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Both the Southern Annular Mode (SAM) and El Niño–Southern Oscillation (ENSO) are critical factors contributing to Antarctic sea ice variability on interannual time scales. However, their joint effects on sea ice are complex and remain unclear for each austral season. In this study, satellite sea ice concentration (SIC) observations and atmospheric reanalysis data are utilized to assess the impacts of combined SAM and ENSO on seasonal Antarctic sea ice changes. The joint SAM–ENSO impacts on southern high latitudes are principally controlled by the strength and position of the wave activity and associated atmospheric circulation anomalies affected by their interactions. In-phase events (La Niña/positive SAM and El Niño/negative SAM) are characterized with an SIC dipole located in the Weddell/Bellingshausen Seas and Amundsen/Ross Seas, while out-of-phase events (El Niño/positive SAM and La Niña/negative SAM) experience significant SIC anomalies in the Indian Ocean and western Pacific Ocean. Sea ice budget analyses are conducted to separate the dynamic and thermodynamic contributions inducing the sea ice intensification anomalies. The results show that in-phase intensification anomalies also display a pattern similar to the SIC dipole and are mainly driven by the direct thermodynamic forcing at the ice edge and thermodynamic responses to meridional sea ice drift in the inner pack, especially in autumn and winter. Dynamic processes caused by zonal sea ice drift also play an important role during out-of-phase conditions in addition to the same mechanisms during in-phase conditions.

Sea level rise contributions from the Pine Island Glacier (PIG) are strongly modulated by the backstress that its floating extension – Pine Island Ice Shelf (PIIS) – exerts on the adjoining grounded ice. The front of PIIS has recently retreated significantly via calving, and satellite and theoretical analyses have suggested further retreat is inevitable. As well as inducing an instantaneous increase in ice flow, retreat of the PIIS front may result in increased ocean melting, by relaxing the topographic barrier to warm ocean water that is currently provided by a prominent seabed ridge. Recently published research (Bradley and others, 2022a) has shown that PIIS may exhibit a strong melting response to calving, with melting close to the PIG grounding line always increasing with ice front retreat. Here, we summarise this research and, additionally, place the results in a glaciological context by comparing the impact of melt-induced and ice-dynamical changes in the ice shelf thinning rate. We find that while PIG is expected to experience rapid acceleration in response to further ice front retreat, the mean instantaneous thinning response is set primarily by changes in melting, rather than ice dynamics. Overall, further ice front retreat is expected to lead to enhanced ice-shelf thinning, with potentially detrimental consequences for ice shelf stability.

The ice shelf–ocean boundary current has an important control on heat delivery to the base of an ice shelf. Climate and regional models that include a representation of ice shelf cavities often use a coarse grid, and results have a strong dependence on resolution near the ice shelf–ocean interface. This study models the ice shelf–ocean boundary current with a nonhydrostatic z-level configuration at turbulence-permitting resolution (1 m). The z-level model performs well when compared against state-of-the-art large-eddy simulations, showing its capability in representing the correct physics. We show that theoretical results from a one-dimensional model with parameterized turbulence reproduce the z-level model results to a good degree, indicating possible utility as a turbulence closure. The one-dimensional model evolves to a state of marginal instability, and we use the z-level model to demonstrate how this is represented in three dimensions. Instabilities emerge that regulate the strength of the pycnocline and coexist with persistent Ekman rolls, which are identified prior to the flow becoming intermittently unstable. When resolution of the z-level model is degraded to understand the gridscale dependencies, the degradation is dominated by the established problem of excessive numerical diffusion. We show that at intermediate resolutions (2–4 m), the boundary layer structure can be partially recovered by tuning diffusivities. Last, we compare replacing prescribed melting with interactive melting that is dependent on the local ocean conditions. Interactive melting results in a feedback such that the system evolves more slowly, which is exaggerated at lower resolution.

In molecular phylogenetics, partition models and mixture models provide different approaches to accommodating heterogeneity in genomic sequencing data. Both types of models generally give a superior fit to data than models that assume the process of sequence evolution is homogeneous across sites and lineages. The Akaike Information Criterion (AIC), an estimator of Kullback–Leibler divergence, and the Bayesian Information Criterion (BIC) are popular tools to select models in phylogenetics. Recent work suggests that AIC should not be used for comparing mixture and partition models. In this work, we clarify that this difficulty is not fully explained by AIC misestimating the Kullback–Leibler divergence. We also investigate the performance of the AIC and BIC at comparing amongst mixture models and amongst partition models. We find that under nonstandard conditions (i.e. when some edges have small expected number of changes), AIC underestimates the expected Kullback–Leibler divergence. Under such conditions, AIC preferred the complex mixture models and BIC preferred the simpler mixture models. The mixture models selected by AIC had a better performance in estimating the edge length, while the simpler models selected by BIC performed better in estimating the base frequencies and substitution rate parameters. In contrast, AIC and BIC both prefer simpler partition models over more complex partition models under nonstandard conditions, despite the fact that the more complex partition model was the generating model. We also investigated how mispartitioning (i.e., grouping sites that have not evolved under the same process) affects both the performance of partition models compared with mixture models and the model selection process. We found that as the level of mispartitioning increases, the bias of AIC in estimating the expected Kullback–Leibler divergence remains the same, and the branch lengths and evolutionary parameters estimated by partition models become less accurate. We recommend that researchers are cautious when using AIC and BIC to select among partition and mixture models; other alternatives, such as cross-validation and bootstrapping, should be explored, but may suffer similar limitations [AIC; BIC; mispartitioning; partitioning; partition model; mixture model].

Background Imaging migraine premonitory studies show increased midbrain activation consistent with the ventral tegmental area, an area involved in pain modulation and hedonic feeding. We investigated ventral tegmental area pharmacological modulation effects on trigeminovascular processing and consequent glycemic levels, which could be involved in appetite changes in susceptible migraine patients. Methods Serotonin and pituitary adenylate cyclase-activating polypeptide receptors immunohistochemistry was performed in ventral tegmental area parabrachial pigmented nucleus of male Sprague Dawley rats. In vivo trigeminocervical complex neuronal responses to dura mater nociceptive electrical stimulation, and facial mechanical stimulation of the ophthalmic dermatome were recorded. Changes in trigeminocervical complex responses following ventral tegmental area parabrachial pigmented nucleus microinjection of glutamate, bicuculline, naratriptan, pituitary adenylate cyclase-activating polypeptide-38 and quinpirole were measured, and blood glucose levels assessed pre- and post-microinjection. Results Glutamatergic stimulation of ventral tegmental area parabrachial pigmented nucleus neurons reduced nociceptive and spontaneous trigeminocervical complex neuronal firing. Naratriptan, pituitary adenylate cyclase-activating polypeptide-38 and quinpirole inhibited trigeminovascular spontaneous activity, and trigeminocervical complex neuronal responses to dural-evoked electrical and mechanical noxious stimulation. Trigeminovascular sensory processing through modulation of the ventral tegmental area parabrachial pigmented nucleus resulted in reduced circulating glucose levels. Conclusion Pharmacological modulation of ventral tegmental area parabrachial pigmented nucleus neurons elicits changes in trigeminovascular sensory processing. The interplay between ventral tegmental area parabrachial pigmented nucleus activity and the sensory processing by the trigeminovascular system may be relevant to understand associated sensory and homeostatic symptoms in susceptible migraine patients.

Perennial plant species from water-limiting environments (including climates of extreme drought, heat, and freezing temperatures) have evolved traits that allow them to tolerate these conditions. As such, traits that are associated with water stress may show evidence of adaptation to climate when compared among closely related species inhabiting contrasting climatic conditions. In this study, we tested whether key hydraulic traits linked to drought stress, including the vulnerability of leaves to embolism (P50 leaf) and the minimum diffusive conductance of shoots (gmin) were associated with climatic characteristics of fourteen Tasmanian eucalypt species from sites that vary in precipitation and temperature. Across species, greater cavitation resistance (more negative P50 leaf) was associated with increasing aridity and decreasing minimum temperature. In contrast, gmin showed strong associations with aridity only. Among these Tasmanian eucalypts, evidence suggests that trait variation is influenced by both cold and dry conditions, highlighting the need to consider both aspects when exploring adaptive trait-climate relationships.

Over the past decade, Antarctic sea ice extent exhibited a sequence of record maxima, followed by a rapid decline in 2015/16, and record minima since. In this presentation, we show that this sudden and remarkable ice loss marks an abrupt transition from a high to a low ice state that cannot be explained by year-to-year variability. Instead, it is most likely associated with a longer term variability arising from ice–ocean feedbacks. The abrupt transition was preceded by a multi-decadal increase in persistence and variance of the sea ice anomalies, an increasing upper Southern Ocean density stratification, and an accumulation of heat at the subsurface; suggesting a decoupling of the surface from the subsurface ocean. During this period, the sea ice anomalies shifted from being structured predominantly regionally and seasonally to a largely circumpolar and interannual regime. In 2015/16, the upper ocean density stratification in the ice-covered region suddenly weakened, leading to a release of heat from the subsurface, contributing to the sea ice decline during winter. Our analysis suggests that the sudden sea ice loss in 2015/16, and the persisting low ice conditions since, arose from a systematic change in the physical state of the coupled circumpolar ice–ocean system. This change will have wide implications for global climate, ecosystems, and the Antarctic Ice Sheet.

Mass loss from the West Antarctic Ice Sheet is dominated by glaciers draining into the Amundsen Sea Embayment (ASE), yet the impact of anomalous precipitation on the mass balance of the ASE is poorly known. Here we present a 25-year (1996–2021) record of ASE input-output mass balance and evaluate how two periods of anomalous precipitation affected its sea level contribution. Since 1996, the ASE has lost 3331 ± 424 Gt ice, contributing 9.2 ± 1.2 mm to global sea level. Overall, surface mass balance anomalies contributed little (7.7%) to total mass loss; however, two anomalous precipitation events had larger, albeit short-lived, impacts on rates of mass change. During 2009–2013, persistently low snowfall led to an additional 51 ± 4 Gt yr−1 mass loss in those years (contributing positively to the total loss of 195 ± 4 Gt yr−1). Contrastingly, extreme precipitation in the winters of 2019 and 2020 decreased mass loss by 60 ± 16 Gt yr−1 during those years (contributing negatively to the total loss of 107 ± 15 Gt yr−1). These results emphasise the important impact of extreme snowfall variability on the short-term sea level contribution from West Antarctica.

The development of clinically meaningful, objective, and quantitative methods for assessing the performance of ultrasound imaging systems represents a continuing area of interest. One approach has been to image phantoms with randomly distributed spherical voids.The objectives of this study were: (1) to explore the potential of using relatively high-volume fraction random spherical void (RSV) phantoms as an approach for quantitatively assessing the performance of ultrasound imaging systems; (2) to identify potential metrics that can be used to provide quantitative assessments of images obtained from relatively high-volume fraction RSV phantoms; and (3) to demonstrate changes in the quantitative metrics that can occur as image features are degraded.A series (10 each) of computer-simulated RSV phantoms with a range of RSV volume fractions (0.05, 0.15, and 0.25) were generated. To determine the number of image planes necessary to provide robust measurements, a series of consecutive planes (ranging from 1 to 150) within each type of simulated phantom were analyzed. The observed circular cross-section radii histogram distributions (representing the intersection of each plane with the local distribution of spherical voids) were compared with the theoretical histogram distribution. Simulated phantom images were produced by adding speckle and degradation of imaging system performance was modeled by averaging 1 to 9 neighboring planes to represent increasing elevation plane thicknesses. Quantification of the performance of the imaging system was determined by measuring the: (1) mean number of circular cross-sections detected per image frame; (2) mean fractional area of circular cross-sections detected per image frame; (3) agreement of observed circular cross-section radii histogram distribution with the theoretical distribution (Chi-square statistic); and (4) contrast and contrast-to-noise ratio as a function of observed circular cross-section radius.Results suggest that analyses of a sufficient number of image planes (providing over approximately 3000 total circular cross-sectional areas) provides excellent agreement between the observed and theoretical histogram distributions (mean Chi-square 0.004). For the 0.15 volume fraction series of simulated RSV phantoms, using 150 image plane analyses, phantom images show decreasing mean number of circle cross-sections detected per frame (31.5 ± 0.3, 28.4 ± 0.3, 28.2 ± 0.3, 26.3 ± 0.3, and 25.3 ± 0.3); decreasing mean fractional area of circle cross-sections per frame (0.157 ± 0.002, 0.133 ± 0.001, 0.133 ± 0.001, 0.111 ± 0.001, and 0.108 ± 0.001); and a decreasing agreement with the theoretical histogram distribution of radii (Chi-square values: 0.070 ± 0.004, 0.140 ± 0.005, 0.149 ± 0.007, 0.379 ± 0.011, and 0.518 ± 0.010) for 1, 3, 5, 7, and 9 plane averages, respectively. Contrast and contrast-to-noise measurements as a function of observed circular cross-section radius also demonstrate marked changes with simulated image degradation.Results of this simulation study suggest that analyses of images obtained from relatively high-density RSV phantoms may offer a promising approach for assessing ultrasound imaging systems. The proposed measurements appear to provide reproducible, robust, quantitative metrics that can be compared with corresponding theoretical values to provide quantifiable, objective metrics of imaging system performance.

BackgroundThere is a bidirectional link between sleep and migraine, however causality is difficult to determine. Previous studies rely on retrospective questionnaires, and small samples to support their findings. This study aimed to overcome this by teasing apart this relationship using sleep assessment and concomitant migraine data collected from a smartphone application using Bayesian modelling.MethodsAnonymized self-reported data on sleep and migraine from 11,166 global users (aged 18-81 years, mean: 41.21, standard deviation: 11.49) were collected from the Migraine Buddy application (Healint Pte. Ltd.) between 30thJune and 31stDecember 2021. Measures included: demographics, start and end times of each sleep episode and migraine attack, and the pain intensity for each migraine attack (visual analogue scale 0-10). Bayesian regression models were used to predict occurrence of a migraine attack the next day based on users’ deviations from mean monthly sleep, number of sleep interruptions, and hours slept the night before in those reporting ≥ 4 and ResultsOnce exclusion criteria were applied, there were 724 users (129 males, 412 females, 183 unknown) with an average age of 41.88 years (SD= 11.63), with a mean monthly number of attacks of 9.94. A greater number of sleep interruptions (95% Highest Density Interval (95% HDI [0.112 – 0.205]) and deviation from a user’s mean sleep the night before (95% HDI [0.040 – 0.080]) were significant predictors of a next day migraine attack. Total hours slept was not a significant predictor (95% HDI [-0.04 – 0.04]). Pain intensity, but not attack occurrence was a positive predictor of hours slept.DiscussionSleep fragmentation and deviation from typical sleep are the main drivers of the relationship between sleep and migraine, whereas overall sleep duration is not. Conversely, simply having a migraine attack does not predict sleep duration, it is the pain associated with an attack which alters sleep. This study has shed light on the causal mechanisms of sleep and migraine and highlights sleep hygiene as crucial in migraine management.

The scale and resolution of trait databases and molecular phylogenies is increasing rapidly. These resources permit many questions in macro evolution and ecology to be addressed with the right statistical tools. Phylogenetic mixed models (PMM), particularly multi-response (MR) implementations, offer great potential for analyses of trait evolution. While flexible and powerful, these models can be conceptually challenging. The literature describing PMM is also highly technical, creating additional barriers for many biologists. Here we present an accessible and practical guide to the PMM. We begin by outlining key concepts in mixed modelling, emphasising the use of covariance matrices to model correlative structure in the data. We present a simple notation for PMM, of which phylogenetic generalised least squares (PGLS) is a special case. We outline the limitations of single-response (SR) models such as PGLS for characterising patterns of trait variation, and emphasise that MR models will often be a preferable approach to analyses involving multiple species traits. Using simulated data and visual examples, we demonstrate the capacity of MR-PMM to partition trait covariance into phylogenetic and independent components. We discuss interpretation, prediction, and model validation, including methods based on leave-one-out cross validation. We then apply this approach to a real-world data set of leaf traits in Eucalyptus to show how MR-PMM can offer a more nuanced understanding of trait correlations compared to SR approaches. Finally, we highlight common pitfalls and offer practical recommendations to analysts. To complement this material, we provide an online tutorial including additional examples, as well as side-by-side implementations in two popular R packages,MCMCglmmandbrms.

A major source of uncertainty in future sea-level projections is the ocean-driven basal melt of Antarctic ice shelves. Whereas ice sheet models require a kilometer-scale resolution to realistically resolve ice shelf stability and grounding line migration, global or regional 3D ocean models are computationally too expensive to produce basal melt forcing fields at this resolution. To bridge this resolution gap, we introduce the 2D numerical model LADDIE (one-Layer Antarctic model for Dynamical Downscaling of Ice–ocean Exchanges) which allows for the computationally efficient modeling of basal melt rates. The model is flexible, and can be forced with output from coarse 3D ocean models or with vertical profiles of offshore temperature and salinity. In this study, we describe the model equations and numerics. To illustrate and validate the model performance, we apply the model to two test cases: the small Crosson-Dotson Ice Shelf in the warm Amundsen Sea region, and the large Filchner-Ronne Ice Shelf in the cold Weddell Sea. At ice-shelf wide scales, LADDIE reproduces observed patterns of basal melt and freezing that are also well reproduced by 3D ocean models. At scales of 0.5–5 km, which are unresolved by 3D ocean models and poorly constrained by observations, LADDIE produces plausible basal melt patterns. Most significantly, the simulated basal melt patterns are physically consistent with the applied ice shelf topography. These patterns are governed by the topographic steering and Coriolis deflection of meltwater flows, two processes that are poorly represented in basal melt parameterisations. The kilometer-scale melt patterns simulated by LADDIE include enhanced melt rates in basal channels, in some shear margins, and nearby grounding lines. As these regions are critical for ice shelf stability, we conclude that LADDIE can provide detailed basal melt patterns at the essential resolution that ice sheet models require. The physical consistency between the applied geometry and the simulated basal melt fields indicates that LADDIE can play a valuable role in the development of coupled ice–ocean modeling.

BACKGROUND AND PURPOSE Lasmiditan is a novel selective 5-HT1F receptor agonist, recently approved for acute treatment of migraine. 5-HT1F receptors are widely expressed in the CNS and trigeminovascular system. Here, we have explored the therapeutic effects of 5-HT1F receptor activation in preclinical models of migraine and cluster headache. EXPERIMENTAL APPROACH Electrical stimulation of the dura mater or the superior salivatory nucleus in anaesthetised rats evoked trigeminovascular or trigeminal-autonomic reflex activation at the level of the trigeminocervical complex. Additionally, cranial autonomic manifestations in response to trigeminal-autonomic reflex activation were measured, via anterior choroidal blood flow alterations. These responses were then challenged with lasmiditan. We explored the tissue distribution of mRNA for 5-HT1F receptors in human post-mortem tissue and of several 5-HT1 receptor subtypes in specific tissue beds. KEY RESULTS Lasmiditan dose-dependently reduced trigeminovascular activation in a preclinical model of migraine. Lasmiditan also reduced superior salivatory nucleus-evoked activation of the trigeminal-autonomic reflex, but had no effect on cranial autonomic activation. mRNA profiling in human tissue showed expression of the 5-HT1F receptor in several structures relevant for migraine and cluster headache. CONCLUSION AND IMPLICATIONS Our data suggest that lasmiditan acts, at least in part, as an anti-migraine agent by reducing trigeminovascular activation. Furthermore, our results highlight a clear action for lasmiditan in a preclinical model of cluster headache. Given the proven translational efficacy of this model, our data support the potential utility of lasmiditan as a therapeutic option for the acute treatment of cluster headache attacks.

Magnetic resonance imaging (MRI) is a well-established and widely used technique to characterize and quantify skeletal and cardiac muscle changes in Duchenne muscular dystrophy (DMD). Recently, MRI has been explored to study disease progression and response to gene therapy in the canine DMD model. Using traditional sequences, delayed gadolinium enhancement, novel sequences, and spectroscopy, investigators have begun to (i) establish the baseline MRI characteristics of the muscles in normal and affected dogs and (ii) evaluate gene therapy outcomes in treated dogs. As a noninvasive assay, MRI offers an excellent opportunity to study longitudinal muscle changes in long-term gene therapy studies in the canine model. In this chapter, we outline the MRI method used to study DMD in the canine model.

Phylogenetic trees are widely used to understand the evolutionary history of organisms. Tree shapes provide information about macroevolutionary processes. However, macroevolutionary models are unreliable for inferring the true processes underlying empirical trees. Here, we propose a flexible and biologically plausible macroevolutionary model for phylogenetic trees where times to speciation or extinction events are drawn from a Coxian phase-type (PH) distribution. First, we show that different choices of parameters in our model lead to a range of tree balances as measured by Aldous' $\beta$ statistic. In particular, we demonstrate that it is possible to find parameters that correspond well to empirical tree balance. Next, we provide a natural extension of the $\beta$ statistic to sets of trees. This extension produces less biased estimates of $\beta$ compared to using the median $\beta$ values from individual trees. Furthermore, we derive a likelihood expression for the probability of observing any tree with branch lengths under a model with speciation but no extinction. Finally, we illustrate the application of our model by performing both absolute and relative goodness-of-fit tests for two large empirical phylogenies (squamates and angiosperms) that compare models with Coxian PH distributed times to speciation with models that assume exponential or Weibull distributed waiting times. In our numerical analysis, we found that, in most cases, models assuming a Coxian PH distribution provided the best fit., Comment: 32 pages, 14 figures, 2 tables

Author(s): Li, X; Cai, W; Meehl, GA; Chen, D; Yuan, X; Raphael, M; Holland, DM; Ding, Q; Fogt, RL; Markle, BR; Wang, G; Bromwich, DH; Turner, J; Xie, SP; Steig, EJ; Gille, ST; Xiao, C; Wu, B; Lazzara, MA; Chen, X; Stammerjohn, S; Holland, PR; Holland, MM; Cheng, X; Price, SF; Wang, Z; Bitz, CM; Shi, J; Gerber, EP; Liang, X; Goosse, H; Yoo, C; Ding, M; Geng, L; Xin, M; Li, C; Dou, T; Liu, C; Sun, W; Wang, X; Song, C | Abstract: Over the modern satellite era, substantial climatic changes have been observed in the Antarctic, including atmospheric and oceanic warming, ice sheet thinning and a general Antarctic-wide expansion of sea ice, followed by a more recent rapid loss. Although these changes, featuring strong zonal asymmetry, are partially influenced by increasing greenhouse gas emissions and stratospheric ozone depletion, tropical–polar teleconnections are believed to have a role through Rossby wave dynamics. In this Review, we synthesize understanding of tropical teleconnections to the Southern Hemisphere extratropics arising from the El Nino–Southern Oscillation, Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation, focusing on the mechanisms and long-term climatic impacts. These teleconnections have contributed to observed Antarctic and Southern Ocean changes, including regional rapid surface warming, pre-2015 sea ice expansion and its sudden reduction thereafter, changes in ocean heat content and accelerated thinning of most of the Antarctic ice sheet. However, due to limited observations and inherent model biases, uncertainties remain in understanding and assessing the importance of these teleconnections versus those arising from greenhouse gases, ozone recovery and internal variability. Sustained pan-Antarctic efforts towards long-term observations, and more realistic dynamics and parameterizations in high-resolution climate models, offer opportunities to reduce these uncertainties.

Background Published data on pharmacist-provided chronic care management (CCM) services is limited, particularly for programs led by community-based pharmacists. Objective The objective was to quantify the total revenue generated from a community pharmacist-led CCM service, including CCM billing and appointment referrals. A second objective was to identify the types and frequencies of medication discrepancies identified during medication reconciliation. Practice description Realo Drugs is a group of 18 independent community pharmacies serving eastern North Carolina. Practice innovation Exploration of revenue generated from a community pharmacist-led CCM service. Evaluation methods This retrospective analysis assessed interventions completed by pharmacists between April 1, 2018 through June 30, 2019. Data was extracted from the electronic health record (EHR), including revenue generated from CCM billing codes, appointment referrals made by the pharmacist resulting in a completed in-office appointment, and which patients received medication reconciliation. The types and frequencies of medication discrepancies were documented, including medication no longer being used by the patient, medication omission, and strength or dose mismatch. Descriptive statistics were used to analyze data. Results Over 15 months with a total of 112 patients, a total of $26,148 was generated from CCM services, representing an average of $15.56 per patient per month. The majority (approximately 80%) of the revenue was generated from noncomplex patient encounters. Of the 239 medication reconciliations completed, 609 medication discrepancies were identified. The majority of medication discrepancies (67%) were categorized as “patient no longer takes medication listed on EHR medication list.” The second most common discrepancy was “patient takes medication not listed on the EHR medication list” (22%), followed by “strength/dose mismatch” (10%). Conclusion These data can demonstrate to provider partners the sources of revenue that can be provided through CCM services. In addition to revenue, pharmacists can positively impact patient care through identification of medication discrepancies through medication reconciliation.

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium’s plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled—along with validated datasets—into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit—and the knowledge generated by its applications—as a means to accelerate the clinical development of new therapies for a wide range of conditions., This Perspective discusses how the Somatic Cell Genome Editing Consortium aims to accelerate the implementation of safe and effective genome-editing therapies in the clinic.

Medical abzymology has made a great contribution to the development of general autoimmunity theory: it has put the autoantibodies (Ab) as the key brick of the theory to the level of physiological functionality by providing such Ab with the ability to catalyze and mediate direct and independent cytotoxic effect on cellular and molecular targets. Natural catalytic autoantibodies (abzymes) while being a pool of canonical Abs and possessing catalytic activity belong to the new group of physiologically active substances whose features and properties are evolutionary consolidated in one functionally active biomolecule. Therefore, further studies on Ab-mediated autoAg degradation and other targeted Ab-mediated proteolysis may provide biomarkers of newer generations and thus a supplementary tool for assessing the disease progression and predicting disability of the patients and persons at risks. This chapter is a summary of current knowledge and prognostic perspectives toward catalytic Abs in autoimmunity and thus some autoimmune clinical cases, their role in pathogenesis, and the exploitation of both whole molecules and their constituent parts in developing highly effective targeted drugs of the future to come, and thus the therapeutic protocols being individualized.

Targeted delivery of diagnostics and therapeutics offers essential advantages over nontargeted systemic delivery. These include the reduction of toxicity, the ability to reach sites beyond biological barriers, and the delivery of higher cargo concentrations to diseased sites. Virus-like particles (VLPs) can efficiently be used for targeted delivery purposes. VLPs are derived from the coat proteins of viral capsids. They are self-assembled, biodegradable, and homogeneously distributed. In this study, hepatitis E virus (HEV) VLP derivatives, hepatitis E virus nanoparticles (HEVNPs), were radiolabeled with gallium-68, and consequently, the biodistribution of the labeled [Ga-68]Ga-DOTA-HEVNPs was studied in mice. The results indicated that [Ga-68]Ga-DOTA-HEVNPs can be considered as promising theranostic nanocarriers, especially for hepatocyte-targeting therapies.

Targeted delivery of diagnostics and therapeutics offers essential advantages over nontargeted systemic delivery. These include the reduction of toxicity, the ability to reach sites beyond biological barriers, and the delivery of higher cargo concentrations to diseased sites. Virus-like particles (VLPs) can efficiently be used for targeted delivery purposes. VLPs are derived from the coat proteins of viral capsids. They are self-assembled, biodegradable, and homogeneously distributed. In this study, hepatitis E virus (HEV) VLP derivatives, hepatitis E virus nanoparticles (HEVNPs), were radiolabeled with gallium-68, and consequently, the biodistribution of the labeled [

ObjectivesThe primary objective of this study was to co-design and conduct a pilot evaluation of a novel, immersive virtual reality (VR) experience for procedural pain and anxiety in an Australian healthcare setting. The secondary objective was to identify key parameters that can facilitate the development and implementation of VR experiences in clinical practice.MethodA qualitative, Design Box method was selected for co-design. It was used with adult burns survivors and adolescents and young adults (AYAs) with cancer, and healthcare professionals from these fields to identify the practical and design parameters required for the application of VR technology within the clinical setting. Results informed the development of the VR experience that was evaluated by consumers and healthcare professionals, who completed qualitative surveys. Thematic analysis was conducted on co-design notes and survey data.ResultsProcedural pain and management was a challenge for both cohorts, but particularly the burns cohort. Anxiety was significant challenge for both cohorts. Boredom and quality of life was a significant challenge, particularly for the AYA oncology cohort. These results informed the development of “A Wanderers Tale,” an Australiana-themed, gaze-controlled VR application for Oculus Quest platforms. Thematic analysis results suggest that cultural preferences, procedural contexts of use, and agency through customization and interaction are three parameters to consider when creating or selecting VR experiences for application in health.Significance of resultsThis work describes a novel method for the use VR as an adjuvant pain management tool in patients with burns and cancer. The VR experience may provide a culturally, practice and procedure-appropriate tool in comparable settings of care. The study also describes interdisciplinary co-design and evaluation approaches that can help maximize the use of VR to improve healthcare approaches that address clinical challenges in pain, anxiety, and quality of life for patients while in hospital.

Resiquimod (R848) is a toll-like receptor 7 and 8 (TLR7/8) agonist with potent antitumor and immunostimulatory activity. However, systemic delivery of R848 is poorly tolerated because of its poor solubility in water and systemic immune activation. In order to address these limitations, we developed an intravenously-injectable formulation with R848 using thermosensitive liposomes (TSLs) as a delivery vehicle. R848 was remotely loaded into TSLs composed of DPPC: DSPC: DSPE-PEG2K (85:10:5, mol%) with 100mM FeSO4 as the trapping agent inside. The final R848 to lipid ratio of the optimized R848-loaded TSLs (R848-TSLs) was 0.09 (w/w), 10-fold higher than the previously-reported values. R848-TSLs released 80% of R848 within 5min at 42°C. These TSLs were then combined with αPD-1, an immune checkpoint inhibitor, and ultrasound-mediated hyperthermia in a neu deletion (NDL) mouse mammary carcinoma model (Her2+, ER/PR negative). Combined with αPD-1, local injection of R848-TSLs showed superior efficacy with complete NDL tumor regression in both treated and abscopal sites achieved in 8 of 11 tumor bearing mice over 100days. Immunohistochemistry confirmed enhanced CD8+ T cell infiltration and accumulation by R848-TSLs. Systemic delivery of R848-TSLs, combined with local hyperthermia and αPD-1, inhibited tumor growth and extended median survival from 28days (non-treatment control) to 94days. Upon re-challenge with reinjection of tumor cells, none of the previously cured mice developed tumors, as compared with 100% of age-matched control mice. The dose of R848 (10μg for intra-tumoral injection or 6mg/kg for intravenous injection delivered up to 4 times) was well-tolerated without weight loss or organ hypertrophy. In summary, we developed R848-TSLs that can be administered locally or systematically, resulting in tumor regression and enhanced survival when combined with αPD-1 in mouse models of breast cancer.

The transport of heat and salt through turbulent ice shelf–ocean boundary layers is a large source of uncertainty within ocean models of ice shelf cavities. This study uses small-scale, high-resolution, 3D numerical simulations to model an idealized boundary layer beneath a melting ice shelf to investigate the influence of ambient turbulence on double-diffusive convection (i.e., convection driven by the difference in diffusivities between salinity and temperature). Isotropic turbulence is forced throughout the simulations and the temperature and salinity are initialized with homogeneous values similar to observations. The initial temperature and the strength of forced turbulence are varied as controlling parameters within an oceanographically relevant parameter space. Two contrasting regimes are identified. In one regime double-diffusive convection dominates, and in the other convection is inhibited by the forced turbulence. The convective regime occurs for high temperatures and low turbulence levels, where it is long lived and affects the flow, melt rate, and melt pattern. A criterion for identifying convection in terms of the temperature and salinity profiles, and the turbulent dissipation rate, is proposed. This criterion may be applied to observations and theoretical models to quantify the effect of double-diffusive convection on ice shelf melt rates.

The use of nanoparticulate systems to diagnose and treat tumors has gained momentum with the rapid development of nanomedicine. Many nanotheranostics fail due to insufficient bioavailability and low accumulation at the tumor site, resulting in undesirable side effects. We describe the use of an engineered hepatitis E viral nanoparticle (HEVNP) with enhanced bioavailability, tissue retention and mucosal penetration capacities. HEVNP is a modular nanocapsule that can encapsulate heterologous nucleotides, proteins and inorganic metals, such as ferrite oxide nanoparticles. Additionally, the exterior protruding arms of HEVNP is composed of loops that are used for chemical coupling of targeting and therapeutic peptides. We propose the use of HEVNP to target colorectal cancer (i.e., polyps) with imaging-guided delivery using colonoscopy.

Medication overuse headache is estimated to affect 2% of the population, and is ranked in the top 20 most disabling disorders due to its high level of disability. Several therapies used in the treatment of acute migraine are thought to be associated with medication overuse headache, including opioids and triptans. With limited treatment options, it is critical to determine the risk profile of novel therapies prior to their widespread use. The current study explores the potential medication overuse risk of two novel therapeutic drug classes, namely the ditans: 5-HT1F receptor agonists, and the gepants: calcitonin gene-related peptide receptor antagonists, in a preclinical model of medication overuse. Persistent exposure of mice to the 5-HT1F agonist LY344864, but not olcegepant produced a significant reduction in hind paw and orofacial mechanical withdrawal thresholds as a surrogate readout of allodynia. In agreement, only LY344864 induced neuroplastic changes in trigeminal sensory afferents, increasing calcitonin gene-related peptide expression and basal trigeminal nociception. Our data highlight a differential medication overuse headache risk profile for the ditan and gepant classes of drugs that has important implications for their clinical use and patient education to help reduce the burden of medication overuse headache.

The objectives of this study were to assess 30- and 60-day hospitalizations and to determine the number of medication therapy problems (MTPs) identified during pharmacy technician-driven medication reconciliation for high- to very high-risk home health patients.The study was conducted in 8 independent community pharmacy locations.Realo Discount Drugs is a group of 16 independent community pharmacies serving eastern North Carolina.Realo Discount Drugs partnered with Well Care Home Health to provide medication reconciliation services to high- and very high-risk patients. A pharmacy technician contacts the patient to obtain an accurate medication list and complete a falls risk assessment and depression screening. The technician updates the medication list, allergies, and vaccination status in the electronic health record (EHR). The pharmacist reviews the medication list for completeness; assesses for falls risk, depression, and medication interactions; and generates communication to the provider for clarifications or recommendations, if needed. Additional counseling points that need to be conveyed to the patient by the home health nurse are documented in the EHR.Thirty- and 60-day hospitalizations for enrolled patients were manually pulled from documented transfers in the EHR and compared with data from a third-party administrator. MTPs were categorized by the pharmacist and documented. Descriptive statistics were used to evaluate the data collected.At 30 days from the start of care, 13.4% (93/695) of patients who received pharmacy services were hospitalized compared with 26.8% (143/534) of patients who did not receive pharmacy services (P0.01). At 60 days from the start of care, 20.9% (145/695) of patients who received pharmacy services were hospitalized compared with 33.3% (178/534) of patients who did not receive pharmacy services (P0.01).A technician-driven medication reconciliation process led to a reduction in hospitalizations and identified MTPs in home health patients.

The focus of this work is the numerical application of a stochastic decision support model for the patient admission scheduling problem with random arrivals and departures. Here, we discuss the methodology for applying our model to real-world problems. We outline a solution approach for efficient computation, provide a numerical analysis of the model, and illustrate the methodology with examples. A key component of the model is an integer linear program which formulates the patient admission scheduling problem as an optimization of the total expected cost accumulated over a finite planning horizon. We rewrite some of the components of this integer linear program in order to improve numerical efficiency. We use Poisson processes and discrete phase-type distributions to model the random arrivals and departures, respectively. We argue that this stochastic component is essential for an accurate treatment of real-world problems which are stochastic in nature. We support our claim with simple numerical examples, and show that the optimal solutions obtained from deterministic models are inadequate when compared with the solutions of our stochastic model. We also construct more complex numerical examples for large-scale problems using heuristics that approximate the objective function, in order to demonstrate that our model can be efficiently applied to real-world problems, which typically involve large data sets.

Hymenopteran parasitoid wasps are a diverse collection of species that infect arthropod hosts and use factors found in their venoms to manipulate host immune responses, physiology, and behaviour. Whole parasitoid venoms have been profiled using proteomic approaches, and here we present a bioinformatic characterization of the venom protein content from Ganaspis sp. 1, a parasitoid that infects flies of the genus Drosophila. We find evidence that diverse evolutionary processes including multifunctionalization, co-option, gene duplication, and horizontal gene transfer may be acting in concert to drive venom gene evolution in Ganaspis sp.1. One major role of parasitoid wasp venom is host immune evasion. We previously demonstrated that Ganaspis sp. 1 venom inhibits immune cell activation in infected Drosophila melanogaster hosts, and our current analysis has uncovered additional predicted virulence functions. Overall, this analysis represents an important step towards understanding the composition and activity of parasitoid wasp venoms.

Caring for critically ill patients requires non-technical skills such as teamwork, communication, and task management. The Behaviorally Anchored Rating Scale (BARS) is a brief tool used to assess non-technical skills. The investigators determined inter- and intra-rater reliability of the BARS when used to assess medical students in simulated scenarios.The investigators created simulation scenarios for medical students during their pediatric clerkship. Content experts reviewed video recordings of the simulations and assigned BARS scores for four performance components (Situational Awareness, Decision-Making, Communication, and Teamwork) for the leader and for the team as a whole. Krippendorff's alpha with ordinal difference was calculated to measure inter- and intra-rater reliability.Thirty medical students had recordings available for review. Inter- and intra-rater reliability for performance components were, respectively, Individual Situational Awareness (0.488, 0.638), Individual Decision-Making (0.529, 0.691), Individual Communication (0.347, 0.473), Individual Teamwork (0.414, 0.466), Team Situational Awareness (0.450, 0.593), Team Decision Making (0.423, 0.703), Team Communication (0.256, 0.517), and Team Teamwork (0.415, 0.490).The BARS demonstrated limited reliability when assessing medical students during their pediatric clerkship. Given the unique needs of this population, a modified or new objective scoring system for assessing non-technical skills may be needed for medical students.

This chapter surveys theory and research on transgender identity and disclosures. Historically, transgender people in Western societies represent a highly stigmatized population who are likely to encounter significant communication challenges. Interpersonally, transgender people often grapple with privacy and disclosure, especially in regards to when, where, how, and with whom to disclose their gender identity, as they risk rejection from friends and family and experiencing violence. Thus, insofar as transgender individuals find that conversations about their sexuality and/or gender identity are proscribed by society and carry the threat of stigmatizing or violent personal and interpersonal outcomes, discussion of transgender identity can be seen as a taboo topic. In light of that, this chapter surveys theory and research on transgender identity and disclosures.

Nanotechnology is one of the scientific advances in technology. Nanoparticles (NPs) are small materials ranging from 1 to 100 nm. When the shape of the supplied nanoparticles changes, the physiological response of the cells can be very different. Several characteristics of NPs such as the composition, surface chemistry, surface charge, and shape are also important parameters affecting the toxicity of nanomaterials. This review covered specific topics that address the effects of NPs on nanomedicine. Furthermore, mechanisms of different types of nanomaterial-induced cytotoxicities were described. The distributions of different NPs in organs and their adverse effects were also emphasized. This review provides insight into the scientific community interested in nano(bio)technology, nanomedicine, and nanotoxicology. The content may also be of interest to a broad range of scientists.

The melt rate of Antarctic ice shelves is of key importance for rising sea levels and future climate scenarios. Recent observations beneath Larsen C Ice Shelf revealed an ocean boundary layer that was highly turbulent and raised questions on the effect of these rich flow dynamics on the ocean heat transfer and the ice shelf melt rate. Directly motivated by the field observations, we have conducted large-eddy simulations (LES) to further examine the ocean boundary layer beneath Larsen C Ice Shelf. The LES was initialized with uniform temperature and salinity (T–S) and included a realistic tidal cycle and a small basal slope. A new parameterization based on previous work was applied at the top boundary to model near-wall turbulence and basal melting. The resulting vertical T–S profiles, melt rate, and friction velocity matched well with the Larsen C Ice Shelf observations. The instantaneous melt rate varied strongly with the tidal cycle, with faster flow increasing the turbulence and mixing of heat toward the ice base. An Ekman layer formed beneath the ice base and, due to the strong vertical shear of the current, Ekman rolls appeared in the mixed layer and stratified region (depth ≈ 20–60 m). In an additional high-resolution simulation (conducted with a smaller domain) the Ekman rolls were associated with increased turbulent kinetic energy, but a relatively small vertical heat flux. Our results will help with interpreting field observations and parameterizing the ocean-driven basal melting of ice shelves.

In molecular phylogenetics, partition models and mixture models provide different approaches to accommodating heterogeneity in genomic sequencing data. Both types of models generally give a superior fit to data than models that assume the process of sequence evolution is homogeneous across sites and lineages. The Akaike Information Criterion (AIC), an estimator of Kullback-Leibler divergence, and the Bayesian Information Criterion (BIC), are popular tools to select models in phylogenetics. Recent work suggests AIC should not be used for comparing mixture and partition models. In this work, we clarify that this difficulty is not fully explained by AIC misestimating the Kullback-Leibler divergence. We also investigate the performance of the AIC and BIC at comparing amongst mixture models and amongst partition models. We find that under non-standard conditions (i.e. when some edges have small expected number of changes), AIC underestimates the expected Kullback-Leibler divergence. Under such conditions, AIC preferred the complex mixture models and BIC preferred the simpler mixture models. The mixture models selected by AIC had a better performance in estimating the edge length, while the simpler models selected by BIC performed better in estimating the base frequencies and substitution rate parameters. In contrast, AIC and BIC both prefer simpler partition models over more complex partition models under non-standard conditions, despite the fact that the more complex partition model was the generating model. We also investigated how mispartitioning (i.e. grouping sites that have not evolved under the same process) affects both the performance of partition models compared to mixture models and the model selection process. We found that as the level of mispartitioning increases, the bias of AIC in estimating the expected Kullback-Leibler divergence remains the same, and the branch lengths and evolutionary parameters estimated by partition models become less accurate. We recommend that researchers be cautious when using AIC and BIC to select among partition and mixture models; other alternatives, such as cross-validation and bootstrapping should be explored, but may suffer similar limitations.

In the outpatient setting, ambulatory electrocardiography is the most frequently used diagnostic modality for the evaluation of patients in whom cardiac arrhythmias or conduction abnormalities are suspected. Proper selection of the device type and monitoring duration is critical for optimizing diagnostic yield and cost-effective resource utilization. However, despite guidance from major professional societies, the lack of systematic guidance for proper test selection in many institutions results in the need for repeat testing, which leads to not only increased resource utilization and cost of care, but also suboptimal patient care. To address this unmet need at our own institution, we formed a multidisciplinary panel to develop a concise, yet comprehensive algorithm, incorporating the most common indications for ambulatory electrocardiography, to efficiently guide clinicians to the most appropriate test option for a given clinical scenario, with the goal of maximizing diagnostic yield and optimizing resource utilization. The algorithm was designed as a single-page, color-coded flowchart to be utilized both as a rapid reference guide in printed form, and a decision support tool embedded within the electronic medical records system at the point of order entry. We believe that systematic adoption of this algorithm will optimize diagnostic efficiency, resource utilization, and importantly, patient care and satisfaction.

Pretargeted PET imaging allows the use of radiotracers labeled with short-living PET radionuclides for tracing drugs with slow pharmacokinetics. Recently, especially methods based on bioorthogonal chemistry have been under intensive investigation for pretargeted PET imaging. The pharmacokinetics of the radiotracer is one of the factors that determine the success of the pretargeted strategy. Here, we report synthesis and biological evaluation of two