To elucidate the mechanism by which oxidized functional groups influence asphalt-aggregate adhesion behavior at the microscopic level, molecular dynamics (MD) simulations were employed based on the Derek four-component model-a model well-matched with real asphalt's density and thermal expansion coefficient. Asphalt molecular models containing 12 characteristic molecules were constructed, with two stable oxidized functional groups (carbonyl, C=O; sulfoxyl, S=O) introduced to represent asphalt aging. Three concentration gradients (0%, 50%, 100%) were designed by adjusting the number of functional groups. Meanwhile, silica (SiO2) aggregate models were cleaved along the (0 0 1) crystal plane, transformed into an orthorhombic structure, and passivated with hydrogen atoms to simulate real aggregate surface properties. An asphalt-aggregate interface system with a "SiO2 layer-10Å vacuum layer-asphalt layer-50Å vacuum layer" sandwich structure was established. The model rationality was verified by three key indicators: density (1.011~1.079g/cm3), solubility parameter (18.604~19.237 (J cm-3)0.5), and glass transition temperature (237.97~247.61K), ensuring consistency with published experimental and simulation data. The effects of functional group type and concentration on asphalt-aggregate adhesion were analyzed by evaluating interfacial energies (interaction energy, van der Waals energy, electrostatic energy). As the concentration of carbonyl (C=O) groups increased, the interaction energy, van der Waals energy, and electrostatic energy in the asphalt-aggregate system all showed an upward trend. The increase at 100% concentration was greater than that at 50% concentration, with electrostatic energy exhibiting the largest overall increase. As the sulfoxyl group (S=O) content increased, the interaction energy and van der Waals energy in the asphalt-aggregate system decreased, while the electrostatic energy increased. When both carbonyl (C=O) and sulfoxyl (S=O) groups coexist, the variation patterns of various interfacial energies resemble those observed under sulfoxide influence alone. This indicates that, under identical conditions, sulfoxyl (S=O) exerts a greater impact on interfacial energies. Oxidized functional groups significantly influence the adhesion properties between asphalt and aggregates. To investigate the effects of oxygen-containing functional groups with different concentrations and types on the asphalt-aggregate adhesion behavior, asphalt molecular models were first constructed via the molecular assembly method using the Amorphous Cell module in Materials Studio 2023 software, referencing TLC-FID data of asphalt four components to determine the molecular quantity of each component. A total of 15 asphalt models were established, covering three functional group types (C=O, S=O, C=O + S=O) and three concentration gradients. SiO2 aggregate models were built by cleaving SiO2 crystals along the (0 0 1) direction, inserting a 10Å vacuum layer to form periodic unit cells, and passivated with hydrogen atoms to simulate real aggregate surface properties. Subsequently, molecular dynamics simulations were performed on the asphalt-aggregate models via the Forcite module, where the COMPASS III force field was adopted to describe intermolecular bonding and non-bonding interactions. The simulation process included three key steps: (1) geometric optimization (medium precision, 50,000 iterations) to eliminate unreasonable atomic configurations, (2) five annealing cycles (298~498K, 200ps total) under the NVT ensemble (controlled by a Nose thermostat) to stabilize the system, (3) equilibrium simulations (500ps NVT + 1000ps NPT) at 298K and 1.0 × 10-4 GPa (controlled by a Berendsen barostat).

Exploring the Mechanism of Oral Cancer With Shikonin Based on the Network Pharmacology and Molecular Docking Technology.

Early and accurate identification and quantification of plant-parasitic nematodes (PPN) is crucial for their effective control. Although valuable, the current techniques for identifying PPN, such as morphology and molecular marker-based methods, can be time and resource-intensive. This study aims to develop and validate cutting-edge computer vision tools for automated, accurate, and reproducible PPN detection. To achieve this goal, we captured microscopic images of the three economically-important PPN genera associated with potato crop: root lesion (RLN; Pratylenchus spp.), root-knot (RKN; Meloidogyne spp.), and stubby root (SRN; Paratrichodorus and Trichodorus spp.), additional plant-parasitic nematodes (PPN-OTHERS) and non-parasitic (NON-PARASITIC) nematodes, for a total of five groups. The captured images (total instances = 8,654) were preprocessed, annotated, and randomly split into three datasets: 75% for training, 15% for validation, and 10% for testing. An object segmentation algorithm, YOLOv11-seg, which predicts each pixel in the image, was trained and evaluated on previously unseen images. The model achieved high accuracy in validation (92.4%) and test: (88.6%) datasets with strong performance for key PPN genera (RKN, RLN, SRN; F1-scores >0.92; AUC >0.93 in the test set). While the NON-PARASITIC showed strong performance (F1-score > 0.846 and AUC >0.91), the PPN-OTHERS group performed poorly (test accuracy: 43.9%), frequently misclassified as RLN and NON-PARASITIC nematodes. The results highlight the potential of artificial intelligence-based tools in identifying PPN, paving the way for the long-term goal of developing automated detection and quantification systems for plant pathogens.

Non-destructive identification of forensically relevant body fluid stains using a portable electronic nose: A pilot study.

PIK3R1 acts as a prominent biomarker for tumor immune microenvironment modulation in intravenous leiomyomatosis.

Clinical evaluation of nasal swab specimens in VTM/UTM and RespDirect eSTM using the Panther Fusion SARS-CoV-2/Flu A/B/RSV assay.

Carbohydrate polymers in cancer theranostics: Smart solutions for advanced diagnosis and therapy.

High throughput influenza A virus detection by isothermal amplification in sequential-injection paper-based microfluidics.

Chronic Aphanomyces astaci infection in wild white-clawed crayfish: risks and implications for breeding programs.

Sensitive and specific detection of influenza virus A/H3N2: An electrochemical aptasensor modified with AuNPs-PEI-MWCNTs.

Understanding limitations to successful avian influenza virus isolation from wild birds.

We study the dynamics of a model for double proton transfer reaction in order to gain insights into the reaction mechanism. The model potential energy surface exhibits four minima, four rank one saddles and a second rank saddle. Our interest in this model is twofold. First, to establish the extent to which the mechanism can be classified as a dynamically concerted one as a function of total energy. Second, to investigate whether quantum dynamics can significantly alter the notion of dynamical concertedness. The first issue is addressed by a classical dynamical analysis of the so called delay time distributions as a measure of dynamical concertedness, which shows that the fraction of dynamically concerted reactive trajectories exhibits substantial fluctuations even at energies well above that of the rank two saddle energy. For the second question our approach involves using the entangled trajectory molecular dynamics method to compute the quantum analog of the classical delay time distribution. Our results show that one can still use the notion of dynamical concertedness. However, significant deviations due to quantum effects are observed in certain energy and parameter regimes. Such quantum deviations are further characterized by computing the linear entropy of the system, which hints at the possible role of quantum entanglement.

Leptospirosis is a globally-distributed zoonotic disease caused by pathogenic Leptospira spp., affecting humans, domestic animals, and wildlife. Despite its importance, little is known about the ecological and epidemiological aspects of Leptospira spp. infection in wild carnivores, particularly martens. This study investigated the presence of Leptospira spp. in stone martens (Martes foina) and pine martens (Martes martes) in northern Poland using serological (MAT) and molecular (real-time PCR and MLST) methods. Samples from 129 martens collected between 2012 and 2022 revealed an 18% seroprevalence and a 13% PCR-positivity rate. Seroreactivity against six Leptospira spp. serovars was identified, all associated with rodent transmission cycles.. Molecular analysis confirmed the presence of sequence types ST117 and ST110, previously reported in small mammals in Central Europe. Martens are susceptible hosts for Leptospira spp.. Given their adaptability and overlapping habitats with livestock and humans, they also represent valuable targets for integrated surveillance within the One Health framework. This study provides the first evidence of Leptospira spp. sequence types and serological diversity in martens in Poland, and offers valuable insights into the epidemiology of wildlife leptospirosis.

Rhizostomeae (Scyphozoa) jellyfishes are widespread in neritic waters and include species of commercial importance in Asia. This group comprises jellyfish taxa that host endosymbiotic dinoflagellates of the family Symbiodiniaceae, which provide autotrophic benefits. Despite their value, limited molecular data for Japanese rhizostome taxa has hinder accurate taxonomic classification and interpretation of novel traits. This study combines molecular methods to provide the most complete understanding of molecular phylogenetic relations of Rhizostomeae jellyfishes while assessing the number of Symbiodiniaceae taxa that can be hosted in each species at the medusa level through a new method developed herein for tandem amplification of symbionts and host, validated with microscopy. We also evaluate which rhizostomes produce cassiosomes and whether Symbiodiniaceae are found in the core. Phylogenetic analysis of host mitochondrial (16S rRNA, COI) and nuclear (28S) gene regions of 18 medusae from five genera revealed: (1) Mastigias in Japanese waters corresponds to M. albipunctata ; (2) Cassiopea from Kagoshima likely represents an undescribed species, though Cassiopea xamachana may have been introduced; (3) Two cepheid species - Cephea cephea and Netrostoma setouchianum - occur in Japan; (4) Rhopilema esculentum , a commonly harvested species, is endemic to western Japan. Symbiotic Symbiodiniaceae ITS2 analysis identified three dominant genera ( Symbiodinium , Cladocopium , and Durusdinium ). More than one genus among these was found to be hosted in samples of the genera Mastigias and Cassiopea , indicating plasticity in symbiont association at both the taxon and individual medusa level. Microscopy confirmed cassiosome production exclusively in species examined of the suborder Kolpophorae: Cassiopea sp., N. setouchianum , and M. albipunctata , though absent in a juvenile M. albipunctata sample. Conversely, R. esculentum hosts Symbiodiniaceae but appears to lack the ability to produce cassiosomes. Overall, findings support the distinctive evolution of Symbiodiniaceae–Rhizostomeae symbiosis, the monophyly of the suborder Kolpophorae, and the synapomorphy of cassiosome production in Kolpophorae with onset likely influenced by developmental stage. Broader taxon sampling, especially within Dactyliophorae, will provide further clues on the functional evolution and cellular organization underlying photoendosymbiosis and cassiosome production in these medusozoans.

Progressive aggregation of TAR DNA-binding protein 43 (TDP-43) is a hallmark of numerous neurodegenerative diseases, including amyotrophic lateral sclerosis, frontotemporal dementia, Alzheimer's disease, and limbic predominant age-related TDP-43 encephalopathy (LATE). This highly conserved nuclear RNA/DNA-binding protein is involved in the regulation of RNA processing. The C-terminal domain (CTD) of TDP-43 plays a key role in protein solubility, cellular localization, and protein-protein interactions. CTD is rich in glycine, glutamine, and asparagine, which facilitate TDP-43 aggregation into amyloid oligomers and fibrils observed in the brain. In this study, we examine the role of lipid bilayers in the aggregation properties of the CTD of TDP-43. We found that lipid bilayers composed of anionic phosphatidylserine and cardiolipin accelerated TDP-43 aggregation. Although lipids did not alter the secondary structure, they altered the cytotoxicity that TDP-43 fibrils exerted to rat dopaminergic cells. Using molecular methods, we showed that TDP-43 fibrils damage cell endosomes. This causes aggregate leakage into the cytosol, where TDP-43 fibrils impair cell autophagy, simultaneously triggering a severe unfolded protein response in the endoplasmic reticulum. Our results indicate that TDP-43 aggregation may be linked to pathological changes in the lipid profiles of neurons.

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor worldwide, with Chinese patients accounting for more than 50%. Microvascular invasion (MVI) is a key risk factor for postoperative HCC recurrence. Currently, preoperative identification and prediction of MVI in HCC remains challenging and a clinical challenge. Numerous studies have utilized clinical, laboratory, molecular, and imaging methods to predict MVI in HCC preoperatively, but these efforts have proven limited in effectiveness. To investigate the clinical value of 18 F-fluorodeoxyglucose (18 F-FDG) PET/computed tomography (CT) and Gd-EOB-DTPA dynamic contrast-enhanced MRI in predicting MVI of HCC before liver transplantation, and to construct a nomogram prediction model by combining laboratory indicators. A total of 121 HCC patients who underwent liver transplantation were retrospectively enrolled (71 patients in the MVI-positive group and 50 patients in the MVI-negative group). Clinical characteristics, laboratory parameters, 18 F-FDG, the correlation between PET/CT and Gd-EOB-DTPA MRI findings, and MVI were analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent predictors, and a nomogram model was constructed. Calibration curves and receiver operating characteristic (ROC) curves were used to evaluate the model performance. Univariate analysis showed significant differences between the two groups in abnormal prothrombin (PIVKA-II), alpha-fetoprotein, tumor size, peritumoral hypointensity during the hepatobiliary phase, maximum standardized uptake value, mean standardized uptake value, peak standardized uptake value, total lesion glycolysis, coefficient of variation, heterogeneity index, and tumor-to-liver ratio (all P < 0.05). Multivariate analysis revealed that PIVKA-II [odds ratio (OR) = 1.001, P = 0.002], peritumoral hypointensity during the hepatobiliary phase (OR = 5.556, P < 0.001), and heterogeneity index (OR = 2.064, P = 0.004) were independent predictors of MVI. The combined model achieved an area under the ROC curve of 0.875 (95% confidence interval: 0.808-0.941), significantly outperforming any single parameter. Nomogram calibration curves demonstrated high agreement between the predicted and observed probabilities (mean absolute error = 0.016). 18 F-FDG PET/CT and Gd-EOB-DTPA dynamic contrast-enhanced MRI can effectively predict the risk of MVI in HCC patients before liver transplantation. The nomogram model constructed by combining laboratory indicators provides a reliable tool for preoperative individualized assessment.

Body fluid identification at crime scenes is the first step in the forensic biology workflow, leading to the identification of the perpetrator and/or, in some cases, the victim. Current methods that are regularly used in forensic criminal evidence analysis utilize well-studied properties of each fluid as the foundation of the protocol. Among these approaches, alternative light sources, chemical reactions, lateral flow immunochromatographic tests, and microscopic detection stand out to identify the main body fluids encountered at crime scenes: blood, semen, and saliva. However, these often come with limits for specificity and sensitivity. There is also difficulty with fluid mixtures, environmental degradation, and destruction of the sample by the method used. Other fluids, like vaginal fluid and fecal matter, lack standardized protocols and require innovative ideas for accurate analysis without compromising the sample. Emerging technologies based on molecular methods have been the focus of body fluid research, with emphasis on topics such as mRNA, microRNA, epigenetics, and microbial analysis. Additional information alongside the determination of fluid origin could be an advantage from new molecular techniques, such as the identification of donors from SNP analysis, if regular STR analysis is not possible. Validation studies and the integration of such research have the potential to expand and enhance the laboratory practices of forensic science. This article will provide an overview of the current methods applied in the crime lab for body fluid identification before exploring active research in this field, pointing out the potential of these techniques for application in forensic cases to overcome present issues and expand the variety of body fluids identified.

This study investigated the genetic diversity of 25 okra (Abelmoschus esculentus (L.) Moench) genotypes using phenotypic and molecular characterization methods. Phenotypic analysis of 11 quantitative traits revealed significant divergence among accessions, particularly for traits such as the coefficient of infection, average fruit weight, fruit yield and number of fruits per plant. High Phenotypic Coefficient of Variation (PCV) and Genotypic Coefficient of Variation (GCV) values were observed for plant height, number of branches per plant, number of nodes per plant, average fruit weight, fruit yield and coefficient of infection. High heritability with genetic advance as a percentage of mean was observed for plant height, number of branches per plant, number of nodes per plant, internodal length, number of fruits per plant, fruit length, fruit girth, average fruit weight, fruit yield and coefficient of infection. The germplasm was categorised into six groups after Mahalanobis D2 analysis. Molecular characterisation of the 50 SSR markers identified substantial genetic diversity. 21 markers were polymorphic, exhibiting 2-4 alleles per locus. Fifteen SSR markers showed high polymorphism information content values exceeding 0.5, with a range of 0.41 to 0.8. Jaccard's similarity coefficient ranged from 0.17 to 0.86 (average 0.63). Phenotypic and molecular analyses clustered the genotypes into six distinct groups, underscoring the considerable genetic variability within the studied okra germplasm. These findings provide valuable resources for future okra breeding programs.

Abstract Pea necrotic yellow dwarf virus (PNYDV), Nanoviridae, is an emerging and economically significant threat to legume production in Europe, posing significant risks to crop yield. This nanovirus is transmitted by aphid vectors, including pea aphids ( Acyrthosiphon pisum [Harris]) and black bean aphids ( Aphis fabae [Scopoli]). The severity of PNYDV infections varies among host plants and cultivars, with symptoms ranging from leaf yellowing and deformation to dwarfing and necrosis, which often leads to substantial yield losses. Early and accurate detection currently relies on serological and molecular diagnostic methods, though the sensitivity differs between methods. PNYDV is a multipartite virus that consists of at least eight genomic components each encapsidated within individual virions. The distribution of each segment in their host plants and their insect vectors, and the functional roles of some segments remain poorly understood. Current research aims to elucidate the molecular mechanisms underlying PNYDV-host interactions, improve diagnostic tools for early detection, and identify resistant legume cultivars. Additionally, efforts are focused on understanding the epidemiology of PNYDV, its transmission dynamics, and aphid-virus interactions to develop sustainable management strategies. Addressing these knowledge gaps is essential to mitigate the spread and impact of PNYDV on the European and global legume production. Information © The Authors 2026.

A new formulation of the many-body expansion of the electron density expressed in terms of the wave function data is developed in the framework of the fragment molecular orbital (FMO) method for the purpose of visualizing noncovalent interactions (NCI) in large systems. This expansion can also be used for a selected site of interest, such as a ligand binding site in a protein. The site formulation is shown to be both accurate and efficient, as demonstrated for a small protein-ligand complex (Trp-cage protein, PDB: 1L2Y) and a large complex of prostaglandin H2 synthase-1 (1EQG) with ibuprofen. In addition, the FMO/NCI methodology is extended to treat periodic boundary conditions, with an application to study packing effects in the crystal of crambin (1CBN).