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.

Energy landscapes for clusters of hexapeptides.

We present the results for energy landscapes of hexapeptides obtained using interfaces to the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. We have used basin-hopping global optimization and discrete path sampling to explore the landscapes of hexapeptide monomers, dimers, and oligomers containing 10, 100, and 200 monomers modeled using a residue-level coarse-grained potential, Mpipi, implemented in LAMMPS. We find that the dimers of peptides containing amino acid residues that are better at promoting phase separation, such as tyrosine and arginine, have melting peaks at higher temperature in their heat capacity compared to phenylalanine and lysine, respectively. This observation correlates with previous work on the same uncapped hexapeptide monomers modeled using atomistic potential. For oligomers, we compare the variation in monomer conformations with radial distance and observe trends for selected angles calculated for each monomer. The LAMMPS interfaces to the GMIN and OPTIM programs for landscape exploration offer new opportunities to investigate larger systems and provide access to the coarse-grained potentials implemented within LAMMPS.

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.

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.

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.

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.

Integrative modelling reveals mechanisms linking productivity and plant species richness.

How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

Addition of multiple limiting resources reduces grassland diversity.

Niche dimensionality provides a general theoretical explanation for biodiversity-more niches, defined by more limiting factors, allow for more ways that species can coexist. Because plant species compete for the same set of limiting resources, theory predicts that addition of a limiting resource eliminates potential trade-offs, reducing the number of species that can coexist. Multiple nutrient limitation of plant production is common and therefore fertilization may reduce diversity by reducing the number or dimensionality of belowground limiting factors. At the same time, nutrient addition, by increasing biomass, should ultimately shift competition from belowground nutrients towards a one-dimensional competitive trade-off for light. Here we show that plant species diversity decreased when a greater number of limiting nutrients were added across 45 grassland sites from a multi-continent experimental network. The number of added nutrients predicted diversity loss, even after controlling for effects of plant biomass, and even where biomass production was not nutrient-limited. We found that elevated resource supply reduced niche dimensionality and diversity and increased both productivity and compositional turnover. Our results point to the importance of understanding dimensionality in ecological systems that are undergoing diversity loss in response to multiple global change factors.

Species loss due to nutrient addition increases with spatial scale in global grasslands.

The effects of altered nutrient supplies and herbivore density on species diversity vary with spatial scale, because coexistence mechanisms are scale dependent. This scale dependence may alter the shape of the species-area relationship (SAR), which can be described by changes in species richness (S) as a power function of the sample area (A): S = cAz , where c and z are constants. We analysed the effects of experimental manipulations of nutrient supply and herbivore density on species richness across a range of scales (0.01-75 m2 ) at 30 grasslands in 10 countries. We found that nutrient addition reduced the number of species that could co-occur locally, indicated by the SAR intercepts (log c), but did not affect the SAR slopes (z). As a result, proportional species loss due to nutrient enrichment was largely unchanged across sampling scales, whereas total species loss increased over threefold across our range of sampling scales.

Predicting species and community responses to global change using structured expert judgement: An Australian mountain ecosystems case study.

Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which have already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we use a structured expert elicitation method (the IDEA protocol) to estimate the change in abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles are expected to decline in abundance than other species. While long-term ecological data will always be the gold standard for informing the future of biodiversity, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and a paucity of data.

Gastric Cancer Peritoneal Carcinomatosis Risk Score.

BACKGROUND: Gastric cancer (GC) peritoneal carcinomatosis (PC) is associated with a poor prognosis. Although grade, histology, and stage are associated with PC, the cumulative risk of PC when multiple risk factors are present is unknown. This study aimed to develop a cumulative GCPC risk score based on individual demographic/tumor characteristics. METHODS: Patient-level data (2004-2014) from the California Cancer Registry were reviewed by creating a keyword search algorithm to identify patients with gastric PC. Multivariable logistic regression was used to assess demographic/tumor characteristics associated with PC in a randomly selected testing cohort. Scores were assigned to risk factors based on beta coefficients from the logistic regression result, and these scores were applied to the remainder of the subjects (validation cohort). The summed scores of each risk factor formed the total risk score. These were grouped, showing the percentages of patients with PC. RESULTS: The study identified 4285 patients with gastric adenocarcinoma (2757 males, 64.3%). The median age of the patients was 67 years (interquartile range [IQR], 20 years). Most of the patients were non-Hispanic white (n = 1748, 40.8%), with proximal (n = 1675, 39.1%) and poorly differentiated (n = 2908, 67.9%) tumors. The characteristics most highly associated with PC were T4 (odds ratio [OR], 3.12; 95% confidence interval [CI], 2.19-4.44), overlapping location (OR 2.27; 95% CI 1.52-3.39), age of 20-40 years (OR 3.42; 95% CI 2.24-5.21), and Hispanic ethnicity (OR 1.86; 95% CI 1.36-2.54). The demographic/tumor characteristics used in the risk score included age, race/ethnicity, T stage, histology, tumor grade, and location. Increasing GCPC score was associated with increasing percentage of patients with PC. CONCLUSION: Based on demographic/tumor characteristics in GC, it is possible to distinguish groups with varying odds for PC. Understanding the risk for PC based on the cumulative effect of high-risk features can help clinicians to customize surveillance strategies and can aid in early identification of PC.

Peritoneal carcinomatosis in gastric cancer: Are Hispanics at higher risk?

BACKGROUND: A recent study from our group identified Hispanic race/ethnicity as an independent predictor of peritoneal carcinomatosis (PC) in gastric cancer. We sought to identify the tumor factors that might contribute to this strong association in Hispanics. METHODS: California Cancer Registry data were used to identify patients diagnosed with gastric adenocarcinoma from 2004 to 2014. Logistic regression analyses were performed to determine odds ratios for cancer stage, tumor location, grade, histology, and PC. RESULTS: Of 16,275 patients with gastric adenocarcinoma who met inclusion criteria, 6463 (39.7%) were non-Hispanic White (NHW), 4953 (30.4%) were Hispanic, 1020 (6.3%) were non-Hispanic Black (NHB), and 3915 (23.6%) were Asian/other. Compared to NHW, Hispanics were more likely to have a poorly differentiated grade (65.9% vs. 57.6%; p < .001), signet ring adenocarcinoma (28.1% vs. 17.6%; p < .001) and stage IV (51.9% vs. 45.0%; p < .001) gastric cancer. The proportion of stage IV patients with PC was also significantly higher in Hispanics compared to NHW, NHB, and Asian/other (28.5% vs. 16.6%, 20.5%, and 25.2%, respectively; p < .001). CONCLUSIONS: Hispanic ethnicity is an independent predictor of aggressive tumor phenotype and PC. Disproportionate incidence of signet ring adenocarcinoma and PC highlight the need to explore the genomic differences in Hispanic gastric cancer.

The alchemical energy landscape for a pentameric cluster.

We investigate the energy landscape of an alchemical system of point particles in which the parameters of the interparticle potential are treated as degrees of freedom. Using geometrical optimization, we locate minima and transition states on the landscape for pentamers. We show that it is easy to find the parameters that give the lowest energy minimum and that the distribution of minima on the alchemical landscape is concentrated in particular areas. In contrast to the usual changes to an energy landscape when adding more degrees of freedom, we find that introducing alchemical degrees of freedom can reduce the number of minima. Moreover, compared to landscapes of the same system with fixed parameters, these minima on the alchemical landscape are separated by high barriers. We classify transition states on the alchemical landscape by whether they become minima or remain transition states when the potential parameters are fixed at the stationary point value. We show that those that become minima have a significant alchemical component in the direction of the pathway, while those that remain as transition states can be characterized mainly in terms of atomic displacements.

Effects of drought and fire on resprouting capacity of 52 temperate Australian perennial native grasses.

It remains uncertain how perennial grasses with different photosynthetic pathways respond to fire, and how this response varies with stress at the time of burning. Resprouting after fire was examined in relation to experimentally manipulated pre-fire watering frequencies. We asked the following questions: are there response differences to fire between C3 and C4 grasses? And, how does post-fire resprouting vary with pre-fire drought stress? Fifty-two perennial Australian grasses (37 genera, 13 tribes) were studied. Three watering frequencies were applied to simulate increasing drought. Pre-fire tiller number, tiller density, specific leaf area and leaf dry matter content were measured as explanatory variables to assess response. Most species (90%) and individuals (79%) resprouted following experimental burning. C4 grasses had higher probabilities of surviving fire relative to C3 grasses. Responses were not related to phylogeny or tribe. High leaf dry matter content reduced the probability of dying, but also reduced the re-emergence of tillers. Post-fire tiller number increased with increasing drought, regardless of photosynthetic type, suggesting that drought plays a role in the ability of grasses to recover after fire. This has implications for understanding the persistence of species in landscapes where fire management is practiced.

Spatial heterogeneity in species composition constrains plant community responses to herbivory and fertilisation.

Environmental change can result in substantial shifts in community composition. The associated immigration and extinction events are likely constrained by the spatial distribution of species. Still, studies on environmental change typically quantify biotic responses at single spatial (time series within a single plot) or temporal (spatial beta diversity at single time points) scales, ignoring their potential interdependence. Here, we use data from a global network of grassland experiments to determine how turnover responses to two major forms of environmental change - fertilisation and herbivore loss - are affected by species pool size and spatial compositional heterogeneity. Fertilisation led to higher rates of local extinction, whereas turnover in herbivore exclusion plots was driven by species replacement. Overall, sites with more spatially heterogeneous composition showed significantly higher rates of annual turnover, independent of species pool size and treatment. Taking into account spatial biodiversity aspects will therefore improve our understanding of consequences of global and anthropogenic change on community dynamics.

Impact of Breast Reconstruction on Time to Definitive Surgical Treatment, Adjuvant Therapy, and Breast Cancer Outcomes.

BACKGROUND: Delays in surgery and adjuvant treatment for breast cancer are associated with decreased survival. However, the time between diagnosis and surgery is rising, partly attributed to the added complexity of immediate breast reconstruction (IBR). We sought to investigate time to treatment and survival outcomes in breast cancer patients undergoing IBR. METHODS: We performed a retrospective review of 2004-2014 California Cancer Registry data for stage 0-III breast cancer patients undergoing mastectomy. Time to surgery, adjuvant systemic therapy and radiation therapy, propensity score, and covariate-adjusted overall mortality hazard ratios (HRs) were assessed by IBR status. RESULTS: Of 56,782 patients, 13,738 (24.2%) underwent IBR, with a median follow-up of 68.8 months. Median time between diagnosis and surgery was increased for patients undergoing IBR compared with those without {49 days (interquartile range [IQR] 34-73) vs. 35 days (IQR 21-56), p < 0.001}. IBR did not affect the interval from surgery to adjuvant chemotherapy or radiation, but prolonged time to endocrine therapy by 5 days (p = 0.014). Significantly lower survival was observed when time to surgery exceeded 120 days (vs. 0-30 days; HR 1.14 [1.02-1.28], p = 0.023), and improved survival with IBR (vs. without; HR 0.67 [0.61-0.74], p < 0.001). The benefit associated with reconstruction persisted for all age groups except age 80 + years, while surgical delay > 120 days demonstrated significantly lower survival in women < 60 years of age. CONCLUSIONS: While IBR delays time to definitive surgery, its use did not substantially affect time to adjuvant treatment or survival outcomes. Further research is ongoing to mitigate the effects of potential selection bias in favor of IBR.

High-Risk Stage II Colon Cancer: Not All Risks Are Created Equal.

INTRODUCTION: Adjuvant chemotherapy is recommended in patients with stage II colon cancer with high-risk features (HRF). However, there is no quantification of the amount of risk conferred by each HRF or the overall survival (OS) benefit gained by chemotherapy based on the risk factor. OBJECTIVE: To assess survival benefits associated with adjuvant chemotherapy among stage II colon cancer patients having one or more HRF [T4 tumors, less than 12 lymph nodes examined (< 12LN), positive margins, high-grade tumor, perineural invasion (PNI), and lymphovascular invasion (LVI)]. METHODS: Patients diagnosed with stage II colon cancer between 2010 and 2013 were identified from California Cancer Registry. Propensity score weighted all-cause mortality hazard ratios (HR) were calculated for combinations of HRF. RESULTS: A total of 5160 stage II colon cancer patients were identified, of which 2398 had at least one HRF and 510 of 2398 (21%) received adjuvant chemotherapy. Compared with patients with a single HRF, presence of any 2 or ≥ 3 HRF showed increasingly poorer survival [HR 1.42, 95% confidence interval (CI) 1.16-1.73 and HR 2.50, 95% CI 1.96-3.20, respectively]. Chemotherapy was associated with improved overall survival only among patients with T4 as the single HRF (HR 0.51, 95% CI 0.34-0.78) or combinations involving T4 as T4/< 12 LN (HR 0.31, 95% CI 0.11-0.90), T4/high grade (HR 0.26, 95% CI 0.11-0.61), and T4/LVI (HR 0.16, 95% CI 0.04-0.61). CONCLUSIONS: Not all high-risk features have similar adverse effects on OS. T4 tumors and their combination with other HRF achieve the most survival benefit with adjuvant therapy. Type and number of high-risk features should be taken into consideration when recommending adjuvant chemotherapy in stage II colon cancer.