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.

Relative contribution of photodegradation to litter breakdown in Australian grasslands.

Grassy ecosystems cover ~40% of the global land surface and are an integral component of the global carbon (C) cycle. Grass litter decomposes via a combination of photodegradation (which returns C to the atmosphere rapidly) and biological decomposition (a slower C pathway). As such, decomposition and C storage in grasslands may vary with climate and exposure to solar radiation. We investigated rates of grass litter decomposition in Australian temperate grasslands along a climate gradient to uncouple the relative importance of photodegradation and climate on decomposition. Litterbags containing leaf litter from two common native grass species (Poa labillardierei, Themeda triandra) were deployed at six grassland sites across a precipitation gradient (380-890 mm) in south-eastern Australia. Bags were retrieved over 39 weeks to measure mass loss from decomposition. We used shade treatments on the litter of one species (T. triandra) to partition photodegradation from biological decomposition. The shade treatment reduced the rate of decomposition of T. triandra relative to the full-sun treatment at all sites, by an average of 38% at 39 weeks; the effect size of the shade treatment was not correlated with site productivity. The rate of decomposition in both species was positively correlated with rainfall midway through the experiment, but there were no significant differences in total decomposition among sites after 39 weeks. By week 39, total decomposition of T. triandra was significantly greater than for P. labillardierei. In general, we observed relatively linear decomposition rather than the strong negative exponential decay observed in many global litter decomposition studies. Synthesis: We found that solar radiation exposure was a strong contributor to litter decomposition in temperate Australian grasslands across a broad climate gradient, which may be related to a period of photopriming prior to further biotic decomposition. This study highlights the importance of litter composition and solar radiation exposure in our understanding of how decomposition patterns contribute to global C cycling.

Assessing the diet and seed dispersal ability of non-native sambar deer (Rusa unicolor) in native ecosystems of south-eastern Australia.

Understanding the influence of non-native herbivores on ecosystems by means of dietary foraging and seed dispersal is important for understanding how non-native species can alter an invaded landscape, yet requires multiple methodologies. In south-eastern Australia, introduced sambar deer (Rusa unicolor) are rapidly expanding in range and placing native ecosystems at risk through browsing and as vectors for seed dispersal. We simultaneously investigated sambar deer dietary composition and seed dispersal using DNA sequencing and germination trials, from faecal pellets collected in alpine and wet forest ecosystems. This allowed us to contrast the dietary impacts of introduced sambar deer in different environments, and to explore the potential for habitat-specific variation in diet. DNA sequencing of the trnL, ITS2 and rbcL gene regions revealed a diverse plant species dietary composition comprising 1003 operational taxonomic units (OTUs). Sambar deer exhibited intermediate feeder behaviours dominated by forbs in alpine and shrubs in wet forest ecosystems. A large proportion of plant OTUs were considered likely to be native, however, the proportion of exotic species in the diet in both ecosystems was greater than would be expected based on the proportion of exotic species in each of the two landscapes. Seed germination trials indicated that sambar deer can disperse a substantial number of native and exotic species in both alpine and wet forest ecosystems. In alpine ecosystems, an individual sambar deer was estimated to disperse on average 816 (±193) seeds per day during the study period, of which 652 (±176) were exotic. Synthesis and applications. Our results suggest that native plant species comprise the majority of sambar deer diets in Australian ecosystems and that the introduced species is dispersing both native and exotic plant species via endozoochory. However, exotic species seedling germination numbers were significantly higher in alpine ecosystems, and given the large daily movements of sambar deer, represents a significant vector for the spread of exotic plant species. Management of native plant species and vegetation communities of conservation significance, or at risk to sambar deer browsing is of high priority, through either the removal of sambar deer or implementation of exclusion-based methods.

Energy landscapes for proteins described by the UNRES coarse-grained potential.

The self-assembly of proteins is encoded in the underlying potential energy surface (PES), from which we can predict structure, dynamics, and thermodynamic properties. However, the corresponding analysis becomes increasingly challenging with larger protein sizes, due to the computational time required, which grows significantly with the number of atoms. Coarse-grained models offer an attractive approach to reduce the computational cost. In this Feature Article, we describe our implementation of the UNited RESidue (UNRES) coarse-grained potential in the Cambridge energy landscapes software. We have applied this framework to explore the energy landscapes of four proteins that exhibit native states involving different secondary structures. Here we have tested the ability of the UNRES potential to represent the global energy landscape of proteins containing up to 100 amino acid residues. The resulting potential energy landscapes exhibit good agreement with experiment, with low-lying minima close to the PDB geometries and to results obtained using the all-atom AMBER force field. The new program interfaces will allow us to investigate larger biomolecules in future work, using the UNRES potential in combination with all the methodology available in the computational energy landscapes framework.

Multidimensional responses of grassland stability to eutrophication.

Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change.

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.

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.

Advancing health equity through medication formulary policy.

Awareness of the presence and significance of disparities in American health outcomes is growing. Equitable access to appropriate medication-pharmacoequity-is foundational to equitable health care, with medication formularies representing a key determinant of medication access. Critical formulary design elements include clinical criteria, prescription processes, and patient access policies. Facets of each can be refined to ensure more equitable access to medications, including avoidance of prior authorization requirements, awareness of the complex determinants of human behavior, streamlined authorization processes, and optimized costs and convenience for patients. Optimizing these factors for proven treatments of conditions disproportionately borne by vulnerable communities is especially critical in the pursuit of equitable access. For policy makers at payer and pharmacy benefit manager organizations to successfully pursue corresponding changes in formulary policy, it is critical that teams educate leadership regarding the importance of policy change, invest in comprehensive patient data, and engage community members in their efforts.

Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference.

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs - designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [-4.1, -0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones.

Rapid upwards spread of non-native plants in mountains across continents.

High-elevation ecosystems are among the few ecosystems worldwide that are not yet heavily invaded by non-native plants. This is expected to change as species expand their range limits upwards to fill their climatic niches and respond to ongoing anthropogenic disturbances. Yet, whether and how quickly these changes are happening has only been assessed in a few isolated cases. Starting in 2007, we conducted repeated surveys of non-native plant distributions along mountain roads in 11 regions from 5 continents. We show that over a 5- to 10-year period, the number of non-native species increased on average by approximately 16% per decade across regions. The direction and magnitude of upper range limit shifts depended on elevation across all regions. Supported by a null-model approach accounting for range changes expected by chance alone, we found greater than expected upward shifts at lower/mid elevations in at least seven regions. After accounting for elevation dependence, significant average upward shifts were detected in a further three regions (revealing evidence for upward shifts in 10 of 11 regions). Together, our results show that mountain environments are becoming increasingly exposed to biological invasions, emphasizing the need to monitor and prevent potential biosecurity issues emerging in high-elevation ecosystems.

Enhancing Biomolecular Simulations with Hybrid Potentials Incorporating NMR Data.

Some recent advances in biomolecular simulation and global optimization have used hybrid restraint potentials, where harmonic restraints that penalize conformations inconsistent with experimental data are combined with molecular mechanics force fields. These hybrid potentials can be used to improve the performance of molecular dynamics, structure prediction, energy landscape sampling, and other computational methods that rely on the accuracy of the underlying force field. Here, we develop a hybrid restraint potential based on NapShift, an artificial neural network trained to predict protein nuclear magnetic resonance (NMR) chemical shifts from sequence and structure. In addition to providing accurate predictions of experimental chemical shifts, NapShift is fully differentiable with respect to atomic coordinates, which allows us to use it for structural refinement. By employing NapShift to predict chemical shifts from the protein conformation at each simulation step, we can compute an energy penalty and the corresponding hybrid restraint forces based on the difference between the predicted values and the experimental chemical shifts. The performance of the hybrid restraint potential was benchmarked using both basin-hopping global optimization and molecular dynamics simulations. In each case, the NapShift hybrid potential improved the accuracy, leading to better structure prediction via basin-hopping and increased local stability in molecular dynamics simulations. Our results suggest that neural network hybrid potentials based on NMR observables can enhance a broad range of molecular simulation methods, and the prediction accuracy will improve as more experimental training data become available.

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.

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.

Survival and growth of a high-mountain daisy transplanted outside its local range, and implications for climate-induced distribution shifts.

Field transplant experiments can improve our understanding of the effects of climate on distributions of plants versus a milieu of biotic factors which may be mediated by climate. We use a transplant experiment to test how survival and growth of a mountain-top daisy (Podolepis robusta), when planted within and outside its current local range, varies as a function of individual plant size, elevation, aspect and the presence of other vegetation. We expected a home-site advantage for the species, with highest survival and growth within the species' current elevational limits, and a decline in vital rates above (due to physiological limitations) and below (due to competition with near-neighbours) these limits. Transplant survival during the beginning of the census was high (89 %), though by the third growing season, 36 % of initial transplants were remaining. Elevation had a significant negative effect on individual mortality rates; plants growing at higher elevations had a lower estimated hazard rate and thus, higher survival relative to those planted at elevations below the current lower limit of the distribution. By contrast, we detected no significant effect of elevation on growth rates. Small vegetation gaps had no effect on growth rates, though we found a negative, but non-significant, effect on mortality rates. Aspect had a very strong impact on growth. Plants transplanted to cool aspects had a significantly lower growth rate relative to transplants growing on a warm aspect. Conversely, aspect was not a significant predictor of individual mortality rates. Restrictions on the local distribution of P. robusta appear to be governed by mortality drivers at lower elevation and by growth drivers associated with aspect. We highlight that our ability to understand the drivers of distributions in current and future climates will be limited if contextual- and individual-level plant responses remain understudied.

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.

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients.

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

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.

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.

Gram-Negative Bacterial Lipopolysaccharide Promotes Tumor Cell Proliferation in Breast Implant-Associated Anaplastic Large-Cell Lymphoma.

Breast implant-associated anaplastic large-cell lymphoma (BIA-ALCL) is a distinct malignancy associated with textured breast implants. We investigated whether bacteria could trigger the activation and multiplication of BIA-ALCL cells in vitro. BIA-ALCL patient-derived BIA-ALCL tumor cells, BIA-ALCL cell lines, cutaneous ALCL cell lines, an immortal T-cell line (MT-4), and peripheral blood mononuclear cells (PBMC) from BIA-ALCL, capsular contracture, and primary augmentation patients were studied. Cells were subjected to various mitogenic stimulation assays including plant phytohemagglutinin (PHA), Gram-negative bacterial lipopolysaccharide (LPS), Staphylococcal superantigens enterotoxin A (SEA), toxic shock syndrome toxin-1 (TSST-1), or sterilized implant shells. Patient-derived BIA-ALCL tumor cells and BIA-ALCL cell lines showed a unique response to LPS stimulation. This response was dampened significantly in the presence of a Toll-like receptor 4 (TLR4) inhibitor peptide. In contrast, cutaneous ALCL cells, MT-4, and PBMC cells from all patients responded significantly more to PHA, SEA, and TSST-1 than to LPS. Breast implant shells of all surface grades alone did not produce a proliferative response of BIA-ALCL cells, indicating the breast implant does not act as a pro-inflammatory stimulant. These findings indicate a possible novel pathway for LPS to promote BIA-ALCL cell proliferation via a TLR4 receptor-mediated bacterial transformation of T-cells into malignancy.