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Aquaporin-1 (Aqp1), a water channel, has garnered significant interest for cell-based medicine and in vivo synthetic biology due to its ability to be genetically encoded to produce magnetic resonance signals by increasing the rate of water diffusion in cells. However, concerns regarding the effects of Aqp1 overexpression and increased membrane diffusivity on cell physiology have limited its widespread use as a deep-tissue reporter. In this study, we present evidence that Aqp1 generates strong diffusion-based magnetic resonance signals without adversely affecting cell viability or morphology in diverse cell lines derived from mice and humans. Our findings indicate that Aqp1 overexpression does not induce ER stress, which is frequently associated with heterologous expression of membrane proteins. Furthermore, we observed that Aqp1 expression had no detrimental effects on native biological activities, such as phagocytosis, immune response, insulin secretion, and tumor cell migration in the analyzed cell lines. These findings should serve to alleviate any lingering safety concerns regarding the utilization of Aqp1 as a genetic reporter and should foster its broader application as a noninvasive reporter for in vivo studies.

The study applied the Technology Acceptance Model (TAM) to assess trust in artificial intelligence (AI) within the US commercial aviation industry. It found that ease of use and usefulness positively influenced attitudes toward AI, impacting users’ intention to use it. However, perceived usefulness did not significantly affect meaning, purpose, and mood positively correlated with trust in AI. In some cases, higher perceived usefulness led to lower trust, indicating the complexity of trust in AI in aviation. This study highlights the importance of trust in AI and suggests the need for further investigation in the aviation context. It also recommends expanding the framework of trustworthy AI to consider factors like algorithm transparency, explainability, and fairness for a more comprehensive understanding.

Determining movement parameters for pest insects such as tephritid fruit flies is critical to developing models which can be used to increase the effectiveness of surveillance and control strategies. In this study, harmonic radar was used to track wild-caught male Queensland fruit flies (Qflies), Bactrocera tryoni, in papaya fields. Experiment 1 continuously tracked single flies which were prodded to induce movement. Qfly movements from this experiment showed greater mean squared displacement than predicted by both a simple random walk (RW) or a correlated random walk (CRW) model, suggesting that movement parameters derived from the entire data set do not adequately describe the movement of individual Qfly at all spatial scales or for all behavioral states. This conclusion is supported by both fractal and hidden Markov model (HMM) analysis. Lower fractal dimensions (straighter movement paths) were observed at larger spatial scales (> 2.5 m) suggesting that Qflies have qualitatively distinct movement at different scales. Further, a two-state HMM fit the observed movement data better than the CRW or RW models. Experiment 2 identified individual landing locations, twice a day, for groups of released Qflies, demonstrating that flies could be tracked over longer periods of time.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC.METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials.RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1.CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of

PR, IFPRI3; 1 Fostering Climate-Resilient and Sustainable Food Supply; 2 Promoting Healthy Diets and Nutrition for all; GCAN, Natural Resources and Resilience (NRR); Transformation Strategies, There is growing recognition that water insecurity – the inability to reliably access sufficient water for all household uses – is commonly experienced globally and has myriad adverse consequences for human well-being. The role of water insecurity in food insecurity and diet quality, however, has received minimal attention. Data are from panel surveys conducted during 2020–21 among adults involved in smallholder agriculture in Niger (n = 364, 3 rounds), Nigeria (n = 501, 5 rounds), Senegal (n = 501, 5 rounds), and Ghana (n = 543, 5 rounds). We hypothesized that household water insecurity (measured using the brief Household Water Insecurity Experiences Scale) would be associated with greater individual food insecurity (using 5 of the 8 Food Insecurity Experiences Scale items) and lower dietary diversity (using the Minimum Dietary Diversity Score for Women). At baseline, 37.1% of individuals were living in water-insecure households and of these, 90.6% had some experience of food insecurity. In multilevel mixed-effects regressions, individuals living in water-insecure households had 1.67 (95% CI: 1.47, 1.89) times higher odds of reporting any food insecurity experience and were estimated to consume 0.38-fewer food groups (95% CI: -0.50, -0.27) than those living in water-secure households. Experiences with suboptimal water access and use are associated with poor nutrition. The pathways by which water insecurity impacts nutrition should be identified. Global and national food and nutrition security policies could be strengthened by monitoring and developing strategies to address household water insecurity.

Background: Osteoarthritis (OA), the leading cause of disability among adults, has no cure and is associated with significant comorbidities. The premise of this randomized clinical trial is that, in a population at risk, a 48-month program of dietary weight loss and exercise will result in less incident structural knee OA compared to control. Methods/design: The Osteoarthritis Prevention Study (TOPS) is a Phase III, assessor-blinded, 48-month, parallel 2 arm, multicenter randomized clinical trial designed to reduce the incidence of structural knee OA. The study objective is to assess the effects of a dietary weight loss, exercise, and weight-loss maintenance program in preventing the development of structural knee OA in females at risk for the disease. TOPS will recruit 1230 ambulatory, community dwelling females with obesity (Body Mass Index (BMI) ​≥ ​30 ​kg/m2) and aged ≥50 years with no radiographic (Kellgren-Lawrence grade ≤1) and no magnetic resonance imaging (MRI) evidence of OA in the eligible knee, with no or infrequent knee pain. Incident structural knee OA (defined as tibiofemoral and/or patellofemoral OA on MRI) assessed at 48-months from intervention initiation using the MRI Osteoarthritis Knee Score (MOAKS) is the primary outcome. Secondary outcomes include knee pain, 6-min walk distance, health-related quality of life, knee joint loading during gait, inflammatory biomarkers, and self-efficacy. Cost effectiveness and budgetary impact analyses will determine the value and affordability of this intervention. Discussion: This study will assess the efficacy and cost effectiveness of a dietary weight loss, exercise, and weight-loss maintenance program designed to reduce incident knee OA.Trial registration: ClinicalTrials.gov Identifier: NCT05946044.

Water distribution networks (WDNs) require large capital investment and ongoing operational costs, resulting in their optimisation being a highly researched field. Despite the benefits tanks bring to networks, most optimisation models omit them as decision variables due to the complexity they can introduce to heuristic approaches. This paper addresses the least-cost optimisation of WDN design and operation through the development and application of the Small-network Configurator for Optimising Pump Energy consumption (SCOPE). The SCOPE algorithm incorporates pipes, pumps and tanks as decision variables and solves the optimisation problem through an iterative approach that pairs EPANET simulation results with subsequent hydraulic calculations to converge on the pumping and storage configuration which yields the lowest energy consumption. The SCOPE output can then be used to seed further optimisation techniques. This approach has been tested on the synthetic Nametown and real-life Dili networks and demonstrated annual cost savings of 10% and 25%, respectively.

One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressing such exploration challenges. In this paper, we demonstrate a system for large-scale exploration using a team of aerial and ground robots. Our system uses semantics as lingua franca, and relies on fully opportunistic communications. We highlight the unique challenges from this approach, explain our system architecture and showcase lessons learned during our experiments. All our code is open-source, encouraging researchers to use it and build upon., Comment: 6 pages, 5 figres

Concern that synthetic food dyes may impact behavior in children prompted a review by the California Office of Environmental Health Hazard Assessment (OEHHA). OEHHA conducted a systematic review of the epidemiologic research on synthetic food dyes and neurobehavioral outcomes in children with or without identified behavioral disorders (particularly attention and activity). We also conducted a search of the animal toxicology literature to identify studies of neurobehavioral effects in laboratory animals exposed to synthetic food dyes. Finally, we conducted a hazard characterization of the potential neurobehavioral impacts of food dye consumption. We identified 27 clinical trials of children exposed to synthetic food dyes in this review, of which 25 were challenge studies. All studies used a cross-over design and most were double blinded and the cross-over design was randomized. Sixteen (64%) out of 25 challenge studies identified some evidence of a positive association, and in 13 (52%) the association was statistically significant. These studies support a relationship between food dye exposure and adverse behavioral outcomes in children. Animal toxicology literature provides additional support for effects on behavior. Together, the human clinical trials and animal toxicology literature support an association between synthetic food dyes and behavioral impacts in children. The current Food and Drug Administration (FDA) acceptable daily intakes are based on older studies that were not designed to assess the types of behavioral effects observed in children. For four dyes where adequate dose-response data from animal and human studies were available, comparisons of the effective doses in studies that measured behavioral or brain effects following exposure to synthetic food dyes indicate that the basis of the ADIs may not be adequate to protect neurobehavior in susceptible children. There is a need to re-evaluate exposure in children and for additional research to provide

We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike other ML models that use DFT data, our models directly predict the local density of states (LDOS) of the electronic structure. This provides several advantages, including access to multiple observables such as the electronic density and electronic total free energy. Moreover, our models account for both the electronic and ionic temperatures independently, making them ideal for applications like laser-heating of matter. We validate the efficacy of our LDOS-based models on a metallic test system. They accurately capture energetic effects induced by variations in ionic and electronic temperatures over a broad temperature range, even when trained on a subset of these temperatures. These findings open up exciting opportunities for investigating the electronic structure of materials under both ambient and extreme conditions.

Naval leadership has identified the lack of logistics experience as a critical force vulnerability in the Unrestricted Line (URL) community officer corps. They believe this gap will limit the Navy’s ability to sustain operations in contested and constrained environments. As the United States enters a new era of strategic competition with near-peer competitors, increasing the logistical knowledge and educational experiences of the URL community is of paramount importance. Peacetime naval operations have dominated the operational landscape for several decades with logistical support mirroring that static and predictable environment. Strategic competition will challenge the established logistic concepts and those concepts must also change. This project develops case studies to equip URL officers with the necessary mindset to approach and analyze complex logistic concerns. Each case study touches on specific logistics topics, incorporates broader logistical implications, and uses various investigative and analytic tools to help solve real-world problems. Equally important, this study will build a stronger foundation that will make the warfighter more combat effective and further enhance his or her grasp of operational and tactical environments., NPS Naval Research Program, This project was funded in part by the NPS Naval Research Program., Lieutenant Commander, United States Navy, Lieutenant Commander, United States Navy, Approved for public release. Distribution is unlimited.

The role of macroalgae (seaweed) as a global contributor to carbon drawdown within marine sediments – termed ‘blue carbon’ – remains uncertain and controversial. While studies are needed to validate the potential for macroalgal‑carbon sequestration in marine and coastal sediments, fundamental questions regarding the fate of dislodged macroalgal biomass need to be addressed. Evidence suggests macroalgal biomass may be advected and deposited within other vegetated coastal ecosystems and down to the deep ocean; however, contributions to near-shore sediments within coastal waters remain uncertain. In this study a combination of eDNA metabarcoding and surficial sediment sampling informed by seabed mapping from different physical environments was used to test for the presence of macroalgal carbon in near-shore coastal sediments in south-eastern Australia, and the physical factors influencing patterns of macroalgal transport and deposition. DNA products for a total of 68 macroalgal taxa, representing all major macroalgal groups (Phaeophyceae, Rhodophyta, and Chlorophyta) were successfully detected at 112 near-shore locations. These findings confirm the potential for macroalgal biomass to be exported into near-shore sediments and suggest macroalgal carbon donors could be both speciose and diverse. Modelling suggested that macroalgal transport and deposition, and total organic carbon (TOC), are influenced by complex interactions between several physical environmental factors including water depth, sediment grain size, wave orbital velocity, current speed, current direction, and the extent of the infralittoral zone around depositional areas. Extrapolation of the optimised model was used to predict spatial patterns of macroalgal deposition and TOC across the coastline and to identify potentially important carbon sinks. This study builds on recent studies providing empirical evidence for macroalgal biomass deposits in near-shore sediments, and a framework for predicting the spa

PurposeTo investigate management trends for American Association for the Surgery of Trauma (AAST) grade V renal trauma with focus on non-operative management.MethodsWe used prospectively collected data as part of the Multi-institutional Genito-Urinary Trauma Study (MiGUTS). We included patients with grade V renal trauma according to the AAST Injury Scoring Scale 2018 update. All cases submitted by participating centers with radiology images available were independently reviewed to confirm renal trauma grade. Management was classified as expectant, conservative (minimally invasive, endoscopic or percutaneous procedures), or operative (renal-related surgery).ResultsEighty patients were included, 25 of whom had complete imaging and had independent confirmation of AAST grade V renal trauma. Median age was 35 years (Interquartile range (IQR) 25-50) and 23 (92%) had blunt trauma. Ten patients (40%) were managed operatively with nephrectomy. Conservative management was used in nine patients (36%) of which six received angioembolization and three had a stent or drainage tube placed. Expectant management was followed in six (24%) patients. Transfusion requirements were progressively higher with groups requiring more aggressive treatment, and injury characteristics differed significantly across management groups in terms of hematoma size and laceration size. Vascular contrast extravasation was more likely in operatively managed patients though a statistically significant association was not found.ConclusionSuccessful use of nonoperative management for grade V injuries is used for a substantial subset of patients. Lower transfusion requirement and less severe injury radiologic phenotype appear to be important characteristics delineating this group.

BackgroundLiquid biopsies have become an integral part of cancer management as minimally invasive options to detect molecular and genetic changes. However, current options show poor sensitivity in peritoneal carcinomatosis (PC). Novel exosome-based liquid biopsies may provide critical information on these challenging tumors. In this initial feasibility analysis, we identified an exosome gene signature of 445 genes (ExoSig445) from colon cancer patients, including those with PC, that is distinct from healthy controls.MethodsPlasma exosomes from 42 patients with metastatic and non-metastatic colon cancer and 10 healthy controls were isolated and verified. RNAseq analysis of exosomal RNA was performed and differentially expressed genes (DEGs) were identified by the DESeq2 algorithm. The ability of RNA transcripts to discriminate control and cancer cases was assessed by principal component analysis (PCA) and Bayesian compound covariate predictor classification. An exosomal gene signature was compared with tumor expression profiles of The Cancer Genome Atlas.ResultsUnsupervised PCA using exosomal genes with greatest expression variance showed stark separation between controls and patient samples. Using separate training and test sets, gene classifiers were constructed capable of discriminating control and patient samples with 100% accuracy. Using a stringent statistical threshold, 445 DEGs fully delineated control from cancer samples. Furthermore, 58 of these exosomal DEGs were found to be overexpressed in colon tumors.ConclusionsPlasma exosomal RNAs can robustly discriminate colon cancer patients, including patients with PC, from healthy controls. ExoSig445 can potentially be developed as a highly sensitive liquid biopsy test in colon cancer.

The Workgroup on Interactive Systems in Healthcare (WISH) connects academic and industry researchers across human-computer interaction, medical informatics, health informatics, digital health, and beyond to foster a community around innovations in consumer and medical health and wellbeing. The WISH Symposium at CHI 2023 will regather the HCI health and wellbeing research community for the first in-person community meeting in four years, allowing us to discuss and disseminate findings, methods, and approaches towards understanding and creating interactive health and wellbeing systems. We will continue the tradition of providing mentoring opportunities for early- and mid-career researchers, ranging from undergraduates to post-PhD, to establish future generations of scholars in the area. This will be the tenth WISH meeting, following a successful tradition of workshops at relevant venues including CHI over the past decade.

We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike other ML models that use DFT data, our models directly predict the local density of states (LDOS) of the electronic structure. This provides several advantages, including access to multiple observables such as the electronic density and electronic total free energy. Moreover, our models account for both the electronic and ionic temperatures independently, making them ideal for applications like laser-heating of matter. We validate the efficacy of our LDOS-based models on a metallic test system. They accurately capture energetic effects induced by variations in ionic and electronic temperatures over a broad temperature range, even when trained on a subset of these temperatures. These findings open up exciting opportunities for investigating the electronic structure of materials under both ambient and extreme conditions.

We characterize decreasing impatience, a common behavioral phenomenon in intertemporal choice. Discount factors that display decreasing impatience are characterized through a convexity axiom for investments at fixed interest rates. Then we show that they are equivalent to a geometric average of generalized quasi-hyperbolic discount rates. Finally, they emerge through parimutuel preference aggregation of exponential discount factors.

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the submitted predictions. While the overall ability to predict three-dimensional protein structures continues to impress, reproducing uncommon features not previously observed in experimental structures is still a challenge. Furthermore, instances with conformational flexibility and large multimeric complexes highlight the need for novel scoring strategies to better emphasize biologically relevant structural regions. Looking ahead, closer integration of computational and experimental techniques will play a key role in determining the next challenges to be unraveled in the field of structural molecular biology.

Background: Increasing research suggests that gait abnormalities can be a risk factor for Alzheimer’s Disease (AD). Notably, there is growing evidence highlighting this risk factor in individuals with amnestic Mild Cognitive Impairment (aMCI), however further studies are needed. The aim of this study is to analyze cognitive tests results and brain-related measures over time in aMCI and examine how the presence of gait abnormalities (neurological or orthopedic) or normal gait affects these trends. Additionally, we sought to assess the significance of gait and gait-related measures as prognostic indicators for the progression from aMCI to AD dementia, comparing those who converted to AD with those who remained with a stable aMCI diagnosis during the follow-up. Methods: Four hundred two individuals with aMCI from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were included. Robust linear mixed-effects models were used to study the impact of gait abnormalities on a comprehensive neuropsychological battery over 36 months while controlling for relevant medical variables at baseline. The impact of gait on brain measures was also investigated. Lastly, the Cox proportional-hazards model was used to explore the prognostic relevance of abnormal gait and neuropsychological associated tests. Results: While controlling for relevant covariates, we found that gait abnormalities led to a greater decline over time in attention (DSST) and global cognition (MMSE). Intriguingly, psychomotor speed (TMT-A) and divided attention (TMT-B) declined uniquely in the abnormal gait group. Conversely, specific AD global cognition tests (ADAS-13) and auditory-verbal memory (RAVLT immediate recall) declined over time independently of gait profile. All the other cognitive tests were not significantly affected by time or by gait profile. In addition, we found that ventricles size increased faster in the abnormal gait group compared to the normal gait group. In terms of prognosis, abno

The flight deck of a commercial aircraft has become progressively digitized and operates in multiple modes with displays and indicators that require increasing levels of comprehension. Examining several aspects of cognitive processing is important to understand how threats to safety might occur and what actions might be taken to reduce severity or to eliminate the threat altogether. This paper presents the elements of cognition to consider, relevant characteristics of working memory and cognitive processing speed, types of disruptions and how they are addressed, results from overload or confusion, and the need for effective cognitive resilience to recover and repair the threat. Data from Aviation Safety Reporting System (ASRS) databases indicate 30% of cases could represent a distinct threat of cognitive overload. These are evaluated to identify sources and likelihood for surprise disruptions and to assess the potential of cognitive resilience. Adaptation of the CRMTEM model is considered for potential application in training and investigations.

Ecosystem Service (ES) toolkits are increasingly used to quantify and visualize the benefits gained from Nature-based-solutions (NBS) but modules for hydrology are often absent, or if present they lack meaningful hydrological functionality or validation. This leads to gaps in the evidence base required by decision makers. To bridge the gap between such limitations and more complex hydrological models this paper presents a hydrologically based NBS model compatible with spatial ES toolkits. The approach ‘Adapted Nature-based-solutions Rational Method’ (ANaRM) is based on the Rational Method, widely used in hydrology. We apply this model to the city of Birmingham, England, to validate its performance and to analyse the effects of different NBS scenarios. The validated ANaRM model provided robust estimates of peak flow using design storm rainfall. It proved capable of simulating the hydrological effects of NBS such as land use change from urban to green, or installation of SuDS and ponds. Results suggest ponds are found most effective for achieving peak flow reduction in channels and are the best option for mitigating fluvial flooding downstream. Reduction in localised runoff and pluvial flooding is best achieved by converting impervious surfaces such as buildings, hardstanding and roads to green solutions such as green roofs, permeable pavements and greenspace. This paper highlights the importance of considering the spatial effects of urban NBS on hydrology, and that these can be captured with relatively simple modelling approaches such as ANaRM. Its ease of use means it suits any level of user looking to represent the flood mitigation aspect of NBS spatially and has high potential as part of any ES toolkit focused on representing the spatial effects of NBS on ecosystem services.

We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike other ML models that use DFT data, our models directly predict the local density of states (LDOS) of the electronic structure. This provides several advantages, including access to multiple observables such as the electronic density and electronic total free energy. Moreover, our models account for both the electronic and ionic temperatures independently, making them ideal for applications like laser-heating of matter. We validate the efficacy of our LDOS-based models on a metallic test system. They accurately capture energetic effects induced by variations in ionic and electronic temperatures over a broad temperature range, even when trained on a subset of these temperatures. These findings open up exciting opportunities for investigating the electronic structure of materials under both ambient and extreme conditions.

# Data and Scripts for "Machine learning the electronic structure of matter across temperatures" This dataset contains data and calculation scripts for the publication "Machine learning the electronic structure of matter across temperatures". Its goal is to enable interested parties to reproduce the experiments we have carried out. ## Prerequesites The following software versions are needed for the python scripts: - `python`: 3.8.x - `mala`: 1.2.0 - `numpy`: 1.23.0 (lower version may work) Further, make sure you have downloaded additional data such as local pseudopotentials and training data. ## Contents - `data_analysis/`: Contains scripts contain useful functions to reproduce the analysis carried out on the provided data. - `model_training/`: Contains scripts that allow the training and testing of the models discussed in the accompanying publication. - `trained_models`: Contains the models discussed in the accompanying publication. Per data set, five models with different random initializations were trained. re> 

The role of macroalgae (seaweed) as a global contributor to carbon drawdown within marine sediments – termed ‘blue carbon’ – remains uncertain and controversial. While studies are needed to validate the potential for macroalgal‑carbon sequestration in marine and coastal sediments, fundamental questions regarding the fate of dislodged macroalgal biomass need to be addressed. Evidence suggests macroalgal biomass may be advected and deposited within other vegetated coastal ecosystems and down to the deep ocean; however, contributions to near-shore sediments within coastal waters remain uncertain. In this study a combination of eDNA metabarcoding and surficial sediment sampling informed by seabed mapping from different physical environments was used to test for the presence of macroalgal carbon in near-shore coastal sediments in south-eastern Australia, and the physical factors influencing patterns of macroalgal transport and deposition. DNA products for a total of 68 macroalgal taxa, representing all major macroalgal groups (Phaeophyceae, Rhodophyta, and Chlorophyta) were successfully detected at 112 near-shore locations. These findings confirm the potential for macroalgal biomass to be exported into near-shore sediments and suggest macroalgal carbon donors could be both speciose and diverse. Modelling suggested that macroalgal transport and deposition, and total organic carbon (TOC), are influenced by complex interactions between several physical environmental factors including water depth, sediment grain size, wave orbital velocity, current speed, current direction, and the extent of the infralittoral zone around depositional areas. Extrapolation of the optimised model was used to predict spatial patterns of macroalgal deposition and TOC across the coastline and to identify potentially important carbon sinks. This study builds on recent studies providing empirical evidence for macroalgal biomass deposits in near-shore sediments, and a framework for predicting the spa

Diphyllin is a natural arylnaphtalide lignan extracted from tropical plants of particular importance in traditional Chinese medicine. This compound has been described as a potent inhibitor of vacuolar (H+)ATPases and hence of the endosomal acidification process that is required by numerous enveloped viruses to trigger their respective viral infection cascades after entering host cells by receptor-mediated endocytosis. Accordingly, we report here a revised, updated, and improved synthesis of diphyllin, and demonstrate its antiviral activities against a panel of enveloped viruses from Flaviviridae, Phenuiviridae, Rhabdoviridae, and Herpesviridae families. Diphyllin is not cytotoxic for Vero and BHK-21 cells up to 100 mu M and exerts a sub-micromolar or low-micromolar antiviral activity against tick-borne encephalitis virus, West Nile virus, Zika virus, Rift Valley fever virus, rabies virus, and herpes-simplex virus type 1. Our study shows that diphyllin is a broad-spectrum host cell-targeting antiviral agent that blocks the replication of multiple phylogenetically unrelated enveloped RNA and DNA viruses. In support of this, we also demonstrate that diphyllin is more than just a vacuolar (H+)ATPase inhibitor but may employ other antiviral mechanisms of action to inhibit the replication cycles of those viruses that do not enter host cells by endocytosis followed by low pH-dependent membrane fusion., Difyllin je přírodní lignanový arylnaftalid extrahovaný z tropických rostlin používaný v tradiční čínské medicíně. Tato sloučenina byla popsána jako silný inhibitor vakuolárních (H+)ATPáz a tudíž endosomálního acidifikačního procesu, který je vyžadován mnoha obalenými viry ke spuštění jejich příslušných virových infekčních kaskád po vstupu do hostitelských buněk receptorem zprostředkovanou endocytózou. V souladu s tím zde uvádíme revidovanou, aktualizovanou a zlepšenou syntézu difyllinu a demonstrujeme jeho antivirové aktivity proti panelu obalených virů z čeledí Flaviviridae, Phenuiviridae, Rhabdoviridae a Herpesviridae. Difyllin není cytotoxický pro buňky Vero a BHK-21 do 100 uM a vykazuje submikromolární nebo nízkomikromolární antivirovou aktivitu proti viru klíšťové encefalitidy, viru West Nile, viru Zika, viru horečky Rift Valley, viru vztekliny, a herpes simplex virus typu 1. Naše studie ukazuje, že difyllin je širokospektrální antivirové činidlo zacílené na hostitelskou buňku, které blokuje replikaci mnoha fylogeneticky nepříbuzných obalených RNA a DNA virů. Na podporu toho také demonstrujeme, že difyllin je více než jen vakuolární inhibitor (H+)ATPázy, ale může využívat jiné antivirové mechanismy účinku k inhibici replikačních cyklů těch virů, které nevstupují do hostitelských buněk endocytózou následovanou nízkým pH- závislá membránová fúze.

Arcus is a concept for a probe class mission to deliver high-resolution FUV and X-ray spectroscopy. For X-rays, it combines cost-effective silicon pore optics (SPO) with high-throughput critical-angle transmission (CAT) gratings to achieve $R> 3000$ in a bandpass from 12-50 Angstroem. We show in detail how the X-ray and the UV spectrographs (XRS and UVS) on Arcus will be aligned to each other. For XRS we present ray-tracing studies to derive performance characteristics such as the spectral resolving power and effective area, study the effect of misalignments on the performance, and conclude that most tolerances can be achieved with mechanical means alone. We also present an estimate of the expected on-orbit background., Comment: submitted to SPIE UV, X-Ray, and Gamma-Ray Space Instrumentation for Astronomy XXIII (2023)

In the outskirts of galaxy clusters, entropy profiles measured from X-ray observations of the hot intracluster medium (ICM) drops off unexpectedly. One possible explanation for this effect is gas clumping, where pockets of cooler and denser structures within the ICM are present. Current observatories are unable to directly detect these hypothetical gas clumps. One of the science drivers of the proposed STAR-X observatory is to resolve these or similar structures. Its high spatial resolution, large effective area, and low instrumental background make STAR-X ideal for directly detecting and characterizing clumps and diffuse emission in cluster outskirts. The aim of this work is to simulate observations of clumping in clusters to determine how well STAR-X will be able to detect clumps, as well as what clumping properties reproduce observed entropy profiles. This is achieved by using yt, pyXSIM, SOXS, and other tools to inject ideally modeled clumps into three-dimensional models derived from actual clusters using their observed profiles from other X-ray missions. Radial temperature and surface brightness profiles are then extracted from mock observations using concentric annuli. We find that in simulated observations for STAR-X, a parameter space of clump properties exists where gas clumps can be successfully identified using wavdetect and masked, and are able to recover the true cluster profiles. This demonstrates that STAR-X could be capable of detecting substructure in the outskirts of nearby clusters and that the properties of both the outskirts and the clumps will be revealed., Comment: This article has been accepted for publication in RAS Techniques and Instruments \c{opyright}: 2023 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. The version of record is available online at: https://academic.oup.com/rasti/article/doi/10.1093/rasti/rzad042/7258824

AXIS is a Probe-class mission concept that will provide high-throughput, high-spatial-resolution X-ray spectral imaging, enabling transformative studies of high-energy astrophysical phenomena. To take advantage of the advanced optics and avoid photon pile-up, the AXIS focal plane requires detectors with readout rates at least 20 times faster than previous soft X-ray imaging spectrometers flying aboard missions such as Chandra and Suzaku, while retaining the low noise, excellent spectral performance, and low power requirements of those instruments. We present the design of the AXIS high-speed X-ray camera, which baselines large-format MIT Lincoln Laboratory CCDs employing low-noise pJFET output amplifiers and a single-layer polysilicon gate structure that allows fast, low-power clocking. These detectors are combined with an integrated high-speed, low-noise ASIC readout chip from Stanford University that provides better performance than conventional discrete solutions at a fraction of their power consumption and footprint. Our complementary front-end electronics concept employs state of the art digital video waveform capture and advanced signal processing to deliver low noise at high speed. We review the current performance of this technology, highlighting recent improvements on prototype devices that achieve excellent noise characteristics at the required readout rate. We present measurements of the CCD spectral response across the AXIS energy band, augmenting lab measurements with detector simulations that help us understand sources of charge loss and evaluate the quality of the CCD backside passivation technique. We show that our technology is on a path that will meet our requirements and enable AXIS to achieve world-class science., Comment: 17 pages, 11 figures, submitted to Proceedings of SPIE Optics + Photonics 2023

Age and gender differences in narcissism have been studied often. However, considering the rich history of narcissism research accompanied by its diverging conceptualizations, little is known about age and gender differences across various narcissism measures. The present study investigated age and gender differences and their interactions across eight widely used narcissism instruments (i.e., Narcissistic Personality Inventory, Hypersensitive Narcissism Scale, Dirty Dozen, Psychological Entitlement Scale, Narcissistic Personality Disorder Symptoms from the Diagnostic and Statistical Manual of Mental Disorders, Version IV, Narcissistic Admiration and Rivalry Questionnaire-Short Form, Single-Item Narcissism Scale, and brief version of the Pathological Narcissism Inventory). The findings of Study 1 (N = 5,736) revealed heterogeneity in how strongly the measures are correlated. Some instruments loaded clearly on one of the three factors proposed by previous research (i.e., Neuroticism, Extraversion, Antagonism), while others cross-loaded across factors and in distinct ways. Cross-sectional analyses using each measure and meta-analytic results across all measures (Study 2) with a total sample of 270,029 participants suggest consistent linear age effects (random effects meta-analytic effect of r = -.104), with narcissism being highest in young adulthood. Consistent gender differences also emerged (random effects meta-analytic effect was -.079), such that men scored higher in narcissism than women. Quadratic age effects and Age × Gender effects were generally very small and inconsistent. We conclude that despite the various conceptualizations of narcissism, age and gender differences are generalizable across the eight measures used in the present study. However, their size varied based on the instrument used. We discuss the sources of this heterogeneity and the potential mechanisms for age and gender differences.

Observations of galaxy cluster mergers provide insights on the particle acceleration and heating mechanisms taking place within the intracluster medium. Mergers form shocks that propagate through the plasma, which result in shock/cold fronts in the X-ray, and radio halos and/or relics in the radio regime. The connection between these tracers and the mechanisms driving non-thermal processes, such as inverse Compton, are not well understood. ZWCL 1856.8 is one of the few known double radio relic systems that originate from nearly head-on collisions observed close to the plane of the sky. For the first time, we study NuSTAR and Chandra observations of such a system that contains both relics within their field of view. The spectro-imaging analyses results of the system suggest weak shock fronts with $\mathcal{M}$ numbers within 2$\sigma$ of the radio derived values, and provide evidence of inverse Compton emission at both relic sites. Our findings have great uncertainties due to the shallow exposure times available. Deeper NuSTAR and Chandra data are crucial for studying the connection of the radio and X-ray emission features and for constraining the thermal vs. non-thermal emission contributions in this system. We also present methods and approaches on how to investigate X-ray properties of double relic systems by taking full advantage of the complementary properties of NuSTAR and Chandra missions., Comment: Accepted for publication in ApJ. 14 pages, 9 figures, 3 tables

Stellar and black hole feedback heat and disperse surrounding cold gas clouds, launching gas flows off circumnuclear and galactic disks and producing a dynamic interstellar medium. On large scales bordering the cosmic web, feedback drives enriched gas out of galaxies and groups, seeding the intergalactic medium with heavy elements. In this way, feedback shapes galaxy evolution by shutting down star formation and ultimately curtailing the growth of structure after the peak at redshift 2-3. To understand the complex interplay between gravity and feedback, we must resolve both the key physics within galaxies and map the impact of these processes over large scales, out into the cosmic web. The Advanced X-ray Imaging Satellite (AXIS) is a proposed X-ray probe mission for the 2030s with arcsecond spatial resolution, large effective area, and low background. AXIS will untangle the interactions of winds, radiation, jets, and supernovae with the surrounding ISM across the wide range of mass scales and large volumes driving galaxy evolution and trace the establishment of feedback back to the main event at cosmic noon., Comment: 29 pages, 18 figures; this white paper is part of a series commissioned for the AXIS Probe mission concept

The Advanced X-ray Imaging Satellite (AXIS) is a Probe-class concept that will build on the legacy of the Chandra X-ray Observatory by providing low-background, arcsecond-resolution imaging in the 0.3-10 keV band across a 450 arcminute$^2$ field of view, with an order of magnitude improvement in sensitivity. AXIS utilizes breakthroughs in the construction of lightweight segmented X-ray optics using single-crystal silicon, and developments in the fabrication of large-format, small-pixel, high readout rate CCD detectors with good spectral resolution, allowing a robust and cost-effective design. Further, AXIS will be responsive to target-of-opportunity alerts and, with onboard transient detection, will be a powerful facility for studying the time-varying X-ray universe, following on from the legacy of the Neil Gehrels (Swift) X-ray observatory that revolutionized studies of the transient X-ray Universe. In this paper, we present an overview of AXIS, highlighting the prime science objectives driving the AXIS concept and how the observatory design will achieve these objectives., Comment: Published in Proceedings of SPIE Optics & Photonics 2023, San Diego

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by cl

We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike other ML models that use DFT data, our models directly predict the local density of states (LDOS) of the electronic structure. This provides several advantages, including access to multiple observables such as the electronic density and electronic total free energy. Moreover, our models account for both the electronic and ionic temperatures independently, making them ideal for applications like laser-heating of matter. We validate the efficacy of our LDOS-based models on a metallic test system. They accurately capture energetic effects induced by variations in ionic and electronic temperatures over a broad temperature range, even when trained on a subset of these temperatures. These findings open up exciting opportunities for investigating the electronic structure of materials under both ambient and extreme conditions.

BackgroundIncreasing research suggests that gait abnormalities can be a risk factor for Alzheimer's Disease (AD). Notably, there is growing evidence highlighting this risk factor in individuals with amnestic Mild Cognitive Impairment (aMCI), however further studies are needed. The aim of this study is to analyze cognitive tests results and brain-related measures over time in aMCI and examine how the presence of gait abnormalities (neurological or orthopedic) or normal gait affects these trends. Additionally, we sought to assess the significance of gait and gait-related measures as prognostic indicators for the progression from aMCI to AD dementia, comparing those who converted to AD with those who remained with a stable aMCI diagnosis during the follow-up.MethodsFour hundred two individuals with aMCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were included. Robust linear mixed-effects models were used to study the impact of gait abnormalities on a comprehensive neuropsychological battery over 36 months while controlling for relevant medical variables at baseline. The impact of gait on brain measures was also investigated. Lastly, the Cox proportional-hazards model was used to explore the prognostic relevance of abnormal gait and neuropsychological associated tests.ResultsWhile controlling for relevant covariates, we found that gait abnormalities led to a greater decline over time in attention (DSST) and global cognition (MMSE). Intriguingly, psychomotor speed (TMT-A) and divided attention (TMT-B) declined uniquely in the abnormal gait group. Conversely, specific AD global cognition tests (ADAS-13) and auditory-verbal memory (RAVLT immediate recall) declined over time independently of gait profile. All the other cognitive tests were not significantly affected by time or by gait profile. In addition, we found that ventricles size increased faster in the abnormal gait group compared to the normal gait group. In terms of prognosis, abnormal gai

Determining the structure of a protein has been a decades-long open question. A protein's three-dimensional structure often poses nontrivial computation costs, when classical simulation algorithms are utilized. Advances in the transformer neural network architecture -- such as AlphaFold2 -- achieve significant improvements for this problem, by learning from a large dataset of sequence information and corresponding protein structures. Yet, such methods only focus on sequence information; other available prior knowledge, such as protein crystallography and partial structure of amino acids, could be potentially utilized. To the best of our knowledge, we propose the first transformer-based model that directly utilizes protein crystallography and partial structure information to predict the electron density maps of proteins. Via two new datasets of peptide fragments (2-residue and 15-residue) , we demonstrate our method, dubbed \texttt{CrysFormer}, can achieve accurate predictions, based on a much smaller dataset size and with reduced computation costs.

Multi-robot collaboration in large-scale environments with limited-sized teams and without external infrastructure is challenging, since the software framework required to support complex tasks must be robust to unreliable and intermittent communication links. In this work, we present MOCHA (Multi-robot Opportunistic Communication for Heterogeneous Collaboration), a framework for resilient multi-robot collaboration that enables large-scale exploration in the absence of continuous communications. MOCHA is based on a gossip communication protocol that allows robots to interact opportunistically whenever communication links are available, propagating information on a peer-to-peer basis. We demonstrate the performance of MOCHA through real-world experiments with commercial-off-the-shelf (COTS) communication hardware. We further explore the system's scalability in simulation, evaluating the performance of our approach as the number of robots increases and communication ranges vary. Finally, we demonstrate how MOCHA can be tightly integrated with the planning stack of autonomous robots. We show a communication-aware planning algorithm for a high-altitude aerial robot executing a collaborative task while maximizing the amount of information shared with ground robots. The source code for MOCHA and the high-altitude UAV planning system is available open source: http://github.com/KumarRobotics/MOCHA, http://github.com/KumarRobotics/air_router., Comment: 7 pages, 8 figures

BackgroundHousehold food insecurity (FI) and water insecurity (WI) are prevalent public health issues that can co-occur. Few studies have concurrently assessed their associations with health outcomes, particularly among people living with HIV.ObjectivesWe aimed to investigate the associations between FI and WI and how they relate to physical and mental health.MethodsFood-insecure adult smallholder farmers living with HIV in western Kenya were recruited to participate in a cluster-randomized controlled trial of a multisectoral agricultural and asset loan intervention. We used baseline data on experiences of FI (using the Household Food Insecurity Access Scale, range: 0-27) and WI (using a modified scale developed for this region, range: 0-51) in the prior month (n = 716). Outcomes included probable depression (using the Hopkins Symptom Checklist), fatigue and diarrhea in the prior month, and overall mental and physical health (using the Medical Outcomes Study HIV Health Survey, range: 0-100). We first assessed Pearson correlations between FI, WI, and sociodemographic characteristics. We then developed 3 regressions for each health outcome (control variables and FI; control variables and WI; control variables, FI, and WI) and compared model fit indexes.ResultsCorrelations between household FI, WI, and wealth were low, meaning they measure distinct constructs. FI and WI were associated with numerous physical and mental health outcomes; accounting for both resource insecurities typically provided the best model fit. For instance, when controlling for FI, each 10-point higher WI score was associated with a 6.42-point lower physical health score (P < 0.001) and 2.92 times greater odds of probable depression (P < 0.001).ConclusionsAssessing both FI and WI is important for correctly estimating their relation with health outcomes. Interventions that address food- and water-related issues among persons living with HIV concurrently will like

Reliable access to safe and acceptable water in sufficient quantities (i.e., water security) is important for medication adherence and limiting pathogen exposure, yet prior studies have only considered the role of food security as a social determinant of HIV-related health. Therefore, the objective of this analysis was to assess the relationships between household water insecurity and HIV-related outcomes among adults living with HIV in western Kenya (N = 716). We conducted a cross-sectional analysis of baseline data from Shamba Maisha (NCT02815579), a cluster randomized controlled trial of a multisectoral agricultural and asset loan intervention. Baseline data were collected from June 2016 to December 2017. We assessed associations between water insecurity and HIV-related outcomes, adjusting for clinical and behavioral confounders, including food insecurity. Each five-unit higher household water insecurity score (range: 0-51) was associated with 1.21 higher odds of having a viral load ≥ 1000 copies/mL (95% CI 1.07, 1.36) and 1.26 higher odds of AIDS-defining illness (95% CI 1.11, 1.42). Household water insecurity was not associated with CD4 cell count (B: 0.27; 95% CI -3.59, 13.05). HIV treatment and support programs should consider assessing and addressing water insecurity in addition to food insecurity to optimize HIV outcomes.

Introduction: Chest pain is a common reason for ambulance transport. Acute coronary syndrome (ACS) and pulmonary embolism (PE) risk assessments, such as history, electrocardiogram, age, risk factors (HEAR); Emergency Department Assessment of Chest Pain Score (EDACS); Pulmonary Embolism Rule-out Criteria (PERC); and revised Geneva score, are well validated for emergency department (ED) use but have not been translated to the prehospital setting. The objectives of this study were to evaluate the 1) prehospital completion rate and 2) inter-rater reliability of chest pain risk assessments.Methods: We conducted a prospective observational cohort study in two emergency medical services (EMS) agencies (April 18, 2018 – January 2, 2019). Adults with acute, non-traumatic chest pain without ST-elevation myocardial infarction or unstable vital signs were accrued. Paramedics were trained to use the HEAR, EDACS, PERC, and revised Geneva score assessments. A subset of patients (a priori goal of N = 250) also had the four risk assessments completed by their treating clinicians in the ED, who were blinded to the EMS risk assessments. Outcomes were 1) risk assessments completion rate and 2) inter-rater reliability between EMS and ED assessments. An a priori goal for completion rate was set as >75%. We computed kappa with corresponding 95% confidence intervals (CI) for each risk assessment as a measure of inter-rater reliability. Acceptable agreement was defined a priori as kappa ≥ 0.60.Results: During the study period, 837 patients with acute chest pain were accrued. The median age was 54 years, interquartile range 43-66, with 53% female and 51% Black. Completion rates for each risk assessment were above goal: the HEAR score was completed on 95.1% (796/837), EDACS on 92.0% (770/837), PERC on 89.4% (748/837), and revised Geneva score on 90.7% (759/837) of patients. We assessed agreement in a subgroup of 260 patients. The HEAR score had a kappa of 0.51 (95% CI, 0.41- 0.61); EDACS w

The Wide Field Imager (WFI) flying on Athena will usher in the next era of studying the hot and energetic Universe. WFI observations of faint, diffuse sources will be limited by uncertainty in the background produced by high-energy particles. These particles produce easily identified "cosmic-ray tracks" along with signals from secondary photons and electrons generated by particle interactions with the instrument. The signal from these secondaries is identical to the X-rays focused by the optics, and cannot be filtered without also eliminating these precious photons. As part of a larger effort to understand the WFI background, we here present results from a study of background-reduction techniques that exploit the spatial correlation between cosmic-ray particle tracks and secondary events. We use Geant4 simulations to generate a realistic particle background, sort this into simulated WFI frames, and process those frames in a similar way to the expected flight and ground software to produce a WFI observation containing only particle background. The technique under study, Self Anti-Coincidence or SAC, then selectively filters regions of the detector around particle tracks, turning the WFI into its own anti-coincidence detector. We show that SAC is effective at improving the systematic uncertainty for observations of faint, diffuse sources, but at the cost of statistical uncertainty due to a reduction in signal. If sufficient pixel pulse-height information is telemetered to the ground for each frame, then this technique can be applied selectively based on the science goals, providing flexibility without affecting the data quality for other science. The results presented here are relevant for any future silicon-based pixelated X-ray imaging detector, and could allow the WFI and similar instruments to probe to truly faint X-ray surface brightness., Comment: 38 pages, 27 figures. Accepted for publication in JATIS. arXiv admin note: text overlap with arXiv:2012.01347

Future high-resolution imaging X-ray observatories may require detectors with both fine spatial resolution and high quantum efficiency at relatively high X-ray energies (>5keV). A silicon imaging detector meeting these requirements will have a ratio of detector thickness to pixel size of six or more, roughly twice that of legacy imaging sensors. This implies greater diffusion of X-ray charge packets. We investigate consequences for sensor performance, reporting charge diffusion measurements in a fully-depleted, 50um thick, back-illuminated CCD with 8um pixels. We are able to measure the size distributions of charge packets produced by 5.9 keV and 1.25 keV X-rays in this device. We find that individual charge packets exhibit a gaussian spatial distribution, and determine the frequency distribution of event widths for a range of internal electric field strength levels. We find a standard deviation for the largest charge packets, which occur near the entrance window, of 3.9um. We show that the shape of the event width distribution provides a clear indicator of full depletion and infer the relationship between event width and interaction depth. We compare measured width distributions to simulations. We compare traditional, 'sum-above-threshold' algorithms for event amplitude determination to 2D gaussian fitting of events and find better spectroscopic performance with the former for 5.9 keV events and comparable results at 1.25 keV. The reasons for this difference are discussed. We point out the importance of read noise driven detection thresholds in spectral resolution, and note that the derived read noise requirements for mission concepts such as AXIS and Lynx may be too lax to meet spectral resolution requirements. While we report measurements made with a CCD, we note that they have implications for the performance of high aspect-ratio silicon active pixel sensors as well., Comment: 36 pages, 10 figures, accepted by JATIS

Macroscale additive manufacturing has seen significant advances recently, but these advances are not yet realized for the bottom-up formation of nanoscale polymeric features. We describe a platform technology for creating crosslinked polymer features using rapid surface-initiated crosslinking and versatile macrocrosslinkers, delivered by a microfluidic-coupled atomic force microscope known as FluidFM. A crosslinkable polymer containing norbornene moieties is delivered to a catalyzed substrate where polymerization occurs, resulting in extremely rapid chemical curing of the delivered material. Due to the living crosslinking reaction, construction of lines and patterns with multiple layers is possible, showing quantitative material addition from each deposition in a method analogous to fused filament fabrication, but at the nanoscale. Print parameters influenced printed line dimensions, with the smallest lines being 450 nm across with a vertical layer resolution of 2 nm. This nanoscale 3D printing platform of reactive polymer materials has applications for device fabrication, optical systems and biotechnology.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sandin, S. A., Alcantar, E., Clark, R., de Leon, R., Dilrosun, F., Edwards, C. B., Estep, A. J., Eynaud, Y., French, B. J., Fox, M. D., Grenda, D., Hamilton, S. L., Kramp, H., Marhaver, K. L., Miller, S. D., Roach, T. N. F., Seferina, G., Silveira, C. B., Smith, J. E., Zgliczynski, B. J., & Vermeij, M. J. A. Benthic assemblages are more predictable than fish assemblages at an island scale. Coral Reefs, 41, (2022.): 1031–1043, https://doi.org/10.1007/s00338-022-02272-5., Decades of research have revealed relationships between the abundance of coral reef taxa and local conditions, especially at small scales. However, a rigorous test of covariation requires a robust dataset collected across wide environmental or experimental gradients. Here, we surveyed spatial variability in the densities of major coral reef functional groups at 122 sites along a 70 km expanse of the leeward, forereef habitat of Curaçao in the southern Caribbean. These data were used to test the degree to which spatial variability in community composition could be predicted based on assumed functional relationships and site-specific anthropogenic, physical, and ecological conditions. In general, models revealed less power to describe the spatial variability of fish biomass than cover of reef builders (R2 of best-fit models: 0.25 [fish] and 0.64 [reef builders]). The variability in total benthic cover of reef builders was best described by physical (wave exposure and reef relief) and ecological (turf algal height and coral recruit density) predictors. No metric of anthropogenic pressure was related to spatial variation in reef builder cover. In contrast, total fish biomass showed a consistent (albeit weak) association with anthropogenic predictors (fishing and diving pressure). As is typical of most environmental gradients, the spatial patterns of both fish biomass density and reef builder cover were spatially autocorrelated. Residuals from the best-fit model for fish biomass retained a signature of spatial autocorrelation while the best-fit model for reef builder cover removed spatial autocorrelation, thus reinforcing our finding that environmental predictors were better able to describe the spatial variability of reef builders than that of fish biomass. As we seek to understand spatial variability of coral reef communities at the scale of most management units (i.e., at kilometer- to island-scales), distinct and scale-dependent perspectives will be needed when consi, This research and the larger efforts of Blue Halo Curacao were supported by funding from the Waitt Institute and with permissions from the Government of Curacao, Ministry of Health, Environment, and Nature. Field logistics were further supported by the Waitt Institute vessel crew, CARMABI Foundation, The Dive Shop Curacao, and Dive Charter Curacao.

Decades of research have revealed relationships between the abundance of coral reef taxa and local conditions, especially at small scales. However, a rigorous test of covariation requires a robust dataset collected across wide environmental or experimental gradients. Here, we surveyed spatial variability in the densities of major coral reef functional groups at 122 sites along a 70 km expanse of the leeward, forereef habitat of Curaçao in the southern Caribbean. These data were used to test the degree to which spatial variability in community composition could be predicted based on assumed functional relationships and site-specific anthropogenic, physical, and ecological conditions. In general, models revealed less power to describe the spatial variability of fish biomass than cover of reef builders (R2 of best-fit models: 0.25 [fish] and 0.64 [reef builders]). The variability in total benthic cover of reef builders was best described by physical (wave exposure and reef relief) and ecological (turf algal height and coral recruit density) predictors. No metric of anthropogenic pressure was related to spatial variation in reef builder cover. In contrast, total fish biomass showed a consistent (albeit weak) association with anthropogenic predictors (fishing and diving pressure). As is typical of most environmental gradients, the spatial patterns of both fish biomass density and reef builder cover were spatially autocorrelated. Residuals from the best-fit model for fish biomass retained a signature of spatial autocorrelation while the best-fit model for reef builder cover removed spatial autocorrelation, thus reinforcing our finding that environmental predictors were better able to describe the spatial variability of reef builders than that of fish biomass. As we seek to understand spatial variability of coral reef communities at the scale of most management units (i.e., at kilometer- to island-scales), distinct and scale-dependent perspectives will be needed when consi

Introduction: Chest pain is a common reason for ambulance transport. Acute coronary syndrome (ACS) and pulmonary embolism (PE) risk assessments, such as history, electrocardiogram, age, risk factors (HEAR); Emergency Department Assessment of Chest Pain Score (EDACS); Pulmonary Embolism Rule-out Criteria (PERC); and revised Geneva score, are well validated for emergency department (ED) use but have not been translated to the prehospital setting. The objectives of this study were to evaluate the 1) prehospital completion rate and 2) inter-rater reliability of chest pain risk assessments.Methods: We conducted a prospective observational cohort study in two emergency medical services (EMS) agencies (April 18, 2018 – January 2, 2019). Adults with acute, non-traumatic chest pain without ST-elevation myocardial infarction or unstable vital signs were accrued. Paramedics were trained to use the HEAR, EDACS, PERC, and revised Geneva score assessments. A subset of patients (a priori goal of N = 250) also had the four risk assessments completed by their treating clinicians in the ED, who were blinded to the EMS risk assessments. Outcomes were 1) risk assessments completion rate and 2) inter-rater reliability between EMS and ED assessments. An a priori goal for completion rate was set as >75%. We computed kappa with corresponding 95% confidence intervals (CI) for each risk assessment as a measure of inter-rater reliability. Acceptable agreement was defined a priori as kappa ≥ 0.60.Results: During the study period, 837 patients with acute chest pain were accrued. The median age was 54 years, interquartile range 43-66, with 53% female and 51% Black. Completion rates for each risk assessment were above goal: the HEAR score was completed on 95.1% (796/837), EDACS on 92.0% (770/837), PERC on 89.4% (748/837), and revised Geneva score on 90.7% (759/837) of patients. We assessed agreement in a subgroup of 260 patients. The HEAR score had a kappa of 0.51 (95% CI, 0.41- 0.61); EDACS w

Reliable access to safe and acceptable water in sufficient quantities (i.e., water security) is important for medication adherence and limiting pathogen exposure, yet prior studies have only considered the role of food security as a social determinant of HIV-related health. Therefore, the objective of this analysis was to assess the relationships between household water insecurity and HIV-related outcomes among adults living with HIV in western Kenya (N = 716). We conducted a cross-sectional analysis of baseline data from Shamba Maisha (NCT02815579), a cluster randomized controlled trial of a multisectoral agricultural and asset loan intervention. Baseline data were collected from June 2016 to December 2017. We assessed associations between water insecurity and HIV-related outcomes, adjusting for clinical and behavioral confounders, including food insecurity. Each five-unit higher household water insecurity score (range: 0-51) was associated with 1.21 higher odds of having a viral load ≥ 1000 copies/mL (95% CI 1.07, 1.36) and 1.26 higher odds of AIDS-defining illness (95% CI 1.11, 1.42). Household water insecurity was not associated with CD4 cell count (B: 0.27; 95% CI -3.59, 13.05). HIV treatment and support programs should consider assessing and addressing water insecurity in addition to food insecurity to optimize HIV outcomes.