Short-term Response of Holcus lanatus L. (Common Velvetgrass) to Chemical and Manual Control at Yosemite National Park, USA

One of the highest priority invasive species at both Yosemite and Sequoia and Kings Canyon national parks is Holcus lanatus L. (common velvetgrass), a perennial bunchgrass that invades mid-elevation montane meadows. Despite velvetgrass being a high priority species, there is little information available on control techniques. The goal of this project was to evaluate the short-term response of a single application of common chemical and manual velvetgrass control techniques. The study was conducted at three montane sites in Yosemite National Park. Glyphosate spotspray treatments were applied at 0.5, 1.0, 1.5, and 2.0% concentrations, and compared with hand pulling to evaluate effects on cover of common velvetgrass, cover of other plant species, and community species richness. Posttreatment year 1 cover of common velvetgrass was 12.1% 6 1.6 in control plots, 6.3% 6 1.5 averaged over the four chemical treatments (all chemical treatments performed similarly), and 13.6% 6 1.7 for handpulled plots. This represents an approximately 50% reduction in common velvetgrass cover in chemically- treated plots recoded posttreatment year 1 and no statistically significant reduction in hand pulled plots compared with controls. However, there was no treatment effect in posttreatment year 2, and all herbicide application rates performed similarly. In addition, there were no significant treatment effects on nontarget species or species richness. These results suggest that for this level of infestation and habitat type, (1) one year of hand pulling is not an effective control method and (2) glyphosate provides some level of control in the short-term without impact to nontarget plant species, but the effect is temporary as a single year of glyphosate treatment is ineffective over a twoyear period

Provider-initiated testing and counselling programmes in sub-Saharan Africa: a systematic review of their operational implementation.

OBJECTIVE: The routine offer of an HIV test during patient-provider encounters is gaining momentum within HIV treatment and prevention programmes. This review examined the operational implementation of provider-initiated testing and counselling (PITC) programmes in sub-Saharan Africa. DESIGN AND METHODS: PUBMED, EMBASE, Global Health, COCHRANE Library and JSTOR databases were searched systematically for articles published in English between January 2000 and November 2010. Grey literature was explored through the websites of international and nongovernmental organizations. Eligibility of studies was based on predetermined criteria applied during independent screening by two researchers. RESULTS: We retained 44 studies out of 5088 references screened. PITC polices have been effective at identifying large numbers of previously undiagnosed individuals. However, the translation of policy guidance into practice has had mixed results, and in several studies of routine programmes the proportion of patients offered an HIV test was disappointingly low. There were wide variations in the rates of acceptance of the test and poor linkage of those testing positive to follow-up assessments and antiretroviral treatment. The challenges encountered encompass a range of areas from logistics, to data systems, human resources and management, reflecting some of the weaknesses of health systems in the region. CONCLUSIONS: The widespread adoption of PITC provides an unprecedented opportunity for identifying HIV-positive individuals who are already in contact with health services and should be accompanied by measures aimed at strengthening health systems and fostering the normalization of HIV at community level. The resources and effort needed to do this successfully should not be underestimated

An online experiment to assess bias in professional medical coding.

BackgroundMultiple studies have documented bias in medical decision making, but no studies have examined whether this bias extends to medical coding practices. Medical coding is foundational to the US health care enterprise. We evaluate whether bias based on patient characteristics influences specific coding practices of professional medical coders.MethodsThis is an online experimental study of members of a national professional medical coding organization. Participants were randomly assigned a set of six clinical scenarios reflecting common medical conditions and asked to report encounter level of service codes for these clinical scenarios. Clinical scenarios differed by patient demographics (race, age, gender, ability) or social context (food insecurity, housing security) but were otherwise identical. We estimated Ordinary Least Squares regression models to evaluate differences in outcome average visit level of service by patient demographic characteristics described in the clinical scenarios; we adjusted for coders' age, gender, race, and years of coding experience.ResultsThe final analytic sample included 586 respondents who coded at least one clinical scenario. Higher mean level of service was assigned to clinical scenarios describing seniors compared to middle-aged patients in two otherwise identical scenarios, one a patient with type II diabetes mellitus (Coef: 0.28, SE: 0.15) and the other with rheumatoid arthritis (Coef: 0.30, SE: 0.13). Charts describing women were assigned lower level of service than men in patients with asthma exacerbation (Coef: -0.25, SE: 0.13) and rheumatoid arthritis (Coef: -0.20, SE: 0.12). There were no other significant differences in mean complexity score by patient demographics or social needs.ConclusionWe found limited evidence of bias in professional medical coding practice by patient age and gender, though findings were inconsistent across medical conditions. Low levels of observed bias may reflect medical coding workflow and training practices. Future research is needed to better understand bias in coding and to identify effective and generalizable bias prevention practices

Intra-dance variation among waggle runs and the design of efficient protocols for honey bee dance decoding

Noise is universal in information transfer. In animal communication, this presents a challenge not only for intended signal receivers, but also to biologists studying the system. In honey bees, a forager communicates to nestmates the location of an important resource via the waggle dance. This vibrational signal is composed of repeating units (waggle runs) that are then averaged by nestmates to derive a single vector. Manual dance decoding is a powerful tool for studying bee foraging ecology, although the process is time-consuming: a forager may repeat the waggle run 1- >100 times within a dance. It is impractical to decode all of these to obtain the vector; however, intra-dance waggle runs vary, so it is important to decode enough to obtain a good average. Here we examine the variation among waggle runs made by foraging bees to devise a method of dance decoding. The first and last waggle runs within a dance are significantly more variable than the middle run. There was no trend in variation for the middle waggle runs. We recommend that any four consecutive waggle runs, not including the first and last runs, may be decoded, and we show that this methodology is suitable by demonstrating the goodness-of-fit between the decoded vectors from our subsamples with the vectors from the entire dances

Adaptive genomic structural variation in the grape powdery mildew pathogen, Erysiphe necator.

BackgroundPowdery mildew, caused by the obligate biotrophic fungus Erysiphe necator, is an economically important disease of grapevines worldwide. Large quantities of fungicides are used for its control, accelerating the incidence of fungicide-resistance. Copy number variations (CNVs) are unbalanced changes in the structure of the genome that have been associated with complex traits. In addition to providing the first description of the large and highly repetitive genome of E. necator, this study describes the impact of genomic structural variation on fungicide resistance in Erysiphe necator.ResultsA shotgun approach was applied to sequence and assemble the genome of five E. necator isolates, and RNA-seq and comparative genomics were used to predict and annotate protein-coding genes. Our results show that the E. necator genome is exceptionally large and repetitive and suggest that transposable elements are responsible for genome expansion. Frequent structural variations were found between isolates and included copy number variation in EnCYP51, the target of the commonly used sterol demethylase inhibitor (DMI) fungicides. A panel of 89 additional E. necator isolates collected from diverse vineyard sites was screened for copy number variation in the EnCYP51 gene and for presence/absence of a point mutation (Y136F) known to result in higher fungicide tolerance. We show that an increase in EnCYP51 copy number is significantly more likely to be detected in isolates collected from fungicide-treated vineyards. Increased EnCYP51 copy numbers were detected with the Y136F allele, suggesting that an increase in copy number becomes advantageous only after the fungicide-tolerant allele is acquired. We also show that EnCYP51 copy number influences expression in a gene-dose dependent manner and correlates with fungal growth in the presence of a DMI fungicide.ConclusionsTaken together our results show that CNV can be adaptive in the development of resistance to fungicides by providing increasing quantitative protection in a gene-dosage dependent manner. The results of this work not only demonstrate the effectiveness of using genomics to dissect complex traits in organisms with very limited molecular information, but also may have broader implications for understanding genomic dynamics in response to strong selective pressure in other pathogens with similar genome architectures

Initial experience of dedicated breast PET imaging of ER+ breast cancers using [F-18]fluoroestradiol.

Dedicated breast positron emission tomography (dbPET) is an emerging technology with high sensitivity and spatial resolution that enables detection of sub-centimeter lesions and depiction of intratumoral heterogeneity. In this study, we report our initial experience with dbPET using [F-18]fluoroestradiol (FES) in assessing ER+ primary breast cancers. Six patients with >90% ER+ and HER2- breast cancers were imaged with dbPET and breast MRI. Two patients had ILC, three had IDC, and one had an unknown primary tumor. One ILC patient was treated with letrozole, and another patient with IDC was treated with neoadjuvant chemotherapy without endocrine treatment. In this small cohort, we observed FES uptake in ER+ primary breast tumors with specificity to ER demonstrated in a case with tamoxifen blockade. FES uptake in ILC had a diffused pattern compared to the distinct circumscribed pattern in IDC. In evaluating treatment response, the reduction of SUVmax was observed with residual disease in an ILC patient treated with letrozole, and an IDC patient treated with chemotherapy. Future study is critical to understand the change in FES SUVmax after endocrine therapy and to consider other tracer uptake metrics with SUVmax to describe ER-rich breast cancer. Limitations include variations of FES uptake in different ER+ breast cancer diseases and exclusion of posterior tissues and axillary regions. However, FES-dbPET has a high potential for clinical utility, especially in measuring response to neoadjuvant endocrine treatment. Further development to improve the field of view and studies with a larger cohort of ER+ breast cancer patients are warranted

Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis.

Radiomics is an emerging technology for imaging biomarker discovery and disease-specific personalized treatment management. This paper aims to determine the benefit of using multi-modality radiomics data from PET and MR images in the characterization breast cancer phenotype and prognosis. Eighty-four features were extracted from PET and MR images of 113 breast cancer patients. Unsupervised clustering based on PET and MRI radiomic features created three subgroups. These derived subgroups were statistically significantly associated with tumor grade (p = 2.0 × 10-6), tumor overall stage (p = 0.037), breast cancer subtypes (p = 0.0085), and disease recurrence status (p = 0.0053). The PET-derived first-order statistics and gray level co-occurrence matrix (GLCM) textural features were discriminative of breast cancer tumor grade, which was confirmed by the results of L2-regularization logistic regression (with repeated nested cross-validation) with an estimated area under the receiver operating characteristic curve (AUC) of 0.76 (95% confidence interval (CI) = [0.62, 0.83]). The results of ElasticNet logistic regression indicated that PET and MR radiomics distinguished recurrence-free survival, with a mean AUC of 0.75 (95% CI = [0.62, 0.88]) and 0.68 (95% CI = [0.58, 0.81]) for 1 and 2 years, respectively. The MRI-derived GLCM inverse difference moment normalized (IDMN) and the PET-derived GLCM cluster prominence were among the key features in the predictive models for recurrence-free survival. In conclusion, radiomic features from PET and MR images could be helpful in deciphering breast cancer phenotypes and may have potential as imaging biomarkers for prediction of breast cancer recurrence-free survival