Search

Metallic glasses (MGs) are of high strength but limited plasticity at room temperature (RT) due to localized shear in the intrinsically heterogeneous structure. Here, we investigate the variation of structural heterogeneity and plasticity of a Zr-based MG after high-temperature (T) tension under different stresses (σ) at 579 K (0.9Tg, where Tg is the glass transition temperature). The correlation length (ξ) of the heterogeneous structure and the average Young's modulus ( E ¯ ) increase with σ when σ is below 160 MPa; when σ exceeds 160 MPa, both ξ and E ¯ decrease with σ, leading to the improvement of the plasticity. This research could be enlightening for improving the plasticity of MGs at RT through tuning their structural heterogeneity with high-T deformation. [ABSTRACT FROM AUTHOR]

Glass-forming liquids exhibit long-lived, spatially correlated dynamical heterogeneity, in which some nm-scale regions in the fluid relax more slowly than others. In the nanoscale vicinity of an interface, glass-formers also exhibit the emergence of massive interfacial gradients in glass transition temperature Tg and relaxation time τ. Both of these forms of heterogeneity have a major impact on material properties. Nevertheless, their interplay has remained poorly understood. Here, we employ molecular dynamics simulations of polymer thin films in the isoconfigurational ensemble in order to probe how bulk dynamic heterogeneity alters and is altered by the large gradient in dynamics at the surface of a glass-forming liquid. Results indicate that the τ spectrum at the surface is broader than in the bulk despite being shifted to shorter times, and yet it is less spatially correlated. This is distinct from the bulk, where the τ distribution becomes broader and more spatially organized as the mean τ increases. We also find that surface gradients in slow dynamics extend further into the film than those in fast dynamics—a result with implications for how distinct properties are perturbed near an interface. None of these features track locally with changes in the heterogeneity of caging scale, emphasizing the local disconnect between these quantities near interfaces. These results are at odds with conceptions of the surface as reflecting simply a higher "rheological temperature" than the bulk, instead pointing to a complex interplay between bulk dynamic heterogeneity and spatially organized dynamical gradients at interfaces in glass-forming liquids. [ABSTRACT FROM AUTHOR]

Despite the enormous theoretical and application interests, a fundamental understanding of the glassy dynamics remains elusive. The static properties of glassy and ordinary liquids are similar, but their dynamics are dramatically different. What leads to this difference is the central puzzle of the field. Even the primary defining glassy characteristics, their implications, and if they are related to a single mechanism remain unclear. This lack of clarity is a severe hindrance to theoretical progress. Here, we combine analytical arguments and simulations of various systems in different dimensions and address these questions. Our results suggest that the myriad of glassy features are manifestations of two distinct mechanisms. Particle caging controls the mean, and coexisting slow- and fast-moving regions govern the distribution of particle displacements. All the other glassy characteristics are manifestations of these two mechanisms; thus, the Fickian yet non-Gaussian nature of glassy liquids is not surprising. We discover a crossover, from stretched exponential to a power law, in the behavior of the overlap function. This crossover is prominent in simulation data and forms the basis of our analyses. Our results have crucial implications on how the glassy dynamics data are analyzed, challenge some recent suggestions on the mechanisms governing glassy dynamics, and impose strict constraints that a correct theory of glasses must have. [ABSTRACT FROM AUTHOR]

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models. [ABSTRACT FROM AUTHOR]

The occurrence of atrial fibrillation (AF), one of the most socially significant arrhythmias, is associated with the presence of areas of fibrosis. Fibrosis introduces conduction heterogeneity into the cardiac tissue and, thus, may be a substrate for spiral wave reentry, which provokes the onset of AF and is often associated with its persistence. Despite results from computer and animal models of cardiac tissues, data on the conditions under which microreentries occur in human tissues are limited. In this work, we conducted a study of the new approach to modeling the fibrous atrial tissue, which takes into account the cellular structure and conduction in fibrosis areas. Using the Potts model, we created a realistic texture of atrial tissues remodeled by fibroblasts and showed the presence of pathways in such a system with a low proportion of fibroblasts. Our study revealed the relationship between the shape of the cells' action potential, their location in the tissue, and the direction of the wave propagation. The wavefront obtained in the model creates a dynamic heterogeneity of the tissue, which affects the migration and pinning of spiral waves, and explains the formation of microreentries in the cardiac tissue. In the future, such a model can become a potential tool for predictive modeling of AF and the search for ablation target identification. [ABSTRACT FROM AUTHOR]

The structure, composition, and spatial distribution heterogeneity of artificial pinning centers affect the critical current density of REBa2Cu3O7−y (RE: rare earth) coated conductors. Nanoscale structures and compositions have been analyzed with transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM). However, microscale heterogeneity has been difficult to characterize. Here, YBa2Cu3O7−y thin films doped with double-perovskite Ba2YbNbO6 were prepared via pulsed-laser deposition and characterized with TEM, STEM, and scanning electron microscopy (SEM). Cross-sectional and plan-view TEM/STEM imaging revealed hybrid pinning structures consisting of nanorods, nanoparticles, and planar defects that were formed spontaneously. Nanorods were imaged with high spatial resolution via field-emission SEM of thin-foil specimens. Focused-ion-beam (FIB) micro-sectioning enables SEM imaging of microscale heterogeneity in nanorod spatial distributions. By using TEM/STEM in conjunction with FIB-SEM, the coated conductor inhomogeneity was directly evaluated from the nano- to micrometer scales. [ABSTRACT FROM AUTHOR]

In polydisperse systems, describing the structure and any structural order parameter (SOP) is not trivial as it varies with the number of species we use to describe the system, M. Depending on the degree of polydispersity, there is an optimum value of M = M0 where we show that the mutual information of the system increases. However, surprisingly, the correlation between a recently proposed SOP and the dynamics is highest for M = 1. This effect increases with polydispersity. We find that the SOP at M = 1 is coupled with the particle size, σ, and this coupling increases with polydispersity and decreases with an increase in M. Careful analysis shows that at lower polydispersities, the SOP is a good predictor of the dynamics. However, at higher polydispersity, the dynamics is strongly dependent on σ. Since the coupling between the SOP and σ is higher for M = 1, it appears to be a better predictor of the dynamics. We also study the Vibrality, an order parameter independent of structural information. Compared to SOP, at high polydispersity, we find Vibrality to be a marginally better predictor of the dynamics. However, this high predictive power of Vibrality, which is not there at lower polydispersity, appears to be due to its stronger coupling with σ. Therefore, our study suggests that for systems with high polydispersity, the correlation of any order parameter and σ will affect the correlation between the order parameter and dynamics and need not project a generic predictive power of the order parameter. [ABSTRACT FROM AUTHOR]

Using first-principles density functional calculations, we investigate the structure and properties of previously unstudied grain boundaries (GBs) in the solar absorber material copper-zinc-tin-sulfide (CZTS). We identify four stable low-Σ value symmetric tilt GBs with low formation energies: Σ3 (111) and Σ5 (201), each with two different GB terminations. Compared to CdTe and CuInSe, GBs in the quaternary semiconductor CZTS exhibit a wider variety of electronic states due to the more complex chemical environment near the GB, including under-coordinated atoms and dangling bonds. Further analysis confirms that strong dangling bonds introduce deep gap states in all GBs studied. We also investigate segregation and electronic properties of intrinsic point defects to GBs and find that one of the Σ3 (111) GBs exhibits an abnormal defect segregation behavior that favors Cu-poor (Zn-rich) GB composition, which is beneficial for its overall performance. [ABSTRACT FROM AUTHOR]

The positive relationship between knowledge transfer and knowledge innovation is recognized by most scholars, while knowledge heterogeneity, as a knowledge situation of the enterprise organization, affects knowledge transfer within enterprise organizations. Therefore, as a state, knowledge transfer can be regarded as a result of knowledge heterogeneity, and it becomes the intermediary state between knowledge heterogeneity and knowledge innovation. The organizational structure of individuals within an enterprise organization may affect these three elements and their interrelationships. In this paper, data are collected by means of on-the-spot investigation and a network questionnaire for analysis. The results show that the microstructure state of the individual in the enterprise organization plays a moderating role for the first three elements. The lower that the micro-restriction of the individual is, the more favorable the knowledge heterogeneity is for the inverted U-shaped impact of knowledge transfer and knowledge innovation and the more favorable the occurrence of knowledge innovation. [ABSTRACT FROM AUTHOR]

Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity. Using data from the UK Biobank (n = 41,948–109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (r g) of both sets of MDD symptoms. We further compared their r g with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms. Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (r g = 0.43–0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences. MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity. [ABSTRACT FROM AUTHOR]

Ceramic-based dielectric capacitors are showing great potential in advanced high-power applications. However, simultaneous achievement of high energy density (W rec) and temperature stability is still a main bottleneck. Herein, an extraordinary nanoscale structural heterogeneity is developed to promote temperature-stable energy storage in Er/Mn co-doped Bi 0.5 Na 0.5 TiO 3 based ceramics via domain and defect dipoles engineering. The composition-driven domain reconstruction by Er/Mn co-doping can induce internal random fields with rapid response to the electric field, and thus enhance ΔP and η. Meanwhile, the donor-accpetor Er/Mn doping could manipulate defect dipoles coupling to resist the applied field evolution to elevate BDS and η. Besides, the improved relaxor feature and core-shell structure give rise to the enhanced temperature stability. Ceramics with 2 mol % Er 2 O 3 demonstrate high W rec ∼2.79 J/cm3, large efficiency ∼89.4% and outstanding dielectric stability within 70–500 °C. The proposed nanostructural heterogeneity was verified as a promising pathway to manufact temperature-stable energy storage ceramics. The nanoscale structural heterogeneity via domain and defect dipoles strategies is developed to promote temperature-stable energy storage in NBT-based ceramics. [Display omitted] [ABSTRACT FROM AUTHOR]

Emerging research suggests that episodic memory challenges are commonly encountered by autistic individuals; however, the specific nature of these memory challenges remains elusive. Here, we address critical gaps in the literature by examining pattern separation memory, the ability to store distinct memories of similar stimuli, and its links to the core autistic trait of repetitive, restricted interests and behaviors. Utilizing a large sample of over 120 autistic children and well-matched non-autistic peers, we found that autistic children showed significantly reduced performance on pattern separation memory. A clustering analysis identified three distinct pattern separation memory profiles in autism, each characterized by reduced or increased generalization abilities. Importantly, pattern separation memory was negatively correlated with the severity of repetitive, restricted interest and behavior symptoms in autism. These findings offer new evidence for challenges in pattern separation memory in autism and emphasize the need to consider these challenges when assessing and supporting autistic individuals in educational and clinical settings. Memory challenges remain understudied in childhood autism. Our study investigates one specific aspect of memory function, known as pattern separation memory, in autistic children. Pattern separation memory refers to the critical ability to store unique memories of similar stimuli; however, its role in childhood autism remains largely uncharted. Our study first uncovered that the pattern separation memory was significantly reduced in autistic children, and then showed that reduced memory performance was linked to their symptoms of repetitive, restricted interest and behavior. We also identified distinct subgroups with profiles of reduced and increased generalization for pattern separation memory. More than 72% of autistic children showed a tendency to reduce memory generalization, focusing heavily on unique details of objects for memorization. This focus made it challenging for them to identify commonalities across similar entities. Interestingly, a smaller proportion of autistic children displayed an opposite pattern of increased generalization, marked by challenges in differentiating between similar yet distinct objects. Our findings advance the understanding of memory function in autism and have practical implications for devising personalized learning strategies that align with the unique memory patterns exhibited by autistic children. This study will be of broad interest to researchers in psychology, psychiatry, and brain development as well as teachers, parents, clinicians, and the wider public. [ABSTRACT FROM AUTHOR]

Drunk-driving events often escalate into drunk-driving crashes, however, the contributing factors of this progression remain elusive. To mitigate the likelihood of crashes stemming from drunk-driving events, this paper introduces the notion of 'the severity of drunk-driving event' and examines the complex relationship between the severity and its contributing factors, considering spatiotemporal heterogeneity. The study utilizes a Geographically and Temporally Weighted Binary Logistic Regression (GTWBLR) model to conduct spatiotemporal analysis based on police-reported drunk-driving events in Beijing, China. The results show that most factors passed the non-stationary test, indicating their effects on the severity of drunk-driving event vary significantly across different spatial and temporal domains. Notably, during non-workday, drunk-driving events in northeast of Beijing are more likely to escalate into crashes. Furthermore, severe weather during winter in the northwest of Beijing is associated with high risk of drunk-driving crashes. Based on these insights, the authorities can strengthen drunk-driving checks in the northeast region of Beijing, particularly during non-workdays. And it is crucial to promptly clear accumulated snow on the roads during severe winter weather to improve road safety. These insights and recommendations are highly valuable for reducing the risk of drunk-driving crashes. [ABSTRACT FROM AUTHOR]

Delivery riders are more vulnerable than other traffic participants, especially in vehicle-involved delivery crashes. This study aims at identifying the unobserved heterogeneities in different factors, based on 4251 vehicle-scooter-style electric bicycle (SSEB) crashes. First, some potential factors are selected from seven perspectives, and the spatiotemporal characteristics are analysed. Second, a latent class clustering method is proposed to clarify the optimal number of clusters by maximizing the heterogeneities across clusters. Third, partial proportional odds (PPO) models for the whole dataset and sub-datasets are developed to explore the heterogeneities across various clusters. Besides, marginal effects are implemented to quantify the heterogeneities. The results evidence that there are remarkable heterogeneities across different clusters, especially in riding behaviours and road conditions. Several factors only significantly affect particular clusters but not the whole dataset. The PPO models for the sub-datasets perform better in identifying the underlying heterogeneities. The results also highlight the greater roles of riding behaviours and road conditions in delivery SSEB-vehicle crashes. The top five influencing factors are running red light, using cell phones, vehicle type, reverse riding and bike lane (their maximum marginal effects exceeding +35%). The findings could support to mitigate the related crash losses. [ABSTRACT FROM AUTHOR]

Trade-offs are central to life history theory and play a role in driving life history diversity. They arise from a finite amount of resources that need to be allocated among different functions by an organism. Yet covariation of demographic rates among individuals frequently do not reflect allocation trade-offs because of variation in resource acquisition. The covariation of traits among individuals can thus vary with the environment and often increases in benign environments. Surprisingly, little is known about how such context-dependent expression of trade-offs among individuals affect population dynamics across species with different life histories. To study their influence on population stability, we develop an individual-based simulation where covariation in demographic rates varies with the environment. We use it to simulate population dynamics for various life histories across the slow-fast pace-of-life continuum. We found that the population dynamics of slower life histories are relatively more sensitive to changes in covariation, regardless of the trade-off considered. Additionally, we found that the impact on population stability depends on which trade-off is considered, with opposite effects of intraindividual and intergenerational trade-offs. Last, the expression of different trade-offs can feed back to influence generation time through selection acting on individual heterogeneity within cohorts, ultimately affecting population dynamics. [ABSTRACT FROM AUTHOR]

The multifaceted nature of osteoarthritis (OA) pain presents a challenge in understanding and managing the condition. The diverse pain experiences, progression rates, individual responses to treatments, and complex disease mechanisms contribute to heterogeneity in the clinical studies outcomes. The lack of a standardized methodology for assessing and classifying OA pain challenges healthcare practitioners. This complicates the establishment of universally applicable protocols or standardized guidelines for treatment. This article explores the heterogeneity observed in clinical studies evaluating OA pain treatments, highlighting the necessity for refined methodologies, personalized patient categorization, and consistent outcome measures. It discusses the role of the multidimensional nature of OA pain, underlying pain mechanisms, and other contributing factors to the heterogeneity in outcome measures. Addressing these variations is crucial to establishing a more consistent framework for evidence-based treatments and advancing care of the patient with OA pain. [ABSTRACT FROM AUTHOR]

Evaluation of physical and mechanical heterogeneity in commercial paperboards is needed to promote their use in structural applications, especially within the field of packaging. Understanding the range of their behaviors is needed to compete with other materials in the current marketplace and expand in others. This work describes the physical and stiffness heterogeneities of twelve commercial materials using tensile tests in the cross-machine direction and several inverse analyses. The effects of grammage, thickness, and apparent density on tensile stiffness were evaluated in both the linear elastic and nonlinear regimes. Thickness and density provided the best explanation for elastic heterogeneous behavior in most of the materials; local grammage was not the best descriptor for any material. The analyses used here were not able to provide a good explanation of the nonlinear behavior, which was attributed to the development of large shear strains within the materials as they neared failure. This work provides a methodology for additional heterogeneous behavior examinations. [ABSTRACT FROM AUTHOR]

Wilson disease (WD) is a rare autosomal recessive disorder of copper metabolism caused due to mutations in the copper transporter ATP7B. There is often a striking variability of clinical manifestations among patients with ATP7B mutations, including in siblings. This phenomenon may be caused by individual differences in copper accumulation in hepatocytes and intolerance to copper toxicity as governed by genetic variations in copper metabolism genes acting as modifier loci to the disease. To elucidate the genetic basis of striking clinical heterogeneity among two siblings of two families with WD. The disease diagnosis and subsequent clinical examinations were performed by expert clinicians. The younger siblings in both families presented with early neurological manifestations at a younger age than their older siblings. Interestingly, only the younger siblings were reported to have had hepatic manifestations. Exome sequencing of all the four individuals was performed to understand their heterogeneous phenotypic outcomes. Genetic screening revealed no difference in the ATP7B variant spectrum between the siblings of each family. However, the siblings of both the families were found to harbor mutually exclusive pathogenic variants in suspected modifier genes implicated in copper metabolism and/or other neurological and hepatic disorders having overlapping symptoms with WD, viz., CFTR, PPARG, ABCB11, ATP7A, CYP2D6, mTOR, TOR1A, and CP, which can potentially explain their differential clinical phenotypes. Clinical heterogeneity between siblings with WD with the same ATP7B mutation profile may be attributed to the presence of different pathogenic variants in potential modifier genes. [ABSTRACT FROM AUTHOR]

It is not only the states of the European Union (EU) that are heterogeneous in many respects, but also the regions existing within them. In this paper, we make use of a conjoint experiment on a particular type of technocratic solidarity – joint procurement of medical countermeasures (JPMC) – to explore how old and new regional-level heterogeneities affect public support for such type of solidarity. To this end, we exploit an experimental dataset, covering five EU countries at different phases of the Covid-19 pandemic in spring 2020. Our experimental results show that a broad policy scope, allocation based on need and EU governance all raise support for JPMC. Moreover, economically weaker regions and areas more severely hit by the pandemic exhibit stronger public backing for JPMC. Turning to the link between regional heterogeneities and specific design features of JPMC, evidence suggests that wealthier regions display greater public backing for a broader scope of the policy. Thus, our results suggest that public preferences for technocratic solidarity are generally strong, but also depend to some extent on regional collective rationalism. [ABSTRACT FROM AUTHOR]

The dissolution of nonprofit organizations has been increasingly documented by scholars in recent decades. Within this body of literature, how nonprofits' community environments affect their dissolution has not been extensively studied. This research combines a range of data sources to conduct a longitudinal analysis (2007–2015) of how two community factors influence the dissolution of nonprofit organizations across U.S. counties: demographic heterogeneity and political ideology. The study finds that counties with higher demographic heterogeneity and more liberal ideology generally experience higher levels of nonprofit dissolution, although these effects vary slightly across nonprofits' service fields. The findings extend the literature on nonprofit dissolution and offer implications for nonprofits to promote organizational sustainability. [ABSTRACT FROM AUTHOR]

Transportation accessibility has been treated as an important means of reducing the urban-rural income disparity. However, only a few studies have examined the effects of different types of transportation accessibility on urban-rural income disparity and their spatial heterogeneity. Based on data from 285 prefecture-level (and above) Chinese cities in 2000, 2005, 2010, 2015, and 2020, this study uses spatial econometric models to examine how highway accessibility and railway accessibility influence the urban-rural income disparity and to identify their spatial heterogeneity. The result reveals that highway accessibility and railway accessibility have 'coreperiphery' ring-like circle structures. The urban-rural income disparity exhibits strong spatial clustering effects. Both highway accessibility and railway accessibility are negatively associated with urban-rural income disparity, and the former having a greater effect size. Moreover, there is a substitution effect between highway accessibility and railway accessibility in the whole sample. Furthermore, these associations differ in geographic regions. In the central region, highway accessibility is more important in reducing the urban-rural income disparity, but its effect is weakened with the increase of railway accessibility. In the western region, railway accessibility has a larger effect on narrowing the urban-rural income disparity, and this effect is strengthened by the increase of highway accessibility. We conclude that improving transportation accessibility is conducive to reducing the urban-rural income disparity but its effect is spatial heterogenetic. Highways and railways should be developed in a coordinated manner to promote an integrated transport network system. [ABSTRACT FROM AUTHOR]

There are currently no studies examining differences in perceptions and expected impact of the Step 1 score change to pass/fail between surgical and non-surgical program directors (PDs). We conducted a systematic review in May 2023 of PubMed, Scopus, Web of Science, and PSYCInfo to evaluate studies examining PDs' perspectives regarding the Step 1 score change. We performed random-effects meta-analyses to determine differences in perspectives among surgical and non-surgical PDs. Surgical PDs (76.8% [95% CI, 72.1%-82.0%], I 2 = 52%) reported significantly greater rates of disagreement with the score change compared to non-surgical (65.1% [95% CI, 57.9%-73.1%], I 2 = 69.7%) (P =.01). Surgical PDs also reported significantly greater rates of agreement that the score change will increase the difficulty in objectively comparing applicants (88.1% [95% CI, 84.6%-91.7%], I 2 = 16.4%), compared to non-surgical (81.0% [95% CI, 75.6%-86.8%], I 2 = 72.6%) (P =.04). There was less heterogeneity among non-surgical PDs (88.7% [95% CI, 86.2%-91.2%], I 2 = 0%), compared to surgical (84.7% [95% CI, 79.0%-90.8%], I 2 = 67.3%), regarding expected increases in emphasis on Step 2, although the difference in rates of agreement was not statistically significant. Overall, there is significant heterogeneity in the literature regarding expected changes in the residency application review process. Most PDs reported significant disagreement with the score change, greater expected difficulty in objectively evaluating applicants, and greater emphasis on Step 2, with surgical PDs reporting greater rates of disagreement, greater expected difficulty, and heterogeneity regarding expected increases in emphasis on Step 2, compared to non-surgical. Additionally, there is significant heterogeneity in the overall literature regarding expected changes in the residency application review process. Further research is needed to establish evidence-based guidelines that improve the overall residency application process for all stakeholders. [ABSTRACT FROM AUTHOR]

One specific phenomenon in the Spring Festival travel rush in China is that purchasing a train ticket becomes tough as the train tickets could be sold out extremely soon. Therefore, the current paper presents an analysis of college students' trip ticket purchasing strategies for homecoming trips during Chinese Spring Festival using a sequential stated adaptation experiment, based on which three different choice models were applied and the results show that 1) college students would keep purchasing the ticket of planned train trip and this willingness would decrease with the increasing of the times they fail to get the ticket; 2) if college students decide to give up the conventional train trip they have planned, they have a tendency to choose other conventional train trips, but it is not the case regarding high-speed train trips; 3) air itinerary trips are attractive alternatives to trains trips, especially to high-speed train trips. [ABSTRACT FROM AUTHOR]

Due to the complex interactions between multiple infectious diseases, the spreading of diseases in human bodies can vary when people are exposed to multiple sources of infection at the same time. Typically, there is heterogeneity in individuals' responses to diseases, and the transmission routes of different diseases also vary. Therefore, this paper proposes an SIS disease spreading model with individual heterogeneity and transmission route heterogeneity under the simultaneous action of two competitive infectious diseases. We derive the theoretical epidemic spreading threshold using quenched mean-field theory and perform numerical analysis under the Markovian method. Numerical results confirm the reliability of the theoretical threshold and show the inhibitory effect of the proportion of fully competitive individuals on epidemic spreading. The results also show that the diversity of disease transmission routes promotes disease spreading, and this effect gradually weakens when the epidemic spreading rate is high enough. Finally, we find a negative correlation between the theoretical spreading threshold and the average degree of the network. We demonstrate the practical application of the model by comparing simulation outputs to temporal trends of two competitive infectious diseases, COVID-19 and seasonal influenza in China. [ABSTRACT FROM AUTHOR]

The use of Constant‐stress accelerated degradation tests (CSADT) modeling is an effective way to assess the reliability of products. However, when conducting reliability experiments, the data collected may come from various sources such as different manufacturing batches, equipment, and operators. This can result in reduced accuracy of the test evaluations. In this research paper, we propose optimal designs for the Wiener constant‐stress accelerated degradation model that take into account the heterogeneity of manufacturing batches and individual differences. Our goal is to minimize the variability of the mean time to failure (MTTF) while working within a specified budget, test time, and available test units. To achieve this, we utilize particle swarm optimization (PSO) to find the best solution based on a complex objective function. We also compare our model with others using degradation data from LEDs, showing that our model has a better goodness‐of‐fit. Finally, we present examples of optimal CSADT plans under different constraints and conduct sensitivity analysis. [ABSTRACT FROM AUTHOR]

Background: There is no consensus on tests required to either diagnose unexplained infertility or use for research inclusion criteria. This leads to heterogeneity and bias affecting meta‐analysis and best practice advice. Objectives: This systematic review analyses the variability of inclusion criteria applied to couples with unexplained infertility. We propose standardised criteria for use both in future research studies and clinical diagnosis. Search strategy: CINAHL and MEDLINE online databases were searched up to November 2022 for all published studies recruiting couples with unexplained infertility, available in full text in the English language. Data collection and analysis: Data were collected in an Excel spreadsheet. Results were analysed per category and methodology or reference range. Main results: Of 375 relevant studies, only 258 defined their inclusion criteria. The most commonly applied inclusion criteria were semen analysis, tubal patency and assessment of ovulation in 220 (85%), 232 (90%), 205 (79.5%) respectively. Only 87/220 (39.5%) studies reporting semen analysis used the World Health Organization (WHO) limits. Tubal patency was accepted if bilateral in 145/232 (62.5%) and if unilateral in 24/232 (10.3%). Ovulation was assessed using mid‐luteal serum progesterone in 115/205 (56.1%) and by a history of regular cycles in 87/205 (42.4%). Other criteria, including uterine cavity assessment and hormone profile, were applied in less than 50% of included studies. Conclusions: This review highlights the heterogeneity among studied populations with unexplained infertility. Development and application of internationally accepted criteria will improve the quality of research and future clinical care. Linked article: This article is commented on by Tarek El‐Toukhy, pp. 898 in this issue. To view this mini commentary visit https://doi.org/10.1111/1471‐0528.17778 [ABSTRACT FROM AUTHOR]

This study evaluated urban space quality in Beijing using service quality and landscape quality based on points of interest (POI) data, street view data, and perception data derived from deep learning and then applied a hedonic price model (HPM) and a spatial lag model (SLM) to calculate people's heterogeneity marginal willingness to pay (MWTP) for urban space quality across categories, locations, and purchasers. The results showed that (1) people are willing to pay for urban space quality, especially urban landscape quality; however, the MWTP for urban space quality decreases as its distance from the main employment center increases; (2) the MWTP for urban space quality has an inverted u-shaped relationship, indicating that individuals with medium income exhibit a higher willingness to pay for urban space quality; and (3) urban space quality exhibits spatial spillover effects on individuals' MWTP in surrounding areas, with a spatial spillover boundary of approximately 22 km. Overall, this study provided important insights into quantifying the economic benefits of urban space quality and highlights the importance of considering different categories, locations, and purchasers when assessing urban space quality. [ABSTRACT FROM AUTHOR]

In response to severe old-age poverty in South Korea, the Basic Pension has been operated since 2008 for 70% of low-income older adults as a means-tested benefit. It has become an important income supplement for them; however, its expenditure has sharply increased due to rapid population aging. This study analyzed the Korea Household Income and Expenditure Survey using changes-in-changes to examine heterogeneous effects at different income deciles among its development phases in 2008, 2014, 2018, and 2019–2021. First, the largest benefit increase in 2014 records greater income support effects. Second, in terms of heterogeneous effects, the bottom 10th percentile has insignificant effects in 2018 compared to 2014 because it can select another means-tested programme for general citizens, which provides more extensive benefits since 2015. The 20th–50th percentiles presented significant income increase effects. Although the benefits are distributed for the 60th–70th percentiles, who are positioned above the poverty threshold, they consistently displayed insignificant effects. Practically, obtaining a sufficient increase effect like in 2014 may be difficult considering population aging and massive budget pressure. Therefore, it is necessary to collaborate with other social service programmes and concentrate on vulnerable population to provide sustainable welfare services. [ABSTRACT FROM AUTHOR]

Starting from a classic non-local (in space) Cahn–Hilliard–Stokes model for two-phase flow in a thin heterogeneous fluid domain, we rigorously derive by mathematical homogenization a new effective mixture model consisting of a coupling of a non-local (in time) Hele-Shaw equation with a non-local (in space) Cahn–Hilliard equation. We then analyse the resulting model and prove its well-posedness. A key to the analysis is the new concept of sigma-convergence in thin heterogeneous domains allowing to pass to the homogenization limit with respect to the heterogeneities and the domain thickness simultaneously. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance We aimed to develop consensus for diagnosis/management of SCN8A‐related disorders. Utilizing a modified Delphi process, a global cohort of experienced clinicians and caregivers provided input on diagnosis, phenotypes, treatment, and management of SCN8A‐related disorders.A Core Panel (13 clinicians, one researcher, six caregivers), divided into three subgroups (diagnosis/phenotypes, treatment, comorbidities/prognosis), performed a literature review and developed questions for the modified Delphi process. Twenty‐eight expert clinicians, one researcher, and 13 caregivers from 16 countries participated in the subsequent three survey rounds. We defined consensus as follows: strong consensus, ≥80% fully agree; moderate consensus, ≥80% fully/partially agree, <10% disagree; and modest consensus, 67%–79% fully/partially agree, <10% disagree.Early diagnosis is important for long‐term clinical outcomes in SCN8A‐related disorders. There are five phenotypes: three with early seizure onset (severe developmental and epileptic encephalopathy [DEE], mild/moderate DEE, self‐limited (familial) infantile epilepsy [SeL(F)IE]) and two with later/no seizure onset (neurodevelopmental delay with generalized epilepsy [NDDwGE], NDD without epilepsy [NDDwoE]). Caregivers represented six patients with severe DEE, five mild/moderate DEE, one NDDwGE, and one NDDwoE. Phenotypes vary by age at seizures/developmental delay onset, seizure type, electroencephalographic/magnetic resonance imaging findings, and first‐line treatment. Gain of function (GOF) versus loss of function (LOF) is valuable for informing treatment. Sodium channel blockers are optimal first‐line treatment for GOF, severe DEE, mild/moderate DEE, and SeL(F)IE; levetiracetam is relatively contraindicated in GOF patients. First‐line treatment for NDDwGE is valproate, ethosuximide, or lamotrigine; sodium channel blockers are relatively contraindicated in LOF patients.This is the first‐ever global consensus for the diagnosis and treatment of SCN8A‐related disorders. This consensus will reduce knowledge gaps in disease recognition and inform preferred treatment across this heterogeneous disorder. Consensus of this type allows more clinicians to provide evidence‐based care and empowers SCN8A families to advocate for their children. [ABSTRACT FROM AUTHOR]

For energy and cost-efficient computing, many desktops and embedded computing devices these days use voltage frequency islands (VFIs) based processors. An island in VFIs consists of multiple homogeneous cores; however, multiple islands are generally heterogeneous in nature. In contrary to architectures (non-VFI) with per-core dynamic voltage frequency scaling (DVFS), in VFI, all the cores in an island run on the same voltage/frequency at the same time. The energy-aware scheduling of task graphs on VFI architectures is challenging and different from non-VFI architectures in which task-based DVFS is possible. However, in VFI scheduling, the time slot for which an island runs on a particular voltage will be decided. In this paper, we analyse 20 different scheduling heuristics for VFI architectures by varying the size of this time slot based on the workload properties and also by varying the voltage/frequency of the time slots. We also propose a heuristic OptSlotVFI to utilize all the slots optimally. The results show that the VFI scheduling heuristics are able to generate schedules which improve energy consumption up to 25% with an equivalent or shorter schedule length than the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Background: "Regeneration time" (RT) denotes the time required to obtain a stable mortality rate for mosquitoes exposed to insecticide-treated nets (ITNs) after three consecutive washes of a net in a day. The RT informs the wash interval used to artificially age ITNs to simulate their lifetime performance under user conditions (20 washes). RT was estimated following World Health Organization (WHO) longitudinal method (LM) procedures. Longitudinal evaluation may introduce heterogeneity due to mosquito batch variability, complicating RT determination. To overcome this, nets at each stage of regeneration (i.e., 1, 2, 3, 5 and 7 days post wash) were prepared in advance and refrigerated; then, a complete regeneration series was tested with a single mosquito batch on 1 testing day, completing four series over 4 days. This study compared the complete series method (CSM) against the LM. Methods: The overall heterogeneity in the methods for estimating RT of one incorporated alpha-cypermethrin and piperonyl butoxide (PBO) and one incorporated permethrin with PBO ITNs was determined using laboratory-reared resistant Anopheles arabiensis under standard laboratory conditions. LM methods and CSM were compared in two experiments with refrigerated nets acclimated for (i) 2 h (test 1) and (ii) 3 h (test 2). Four regeneration replicates per day were tested per ITN product with 50 mosquitoes exposed per replicate (equivalent sample size to LM). The heterogeneity from these methods was compared descriptively. Results: The intra-method variability for unwashed pieces was minimal, with variance of 1.26 for CSM and 1.18 for LM. For unwashed nets, LM had substantially greater variance and ratio of LM:CSM was 2.66 in test 1 and 2.49 in test 2. The magnitude of mortality measured in bioassays depended on sample acclimation after refrigeration. Conclusions: The CSM is a convenient method for determining the regeneration times. ITNs are prepared in advance, reducing pressure to prepare all samples to start on a single day. A complete regeneration series of samples is removed from the refrigerator, defrosted and evaluated on a single day with one mosquito batch reducing the influence of mosquito batch heterogeneity on results. Replicates can be conducted over several days but do not have to be conducted on consecutive days, allowing easy facility scheduling. [ABSTRACT FROM AUTHOR]

Membrane proteins are the main targets of therapeutic drugs and most of them are glycosylated. Glycans play pivotal roles in several biological processes, and glycosylation changes are a well-established hallmark of several types of cancer, including pancreatic cancer, that contribute to tumor growth. Mucin-4 (MUC-4) is a membrane glycoprotein which is associated with pancreatic cancer and metastasis, and it has been targeted as a promising vaccine candidate. In this study, Surface Plasmon Resonance Microscopy (SPRM) was implemented to study complex influences of the native N-glycan cellular environment on binding interactions to the MUC-4 receptor as this is currently the only commercially available label-free technique with high enough sensitivity and resolution to measure binding kinetics and heterogeneity on single cells. Such unique capability enables for a more accurate understanding of the "true" binding interactions on human cancer cells without disrupting the native environment of the target MUC-4 receptor. Removal of N-linked glycans in pancreatic cancer cells using PNGase F exposed heterogeneity in Concanavalin (Con A) binding by revealing three new binding populations with higher affinities than the glycosylated control cells. Anti-MUC-4 binding interactions of enzymatically N-linked deglycosylated pancreatic cancer cells produced a 25x faster association and 37x higher affinity relative to the glycosylated control cells. Lastly, four interaction modes were observed for Helix Pomatia Agglutinin (HPA) binding to the glycosylated control cells, but shifted and increased in activity upon removal of N-linked glycans. These results identified predominant interaction modes of glycan and MUC-4 in pancreatic cancer cells, the kinetics of their binding interactions were quantified, and the influence of N-linked glycans in MUC-4 binding interactions was revealed. [ABSTRACT FROM AUTHOR]

Glycans, with their variable compositions and highly dynamic conformations, vastly expand the heterogeneity of whatever factor or cell they are attached to. These properties make them crucial contributors to biological function and organismal health and also very difficult to study. That may be changing as we look to the future of glycobiology. [ABSTRACT FROM AUTHOR]

Cancer heterogeneity analysis is essential for precision medicine. Most of the existing heterogeneity analyses only consider a single type of data and ignore the possible sparsity of important features. In cancer clinical practice, it has been suggested that two types of data, pathological imaging and omics data, are commonly collected and can produce hierarchical heterogeneous structures, in which the refined sub‐subgroup structure determined by omics features can be nested in the rough subgroup structure determined by the imaging features. Moreover, sparsity pursuit has extraordinary significance and is more challenging for heterogeneity analysis, because the important features may not be the same in different subgroups, which is ignored by the existing heterogeneity analyses. Fortunately, rich information from previous literature (for example, those deposited in PubMed) can be used to assist feature selection in the present study. Advancing from the existing analyses, in this study, we propose a novel sparse hierarchical heterogeneity analysis framework, which can integrate two types of features and incorporate prior knowledge to improve feature selection. The proposed approach has satisfactory statistical properties and competitive numerical performance. A TCGA real data analysis demonstrates the practical value of our approach in analyzing data heterogeneity and sparsity. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been used to study the predictability of laboratory earthquakes. However, the question remains whether or not this approach can be applied in a tectonic setting where one may have to rely on sparse earthquake catalogs, and where important timescales vary by orders of magnitude. Here, we apply ML to a synthetic seismicity catalog, generated by continuum models of a rate‐and‐state fault with frictional heterogeneities, which contains foreshocks, mainshocks, and aftershocks that nucleate in a similar manner. We develop a network representation of the seismicity catalog to calculate input features and find that the trained ML model can predict the time‐to‐mainshock with great accuracy, from the scale of decades to minutes. Our results offer clues as to why ML can predict laboratory earthquakes and how the developed approach could be applied to more complex problems where multiple timescales are at play. Plain Language Summary: Accurately forecasting the timing of an impending large earthquake is one of the main but elusive goals of seismology. Recent studies show that machine learning (ML), a powerful tool that can draw inferences from hidden patterns in data, can predict the timing of laboratory earthquakes that mimic faulting in nature. However, the question remains whether or not an ML approach can be applied to natural faults where one may have to rely on sparse earthquake catalogs, and where important timescales vary by orders of magnitude. In this study, we develop and apply an ML approach to a synthetic earthquake catalog generated by physics‐based computer simulations. We find that the trained model can predict the time remaining before the mainshock with great accuracy, from the scale of decades, long before the upcoming earthquake, down to the scale of hours to minutes, right before the mainshock. Our results provide clues as to why ML can predict laboratory earthquakes and how to apply an ML‐based approach to real earthquakes where multiple timescales are at play. Key Points: We developed a network representation of a synthetic earthquake catalog to train a machine‐learning Machine learning (ML) modelThe trained ML model can predict the time remaining before simulated mainshocks with great accuracyThe network representation of seismic moment and event interval enables us to accurately predict the timing of mainshocks [ABSTRACT FROM AUTHOR]

Context: Sheep are seasonal breeding animals. Different reproduction systems exist to enhance productivity in non-breeding season. One of the methods used in enhancing reproductive performance in sheep breeding is melatonin administration. Aim: This study aimed to evaluate the impact of melatonin application on reproductive performance in sheep by meta-analysis according to different factors. Methods: To find eligible studies, PubMed and Web of Science databases were searched. Twenty studies published between 1991 and 2021 were included in the meta-analysis. The effect sizes of pregnancy rate, lambing rate and litter size were calculated according to breeds, production characteristics (dairy-meat breeds) and season (breeding–non-breeding). The study estimated the risk ratio for pregnancy and lambing rates, and standardized mean difference for litter size as effect size. Key results: The melatonin hormone increases the pregnancy rate by 1.07 times and the lambing rate by 1.36 times. The effect size (risk ratio) of the Rasa Aragonesa breed (1.15) for pregnancy rate and the Merino breed (1.65) for lambing rate was higher than the Sarda breed. Conclusions: The positive effect of melatonin was found to be higher in the non-breeding season than in the breeding season for the three reproductive performance traits examined. Implications: This study is a comprehensive research study examining the effect of melatonin application in sheep according to different factors. This study, evaluated the effect of melatonin on reproductive performance in sheep via meta-analysis. Pregnancy rate, lambing rate and litter size were used for reproductive performance parameters. Effect sizes of reproductive performance parameters were calculated according to breeds, production characteristics and seasons. The positive effect of melatonin was found greater in the non-reproductive period than in the breeding period for the three reproductive performance traits examined. This comprehensive research examined the effect of melatonin on sheep according to different factors. [ABSTRACT FROM AUTHOR]

Mesenchymal stem/stromal cells (MSCs) represent a heterogeneous cell population distributed throughout various tissues, demonstrating remarkable adaptability to microenvironmental cues and holding immense promise for disease treatment. However, the inherent diversity within MSCs often leads to variability in therapeutic outcomes, posing challenges for clinical applications. To address this heterogeneity, purification of MSC subpopulations through marker-based isolation has emerged as a promising approach to ensure consistent therapeutic efficacy. In this review, we discussed the reported markers of MSCs, encompassing those developed through candidate marker strategies and high-throughput approaches, with the aim of explore viable strategies for addressing the heterogeneity of MSCs and illuminate prospective research directions in this field. [ABSTRACT FROM AUTHOR]

In recent years, Federated Learning (FL) has gained traction as a privacy-centric approach in medical imaging. This study explores the challenges posed by data heterogeneity on FL algorithms, using the COVIDx CXR-3 dataset as a case study. We contrast the performance of the Federated Averaging (FedAvg) algorithm on non-identically and independently distributed (non-IID) data against identically and independently distributed (IID) data. Our findings reveal a notable performance decline with increased data heterogeneity, emphasizing the need for innovative strategies to enhance FL in diverse environments. This research contributes to the practical implementation of FL, extending beyond theoretical concepts and addressing the nuances in medical imaging applications. This research uncovers the inherent challenges in FL due to data diversity. It sets the stage for future advancements in FL strategies to effectively manage data heterogeneity, especially in sensitive fields like healthcare. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is an extensive heterogeneous disease with a complex cellular ecosystem in the tumor microenvironment (TME). However, the manner in which heterogeneity is shaped by tumors and stromal cells, or vice versa, remains poorly understood. In this study, single‐cell RNA sequencing, spatial transcriptomics, and bulk ATAC‐sequence are integrated from a series of patients with PCa and healthy controls. A stemness subset of club cells marked with SOX9highARlow expression is identified, which is markedly enriched after neoadjuvant androgen‐deprivation therapy (ADT). Furthermore, a subset of CD8+CXCR6+ T cells that function as effector T cells is markedly reduced in patients with malignant PCa. For spatial transcriptome analysis, machine learning and computational intelligence are comprehensively utilized to identify the cellular diversity of prostate cancer cells and cell‐cell communication in situ. Macrophage and neutrophil state transitions along the trajectory of cancer progression are also examined. Finally, the immunosuppressive microenvironment in advanced PCa is found to be associated with the infiltration of regulatory T cells (Tregs), potentially induced by an FAP+ fibroblast subset. In summary, the cellular heterogeneity is delineated in the stage‐specific PCa microenvironment at single‐cell resolution, uncovering their reciprocal crosstalk with disease progression, which can be helpful in promoting PCa diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Information about cell composition in tissue samples is crucial for biomarker discovery and prognosis. Specifically, cancer tissue samples present challenges in deconvolution studies due to mutations and genetic rearrangements. Here, we optimized a robust, DNA methylation-based protocol, to be used for deconvolution of ovarian cancer samples. We compared several state-of-the-art methods (HEpiDISH, MethylCIBERSORT and ARIC) and validated the proposed protocol in an in-silico mixture and in an external dataset containing samples from ovarian cancer patients and controls. The deconvolution protocol we eventually implemented is based on MethylCIBERSORT. Comparing deconvolution methods, we paid close attention to the role of a reference panel. We postulate that a possibly high number of samples (in our case: 247) should be used when building a reference panel to ensure robustness and to compensate for biological and technical variation between samples. Subsequently, we tested the performance of the validated protocol in our own study cohort, consisting of 72 patients with malignant and benign ovarian disease as well as in five external cohorts. In conclusion, we refined and validated a reference-based algorithm to determine cell type composition of ovarian cancer tissue samples to be used in cancer biology studies in larger cohorts. [ABSTRACT FROM AUTHOR]

Bicycle safety has emerged as a pressing concern within the vulnerable transportation community. Numerous studies have been conducted to identify the significant factors that contribute to the severity of cyclist injuries, yet the findings have been subject to uncertainty due to unobserved heterogeneity and class imbalance. This research aims to address these issues by developing a model to examine the impact of key factors on cyclist injury severity, accounting for data heterogeneity and imbalance. To incorporate unobserved heterogeneity, a total of 3,895 bicycle accidents were categorized into three homogeneous sub-accident clusters using Latent Class Cluster Analysis (LCA). Additionally, five over-sampling techniques were employed to mitigate the effects of data imbalance in each accident cluster category. Subsequently, Bayesian Network (BN) structure learning algorithms were utilized to construct 32 BN models after pairing the accident data from the four accident cluster types before and after sampling. The optimal BN models for each accident cluster type provided insights into the key factors associated with cyclist injury severity. The results indicate that the key factors influencing serious cyclist injuries vary heterogeneously across different accident clusters. Female cyclists, adverse weather conditions such as rain and snow, and off-peak periods were identified as key factors in several subclasses of accident clusters. Conversely, factors such as the week of the accident, characteristics of the trafficway, the season, drivers failing to yield to the right-of-way, distracted cyclists, and years of driving experience were found to be key factors in only one subcluster of accident clusters. Additionally, factors such as the time of the crash, gender of the cyclist, and weather conditions exhibit varying levels of heterogeneity across different accident clusters, and in some cases, exhibit opposing effects. [ABSTRACT FROM AUTHOR]

To manage the negative impact of job burnout for the researchers, especially during COVID-19 pandemic, is not easy. Thus, it is essential for educational institutions to provide them with the support they need to improve the person-organization (P-O) fit. Drawing upon the data from the Nature's Global Survey initiated in 2021, this paper analyzed 2,424 effective samples from eleven countries in the world to investigate how P-O fit impacts researchers' job burnout in different countries and their career stages during the COVID-19 pandemic. The findings show that both organizational support and P-O fit have significantly assisted researchers in all career stages to reduce job burnout. Moreover, P-O fit has a greater inhibitory effect on job burnout than organizational support. However, when resources are relatively scarce in some developing countries, it is more important to provide organizational support for researchers. Therefore, in order to improve the efficiency of organizational support and reduce researchers' job burnout, those aspects which are less fit but helpful should be increased appropriately. Moreover, it implies that it would be significant to emphasize the differentiated and career-stage-sensitive resources and support to researchers in different countries in the post-pandemic era to improve researchers' well-being and organizational performance. [ABSTRACT FROM AUTHOR]

Background: Circulating tumor cells (CTCs) are considered as a useful biomarker for early cancer diagnosis, which play a crucial role in metastatic process. Unfortunately, the tumor heterogeneity and extremely rare occurrence rate of CTCs among billions of interfering leukocytes seriously hamper the sensitivity and purity of CTCs isolation. Methods: To address these, we firstly used microfluidic chips to detect the broad-spectrum of triple target combination biomarkers in CTCs of 10 types of cancer patients, including EpCAM, EGFR and Her2. Then, we constructed hybrid engineered cell membrane-camouflaged magnetic nanoparticles (HE-CM-MNs) for efficient capture of heterogeneous CTCs with high-purity, which was enabled by inheriting the recognition ability of HE-CM for various CTCs and reducing homologous cell interaction with leukocytes. Compared with single E-CM-MNs, HE-CM-MNs showed a significant improvement in the capture efficiency for a cell mixture, with an efficiency of 90%. And the capture efficiency of HE-CM-MNs toward 12 subpopulations of tumor cells was ranged from 70 to 85%. Furthermore, by using HE-CM-MNs, we successfully isolated heterogeneous CTCs with high purity from clinical blood samples. Finally, the captured CTCs by HE-CM-MNs could be used for gene mutation analysis. Conclusions: This study demonstrated the promising potential of HE-CM-MNs for heterogeneous CTCs detection and downstream analysis. [ABSTRACT FROM AUTHOR]

A major challenge within the academic literature on SDHs has been inconsistent outcomes reported across studies. Historically, patients have been categorized by the blood-product age identified on imaging (i.e., acute, subacute, or chronic). However, this schematic has likely played a central role in producing the heterogeneity encountered in the literature. In this investigation, a total of 494 patients that underwent SDH evacuation at a tertiary medical center between November 2013-December 2021 were retrospectively identified. Mechanism of injury was reviewed by the authors and categorized as either positive or negative for a high-velocity impact (HVI) injury. Any head strike injury leading to the formation of a SDH while traveling at a velocity beyond that of normal locomotion or daily activities was categorized as an HVI. Patients were subsequently stratified by those with an acute SDHs after a high-velocity impact (aSDHHVI), those with an acute SDH without a high-velocity impact injury (aSDHWO), and those with any combination of subacute or chronic blood products (mixed-SDH [mSDH]). Nine percent (n = 44) of patients experienced an aSDHHVI, 23% (n = 113) aSDHWO, and 68% (n = 337) mSDH. Between these groups, highly distinct patient populations were identified using several metrics for comparison. Most notably, aSDHHVI had a significantly worse neurological status at discharge (50% vs. 23% aSDHWO vs. 8% mSDH; p < 0.001) and mortality (25% vs. 8% aSDHWO vs. 4% mSDH; p < 0.001). Controlling for gender, midline shift (mm), and anticoagulation use in the acute SDH population, multivariable logistic regression revealed a 6.85x odds ratio (p < 0.001) for poor outcomes in those with a positive history for a high-velocity impact injury. As such, the distribution of patients that suffer an HVI related acute SDH versus those that do not can significantly affect the outcomes reported. Adoption of this stratification system will help address the heterogeneity of SDH reporting in the literature while still closely aligning with conventional reporting. [ABSTRACT FROM AUTHOR]

Aim Background Design Methods Results Conclusion Impact Examine profiles of safety attitudes among novices and explore whether profiles moderate the occupational identity–turnover pathway.Novice nurses face unique challenges in adopting positive safety attitudes, which influence outcomes like turnover. However, past research found only average levels of safety attitudes among novices, ignoring possible heterogeneity. Exploring whether meaningful subgroups exist based on safety perspectives and factors shaping them can provide insights to improve safety attitudes and retention.This study was designed as a cross‐sectional investigation.Data were collected through the distribution of questionnaires. Descriptive statistics were first conducted, followed by latent profile analysis. We then carried out univariate analysis and ordinal multinomial regression to explore the factors shaping the different profiles. Finally, we examine the moderating effect of nurses' safety attitudes with different latent profiles on the relationship between professional identification and turnover intention.A total of 816 novice nurses were included. Three profiles were identified: high, moderate and low safety attitudes – higher attitudes were associated with lower turnover intention. Interest in nursing, health status, identity and turnover predicted profile membership. Moderate profile had a stronger buffering effect on the identity–turnover link versus high profile.Multiple safety attitude profiles exist among novice nurses. Certain factors like interest in nursing and occupational identity are associated with more positive safety profiles. Targeting these factors could potentially improve safety attitudes and reduce turnover among novice nurses. The moderating effects suggest that tailored interventions matching specific subgroups may maximize impact.Assessing subgroup attitudes enables tailored training for novices' specific needs, nurturing continuous improvement. Supporting early career development and role identity may strengthen retention intentions. [ABSTRACT FROM AUTHOR]

Impact electrochemistry allows for the investigation of the properties of single entities, ranging from nanoparticles (NPs) to soft bio-particles. It has introduced a novel dimension in the field of biological analysis, enhancing researchers' ability to comprehend biological heterogeneity and offering a new avenue for developing novel diagnostic devices for quantifying biological analytes. This review aims to summarize the recent advancements in impact electrochemistry-based biosensing over the past two to three years and provide insights into the future directions of this field. [ABSTRACT FROM AUTHOR]

Cancer's complexity is in part due to the presence of intratumor heterogeneity and the dynamic nature of cancer cell plasticity, which create substantial obstacles in effective cancer management. Variability within a tumor arises from the existence of diverse populations of cancer cells, impacting the progression, spread, and resistance to treatments. At the core of this variability is the concept of cellular plasticity - the intrinsic ability of cancer cells to alter their molecular and cellular identity in reaction to environmental and genetic changes. This adaptability is a cornerstone of cancer's persistence and progression, making it a formidable target for treatments. Emerging studies have emphasized the critical role of such plasticity in fostering tumor diversity, which in turn influences the course of the disease and the effectiveness of therapeutic strategies. The transformative nature of cancer involves a network of signal transduction pathways, notably those that drive the epithelial-to-mesenchymal transition and metabolic remodeling, shaping the evolutionary path of cancer cells. Despite advancements, our understanding of the precise molecular machinations and signaling networks driving these changes is still evolving, underscoring the necessity for further research. This editorial presents a series entitled "Signaling Cancer Cell Plasticity and Intratumor Heterogeneity" in Cell Communication and Signaling, dedicated to unraveling these complex processes and proposing new avenues for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity. [ABSTRACT FROM AUTHOR]

Deriving from the growing cultural and religious diversity in Germany and the need for educational professionals to be able to deal with heterogeneous groups and communicate to children about how to coexist peacefully with others, this essay focuses on the relationship between common sense and tolerance, particularly in places of inescapable dense coexistence characterised by religious and cultural diversity. Using institutions of preschool and primary education as an example, the extent to which peaceful coexistence and conflict resolution is borne by common sense and supported by practices of tolerance is discussed. Subsequently, the significance of a common-sense approach to practices of tolerance for conceptualising ethical judgement in intercultural and inter-religious education is explored. The article closes with thoughts on the contribution of religious ethics to questions of human coexistence in highly dense and conflict-ridden contexts and briefly addresses aspects of Protestant social ethics. [ABSTRACT FROM AUTHOR]