Phenotypic plasticity: A missing element in the theory of vegetation pattern formation.

Regular spatial patterns of vegetation are a common sight in drylands. Their formation is a population-level response to water stress that increases water availability for the few via partial plant mortality. At the individual level, plants can also adapt to water stress by changing their phenotype. Phenotypic plasticity of individual plants and spatial patterning of plant populations have extensively been studied independently, but the likely interplay between the two robust mechanisms has remained unexplored. In this paper, we incorporate phenotypic plasticity into a multi-level theory of vegetation pattern formation and use a fascinating ecological phenomenon, the Namibian "fairy circles," to demonstrate the need for such a theory. We show that phenotypic changes in the root structure of plants, coupled with pattern-forming feedback within soil layers, can resolve two puzzles that the current theory fails to explain: observations of multi-scale patterns and the absence of theoretically predicted large-scale stripe and spot patterns along the rainfall gradient. Importantly, we find that multi-level responses to stress unveil a wide variety of more effective stress-relaxation pathways, compared to single-level responses, implying a previously underestimated resilience of dryland ecosystems.

Validation of the Nelson Tool: A Scoring Tool for Nonsurgical Service Admission of Injured Patients.

BACKGROUND: Trauma performance improvement programs are required by the American College of Surgeons to review all nonsurgical admissions if the annual rate exceeds 10%. These reviews can have varying consistency between reviewers, are time consuming, and the consequent aggregate data are difficult to evaluate for trends. OBJECTIVE: This study set forth to standardize nonsurgical admission review through validation of the Nelson tool, which is a published objective scoring tool to determine the appropriateness of nonsurgical admissions. We hypothesized that implementation of this tool would facilitate earlier identification of events resulting in meaningful intervention and a reduction of inappropriate nonsurgical admissions. METHODS: The Nelson tool and scoring was integrated into the nonsurgical admission review process. A customized audit filter and report were built in the trauma registry. Data were reviewed with respect to scores and admitting service. Statistical analysis included using analysis of variance and t tests to examine differences between admitting services, χ2 test of independence or Fisher's exact to test the association of categorical variables, and ordinal logistic regression to test the ability of the total Nelson tool to predict appropriateness of admission. RESULTS: Using the Nelson tool, scores resulted in appropriate admission service in over 90% of cases. Implementation of the tool resulted in a decreased performance improvement workload with a 78% reduction in nonsurgical admission cases required to go to secondary level of review. CONCLUSIONS: Utilization of a validated scoring tool decreases performance improvement workload without compromising patient safety.

Acetone Ingestion Mimics a Fasting State to Improve Glucose Tolerance in a Mouse Model of Gestational Hyperglycemia.

Gestational diabetes mellitus results, in part, from a sub-optimal ß-cell mass (BCM) during pregnancy. Artemisinins were reported to increase BCM in models of diabetes by α- to ß-cell conversion leading to enhanced glucose tolerance. We used a mouse model of gestational glucose intolerance to compare the effects of an artemisinin (artesunate) on glycemia of pregnant mice with vehicle treatment (acetone) or no treatment. Animals were treated daily from gestational days (GD) 0.5 to 6.5. An intraperitoneal glucose tolerance test was performed prior to euthanasia at GD18.5 or post-partum. Glucose tolerance was significantly improved in both pregnant and non-pregnant mice with both artesunate and vehicle-alone treatment, suggesting the outcome was primarily due to the acetone vehicle. In non-pregnant, acetone-treated animals, improved glucose tolerance was associated with a higher BCM and a significant increase in bihormonal insulin and glucagon-containing pancreatic islet cells, suggesting α- to ß-cell conversion. BCM did not differ with treatment during pregnancy or post-partum. However, placental weight was higher in acetone-treated animals and was associated with an upregulation of apelinergic genes. Acetone-treated animals had reduced weight gain during treatment despite comparable food consumption to non-treated mice, suggesting transient effects on nutrient uptake. The mean duodenal and ileum villus height was reduced following exposure to acetone. We conclude that acetone treatment may mimic transient fasting, resulting in a subsequent improvement in glucose tolerance during pregnancy.

Long-distance seed dispersal affects the resilience of banded vegetation patterns in semi-deserts.

Landscape-scale vegetation stripes (tiger bush) observed on the gentle slopes of semi-arid regions are useful indicators of future ecosystem degradation and catastrophic shifts towards desert. Mathematical models like the Klausmeier model-a set of coupled partial differential equations describing vegetation and water densities in space and time-are central to understanding their formation and development. One assumption made for mathematical simplicity is the local dispersal of seeds via a diffusion term. In fact, a large amount of work focuses on fitting dispersal 'kernels', probability density functions for seed dispersal distance, to empirical data of different species and modes of dispersal. In this paper, we address this discrepancy by analysing an extended Klausmeier model that includes long-distance seed dispersal via a non-local convolution term in place of diffusion, and assessing its effect on the resilience of striped patterns. Many authors report a slow uphill migration of stripes; but others report no detectable migration speed. We show that long-distance seed dispersal permits the formation of patterns with a very slow (possibly undetectable) migration speed, and even stationary patterns which could explain the inconsistencies in the empirical data. In general, we show that the resilience of patterns to reduced rainfall may vary significantly depending on the rate of seed dispersal and the width of the dispersal kernel, and compare a selection of ecologically relevant kernels to examine the variation in pattern resilience.

Large scale patterns in mussel beds: stripes or spots?

An aerial view of an intertidal mussel bed often reveals large scale striped patterns aligned perpendicular to the direction of the tide; dense bands of mussels alternate periodically with near bare sediment. Experimental work led to the formulation of a set of coupled partial differential equations modelling a mussel-algae interaction, which proved pivotal in explaining the phenomenon. The key class of model solutions to consider are one-dimensional periodic travelling waves (wavetrains) that encapsulate the abundance of peak and trough mussel densities observed in practice. These solutions may, or may not, be stable to small perturbations, and previous work has focused on determining the ecologically relevant (stable) wavetrain solutions in terms of model parameters. The aim of this paper is to extend this analysis to two space dimensions by considering the full stripe pattern solution in order to study the effect of transverse two-dimensional perturbations-a more true to life problem. Using numerical continuation techniques, we find that some striped patterns that were previously deemed stable via the consideration of the associated wavetrain solution, are in fact unstable to transverse two-dimensional perturbations; and numerical simulation of the model shows that they break up to form regular spotted patterns. In particular, we show that break up of stripes into spots is a consequence of low tidal flow rates. Our consideration of random algal movement via a dispersal term allows us to show that a higher algal dispersal rate facilitates the formation of stripes at lower flow rates, but also encourages their break up into spots. We identify a novel hysteresis effect in mussel beds that is a consequence of transverse perturbations.

Prediction of future dementia among patients with mild cognitive impairment (MCI) by integrating multimodal clinical data.

Efficiently and objectively analyzing the complex, diverse multimodal data collected from patients at risk for dementia can be difficult in the clinical setting, contributing to high rates of underdiagnosis or misdiagnosis of this serious disorder. Patients with mild cognitive impairment (MCI) are especially at risk of developing dementia in the future. This study evaluated the ability of multi-modal machine learning (ML) methods, especially the Ensemble Integration (EI) framework, to predict future dementia development among patients with MCI. EI is a machine learning framework designed to leverage complementarity and consensus in multimodal data, which may not be adequately captured by methods used by prior dementia-related prediction studies. We tested EI's ability to predict future dementia development among MCI patients using multimodal clinical and imaging data, such as neuroanatomical measurements from structural magnetic resonance imaging (MRI) and positron emission tomography (PET) scans, from The Alzheimer's Disease Prediction of Longitudinal Evolution (TADPOLE) challenge. For predicting future dementia development among MCI patients, on a held out test set, the EI-based model performed better (AUC = 0.81, F-measure = 0.68) than the more commonly used XGBoost (AUC = 0.68, F-measure = 0.57) and deep learning (AUC = 0.79, F-measure = 0.61) approaches. This EI-based model also suggested MRI-derived volumes of regions in the middle temporal gyrus, posterior cingulate gyrus and inferior lateral ventricle brain regions to be predictive of progression to dementia.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events.

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Reversible recruitment and emission of DO3A-derived lanthanide complexes at ligating molecular films on gold.

The recruitment of DO3A-derived lanthanide complexes by ligation to isophthalic acid and catechol-modified gold surfaces, and their resulting sensitization, is reported herein. Predictably pH-dependent surface recruitment is associated with the expected fingerprint europium and terbium emission characteristics. The intensity of the lanthanide luminescence scales exponentially with spacer length, indicating a strong quenching interaction between the lanthanide and the gold surface. The switchable catechol oxidation state provides a means of electrochemically triggering the release of prior ligated complexes.

Evidence for scale-dependent root-antation feedback and its role in halting the spread of a pantropical shrub into an endemic sedge.

Vegetation pattern formation is a widespread phenomenon in resource-limited environments, but the driving mechanisms are largely unconfirmed empirically. Combining results of field studies and mathematical modeling, empirical evidence for a generic pattern-formation mechanism is demonstrated with the clonal shrub Guilandina bonduc L. (hereafter Guilandina) on the Brazilian island of Trindade. The mechanism is associated with water conduction by laterally spread roots and root augmentation as the shoot grows-a crucial element in the positive feedback loop that drives spatial patterning. Assuming precipitation-dependent root-shoot relations, the model accounts for the major vegetation landscapes on Trindade Island, substantiating lateral root augmentation as the driving mechanism of Guilandina patterning. Guilandina expands into surrounding communities dominated by the Trindade endemic, Cyperus atlanticus Hemsl. (hereafter Cyperus). It appears to do so by decreasing the water potential in soils below Cyperus through its dense lateral roots, leaving behind a patchy Guilandina-only landscape. We use this system to highlight a novel form of invasion, likely to apply to many other systems where the invasive species is pattern-forming. Depending on the level of water stress, the invasion can take two distinct forms: (i) a complete invasion at low stress that culminates in a patchy Guilandina-only landscape through a spot-replication process, and (ii) an incomplete invasion at high stress that begins but does not spread, forming isolated Guilandina spots of fixed size, surrounded by bare-soil halos, in an otherwise uniform Cyperus grassland. Thus, drier climates may act selectively on pattern-forming invasive species, imposing incomplete invasion and reducing the negative effects on native species.

Situational and psychosocial factors mediating coordinated joint attention with augmentative and alternative communication systems with beginning communicators without disabilities.

This study examined how infants' age, joint attention (JA) skills, caregiver ratings of language and temperament, and caregiver JA style related to JA in a structured literacy task with an augmentative and alternative communication (AAC) system. Sixteen infants (mean = 10.6 months) without disabilities participated in two storybook reading interactions with an experimenter in two conditions where the AAC system was either aligned or divided from the experimenter's eye gaze. Individual differences in JA skills, caregiver JA style, and temperament were associated with coordinated JA across both conditions. The findings suggest it is important to examine both extrinsic and intrinsic factors, which may not only reduce attention demands but also mediate the success of JA interactions with AAC systems.

Linking spatial self-organization to community assembly and biodiversity.

Temporal shifts to drier climates impose environmental stresses on plant communities that may result in community reassembly and threatened ecosystem services, but also may trigger self-organization in spatial patterns of biota and resources, which act to relax these stresses. The complex relationships between these counteracting processes - community reassembly and spatial self-organization - have hardly been studied. Using a spatio-temporal model of dryland plant communities and a trait-based approach, we study the response of such communities to increasing water-deficit stress. We first show that spatial patterning acts to reverse shifts from fast-growing species to stress-tolerant species, as well as to reverse functional-diversity loss. We then show that spatial self-organization buffers the impact of further stress on community structure. Finally, we identify multistability ranges of uniform and patterned community states and use them to propose forms of non-uniform ecosystem management that integrate the need for provisioning ecosystem services with the need to preserve community structure.

Increased alpha and beta cell mass during mouse pregnancy is not dependent on transdifferentiation.

Maternal pancreatic beta-cell mass (BCM) increases during pregnancy to compensate for relative insulin resistance. If BCM expansion is suboptimal, gestational diabetes mellitus can develop. Alpha-cell mass (ACM) also changes during pregnancy, but there is a lack of information about α-cell plasticity in pregnancy and whether α- to ß-cell transdifferentiation can occur. To investigate this, we used a mouse model of gestational glucose intolerance induced by feeding low-protein (LP) diet from conception until weaning and compared pregnant female offspring to control diet-fed animals. Control and LP pancreata were collected for immunohistochemical analysis and serum glucagon levels were measured. In order to lineage trace α- to ß-cell conversion, we utilized transgenic mice expressing yellow fluorescent protein behind the proglucagon gene promoter (Gcg-Cre/YFP) and collected pancreata for histology at various gestational timepoints. Alpha-cell proliferation increased significantly at gestational day (GD) 9.5 in control pregnancies resulting in an increased ACM at GD18.5, and this was significantly reduced in LP animals. Despite these changes, serum glucagon was higher in LP mice at GD18.5. Pregnant Gcg-Cre/YFP mice showed no increase in the abundance of insulin+YFP+glucagon- cells (phenotypic ß-cells). A second population of insulin+YFP+glucagon+ cells was identified which also did not alter during pregnancy. However, there was an altered anatomical distribution within islets with fewer insulin+YFP+glucagon- cells but more insulin+YFP+glucagon+ cells being present in the islet mantle at GD18.5. These findings demonstrate that dynamic changes in ACM occur during normal pregnancy and were altered in glucose-intolerant pregnancies.

Ontology of the apelinergic system in mouse pancreas during pregnancy and relationship with ß-cell mass.

The apelin receptor (Aplnr) and its ligands, Apelin and Apela, contribute to metabolic control. The insulin resistance associated with pregnancy is accommodated by an expansion of pancreatic ß-cell mass (BCM) and increased insulin secretion, involving the proliferation of insulin-expressing, glucose transporter 2-low (Ins+Glut2LO) progenitor cells. We examined changes in the apelinergic system during normal mouse pregnancy and in pregnancies complicated by glucose intolerance with reduced BCM. Expression of Aplnr, Apelin and Apela was quantified in Ins+Glut2LO cells isolated from mouse pancreata and found to be significantly higher than in mature ß-cells by DNA microarray and qPCR. Apelin was localized to most ß-cells by immunohistochemistry although Aplnr was predominantly associated with Ins+Glut2LO cells. Aplnr-staining cells increased three- to four-fold during pregnancy being maximal at gestational days (GD) 9-12 but were significantly reduced in glucose intolerant mice. Apelin-13 increased ß-cell proliferation in isolated mouse islets and INS1E cells, but not glucose-stimulated insulin secretion. Glucose intolerant pregnant mice had significantly elevated serum Apelin levels at GD 9 associated with an increased presence of placental IL-6. Placental expression of the apelinergic axis remained unaltered, however. Results show that the apelinergic system is highly expressed in pancreatic ß-cell progenitors and may contribute to ß-cell proliferation in pregnancy.

The potential of prison-based democratic therapeutic communities.

Purpose The purpose of this paper is to describe the work of HMP Grendon, the only prison in the UK to operate entirely as a series of democratic therapeutic communities and to summarise the research of its effectiveness. Design/methodology/approach The paper is both descriptive, providing an overview of the work of a prison-based therapeutic community, and offers a literature review regarding evidence of effectiveness. Findings The work of HMP Grendon has a wide range of positive benefits including reduced levels of disruption in prison, reduced self-harm, improved well-being, an environment that is experienced as more humane and reduced levels of reoffending. Originality/value The work of HMP Grendon offers a well established and evidenced approach to managing men who have committed serious violent and sexually violent offences. It also promotes and embodies a progressive approach to managing prisons rooted in the welfare tradition.

Data Quality and Interoperability Challenges for eHealth Exchange Participants: Observations from the Department of Veterans Affairs' Virtual Lifetime Electronic Record Health Pilot Phase.

Authors studied the United States (U.S.) Department of Veterans Affairs' (VA) Virtual Lifetime Electronic Record (VLER) Health pilot phase relative to two attributes of data quality - the adoption of eHealth Exchange data standards, and clinical content exchanged. The VLER Health pilot was an early effort in testing implementation of eHealth Exchange standards and technology. Testing included evaluation of exchange data from the VLER Health pilot sites partners: VA, U.S. Department of Defense (DoD), and private sector health care organizations. Domains assessed data quality and interoperability as it relates to: 1) conformance with data standards related to the underlying structure of C32 Summary Documents (C32) produced by eHealth Exchange partners; and 2) the types of C32 clinical content exchanged. This analysis identified several standards non-conformance issues in sample C32 files and informed further discourse on the methods needed to effectively monitor Health Information Exchange (HIE) data content and standards conformance.

The Department of Veterans Affairs' (VA) implementation of the Virtual Lifetime Electronic Record (VLER): findings and lessons learned from Health Information Exchange at 12 sites.

PURPOSE: We describe the Department of Veterans Affairs' (VA) Virtual Lifetime Health Electronic Record (VLER) pilot phase in 12 communities to exchange health information with private sector health care organizations and the Department of Defense (DoD), key findings, lessons, and implications for advancing Health Information Exchanges (HIE), nationally. METHODS: A mixed methods approach was used to monitor and evaluate the status of VLER Health Exchange pilot phase implementation from December 2009 through October 2012. Selected accomplishments, contributions, challenges, and early lessons that are relevant to the growth of nationwide HIE are discussed. RESULTS: Veteran patient and provider acceptance, trust, and perceived value of VLER Health Exchange are found to be high, and usage by providers is steadily growing. Challenges and opportunities to improve provider use are identified, such as better data quality and integration with workflow. Key findings and lessons for advancing HIE are identified. CONCLUSIONS: VLER Health Exchange has made great strides in advancing HIE nationally by addressing important technical and policy issues that have impeded scalability, and by increasing trust and confidence in the value and accuracy of HIE among users. VLER Health Exchange has advanced HIE interoperability standards and patient consent policies nationally. Policy, programmatic, technology, and health Information Technology (IT) standards implications to advance HIE for improved delivery and coordination of health care are discussed. The pilot phase success led to VA-wide deployment of this data sharing capability in 2013.

Toward a Virtual Lifetime Electronic Record: the Department of Veterans Affairs experience with the Nationwide Health Information Network.

Health information exchange is expected of all electronic health records (EHRs) in order to ensure safe, quality care coordination. The U.S. Department of Veterans Affairs (VA) has a long history of information exchange across VA facilities and with the U.S. Department of Defense (DoD). However, since a majority of VA and DoD patients receive a portion of their health care from the private sector, it is essential that both agencies enable health information exchange with private sector providers. This has been made possible by the use of the specifications and trust agreement developed by the Nationwide Health Information Network (NwHIN) initiative. Currently, VA has 12 medical centers exchanging information with the private sector and is evaluating the value of the exchange. The authors report on the success of these pilots as well as on the challenges, which include stricter technical specifications and a more efficient approach to patient identification (ID) matching and consent management.

The Department of Veterans Affairs, Department of Defense, and Kaiser Permanente Nationwide Health Information Network exchange in San Diego: patient selection, consent, and identity matching.

The Nationwide Health Information Network allow for the secure exchange of Electronic Health Records over the Internet. The Department of Veterans Affairs, Department of Defense, and Kaiser Permanente, participated in an implementation of the NwHIN specifications in San Diego, California. This paper focuses primarily on patient involvement. Specifically, it describes how the shared patients were identified, were invited to participate and to provide consent for disclosing parts of their medical record, and were matched across organizations. A total 1,144 were identified as shared patients. Invitation letters containing consent forms were mailed and resulted in 42% participation. Invalid consent forms were a significant issue (25%). Initially, the identity matching algorithms yielded low success rate (5%). However, elimination of certain traits and abbreviations and probabilistic algorithms have significantly increased matching rate. Access to information from external sources better informs providers, improves decisions and efficiency, and helps meet the meaningful use criteria.

Anti-CCL2 treatment inhibits Theiler's murine encephalomyelitis virus-induced demyelinating disease.

Theiler's murine encephalomyelitis virus induces a demyelinating disease (TMEV-IDD) of the central nervous system (CNS) in susceptible mouse strains with accompanying histopathology characterized by mononuclear cell infiltrates. In susceptible strains of mice such as SJL, virus establishes a persistent infection in macrophages, induces a CNS infiltration by macrophages, T cells, and B cells, which results in chronic-progressive paralysis. In the present report the authors have investigated the functional role of CCL2 (monocyte chemotactic protein-1) in the induction and progression of demyelinating disease. Treatment of infected mice at day 0, 14, or 28 with anti-CCL2 resulted in a significant decrease in the clinical disease progression. Further analysis of anti-CCL2-treated mice revealed decreased CNS inflammation and mononuclear cell infiltration with an accompanying change in inflammatory cytokine responses. There was an overall decrease in the absolute numbers of CNS-infiltrating CD4+ T cells, macrophages, and B cells. Finally, anti-CCL2 treatment resulted in decreased viral load in the CNS. These data directly demonstrate a role for CCL2 in the pathogenesis of TMEV-IDD.

Magnetic resonance imaging of pulmonary lesions in guinea pigs infected with Mycobacterium tuberculosis.

We utilized magnetic resonance imaging to visualize lesions in the lungs of guinea pigs infected by low-dose aerosol exposure to Mycobacterium tuberculosis. Lesions were prominent in such images, and colorized three-dimensional reconstructions of images revealed a very uniform distribution in the lungs. Lesion numbers after 1 month were approximately similar to the aerosol exposure algorithm, suggesting that each was established by a single bacterium. Numbers of lesions in unprotected and vaccinated animals were similar over the first month but increased thereafter in the control animals, indicating secondary lesion development. Whereas lesion sizes increased progressively in control guinea pigs, lesions remained small in BCG-vaccinated animals. A prominent feature of the disease pathology in unprotected animals was rapid and severe lymphadenopathy of the mediastinal lymph node cluster, which is paradoxical given the strong state of cellular immunity at this time. Further development of this technical approach could be very useful in tracking lesion size, number, and progression in the search for new tuberculosis vaccines.