a descriptive variation in the final transition toward conative acceptance: affective and cognitive responses were both significant in the two models, with a relatively larger affective coefficient for cultivated meat and more balanced coefficients for algae-/microalgae-based products. Overall, the findings support a process-based interpretation of alternative protein acceptance and highlight the central role of innovation-related perception in shaping early consumer responses. These results provide relevant implications for communication strategies, product positioning, and policy actions aimed at improving the acceptability of alternative proteins in food cultures characterised by strong culinary traditions.

Italy↗

PubMed2026

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗

PubMed2026

Strategy for enhanced production of A40926B0 in Nonomuraea gerenzanensis using an efficient CRISPR/AsCas12f1 system.

The global emergence of vancomycin-resistant Gram-positive pathogens underscores the urgent need for efficient production of novel lipoglycopeptide antibiotics. Dalbavancin, a last-resort therapeutic agent, relies on its key biosynthetic precursor A40926B0, whose industrial manufacture is severely limited by the low yield of wild-type Nonomuraea gerenzanensis and inefficient genetic tools for this rare actinomycete. Here, we developed a high-efficiency CRISPR/AsCas12f1 genome editing system and applied systematic metabolic engineering to boost A40926B0 biosynthesis. First, conjugation conditions were optimized to elevate the transfer efficiency in N. gerenzanensis D11. The hypercompact AsCas12f1 nuclease showed markedly lower cytotoxicity than SpCas9 and enabled 100% gene deletion efficiency with preferred PAMs (TTTG, CTTG, GTTG). Second, we strengthened the shikimate pathway via multiple genetic strategies: overexpressing feedback-resistant DAHP synthase (aroG fbr ) and chorismate mutase/prephenate dehydrogenase (tyrA fbr ), as well as knocking out pheA. This manipulation blocks the phenylalanine synthetic branch and redirects metabolic flux toward the l-tyrosine branch. Third, we engineered the branched-chain fatty acid (BCFA) pathway via promoter replacement of bkdA2B2C2, LipAB, fabF and deletion of acdH to enhance isododecanoyl side-chain supply. The combinatorial engineering yielded strain B-13, which produced 1740 mg/L A40926B0 in shake flasks. Finally, 50-L fed-batch fermentation with continuous maltodextrin feeding further increased the titer to 1817 mg/L, the highest reported titer to date. This work establishes a robust CRISPR editing tool for N. gerenzanensis and provides valuable engineering references for precursor-oriented strain improvement targeting lipoglycopeptide antibiotics, offering insights for the industrial scale production of A40926B0.

A40926B0↗

PubMed2026

Cine-derived mitral annular relaxation velocity for detection of preclinical left ventricular diastolic dysfunction.

OBJECTIVES: Imaging diastolic dysfunction in pre-clinical heart failure (HF) is challenging. We evaluated a novel cardiac MRI (CMR) biomarker, CMR e-prime (CMR-MARV), in patients at risk of HF. METHODS: In this substudy of the PARABLE trial (NCT04687111), 236 patients (71.6 ± 7.7 years, 61.6% male) fulfilling trial-defined ALVDD citeria underwent CMR with measurement of mitral annular relaxation velocity (CMR-MARV) at four mitral annular anchor points. Diastolic strain rates from FT were also assessed. Twenty-five age- and sex-matched controls were included (73.8 ± 3.1 years, 52% male). Group differences were tested with t-tests, diagnostic accuracy with ROC analysis, and predictors of diastolic dysfunction with adjusted logistic regression. RESULTS: Compared with controls, patients had significantly higher indexed maximal left atrial volume (LAVimax), LV end-diastolic and end-systolic volumes, and LV mass (all p < 0.001). Of FT variables, only peak diastolic longitudinal velocity differed between groups (p < 0.001). In multivariate models, CMR-MARV correlated with radial, circumferential, and longitudinal diastolic strain rates, radial and longitudinal diastolic velocities (all p < 0.001), echocardiographic e' (r = 0.20, p = 0.007), LV mass (r = -0.18, p = 0.008), LAVimax (r = -0.18, p = 0.008), and NT-proBNP (r = -0.30, p < 0.0001). LAVimax and CMR-MARV were strongly independently associated with ALVDD (AUC 0.89 and 0.76, respectively; p < 0.0001). A combined model (LAVimax + CMR-MARV) achieved excellent discrimination (AUC 0.91, 95% CI 0.86-0.97, p < 0.0001). Independent predictors included LAVimax, CMR-MARV, and peak diastolic longitudinal velocity (all p < 0.001). CONCLUSION: CMR-MARV provides a simple cine-derived measure of longitudinal relaxation that correlates with established structural and biochemical markers of diastolic burden. Within an at-risk population, it offers incremental functional information beyond conventional parameters and may support multiparametric CMR phenotyping of preclinical diastolic dysfunction.

Aged↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

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↗

PubMed2026

Effect of flavored on!® nicotine pouch products on smoking behaviors: A sequential, multiple assignment, randomized controlled trial.

PURPOSE: To evaluate whether flavored versus unflavored nicotine pouch (NP) access affects cigarette reduction and smoke exposure among adults who smoke daily, and whether delayed flavor introduction affects these outcomes. METHODS: Adults who smoked ≥ 5 cigarettes/day (CPD) with interest in replacing cigarettes with NPs were enrolled in a remote, six-week, sequential multiple assignment randomized trial (n = 402 randomized; n = 400 analyzed). Participants were randomized to immediate access to seven NP flavors (Flavor), unflavored-only access for six weeks (Original), or unflavored-only for three weeks followed by flavor access (Delayed Flavor). Primary outcomes were ≥ 50% reduction in weekly mean expired-air carbon monoxide (CO) from baseline and mean CO at Week 6. Secondary outcomes included ≥ 50% CPD reduction, mean CPD, CO-verified 7-day abstinence, and incident smoke-free days. RESULTS: At Week 6, Flavor and Original did not differ in ≥ 50% CO reduction (14.3% vs 14.2%; IRR=1.0, 95% CI=0.6-1.8) or mean CO (18.3 vs 16.5 ppm; β=1.9, 95% CI=-1.3-5.0). CPD decreased across groups by Week 6, with no differences between Flavor and Original in ≥ 50% CPD reduction (50.3% vs 51.6%; IRR=1.0, 95% CI=0.8-1.2) or CO-verified abstinence (9.3% vs 8.9%; IRR=1.0, 95% CI=0.5-2.2). Flavor increased smoke-free days early, with attenuation over time. Among Week 3 non-responders, delayed flavor access increased ≥ 50% CPD reduction at Week 6 (33.3% vs 18.6%; IRR=1.8, 95% CI=1.0-3.2). CONCLUSIONS: NP access supported cigarette reduction regardless of flavor availability, but flavors may accelerate smoke-free days and improve response among individuals who do not reduce cigarette consumption with unflavored products alone.

Humans↗

PubMed2026

Design, rationale, and baseline patient characteristics for the Sickle Cell Disease and CardiovAscular Risk-Red cell Exchange (SCD-CARRE) trial.

BACKGROUND: Despite wide utilization of automated red blood cell exchange (RBCX) transfusion in adult patients with sickle cell disease (SCD), no consensus or quality efficacy data exist on its use. The Sickle Cell Disease and CardiovAscular Risk- Red cell Exchange (SCD-CARRE) trial tests the hypothesis that an automated chronic RBCX transfusion strategy reduces acute health care encounters and death while improving quality of life and end-organ function (cardiac, pulmonary and renal) in participants with SCD that are at high risk of death. METHODS: Adult patients with SCD with elevated tricuspid regurgitant jet velocity (TRV) and/or chronic kidney disease were considered to be at high risk of death and were randomly assigned to RBCX plus standard of care vs standard of care alone. Participants assigned to RBCX received 12 months of exchange transfusions to maintain target pretransfusion hemoglobin S% < 30%, post-transfusion hemoglobin S% < 20%, and post-transfusion hemoglobin concentration ≥10 g/dL. All study participants were managed according to NHLBI/ASH/ATS Expert Panel guidelines. The primary endpoint was the number of SCD acute health care encounters or death over 13 months. Secondary endpoints included measures of cardiovascular and renal function, exercise capacity, patient reported outcomes (all collected at baseline, and months 4, 8, and 12), and transfusion-related adverse events (collected monthly). RESULTS: Between 2020 and 2025, the SCD-CARRE trial randomized 173 participants at 23 sites across 3 countries. Enrolled participants had mean (SD) age of 45.8 (11.8) years and 54% were female. At baseline, participants had average TRV of 2.8 (0.5) m/s such that 45.9% had a TRV between 2.5 to 2.9 m/sec and 28.1% had a TRV ≥ 3.0 m/sec. The median (Q1, Q3) eGFR in this cohort was 60 (36, 110) mL/min/1.73 m2. The median (Q1, Q3) 6-minute walk test distance was 375 meters (309, 439), the median daily steps were 3,728 (2,187, 5,821), and participants experienced a median (Q1, Q3) of 2 (1, 5) pain episodes in the year prior to randomization. The trial results are pending. CONCLUSIONS: The SCD-CARRE trial successfully enrolled a cohort of n = 173 adults with SCD. This study highlights a rationale to evaluate the effect of automated chronic RBCX transfusion strategy plus standard of care as compared to standard of care alone in SCD patients at high risk of death with a focus on patient centered outcomes, preservation of cardiovascular function, end-organ complications and death. TRIAL REGISTRATION: ClinicalTrials.gov, Identifier: NCT04084080, https://clinicaltrials.gov/study/NCT04084080.

Adult↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗