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Background: Undergraduate engineering students experiencing distress are less likely than peers to ask for professional help. A population-specific instrument to facilitate the identification of factors that influence mental healthcare utilization could guide development and testing of interventions to increase help seeking. Purpose: We used mixed methods guided by the Integrated Behavioral Model (IBM) to develop and evaluate the Undergraduate Engineering Mental Health Help-Seeking Instrument (UE-MH-HSI). Method: First, we adapted existing measures of mental health help-seeking intention and mechanisms (i.e., attitudes, perceived norm: injunctive, perceived norm: descriptive, personal agency: autonomy, personal agency: capacity). Second, we coded qualitative interviews (N = 33) to create population-specific mental health help-seeking belief measures (i.e., outcome beliefs, experiential beliefs, beliefs about others' expectations, beliefs about others' behavior, beliefs about barriers and facilitators). Third, we tested the psychometric properties using data from 596 undergraduate engineering students at a historically White, research-focused institution in southern United States. Results: Psychometric analyses indicated that (1) help-seeking mechanism and intention measures demonstrated unidimensionality, internal consistency, construct replicability, and sufficient variability; (2) mechanism measures demonstrated criterion evidence of validity; and (3) most items within the belief measures demonstrated sufficient variability and convergent evidence of validity. Conclusions: The UE-MH-HSI is an evidence-based tool for investigating mental health help-seeking factors and their relationship to help-seeking behavior, well-being, academic success, and engineering identity formation. Guidelines for use are provided.

UAS imagery has become a widely used source of information in geomorphic research. When photogrammetric methods are applied to quantify geomorphic change, camera calibration is essential to ensure accuracy of the image measurements. Insufficient self-calibration based on survey data can induce systematic errors that can cause DEM deformations. The typically low geometric stability of consumer grade sensors necessitates in-situ calibration, as the reliability of a lab based calibration can be affected by transport. In this research a robust on-site workflow is proposed that allows the time-efficient and repeatable calibration of thermal and optical sensors at the same time. A stone building was utilised as calibration object with TLS scans for reference. The approach was applied to calculate eight separate camera calibrations using two sensors (DJI Phantom 4 Pro and Workswell WIRIS pro), two software solutions (Vision Measurement System (VMS) and Agisoft Metashape) and two different subsets of images per sensor. The presented results demonstrate that the approach is suitable to determine camera parameters for pre-calibrating photogrammetric surveys.

Although executive functions (EFs) have been identified as a cornerstone of cognitive development, knowledge of this fundamental ability in children is based primarily on research with North American and Western European samples of middle to high socioeconomic status (SES). In this article, we highlight advances in research on developmental EFs from Latin American regions, an understudied area that provides a unique context important to understanding EFs. Our narrative review suggests the potential for both universality (e.g., increasing cohesion and longitudinal stability among EFs' task performance, general positive associations with age, and other social and cognitive abilities) and cultural specificity in EF development (i.e., contributions of SES, educational environments, parenting styles, and cultural values). It is important to consider the development of EFs outside of typically examined samples--and specifically within Latin American countries--to understand more thoroughly these abilities and to generate interventions that consider cultural context.

To better understand the current challenges surrounding the use of artificial intelligence (AI) in K-12 schools, a team of researchers (Raffaella Borasi, David E. Miller, Patricia Vaughan-Brogan, Karen DeAngelis, Yu Jung Han, and Sharon Mason) interviewed 36 western New York school leaders in late 2023. Their concerns moved beyond potential cheating, as they instead identified four main priorities: receiving guidance to inform their decisions about AI, empowering all stakeholders to better understand AI and its implications, capitalizing on AI to support the work of teachers and staff, and enabling better technology solutions. These should inform future interventions aiming at leveraging AI in K-12 education.

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of openness, amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.

Abstract PIK3CA-related overgrowth spectrum (PROS) disorders are caused by somatic mosaic variants that result in constitutive activation of the phosphatidylinositol-3-kinase/AKT/mTOR pathway. Promising responses to molecularly targeted therapy have been reported, although identification of an appropriate agent can be hampered by the mosaic nature and corresponding low variant allele frequency of the causal variant. Moreover, our understanding of the molecular consequences of these variants—for example how they affect gene expression profiles—remains limited. Here we describe in vitro expansion of a human capillary malformation followed by molecular characterization using exome sequencing, single cell gene expression, and targeted long-read single cell RNA-sequencing in a patient with clinical features consistent with Megalencephaly-Capillary Malformation Syndrome (MCAP, a PROS condition). These approaches identified a targetable PIK3CA variant with expression restricted to PAX3+ fibroblast and undifferentiated keratinocyte populations. This study highlights the innovative combination of next-generation single cell sequencing methods to better understand unique transcriptomic profiles and cell types associated with MCAP, revealing molecular intricacies of this genetic syndrome.

Abstract Maternal stress and depression during pregnancy and the first year of the infant’s life affect a large percentage of mothers. Maternal stress and depression have been associated with adverse fetal and childhood outcomes as well as differential child DNA methylation (DNAm). However, the biological mechanisms connecting maternal stress and depression to poor health outcomes in children are still largely unknown. Here we aim to determine whether prenatal stress and depression are associated with differences in cord blood mononuclear cell DNAm (CBMC-DNAm) in newborns (n = 119) and whether postnatal stress and depression are associated with differences in peripheral blood mononuclear cell DNAm (PBMC-DNAm) in children of 12 months of age (n = 113) from the Canadian Healthy Infant Longitudinal Development (CHILD) cohort. Stress was measured using the 10-item Perceived Stress Scale (PSS) and depression was measured using the 20-item Center for Epidemiologic Studies Depression Questionnaire (CESD). Both stress and depression were measured longitudinally at 18 weeks and 36 weeks of pregnancy and six months and 12 months postpartum. We conducted epigenome-wide association studies (EWAS) using robust linear regression followed by a sensitivity analysis in which we bias-adjusted for inflation and unmeasured confounding using the bacon and cate methods. To quantify the cumulative effect of maternal stress and depression, we created composite prenatal and postnatal adversity scores. We identified a significant association between prenatal stress and differential CBMC-DNAm at 8 CpG sites and between prenatal depression and differential CBMC-DNAm at 2 CpG sites. Additionally, we identified a significant association between postnatal stress and differential PBMC-DNAm at 8 CpG sites and between postnatal depression and differential PBMC-DNAm at 11 CpG sites. Using our composite scores, we further identified 2 CpG sites significantly associated with prenatal adversity and 7 CpG sites significantly associated with postnatal adversity. Several of the associated genes, including PLAGL1, HYMAI, BRD2, and ERC2 have been implicated in adverse fetal outcomes and neuropsychiatric disorders. These data further support the finding that differential DNAm may play a role in the relationship between maternal mental health and child health.

Abstract Aims New tools are needed to identify heart failure (HF) risk earlier in its course. We evaluated the association of multidimensional cardiopulmonary exercise testing (CPET) phenotypes with subclinical risk markers and predicted long‐term HF risk in a large community‐based cohort. Methods and results We studied 2532 Framingham Heart Study participants [age 53 ± 9 years, 52% women, body mass index (BMI) 28.0 ± 5.3 kg/m2, peak oxygen uptake (VO2) 21.1 ± 5.9 kg/m2 in women, 26.4 ± 6.7 kg/m2 in men] who underwent maximum effort CPET and were not taking atrioventricular nodal blocking agents. Higher peak VO2 was associated with a lower estimated HF risk score (Spearman correlation r: −0.60 in men and −0.55 in women, P

Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm.

This study builds on existing literature of glacier change estimation in polar regions and is a continuation of efforts aimed at unlocking the information encapsulated in archival aerial photography of Antarctic Peninsula glaciers. Historical aerial imagery acquired in 1957 over three marine-terminating glaciers at Lindblad Cove on the West Coast of Trinity Peninsula is processed to extract digital elevation models (DEMs) which are subsequently compared to DEMs generated from present day (2014) WorldView-2 satellite stereo-imagery. The new WorldView-2 images offer unprecedented sub-metre resolution of the Antarctic Peninsula and are explored here to facilitate improved registration and higher accuracy analysis of glacier changes. Unlike many studies, which focus on glacier fronts or only restricted regions of glaciers, this paper presents a complete coverage of elevation changes across the glacier surfaces for two of the studied glaciers. The study utilises a robust least squares matching technique to ensure precise registration of the archival and modern DEMs, which is applied due to lack of existing ground control in this remote region. This case study reveals that, while many glaciers in polar regions are reported as experiencing significant mass loss, some glaciers are stable or even demonstrate mass gain. All three glaciers reported here demonstrated overall mean increases in surface elevation, indicative of positive mass balance ranging from 0.6 to 5.8 metre water equivalent between 1957 and 2014.

Over the last 20 years the demand for three dimensional (3D) building models has resulted in a vast amount of research being conducted in attempts to automate the extraction and reconstruction of models from airborne sensors. Recent results have shown that current methods tend to favour planar fitting procedures from lidar data, which are able to successfully reconstruct simple roof structures automatically but fail to reconstruct more complex structures or roofs with small artefacts. Current methods have also not fully explored the potential of recent developments in digital photogrammetry. Large format digital aerial cameras can now capture imagery with increased overlap and a higher spatial resolution, increasing the number of pixel correspondences between images. Every pixel in each stereo pair can also now be matched using per-pixel algorithms, which has given rise to the approach known as dense image matching. This paper presents an approach to 3D building reconstruction to try and overcome some of the limitations of planar fitting procedures. Roof vertices, extracted from true-orthophotos using edge detection, are refined and converted to roof corner points. By determining the connection between extracted corner points, a roof plane can be defined as a closed-cycle of points. Presented results demonstrate the potential of this method for the reconstruction of complex 3D building models at CityGML LoD2 specification.

Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.

Historically, university systems have maintained gender inequities that facilitate promotion and advancement for Caucasian men, while creating barriers to career advancement for women and marginalised groups. Significant obstacles have existed for faculty mothers who have attempted to fulfill responsibilities as both mother and worker, particularly amid the COVID-19 global pandemic. The purpose of this study is to explore how, during the health crisis, faculty mothers perceived their experiences to impact their research productivity. Based on demographic and open-ended questionnaire data from 134 study participants in the United States, the findings suggest that as supportive duties demanded participants' prompt attention, research was pushed to the side, resulting in perceived threats to faculty mothers' careers. Given the value many institutions place on publications in the hiring, tenure, and promotion process, decreased or stalled publications could result in career repercussions. Specifically, participants viewed losses in research productivity as hindering job mobility for adjuncts and instructors; creating barriers to tenure and promotion for tenure-track faculty; and stalling career advancement for tenured faculty.

One way to support young children's factual learning is through shared book reading (reading books with a knowledgeable other). Many books that teach factual content are narrative in structure, in which factual content is embedded within a fictional storyline. However, there are gaps in our understanding of factors influencing children's factual learning from narrative books. In this experiment, 38 caregivers and their 4- to 5-year-old children from the Southeastern United States participated. Each caregiver read to their child two narrative books on science concepts. The books varied in their levels of cohesion (e.g. drawing connections between textual elements and providing details and comparisons). We coded caregivers' extratextual talk while reading for the extent to which it emphasized science information (informational highlighted talk) or went beyond the text to provide further related information (informational elaborative talk). Children's recall of the books' science and story content was tested in free and probed recall formats. We found that children had higher recall of the story content, even though caregivers emphasized the science content through their highlighted extratextual talk. Caregivers used more elaborative extratextual talk with the low cohesion book, perhaps as compensation for the book's lack of cohesion. However, children's recall of the science content was most strongly predicted by the books' cohesion and caregivers' highlighted extratextual talk. These results emphasize the important role that books' textual features and caregivers' extratextual talk during book reading have on young children's factual learning from narrative books.

Purpose: This study investigated the reading profiles of middle school Spanish-speaking emergent bilinguals (EBs) with significantly below grade level reading comprehension and whether these profiles varied in their reading comprehension performance over time. Method: Latent profile analyses were used to classify Grade 6 and 7 Hispanic EBs (n = 340; 39% female) into subgroups based on their word reading and vocabulary knowledge. Growth models were then fit within each profile to evaluate reading comprehension performance over time. Results: Analyses revealed four latent profiles emerged: (a) very low word reading and low vocabulary (10%), (b) low word reading and low vocabulary (71%), (c) average word reading and low vocabulary (16%), and (d) high word reading and low vocabulary (3%). Subgroups varied in their reading comprehension initially and over one year. Students in the subgroup marked by very low word reading and low vocabulary showed the lowest reading comprehension performance initially; however, they also showed the greatest growth over one year. Conclusion: These findings suggest that there is heterogeneity in the reading skill profiles of Spanish-speaking EBs with reading comprehension difficulties. They also underscore the prevalence of word reading difficulties among these students. These may be important factors to consider when developing interventions to prevent and remediate these difficulties.

Over the last 20 years the use of, and demand for, three dimensional (3D) building models has meant there has been a vast amount of research conducted in automating the extraction and reconstruction of these models from airborne sensors. Whilst many different approaches have been suggested, full automation is yet to be achieved and research has suggested that the combination of data from multiple sources is required in order to achieve this. Developments in digital photogrammetry have delivered improvements in spatial resolution whilst higher image overlap to increase the number of pixel correspondents between images, giving the name multi-ray photogrammetry, has improved the resolution and quality of its by-products. In this paper the extraction of roof geometry from multiray photogrammetry will be covered, which underpins 3D building reconstruction. Using orthophotos, roof vertices are extracted using the Canny edge detector. Roof planes are detected from digital surface models (DSM) by extracting information from 2D cross sections and measuring height differences. To eliminate overhanging vegetation, the segmentation of trees is investigated by calculating the characteristics of a point within a local neighbourhood of the photogrammetric point cloud. The results highlight the complementary nature of these information sources, and a methodology for integration and reconstruction of roof geometry is proposed.

The study reveals the results of consideration of problematic issues reflecting the choice of scenario options for the sustainability of technological development of regional industrial complexes. The methodology of application of modular models under study provided an opportunity to identify the goal orientation and key aspects of the sustainability of technological development at the regional level. Among the specific features of the methodology under consideration, it is advisable to include: a set of parameters of technological development; substantiation of the essential features influencing the formation of a model of technological development of a regional industrial complex based on a scenario-modular approach. The considered features provide an opportunity to specify the fundamental principles of the classical theory of sustainable development in the context of insufficiently researched issues of the regional economy. In the process of methodological application of the methodology under consideration, a scenario-modular approach is justified, aimed at achieving the goals of sustainability of technological development and expressed in the formation of predictive scenarios of technological development based on local modules, various combinations of which allow synthesizing all possible scenarios. The advantages of the scenario-modular approach include: the achievability of standardization of technological development; identification of the integration nature of technological development; designing a predictive option for investing resources in technological development; substantiation of a scenario modular model. The given model makes it possible to: streamline the structure of products; systematize technological processes and management procedures.

Abstract Background Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and transformative recent growth of AI in cardiovascular care, to inform practice guidelines and regulatory policies that facilitate ethical and trustworthy use of AI in medicine, we conducted a literature review to identify key ethical and trust barriers and facilitators from patients’ and healthcare providers’ perspectives when using AI in cardiovascular care. Methods In this rapid literature review, we searched six bibliographic databases to identify publications discussing transparency, trust, or ethical concerns (outcomes of interest) associated with AI-based medical devices (interventions of interest) in the context of cardiovascular care from patients’, caregivers’, or healthcare providers’ perspectives. The search was completed on May 24, 2022 and was not limited by date or study design. Results After reviewing 7,925 papers from six databases and 3,603 papers identified through citation chasing, 145 articles were included. Key ethical concerns included privacy, security, or confidentiality issues (n = 59, 40.7%); risk of healthcare inequity or disparity (n = 36, 24.8%); risk of patient harm (n = 24, 16.6%); accountability and responsibility concerns (n = 19, 13.1%); problematic informed consent and potential loss of patient autonomy (n = 17, 11.7%); and issues related to data ownership (n = 11, 7.6%). Major trust barriers included data privacy and security concerns, potential risk of patient harm, perceived lack of transparency about AI-enabled medical devices, concerns about AI replacing human aspects of care, concerns about prioritizing profits over patients’ interests, and lack of robust evidence related to the accuracy and limitations of AI-based medical devices. Ethical and trust facilitators included ensuring data privacy and data validation, conducting clinical trials in diverse cohorts, providing appropriate training and resources to patients and healthcare providers and improving their engagement in different phases of AI implementation, and establishing further regulatory oversights. Conclusion This review revealed key ethical concerns and barriers and facilitators of trust in AI-enabled medical devices from patients’ and healthcare providers’ perspectives. Successful integration of AI into cardiovascular care necessitates implementation of mitigation strategies. These strategies should focus on enhanced regulatory oversight on the use of patient data and promoting transparency around the use of AI in patient care.

Studies in recent decades have shown strong evidence of physical and biological changes in the Arctic tundra, largely in response to rapid rates of warming. Given the important implications of these changes for ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this great need, scientific understanding of tundra ecology and change remains limited, largely due to the inaccessibility of this region and less intensive studies compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation and active-layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potentially increasing intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled the Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: https://doi.org/10.3334/ORNLDAAC/2177).

Abstract Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.

Abstract Background A concern before 2020, physician burnout worsened during the COVID-19 pandemic. Little empirical data are available on pandemic workplace support interventions or their influence on burnout. We surveyed a national sample of frontline physicians on burnout and workplace support during the pandemic. Methods We surveyed a stratified random sample of 12,833 US physicians most likely to care for adult COVID-19 patients from the comprehensive AMA Physician Professional Data ™ file. The sample included 6722 primary care physicians (3331 family physicians, 3391 internists), 880 hospitalists, 1783 critical care physicians (894 critical care physicians, 889 pulmonary intensivists), 2548 emergency medicine physicians, and 900 infectious disease physicians. The emailed survey elicited physicians’ perceptions of organizational interventions to provide workplace support and/or to address burnout. Burnout was assessed with the Professional Fulfillment Index Burnout Composite scale (PFI-BC). Proportional specialty representation and response bias were addressed by survey weighting. Logistic regression assessed the association of physician characteristics and workplace interventions with burnout. Results After weighting, respondents were representative of the total sample. Overall physician burnout was 45.4%, significantly higher than in our previous survey. Open-ended responses mentioned that staffing shortages (physician, nursing, and other staff) combined with the increased volume, complexity, and acuity of patients during the pandemic increased job demands. The most frequent workplace support interventions were direct pandemic control measures (increased access to personal protective equipment, 70.0%); improved telehealth functionality (43.4%); and individual resiliency tools (yoga, meditation, 30.7%). Respondents placed highest priority on workplace interventions to increase financial support and increase nursing and clinician staffing. Factors significantly associated with lower odds of burnout were practicing critical care (compared with emergency medicine) OR 0.33 (95% CI 0.12 – 0.93), improved telehealth functionality OR 0.47 (95% CI 0.23 – 0.97) and being in practice for 11 years or longer OR 0.44 (95% CI 0.19–0.99). Conclusions Burnout across frontline specialties increased during the pandemic. Physician respondents focused on inadequate staffing in the context of caring for more and sicker patients, combined with the lack of administrative efforts to mitigate problems. Burnout mitigation requires system-level interventions beyond individual-focused stress reduction programs to improve staffing, increase compensation, and build effective teams.

Abstract Background Professional societies such as the American College of Obstetricians and Gynecologists (ACOG) promote the idea that postpartum care is an ongoing process where there is adequate opportunity to provide services and support. Nonetheless, in practice, the guidelines ask clinicians to perform more clinical responsibilities than they might be able to do with limited time and resources. Methods We conducted an online survey among practicing obstetric clinicians (obstetrician/gynecologists (OB/GYNs), midwives, and family medicine doctors) in California about their priorities and care practices for the first postpartum visit and explored how they prioritize multiple clinical responsibilities within existing time and resources. Between September 2023 and February 2024, 174 out of 229 eligible participants completed the survey, a 76% response rate. From a list of care components, we used descriptive statistics to identify those that were highly prioritized by most clinicians and those that were considered a priority by very few and examined the alignment between prioritized components and recommended care practices. Results Clinicians were highly invested in the care components that they rated as most important, indicating that they always check these components or assess them when they perceive patient need. Depression and anxiety, breast health/breast feeding issues, vaginal birth complications and family planning counseling were highly ranked components by all clinicians. In contrast, clinicians more often did not assess those care components that infrequently ranked highly among the priority listing, consisting mainly of social drivers of health such as screening and counseling for intimate partner violence, working conditions and food/housing insecurity. In both instances, we found little discordance between priorities and care practices. However, OB/GYNs and midwives differed in some care components that they prioritized highly. Conclusions While there is growing understanding of how important professional society recommendations are for maternal-infant health, clinicians face barriers completing all recommendations, especially those components related to social drivers of health. However, what the clinicians do prioritize highly, they are likely to perform. Now that Medi-Cal (Medicaid) insurance is available in California for up to 12 months postpartum, there is a need to understand what care clinicians provide and what gaps remain.

Abstract Objectives This work aims to determine the efficacy and safety of preoperative alpha‐blocker therapy on ureteroscopy (URS) outcomes. Methods In this systematic review and meta‐analysis of randomised trials of URS with or without preoperative alpha‐blocker therapy, outcomes included the need for ureteral dilatation, stone access failure, procedure time, residual stone rate, hospital stay, and complications. Residual stone rates were reported with and without adjustments for spontaneous stone passage, medication noncompliance, or adverse events leading to patient withdrawal. Data were analysed using random‐effects meta‐analysis and meta‐regression. Certainty of evidence was assessed using the GRADE criteria. Results Among 15 randomised trials with 1653 patients, URS was effective and safe with a stone‐free rate of 81.2% and rare (2.3%) serious complications. The addition of preoperative alpha‐blockers reduced the need for ureteral dilatation (risk ratio [RR] = 0.48; 95% CI = 0.30 to 0.75; p = 0.002), access failure rate (RR = 0.36; 95% CI = 0.23 to 0.57; p

Abstract Background Macrophages play important roles in phagocytosing tumor cells. However, tumors escape macrophage phagocytosis in part through the expression of anti-phagocytic signals, most commonly CD47. In Ewing sarcoma (ES), we found that tumor cells utilize dual mechanisms to evade macrophage clearance by simultaneously over-expressing CD47 and down-regulating cell surface calreticulin (csCRT), the pro-phagocytic signal. Here, we investigate the combination of a CD47 blockade (magrolimab, MAG) to inhibit the anti-phagocytic signal and a chemotherapy regimen (doxorubicin, DOX) to enhance the pro-phagocytic signal to induce macrophage phagocytosis of ES cells in vitro and inhibit tumor growth and metastasis in vivo. Methods Macrophages were derived from human peripheral blood monocytes by granulocyte–macrophage colony-stimulating factor (GM-CSF) and macrophage colony-stimulating factor (M-CSF). Flow cytometry- and microscopy-based in-vitro phagocytosis assays were performed to evaluate macrophage phagocytosis of ES cells. Annexin-V assay was performed to evaluate apoptosis. CD47 was knocked out by CRISPR/Cas9 approach. ES cell-based and patient-derived-xenograft (PDX)-based mouse models were utilized to assess the effects of MAG and/or DOX on ES tumor development and animal survival. RNA-Seq combined with CIBERSORTx analysis was utilized to identify changes in tumor cell transcriptome and tumor infiltrating immune cell profiling in MAG and/or DOX treated xenograft tumors. Results We found that MAG significantly increased macrophage phagocytosis of ES cells in vitro (p

Due to the complementary characteristics of lidar and photogrammetry, the integration of data derived from these techniques continues to receive attention from the relevant research communities. The research presented in this paper draws on this by adopting lidar data as a control surface from which aerial triangulation and camera system calibration can be performed. The research methodology implements automatic registration between the reference lidar DTM and dense photogrammetric point clouds which are derived using Integrated Sensing Orientation (ISO). This utilises a robust least squares surface matching algorithm, which is iterated to improve results by increasing the photogrammetric point quality through self-calibrating bundle adjustment. After a successful registration, well distributed lidar control points (LCPs) are automatically extracted from the transformed photogrammetric point clouds using predefined criteria. Finally, self-calibrating bundle block adjustment using different configurations of LCPs is performed to refine camera interior orientation (IO) parameters. The methodology has been assessed using imagery from a Vexcel UltraCamX large format camera. Analysis and the performance of the camera and its impact on the registration accuracy was performed. Furthermore, refinement of camera IO parameters was also applied using the derived LCPs. Tests also included investigations into the influence of the number and weight of LCPs in the accuracy of the bundle adjustment. Results from the UltraCamX block were compared with reference calibration results using ground control points in the test area, with good agreement found between the two approaches.

Health-related quality of life (HRQoL) is a patient-perceived measure of physical, social, and emotional health. Acquired brain injury (ABI) occurs due to damage to the brain after birth. Individuals with an ABI typically present with reduced HRQoL and require additional support to maintain their HRQoL. Although structured exercise training has been shown to improve HRQoL in individuals with ABI, there is little research on habitual, real-world activity. Most activity research characterizes moderate-to-vigorous physical activity (MVPA) in absolute terms; however, relative physical activity levels have been promoted for research in clinical populations. We tested whether longer MVPA durations, measured in absolute/relative levels, are associated with higher HRQoL in outpatients with ABIs. In total, 26 adults (54 ± 13 years, 16 females) with ABI completed the Quality of Life After Brain Injury questionnaire, a 6-min walk test (a measure of aerobic fitness; 490 ± 105 m), and wore an activPAL device 24 h/day for 7 days. Participants had an average HRQoL score of 53.4 ± 15.0 (out of 100), with 20 of 26 showing impaired HRQoL (score 0.14). Targeting more absolute MVPA, but not necessarily relative MVPA, may be an effective strategy for interventions aiming to improve HRQoL in individuals with ABI.

Per- and poly-fluoroalkyl substances (PFAS) are chemicals of concern—they are ubiquitous, persistent, with known and suspected health impacts. Well studied, primary sources of exposure to PFAS are drinking water and food. The presence of PFAS in human tissue of general populations suggests other important exposure sources/pathways. House dust measurements suggest widespread presence of PFAS in residences. Limited studies report paired analyses of PFAS occurrence in indoor media and PFAS concentrations in serum. While paired samples of house dust and blood serum are currently rare, the National Children’s Study (NCS) contains paired samples, as well as sociodemographic information, from pregnant people that participated in the study. These archived NCS data and specimens for 104 participants collected between 2009 and 2014 were leveraged and analyzed for 16 commonly measured PFAS. We evaluated PFAS levels in the home, and the relationships between PFAS in dust and serum, and sociodemographic or housing variables. In addition, mechanistic exposure models, and then steady-state serum level models with simple parameters were used to estimate dust contributions of PFAS to serum. The geometric means for the most commonly found PFAS (full names in table 1) in serum were: 4.1 ng/mL for PFOS, 1.1 ng/mL for PFOA, 0.87 ng/mL for PFHxS, 0.16 ng/mL for PFDA. The geometric means of PFAS in dust were: 17 µg/kg for PFOS, 16 µg/kg for PFOA, 9.6 µg/kg for PFDS, 4.5 µg/kg for PFHpA, 4.4 µg/kg for PFNA, 3.9 µg/kg for PFHxS, 3.5 µg/kg for PFDA, 2.3 µg/kg for PFDoA, 2.1 µg/kg for PFUdA. PFOA was significantly correlated in serum and dust as was the sum of all PFAS detected in > 50 % of serum and dust. PFAS in serum was significantly associated with: Higher income, recent renovations, years lived in the home, and educational attainment. PFAS in dust was significantly associated with: Higher participant age, type of home, amount of carpet, educational attainment, higher income, recent renovation, and membership in the military. For some PFAS, 25 % of the overall exposure, on average, is from dust, but for others, 3–4 % is attributed to dust.We were able to identify important associations in PFAS exposure in the homes of pregnant people based on paired serum and dust samples. This built a clearer picture of which PFAS and at what quantities they exist in these homes, how they relate to each other, and how they are tied to sociodemographic and housing factors. Our results demonstrate that exposure to PFAS via house dust may contribute up to 25% of total exposure for adults, highlighting the importance of understanding what drives residential exposures.

Despite the increasing availability of comprehensive next generation sequencing (NGS), its role in characterizing pediatric hematologic malignancies remains undefined. We describe findings from comprehensive genomic profiling of hematologic malignancies at a pediatric tertiary care center. Patients enrolled on a translational research protocol to aid in cancer diagnosis, prognostication, treatment, and detection of cancer predisposition. Disease-involved samples underwent exome and RNA sequencing and analysis for single nucleotide variation, insertion/deletions, copy number alteration, structural variation, fusions, and gene expression. Twenty-eight patients with hematologic malignancies were nominated between 2018-2021. Eighteen individuals received both germline and somatic sequencing; two received germline sequencing only. Germline testing identified patients with cancer predisposition syndromes and non-cancer carrier states. Fifteen patients (15/18, 83%) had cancer-relevant somatic findings. Potential therapeutic targets were identified in seven patients (7/18, 38.9%); three (3/7, 42.9%) received targeted therapies and remain in remission an average of 47 months later.

Most people in the United States have been exposed to per- and polyfluoroalkyl substances (PFAS) which have been linked to a wide array of adverse health conditions in adults and children. The consumption of contaminated drinking water is an important human exposure pathway to PFAS. Residential sources also contribute to PFAS exposure through dermal contact and ingestion of house dust, which acts as an aggregate of chemicals from sources like furnishing materials and consumer products. The U.S. Department of Housing and Urban Development (HUD) conducted the first nationwide survey of residential hazards called the American Healthy Homes Survey (AHHS) in 2005, followed by a second survey (AHHS II) in 2017. The U.S. Environmental Protection Agency (EPA) collaborated with HUD on both efforts and subsequently analyzed PFAS in household tap water and house dust collected from the same homes during the AHHS II study. This study leverages these paired samples to investigate potentially important exposure sources and pathways in the residential environment. Here we report results for paired household tap water and house dust samples from 241 homes for 13 and 16 PFAS chemicals, respectively. All 13 targeted chemicals were detected in the household tap water samples with detections ranging from 100 % for PFBS to 1 % for PFNS, and all 16 targeted chemicals were detected in the house dust samples with detections ranging from 97 % for PFOA to 9 % for PFNS. Four chemicals (PFOA, PFOS, PFHxS, and PFHpA) were measured above the limit of detection in at least 50 % of the samples in both media. All households had at least one of the targeted PFAS detected in both their tap water and house dust. Results provided evidence that geographical factors, such as proximity to ambient contamination sources, were main drivers of PFAS contamination in tap water, while PFAS contamination in house dust was driven mainly by within-home sources. Exposure estimates calculated from the measured PFAS concentrations highlight the importance of addressing potential sources of exposure to PFAS within homes in addition to ambient sources affecting communities’ drinking water, particularly to reduce children’s exposure to these chemicals.

While the structural organization and molecular biology of neurons are well characterized, the physical process of axonal elongation remains elusive. The classic view posited elongation occurs through the deposition of cytoskeletal elements in the growth cone at the tip of a stationary array of microtubules. Yet, recent studies reveal axonal microtubules and docked organelles flow forward in bulk in the elongating axons of Aplysia, chick sensory, rat hippocampal, and Drosophila neurons. Noting that the morphology, molecular components, and subcellular flow patterns of growth cones strongly resemble the leading edge of migrating cells and the polar regions of dividing cells, our working hypothesis is that axonal elongation utilizes the same physical mechanisms that drive cell crawling and cell division. As a test of that hypothesis, here we take experimental data sets of sub-cellular flow patterns in cells undergoing cytokinesis, mesenchymal migration, amoeboid migration, neuronal migration, and axonal elongation. We then apply active fluid theory to develop a biophysical model that describes the different sub-cellular flow profiles across these forms of motility and how this generates cell motility under low Reynolds numbers. The modeling suggests that mechanisms for generating motion are shared across these processes, and differences arise through modifications of sub-cellular adhesion patterns and the profiles of internal force generation. Collectively, this work suggests that ameboid and mesenchymal cell crawling may have arisen from processes that first developed to support cell division, that growth cone motility and cell crawling are closely related, and that neuronal migration and axonal elongation are fundamentally similar, differing primarily in the motion and strength of adhesion under the cell body.

Large format digital aerial cameras are now in widespread commercial operation. Despite the advantages of the new cameras over their traditional film counterparts, systematic image errors have been observed in all existing large format digital cameras. Organizations such as the USGS and EuroSDR have therefore focused efforts on calibration, validation and certification of digital camera systems. However, to-date, few studies have assessed the effects of extreme temperature and humidity variations on these camera systems, and the potential for self-calibration in this respect. This research addresses these issues through investigation of the UltraCamD, with test data acquired over a range of climatic zones in Libya. This presentation will report the preliminary results of self-calibration using a bundle block adjustment for an UltraCamD system, based upon aerial data acquired for two test sites during a single field campaign. The datasets were flown at two different flying heights and incorporate differing block geometries. A SOCET SET (v5.4.1) digital photogrammetric workstation was used to triangulate the imagery with investigation of different tie point densities. Following this, a self-calibrating bundle block adjustment was performed using the BLUH software provided by the University of Hannover. Initial testing investigated the influence of tie point density and different coordinate systems and datums on the bundle adjustment results. Further testing was then performed within BLUH in order to determine the optimal set of additional parameters, compensating for systematic image errors and impact upon object space coordinates of independent check points and ground control points.

Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration routine by accounting for all the variables affecting the backscattered energy, including the essential factor of angle of incidence. A new robust incidence angle estimation approach has been developed which has proven capable of delivering a reliable estimation for the scattering direction of the individual echoes. The routine was tested and validated both visually and statistically over various land cover types with simple and challenging surface trends. This proved the validity of this approach to deliver the optimal match between overlapping flightlines after calibration, particularly by adopting a parameter which accounts for the angle of incidence effect.

Climate records show that the Antarctic Peninsula is rapidly warming. Dramatic changes in ice shelf and glacier extent have been recorded over the last few decades. Mapping recent changes in the Antarctic Peninsula is relatively straightforward, as increased amounts of earth observation data become readily available for scientific purposes. However, long term measurements of volumetric changes within the region are rare and less is known of changes which have occurred over the second half of the 20th Century. Nonetheless, historical observations are available in the form of archival aerial stereo-photography. However, extracting information from historical data, i.e. to compare it to recent data, is not trivial, and to-date, this data source remains largely untapped, despite its rich potential. Often such imagery is stored in non-digital format and may have degraded over time. Other problems relate to insufficient metadata or ground control. Typically these difficulties result in poor registration of multi-temporal DEMs, which degrade subsequent measurements of surface change. This is one of the fundamental limitations of accessing archival datasets. In this research a least squares surface matching technique is introduced to overcome these challenges and achieve reliable registration of multi-temporal DEMs. Historical imagery acquired in the 1960s for two Antarctic Peninsula glaciers is processed to extract DEMs, which are subsequently compared to DEMs derived from modern ASTER satellite data and aerial photography. Through the surface matching approach, it is shown that the registration accuracy of the historical and modern-day datasets can be improved significantly. This enables precise quantification of glacier elevation changes on a multi-decadal time scale. Frontal glacier surface lowering of up to 50 m was observed over the last ~4 decades. Results of this study allow a better understanding of historical volumetric glacier changes of the Antarctic Peninsula and provide an efficient and automated method for improved DEM co-registration.

Road and rail networks are essential components of national infrastructures, underpinning the economy, and facilitating the mobility of goods and the human workforce. Earthwork slopes such as cuttings and embankments are primary components, and their reliability is of fundamental importance. However, instability and failure can occur, through processes such as landslides. Monitoring the condition of earthworks is a costly and continuous process for network operators, and currently, geospatial data is largely underutilised. The research presented here addresses this by combining airborne laser scanning and multispectral aerial imagery to develop a methodology for assessing landslide hazard. This is based on the extraction of key slope stability variables from the remotely sensed data. The methodology is implemented through numerical modelling, which is parameterised with the slope stability information, simulated climate conditions, and geotechnical properties. This allows determination of slope stability (expressed through the factor of safety) for a range of simulated scenarios. Regression analysis is then performed in order to develop a functional model relating slope stability to the input variables. The remotely sensed raster datasets are robustly re-sampled to two-dimensional cross-sections to facilitate meaningful interpretation of slope behaviour and mapping of landslide hazard. Results are stored in a geodatabase for spatial analysis within a GIS environment. For a test site located in England, UK, results have shown the utility of the approach in deriving practical hazard assessment information. Outcomes were compared to the network operator’s hazard grading data, and show general agreement. The utility of the slope information was also assessed with respect to auto-population of slope geometry, and found to deliver significant improvements over the network operator’s existing field-based approaches.

Structural monitoring requires instruments which can provide high precision and accuracy, reliable measurements at good temporal resolution and rapid processing speeds. Long-term campaigns and flexible structures are regarded as two of the most challenging subjects in monitoring engineering structures. Long-term monitoring in civil engineering is generally considered to be labourintensive and financially expensive and it can take significant effort to arrange the necessary human resources, transportation and equipment maintenance. When dealing with flexible structure monitoring, it is of paramount importance that any monitoring equipment used is able to carry out rapid sampling. Low cost, automated, photogrammetric techniques therefore have the potential to become routinely viable for monitoring non-rigid structures. This research aims to provide a photogrammetric solution for long-term flexible structural monitoring purposes. The automated approach was achieved using low-cost imaging devices (mobile phones) to replace traditional image acquisition stations and substantially reduce the equipment costs. A self-programmed software package was developed to deal with the hardware-software integration and system operation. In order to evaluate the performance of this low-cost monitoring system, a shaking table experiment was undertaken. Different network configurations and target sizes were used to determine the best configuration. A large quantity of image data was captured by four DSLR cameras and four mobile phone cameras respectively. These image data were processed using photogrammetric techniques to calculate the final results for the system evaluation.

Permafrost-affected ecosystems of the Arctic–boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ∼80 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl).

Abstract Background Despite the promise of wearable sensors for both rehabilitation research and clinical care, these technologies pose significant burden on data collectors and analysts. Investigations of factors that may influence the wearable sensor data processing pipeline are needed to support continued use of these technologies in rehabilitation research and integration into clinical care settings. The purpose of this study was to investigate the effect of one such factor, sleep, on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment and across a two-day wearing period. Methods This was a secondary analysis of data collected during a prospective, longitudinal cohort study (n = 127 individuals, 62 with upper limb impairment and 65 without). Participants wore a wearable sensor on each wrist for 48 h. Five upper limb sensor variables were calculated over the full wear period (sleep included) and with sleep time removed (sleep excluded): preferred time, non-preferred time, use ratio, non-preferred magnitude and its standard deviation. Linear mixed effects regression was used to quantify the effect of sleep on each sensor variable and determine if the effect differed between people with and without upper limb impairment and across a two-day wearing period. Results There were significant differences between sleep included and excluded for the variables preferred time (p

The article reflects the achieved results of research on methodological provisions related to the application of economic models in the digital transformation of industrial holdings. The methodology of using economic models under consideration made it possible to identify the target orientation and the main tasks of digital transformation. The characteristic features of the proposed methodology should be considered: generalization of the signs of digital transformation; argumentation of distinctive properties that affect the development of economic models in the digital transformation of industrial holdings. The studied aspects make it possible to clarify the conceptual provisions of the classical theory of digital transformation of economic systems, in terms of studying problematic situations arising in the process of digital transformation of industrial holdings, as well as substantiating concepts such as modeling, digital transformation, models of digital transformation of industrial systems, to highlight the main stages of development of digital transformation of industrial systems. As part of the methodological implementation of the proposed methodology, an instrumental approach is considered that allows to systematize the tools of digital transformation of industrial systems in the context of digital business models, digital technologies and platform solutions, as well as to argue the key features of each of the tools. The advantage of the instrumental approach is the possibility of studying the established economic models of digital transformation and substantiating the author’s model of digital transformation of an industrial holding. The proposed model allows you to: optimize the configuration of manufactured products and processes of its life cycle in terms of optimizing the added value of an industrial holding; integrate systems and processes, as well as the value chain of an industrial holding, the components of which are: optimization of production, environmental safety, cost reduction, asset productivity, productivity improvement, profitability growth and increase in the value of the holding.

Abstract Animals can quickly adapt learned movements to external perturbations, and their existing motor repertoire likely influences their ease of adaptation. Long-term learning causes lasting changes in neural connectivity, which shapes the activity patterns that can be produced during adaptation. Here, we examined how a neural population’s existing activity patterns, acquired through de novo learning, affect subsequent adaptation by modeling motor cortical neural population dynamics with recurrent neural networks. We trained networks on different motor repertoires comprising varying numbers of movements, which they acquired following various learning experiences. Networks with multiple movements had more constrained and robust dynamics, which were associated with more defined neural ‘structure’—organization in the available population activity patterns. This structure facilitated adaptation, but only when the changes imposed by the perturbation were congruent with the organization of the inputs and the structure in neural activity acquired during de novo learning. These results highlight trade-offs in skill acquisition and demonstrate how different learning experiences can shape the geometrical properties of neural population activity and subsequent adaptation.

Abstract Background The potential effect modification of sleep on the relationship between anxiety and elevated blood pressure (BP) in pregnancy is understudied. We evaluated the relationship between anxiety, insomnia, and short sleep duration, as well as any interaction effects between these variables, on BP during pregnancy. Methods This was a prospective pilot cohort of pregnant people between 23 to 36 weeks’ gestation at a single institution between 2021 and 2022. Standardized questionnaires were used to measure clinical insomnia and anxiety. Objective sleep duration was measured using a wrist-worn actigraphy device. Primary outcomes were systolic (SBP), diastolic (DBP), and mean (MAP) non-invasive BP measurements. Separate sequential multivariable linear regression models fit with generalized estimating equations (GEE) were used to separately assess associations between anxiety (independent variable) and each BP parameter (dependent variables), after adjusting for potential confounders (Model 1). Additional analyses were conducted adding insomnia and the interaction between anxiety and insomnia as independent variables (Model 2), and adding short sleep duration and the interaction between anxiety and short sleep duration as independent variables (Model 3), to evaluate any moderating effects on BP parameters. Results Among the 60 participants who completed the study, 15 (25%) screened positive for anxiety, 11 (18%) had subjective insomnia, and 34 (59%) had objective short sleep duration. In Model 1, increased anxiety was not associated with increases in any BP parameters. When subjective insomnia was included in Model 2, increased DBP and MAP was significantly associated with anxiety (DBP: β 6.1, p = 0.01, MAP: β 6.2 p

Abstract Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Silt-rich meltwater plume deposits (MPDs) analyzed from marine sediment cores have elucidated relationships that are clearly connected, yet difficult to constrain, between subglacial hydrology, ice-marginal landforms, and grounding-zone retreat patterns for several glacial catchments. Few attempts have been made to infer details of subglacial hydrology, such as flow regime, geometry of drainage pathways, and mode(s) of sediment transport through time, from grain-scale characteristics of MPDs. Using sediment samples from MPD, till, and grounding-zone proximal diamicton collected offshore of six modern and relict glacial catchments in both hemispheres, we examine grain shape distributions and microtextures (collectively, grain micromorphology) of the silt fraction to explore whether grains are measurably altered from their subglacial sources via meltwater action. We find that 75 % of all imaged grains (n = 9400) can be described by 25 % of the full range of measured shape morphometrics, indicating grain shape homogenization through widespread and efficient abrasive processes in subglacial environments. Although silt grains from MPDs exhibit edge rounding more often than silt grains from tills, grain surface textures indicative of fluvial transport (e.g., v-shaped percussions) occur in only a modest number of grains. Furthermore, MPD grain surfaces retain several textures consistent with transport beneath glacial ice (e.g., straight or arcuate steps, (sub)linear fractures) in comparable abundances to till grains. Significant grain shape alteration in MPDs compared to their till sources is observed in sediments from glacial regions where (1) high-magnitude, potentially catastrophic meltwater drainage events are inferred from marine sediment records and (2) submarine landforms suggest supraglacial melt contributed to the subglacial hydrological budget. This implies that quantifiable grain shape alteration in MPDs could reflect a combination of high-energy flow of subglacial meltwater, persistent sediment entrainment, and/or long sediment transport distances through subglacial drainage pathways. Integrating grain micromorphology into analysis of MPDs in site-specific studies could therefore aid in distinguishing periods of persistent, well-connected subglacial discharge from periods of sluggish or disorganized drainage. In the wider context of deglacial marine sedimentary and bathymetric records, a grain micromorphological approach may bolster our ability to characterize ice response to subglacial meltwater transmission through time. This work additionally demonstrates that glacial and fluvial surface textures are retained on silt-sized quartz grains in adequate amounts for microtexture analysis, which has heretofore been conducted exclusively on the sand fraction. Therefore, grain microtextures can be examined on silt-rich glaciogenic deposits that contain little to no sand as a means to evaluate sediment transport processes.

Abstract Background It is crucial to include a wide range of the population in clinical trials for the outcome to be applicable in real-world settings. Existing literature indicates that under-served groups, including disabled people, have been excluded from participating in clinical trials without justification. Exclusion from clinical trials exacerbates disparities in healthcare and diminishes the benefits for excluded populations. Therefore, this study was conducted to investigate potential obstacles that prevent disabled people from participating in clinical trials in the United Kingdom (UK). Methods The study was carried out through an explanatory sequential mixed methods design. The Imperial Clinical Trials Unit devised and implemented an online questionnaire-based survey (with open/closed-ended questions) and an online focus group discussion. The target population were disabled people, family members/carers of disabled people and staff involved in clinical trials, whereupon the sample was recruited by convenience sampling methods via posters and emails through various networks. The Qualtrics XM survey system was used as the host platform for the online survey, and Microsoft Teams was used for an online focus group discussion. The focus group discussion was conducted to gain a deeper understanding of the themes identified from the survey responses. We analysed responses to the survey via descriptive analysis and used thematic analysis to synthesise the free-text answers from the survey and focus group discussion. Results We received 45 responses to the survey questionnaire and 5 disabled people took part in a focus group discussion. Our findings highlighted the differences between the perspectives of researchers and those “being researched” and different types of barriers experienced by disabled people: opportunity barriers (inadequate recruitment strategy and ambiguous eligibility criteria), awareness barriers (perception of disability) and acceptance/refusal barriers (available support and adjustment, and sharing of trial results). Conclusion Our findings support perspectives drawn from the Ford Framework regarding the need to consider all barriers, not just up to the point of enrolment into trials but also beyond the point of inclusion in clinical trials. We support calls for the introduction of legislation on including disabled people in clinical trials, implementation of industry/community-wide participatory approaches and the development of guidelines, a combined public–private approach.

Abstract As patients continue to live longer from diseases that predispose them to right ventricular (RV) dysfunction or failure, many more patients will require surgery for acute or chronic health issues. Because RV dysfunction results in significant perioperative morbidity if not adequately assessed or managed, understanding appropriate assessment and treatments is important in preventing subsequent morbidity and mortality in the perioperative period. In light of the epidemiology of right heart disease, a working knowledge of right heart anatomy and physiology and an understanding of the implications of right-sided heart function for perioperative care are essential for perioperative practitioners. However, a significant knowledge gap exists concerning this topic. This manuscript is one part of a collection of papers from the PeriOperative Quality Initiative (POQI) IX Conference focusing on “Current Perspectives on the Right Heart in the Perioperative Period.” This review aims to provide perioperative clinicians with an essential understanding of right heart physiology by answering five key questions on this topic and providing an explanation of seven fundamental concepts concerning right heart physiology.

Summary: Background: Insulin resistance (IR) is an important risk factor for multiple chronic diseases, increasing mortality and reducing life expectancy. The associations between emerging surrogates for IR, triglyceride-glucose index (TyG) and TyG-related indicators, with all-cause mortality and life expectancy in middle-aged and older patients in primary care are unclear. Methods: This study originated from the Polish primary care cohort LIPIDOGRAM2015, including patients aged ≥45 years. Baseline fasting triglycerides and fasting glucose were used to derive TyG. Other TyG-related indicators included TyG-adjusted body mass index (TyG-BMI), TyG-adjusted waist circumference (TyG-WC), TyG-adjusted waist-to-hip, and TyG-adjusted waist-to-height. In this longitudinal analysis, we assessed associations between TyG-related indicators with total all-cause mortality, premature (age at death ≤75 years) all-cause mortality and years of life lost (YLL). Findings: We included 10,688 patients (mean age 61.8 ± 9.3 years; 63.5% female). Cumulative total and premature all-cause mortality were 7.2% and 4.6%, respectively, during 5.7 years (IQR 5.6–5.7) of follow-up. Lowest (Q1) and highest quartile (Q4) of TyG-BMI and TyG-WC were associated with total all-cause mortality (second quartile [Q2]: reference; TyG-BMI: Q1: aHR 1.33, 95% CI 1.07–1.65, Q4: aHR 1.28, 95% CI 1.03–1.58; TyG-WC: Q1: aHR 1.44, 95% CI 1.14–1.82, Q4: aHR 1.29, 95% CI 1.04–1.59), similar results for premature all-cause mortality. Within age 45–80 years, compared with Q2 and third quartile, YLL were 4.49 and 5.46 years for TyG-BMI Q1 and Q4, respectively, 3.24 and 5.31 years for TyG-WC Q1 and Q4, respectively. Interpretation: TyG-BMI and TyG-WC demonstrated a U-shaped association with total and premature all-cause mortality. Low and high levels of TyG-BMI and TyG-WC were associated with reduced life expectancy. Despite the relatively short follow-up period, significant associations were still observed, but longer follow-up studies are required to further explore these relationships. Funding: Polish Lipid Association, College of Family Physician in Poland, Valeant in Poland.