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Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines

Virtual, Augmented, and Mixed Reality Technologies in Neurosurgical Training: Enhancing Skills and Surgical Outcomes: A Systematic Review.

OBJECTIVE: To systematically review the role of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in neurosurgical education and training. DESIGN: Systematic review conducted in accordance with the PRISMA guidelines. SETTING: A comprehensive search was performed across PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar for English-language studies published between 1 January 2020 and 30 April 2026. PARTICIPANTS: Studies involving neurosurgeons, fellows, residents, and medical students (maximum sample size: n = 48) were included. RESULTS: Of 7,204 initially identified studies, 25 met the inclusion criteria. VR was primarily used for surgical simulation (100% of VR studies) and anatomical education (62.5%). AR demonstrated broader applications, including preoperative planning (40%) and intraoperative support (30%). MR was evenly distributed across simulation, planning, and intraoperative support (40% each). The most frequently improved outcomes were training effectiveness (52%) and technical proficiency (44%). Methodological quality scores, assessed using the Modified Medical Education Research Study Quality Instrument (MMERSQI), ranged from 39.5 to 84.5, indicating varied rigor. CONCLUSION: VR, AR, and MR technologies show potential to enhance surgical precision, technical skills, and educational outcomes in neurosurgical training. However, standardization of methodologies and cost-effective solutions remain essential. Future research should focus on long-term clinical impact and integration of AI-driven training models.

Virtual Reality

A systematic literature review of cultural concepts taught by pharmacist preceptors during pharmacy student experiential placements.

BACKGROUND: Cultural concepts such as cultural intelligence, awareness, competency and safety are essential in guiding culturally responsive care in health professional practice. Pharmacist preceptors play a pivotal role in sharing both clinical and cultural safe practice with pharmacy students. Culturally responsive care can contribute to achieving health equity, which is especially important for Indigenous communities. AIM: To review literature on cultural concepts in pharmacist preceptorship practices, and how these concepts are taught and communicated to pharmacy students during experiential learning. METHOD: The systematic review followed the PRISMA 2020 guideline. Scopus, PubMed, and Google Scholar were used to identify articles specific to pharmacist preceptors and pharmacy students published between 2015 and 2025, and available in English. RESULTS: Three full-text articles met the inclusion criteria. Major themes and subthemes were identified; pharmacist preceptors lacked preparedness to teach cultural concepts, resulting in variability in preceptors' understanding of cultural concepts and confidence in fulfilling preceptor responsibilities, underutilised structured frameworks to guide students' learning, challenges with preceptorship due to limited resources and support, and the influence of preceptorship on student learning, which impacted students' learning and competency. CONCLUSION: Pharmacy students had minimal exposure to culturally informed pharmacist preceptorship. It is likely that pharmacist preceptors require country-specific educational resources to support culturally safe preceptorship. Future research is required to substantiate these findings, and to guide culturally responsive practice and promote equitable health outcomes in diverse populations.

Humans

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins

Durvalumab and tremelimumab, with or without lenvatinib, combined with transarterial chemoembolisation in participants with embolisation-eligible hepatocellular carcinoma (EMERALD-3): a global, randomised, open-label, sponsor-blinded, phase 3 study.

BACKGROUND: Transarterial chemoembolisation (TACE), a standard treatment for embolisation-eligible hepatocellular carcinoma (HCC), induces tumour immune responses. Single tremelimumab regular interval durvalumab (STRIDE) is a standard treatment in advanced HCC. In this phase 3 trial, we assessed the efficacy and safety of STRIDE, with or without lenvatinib, plus TACE, in participants with embolisation-eligible HCC. METHODS: EMERALD-3 is a phase 3, randomised, open-label, sponsor-blinded study, conducted at 177 medical sites in 21 countries. Eligible participants were 18 years or older (aged &#x2265;21 years in Egypt or Singapore) at screening and had confirmed HCC (by imaging or histopathologically from biopsy specimen, surgery, or both) not amenable to curative surgery, curative ablation, or transplantation but amenable to TACE. Participants had Child-Pugh class A liver function, an Eastern Cooperative Oncology Group performance status of 0-1, and at least one measurable target intrahepatic lesion per modified Response Evaluation Criteria in Solid Tumours. Participants were randomly allocated in a 1:1:1 ratio to receive STRIDE plus lenvatinib plus TACE, STRIDE plus TACE, or TACE until each group reached its preplanned enrolment target of 175 participants. After the STRIDE plus TACE group reached its enrolment target, randomisation was adjusted to continue in a 1:1 ratio between the STRIDE plus lenvatinib plus TACE group and TACE group until approximately 275 participants were enrolled in each of these two groups. Randomisation used a centrally assigned interactive response technology system, stratified by region, baseline tumour burden, and previous palliative embolisation. In the STRIDE plus lenvatinib plus TACE group, on the first day, participants were given 300 mg tremelimumab intravenously, followed by 1500 mg durvalumab plus oral lenvatinib (8 mg for <60 kg bodyweight or 12 mg for &#x2265;60 kg bodyweight); participants then received 1500 mg durvalumab every 4 weeks plus once-daily lenvatinib for up to 36 cycles. In the STRIDE plus TACE group, participants were given 300 mg tremelimumab and 1500 mg durvalumab intravenously on the first day, followed by 1500 mg durvalumab every 4 weeks. The technique and number of TACE procedures were at the investigators' discretion, with the first procedure administered at least 7 days after the first dose of durvalumab in the two investigation treatment groups and within 7 days of random allocation in the TACE group. The primary endpoint was progression-free survival for STRIDE plus lenvatinib plus TACE versus TACE. Key secondary endpoints were overall survival for STRIDE plus lenvatinib plus TACE versus TACE and progression-free survival and overall survival for STRIDE plus TACE versus TACE. This study was registered with ClinicalTrials.gov (NCT05301842), with enrolment completed. FINDINGS: From March 28, 2022, to Nov 20, 2024, 1124 participants were screened. The full analysis set comprised 760 participants, who were randomly allocated to STRIDE plus lenvatinib plus TACE (n=293), STRIDE plus TACE (n=175), or TACE (n=292). 633 (83%) participants were male and 127 (17%) were female; 548 (72%) were Asian. At the first data cutoff (Sept 2, 2025); the overall median follow-up for progression-free survival was 10&#xb7;0 months (IQR 4&#xb7;6-17&#xb7;2); median follow-up for progression-free survival was 11&#xb7;0 months (IQR 4&#xb7;8-18&#xb7;4) for STRIDE plus lenvatinib plus TACE and 8&#xb7;3 months (4&#xb7;1-15&#xb7;5) for TACE. Median progression-free survival was 13&#xb7;0 months (95% CI 12&#xb7;2-16&#xb7;7) for STRIDE plus lenvatinib plus TACE versus 9&#xb7;8 months (8&#xb7;0-11&#xb7;4) for TACE (HR 0&#xb7;70 [95% CI 0&#xb7;57-0&#xb7;86]; p=0&#xb7;0007). At the second data cutoff (Feb 23, 2026) and a median follow-up for overall survival of 24&#xb7;6 months (IQR 16&#xb7;5-31&#xb7;5) for STRIDE plus lenvatinib plus TACE and 22&#xb7;9 months (14&#xb7;9-30&#xb7;2) for TACE, median overall survival was 39&#xb7;5 months (95% CI 34&#xb7;1-not reached) for STRIDE plus lenvatinib plus TACE and 34&#xb7;7 months (28&#xb7;8-not reached) for TACE (HR 0&#xb7;84 [95% CI 0&#xb7;65-1&#xb7;09]; p=0&#xb7;18). At this data cutoff, median progression-free survival was 12&#xb7;9 months (95% CI 10&#xb7;2-15&#xb7;9) for STRIDE plus TACE and 8&#xb7;1 months (6&#xb7;5-10&#xb7;2) for the first 175 participants randomised to TACE (HR 0&#xb7;71 [95% CI 0&#xb7;56-0&#xb7;91]), with median follow-up of 10&#xb7;3 months (IQR 4&#xb7;6-23&#xb7;7) for STRIDE plus TACE and 7&#xb7;7 months (3&#xb7;0-18&#xb7;5) for the first 175 participants randomly allocated to TACE. The most common adverse events of maximum grade 3 or 4 were hypertension (34 [12%] of 287) for STRIDE plus lenvatinib plus TACE, post-embolisation syndrome and anaemia (ten [6%] of 175 each) for STRIDE plus TACE, and post-embolisation (17 [6%] of 290) for TACE. 184 (64%) participants receiving STRIDE plus lenvatinib plus TACE, 89 (51%) receiving STRIDE plus TACE, and 68 (23%) receiving TACE had serious adverse events. Treatment-related adverse events with an outcome of death during the treatment-emergent period occurred in seven (2%) of 287 participants who received STRIDE plus lenvatinib plus TACE (two for myocarditis; and one each for hepatic failure, haemophagocytic lymphohistiocytosis, septic shock, cardiac failure, and unknown cause), none of 175 participants who received STRIDE plus TACE, and two (1%) of 290 participants who received TACE (one each for acute myocardial infarction and unknown cause). INTERPRETATION: STRIDE plus lenvatinib plus TACE showed a statistically significant progression-free survival improvement versus TACE. These findings support a STRIDE-based regimen as a potential new treatment option for people with embolisation-eligible HCC; additional follow-up is being conducted for final analysis of overall survival across treatment groups. FUNDING: AstraZeneca.

Adult

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n&#x202f;=&#x202f;2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p&#xa0;<&#xa0;0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p&#xa0;<&#xa0;0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

Genetic Diversity Analysis of Red Fox Populations (Vulpes vulpes L., 1758) in Natural and Anthropogenic Isolation.

This study presents a comparative analysis of the genetic structure and diversity of three red fox (Vulpes vulpes L.) populations representing different microevolutionary scenarios: panmixia (free-ranging Belarusian foxes), geographic isolation (free-ranging Scottish foxes), and anthropogenic selection (farm-bred foxes). Using a validated set of STR markers, multivariate statistical analysis was conducted to assess the genetic structure and the degree of genetic erosion across the studied groups. The wild red fox population in Belarus has been shown to maintain a state close to panmixia (PHWE&#x2009;=&#x2009;0.090), characterized by a high effective population size (Ne&#x2009;=&#x2009;694) and high allelic diversity. The island population from Scotland exhibits moderate gene pool depletion (Ne&#x2009;=&#x2009;75.9) and a pronounced heterozygote deficiency (FIS&#x2009;=&#x2009;0.18). Critical genetic erosion, which was characterized by a minimal effective population size (Ne&#x2009;=&#x2009;60.2) and allelic fixation, was detected in the farm-bred group. The genetic distance between farm-bred and wild foxes (FST&#x2009;=&#x2009;0.279; p&#x2009;=&#x2009;0.001) reflects both the phylogeographic divergence between the Nearctic ancestors of farmed lineages and Palearctic wild populations, and the consequences of prolonged anthropogenic isolation, genetic drift, and selective breeding. These data indicate that artificial isolation and the impacts of genetic drift and targeted selection lead to a substantial depletion of the species' adaptive potential.

Animals

Prenatal exposure to indoor PM2.5 and children's cognitive performance at 4 years of age: an observational analysis from the UGAAR randomized controlled trial.

Outdoor fine particulate matter (PM2.5) concentrations during pregnancy are linked to reduced cognitive performance in children. We previously reported that portable HEPA filter air cleaners use during pregnancy improved children's mean full-scale IQ (FSIQ), but no previous studies have evaluated the relationship between indoor PM2.5 during pregnancy and FSIQ in childhood. We conducted an observational analysis using data from the Ulaanbaatar Gestation and Air Pollution Research (UGAAR) randomized controlled trial. Using a previously developed model of weekly indoor PM2.5 concentrations, we estimated the average concentrations in participants' homes over the full pregnancy and in each trimester. When the children were four years old, we measured FSIQ using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-IV). We used multiple linear regression to assess the adjusted relationships between interquartile range (IQR) contrasts in indoor PM2.5 during pregnancy and FSIQ among 475 mother-child dyads. An 8.8&#xa0;&#x3bc;g/m3 increase in indoor PM2.5 concentration over the full pregnancy was associated with a reduction of 1.4 points (95% CI: -3.4, 0.6) in mean FSIQ. The strongest association between PM2.5 concentrations and FSIQ was in the first trimester, when a 19.1&#xa0;&#x3bc;g/m3 contrast was associated with a 2.8-point reduction (95% CI: -5.7, 0.2) in mean FSIQ. Indoor PM2.5, particularly during early pregnancy, may impair brain development, leading to lower mean FSIQ scores in four-year old children. These results, combined with our previous analysis of HEPA filter air cleaners, indicate that reducing PM2.5 exposure during pregnancy has beneficial effects on children's cognitive performance.

Humans

Impact of Physical Environment of Pediatric Inpatient Wards on Children: A Systematic Literature Review.

ObjectiveThe study aimed to examine empirical studies published between 2003 and 2025 to identify elements of physical environments influencing health outcomes and experiences of children and families.BackgroundIn the past 40 years, research has shown that the physical environment influences the health and well-being of patients in the healthcare environment. However, similar research in the context of "pediatric inpatient wards" remains underexplored.MethodsPubMed, Embase, Scopus, and Web of Science were used to identify relevant articles. All extracted articles underwent a three-step screening process using PRISMA. A total of 30 eligible articles were used for the analysis. The protocol is registered at PROSPERO (CRD42023408997).ResultsKey findings reveal positive and negative impacts of identified elements. Positive-effect elements include play spaces, space for parents, natural light, connections with nature, and so on, which promote comfort, healing, and emotional resilience. Conversely, negative-effect elements, such as noise, artificial lighting, uncomfortable temperature, and so on, contribute to stress and disrupted sleep. Mixed effects were observed for elements like art and television, which underscore the complexity of designing environments that address the diverse needs of different age groups and genders.ConclusionsThe review findings highlight significant knowledge gaps. The study also tries to bridge existing gaps between research and practice by systematically identifying environmental elements, offering actionable insights to architects, designers, healthcare providers, and policymakers. Future research must adopt rigorous, culturally inclusive approaches to advance the field of pediatric healthcare design and ensure equitable care across diverse sociocultural contexts.

Humans

Culture of infectious human norovirus isolated from live contaminated oysters.

Human noroviruses are a major cause of foodborne outbreaks worldwide. Filter-feeding shellfish, such as oysters, can bioaccumulate these viruses in their digestive tissue when grown in sewage-impacted coastal areas and are often implicated in norovirus foodborne outbreaks. Despite the high sensitivity of current molecular assays, these methods for norovirus detection in shellfish fail to distinguish between infectious and non-infectious particles. Assessing norovirus infectivity in shellfish remains a challenge due to the lack of suitable isolation methods that maintain capsid integrity. In this study, a protocol for isolating infectious norovirus from oyster tissues, based on chloroform-butanol elution and polyethylene glycol concentration (CB-PEG), was optimized for the recovery of human norovirus GI and GII. While CB-PEG method recovered various norovirus GI and GII genotypes, it was less efficient at the genomic level than a protocol based on proteinase K elution (adapted from ISO 15216) and showed genotype-dependent viral recovery rates. By optimizing the flocculation step, we improved the method's compatibility with human intestinal enteroid (HIE) cultures. Using this approach, we successfully quantified infectious norovirus GII.3 titers recovered from artificially-contaminated live oysters. Interestingly, infectious virus was better isolated following a freezing step of the digestive tissues, with titers ranging from 13 to 40 TCID50/mL for positive samples. In conclusion, this study established an optimized methodological approach for the relative quantification of infectious norovirus GII.3 in shellfish, paving the way for future research on viral persistence and inactivation strategies in this foodstuff.

Norovirus

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5&#x202f;kcal/mol, Wogonin (-9.3&#x202f;kcal/mol) and Xanthohumol (-8.1&#x202f;kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans

Unravelling bioanalytical innovations, degradation processes, and impurity landscapes of VEGFR inhibitors.

From pre-formulation studies to clinical trials, VEGFR-targeted small-molecule tyrosine kinase inhibitors (TKIs) require rigorous analytical standards. Bioanalysis, stability-indicating studies, and impurity profiling are used to examine chromatographic advances for VEGFR-targeted TKIs like sunitinib, pazopanib, axitinib, sorafenib, cabozantinib, vandetanib, apatinib, lenvatinib, nintedanib, and regorafenib. An LC-MS/MS and UPLC-MS/MS routinely show sub ng/mL performance, as shown by LLOQs (0.2&#xa0;ng/mL) for sunitinib and axitinib, 1&#xa0;ng/mL for pazopanib, 5-7&#xa0;ng/mL for sorafenib, 0.5-1.5&#xa0;ng/mL for regorafenib metabolic products, and 0.1-0.5&#xa0;ng/mL for lenvatinib. These approaches are used for pharmacokinetics and therapeutic drug monitoring due to their good correlation coefficient of 0.1-10,000&#xa0;ng/mL, accuracy of 95%-108%, and precision of 15% RSD. UPLC-QTOF-MS/MS distinguishes degradants and metabolites during forced degradation studies, enabling structural elucidation following ICH M7 risk evaluation protocol. HPTLC/MLC offers fast, sensitive screenings, while RP-HPLC/DAD or HPLC-UV offer reliable, cost-effective routine quality-control solutions with LOD/LOQ in the &#x3bc;g/mL range and linearity of 10-240&#xa0;&#x3bc;g/mL. This review lists the structures and CAS numbers of ten VEGFR-2 TKI degradants and metabolites, as well as pharmacopeial impurities in SMILES forms. It will be useful for future method development and regulatory applications. To ensure VEGFR-targeted TKI quality, safety, and therapeutic efficacy, LC-MS/MS for trace quantification and HRMS for structure elucidation provide a robust, future-oriented framework. To improve VEGFR-targeted TKI quality, safety, and regulatory compliance, analytical development should focus on HRMS-based impurity characterization, AI-assisted degradation prediction, green chromatography, and harmonized bioanalytical validation.

Humans

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan&#xae; for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans