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Salt metathesis routes to five new -N(SiMe3)2 nickel derivatives were studied to illuminate their mode of formation, structures, and spectroscopy. The reaction between NiI2 and K{N(SiMe3)2} afforded the Ni(II) and Ni(I) complexes [K][Ni{N(SiMe3)2}3] (1) and [K][Ni{N(SiMe3)2}2] (2). Dissolving 1 in tetrahydrofuran (THF) gave the Ni(II) species [K(THF)2][Ni{N(SiMe3)2}3] (3). The Ni(I) salt [K(DME)][Ni2{N(SiMe3)2}3] (4) was obtained by using NiCl2(DME) (DME = 1,2-dimethoxyethane) as the nickel source rather than NiI2. The isolation of the Ni(I) complexes 2 and 4 highlights the tendency for K{N(SiMe3)2} to function as a reducing agent. Introduction of adventitious O2 to solutions of [K][Ni{N(SiMe3)2}2] (2) gave the nickel inverse crown ether (ICE) species [K2][O(Ni{N(SiMe3)2}2)2] (5). Complex 5 is the first ICE complex of nickel and is one of four known ICE complexes for the 3d metals. The experimental results indicate that the reduced Ni(I) bis(trimethylsilyl)amides are relatively easily generated, whereas Ni(III) derivatives that might be expected from a disproportionation of a Ni(II) derivative are apparently not yet isolable by the above routes. Overall, the new species crystallize readily from the reaction mixtures, but under ambient conditions, they begin to decompose as solids within ca. 24 h, which hinders their characterization.

Abstract Background Implementation strategies have predominantly been operationalized and studied in clinical settings. Implementation strategies are also needed to improve evidence-based intervention (EBI) integration in community settings, but there is a lack of systematic characterization of their use, which limits generalizability of findings. The goals of this study were to determine which implementation strategies are most used to deliver primary prevention EBIs in community settings, develop a compilation and pragmatic strategy selection process with accompanying guidance tools, and understand practitioners’ preferences for dissemination. Methods Purposive and snowball sampling was used to recruit community setting researchers and practitioners delivering primary prevention EBIs (nutrition, physical activity, tobacco prevention) in community settings: education, social services, city planning and transportation, workplaces, recreation/sport, faith-based, and other public health organizations. Semi-structured interviews were conducted using a guide based on the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework. Participants were asked to describe barriers experienced and strategies used to overcome them within each RE-AIM dimension. Practitioners were also asked about preferred dissemination strategies, prompted by Diffusion of Innovations theory concepts of sources (who provides information) and channels (how information is provided). A rapid deductive approach was used to analyze findings with a coding matrix aligned with the interview guide. Results Researchers (n = 10) and practitioners (n = 8) across all targeted settings and intervention outcomes completed interviews. Interviewees shared unique implementation strategies (N = 40) which were used to overcome barriers related to multiple RE-AIM dimensions, most commonly implementation (n = 29) and adoption (n = 27). Most frequently mentioned implementation strategies were conduct pragmatic evaluation (n = 31), provide training (n = 26), change adaptable program components (n = 26), and leverage funding sources (n = 21). Webinars (n = 6) and listservs/newsletters (n = 5) were the most mentioned dissemination channels; national public health organizations (n = 13) were the most mentioned sources. Conclusions Results reflect commonly used implementation strategies in community settings (e.g., training, technical assistance) and add novel strategies not reflected in current taxonomies. Dissemination preferences suggest the need to involve broad-reaching public health organizations. The resultant compilation (Implementation Strategies Applied in Communities) and strategy selection process provide resources to assist researchers and practitioners in applying strategies and improving EBI delivery in community settings.

Abstract Bats are becoming recognised as new model species to study naturally evolved mammalian extended healthspan and disease tolerance. However, this research is limited by the lack of bat specific cellular resources. Here we describe an optimised protocol to develop both primary and immortalised fibroblast cell-lines from wing biopsy punches from the Egyptian fruit bat, Rousettus aegyptiacus. We show that the immortalised cell lines and primary cells show similar characteristics in their proliferative capacity and response to oxidative stress. They also exhibited a similar response in their NF-κB immune response to TLR agonists including SARS-CoV2. As wing punches can be acquired non-lethally, these methods can be used to develop primary and immortalised cells, from potentially any bat species, including those of conservation concern that cannot be sacrificed. This can expand the scope of bat species that can be studied in the future, and the development of key cellular resources required to functionally validate the regulators of bats’ unique longevity.

Abstract Understanding regional sea level variations is crucial for assessing coastal vulnerability, with accurate sea level data playing a pivotal role. Utilizing historical sea level marigrams can enhance datasets, but current digitization techniques face challenges such as bends and skews in paper charts, impacting sea level values. This study explores often‐overlooked issues during marigram digitization, focusing on the case study of Dún Laoghaire in Ireland (1925–1931). The methodology involves digitizing the original marigram trace and underlying grid to assess offsets at the nearest ft (foot) interval on the paper chart, corresponding to changes in the water level trace for each hour interval. Subtracting the digitized value from the known value (the actual measurement) allows for the determination of differences, which are then subtracted from each hourly trace value. After adjusting for offsets ranging from −3.962 to 13.716 mm (millimetres), the study improves the final accuracy of sea level data to approximately the 10 mm level. Notably, data from 1926 and 1931 exhibit modest offsets (9–14 mm), emphasizing the importance of adjustments for accuracy. Such 10 mm accuracy is compatible with requirements of the Global Sea Level Observing System. Comparing the adjusted digitized data with other survey data shows similar amplitudes and phases for Dún Laoghaire in both the historical and modern datasets, and there is an overall mean sea level rise of 1.5 mm/year when combined with the available data from the Dublin region.

Cyber-wisdom is the ability to know and do the right thing at the right time, when using digital technologies, and is a concept that is gaining attention from educators. Whilst the theory and practice of cyber-wisdom education is established, to date there has been no attempt to investigate how the virtue of cyber-wisdom might be measured. This is a lacuna as it limits future research in the area, including, in particular, proximal evaluations of cyber-wisdom interventions. This article introduces a new four-component measure of cyber-wisdom, which is relevant to how the virtue may be cultivated in practice via formal education and the teaching of what is generally referred to as digital citizenship education. The measure was piloted with 1,331 13--16 year-olds. The findings provide initial evidence that cyber-wisdom literacy, reasoning, reflection, and motivation can be measured. This study provides preliminary validation of cyber-wisdom sub-measures that might be used in evaluations of educational interventions that seek to help children and adolescents live with wisdom in the digital age.

There is a dearth of studies exploring how younger children engage in civic life, what may be expected of them given their age, and what instruments may be used to capture their levels of civic engagement. Addressing these questions, this article presents key findings from a pilot study that aimed to create a validated instrument designed to measure the civic engagement of primary school children. Based on a survey administered to 655 primary school children aged 9-11 across England, this article focuses on the new measure that was specifically designed, and then tested and validated through both exploratory and confirmatory analyses. The findings validate a tripartite measure of civic engagement that assesses the civic attitudes, actions and awareness of 9-11-year-olds. This measure was found to be both practical and efficient in its administration, and it has been shown to be easily comprehensible by this age group. This new measure addresses an important gap in the literature on civic engagement in children, providing researchers with a validated tool to effectively measure civic engagement in 9-11-year-olds. The findings have implications for both researchers and educators interested in designing and evaluating interventions aimed at promoting civic engagement among younger children.

Over the past two decades, there has been an increased focus on designing STEM learning experiences for primary and second-level students. We posit that for teachers to design rich learning experiences for their students, they must first have the opportunity to develop their own STEM knowledge and competences, either during their pre-service teacher education or as part of their professional learning as in-service teachers. This systematic review of literature examines programmes which offer either pre-service or in-service teachers immersive learning experiences through placements in STEM roles in business or industry. A total of nine papers were identified in this review, featuring three unique programmes--one in the UK for pre-service teachers, and two in the USA involving in-service teachers. The findings indicate a variation in motivation and structures across the three programmes. The influence on teachers' personal and professional development, and their intentions to change their classroom practices or behaviours to incorporate more 'real-world' contexts into their STEM learning activities, inspired by their experiences in industry, is discussed. This study presents recommendations for the design and implementation of immersive learning placements in industry to support STEM teacher professional learning, as well as suggestions for further studies to examine the influence on their classroom practice.

Abstract Staphylococcus aureus is an important human commensal which persistently colonizes up to 30% of the human population, predominantly within the nasal cavity. The commensal lifestyle of S. aureus is complex, and the mechanisms underpinning colonization are not fully understood. S. aureus can induce an immunosuppressive environment in the nasal tissue (NT) by driving IL-10 and IL-27 to facilitate nasal colonization, indicating that S. aureus has the capacity to modulate the local immune environment for its commensal habitation. Mounting evidence suggests commensal bacteria drive type 1 interferons (IFN-I) to establish an immunosuppressive environment and whilst S. aureus can induce IFN-I during infection, its role in colonization has not yet been examined. Here, we show that S. aureus preferentially induces IFN signaling in macrophages. This IFN-I in turn upregulates expression of proapoptotic genes within macrophages culminating in caspase-3 cleavage. Importantly, S. aureus was found to drive phagocytic cell apoptosis in the nasal tissue during nasal colonization in an IFN-I dependent manner with colonization significantly reduced under caspase-3 inhibition. Overall, loss of IFN-I signaling significantly diminished S. aureus nasal colonization implicating a pivotal role for IFN-I in controlling S. aureus persistence during colonization through its ability to induce phagocyte apoptosis. Together, this study reveals a novel strategy utilized by S. aureus to circumvent host immunity in the nasal mucosa to facilitate nasal colonization.

Abstract Background Social network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, and dynamic processes. However, the accuracy of estimated metrics depends on data characteristics like sample proportion, sample size, and frequency. A protocol is needed to assess for bias and robustness of social network metrics estimated for the animal populations especially when a limited number of individuals are monitored. Methods We used GPS telemetry datasets of five ungulate species to combine known social network approaches with novel ones into a comprehensive five-step protocol. To quantify the bias and uncertainty in the network metrics obtained from a partial population, we presented novel statistical methods which are particularly suited for autocorrelated data, such as telemetry relocations. The protocol was validated using a sixth species, the fallow deer, with a known population size where $$\sim 85\%$$ ∼ 85 % of the individuals have been directly monitored. Results Through the protocol, we demonstrated how pre-network data permutations allow researchers to assess non-random aspects of interactions within a population. The protocol assesses bias in global network metrics, obtains confidence intervals, and quantifies uncertainty of global and node-level network metrics based on the number of nodes in the network. We found that global network metrics like density remained robust even with a lowered sample size, while local network metrics like eigenvector centrality were unreliable for four of the species. The fallow deer network showed low uncertainty and bias even at lower sampling proportions, indicating the importance of a thoroughly sampled population while demonstrating the accuracy of our evaluation methods for smaller samples. Conclusions The protocol allows researchers to analyse GPS-based radio-telemetry or other data to determine the reliability of social network metrics. The estimates enable the statistical comparison of networks under different conditions, such as analysing daily and seasonal changes in the density of a network. The methods can also guide methodological decisions in animal social network research, such as sampling design and allow more accurate ecological inferences from the available data. The R package aniSNA enables researchers to implement this workflow on their dataset, generating reliable inferences and guiding methodological decisions.

Abstract Gut microbiomes are widely hypothesised to influence host fitness and have been experimentally shown to affect host health and phenotypes under laboratory conditions. However, the extent to which they do so in free-living animal populations and the proximate mechanisms involved remain open questions. In this study, using long-term, individual-based life history and shallow shotgun metagenomic sequencing data (2394 fecal samples from 794 individuals collected between 2013–2019), we quantify relationships between gut microbiome variation and survival in a feral population of horses under natural food limitation (Sable Island, Canada), and test metagenome-derived predictions using short-chain fatty acid data. We report detailed evidence that variation in the gut microbiome is associated with a host fitness proxy in nature and outline hypotheses of pathogenesis and methanogenesis as key causal mechanisms which may underlie such patterns in feral horses, and perhaps, wild herbivores more generally.

Abstract In response to the COVID-19 pandemic, the American Board of Anesthesiology transitioned from in-person to virtual administration of its APPLIED Examination, assessing more than 3000 candidates for certification purposes remotely in 2021. Four hundred examiners were involved in delivering and scoring Standardized Oral Examinations (SOEs) and Objective Structured Clinical Examinations (OSCEs). More than 80% of candidates started their exams on time and stayed connected throughout the exam without any problems. Only 74 (2.5%) SOE and 45 (1.5%) OSCE candidates required rescheduling due to technical difficulties. Of those who experienced “significant issues”, concerns with OSCE technical stations (interpretation of monitors and interpretation of echocardiograms) were reported most frequently (6% of candidates). In contrast, 23% of examiners “sometimes” lost connectivity during their multiple exam sessions, on a continuum from minor inconvenience to inability to continue. 84% of SOE candidates and 89% of OSCE candidates described “smooth” interactions with examiners and standardized patients/standardized clinicians, respectively. However, only 71% of SOE candidates and 75% of OSCE candidates considered themselves to be able to demonstrate their knowledge and skills without obstacles. When compared with their in-person experiences, approximately 40% of SOE examiners considered virtual evaluation to be more difficult than in-person evaluation and believed the remote format negatively affected their development as an examiner. The virtual format was considered to be less secure by 56% and 40% of SOE and OSCE examiners, respectively. The retirement of exam materials used virtually due to concern for compromise had implications for subsequent exam development. The return to in-person exams in 2022 was prompted by multiple factors, especially concerns regarding standardization and security. The technology is not yet perfect, especially for testing in-person communication skills and displaying dynamic exam materials. Nevertheless, the American Board of Anesthesiology’s experience demonstrated the feasibility of conducting large-scale, high-stakes oral and performance exams in a virtual format and highlighted the adaptability and dedication of candidates, examiners, and administering board staff.

Clonal hematopoiesis (CH), the expansion of hematopoietic stem cells and their progeny driven by somatic mutations in leukemia-associated genes, is a common phenomenon that rises in prevalence with advancing age to affect most people older than 70 years. CH remains subclinical in most carriers, but, in a minority, it progresses to a myeloid neoplasm, such as acute myeloid leukemia, myelodysplastic syndrome, or myeloproliferative neoplasm. Over the last decade, advances in our understanding of CH, its molecular landscape, and the risks associated with different driver gene mutations have culminated in recent developments that allow for a more precise estimation of myeloid neoplasia risk in CH carriers. In turn, this is leading to the development of translational and clinical programs to intercept and prevent CH from developing into myeloid neoplasia. Here, we give an overview of the spectrum of CH driver mutations, what is known about their pathophysiology, and how this informs the risk of incident myeloid malignancy., Introduction Throughout the human lifespan, blood cells are formed continuously through the division and differentiation of cells in a process termed hematopoiesis. At the apex of this hierarchy are a [...]

A series of Mn(II), Fe(II), and Co(II) bisaryloxide dimers ([M(OC6H2-2,4,6-Cy3)2]2 {M = Mn (1), Fe (2), and Co (3)} were synthesized by the addition of 2,4,6-tricyclohexylphenol (HOC6H2-2,4,6-Cy3) to the silyl amido dimers [M(N(SiMe3)2)2]2 (M = Mn, Fe, Co; Cy = cyclohexyl). An unexpected and unique Co(II) phenoxide derivative (4), [Co(OC6H2-2,4,6-Cy3)(O2C6H-3,5,6-Cy3)]2, was obtained via ligand rearrangement of 3 at ca. 180 °C. This yielded 4 in which there are two unchanged, bridging phenoxide ligands as well as a terminal bidentate semiquinone ligand bound to each cobalt. Complexes 1 and 2 did not undergo such a rearrangement under the same conditions; both are thermally stable to temperatures exceeding 250 °C and feature numerous short-contact (

The development of effective therapies for neurological disorders is a growing area of research due to the increasing prevalence of these conditions. Some neurological disorders that are prevalent and remain difficult to treat are glioma, neurodegenerative disease, ischemic stroke, and traumatic brain injury. Subsequently, the therapeutic efficacy of small molecules, proteins, and oligonucleotides remains a challenge due to the presence of the blood–brain barrier (BBB), a highly selective semipermeable membrane. To this end, multifunctional nanomaterials have emerged as promising vehicles for targeted drug delivery to the brain, due to their ability to transport therapeutics across the BBB selectively. The design of advanced nanomaterial‐based drug delivery systems capable of overcoming the BBB is influenced by many factors, such as fabrication technique and surface modification. This review explores the diverse range of nanomaterials, including polymer, lipid, gold, magnetic, and carbon‐based nanostructures, capable of effectively passing the BBB. These materials cross the BBB via a variety of established transport mechanisms for targeted delivery of therapeutics to the brain. Moreover, the structure and function of the BBB are highlighted and the potential for nanotechnology to aid the treatment of neurological disorders based on their ability to undergo transcytosis into the brain is highlighted.

IDH-Mutant-astrocytomas are malignant brain glioma tumors. They are graded as lower grade (grades 2 and 3) or higher grade (grade 4) according to their rate of growth and molecular features. Conventional IDH grading requires pathology examination, which is invasive, costly, and time-consuming. Advanced MRI modalities are widely used to overcome some of these limitations but require a high level of interpretation for tumor grading. Recent advances in deep learning have shown potential to aid and improve the accuracy and efficiency of tumor classification. This study proposes a novel non-invasive approach for grading IDH-Mutant-astrocytomas using a Light-weight Attention Network (LAN) that integrates multi-modal MRI data, including both conventional and advanced MRI modalities. The study addresses inter-modality heterogeneity using Principal Component Analysis (PCA) while minimizing computational complexity. LAN uses a 3D Convolutional Neural Network (CNN) and a volumetric attention mechanism to extract tumor patterns and classify grades 2 to 4. This is followed by an eXplainable AI approach that uses SHapley Additive exPlanations (SHAP) to interpret model decisions and identify key contributing features. The proposed LAN model outperforms other pre-trained state-of-the-art models, achieving an overall accuracy of 0.84. The SHAP attribution scores demonstrate that advanced MRI modalities such as Arterial Spin Labeling (ASL) and Diffusion-weighted Imaging (DWI), along with conventional MRI sequences such as FLAIR, T1-c and T2, contribute significantly to improving tumor heterogeneity visualization for aggressive grade 2 gliomas. This work demonstrates the feasibility of integrating explainable deep learning with multi-modal MRI data for precise and comprehensible early glioma grading, potentially leading to better clinical decision-making.