Search

This multiple case study analysis investigates the culturally engaging nature of a US campus for international students using the Culturally Engaging Campus Environments (CECE) model. Semi-structured interviews and professional development workshop observations were conducted with six faculty and administrative leaders who work closely with international students with the aim of answering the overarching question: how do university faculty and student/academic affairs professionals working with international students perceive the institutional support systems for international students through the lens of the Culturally Engaging Campus Environments conceptual model? Salient findings indicated that change is most needed in the areas of opportunities for meaningful cross-cultural engagement, culturally validating environments, proactive philosophies, and availability of holistic support in within the study's campus context. Practical and theoretical implications are discussed in light of the CECE model.

High school students for whom English is a second language (L2) often struggle with effective text revision because of limited ability to self-regulate their writing, that is, to manage the subprocesses of writing and to use writing-related knowledge and strategies. To help students in China acquire effective text revision skills for English persuasive essays, self-regulated strategy development (SRSD) revision instruction was applied both with and without peer interaction targeting knowledge of six writing dimensions. An experimental design involving 120 Chinese 11th-grade students in three conditions, that is, SRSD revision instruction with and without peer interaction (two treatment conditions) and conventional instruction without SRSD (control condition), was applied to examine the instructional effects on students' writing and text revisions. Analyses of covariance revealed a statistically significant increase in text length and improvement in students' text quality regarding higher-order content-level writing dimensions in both treatment conditions compared to the control condition in a post-intervention test. Notably, the most substantial improvement regarding both text length and text quality was observed in the SRSD plus peer interaction condition. Further, students in both treatment conditions made more text revisions involving longer text segments aimed at improving quality and changing meaning compared to those in the control condition. Among these, the students in the SRSD plus peer interaction condition exhibited the highest frequency of high-quality text revision during the posttest. The findings provide new insights into the effectiveness of SRSD revision instruction and peer interaction in developing L2 high school students' self-regulation in revising English persuasive essays.

A high-nuclearity {Ni18} complex (1) with a unique 'flying saucer' motif has been prepared from the organic chelate, α-methyl-2-pyridine-methanol (mpmH), in conjunction with bridging azido (N3 -) and peroxido (O2 2-) ligands. Magnetic susceptibility measurements revealed the presence of both ferro- and antiferromagnetic exchange interactions between the metal centres in 1, and the stabilization of spin states with appreciable S values at two different temperature regimes. The end-on bridging azido and alkoxido groups are in all likelihood the ferromagnetic mediators, while the η3:η3:μ6-bridging peroxides most likely promote the antiparallel alignment of the metals' spin vectors, yielding an overall non-zero spin ground state for the centrosymmetric compound 1. Furthermore, the {Ni18} nanosized cluster behaves as a single-molecule magnet, exhibiting magnetic hysteresis at low temperatures and two relaxation processes at 15 K and 1.3 K, a very rare phenomenon in polynuclear magnetic 3d-metal clusters.

BackgroundCancer survivors are at increased risk for cardiometabolic comorbidities following cancer treatment, which may be further exacerbated by cannabis and alcohol use. We aimed to examine the direct relationships of cannabis, alcohol, and the co-use of both substances with cardiometabolic risk factors and to explore disparities by race/ethnicity and sex.MethodsCross-sectional data were extracted from adult cancer survivors in the "All of Us" from 2018 to 2022. Cannabis use was defined as occasional or frequent/regular cannabis use (vs. never) in the past 3 months and hazardous alcohol intake (AUDIT-C >3 for females; AUDIT-C >4 for males) versus nonhazardous in the past year, respectively. Co-use was defined as participants who engaged in regular cannabis and hazardous alcohol intake. We identified binary cardiovascular, immune, and metabolic system biomarkers, with high values defined by clinically established cutoffs or >75th percentile. We used multivariable logistic regression adjusting for sociodemographic and clinical factors.ResultsIn our sample (N = 7,054), 7.6% were Hispanic, 6.2% were Black, and 86.2% were White cancer survivors. Less than 5% of Hispanic and White survivors reported substance co-use compared with 7% of Black survivors. Compared with never-users, co-users were 1.58 (95% confidence interval, 1.14-2.19) more likely to have high blood pressure. No significant associations were found between co-use and immune biomarkers or sex differences.ConclusionsCo-use of cannabis and hazardous alcohol may worsen high blood pressure in survivors, who are at higher risk for cardiometabolic comorbidities.ImpactThe study investigates substance use and cardiometabolic biomarkers, urging much research on their effects on cancer survivors.

Coronavirus disease 2019 (COVID-19) poses significant risks for solid organ transplant recipients, who have atypical but poorly characterized immune responses to infection. We aim to understand the host immunologic and microbial features of COVID-19 in transplant recipients by leveraging a prospective multicenter cohort of 86 transplant recipients age- and sex-matched with 172 non-transplant controls. We find that transplant recipients have higher nasal SARS-CoV-2 viral abundance and impaired viral clearance, and lower anti-spike IgG levels. In addition, transplant recipients exhibit decreased plasmablasts and transitional B cells, and increased senescent T cells. Blood and nasal transcriptional profiling demonstrate unexpected upregulation of innate immune signaling pathways and increased levels of several proinflammatory serum chemokines. Severe disease in transplant recipients, however, is characterized by a less robust induction of pro-inflammatory genes and chemokines. Together, our study reveals distinct immune features and altered viral dynamics in solid organ transplant recipients.

Aim: A radio-pathomic machine learning (ML) model has been developed to estimate tumor cell density, cytoplasm density (Cyt) and extracellular fluid density (ECF) from multimodal MR images and autopsy pathology. In this multicenter study, we implemented this model to test its ability to predict survival in patients with recurrent glioblastoma (rGBM) treated with chemotherapy.Methods: Pre- and post-contrast T1-weighted, FLAIR and ADC images were used to generate radio-pathomic maps for 51 patients with longitudinal pre- and post-treatment scans. Univariate and multivariate Cox regression analyses were used to test the influence of contrast-enhancing tumor volume, total cellularity, mean Cyt and mean ECF at baseline, immediately post-treatment and the pre- and post-treatment rate of change in volume and cellularity on overall survival (OS).Results: Smaller Cyt and larger ECF after treatment were significant predictors of OS, independent of tumor volume and other clinical prognostic factors (HR = 3.23 × 10-6, p

A search for heavy right-handed Majorana neutrinos is performed with the ATLAS detector at the CERN Large Hadron Collider, using the 140  fb−1 of proton–proton collision data at s=13  TeV collected during Run 2. This search targets tt¯ production, in which both top quarks decay into a bottom quark and a W boson, where one of the W bosons decays hadronically and the other decays into an electron or muon and a heavy neutral lepton. The heavy neutral lepton is identified through a decay into an electron or muon and another W boson, resulting in a pair of same-charge same-flavor leptons in the final state. This paper presents the first search for heavy neutral leptons in the mass range of 15–75 GeV using tt¯ events. No significant excess is observed over the background expectation, and upper limits are placed on the signal cross sections. Assuming a benchmark scenario of the phenomenological type-I seesaw model, these cross section limits are then translated into upper limits on the mixing parameters of the heavy Majorana neutrino with Standard Model neutrinos. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Immunoglobulin (Ig) A supports mucosal immune homeostasis and host-microbiota interactions. While commensal bacteria are known for their ability to promote IgA, the role of non-bacterial commensal microbes in the induction of IgA remains elusive. Here, we demonstrate that permanent colonization with the protozoan commensal Tritrichomonas musculis (T.mu) promotes T cell-dependent, IgA class-switch recombination, and intestinal accumulation of IgA-secreting plasma cells (PC). T.mu colonization specifically drives the expansion of T follicular helper cells and a unique ICOS+ non-Tfh cell population, accompanied by an increase in germinal center B cells. Blockade of ICOS:ICOSL co-stimulation or MHCII-expression on B cells is central for the induction of IgA following colonization by T.mu, implicating a previously underappreciated mode of IgA induction following protozoan commensal colonization. Finally, T.mu further improves the induction of IgA-secreting PC specific to orally ingested antigens and their peripheral dissemination, identifying T.mu as a natural adjuvant for IgA. Collectively, these findings propose a protozoa-driven mode of IgA induction to support intestinal immune homeostasis.

Climate change is shifting the timing of organismal life-history events. Although consequential food-web mismatches can emerge if predators and prey shift at different rates, research on phenological shifts has traditionally focused on single trophic levels. Here, we analysed >2000 long-term, monthly time series of phytoplankton, zooplankton, and fish abundance or biomass for the San Francisco, Chesapeake, and Massachusetts bays. Phenological shifts occurred in over a quarter (28%) of the combined series across all three estuaries. However, phenological trends for many taxa (ca. 29-68%) did not track the changing environment. While planktonic taxa largely advanced their phenologies, fishes displayed broad patterns of both advanced and delayed timing of peak abundance. Overall, these divergent patterns illustrate the potential for climate-driven trophic mismatches. Our results suggest that even if signatures of global climate change differ locally, widespread phenological change has the potential to disrupt estuarine food webs.

BACKGROUND: Peak-width of skeletonized mean diffusivity (PSMD), a neuroimaging marker of cerebral small vessel disease (SVD), has shown excellent instrumental properties. Here, we extend our work to perform a biological validation of PSMD. METHODS: We included 396 participants from the Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID-1) Consortium and three replication samples (Cohorts for Heart and Aging Research in Genomic Epidemiology = 6172, Rush University Medical Center = 287, University of California Davis Alzheimers Disease Research Center = 567). PSMD was derived from diffusion tensor imaging using an automated algorithm. We related PSMD to a composite measure of general cognitive function using linear regression models adjusting for confounders. RESULTS: Higher PSMD was associated with lower general cognition in MarkVCID-1 independent of age, sex, education, and intracranial volume (Beta [95% confidence interval], -0.8 [-1.2, -0.4], P

PurposeThis study compared the classification performance of normalized apparent diffusion coefficient (nADC) with percentage T2-FLAIR mismatch-volume (%T2FM-volume) for differentiating between IDH-mutant astrocytoma (IDHm-A) and other glioma molecular subtypes.MethodsA total of 105 non-enhancing gliomas were studied. T2-FLAIR digital subtraction maps were used to identify T2FM and T2-FLAIR non-mismatch (T2FNM) subregions within tumor volumes of interest (VOIs). Median nADC from the whole tumor, T2FM, and T2NFM subregions and %T2FM-volume were obtained. IDHm-A classification analyses using receiver-operating characteristic curves and multiple logistic regression were performed in addition to exploratory survival analyses.ResultsT2FM subregions had significantly higher nADC than T2FNM subregions within IDHm-A with ≥ 25% T2FM-volume (P

This paper introduces a methodology designed to augment the inverse design optimization process in scenarios constrained by limited compute, through the strategic synergy of multi-fidelity evaluations, machine learning models, and optimization algorithms. The proposed methodology is analyzed on two distinct engineering inverse design problems: airfoil inverse design and the scalar field reconstruction problem. It leverages a machine learning model trained with low-fidelity simulation data, in each optimization cycle, thereby proficiently predicting a target variable and discerning whether a high-fidelity simulation is necessitated, which notably conserves computational resources. Additionally, the machine learning model is strategically deployed prior to optimization to compress the design space boundaries, thereby further accelerating convergence toward the optimal solution. The methodology has been employed to enhance two optimization algorithms, namely Differential Evolution and Particle Swarm Optimization. Comparative analyses illustrate performance improvements across both algorithms. Notably, this method is adaptable across any inverse design application, facilitating a synergy between a representative low-fidelity ML model, and high-fidelity simulation, and can be seamlessly applied across any variety of population-based optimization algorithms.

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure (ES) methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green’s function based many-body perturbation theory, wave-function based and stochastic ES approaches, relativistic effects and semiempirical ES theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the ES, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for ES based modeling from the vantage point of industry environments. Overall, the field of ES software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

This meta-analysis examined 12 empirical studies, published from 2013 to 2023, to determine the effectiveness of DBL in enhancing scientific creativity. The sample size involved 1211 students. Based on the analysis using random-effect model, DBL has a positive and strong significant effect (ES=1.181) to scientific creativity. Moderator analysis uncovered significant difference in the effect sizes when clustered according to the academic level and geographic location, while the STEM discipline and the implementation period demonstrated otherwise. It is further revealed that engineering design (g=1.546) registered the largest effect size in comparison with design thinking (g=0.896) and STEAM design (g=0.696) models. Moreover, originality, elaboration, fluency, and flexibility are the most frequently used dimensions in assessing scientific creativity. In conclusion, the findings established the effectiveness of DBL in enhancing scientific creativity among STEM students. Hence, teachers must be equipped of the technical knowhow of integrating design process in teaching STEM subjects.

Stemming from the research "The Fourth Impulse of Pedagogical Renewal in Spain", this article addresses three key issues: firstly, and as a terminological exercise, it differentiates three concepts that are too often treated interchangeably. These are: reform, renewal and innovation. Secondly, some of the defining aspects that, in our view, characterise centres of pedagogical renewal are presented. Thirdly, some of the peculiarities of pedagogical renewal today (what we agree to call the "third impulse of pedagogical renewal") are presented. The article closes with some conclusions which, apart from highlighting the main aspects of the article, place topics on the table for further debate.

In the realm of agricultural development, the pursuit of sustainability stands as a paramount objective, necessitating an integration of multifaceted expertise from diverse disciplines. Amidst this pursuit, understanding the perspectives of professionals in both the realms of economy and biology becomes imperative, serving as a cornerstone for innovative strategies. This study examines the viewpoints of economy and biology professionals on multidisciplinary innovations for sustainable agricultural development. Through qualitative analysis of interviews and focus groups, the research identifies key themes and challenges. Participants recognise the need for integrating diverse disciplines to address agricultural sustainability, emphasising the importance of economic viability and technological innovation. However, barriers such as high costs and limited access to resources hinder widespread adoption. Policy recommendations include incentivising sustainable practices and fostering collaboration between stakeholders. The results underscore the significance of multidisciplinary approaches in advancing sustainable agriculture, with implications for policy and practice.

The purpose of this exploratory research study was to examine the roles instructional designers (IDs) play in the integration of generative Artificial Intelligence (GenAI) into their higher education institutions, and how they use GenAI technologies in their own professional practices. Data were collected from 15 participants in the United States (U.S.) in an ID role or with similar job titles (e.g., educational technologist). Using a general qualitative approach, semi-structured interviews were conducted in Zoom about IDs' use and integration of GenAI. Our analysis resulted in three primary themes related to IDs' integration of GenAI in online and blended education: (a) the use of GenAI for instructional design; (b) collaborative guidance for faculty integration of GenAI; and (c) training, resources, and guidelines on the integration of GenAI. A common thread through all the themes was IDs' conscientious and cautious approach and ethical concerns about GenAI integration. We unpack these themes and discuss the implications of IDs in higher education integrating GenAI to meet organizational, faculty, and student needs.

Literary discussions are widely utilized in education, yet their profound impact on students' comprehension requires in-depth exploration. This paper delves into the influence of literary discussions on student comprehension and examines how these discussions can enhance students' understanding and analytical skills. Through literature reviews and case analyses, this study investigates teaching strategies, student engagement levels, classroom ambiance, and other factors involved in literary discussions, revealing the potential mechanisms through which literary discussions influence student comprehension. The paper explores variations in the application of literary discussions across different types of literary works (novels, poetry, drama, etc.) and their relationship with students' creative thinking. Finally, the paper provides recommendations to assist educators in effectively utilizing literary discussions to enhance students' comprehension skills. Students must have the opportunity to discuss literature in ways that provoke deep thought and meaning from each work they encounter. Therefore, English Language Arts teachers and instructors must be creative in finding unique ways in which they encourage their students to experience and respond to literature. This paper discusses a variety of strategies to implement in virtual and in-person classrooms, such as Socratic seminar, Teacher-led as a facilitator, Teacher-led as a promoter of diverse perspectives, Using student-generated discussion questions whole class, Using student-generated discussion questions in small groups, Using Close-ended questions, Using Open-ended questions, Inquiry-based, Making real-world connections to the literature, Literature Circles. These literary discussion strategies can be used for both fiction and nonfiction literature.

Bichronous online learning is the intentional blending of asynchronous and synchronous online learning experiences. Twelve award-winning online instructors participated in interviews to discuss best practices they use, and benefits and challenges in bichronous online courses. When sharing best practices for bichronous online courses, online instructors explained how they combined best practices in asynchronous and synchronous online learning. Asynchronous online best practices included course design and structure, resources, and instructor presence; and synchronous online best practices focused on formats, activities, and content of synchronous sessions, and community-building. The best practices, benefits and challenges discussed in this paper have implications for instructors who currently teach in a bichronous online format or may be considering it in the future, and for instructional designers and administrators who work with faculty on offering courses in this modality. Based on the data, the intentional blending of synchronous and asynchronous components has a lot of potential to enhance students' online learning experiences.

This study aims to equip students with conceptual modeling skills to address compelling 21st-century challenges in chemistry and chemical engineering education. System-based concept mapping is a critical competence for analyzing global, often complex, problems. We examined how conceptual modeling could scaffold practical experimental design, transitioning from problem identification to testable hypotheses. We set up a project in which first-year undergraduates in chemical engineering work in groups of 5-6 students. Their task was to develop concrete hypotheses for assignments that center on finding sustainable solutions for polluted environments. A set of educational roles (i.e., lecturers, tutors, learning assistants, educational specialist, and project coordinator) were implemented to ensure that students could accomplish their main learning outcome; that is, to become familiar with the academic way of thinking and apply critical thinking skills as a team. Interviews were conducted after the project was finished and revealed that, while conceptual modeling helped students to structure their ideas (i.e., to learn how to design research questions, incorporate interventions, and test models), developing hypotheses remains a challenging task. Our findings brought us to the recommendations for teaching conceptual modeling in the curriculum rather than at the project level, allowing students to progressively transition from understanding and applying concept mapping in their first year into creating solutions within the context of solving complex real-world problems in the final year of their bachelor's degree. The collaborative learning environment and project format employed in this work could spark new ways to teach science that facilitates systems thinking in chemistry.

Children's religious education is vital for the formation of pupils in Dutch Orthodox Protestant schools. Therefore, it seems self-evident that parents and teachers cooperate. This article presents research on parents' and teachers' opinions about the helpfulness of cooperative practices in religious education. A total of 1346 parents and teachers completed questionnaires developed from a previous study. This article finds that parents and teachers cherish the ideal of 'coherence between school and family' although differences between the respondent groups and school types occurred. Moreover, the research shows that this ideal influences the valuing of cooperative practices of religious education.

The recent complexity of the university system, with diverse academic trajectories and varying socio-demographic characteristics of students, has led to increased access for historically underrepresented students. This has resulted in a rising number of adult learners, students with external responsibilities and individuals returning to education. However, despite this enhanced access, it remains unclear whether it has improved graduation. This uncertainty stems from the fact that students' social circumstances and external responsibilities differ significantly based on when they enter university. From a life course perspective, the aim of this paper is to explore the interactive effects of age at university entrance and employment status on the probability of graduating of an entire cohort of new students who entered the Catalan Higher Education System in 2012 (N = 29,463). The results show an interaction effect between age and employment status on the probability of graduation where working decreases the probability of graduation among students younger than 42 years old. Conversely, the negative impact of employment on university graduation diminishes among students entering university at an older age. This underscores the importance of adopting a life course perspective to comprehend students' educational experiences and outcomes within higher education.

Contribution: This study explores industry members' perceptions about the ABET-based accreditation in a developing country, using the case study of a program in a publicly funded polytechnic university in Ecuador. Background: Engineering programs often seek international accreditations to enhance the education quality, align with the global standards or gain academic reputation. ABET-based accreditation originates in United States, and thus presents some challenges for institutions in developing countries. Intended Outcomes: This study aimed to investigate the significance of international academic accreditation, as seen through the perspective of industry members. It focused on identifying fundamental competencies valued by employers and aimed to provide insights for institutions in similar contexts. Application Design: The research employed an approach informed by a qualitative methodology, involving in-depth interviews with five industry members who had served on the advisory committee board of an engineering program from a higher education institution in Ecuador. Findings: The findings identified three main areas of competencies that the industry members value: communication skills for teamwork, a problem-solving orientation, and an ability for effective task planning. The study also showed that these industry members value international accreditation as a means for enhancing education quality and ensuring graduates develop the necessary skills and competencies, yet the overall awareness with their peers remains relatively low.

The purpose of this research study was to examine the overall effect of adaptive learning systems deployed using artificial intelligence technology across a range of relevant variables (e.g., duration, student level, etc.). Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45 independent studies utilizing AI-enabled adaptive learning. This meta-analysis examined the overall effect of AI-enabled adaptive learning systems on students' cognitive learning outcomes when compared with non-adaptive learning interventions and found that they have a medium to large positive effect size (g = 0.70). The effect was significantly moderated by publication type, origin of study, student classification level, student discipline, duration, and research design. In addition, all three adaptive sources (cognitive, affective, and behavioral) and adaptive targets (navigation and assessment) were significant moderators. The type of AI used in the adaptive engine did not moderate the effects. Implications for both practice and research are provided.

There has been little attention to personality in research on school refusal (SR). This study examined personality traits among 41 adolescents receiving cognitive-behavioral therapy (CBT) during participation in a School Refusal Program in the Netherlands. Traits were examined via clinical scales and 2-point code types derived from the Minnesota Multiphasic Personality Inventory--Adolescent. The influence of personality traits on treatment outcome was examined at post-treatment and 1-year follow-up. At pretreatment, eight of the 10 clinical scales were disproportionately skewed toward the "high to very high" range relative to a norm group. Social introversion and depressive symptomatology were significantly increased relative to the norm group, and nearly one-half of the adolescents were characterized by code type 2-3/3-2 (depression/hysteria) or 2-0/0-2 (depression/social introversion). Adolescents characterized by a 2-0/0-2 code type were almost twice as likely (odds ratio = 1.78) to be treatment responders at post-treatment. There was no relation between personality traits and treatment outcome at follow-up. The small sample size limits generalization of the study's findings. If the results are replicated, personality traits may provide useful indications for personalizing treatment when employing interventions recommended in CBT manuals for SR.

AIMS: Sodium/glucose transporter 2 (SGLT2 or SLC5A2) inhibitors lower blood glucose and are also approved treatments for heart failure independent of raised glucose. Various studies have showed that SGLT2 inhibitors relax arteries, but the underlying mechanisms are poorly understood and responses variable across arterial beds. We speculated that SGLT2 inhibitor-mediated arterial relaxation is dependent upon calcitonin gene-related peptide (CGRP) released from sensory nerves independent of glucose transport. METHODS AND RESULTS: The functional effects of SGLT1 and 2 inhibitors (mizagliflozin, dapagliflozin, and empagliflozin) and the sodium/hydrogen exchanger 1 (NHE1) blocker cariporide were determined on pre-contracted resistance arteries (mesenteric and cardiac septal arteries) as well as main renal conduit arteries from male Wistar rats using wire myography. SGLT2, CGRP, TRPV1, and NHE1 expression was determined by western blot and immunohistochemistry. Kv7.4/5/KCNE4 and TRPV1 currents were measured in the presence and absence of dapagliflozin and empagliflozin. All SGLT inhibitors (1-100 µM) and cariporide (30 µM) relaxed mesenteric arteries but had negligible effect on renal or septal arteries. Immunohistochemistry with TRPV1 and CGRP antibodies revealed a dense innervation of sensory nerves in mesenteric arteries that were absent in renal and septal arteries. Consistent with a greater sensory nerve component, the TRPV1 agonist capsaicin relaxed mesenteric arteries more effectively than renal or septal arteries. In mesenteric arteries, relaxations to dapagliflozin, empagliflozin, and cariporide were attenuated by the CGRP receptor antagonist BIBN-4096, depletion of sensory nerves with capsaicin, and blockade of TRPV1 or Kv7 channels. Neither dapagliflozin nor empagliflozin activated heterologously expressed TRPV1 channels or Kv7 channels directly. Sensory nerves also expressed NHE1 but not SGLT2 and cariporide pre-application as well as knockdown of NHE1 by translation stop morpholinos prevented the relaxant response to SGLT2 inhibitors. CONCLUSION: SGLT2 inhibitors relax mesenteric arteries by promoting the release of CGRP from sensory nerves in a NHE1-dependent manner.

BackgroundOral pre-exposure prophylaxis (PrEP) with emtricitabine/tenofovir disoproxil fumarate (F/TDF) has high efficacy against HIV-1 acquisition. Seventy-two prospective studies of daily oral F/TDF PrEP were conducted to evaluate HIV-1 incidence, drug resistance, adherence, and bone and renal safety in diverse settings.MethodsHIV-1 incidence was calculated from incident HIV-1 diagnoses after PrEP initiation and within 60 days of discontinuation. Tenofovir concentrations in dried blood spots (DBS), drug resistance, and bone/renal safety indicators were evaluated in a subset of studies.ResultsAmong 17 274 participants, there were 101 cases with new HIV-1 diagnosis (.77 per 100 person-years; 95% confidence interval [CI]: .63-.94). In 78 cases with resistance data, 18 (23%) had M184I or V, 1 (1.3%) had K65R, and 3 (3.8%) had both mutations. In 54 cases with tenofovir concentration data from DBS, 45 (83.3%), 2 (3.7%), 6 (11.1%), and 1 (1.9%) had average adherence of

To combat the rise of antibiotic-resistance in bacteria and the resulting effects on healthcare worldwide, new technologies are needed that can perform rapid antibiotic susceptibility testing (AST). Conventional clinical methods for AST rely on growth-based assays, which typically require long incubation times to obtain quantitative results, representing a major bottleneck in the determination of the optimal antibiotic regimen to treat patients. Here, we demonstrate a rapid AST method based on the metabolic activity measured by fluorescence lifetime imaging microscopy (FLIM). Using lab strains and clinical isolates of Escherichia coli with tetracycline-susceptible and resistant phenotypes as models, we demonstrate that changes in metabolic state associated with antibiotic susceptibility can be quantitatively tracked by FLIM. Our results show that the magnitude of metabolic perturbation resulting from antibiotic activity correlates with susceptibility evaluated by conventional metrics. Moreover, susceptible and resistant phenotypes can be differentiated in as short as 10 min after antibiotic exposure. This FLIM-AST (FAST) method can be applied to other antibiotics and provides insights into the nature of metabolic perturbations inside bacterial cells resulting from antibiotic exposure with single cell resolution.

BACKGROUND AND AIMS: The role of biomarker testing in the management of obstructive hypertrophic cardiomyopathy is not well defined. This pre-specified analysis of SEQUOIA-HCM (NCT05186818) sought to define the associations between clinical characteristics and baseline concentrations of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin I (hs-cTnI), and to evaluate the effect of treatment with aficamten on biomarker concentrations. METHODS: Cardiac biomarkers were measured at baseline and serially throughout the study. Regression analyses determined predictors of baseline NT-proBNP and hs-cTnI concentrations, and evaluated whether early changes in these biomarkers relate to later changes in left ventricular outflow tract gradient (LVOT-G), other echocardiographic measures, health status, and functional capacity. RESULTS: Baseline concentration of NT-proBNP was associated with LVOT-G and measures of diastolic function, while hs-cTnI was associated with left ventricular thickness. Within 8 weeks of treatment with aficamten, NT-proBNP was reduced by 79% (95% confidence interval 76%-83%, P < .001) and hs-cTnI by 41% (95% confidence interval 32%-49%, P < .001); both biomarkers reverted to baseline after washout. Reductions in NT-proBNP and hs-cTnI by 24 weeks were strongly associated with a lowering of LVOT-G, improvement in health status, and increased peak oxygen uptake. N-Terminal pro-B-type natriuretic peptide reduction strongly correlated with the majority of improvements in exercise capacity. Furthermore, the change in NT-proBNP by Week 2 was associated with the 24-week change in key endpoints. CONCLUSIONS: N-Terminal pro-B-type natriuretic peptide and hs-cTnI concentrations are associated with key variables in obstructive hypertrophic cardiomyopathy. Serial measurement of NT-proBNP and hs-cTnI appears to reflect clinical response to aficamten therapy.

Spinocerebellar ataxia type 7 (SCA7) is a genetic neurodegenerative disorder caused by a CAG-polyglutamine repeat expansion. Purkinje cells (PCs) are central to the pathology of ataxias, but their low abundance in the cerebellum underrepresents their transcriptomes in sequencing assays. To address this issue, we developed a PC enrichment protocol and sequenced individual nuclei from mice and patients with SCA7. Single-nucleus RNA sequencing in SCA7-266Q mice revealed dysregulation of cell identity genes affecting glia and PCs. Specifically, genes marking zebrin-II PC subtypes accounted for the highest proportion of DEGs in symptomatic SCA7-266Q mice. These transcriptomic changes in SCA7-266Q mice were associated with increased numbers of inhibitory synapses as quantified by immunohistochemistry and reduced spiking of PCs in acute brain slices. Dysregulation of zebrin-II cell subtypes was the predominant signal in PCs of SCA7-266Q mice and was associated with the loss of zebrin-II striping in the cerebellum at motor symptom onset. We furthermore demonstrated zebrin-II stripe degradation in additional mouse models of polyglutamine ataxia and observed decreased zebrin-II expression in the cerebella of patients with SCA7. Our results suggest that a breakdown of zebrin subtype regulation is a shared pathological feature of polyglutamine ataxias.

BACKGROUND: Weight stigma is a fundamental cause of health inequality. Body positivity may be a counterbalance to weight stigma. Social media is replete with weight-stigmatizing content and is a driver of poor mental health outcomes; however, there remains a gap in understanding its potential to mitigate the prevalence and impact of harmful messaging and to promote positive effects on a large scale. OBJECTIVE: We selected musical artist Lizzo, whose brand emphasizes body positivity and empowerment, for an instrumental case study on the discourse on social media and specifically Instagram. We focused on 3 domains, including body positivity, physical health, and emotional well-being. These domains challenge social norms around weight and body size and have the potential to positively affect the physical and psychological health of people with diverse body sizes. METHODS: We evaluated posts by Lizzo, comments from Instagram users, and replies to comments over a 2-month period (October 11 to December 12, 2019). Two coders rated Lizzos posts and Instagram users comments for their sentiments on the 3 domains. Replies to Instagram users comments were assessed for their reactions to comments (ie, did they oppose or argue against the comment or did they support or bolster the comment). Engagement metrics, including the number of likes, were also collected. RESULTS: The final sample included 50 original posts by Lizzo, 250 comments from Instagram users, and 1099 replies to comments. A proportion of Lizzos content included body positive sentiments (34%) and emotional well-being (18%); no posts dealt explicitly with physical health. A substantial amount Instagram users comments and replies contained stigmatizing content including the use of nauseated and vomiting emojis, implications that Lizzos body was shameful and should be hidden away, accusations that she was promoting obesity, and impeachments of Lizzos health. In spite of the stigmatizing content, we also discovered content highlighting the beneficial nature of having positive representation of a Black woman living in a larger body who is thriving. Moreover, analysis of the discourse between users illustrated that stigmatizing expressions are being combated online, at least to some degree. CONCLUSIONS: This study demonstrates that Lizzo has exposed millions of social media users to messages about body positivity and provided more visibility for conversations about weight and shape. Future research should examine the extent to which body positive messages can lead to greater acceptance of individuals living in larger bodies. Instagram and other social media platforms should consider ways to reduce body-shaming content while finding ways to promote content that features diverse bodies. Shifting the landscape of social media could decrease stereotypes about weight and shape while increasing dialog about the need for greater acceptance and inclusion of people with diverse bodies.

Stress granules (SGs) are macromolecular assemblies that form under cellular stress. Formation of these membraneless organelles is driven by the condensation of RNA and RNA-binding proteins such as G3BPs. G3BPs form SGs following stress-induced translational arrest. Three G3BP paralogues (G3BP1, G3BP2A, and G3BP2B) have been identified in vertebrates. However, the contribution of different G3BP paralogues to SG formation and gene expression changes is incompletely understood. Here, we probed the functions of G3BPs by identifying important residues for SG assembly at their N-terminal domain such as V11. This conserved amino acid is required for formation of the G3BP-Caprin-1 complex, hence promoting SG assembly. Total RNA sequencing and ribosome profiling revealed that a G3BPV11A mutant leads to changes in mRNA levels and ribosome engagement during the integrated stress response (ISR). Moreover, we found that G3BP2B preferentially forms SGs and promotes changes in mRNA expression under endoplasmic reticulum (ER) stress. Furthermore, our work is a resource for researchers to study gene expression changes under cellular stress. Together, this work suggests that perturbing protein-protein interactions mediated by G3BPs affect SG assembly and gene expression during the ISR, and such functions are differentially regulated by G3BP paralogues under ER stress.

A search is presented for direct pair production of the stop, the supersymmetric partner of the top quark, in a decay through an R-parity violating coupling to a charged lepton and a b-quark. The dataset corresponds to an integrated luminosity of 140  fb−1 of proton-proton collisions at a center-of-mass energy of s=13  TeV collected between 2015 and 2018 by the ATLAS detector at the LHC. The final state has two charged leptons (electrons or muons) and two b-jets. The results of the search are interpreted in the context of a Minimal Supersymmetric Standard Model with an additional B−L gauge symmetry that is spontaneously broken. No significant excess is observed over the Standard Model background, and exclusion limits on stop pair production are set at 95% confidence level. The corresponding lower limits on the stop mass for 100% branching ratios to a b-quark and an electron, muon, or tau-lepton are 1.9 TeV, 1.8 TeV and 800 GeV, respectively, extending the reach of previous LHC searches. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Amphibians represent a diverse group of tetrapods, marked by deep divergence times between their three systematic orders and families. Studying amphibian biology through the genomics lens increases our understanding of the features of this animal class and that of other terrestrial vertebrates. The need for amphibian genomic resources is more urgent than ever due to the increasing threats to this group. Amphibians are one of the most imperiled taxonomic groups, with approximately 41% of species threatened with extinction due to habitat loss, changes in land use patterns, disease, climate change, and their synergistic effects. Amphibian genomic resources have provided a better understanding of ontogenetic diversity, tissue regeneration, diverse life history and reproductive modes, anti-predator strategies, and resilience and adaptive responses. They also serve as essential models for studying broad genomic traits, such as evolutionary genome expansions and contractions, as they exhibit the widest range of genome sizes among all animal taxa and possess multiple mechanisms of genetic sex determination. Despite these features, genome sequencing of amphibians has significantly lagged behind that of other vertebrates, primarily due to the challenges of assembling their large, repeat-rich genomes and the relative lack of societal support. The emergence of long-read sequencing technologies, combined with advanced molecular and computational techniques that improve scaffolding and reduce computational workloads, is now making it possible to address some of these challenges. To promote and accelerate the production and use of amphibian genomics research through international coordination and collaboration, we launched the Amphibian Genomics Consortium (AGC, https://mvs.unimelb.edu.au/amphibian-genomics-consortium ) in early 2023. This burgeoning community already has more than 282 members from 41 countries. The AGC aims to leverage the diverse capabilities of its members to advance genomic resources for amphibians and bridge the implementation gap between biologists, bioinformaticians, and conservation practitioners. Here we evaluate the state of the field of amphibian genomics, highlight previous studies, present challenges to overcome, and call on the research and conservation communities to unite as part of the AGC to enable amphibian genomics research to leap to the next level.

BACKGROUND AND OBJECTIVES: Idiopathic/isolated REM sleep behavior disorder (iRBD) has been strongly linked to neurodegenerative synucleinopathies such as Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. However, there have been increasing reports of RBD as a presenting feature of serious and treatable autoimmune syndromes, particularly IGLON5. This studys objective was to investigate the frequency of autoantibodies in a large cohort of participants with iRBD. METHODS: Participants were enrolled in the North American Prodromal Synucleinopathy cohort with polysomnography-confirmed iRBD, free of parkinsonism and dementia. Plasma samples were systematically screened for the autoantibodies IGLON5, DPPX, LGI1, and CASPR2 using plasma IgG cell-based assay. Positive or equivocal results were confirmed by repeat testing, plus tissue-based indirect immunofluorescence assay for IGLON5. RESULTS: Of 339 samples analyzed, 3 participants (0.9%) had confirmed positive IGLON5 autoantibodies in the cell-based assay, which were confirmed by the tissue-based assay. An additional participant was positive for CASPR2 with low titer by cell-based assay only (of lower clinical certainty). These cases exhibited a variety of symptoms including dream enactment, cognitive decline, autonomic dysfunction, and motor symptoms. In 1 IGLON5 case and the CASPR2 case, evolution was suggestive of typical synucleinopathy, suggesting the possibility that findings were incidental. However, 2 participants with IGLON5 died before diagnosis was clinically suspected, with a final clinical picture highly suggestive of autoimmune disease. DISCUSSION: Our finding that nearly 1% of a large iRBD cohort may have a serious but potentially treatable autoantibody syndrome has important clinical implications. In particular, it raises the question of whether autoantibody testing for IGLON-5-IgG should be widely implemented for participants with iRBD, considering the difficulty in diagnosis of autoimmune diseases, their response to treatment, and the potential for rapid disease progression. However, any routine testing protocol will also have to consider costs and potential adverse effects of false-positive findings. TRIAL REGISTRATION INFORMATION: NCT03623672.

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

A search for long-lived particles (LLPs) using 140  fb^{-1} of pp collision data with sqrt[s]=13  TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark.

A search for the exclusive hadronic decays W^{±}→π^{±}γ, W^{±}→K^{±}γ, and W^{±}→ρ^{±}γ is performed using up to 140  fb^{-1} of proton-proton collisions recorded with the ATLAS detector at a center-of-mass energy of sqrt[s]=13  TeV. If observed, these rare processes would provide a unique test bench for the quantum chromodynamics factorization formalism used to calculate cross sections at colliders. Additionally, at future colliders, these decays could offer a new way to measure the W boson mass through fully reconstructed decay products. The search results in the most stringent upper limits to date on the branching fractions B(W^{±}→π^{±}γ)

Explainability of convolutional neural networks (CNNs) is integral for their adoption into radiological practice. Commonly used attribution methods localize image areas important for CNN prediction but do not characterize relevant imaging features underlying these areas, acting as a barrier to the adoption of CNNs for clinical use. We therefore propose Semantic Exploration and Explainability using a Style-based Generative Adversarial Autoencoder Network (SEE-GAAN), an explainability framework that uses latent space manipulation to generate a sequence of synthetic images that semantically visualizes how clinical and CNN features manifest within medical images. Visual analysis of changes in these sequences then facilitates the interpretation of features, thereby improving explainability. SEE-GAAN was first developed on a cohort of 26,664 chest radiographs across 15,409 patients from our institution. SEE-GAAN sequences were then generated across several clinical features and CNN predictions of NT-pro B-type natriuretic peptide (BNPP) as a proxy for acute heart failure. Radiological interpretations indicated SEE-GAAN sequences captured relevant changes in anatomical and pathological morphology associated with clinical and CNN predictions and clarified ambiguous areas highlighted by commonly used attribution methods. Our study demonstrates SEE-GAAN can facilitate our understanding of clinical features for imaging biomarker exploration and improve CNN transparency over commonly used explainability methods.

Mononuclear phagocytes facilitate the dissemination of the obligate intracellular parasite Toxoplasma gondii. Here, we report how a set of secreted parasite effector proteins from dense granule organelles (GRA) orchestrates dendritic cell-like chemotactic and pro-inflammatory activation of parasitized macrophages. These effects enabled efficient dissemination of the type II T. gondii lineage, a highly prevalent genotype in humans. We identify novel functions for effectors GRA15 and GRA24 in promoting CCR7-mediated macrophage chemotaxis by acting on NF-κB and p38 mitogen-activated protein kinase signaling pathways, respectively, with contributions by GRA16/18 and counter-regulation by effector TEEGR. Furthermore, GRA28 boosted chromatin accessibility and GRA15/24/NF-κB-dependent transcription at the Ccr7 gene locus in primary macrophages. In vivo, adoptively transferred macrophages infected with wild-type T. gondii outcompeted macrophages infected with a GRA15/24 double mutant in migrating to secondary organs in mice. The data show that T. gondii, rather than being passively shuttled, actively promotes its dissemination by inducing a finely regulated pro-migratory state in parasitized human and murine phagocytes via co-operating polymorphic GRA effectors.ImportanceIntracellular pathogens can hijack the cellular functions of infected host cells to their advantage, for example, for intracellular survival and dissemination. However, how microbes orchestrate the hijacking of complex cellular processes, such as host cell migration, remains poorly understood. As such, the common parasite Toxoplasma gondii actively invades the immune cells of humans and other vertebrates and modifies their migratory properties. Here, we show that the concerted action of a number of secreted effector proteins from the parasite, principally GRA15 and GRA24, acts on host cell signaling pathways to activate chemotaxis. Furthermore, the protein effector GRA28 selectively acted on chromatin accessibility in the host cell nucleus to selectively boost host gene expression. The joint activities of GRA effectors culminated in pro-migratory signaling within the infected phagocyte. We provide a molecular framework delineating how T. gondii can orchestrate a complex biological phenotype, such as the migratory activation of phagocytes to boost dissemination.

PURPOSE: Current therapy strategies still provide only limited success in the treatment of glioblastoma, the most frequent primary brain tumor in adults. In addition to the characterization of the tumor microenvironment, global changes in the brain of patients with glioblastoma have been described. However, the impact and molecular signature of neuroinflammation distant of the primary tumor site have not yet been thoroughly elucidated. EXPERIMENTAL DESIGN: We performed translocator protein (TSPO)-PET in patients with newly diagnosed glioblastoma (n = 41), astrocytoma WHO grade 2 (n = 7), and healthy controls (n = 20) and compared TSPO-PET signals of the non-lesion (i.e., contralateral) hemisphere. Back-translation into syngeneic SB28 glioblastoma mice was used to characterize Pet alterations on a cellular level. Ultimately, multiplex gene expression analyses served to profile immune cells in remote brain. RESULTS: Our study revealed elevated TSPO-PET signals in contralateral hemispheres of patients with newly diagnosed glioblastoma compared to healthy controls. Contralateral TSPO was associated with persisting epileptic seizures and shorter overall survival independent of the tumor phenotype. Back-translation into syngeneic glioblastoma mice pinpointed myeloid cells as the predominant source of contralateral TSPO-PET signal increases and identified a complex immune signature characterized by myeloid cell activation and immunosuppression in distant brain regions. CONCLUSIONS: Neuroinflammation within the contralateral hemisphere can be detected with TSPO-PET imaging and associates with poor outcome in patients with newly diagnosed glioblastoma. The molecular signature of remote neuroinflammation promotes the evaluation of immunomodulatory strategies in patients with detrimental whole brain inflammation as reflected by high TSPO expression.

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is frequently characterized by chronic motor deficits. Therefore, this clinical trial assessed whether intracranial implantation of allogeneic modified mesenchymal stromal (SB623) cells can improve chronic motor deficits after TBI. METHODS: Post hoc analysis of the double-blind, randomized, prospective, surgical sham-controlled, phase 2, STEMTRA clinical trial (June 2016 and March 2019) with 48 weeks of follow-up was conducted. In this international, multicenter clinical trial, eligible participants had moderate-to-severe TBI, were ≥12 months postinjury, and had chronic motor deficits. Participants were randomized in a 1:1:1:1 ratio to stereotactic surgical intracranial implantation of SB623 cells (2.5 × 106, 5.0 × 106, 10 × 106) or surgical sham-controlled procedure. The prespecified primary efficacy end point was significantly greater change from baseline of the Fugl-Meyer Motor Scale (FMMS) score, a measure of motor status, for the SB623 pooled vs control arm at 24 weeks. RESULTS: A total of 211 participants were screened, 148 were excluded, and 63 underwent randomization, of which 61 (97%; mean age, 34 [SD, 12] years; 43 men [70.5%]) completed the trial. Single participants in the SB623 2.5 × 106 and 5.0 × 106 cell dose groups discontinued before surgery. Safety and efficacy (modified intent-to-treat) were assessed in participants who underwent surgery (N = 61; SB623 = 46, controls = 15). The primary efficacy end point (FMMS) was achieved (least squares mean [SE] SB623: +8.3 [1.4]; 95% CI 5.5-11.2 vs control: +2.3 [2.5]; 95% CI -2.7 to 7.3; p = 0.04), with faster improvement of the FMMS score in SB623-treated groups than in controls at 24 weeks and sustained improvement at 48 weeks. At 48 weeks, improvement of function and activities of daily living (ADL) was greater, but not significantly different in SB623-treated groups vs controls. The incidence of adverse events was equivalent in SB623-treated groups and controls. There were no deaths or withdrawals due to adverse events. DISCUSSION: Intraparenchymal implantation of SB623 cells was safe and significantly improved motor status at 24 weeks in participants with chronic motor deficits after TBI, with continued improvement of function and ADL at 48 weeks. Cell therapy can modify chronic neurologic deficits after TBI. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT02416492. Submitted to registry: April 15, 2015. First participant enrolled: July 6, 2016. Available at: classic.clinicaltrials.gov/ct2/show/NCT02416492. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that intracranial implantation of allogeneic stem (SB623) cells in adults with motor deficits from chronic TBI improves motor function at 24 weeks.