Factors Informing High-Risk Primary Care Patient Choice around Telehealth Use: a Framework.

BACKGROUND: While telehealth's presence in post-pandemic primary care appears assured, its exact role remains unknown. Value-based care's expansion has heightened interest in telehealth's potential to improve uptake of preventive and chronic disease care, especially among high-risk primary care populations. Despite this, the pandemic underscored patients' diverse preferences around using telehealth. Understanding the factors underlying this population's preferences can inform future telehealth strategies. OBJECTIVE: To describe the factors informing high-risk primary care patient choice of whether to pursue primary care via telehealth, in-office or to defer care altogether. DESIGN: Qualitative, cross-sectional study utilizing semi-structured telephone interviews of a convenience sample of 29 primary care patients between July 13 and September 30, 2020. PARTICIPANTS: Primary care patients at high risk of poor health outcomes and/or acute care utilization who were offered a follow-up primary care visit via audiovisual, audio-only or in-office modalities. APPROACH: Responses were analyzed via grounded theory, using a constant comparison method to refine emerging categories, distinguish codes, and synthesize evolving themes. KEY RESULTS: Of the 29 participants, 16 (55.2%) were female and 19 (65.5%) were Black; the mean age (SD) was 64.6 (11.1). Participants identified four themes influencing their choice of visit type: perceived utility (encapsulating clinical and non-clinical utility), underlying costs (in terms of time, money, effort, and safety), modifiers (e.g., participants' clinical situation, choice availability, decision phenotype), and drivers (inclusive of their background experiences and digital environment). The relationship of these themes is depicted in a novel framework of patient choice around telehealth use. CONCLUSIONS: While visit utility and cost considerations are foundational to participants' decisions around whether to pursue care via telehealth, underappreciated modifiers and drivers often magnify or mitigate these considerations. Policymakers, payers, and health systems can leverage these factors to anticipate and enhance equitable high-value telehealth use in primary care settings among high-risk individuals.

The use and misuse of the SCOFF screening measure over two decades: a systematic literature review.

PURPOSE: The SCOFF questionnaire was designed as a simple, memorable screening tool to raise suspicion that a person might have an eating disorder. It is over 20 years since the creation of the SCOFF, during which time it has been widely used. Considering this, we wish to review the use of the SCOFF in peer-reviewed scientific journals, and to assess whether it is being used appropriately in the manner in which it was originally devised and tested. METHODS: The Preferred Reporting Items for a Systematic Review and Meta-analysis (PRISMA) guidelines were followed, and all search strategies and methods were determined before the onset of the study. PubMed and Wiley Online Library were searched using the terms SCOFF and eating. Two reviewers were involved in the reviewing process. Criteria for appropriate use of the SCOFF were formalised with the tool's original authors. RESULTS: 180 articles were included in the final review. 48 articles had used the SCOFF appropriately, 117 articles inappropriately and 15 articles had been mixed in the appropriateness of their use. CONCLUSION: This systematic review highlights the inappropriate use of the SCOFF in diverse languages and settings. When used correctly the SCOFF has made a significant contribution to the understanding of eating disorders and its simplicity has been applauded and led to widespread use. However in over two-thirds of studies, the use of the SCOFF was inappropriate and the paper highlights how and in what way it was misused, Guidelines for the appropriate use of the SCOFF are stated. Future validation and avenues of research are suggested. LEVEL OF EVIDENCE: Level I.

Using artificial intelligence and deep learning to optimise the selection of adult congenital heart disease patients in S-ICD screening.

INTRODUCTION: The risk of complications associated with transvenous ICDs make the subcutaneous implantable cardiac defibrillator (S-ICD) a valuable alternative in patients with adult congenital heart disease (ACHD). However, higher S-ICD ineligibility and higher inappropriate shock rates-mostly caused by T wave oversensing (TWO)- are observed in this population. We report a novel application of deep learning methods to screen patients for S-ICD eligibility over a longer period than conventional screening. METHODS: Adult patients with ACHD and a control group of normal subjects were fitted with a 24-h Holters to record their S-ICD vectors. Their T:R ratio was analysed utilising phase space reconstruction matrices and a deep learning-based model to provide an in-depth description of the T: R variation plot for each vector. T: R variation was compared statistically using t-test. RESULTS: 13 patients (age 37.4 ± 7.89 years, 61.5 % male, 6 ACHD and 7 control subjects) were enrolled. A significant difference was observed in the mean and median T: R values between the two groups (p < 0.001). There was also a significant difference in the standard deviation of T: R between both groups (p = 0.04). CONCLUSIONS: T:R ratio, a main determinant for S-ICD eligibility, is significantly higher with more tendency to fluctuate in ACHD patients when compared to a population with normal hearts. We hypothesise that our novel model could be used to select S-ICD eligible patients by better characterisation of T:R ratio, reducing the risk of TWO and inappropriate shocks in the ACHD patient cohort.

Diffusion of volatile organics and water in the epicuticular waxes of petunia petal epidermal cells.

Plant cuticles are a mixture of crystalline and amorphous waxes that restrict the exchange of molecules between the plant and the atmosphere. The multicomponent nature of cuticular waxes complicates the study of the relationship between the physical and transport properties. Here, a model cuticle based on the epicuticular waxes of Petunia hybrida flower petals was formulated to test the effect of wax composition on diffusion of water and volatile organic compounds (VOCs). The model cuticle was composed of an n-tetracosane (C24 H50 ), 1-docosanol (C22 H45 OH), and 3-methylbutyl dodecanoate (C17 H34 O2 ), reflecting the relative chain length, functional groups, molecular arrangements, and crystallinity of the natural waxes. Molecular dynamics simulations were performed to obtain diffusion coefficients for compounds moving through waxes of varying composition. Simulated VOC diffusivities of the model system were found to highly correlate with in vitro measurements in isolated petunia cuticles. VOC diffusivity increased up to 30-fold in completely amorphous waxes, indicating a significant effect of crystallinity on cuticular permeability. The crystallinity of the waxes was highly dependent on the elongation of the lattice length and decrease in gap width between crystalline unit cells. Diffusion of water and higher molecular weight VOCs were significantly affected by alterations in crystalline spacing and lengths, whereas the low molecular weight VOCs were less affected. Comparison of measured diffusion coefficients from atomistic simulations and emissions from petunia flowers indicates that the role of the plant cuticle in the VOC emission network is attributed to the differential control on mass transfer of individual VOCs by controlling the composition, amount, and dynamics of scent emission.

Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis.

Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.

Cuticle thickness affects dynamics of volatile emission from petunia flowers.

The plant cuticle is the final barrier for volatile organic compounds (VOCs) to cross for release to the atmosphere, yet its role in the emission process is poorly understood. Here, using a combination of reverse-genetic and chemical approaches, we demonstrate that the cuticle imposes substantial resistance to VOC mass transfer, acting as a sink/concentrator for VOCs and hence protecting cells from the potentially toxic internal accumulation of these hydrophobic compounds. Reduction in cuticle thickness has differential effects on individual VOCs depending on their volatility, and leads to their internal cellular redistribution, a shift in mass transfer resistance sources and altered VOC synthesis. These results reveal that the cuticle is not simply a passive diffusion barrier for VOCs to cross, but plays the aforementioned complex roles in the emission process as an integral member of the overall VOC network.

Exploring energy landscapes for solid-state systems with variable cells at the extended tight-binding level.

The design of novel materials requires a theoretical understanding of dynamical processes in the solid state, including polymorphic transitions and associated pathways. The organization of the potential energy landscape plays a crucial role in such processes, which may involve changes in the periodic boundaries. This study reports the implementation of a general framework for periodic condensed matter systems in our energy landscape analysis software, allowing for variation in both the unit cell and atomic positions. This implementation provides access to basin-hopping global optimization, the doubly nudged elastic band procedure for identifying transition state candidates, the missing connection approach for multi-step pathways, and general tools for the construction and analysis of kinetic transition networks. The computational efficacy of the procedures is explored using the state-of-the-art semiempirical method GFN1-xTB for the first time in this solid-state context. We investigate the effectiveness of this level of theory by characterizing the potential energy and enthalpy landscapes of several systems, including silicon, CdSe, ZnS, and NaCl, and discuss further technical challenges, such as translational permutation of the cell. Despite the expected limitations of the semiempirical method, we find that the resulting energy landscapes provide useful insight into solid-state simulations, which will facilitate detailed analysis of processes such as defect and ion migration, including refinement at higher levels of theory.

Global analysis of energy landscapes for materials modeling: A test case for C60.

In this contribution, we employ computational tools from the energy landscape approach to test Gaussian Approximation Potentials (GAPs) for C60. In particular, we apply basin-hopping global optimization and explore the landscape starting from the low-lying minima using discrete path sampling. We exploit existing databases of minima and transition states harvested from previous work using tight-binding potentials. We explore the energy landscape for the full range of structures and pathways spanning from the buckminsterfullerene global minimum up to buckybowls. In the initial GAP model, the fullerene part of the landscape is reproduced quite well. However, there are extensive families of C1@C59 and C2@C58 structures that lie lower in energy. We succeeded in refining the potential to remove these artifacts by simply including two minima from the C2@C58 families found by global landscape exploration. We suggest that the energy landscape approach could be used systematically to test and improve machine learning interatomic potentials.

Role of deep learning methods in screening for subcutaneous implantable cardioverter defibrillator in heart failure.

INTRODUCTION: S-ICD eligibility is assessed at pre-implant screening where surface ECG traces are used as surrogates for S-ICD vectors. In heart failure (HF) patients undergoing diuresis, electrolytes and fluid shifts can cause changes in R and T waves. Subsequently, T:R ratio, a major predictor of S-ICD eligibility, can be dynamic. METHODS: This is a prospective study of patients with structurally normal hearts and HF patients undergoing diuresis. All patients were fitted with Holters® to record their S-ICD vectors. Our deep learning model was used to analyze the T:R ratios across the recordings. Welch two sample t-test and Mann-Whitney U were used to compare the data between the two groups. RESULTS: Twenty-one patients (age 58.43 ± 18.92, 62% male, 14 HF, 7 normal hearts) were enrolled. There was a significant difference in the T:R ratios between both groups. Mean T: R was higher in the HF group (0.18 ± 0.08 vs 0.10 ± 0.05, p < .001). Standard deviation of T: R was also higher in the HF group (0.09 ± 0.05 vs 0.07 ± 0.04, p = .024). There was no difference between leads within the same group. CONCLUSIONS: T:R ratio, a main determinant for S-ICD eligibility, is higher and has more tendency to fluctuate in HF patients undergoing diuresis. We hypothesize that our novel neural network model could be used to select HF patients eligible for S-ICD by better characterization of T:R ratio reducing the risk of T-wave over-sensing (TWO) and inappropriate shocks. Further work is required to consolidate our findings before applying to clinical practice.

Correlation analysis of deep learning methods in S-ICD screening.

BACKGROUND: Machine learning methods are used in the classification of various cardiovascular diseases through ECG data analysis. The concept of varying subcutaneous implantable cardiac defibrillator (S-ICD) eligibility, owing to the dynamicity of ECG signals, has been introduced before. There are practical limitations to acquiring longer durations of ECG signals for S-ICD screening. This study explored the potential use of deep learning methods in S-ICD screening. METHODS: This was a retrospective study. A deep learning tool was used to provide descriptive analysis of the T:R ratios over 24 h recordings of S-ICD vectors. Spearman's rank correlation test was used to compare the results statistically to those of a "gold standard" S-ICD simulator. RESULTS: A total of 14 patients (mean age: 63.7 ± 5.2 years, 71.4% male) were recruited and 28 vectors were analyzed. Mean T:R, standard deviation of T:R, and favorable ratio time (FVR)-a new concept introduced in this study-for all vectors combined were 0.21 ± 0.11, 0.08 ± 0.04, and 79 ± 30%, respectively. There were statistically significant strong correlations between the outcomes of our novel tool and the S-ICD simulator (p < .001). CONCLUSION: Deep learning methods could provide a practical software solution to analyze data acquired for longer durations than current S-ICD screening practices. This could help select patients better suited for S-ICD therapy as well as guide vector selection in S-ICD eligible patients. Further work is needed before this could be translated into clinical practice.

Group B Streptococcus Rectovaginal Colonization and Resistance Patterns in HIV-Positive Compared to HIV-Negative Pregnant Patients.

OBJECTIVE: The objective of our study is to determine if human immunodeficiency virus (HIV)-positive pregnant patients have a higher rate of group B streptococcus (GBS) rectovaginal colonization compared with HIV-negative pregnant patients. STUDY DESIGN: Our study is a multi-site retrospective study performed at Ochsner Louisiana State University-Health Shreveport and Monroe campuses including patients who delivered between December 2011and June 2019. Rates of GBS rectovaginal colonization between HIV-positive pregnant patients were compared with a control group of HIV-negative patients. The control group was age and race matched in a 2:1 fashion. The primary outcome was to investigate rates of GBS rectovaginal colonization. Secondary outcomes included GBS culture antibiotic sensitivities, presence of GBS urinary tract infection, GBS positivity based on HIV viral load, and GBS positivity based on new vs established diagnosis of HIV. Continuous data were analyzed using an unpaired t-test, and categorical data were analyzed using a Chi-squared test. The probability level of <0.05 was set as statistically significant. RESULTS: A total of 225 patients were included in the final analysis, 75 HIV-positive and 150 HIV-negative controls. Demographic differences were noted. HIV-positive patients were more likely to deliver preterm and were more likely to deliver via cesarean section. Our primary outcome showed no significant differences in incidence of GBS colonization between HIV-positive patients and control group (n = 31, 41.3% vs n = 46, 30.6%, p = 0.136). Antibiotic resistance patterns showed no significant difference between the two groups. There were no significant differences in GBS positivity based on HIV viral load. CONCLUSION: Our study does not show a statistically significant difference in the incidence of GBS colonization between HIV-positive patients and HIV-negative controls. KEY POINTS: · HIV-positive pregnant patients do not have an increased risk of GBS rectovaginal colonization.. · HIV-positive pregnant patients have similar rates of GBS colonization regardless of viral load.. · GBS antibiotic sensitivities are similar in HIV-positive and HIV-negative pregnant patients..

CD30 Regulation of IL-13-STAT6 Pathway in Breast Implant-Associated Anaplastic Large Cell Lymphoma.

BACKGROUND: Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare, usually indolent CD30+ T-cell lymphoma with tumor cells, often surrounded by eosinophils, expressing IL-13 and pSTAT6. OBJECTIVES: The aim of this study was to understand the unique tumor pathology and growth regulation of BIA-ALCL, leading to potential targeted therapies. METHODS: We silenced CD30 and analyzed its effect on IL-13 signaling and tumor cell viability. IL-13 signaling receptors of BIA-ALCL cell lines were evaluated by flow cytometry and pSTAT6 detected by immunohistochemistry. CD30 was deleted by CRISPR/Cas9 editing. Effects of CD30 deletion on transcription of IL-13 and IL-4, and phosphorylation of STAT6 were determined by real-time polymerase chain reaction and western blotting. The effect of CD30 deletion on p38 mitogen-activated protein kinase (MAPK) phosphorylation was determined. Suppression of IL-13 transcription by a p38 MAPK inhibitor was tested. Tumor cell viability following CD30 deletion and treatment with a pSTAT6 inhibitor were measured in cytotoxicity assays. RESULTS: BIA-ALCL lines TLBR1 and TLBR2 displayed signaling receptors IL-4Rα, IL-13Rα1 and downstream pSTAT6. Deletion of CD30 by CRISPR/Cas9 editing significantly decreased transcription of IL-13, less so Th2 cytokine IL-4, and phosphorylation of STAT6. Mechanistically, we found CD30 expression is required for p38 MAPK phosphorylation and activation, and IL-13-STAT6 signaling was reduced by an inhibitor of p38 MAPK in BIA-ALCL tumor cells. Tumor cell viability was decreased by silencing of CD30, and a specific inhibitor of STAT6, indicating STAT6 inhibition is cytotoxic to BIA-ALCL tumor cells. CONCLUSIONS: These findings suggest reagents targeting the IL-13 pathway, pSTAT6 and p38 MAPK, may become useful for treating BIA-ALCL patients.

Overexpression of arogenate dehydratase reveals an upstream point of metabolic control in phenylalanine biosynthesis.

Out of the three aromatic amino acids, the highest flux in plants is directed towards phenylalanine, which is utilized to synthesize proteins and thousands of phenolic metabolites contributing to plant fitness. Phenylalanine is produced predominantly in plastids via the shikimate pathway and subsequent arogenate pathway, both of which are subject to complex transcriptional and post-transcriptional regulation. Previously, it was shown that allosteric feedback inhibition of arogenate dehydratase (ADT), which catalyzes the final step of the arogenate pathway, restricts flux through phenylalanine biosynthesis. Here, we show that in petunia (Petunia hybrida) flowers, which typically produce high phenylalanine levels, ADT regulation is relaxed, but not eliminated. Moderate expression of a feedback-insensitive ADT increased flux towards phenylalanine, while high overexpression paradoxically reduced phenylalanine formation. This reduction could be partially, but not fully, recovered by bypassing other known metabolic flux control points in the aromatic amino acid network. Using comparative transcriptomics, reverse genetics, and metabolic flux analysis, we discovered that transcriptional regulation of the d-ribulose-5-phosphate 3-epimerase gene in the pentose phosphate pathway controls flux into the shikimate pathway. Taken together, our findings reveal that regulation within and upstream of the shikimate pathway shares control over phenylalanine biosynthesis in the plant cell.

Nutrient identity modifies the destabilising effects of eutrophication in grasslands.

Nutrient enrichment can simultaneously increase and destabilise plant biomass production, with co-limitation by multiple nutrients potentially intensifying these effects. Here, we test how factorial additions of nitrogen (N), phosphorus (P) and potassium with essential nutrients (K+) affect the stability (mean/standard deviation) of aboveground biomass in 34 grasslands over 7 years. Destabilisation with fertilisation was prevalent but was driven by single nutrients, not synergistic nutrient interactions. On average, N-based treatments increased mean biomass production by 21-51% but increased its standard deviation by 40-68% and so consistently reduced stability. Adding P increased interannual variability and reduced stability without altering mean biomass, while K+ had no general effects. Declines in stability were largest in the most nutrient-limited grasslands, or where nutrients reduced species richness or intensified species synchrony. We show that nutrients can differentially impact the stability of biomass production, with N and P in particular disproportionately increasing its interannual variability.

Linking changes in species composition and biomass in a globally distributed grassland experiment.

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.

Nutrients and herbivores impact grassland stability across spatial scales through different pathways.

Nutrients and herbivores are well-known drivers of grassland diversity and stability in local communities. However, whether they interact to impact the stability of aboveground biomass and whether these effects depend on spatial scales remain unknown. It is also unclear whether nutrients and herbivores impact stability via different facets of plant diversity including species richness, evenness, and changes in community composition through time and space. We used a replicated experiment adding nutrients and excluding herbivores for 5 years in 34 global grasslands to explore these questions. We found that both nutrient addition and herbivore exclusion alone reduced stability at the larger spatial scale (aggregated local communities; gamma stability), but through different pathways. Nutrient addition reduced gamma stability primarily by increasing changes in local community composition over time, which was mainly driven by species replacement. Herbivore exclusion reduced gamma stability primarily by decreasing asynchronous dynamics among local communities (spatial asynchrony). Their interaction weakly increased gamma stability by increasing spatial asynchrony. Our findings indicate that disentangling the processes operating at different spatial scales may improve conservation and management aiming at maintaining the ability of ecosystems to reliably provide functions and services for humanity.

Modulation of auxin formation by the cytosolic phenylalanine biosynthetic pathway.

In plants, phenylalanine biosynthesis occurs via two compartmentally separated pathways. Overexpression of petunia chorismate mutase 2 (PhCM2), which catalyzes the committed step of the cytosolic pathway, increased flux in cytosolic phenylalanine biosynthesis, but paradoxically decreased the overall levels of phenylalanine and phenylalanine-derived volatiles. Concomitantly, the levels of auxins, including indole-3-acetic acid and its precursor indole-3-pyruvic acid, were elevated. Biochemical and genetic analyses revealed the existence of metabolic crosstalk between the cytosolic phenylalanine biosynthesis and tryptophan-dependent auxin biosynthesis mediated by an aminotransferase that uses a cytosolic phenylalanine biosynthetic pathway intermediate, phenylpyruvate, as an amino acceptor for auxin formation.

Livestock grazing to maintain habitat of a critically endangered grassland bird: Is grazer species important?

Livestock grazing is an important management tool for biodiversity conservation in many native grasslands across the globe. Understanding how different grazing species interact with their environment is integral to achieving conservation goals. In the semiarid grasslands of Australia, grazing by sheep or cattle is used to manipulate vegetation structure to suit the habitat needs of a globally unique, critically endangered grassland bird, the plains-wanderer Pedionomus torquatus. However, there has been no investigation of whether sheep and cattle differ in their effects on plains-wanderer habitat and, therefore, it is unknown if these grazers are substitutable as a management tool. Using a grazing experiment in native grasslands over 3 years, we determined the effects of grazer type (sheep, cattle) on occurrence and vocal activity of plains-wanderer, vegetation structure and composition, and food availability. We also examined grazer effects on encounter rates of other grassland birds. Plains-wanderer breeding activity was inferred from vocalization rates captured by bioacoustic recorders. Spotlighting was used to measure encounter rates of other grassland birds. We found that different grazers altered the structure of the habitat. Grasslands grazed by cattle were typically more open, less variable, and lacked patches of dense vegetation relative to those grazed by sheep. Grazer type did not influence the likelihood of plains-wanderer occurrence, but it did interact with year of survey to affect breeding activity. The number of days with one or more calls significantly increased at sheep grazed sites in year-3, which coincided with enduring drought conditions. Similarly, grazer effects on encounter rate of all birds, bird species richness, and Australasian pipit Anthus novaeseelandiae were different between years. Dense vegetation specialists (such as stubble quail Coturnix pectoralis) were positively associated with grasslands grazed by sheep. As a habitat management tool, sheep or cattle grazing are useful when the goal is to support an open grassland structure for the plains-wanderer. However, their substitutability is likely to be dependent upon climate. We caution that a loss of dense vegetation in grasslands grazed by cattle during drought could limit the availability of optimal habitat for the plains-wanderer and habitat for other grassland birds.

Personalized subcutaneous implantable cardioverter-defibrillator sensing vectors generated by mathematical rotation increase device eligibility whilst preserving device performance.

AIMS: Approximately 5.7% of potential subcutaneous implantable cardioverter-defibrillator (S-ICD) recipients are ineligible by virtue of their vector morphology, with higher rates of ineligibility observed in some at-risk groups. Mathematical vector rotation is a novel technique that can generate a personalized sensing vector, one with maximal R:T ratio, using electrocardiogram (ECG) signal recorded from the present S-ICD location. METHODS AND RESULTS: A cohort of S-ICD ineligible patients were identified through ECG screening of ICD patients with no ventricular pacing requirement and their personalized vectors were generated using ECG signal from a Holter monitor. Subcutaneous ICD eligibility in this cohort was then recalculated. In a separate cohort, episodes of arrhythmia were recorded in patients undergoing arrhythmia induction, and arrhythmia detection in standard S-ICD vectors was compared to rotated vectors using an S-ICD simulator. Ninety-two participants (mean age 64.9 ± 2.7 years) underwent screening and 5.4% were found to be S-ICD ineligible. Personalized vector generation increased the R:T ratio in these vectors from 2.21 to 7.21 (4.54-9.88, P < 0.001) increasing the cohort eligibility from 94.6% to 100%. Rotated S-ICD vectors also showed high ventricular fibrillation (VF) detection sensitivity (97.8%), low time to VF detection (6.1 s), and excellent tachycardia discrimination (sensitivity 96%, specificity 88%), with no significant differences between rotated and standard vectors. CONCLUSION: In S-ICD ineligible patients, mathematical vector rotation can generate a personalized vector that is associated with a significant increase in R:T ratio, resulting in universal device eligibility in our cohort. Ventricular fibrillation detection efficacy, time to VF detection, and tachycardia discrimination were not affected by vector rotation.

Richness, not evenness, varies across water availability gradients in grassy biomes on five continents.

We sought to understand the role that water availability (expressed as an aridity index) plays in determining regional and global patterns of richness and evenness, and in turn how these water availability-diversity relationships may result in different richness-evenness relationships at regional and global scales. We examined relationships between water availability, richness and evenness for eight grassy biomes spanning broad water availability gradients on five continents. Our study found that relationships between richness and water availability switched from positive for drier (South Africa, Tibet and USA) vs. negative for wetter (India) biomes, though were not significant for the remaining biomes. In contrast, only the India biome showed a significant relationship between water availability and evenness, which was negative. Globally, the richness-water availability relationship was hump-shaped, however, not significant for evenness. At the regional scale, a positive richness-evenness relationship was found for grassy biomes in India and Inner Mongolia, China. In contrast, this relationship was weakly concave-up globally. These results suggest that different, independent factors are determining patterns of species richness and evenness in grassy biomes, resulting in differing richness-evenness relationships at regional and global scales. As a consequence, richness and evenness may respond very differently across spatial gradients to anthropogenic changes, such as climate change.