Undergoing Transformation to the Patient Centered Medical Home in Safety Net Health Centers: Perspectives from the Front Lines

Objectives—Safety Net Health Centers (SNHCs), which include Federally Qualified Health Centers (FQHCs) provide primary care for underserved, minority and low income patients. SNHCs across the country are in the process of adopting the Patient Centered Medical Home (PCMH) model, based on promising early implementation data from demonstration projects. However, previous demonstration projects have not focused on the safety net and we know little about PCMH transformation in SNHCs. Design—This qualitative study characterizes early PCMH adoption experiences at SNHCs. Setting and Participants—We interviewed 98 staff,(administrators, providers, and clinical staff) at 20 of 65 SNHCs, from five states, who were participating in the first of a five-year PCMH collaborative, the Safety Net Medical Home Initiative. Main Measures—We conducted 30-45 minute, semi-structured telephone interviews. Interview questions addressed benefits anticipated, obstacles encountered, and lessons learned in transition to PCMH. Results—Anticipated benefits for participating in the PCMH included improved staff satisfaction and patient care and outcomes. Obstacles included staff resistance and lack of financial support for PCMH functions. Lessons learned included involving a range of staff, anticipating resistance, and using data as frequent feedback. Conclusions—SNHCs encounter unique challenges to PCMH implementation, including staff turnover and providing care for patients with complex needs. Staff resistance and turnover may be ameliorated through improved healthcare delivery strategies associated with the PCMH. Creating predictable and continuous funding streams may be more fundamental challenges to PCMH transformation

Broad Resistance to ACCase Inhibiting Herbicides in a Ryegrass Population Is Due Only to a Cysteine to Arginine Mutation in the Target Enzyme

BACKGROUND: The design of sustainable weed management strategies requires a good understanding of the mechanisms by which weeds evolve resistance to herbicides. Here we have conducted a study on the mechanism of resistance to ACCase inhibiting herbicides in a Lolium multiflorum population (RG3) from the UK. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of plant phenotypes and genotypes showed that all the RG3 plants (72%) that contained the cysteine to arginine mutation at ACCase codon position 2088 were resistant to ACCase inhibiting herbicides. Whole plant dose response tests on predetermined wild and mutant 2088 genotypes from RG3 and a standard sensitive population indicated that the C2088R mutation is the only factor conferring resistance to all ten ACCase herbicides tested. The associated resistance indices ranged from 13 for clethodim to over 358 for diclofop-methyl. Clethodim, the most potent herbicide was significantly affected even when applied on small mutant plants at the peri-emergence and one leaf stages. CONCLUSION/SIGNIFICANCE: This study establishes the clear and unambiguous importance of the C2088R target site mutation in conferring broad resistance to ten commonly used ACCase inhibiting herbicides. It also demonstrates that low levels "creeping", multigenic, non target site resistance, is not always selected before single gene target site resistance appears in grass weed populations subjected to herbicide selection pressure

Blood Transfusion Requirements for Patients With Sarcomas Undergoing Combined Radio- and Chemotherapy

Patients with bony and soft tissue sarcomas may require intensive treatment with chemotherapy and radiotherapy, which often leads to a fall in haemoglobin levels, requiring blood transfusion. There may be advantages in predicting which patients will require transfusion, partly because anaemia and hypoxia may worsen the response of tumours to chemotherapy and radiotherapy. Between 1997 and 2003, a total of 26 patients who received intensive treatment with curative intent were identified. Transfusions were given to maintain the haemoglobin at 10g/dl or above during chemotherapy, and at 12 g/dl or above during radiotherapy. Eighteen (69%) required a transfusion, the majority as a result of both the chemotherapy and RT criteria. There were 78 transfusion episodes, and 181 units of blood given. In the 18 patients who required transfusion, the average number of units was 10.1, but seven patients required more blood than this. The most significant factor influencing blood transfusion was choice of intensive chemotherapy. Intensive chemotherapy and presenting Hb less than 11.6 g/dl identified 13 out of 18 patients who needed transfusion. Adding a drop in haemoglobin of greater than 1.7 g/dl after one cycle of chemotherapy identified 16 out of 18 patients who required transfusion. The seven patients who had heavy transfusion requirements were identified by age 32 or less, intensive chemotherapy and a presenting Hb of 12 g/dl or less. Erythropoietin might be a useful alternative to transfusion in selected patient groups, especially those with heavy transfusion requirements

Using near-term forecasts and uncertainty partitioning to improve predictions of low-frequency cyanobacterial events

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water and air quality. Importantly, ecological forecasts can identify where uncertainty enters the forecasting system, which is necessary to refine and improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance (uncertainty) introduced by different sources, including specification of the model structure, errors in driver data, and estimation of initial state conditions. Uncertainty partitioning could be particularly useful in improving forecasts of high-density cyanobacterial events, which are difficult to predict and present a persistent challenge for lake managers. Cyanobacteria can produce toxic or unsightly surface scums and advance warning of these events could help managers mitigate water quality issues. Here, we calibrate fourteen Bayesian state-space models to evaluate different hypotheses about cyanobacterial growth using data from eight summers of weekly cyanobacteria density samples in an oligotrophic (low nutrient) lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We identify dominant sources of uncertainty for near-term (one-week to four-week) forecasts of G. echinulata densities over two years. Water temperature was an important predictor in calibration and at the four-week forecast horizon. However, no environmental covariates improved over a simple autoregressive (AR) model at the one-week horizon. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and often did not capture rare peak density occurrences, indicating that significant explanatory variables in calibration are not always effective for near-term forecasting of low-frequency events. Uncertainty partitioning revealed that model process specification and initial conditions uncertainty dominated forecasts at both time horizons. These findings suggest that observed densities result from both growth and movement of G. echinulata, and that imperfect observations as well as spatial misalignment of environmental data and cyanobacteria observations affect forecast skill. Future research efforts should prioritize long-term studies to refine process understanding and increased sampling frequency and replication to better define initial conditions. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.Accepted manuscrip

Anoxia begets anoxia: a positive feedback to the deoxygenation of temperate lakes

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world

What makes a cyanobacterial bloom disappear? A review of the abiotic and biotic cyanobacterial bloom loss factors

Cyanobacterial blooms present substantial challenges to managers and threaten ecological and public health. Although the majority of cyanobacterial bloom research and management focuses on factors that control bloom initiation, duration, toxicity, and geographical extent, relatively little research focuses on the role of loss processes in blooms and how these processes are regulated. Here, we define a loss process in terms of population dynamics as any process that removes cells from a population, thereby decelerating or reducing the development and extent of blooms. We review abiotic (e.g., hydraulic flushing and oxidative stress/UV light) and biotic factors (e.g., allelopathic compounds, infections, grazing, and resting cells/programmed cell death) known to govern bloom loss. We found that the dominant loss processes depend on several system specific factors including cyanobacterial genera-specific traits, in situ physicochemical conditions, and the microbial, phytoplankton, and consumer community composition. We also address loss processes in the context of bloom management and discuss perspectives and challenges in predicting how a changing climate may directly and indirectly affect loss processes on blooms. A deeper understanding of bloom loss processes and their underlying mechanisms may help to mitigate the negative consequences of cyanobacterial blooms and improve current management strategies

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

5-HT modulation of pain perception in humans

© 2017, The Author(s). Introduction: Although there is clear evidence for the serotonergic regulation of descending control of pain in animals, little direct evidence exists in humans. The majority of our knowledge comes from the use of serotonin (5-HT)-modulating antidepressants as analgesics in the clinical management of chronic pain. Objectives: Here, we have used an acute tryptophan depletion (ATD) to manipulate 5-HT function and examine its effects of ATD on heat pain threshold and tolerance, attentional manipulation of nociceptive processing and mood in human volunteers. Methods: Fifteen healthy participants received both ATD and balanced amino acid (BAL) drinks on two separate sessions in a double-blind cross-over design. Pain threshold and tolerance were determined 4 h post-drink via a heat thermode. Additional attention, distraction and temperature discrimination paradigms were completed using a laser-induced heat pain stimulus. Mood was assessed prior and throughout each session. Results: Our investigation reported that the ATD lowered plasma TRP levels by 65.05 ± 7.29% and significantly reduced pain threshold and tolerance in response to the heat thermode. There was a direct correlation between the reduction in total plasma TRP levels and reduction in thermode temperature. In contrast, ATD showed no effect on laser-induced pain nor significant impact of the distraction-induced analgesia on pain perception but did reduce performance of the painful temperature discrimination task. Importantly, all findings were independent of any effects of ATD on mood. Conclusion: As far as we are aware, it is the first demonstration of 5-HT effects on pain perception which are not confounded by mood changes