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Preparation and properties of isocyanate self-healing microcapsule cement-based material
Self-healing microcapsule cement-based materials autonomously repair microcracks within the matrix. This study utilized the interfacial polymerization method to prepare isocyanate microcapsules, incorporating montmorillonite to enhance the wall material. The optimized synthesis conditions were established as follows: a reaction time of 2 hours at 50°C, using 3g of wall material, 13.5g of core material, and 1% montmorillonite, achieving a core material content of 61.5%. Both micro and macro analyses confirm the microcapsules’ excellent alkaline resistance and compatibility with cement-based materials. The ideal microcapsule concentration was determined to be 4%, which increased the compressive strength recovery rate of the self-healing mortar to 117.38%.
Metabolic dysfunction associated steatotic liver disease is associated with atrial fibrillation recurrence following cryoballoon ablation
Coacervation drives morphological diversity of mRNA encapsulating nanoparticles
The spatial arrangement of components within an mRNA encapsulating nanoparticle has consequences for its thermal stability, which is a key parameter for therapeutic utility. The mesostructure of mRNA nanoparticles formed with cationic polymers has several distinct putative structures: here, we develop a field theoretic simulation model to compute the phase diagram for amphiphilic block copolymers that balance coacervation and hydrophobicity as driving forces for assembly. We predict several distinct morphologies for the mesostructure of these nanoparticles, depending on salt conditions and hydrophobicity. We compare our predictions with cryogenic-electron microscopy images of mRNA encapsulated by charge altering releasable transporters. In addition, we provide a graphics processing unit-accelerated, open-source codebase for general purpose field theoretic simulations, which we anticipate will be a useful tool for the community.
Velocities of hippocampal traveling waves are proportional to their coherence frequency
Cortical traveling waves, defined by their spatial, temporal, and frequency characteristics, provide key insights into active brain regions, timing, frequency, and the direction of activity propagation. Emerging evidence suggests that the directionality and spatiotemporal extent of these waves encode cognitive processes. However, the relationship between frequency and this encoding mechanism remains unclear. We investigate the hypothesis that coherence frequency determines wave propagation velocity. By employing both bivariate linear and multivariate nonlinear coherence analyses, we demonstrate that coherence frequency encodes propagation velocity. Unlike linear analyses, which may overestimate velocities due to bidirectional flow when assessing multiple pair coherences, our nonlinear approach—calculating propagation along four-node pathways—treats pathways as holistic units with net unidirectional flow, making it more appropriate for calculating wave velocities. We extracted pairwise coherence and four-node pathways from local field potentials recorded via intracranial electrodes positioned along the hippocampal longitudinal axis in patients with drug-resistant epilepsy. Our findings reveal that average coherence values and contact pair distances calculated by the multivariate analysis are more consistent across frequencies compared to pairwise coherence. The average coherence values are higher, and the average pair distances and wave velocities are lower in the multivariate analysis than in the pairwise approach. Propagation velocities along the hippocampus at low frequencies (<~35 Hz) exhibit a linear dependence on frequency in the alpha and beta bands, with a steeper slope in the gamma band, indicating distinct mechanisms for velocity-frequency dependence across oscillation bands. While observed within the hippocampus, these findings suggest that the relationship between frequency and wave velocity may extend to other cortical areas. Our nonlinear multivariate analysis appears better suited than pairwise coherence for investigating brain network dynamics. Further research is needed to elucidate the role of conduction velocity in brain function.
County-to-county migration is associated with county-level racial bias in the United States
Abstract Millions of people move within the U.S. each year. We propose that people function as proxies for their locations, bringing the culture of their previous residence to their new homes. As a result, migration might systematically influence regional biases across geographic units over time. Using county-to-county migration data from the U.S. census and county-level racial attitude estimates from Project Implicit, the present research examined the impact of people relocating from one U.S. county to another on racial attitudes in their new county. Consistent with our prediction, the bias brought by the migrants positively predicts county-level racial bias after migration, even after controlling for county-level racial bias before migration. This finding remains robust across various sample inclusion criteria and spans three time periods (2006–2010, 2011–2015, and 2016–2020). These results highlight the significant role of migration in spreading and shaping regional racial attitudes, emphasizing the importance of considering macro-societal processes such as migration when studying changes in regional racial attitudes.
Scattering-based structural inversion of soft materials via Kolmogorov–Arnold networks
Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov–Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions—two representative soft matter systems—we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.
Mediating effect of illness perception between self-care ability and health-promoting behaviors among patients with stable coronary artery disease
Background The interaction between illness perception, self-care ability, and health-promoting behaviors (HPB) in stable coronary artery disease (SCAD) patients remains uncertain. We conducted a cross-sectional survey to explore the correlation between self-care ability, illness perception, and HPB among patients with SCAD, as well as the potential mediating role of illness perception between self-care ability and HPB. Methods A cross-sectional study was carried out among 184 inpatients with SCAD in Hefei, China, from December 2022 to March 2023. The Self-Care of Coronary Heart Disease Inventory (SC-CHDI, containing three dimensions: self-care maintenance, self-care management, and self-care confidence), Revised Illness Perception Questionnaire (IPQ-R, containing seven dimensions: illness duration, illness consequence, personal control, treatment control, illness coherence, cyclical timeline, emotional distress), Health-Promoting Lifestyle Profile Ⅱ (HPLP-Ⅱ) were used in the questionnaires. SPSS 25.0 software and PROCESS version 4.2 plug-in was used to analyze the mediating effect. Results HPB of SCAD patients was at moderate level. A range of factors including education level, marital status, self-care maintenance, self-care management, self-care confidence, illness coherence, and emotional distress are potential influencers of HPB. Illness coherence had a partially mediated effect between self-care maintenance and HPB (β = 0.063, 95% CI: 0.021~0.111), accounting for 20.59% of the total effect. Similarly, illness coherence had a partially mediated effect between self-care management and HPB (β = 0.055, 95% CI: 0.016~0.105), accounting for 13.78% of the total effect. However, none of the dimensions of illness perception mediated between self-care confidence and HPB. Self-care confidence directly influenced HPB, accounting for 92.40% of the total effect. Conclusion It is necessary for hospital healthcare workers, community workers, and patients’ families to work together to focus on the self-care ability and positive illness perception of patients with cardiovascular disease, so as to increase patients’ motivation to participate in HPB and improve their quality of life.
Investigating the Electrocatalytic properties of ZnO-Based composite membrane for dye removal
Characterizing the photodissociation dynamics of HPCO in the S1 band
A full-dimensional potential energy surface (PES) represented by the neural network method for the first excited state S1(1A″) of HPCO is reported for the first time. The PES was constructed based on more than 51 000 ab initio points, which were calculated at the multi-reference configuration interaction level with Davidson correction using the augmented correlation consistent polarized valence triple zeta basis set. Based on the newly constructed PES, quasi-classical trajectory calculations were carried out to study the photodissociation dynamics of HPCO at the total energy ranging from 4.0 to 5.6 eV. At low total energies, the HP + CO product is dominant, while the product H + PCO becomes increasingly favored at higher energies. Furthermore, the translational energy distributions of two products are found to be energy-dependent. Owing to the strongly repulsive PES along the HP + CO dissociation pathway, the translational energy distributions of HP + CO are dominated by relatively higher energies in contrast to H + PCO. The diatomic products HP and CO are found to possess the vibrational distributions decaying monotonically with the vibrational quantum number and relatively cold rotational state distributions, consistent with the strongly repulsive potentials toward the HP + CO channel. In addition, the vibrational distributions of HP and CO are found to be quite similar due to their close frequencies, while the rotational distributions of CO have a much more highly excited rotational degree of freedom owing to its rotational constant approximately four times smaller than that of HP.
Metabolic pathways of Alternative Lengthening of Telomeres in pan-carcinoma
Alternative Lengthening of Telomeres (ALT) is a telomerase-independent mechanism deployed by several aggressive cancers to maintain telomere length. This contributes to their malignancy and resistance to conventional therapies. In prior studies, we have identified key proteins linked to the ALT process using multi-omic data integration strategies. In this work, we combined metabolomic datasets with our earlier results to identify targetable metabolic pathways for ALT-positive tumors. 39 ALT-related proteins were found to interact with 42 different metabolites in our analysis. Additional networking analysis revealed a complex interaction between metabolites and ALT-related proteins, suggesting that pan-cancer oncogenes may have an impact on these pathways. Three metabolic pathways have been primarily related with the ALT mechanism: purine metabolism, cysteine and methionine metabolism, and nicotinate and nicotinamide metabolism. Lastly, we prioritized FDA-approved drugs (azathioprine, thioguanine, and mercaptopurine) that could target ALT-positive tumors through purine metabolism. This work provides a wide perspective of the metabolomic pathways associated with ALT and reveals potential therapeutic targets that require further experimental validation.
Modelling the effects of climate change on the interaction between bacteria and phages with a temperature-dependent lifecycle switch
Abstract Ongoing climate change and human activities alter the population dynamics of pathogenic bacteria in natural environments, increasing the risk of disease transmission. Among the key mechanisms of amplification of bacteria in the environment is the alteration of the natural control by their enemies, bacteriophages. Using mathematical modelling, we explore how climate change and implementation of certain agricultural practices affect interactions of bacteria with phage exhibiting condition-dependent lysogeny, where the type of phage infection lifecycle is determined by the ambient temperature. As a case study, we model alteration to the control of the pathogenic bacteria Burkholderia pseudomallei by its dominant phage. B. pseudomallei causes melioidosis, which is among the deadliest infections in Southeast Asia and across the tropics. We use historical records for UV radiation and temperature in Thailand covering the period 2009–2023 to assess the density of the phage-free pathogen, capable of causing infection. We also predict phage-pathogen dynamics for the period 2024–2044. We apply both non-spatial and spatial models to mimic B. pseudomallei population dynamics in the surface water of rice fields and in soil. Our models predict a drastic increase in pathogen density due to less efficient control by the phage which is caused by global warming. We also find that some of the current agricultural practices would enhance the risk of acquisition of melioidosis by altering densities of the pathogen in the environment.
A NEMD approach to the melt-front evolution under gravity
Modeling the evolution of the melt front under gravity in the presence of a horizontal thermal gradient is a challenging issue, hitherto tackled exclusively with the concepts and tools of computational continuum thermomechanics, too phenomenologically driven to have satisfactory predictive capabilities. Here, we show that this complex phenomenon is amenable to treatment by the methods and tools of Non-Equilibrium Molecular Dynamics (NEMD). To do so, we addressed all the difficulties caused by the necessity of applying suitable boundary conditions and minimizing surface effects so that the bulk behavior of the system in non-equilibrium conditions can be detected. Sufficient adiabatic separation of the time scales permits us to use macroscopically relatively short—but microscopically long enough—time averages to get the macroscopic bulk behavior of the system accurately. To get an adequate signal-to-noise ratio, we had to use an unphysically large value of the gravity. However, we know from NEMD simulations in transport studies that the phenomena produced are stable over many orders of magnitude. In conclusion, our work proves that molecular simulation can be a good tool to study this family of non-equilibrium phenomena, although further work is needed to achieve quantitative predictive capabilities.
Perceptions and experiences of young adults and their healthcare team of the D1 Now type 1 diabetes intervention
Background Young adults (18–25 years) with type 1 diabetes can have high blood glucose levels, increasing their risk of complications. The D1 Now intervention aimed to improve outcomes, using a young adult-centred approach, comprising three components: an interactive messaging system, agenda setting tool, and support worker. A pilot randomised controlled trial was conducted to assess acceptability and feasibility of this novel intervention. Aim To explore perceptions and experiences of young adults and healthcare staff participating in the intervention arms of the D1 Now pilot randomised controlled trial. Methods A descriptive qualitative approach using semi structured interviews was used to collect data between May 2020, and January 2021 from sixteen young adults and ten healthcare staff Interviews were conducted online using MS Teams. Thematic analysis was used to analyse the data. A patient and public involvement approach was used with the D1 Now Young Adult Panel deployed from the outset to design and contribute to the study. Both written consent in advance and verbal consent was given by all participants for the online interviews that were video and audio recorded according to individual participant preference. Results Themes were developed separately for young adult and healthcare staff participants. Two themes were developed from the young adult data, 1) ‘empowerment’ and 2) ‘perceptions and experiences of the intervention’. One theme was developed from the healthcare staff data, ‘perceptions and experiences of delivering the intervention’. All participants highlighted that the agenda setting tool and the support worker empowered the young adults as they could focus the consultation process on what mattered most to them. However, the interactive messaging system was perceived as unsuitable by many mainly because the technology was outdated. Overall, the perceived impact of participating in the study was positive. Conclusions Understanding participants perceptions and experiences of taking part in the D1 Now intervention is crucial. The lessons learnt can be used to further refine and develop the intervention with a view to measuring its effectiveness, in a future definitive trial.
A detection method for small casting defects based on bidirectional feature extraction
Spin polarization generated by reversible doublet-quartet transitions in photoexcited chromophore-radical conjugates
Light-induced spin polarization can be produced in chromophore-radical conjugates by reversible transitions between the excited trip-doublet and trip-quartet states. The precise origin of this polarization is often difficult to elucidate because different transition pathways, promoted by different interactions, can occur depending on the nature of the conjugate. Moreover, the complexity of the expressions describing the evolution of the spin state populations and polarization generated by these transitions makes it difficult to estimate the dependence of the polarization on factors such as the exchange interaction and spin–orbit coupling. Here, we present a theoretical analysis and show that by making assumptions for specific cases, simplified expressions can be obtained that provide better insight into the physical origins of the polarization.
Topic recognition and refined evolution path analysis of literature in the field of cybersecurity
Using text analysis techniques to identify the research topics of the literature in the field of cybersecurity allows us to sort out the evolution of their research topics and reveal their evolution trends. The paper takes the literature from the Web of Science in the field of cybersecurity research from 2003 to 2022 as its research subject, dividing it into ten stages. It then integrates LDA and Word2vec methods for topic recognition and topic evolution analysis. The combined LDA2vec model can better reflect the correlation and evolution patterns between adjacent stage topics, thereby accurately identifying topic features and constructing topic evolution paths. Furthermore, to comprehensively evaluate the effectiveness of the LDA model in topic evolution analysis, this paper introduces the Dynamic Topic Model (DTM) for comparative analysis. The results indicate that the LDA model demonstrates higher applicability and clarity in topic extraction and evolution path depiction. In the aspect of topic content evolution, research topics within the field of cybersecurity exhibit characteristics of complexity and diversity, with some topics even displaying notable instances of backtracking. Meanwhile, within the realm of cybersecurity, there exists a dynamic equilibrium between technological developments and security threats.
Surgical site infection following appendectomy in children
Hydrogen bonds vs RMSD: Geometric reaction coordinates for protein folding
Reaction coordinates are a useful tool that allows the complex dynamics of a protein in high-dimensional phase space to be projected onto a much simpler model with only a few degrees of freedom, while preserving the essential aspects of that dynamics. In this way, reaction coordinates could provide an intuitive, albeit simplified, understanding of the complex dynamics of proteins. Together with molecular dynamics (MD) simulations, reaction coordinates can also be used to sample the phase space very efficiently and to calculate transition rates and paths between different metastable states. Unfortunately, ideal reaction coordinates for a system capable of these performances are not known a priori, and an efficient calculation in the course of an MD simulation is currently an active field of research. An alternative is to use geometric reaction coordinates, which, although generally unable to provide quantitative accuracy, are useful for simplified mechanistic models of protein dynamics and can thus help gain insights into the fundamental aspects of these dynamics. In this study, five such geometric reaction coordinates, such as the end-to-end distance, the radius of gyration, the solvent accessible surface area, the root-mean-square distance (RMSD), and the mean native hydrogen bond length, are compared. For this purpose, extensive molecular dynamics simulations were carried out for two peptides and a small protein in order to calculate and compare free energy profiles with the aid of the reaction coordinates mentioned. While none of the investigated geometrical reaction coordinates could be demonstrated to be an optimal reaction coordinate, the RMSD and the mean native hydrogen bond length appeared to perform more effectively than the other three reaction coordinates.
Unveiling triple vulnerability among Mozambican female sex workers—Stigma, physical violence and sexual violence
Background In the shadows of Mozambique’s urban landscape, an invisible struggle unfolds among its most vulnerable: Female Sex Workers (FSWSs). FSWs bear a disproportionate burden of violence as a consequence of the stigma surrounding their profession, as both stigma and violence create significant barriers to the progress of HIV elimination within this group by limiting their access to prevention and treatment services, discourages them from seeking help, while violence itself increases vulnerability to HIV. This study examines the patterns of stigma, physical and sexual violence, and HIV among FSWs. Methodology A secondary analysis was performed using data from a cross-sectional Bio-Behavioral Survey (BBS) conducted among FSW ≥15 and old, implemented between 2019–2020 in five urban areas. Respondent-driven sampling (RDS) was utilized to recruit participants. Aggregate weighted estimates were calculated for self-reported stigma, physical, and sexual violence. Associations between variables were assessed using chi-squared tests, and multivariate logistic regression was employed to identify factors associated with stigma, physical violence, and sexual violence. Results Among 2,567 FSWs surveyed, 24.7% reported experiencing stigma, while 52.3% and 37.9% reported physical and sexual violence, respectively, in the six months preceding the survey. The likelihood of experiencing stigma was over six times higher for FSWs who engaged with more than 7 clients (AOR = 6.1; p <0.001). Drug use was associated with a twofold increase in the odds of physical violence (AOR = 2.3; p <0.001) and a nearly threefold increase in the odds of sexual violence (AOR = 2.7; p <0.001). HIV-positive FSWs were at increased risk for both physical violence (AOR = 1.2; p = 0.006) and sexual violence (AOR = 1.2; p = 0.031). Conclusion This study highlights the substantial burden of stigma and violence among FSWs in Mozambique’s urban areas. The findings underscore the urgent need for targeted interventions to reduce stigma, prevent violence, and protect the rights of FSWs. Addressing these issues is essential for achieving the goals of HIV prevention and treatment in this vulnerable population.