CMS Search Plans and Sensitivity to New Physics using Dijets

CMS will use dijets to search for physics beyond the standard model during early LHC running. The inclusive jet cross section as a function of jet transverse momentum, with 10 pb$^{-1}$ of integrated luminosity, is sensitive to contact interactions beyond the reach of the Tevatron. The dijet mass distribution will be used to search for dijet resonances coming from new particles, for example an excited quark. Additional sensitivity to the existence of contact interactions or dijet resonances can be obtained by comparing dijet rates in two distinct pseudorapidity regions

CMS search plans and sensitivity to new physics with dijets

CMS will use dijets to search for physics beyond the standard model during early LHC running. The inclusive jet cross section as a function of jet transverse momentum, with 10 inverse picobarns of integrated luminosity, is sensitive to contact interactions beyond the reach of the Tevatron. The dijet mass distribution will be used to search for dijet resonances coming from new particles, for example an excited quark. Additional sensitivity to the existence of contact interactions or dijet resonances can be obtained by comparing dijet rates in two distinct pseudorapidity regions.Comment: 10 pages, 4 figures, accepted for publication in J. Phys. G: Nucl. Part. Phy

Sensory profiles of Robusta coffee (Coffea canephora) genetic resources from the Democratic Republic of the Congo

IntroductionThe genetic diversity of Robusta coffee (Coffea canephora), a cornerstone in the global coffee industry, remains not fully explored, leading to a significant gap in our understanding of its sensory intricacies. Our study evaluated the sensory quality potential of the Robusta cultivars from the INERA Coffee Collection in Yangambi (the Democratic Republic of the Congo), the local wild diversity, and their hybrids.MethodsWe evaluated the sensory attributes of 70 genotypes representing the genetic structure of the coffee collection. Of those 70, 22 genotypes were evaluated for two consecutive years to assess the consistency of the sensory quality. Standard coffee cupping with the Fine Robusta Standards and Protocols was enhanced through sensory descriptors from the Coffee Taster’s Flavor Wheel. Each genotype’s sensory profile was constructed based on the Total cupping score and the frequency of reported sensory descriptors. The Total cupping score ranged from 75.75 to 84.75, with a substantial variation in sensory profiles, even within a genetic cluster.Results and discussionNutty/Cocoa was the most frequently reported descriptor class. The sensory profile ideotype exhibits a high frequency of Fruity, Sweet, and Sour/Fermented descriptors and a low frequency of Green/Vegetative, Other, and Roasted descriptors. Evidence suggests that the sensory profile of a genotype is consistent over two harvest years. Genotypes with promising and unique sensory profiles were discovered within the cultivars and the wild – cultivar hybrids. The genetic diversity of wild and cultivated Robusta in the Democratic Republic of the Congo could play an essential role in understanding and improving its sensory quality

Assessing Change in Social Support During Late Life

The purpose of this study is to evaluate change in 14 measures of social support with data provided by a nationwide longitudinal study of older adults. The findings reveal that fairly substantial change took place during the three-year follow-up period. More important, the data indicate that change is not uniform or systematic across the entire study sample. Instead, there appears to be considerable individual-level change taking place. The implications of these findings for the development of conceptual models as well as support-based interventions are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68866/2/10.1177_0164027599214002.pd

Characterization of the genetic composition and establishment of a core collection for the INERA Robusta coffee (Coffea canephora) field genebank from the Democratic Republic of Congo

Cultivation of Robusta coffee is likely to gain importance because of its high disease resistance and climate envelope. Robusta coffee genetic resources conserved in field genebanks can play an important role to further improve its cupping quality and other agronomic traits, but such Coffea canephora collections are limited and still poorly characterized. In this study, we characterized the genetic composition of the historically important but until recently neglected INERA Coffee Collection in Yangambi (the Democratic Republic of Congo). We used GBS to discover genome-wide genetic diversity, created and validated a novel multiplex amplicon sequencing (HiPlex) screening assay to genetically screen 730 coffee shrubs of the Yangambi Coffee Collection, grouped clonal material and delineated 263 accessions with unique genetic fingerprints. Comparison to reference material of three genetic origins revealed that the majority of the Yangambi accessions were assigned a ‘Lula’ cultivar origin, four accessions were assigned to Congolese subgroup A and nine accessions were most closely related to local wild accessions. About one-quarter of the accessions was likely derived from hybridization between these groups, which could result from seed-based propagation of the collection, breeding efforts, or natural cross-pollination. Parental analyses discovered eight preferentially used accessions, which may correspond to historically selected founders, or direct descendants thereof, whose seed material was once widely used to establish coffee plantations. Finally, two core collections were proposed using the maximization strategy (CC-I; 100 accessions) and genetic distance method (CC-X; 10 accessions). Our study demonstrates a method for the genetic characterization of Robusta coffee collections in general and contributes to the re-evaluation and exploration of the Robusta coffee genetic resources in the Democratic Republic of the Congo in particular

Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas

The risk of misclassifying subjects within principal component based asset index

The asset index is often used as a measure of socioeconomic status in empirical research as an explanatory variable or to control confounding. Principal component analysis (PCA) is frequently used to create the asset index. We conducted a simulation study to explore how accurately the principal component based asset index reflects the study subjects’ actual poverty level, when the actual poverty level is generated by a simple factor analytic model. In the simulation study using the PC-based asset index, only 1% to 4% of subjects preserved their real position in a quintile scale of assets; between 44% to 82% of subjects were misclassified into the wrong asset quintile. If the PC-based asset index explained less than 30% of the total variance in the component variables, then we consistently observed more than 50% misclassification across quintiles of the index. The frequency of misclassification suggests that the PC-based asset index may not provide a valid measure of poverty level and should be used cautiously as a measure of socioeconomic status

[Comment] Redefine statistical significance

The lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on “statistically significant” findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (e.g., multiple testing, P-hacking, publication bias, and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: Statistical standards of evidence for claiming discoveries in many fields of science are simply too low. Associating “statistically significant” findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems. For fields where the threshold for defining statistical significance is P<0.05, we propose a change to P<0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called “significant” but do not meet the new threshold should instead be called “suggestive.” While statisticians have known the relative weakness of using P≈0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new (1, 2), a critical mass of researchers now endorse this change. We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (e.g., genomics and high-energy physics research; see Potential Objections below). We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P-values. However, changing the P-value threshold is simple and might quickly achieve broad acceptance

The effect of ω-fatty acids on mrna expression level of PPARγ in patients with gastric adenocarcinoma

Background: The antineoplastic role of peroxisome proliferator-activated receptor gamma (PPARγ) ligandshas previously been demonstrated in several gastric cancer cell lines. Activation of PPARγ by polyunsaturated fatty acids (PUFAs) inhibits growth and proliferationof tumor cells. In this double-blind clinical study, we evaluate the effect of PUFAs on PPARγ mRNA expression in patients with gastric adenocarcinoma. Materials and Methods: A total of 34 chemotherapy-naive patients diagnosed with gastric adenocarcinoma were enrolled in the present study. According to treatment strategies, all subjects were divided into two groups, the first group (17 individuals) received cisplatin without supplements and the second group (17 individuals) received cisplatin plus orally administered PUFAs supplements for 3 weeks. The gastric biopsy samples were obtained from all participants before and after treatment, and PPARγ mRNA expression levels were evaluated by quantitative real-time polymerase chain reaction using validated reference genes. Results: Our findings revealed that PPARγ mRNA expression is significantly upregulated in group II afterreceiving cisplatin plus orally administered PUFAs supplements for three weeks (p < 0.0001), whereas PPARγ mRNA expression did not show significant alteration in group I after receiving cisplatin alone. Conclusion: The results of the study evidence that PPARγ may act as a potential target for the therapy of human gastric adenocarcinoma