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For three specific singular perturbed three-component reaction–diffusion systems that admit N-spike solutions in one of the components on a finite domain, we present a detailed analysis for the dynamics of temporal oscillations in the spike positions. The onset of these oscillations is induced by N Hopf bifurcations with respect to the translation modes that are excited nearly simultaneously. To understand the dynamics of N spikes in the vicinity of Hopf bifurcations, we combine the center manifold reduction and the matched asymptotic method to derive a set of ordinary differential equations (ODEs) of dimension 2N describing the spikes’ locations and velocities, which can be recognized as normal forms of multiple Hopf bifurcations. The reduced ODE system then is represented in the form of linear oscillators with weakly nonlinear damping. By applying the multiple-time method, the leading order of the oscillation amplitudes is further characterized by an N-dimensional ODE system of the Stuart–Landau type. Although the leading order dynamics of these three systems are different, they have the same form after a suitable transformation. On the basis of the reduced systems for the oscillation amplitudes, we prove that there are at most ⌊ N / 2 ⌋ + 1 stable equilibria, corresponding to ⌊ N / 2 ⌋ + 1 types of different oscillations. This resolves an open problem proposed by Xie et al. (Nonlinearity 34(8):5708–5743, 2021) for a three-component Schnakenberg system and generalizes the results to two other classic systems. Numerical simulations are presented to verify the analytic results. [ABSTRACT FROM AUTHOR]

Population migration within spatial structures significantly influences disease spread. Given the typically uneven environment, individuals randomly interact with various others, facilitating disease transmission over time. Complex networks are integrated into infectious disease models and effectively capture these contact dynamics. In this paper, we propose a two-delay networked SIR epidemic model featuring a Crowley-Martin type incidence rate and Holling III type treatment rate. The stability of three equilibria of the model is proved by analyzing the distribution of characteristic roots. When two delays change at the same time, the stable region of the equilibrium on delays plane and the existence of Hopf bifurcation are obtained by the method of stability switching curves. Furthermore, we calculate the normal form of Hopf bifurcation to obtain the direction of Hopf bifurcation and the stability of bifurcation periodic solutions. Finally, numerical simulation on a small-world Watts-Strogatz network is performed to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

A diffusive Lotka–Volterra competition system with memory-based diffusion is analyzed. The stability of the boundary steady states depends on memory-based self-diffusion but is independent of memory-based cross-diffusion. However, memory-based cross-diffusion induces instability in the constant coexistence state, increasing the complexity of the spatiotemporal dynamics of the system. We establish the critical conditions under which the constant coexistence state loses its stability through Turing bifurcation, Hopf bifurcation, and double-Hopf bifurcation. The normal form of the double-Hopf bifurcation is also derived. This allows us to prove the existence of an unstable spatially inhomogeneous quasi-periodic solution, and the coexistence of two types of stable spatially inhomogeneous periodic solutions with different wave numbers. In particular, a repulsive memory-based diffusion induces competing species to coexist in spatially segregated steady-state patterns, and an attractive memory-based diffusion can induce competing species to coexist in spatially segregated time-periodic patterns. [ABSTRACT FROM AUTHOR]

This study establishes a novel time-delay fractional SEIHR infectious disease model to investigate the effects of saturated incidence rates and time delays on different populations, including susceptibles, infected individuals, recovered individuals, and latent infected individuals. First, the existence and boundedness of the model's solutions are verified, confirming its well-posedness. Subsequently, the existence of equilibria is analyzed, and the impact of parameter variations on the system is explored by examining the equilibria ϵ 0 and ϵ ∗ , as well as the basic reproduction number R 0 . Additionally, the global dynamics of the equilibria are further analyzed using the Lyapunov method, while Hopf bifurcation theory is applied to explore the conditions under which the system shifts from stability to oscillatory behavior. Numerical simulations further validate the theoretical analysis, showing that time-delay effects significantly influence the system's responsiveness and the rate of disease transmission. Moreover, when the time delay τ crosses the critical threshold τ 0 , the system exhibits periodic oscillations. By predicting periodic fluctuations and incorporating memory effects and persistent influences, we can better control epidemics, emphasizing the importance of time-delay adjustments and enhancing the system's biological realism. [ABSTRACT FROM AUTHOR]

In this paper, we introduce spatial memory into a predator–prey model with herd behavior. Taking memory-based diffusion coefficient and average memory period of predators as control parameters, we obtain the stable conditions of the positive equilibrium of system and prove the existence of Hopf bifurcation. In addition, a double Hopf bifurcation occurs at the intersection of the nonhomogeneous Hopf bifurcation curves, and a spatially nonhomogeneous quasi-periodic pattern can be observed near the double Hopf bifurcation point by numerical simulation. [ABSTRACT FROM AUTHOR]

Implementing management systems in organisations of all types and sizes often raises the following question: "What benefits will this bring?" Initial resistance and criticism are common as potential challenges are identified during the implementation process. To address this, it is essential to highlight the advantages of these systems and engage stakeholders in supporting management efforts. While the planning, implementation, use, maintenance, auditing, and improvement of management systems are generally voluntary, certification is frequently driven by external factors, particularly customer demands. Employees also stand to gain significantly, with knowledge and information serving as valuable resources, especially for leveraging artificial intelligence. This article explores the management's readiness to adopt and fully utilise two management systems based on international standards: the ISO 30401 Knowledge management system (KMS) and the ISO/IEC 42001 Artificial intelligence management system (AIMS). Through interviews, we assess the challenges and solutions associated with implementing these systems, whether planned or partially adopted. The findings illustrate the synergistic benefits of integrating the KMS and AIMS, demonstrating how their combined use can enhance Integrated Management Systems (IMSs). Such integration supports comprehensive planning, operation, and performance evaluation of processes and services while also promoting continuous improvement. [ABSTRACT FROM AUTHOR]

This paper is concerned with the qualitative analysis of a diffusion SIR epidemic model with networked delay and nonlinear incidence rate. First, we prove the existence and uniqueness of the model by using the method of upper and lower solutions. Then, we prove that the trivial equilibrium (0, 0) is unstable; the disease‐free equilibrium (N, 0) is locally asymptotically stable if the reproduction number R0≤1 and unstable if R0>1; the endemic equilibrium (S∗, I∗) is locally asymptotically stable if R0≤R1 or if R1τ10∗. Moreover, when R1

High throughput in vitro assays for screening chemical hazards focus primarily on specific receptors that are linked with certain adverse outcome pathways, neglecting potential novel endpoints or pathways induced by emerging pollutants. Identifying target proteins that interact with pollutants contributes to finding potential molecular initiating events under the adverse outcome pathways framework. Mass spectrometry-based thermal proteome profiling (TPP) assays have permitted uncovering binding targets of pollutants across the whole proteome. Based on the principle that proteins are thermally stabilized after binding with chemicals, TPP differentiates protein targets by determining the soluble fraction of proteins that remain stable after heat stress. Thus, TPP facilitates qualitative and quantitative measurements of chemical-protein interactions (CPIs) without modifications on chemical structures or immobilization of target proteins. In this mini-review, we introduced the principles, development and procedures of TPP, and summarized its applications in identifying protein targets and speculating toxicity pathways for emerging pollutants in environmental toxicological studies. Additionally, since measurements of CPIs using TPP for multiple chemicals could be labor- and cost-intensive, machine learning-based modeling is a feasible alternative to dissect CPIs due to its capability to mine intrinsic properties determining CPIs. Therefore, the recent development of machine learning models for CPI prediction was reviewed. Lastly, we envisioned prospects of combining TPP data with machine learning for CPI prediction, and the possibility of applying TPP to interpret toxicity pathways and phenotypes generated from multi-omics data, to inform future environmental toxicological research on forecasting targets and outcomes for emerging pollutants. [ABSTRACT FROM AUTHOR]

This study investigates a symmetric fractional-order epidemic model with time delays and non-monotonic incidence rates, considering two viral strains. By confirming the existence, uniqueness, and boundedness of the system's solutions, the research ensures the model's well-posedness, guaranteeing its mathematical soundness and practical relevance. The study calculates and evaluates the equilibrium points and the basic reproduction numbers R 0 1 and R 0 2 to understand the dynamic behavior of the model under different parameter settings. Through the application of the Lyapunov method, the research examines the asymptotic global stability of the system, determining whether it will converge to a particular equilibrium state over time. Furthermore, Hopf bifurcation theory is employed to investigate potential periodic solutions and bifurcation scenarios, highlighting how the system might shift from stability to periodic oscillations under certain conditions. By utilizing the Adams-Bashforth-Moulton numerical simulation method, the theoretical results are validated, reinforcing the conclusions and demonstrating the model's applicability in real-world contexts. It emphasizes the importance of fractional-order models in addressing epidemiological issues related to time delays (τ), individual heterogeneity (m, k), and memory effects (θ), offering greater accuracy compared with traditional integer-order models. In summary, this research provides a theoretical foundation and practical insights, enhancing the understanding and management of epidemic dynamics through fractional-order epidemic models. [ABSTRACT FROM AUTHOR]

This study examines the impact of Bisphenol A (BPA), a prevalent environmental estrogenic toxicant, on the ovarian development of mice. Mice were exposed to varying BPA doses from in utero to postnatal stages, up to weaning (day 21, PND 21) and puberty (day 45, PND 45). The BPA content in the serum of the offspring mice on PND 45 was higher than that of the mice sacrificed at PND 21. However, the ovary organ index of the mice of PND 21 was significantly increased, and the ovarian structure was damaged when exposed to BPA. In contrast, the mice with PND 45 did not show apparent ovarian lesions. On the other hand, granulosa cell apoptosis was detected in both PND 21 and PND 45 mice ovaries, and ERβ was increased under the influence of BPA. Transcriptomic analysis revealed BPA's significant impact on ribosomal gene expression, marked downregulation of Rpl21 and Rpsa, and upregulation of Rps2 in both age groups. These transcriptomic alterations were further corroborated by real-time PCR, highlighting a dose-dependent effect of BPA on Rps2. Our findings confirm BPA's detrimental effects on ovarian health, with more pronounced damage in younger mice, suggesting heightened vulnerability in this group. The study underscores ribosomes as critical targets in BPA-induced ovarian developmental disruptions. [ABSTRACT FROM AUTHOR]

The study proposes an active trailer steering control method for tractor semitrailers to promote the path tracking effect of the trailer portion as well as lateral stability during lane changing. Firstly, a simplified model of a tractor semitrailer is constructed, and the MAP map is formed based on the genetic algorithm for the identification of the key parameters, which improves the model's accuracy. Then the tractor and trailer's yaw rate and sideslip angle at CG are tracked as the control objective and the trailer angle distribution strategy is given. Then the LQR-based corner controller is designed to control the steering actuators of each axle of the trailer. Finally, the effectiveness of the designed control strategy is verified based on the Trucksim/Simulink joint simulation platform and the semi-physical HiL test platform. The simulation results show that the designed controller can effectively improve the path tracking effect of the tractor and the trailer, and at the same time, the lateral stability parameters of the tractor and the trailer are also significantly improved, which improves the driving stability of the tractor semitrailer. [ABSTRACT FROM AUTHOR]

We prove that the R-matrix and Drinfeld presentations of the Yangian double in type A are isomorphic. The central elements of the completed Yangian double in type A at the critical level are constructed. The images of these elements under a Harish-Chandra-type homomorphism are calculated by applying a version of the Poincaré-Birkhoff-Witt theorem for the R-matrix presentation. These images coincide with the eigenvalues of the central elements in the Wakimoto modules. [ABSTRACT FROM AUTHOR]

Motivation Large language models, trained on enormous corpora of biological sequences, are state-of-the-art for downstream genomic and proteomic tasks. Since the genome contains the information to encode all proteins, genomic language models (gLMs) hold the potential to make downstream predictions not only about DNA sequences, but also about proteins. However, the performance of gLMs on protein tasks remains unknown, due to few tasks pairing proteins with the coding DNA sequences (CDS) that can be processed by gLMs. Results In this work, we curated five such datasets and used them to evaluate the performance of gLMs and proteomic language models (pLMs). We show that gLMs are competitive and even outperform their pLMs counterparts on some tasks. The best performance was achieved using the retrieved CDS compared to sampling strategies. We found that training a joint genomic-proteomic model outperforms each individual approach, showing that they capture different but complementary sequence representations, as we demonstrate through model interpretation of their embeddings. Lastly, we explored different genomic tokenization schemes to improve downstream protein performance. We trained a new Nucleotide Transformer (50M) foundation model with 3mer tokenization that outperforms its 6mer counterpart on protein tasks while maintaining performance on genomics tasks. The application of gLMs to proteomics offers the potential to leverage rich CDS data, and in the spirit of the central dogma, the possibility of a unified and synergistic approach to genomics and proteomics. Availability and implementation We make our inference code, 3mer pre-trained model weights and datasets available. [ABSTRACT FROM AUTHOR]

Introduction: A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement. Areas covered: This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches. Expert opinion: CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research. [ABSTRACT FROM AUTHOR]

Protein language models (PLMs) play a dominant role in protein representation learning. Most existing PLMs regard proteins as sequences of 20 natural amino acids. The problem with this representation method is that it simply divides the protein sequence into sequences of individual amino acids, ignoring the fact that certain residues often occur together. Therefore, it is inappropriate to view amino acids as isolated tokens. Instead, the PLMs should recognize the frequently occurring combinations of amino acids as a single token. In this study, we use the byte-pair-encoding algorithm and unigram to construct advanced residue vocabularies for protein sequence tokenization, and we have shown that PLMs pre-trained using these advanced vocabularies exhibit superior performance on downstream tasks when compared to those trained with simple vocabularies. Furthermore, we introduce PETA, a comprehensive benchmark for systematically evaluating PLMs. We find that vocabularies comprising 50 and 200 elements achieve optimal performance. Our code, model weights, and datasets are available at https://github.com/ginnm/ProteinPretraining. Scientific contribution: This study introduces advanced protein sequence tokenization analysis, leveraging the byte-pair-encoding algorithm and unigram. By recognizing frequently occurring combinations of amino acids as single tokens, our proposed method enhances the performance of PLMs on downstream tasks. Additionally, we present PETA, a new comprehensive benchmark for the systematic evaluation of PLMs, demonstrating that vocabularies of 50 and 200 elements offer optimal performance. [ABSTRACT FROM AUTHOR]

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We consider nonlinear delay differential and renewal equations with infinite delay. We extend the work of Gyllenberg et al. [Appl. Math. Comput., 333 (2018), pp. 490--505] by introducing a unifying abstract framework, and we derive a finite-dimensional approximating system via pseudospectral discretization. For renewal equations, we consider a reformulation in the space of absolutely continuous functions via integration. We prove the one-to-one correspondence of equilibria between the original equation and its approximation, and that linearization and discretization commute. Our most important result is the proof of convergence of the characteristic roots of the pseudospectral approximation of the linear(ized) equations when the collocation nodes are chosen as the family of scaled zeros or extrema of Laguerre polynomials. This ensures that the finite-dimensional system correctly reproduces the stability properties of the original linear equation if the dimension of the approximation is large enough. The result is illustrated with several numerical tests, which also demonstrate the effectiveness of the approach for the bifurcation analysis of equilibria of nonlinear equations. The new approach used to prove convergence also provides the exact location of the spectrum of the differentiation matrices for the Laguerre zeros and extrema, adding new insights into properties that are important in the numerical solution of differential equations by pseudospectral methods. [ABSTRACT FROM AUTHOR]

In this paper, we construct an action of 3-cobordisms on the finite dimensional Schrödinger representations of the Heisenberg group by Lagrangian correspondences. In addition, we review the construction of the abelian Topological Quantum Field Theory (TQFT) associated with a q-deformation of U.1/for any root of unity q. We prove that, for 3-cobordisms compatible with Lagrangian correspondences, there is a normalization of the associated Schrödinger bimodule action that reproduces the abelian TQFT. The full abelian TQFT provides a projective representation of the mapping class group Mod.Σ/on the Schrödinger representation, which is linearizable at odd root of 1. Motivated by homology of surface configurations with Schrödinger representation as local coefficients, we define another projective action of Mod.Σ/on Schrödinger representations. We show that the latter is not linearizable by identifying the associated 2-cocycle. [ABSTRACT FROM AUTHOR]

Teacher immediacy and classroom communication apprehension have been well researched in the United States. Instructional communication research in Brazil is limited, and several topics still demand investigation among the population of Brazil. This study extends current research on teacher immediacy and classroom communication apprehension to the Brazilian population. We should extend the analysis to the Brazilian context instead of relying on previous investigations from other regions as the basis for cross-cultural theorizing. A total of 221 students participated in the survey. This study reports four significant findings: (1) Brazilian students' perceptions of teacher immediacy are greater than American students' perceptions of teacher immediacy; (2) American students have higher levels of Classroom Communication Apprehension than Brazilian students; (3) Classroom communication apprehension is negatively correlated with American students' perceptions of teacher immediacy; and (4) Classroom communication apprehension is not significantly correlated with Brazilian students' perceptions of teacher immediacy. Highly immediate teachers will have less apprehensive students. [ABSTRACT FROM AUTHOR]

Temperature is a critical environmental factor affecting nearly all plant processes, including growth, development, and yield. Yet, despite decades of research, we lack the ability to predict plant performance at different temperatures, limiting the development of climate-resilient crops. Further, there is a pressing need to bridge the gap between the prediction of physiological and molecular traits to improve our understanding and manipulation of plant temperature responses. Here, we developed the first enzyme-constrained model of Arabidopsis thaliana's metabolism, facilitating predictions of growth-related phenotypes at different temperatures. We showed that the model can be employed for in silico identification of genes that affect plant growth at suboptimal growth temperature. Using mutant lines, we validated the genes predicted to affect plant growth, demonstrating the potential of metabolic modeling in accurately predicting plant thermal responses. The temperature-dependent enzyme-constrained metabolic model provides a template that can be used for developing sophisticated strategies to engineer climate-resilient crops., (© 2025 The Author(s). New Phytologist © 2025 New Phytologist Foundation.)

Extrinsic motivation can foster effortful cognitive control. Moreover, the selective coupling of extrinsic motivation on low- versus high-control demands tasks would exert an additional impact. However, to what extent their influences are further modulated by the level of Need for Cognition (NFC) remains unclear. Thus, the current study sought to address this question. To this end, we conducted two behavioral experiments wherein cognitive control was triggered by the confound-minimized Stroop task and the NFC questionnaire was administered. Two different forms of extrinsic motivation were manipulated at the block level. In Experiment 1, extrinsic motivation was triggered by evaluative feedback. In Experiment 2, extrinsic motivation was triggered by reward incentives, while evaluative feedback was selectively coupled with low (congruent)- or high (incongruent)- control demands trials. The results indicated that two forms of extrinsic motivation (evaluative feedback vs. reward incentives) presented distinctive effects on effortful cognitive control; while their benefits on overall performance were further influenced by NFC. Interestingly, when incongruent rather than congruent trials were selectively coupled with reward incentives, not only conflict processing, but also overall performance for low-NFC participants only, benefited from this scenario. Taken together, the current study shows that extrinsic motivation can boost cognitive control, which gain was further reduced by high NFC., Competing Interests: Declarations. Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ghent University and the Sichuan Normal University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent: Informed consent was obtained from all individual participants included in the study. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this research, we introduce and analyze a mathematical model for online social networks, incorporating two distinct delays. These delays represent the time it takes for active users within the network to begin disengaging, either with or without contacting non-users of online social platforms. We focus particularly on the user prevailing equilibrium (UPE), denoted as P * , and explore the role of delays as parameters in triggering Hopf bifurcations. In doing so, we find the conditions under which Hopf bifurcations occur, then establish stable regions based on the two delays. Furthermore, we delineate the boundaries of stability regions wherein bifurcations transpire as the delays cross these thresholds. We present numerical simulations to illustrate and validate our theoretical findings. Through this interdisciplinary approach, we aim to deepen our understanding of the dynamics inherent in online social networks. [ABSTRACT FROM AUTHOR]

Spatial memory is key in animal movement modeling, but it has been challenging to explicitly model learning to describe memory acquisition. In this paper, we study novel cognitive consumer-resource models with different consumer learning mechanisms and investigate their dynamics. These models consist of two PDEs in composition with one ODE such that the spectrum of the corresponding linearized operator at a constant steady state is unclear. We describe the spectra of the linearized operators and analyze the eigenvalue problems to determine the stability of the constant steady states. We then perform bifurcation analysis by taking the perceptual diffusion rate as the bifurcation parameter. It is found that steady-state and Hopf bifurcations can both occur in these systems, and the bifurcation points are given so that the stability region can be determined. Moreover, rich spatial and spatiotemporal patterns can be generated in such systems via different types of bifurcation. Our effort establishes a new approach to tackling a hybrid model of PDE-ODE composition and provides a deeper understanding of cognitive movement-driven consumer-resource dynamics. [ABSTRACT FROM AUTHOR]

In current scientific and technological scenarios, studies of transmittance of surface waves across structured interfaces have gained some wind amidst applications to metasurfaces, electronic edge-waves, crystal grain boundaries, etc. The results presented in the present article shed a light on the influence of material inhomogeneities on propagation of surface waves. Within the framework of classical mechanics, an analogue of the Gurtin–Murdoch model is employed where elastic properties on surface are assumed to be distinct from bulk. Restricting to scalar waves on prototype square lattice half-plane, particles on considered structured surface have piecewise-constant mass and surface force-constants across an interfacial point. Particles in bulk lattice interact with nearest neighbours in a way that involves unequal force-constants parallel to surface versus normal to it. A surface wave band exists for such lattice structure wherein the waveform decays exponentially inside the half-plane. A formula for surface wave transmittance is given based on an exact solution on half-plane, and, thus, previous work (Sharma & Eremeyev 2019 Int. J. Eng. Sci.143, 33–38 (doi:10.1016/j.ijengsci.2019.06.007)) is extended. An explicit expression for fraction of energy influx leaked via bulk waves is a highlight. Included are graphical results for several illustrative values of surface structure parameters. [ABSTRACT FROM AUTHOR]

Copyright of Psychological Science is the property of Psychological Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aims. To evaluate the adverse events (and its clinical correlates) in a large prospective cohort of Asian patients with atrial fibrillation (AF) and diabetes mellitus (DM). Material and Methods. We recruited patients with atrial fibrillation (AF) from the Asia-Pacific Heart Rhythm Society (APHRS) AF Registry and included those for whom the diabetic mellitus (DM) status was known. We used Cox-regression analysis to assess the 1-year risk of all-cause death, thromboembolic events, acute coronary syndrome, heart failure and major bleeding. Results. Of 4058 patients (mean age 68.5 ± 11.8 years; 34.4% females) considered for this analysis, 999 (24.6%) had DM (age 71 ± 11 years, 36.4% females). Patients with DM had higher mean CHA2DS2-VASc (2.3 ± 1.6 vs. 4.0 ± 1.5, p < 0.001) and HAS-BLED (1.3 ± 1.0 vs. 1.7 ± 1.1, p < 0.001) risk scores and were less treated with rhythm control strategies compared to patients without DM (18.7% vs. 22.0%). After 1-year of follow-up, patients with DM had higher incidence of all-cause death (4.9% vs. 2.3%, p < 0.001), cardiovascular death (1.3% vs. 0.4%, p = 0.003), and major bleeding (1.8% vs. 0.9%, p = 0.002) compared to those without DM. On Cox regression analysis, adjusted for age, sex, heart failure, coronary and peripheral artery diseases and previous thromboembolic event, DM was independently associated with a higher risk of all-cause death (HR 1.48, 95% CI 1.00–2.19), cardiovascular death (HR 2.33, 95% CI 1.01–5.40), and major bleeding (HR 1.91, 95% 1.01–3.60). On interaction analysis, the impact of DM in determining the risk of all-cause death was greater in young than in older patients (p int = 0.010). Conclusions. Given the high rates of adverse outcomes in these Asian AF patients with DM, efforts to optimize the management approach of these high-risk patients in a holistic or integrated care approach are needed. [ABSTRACT FROM AUTHOR]

Motivation Protein language models (PLMs), which borrowed ideas for modelling and inference from natural language processing, have demonstrated the ability to extract meaningful representations in an unsupervised way. This led to significant performance improvement in several downstream tasks. Clustering amino acids based on their physical–chemical properties to achieve reduced alphabets has been of interest in past research, but their application to PLMs or folding models is unexplored. Results Here, we investigate the efficacy of PLMs trained on reduced amino acid alphabets in capturing evolutionary information, and we explore how the loss of protein sequence information impacts learned representations and downstream task performance. Our empirical work shows that PLMs trained on the full alphabet and a large number of sequences capture fine details that are lost in alphabet reduction methods. We further show the ability of a structure prediction model(ESMFold) to fold CASP14 protein sequences translated using a reduced alphabet. For 10 proteins out of the 50 targets, reduced alphabets improve structural predictions with LDDT-C α differences of up to 19%. Availability and implementation Trained models and code are available at github.com/Ieremie/reduced-alph-PLM. [ABSTRACT FROM AUTHOR]

Metal-based nanomaterials (MNMs) have gained particular interest in nanotechnology industry. They are used in various industrial processes, in biomedical applications or to improve functional properties of several consumer products. The widescale use of MNMs in the global consumer market has resulted in increases in the likelihood of exposure and risks to human beings. Human exposure to MNMs and assessment of their potential health effects through the concomitant application of biomarkers of exposure and effect of the most commonly used MNMs were reviewed in this paper. In particular, interactions of MNMs with biological systems and the nanobiomonitoring as a prevention tool to detect the early damage caused by MNMs as well as related topics like the influence of some physicochemical features of MNMs and availability of analytical approaches for MNMs testing in human samples were summarized in this review. The studies collected and discussed seek to increase the current knowledge on the internal dose exposure and health effects of MNMs, highlighting the advantages in using biomarkers in primary prevention and health surveillance. [ABSTRACT FROM AUTHOR]

Whole-brain models have proven to be useful to understand the emergence of collective activity among neural populations or brain regions. These models combine connectivity matrices, or connectomes, with local node dynamics, noise, and, eventually, transmission delays. Multiple choices for the local dynamics have been proposed. Among them, nonlinear oscillators corresponding to a supercritical Hopf bifurcation have been used to link brain connectivity and collective phase and amplitude dynamics in different brain states. Here, we studied the linear fluctuations of this model to estimate its stationary statistics, i.e., the instantaneous and lagged covariances and the power spectral densities. This linear approximation—that holds in the case of heterogeneous parameters and time-delays—allows analytical estimation of the statistics and it can be used for fast parameter explorations to study changes in brain state, changes in brain activity due to alterations in structural connectivity, and modulations of parameter due to non-equilibrium dynamics. [ABSTRACT FROM AUTHOR]

Background: This study aims to improve nursing students' ability to care for critically ill patients through education in extracorporeal membrane oxygenation (ECMO) nursing. Methods: This study developed a virtual reality (VR) simulation program for the five-step ECMO nursing of the Analysis, Design, Development, Implement, and Evaluation (ADDIE) model and used an equivalent control group pre-test and post-test no-synchronized design to verify the effect. The participants of this study were fourth-year nursing students enrolled in nursing departments at three universities in Seoul, Gangwon, and Gyeonggi in South Korea; it included 66 participants, 33 in each of the experimental and control groups. The program consisted of pre-training, orientation, VR simulation, and debriefing. Results: The interaction effect of the intervention and control groups with time points using the ECMO nursing VR simulation program was rejected due to no statistically significant difference in knowledge (F = 1.41, p =.251), confidence (F = 1.97, p =.144), and clinical reasoning capacity (F = 2.85, p =.061). However, learning immersion (t = 3.97, p <.001) and learning satisfaction (t = 4.25, p <.001) were statistically significantly higher in the experimental group than in the control group. Conclusion: VR simulation program for ECMO nursing developed in this study is a potential educational method that positively affects the learning immersion and learning satisfaction of nursing students. [ABSTRACT FROM AUTHOR]

This paper mainly studies the dynamical behavior of the infectious disease model affected by white noise and Lévy noise. First, a stochastic model of infectious disease with secondary vaccination affected by noises is established. Besides, the existence and uniqueness of the global positive solution for the stochastic model are proved based on stochastic differential equations and Lyapunov function, then the asymptotic behavior of the disease-free equilibrium point is studied. Moreover, the sufficient conditions for the extinction of the disease are obtained and the analysis showed that different noise intensity could affect the extinction of infectious disease on different degree. Finally, the theoretical results are verified by numerical simulation and some suggestions have been put forward on how to prevent the spread of diseases are presented. [ABSTRACT FROM AUTHOR]

Motivation Understanding protein thermostability is essential for numerous biotechnological applications, but traditional experimental methods are time-consuming, expensive, and error-prone. Recently, deep learning (DL) techniques from natural language processing (NLP) was extended to the field of biology, since the primary sequence of proteins can be viewed as a string of amino acids that follow a physicochemical grammar. Results In this study, we developed TemBERTure, a DL framework that predicts thermostability class and melting temperature from protein sequences. Our findings emphasize the importance of data diversity for training robust models, especially by including sequences from a wider range of organisms. Additionally, we suggest using attention scores from Deep Learning models to gain deeper insights into protein thermostability. Analyzing these scores in conjunction with the 3D protein structure can enhance understanding of the complex interactions among amino acid properties, their positioning, and the surrounding microenvironment. By addressing the limitations of current prediction methods and introducing new exploration avenues, this research paves the way for more accurate and informative protein thermostability predictions, ultimately accelerating advancements in protein engineering. Availability and implementation TemBERTure model and the data are available at: https://github.com/ibmm-unibe-ch/TemBERTure. [ABSTRACT FROM AUTHOR]

In the structure of the title compound, C19H19N3O5S·C4H8O2, the two independent dioxane molecules each display inversion symmetry. The pyrazole ring is approximately parallel to the aromatic ring of the oxy-ethanone group and approximately perpendicular to the tolyl ring of the sulfonyl substituent. An extensive system of classical and 'weak' hydrogen bonds connects the residues to form a layer structure parallel to (201), within which dimeric subunits are conspicuous; neighbouring layers are connected by classical hydrogen bonds to dioxanes and by 'weak' hydrogen bonds from Htolyl donors. [ABSTRACT FROM AUTHOR]

Temporary elevation of tumor temperature, also known as hyperthermia, is a safe and well-tolerated treatment modality. The efficacy of hyperthermia can be improved by efficient thermosensitizers, and various candidate drugs, including inhibitors of the heat stress response, have been explored in vitro and in animal models, but clinically relevant thermosensitizers are lacking. Here, we employ unbiased in silico approaches to uncover new mechanisms and compounds that could be leveraged to increase the thermosensitivity of cancer cells. We then focus on elesclomol, a well-performing compound, which amplifies cell killing by hyperthermia by 5- to 20-fold in cell lines and outperforms clinically applied chemotherapy when combined with hyperthermia in vitro. Surprisingly, our findings suggest that the thermosensitizing effects of elesclomol are independent of its previously reported modes of action but depend on copper shuttling. Importantly, we show that, like elesclomol, multiple other copper shuttlers can thermosensitize, suggesting that disturbing copper homeostasis could be a general strategy for improving the efficacy of hyperthermia. [ABSTRACT FROM AUTHOR]

Temperature is a crucial regulator of the rate and direction of biochemical reactions and cell processes. The recent data indicating the presence of local thermal gradients associated with the sites of high-rate thermogenesis, on the one hand, demonstrate the possibility for the existence of "thermal signaling" in a cell and, on the other, are criticized on the basis of thermodynamic calculations and models. Here, we review the main thermometric techniques and sensors developed for the determination of temperature inside living cells and diverse intracellular compartments. A comparative analysis is conducted of the results obtained using these methods for the cytosol, nucleus, endo-/sarcoplasmic reticulum, and mitochondria, as well as their biological consistency. Special attention is given to the limitations, possible sources of errors and ambiguities of the sensor's responses. The issue of biological temperature limits in cells and organelles is considered. It is concluded that the elaboration of experimental protocols for ultralocal temperature measurements that take into account both the characteristics of biological systems, as well as the properties and limitations of each type of sensor is of critical importance for the generation of reliable results and further progress in this field. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the impact of COVID-19 pandemic among a sample of Italian dentists in terms of infection, strategies for infection control, organization of the dental clinic, attitude, and behavior., Material and Methods: This was a cross-sectional survey. The sample consisted of 8000 Italian dentists selected among 63,375 using a computerized random sampling method. An electronic informed consent had to be signed. The questionnaire categories were on demographic, infection risk management, organization, and dentists' attitude and behavior. Geographic macro-areas were used for subgroup analysis., Results: Among 8000 invited dentists, 2443 agreed to participate to the survey (30.6%). Mean age was 51.2 years, women were 34.5%. A total of 6.1% self-reported COVID-19 experience and higher rate of infection was reported in north Italy compared to the south (p < 0.05). FFP2/FFP3 respirators (97.1%) and visors (97.4%) were used by almost all dentists. While, natural ventilation and mouthwashes were the most frequent approaches used to reduce the infection risk. Most of the dentists reported positive attitude, nevertheless 83.6% felt an increased responsibility., Conclusion: The self-reported COVID-19 prevalence was 6.1% with some differences among geographic areas. COVID 19 had a deep impact on preventive strategies, dental office organization, and behavior within this sample., (© 2023 The Authors. Oral Diseases published by Wiley Periodicals LLC.)

In this work, the influences of nonlocal interactions on the growing inclusion are studied which are embedded in an elastic wave metamaterial with local resonators. The nonlocal interactions between main resonators are considered as linear springs connected to the second nearest neighboring ones. In addition, the inclusion is supposed that particle masses change along a straight line. Based on the Wiener–Hopf method, the ratio of the tip to end displacements of the inclusion is derived. Furthermore, the dynamic effective mass and stop band frequency are discussed. Numerical results show that in comparison with the system without nonlocal interactions, the new periodic structure can make the displacement ratio tend to the case of homogeneous lattices for high-speed regions. It indicates that more powerful resistance can be created by nonlocal springs during the inclusion growth. [ABSTRACT FROM AUTHOR]

In bromido(pyrrolidine-κN)gold(I) bis(pyrrolidine-κN)gold(I) bromide, [AuBr- (pyr)]⋅[Au(pyr)2]Br (pyr = pyrrolidine, C4H9N), 2, alternating [AuBr(pyr)] molecules and [Au(pyr)2]+ cations are connected by aurophilic contacts to form infinite chains of residues parallel to the b axis. The chains are cross-linked by three N--H⋯Br_ hydrogen bonds and an Au⋯Br contact to form a layer structure parallel to the ab plane. Trichlorido(piperidine-κN)gold(III), [AuCl3(pip)] (pip = piperidine, C5H11N), 3, consists of molecules with the expected square-planar coordination at the gold atom, which are connected by an N--H⋯Cl hydrogen bond and an Au⋯Cl contact to form a layer structure parallel to the ac plane. The structures of bis(piperidinium) tetrachloridoaurate( III) chloride, (pipH)2[AuCl4]Cl, 4, and bis(pyrrolidinium) tetrabromidoaurate( III) bromide, (pyrH)2[AuBr4]Br, 6, are closely related but not isotypic. Compound 6 crystallizes in space group Ibam; the Au and two Br atoms of the anion lie in the mirror plane x, y, 0, whereas the bromide ions occupy special positions 0, 0.5, 0 and 0, 0.5, 0.25, with site symmetry 2/m. The NH2 group forms a hydrogen bond to one bromide ion, and also a three-centre hydrogen bond to the other bromide atom and to a metal-bonded Br atom. The packing involves chains of hydrogen-bonded pyrrolidinium and bromide ions parallel to the c axis, combined with a layer structure of [AuBr4]- and bromide anions, parallel to the ab plane and involving Au⋯Br and Br⋯Br contacts. Compound 4, however, crystallizes pseudosymmetrically in space group Iba2; two chlorine atoms of the anion lie on the twofold axis 0.5, 0.5, z, and there are two independent cations. The packing is closely similar to that of 6, but there are no N--H⋯Cl hydrogen bonds to metal-bonded chlorines. The contact distances Au⋯Cl are appreciably longer than their Au⋯Br counterparts in 6, whereas the Cl⋯Cl contact is much shorter than Br⋯Br in 6. Tribromido(piperidine-κN)gold(III) crystallizes as its dichloromethane solvate, [AuBr3(pip)]•CH2Cl2, 7. It too displays a square-planar coordination at the gold atom. The packing involves hydrogen bonds N--H⋯Br, stacking of neighbouring AuBr3 units by Au⋯Br contacts, and a short Br⋯Br contact; these combine to form a layer structure parallel to the ac plane. [ABSTRACT FROM AUTHOR]

Joint arthroplasty is an option for end-stage septic arthritis due to joint infection after effective control of infection. However, complications such as osteolysis and aseptic loosening can arise afterwards due to wear and tear caused by high joint activity after surgery, necessitating joint revision. Some studies on tissue pathology after prosthesis implantation have identified various cell populations involved in the process. However, these studies have often overlooked the complexity of the altered periprosthetic microenvironment, especially the role of nano wear particles in the etiology of osteolysis and aseptic loosening. To address this gap, we propose the concept of the "prosthetic microenvironment". In this perspective, we first summarize the histological changes in the periprosthetic tissue from prosthetic implantation to aseptic loosening, then analyze the cellular components in the periprosthetic microenvironment post prosthetic implantation. We further elucidate the interactions among cells within periprosthetic tissues, and display the impact of wear particles on the disturbed periprosthetic microenvironments. Moreover, we explore the origins of disease states arising from imbalances in the homeostasis of the periprosthetic microenvironment. The aim of this review is to summarize the role of relevant factors in the microenvironment of the periprosthetic tissues, in an attempt to contribute to the development of innovative treatments to manage this common complication of joint replacement surgery. [ABSTRACT FROM AUTHOR]

Various approaches have used neural networks as probabilistic models for the design of protein sequences. These "inverse folding" models employ different objective functions, which come with trade-offs that have not been assessed in detail before. This study introduces probabilistic definitions of protein stability and conformational specificity and demonstrates the relationship between these chemical properties and the p (structure | seq) Boltzmann probability objective. This links the Boltzmann probability objective function to experimentally verifiable outcomes. We propose a novel sequence decoding algorithm, referred to as "BayesDesign", that leverages Bayes' Rule to maximize the p (structure | seq) objective instead of the p (seq | structure) objective common in inverse folding models. The efficacy of BayesDesign is evaluated in the context of two protein model systems, the NanoLuc enzyme and the WW structural motif. Both BayesDesign and the baseline ProteinMPNN algorithm increase the thermostability of NanoLuc and increase the conformational specificity of WW. The possible sources of error in the model are analyzed. [ABSTRACT FROM AUTHOR]

The method of characteristics is extended to set-valued Hamilton-Jacobi equations. This problem arises from a calculus of variations’ problem with a multicriteria Lagrangian function: through an embedding into a set-valued framework, a set-valued Hamilton-Jacobi equation is derived, where the Hamiltonian function is the Fenchel conjugate of the Lagrangian function. In this paper a method of characteristics is described and some results are given for the Fenchel conjugate. [ABSTRACT FROM AUTHOR]