Using Similarity Metrics on Real World Data and Patient Treatment Pathways to Recommend the Next Treatment

Non-small-cell lung cancer (NSCLC) is one of the most prevalent types of lung cancer and continues to have an ominous five year survival rate. Considerable work has been accomplished in analyzing the viability of the treatments offered to NSCLC patients; however, while many of these treatments have performed better over populations of diagnosed NSCLC patients, a specific treatment may not be the most effective therapy for a given patient. Coupling both patient similarity metrics using the Gower similarity metric and prior treatment knowledge, we were able to demonstrate how patient analytics can complement clinical efforts in recommending the next best treatment. Our retrospective and exploratory results indicate that a majority of patients are not recommended the best surviving therapy once they require a new therapy. This investigation lays the groundwork for treatment recommendation using analytics, but more investigation is required to analyze patient outcomes beyond survival

Exaggerated CpH methylation in the autism-affected brain.

BackgroundThe etiology of autism, a complex, heritable, neurodevelopmental disorder, remains largely unexplained. Given the unexplained risk and recent evidence supporting a role for epigenetic mechanisms in the development of autism, we explored the role of CpG and CpH (H = A, C, or T) methylation within the autism-affected cortical brain tissue.MethodsReduced representation bisulfite sequencing (RRBS) was completed, and analysis was carried out in 63 post-mortem cortical brain samples (Brodmann area 19) from 29 autism-affected and 34 control individuals. Analyses to identify single sites that were differentially methylated and to identify any global methylation alterations at either CpG or CpH sites throughout the genome were carried out.ResultsWe report that while no individual site or region of methylation was significantly associated with autism after multi-test correction, methylated CpH dinucleotides were markedly enriched in autism-affected brains (~2-fold enrichment at p < 0.05 cutoff, p = 0.002).ConclusionsThese results further implicate epigenetic alterations in pathobiological mechanisms that underlie autism

Light Quark Masses with an O(a)-Improved Action

We present the recent Fermilab calculations of the masses of the light quarks, using tadpole-improved Sheikholeslami-Wohlert (SW) quarks. Various sources of systematic errors are studied. Our final result for the average light quark mass in the quenched approximation evaluated in the $\bar{MS}$ scheme is $\bar{m}_q(\mu=2 GeV;n_f=0)= (m_u+m_d)/2=3.6 \pm 0.6 MeV$.Comment: 3 pgs. 3 figures. espcrc2.sty included. Talk presented at LATTICE96(phenomenology

RNA-Seq optimization with eQTL gold standards.

BackgroundRNA-Sequencing (RNA-Seq) experiments have been optimized for library preparation, mapping, and gene expression estimation. These methods, however, have revealed weaknesses in the next stages of analysis of differential expression, with results sensitive to systematic sample stratification or, in more extreme cases, to outliers. Further, a method to assess normalization and adjustment measures imposed on the data is lacking.ResultsTo address these issues, we utilize previously published eQTLs as a novel gold standard at the center of a framework that integrates DNA genotypes and RNA-Seq data to optimize analysis and aid in the understanding of genetic variation and gene expression. After detecting sample contamination and sequencing outliers in RNA-Seq data, a set of previously published brain eQTLs was used to determine if sample outlier removal was appropriate. Improved replication of known eQTLs supported removal of these samples in downstream analyses. eQTL replication was further employed to assess normalization methods, covariate inclusion, and gene annotation. This method was validated in an independent RNA-Seq blood data set from the GTEx project and a tissue-appropriate set of eQTLs. eQTL replication in both data sets highlights the necessity of accounting for unknown covariates in RNA-Seq data analysis.ConclusionAs each RNA-Seq experiment is unique with its own experiment-specific limitations, we offer an easily-implementable method that uses the replication of known eQTLs to guide each step in one's data analysis pipeline. In the two data sets presented herein, we highlight not only the necessity of careful outlier detection but also the need to account for unknown covariates in RNA-Seq experiments

Taxonomy Induction using Hypernym Subsequences

We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms. Unlike all previous approaches, which typically extract direct hypernym edges for terms, our approach utilizes a novel probabilistic framework to extract hypernym subsequences. Taxonomy induction from extracted subsequences is cast as an instance of the minimumcost flow problem on a carefully designed directed graph. Through experiments, we demonstrate that our approach outperforms stateof- the-art taxonomy induction approaches across four languages. Importantly, we also show that our approach is robust to the presence of noise in the input vocabulary. To the best of our knowledge, no previous approaches have been empirically proven to manifest noise-robustness in the input vocabulary

Psoriasis Area and Severity Index response in moderate-severe psoriatic patients switched to adalimumab: results from the OPPSA study

Background: Few studies have compared the efficacy of switching to adalimumab in the real-life setting in plaque psoriasis patients. Objective: To evaluate the effect of adalimumab in psoriasis patients previously treated with other biologics. Methods: In this multicentre study, psoriasis patients (N = 262) treated with an anti-TNF-alpha agent, ustekinumab or naïve to biologics then switched to adalimumab were included. Disease severity was assessed by the Psoriasis Area and Severity Index (PASI) at baseline and after 3, 6, 12, 24 and 36 months. The association between clinical risk factors and achievement of PASI response was evaluated by logistic regression. Results: Adalimumab treatment resulted in a decrease in PASI (15.1 ± 6.2 at baseline vs. 2.7 ± 4.8 at 6 months, P < 0.0001), regardless of previous biologic treatment. Furthermore, adalimumab allowed 92.5%, 79% and 56% of patients to achieve PASI response (PASI 50, 75 and 90, respectively) and complete remission (PASI 100 response) in 48.4% of patients, by 6 months and maintained over 3 years, independent of prior biologic treatment. The absence of metabolic syndrome, dyslipidemia, hypertension and lower PASI and lower age at baseline was associated with achievement of PASI response at 3, 6 and 12 months, whereas at later time points (24 and 36 months), PASI 90 and PASI 100 response was associated with diagnosis of psoriasis/psoriatic arthritis. Conclusion: Adalimumab was effective at reducing PASI score over 3 years, irrespective of whether patients were biologic naïve or previously treated with a TNF-alpha or IL-12/23 inhibitor

Heavy Light Weak Matrix Elements

I review the status of lattice calculations of heavy-light weak matrix elements, concentrating on semileptonic B decays to light mesons, B -> K* gamma, the B meson decay constant, f_B, and the mixing parameter B_B.Comment: 12 pages, LaTeX2e with 6 postscript figures. Uses espcrc2.sty and epsf.sty (included). Talk presented at LATTICE96(heavy quarks

Chiral Perturbation Theory and Weak Matrix Elements

I describe recent developments in quenched chiral perturbation theory (QChPT) and the status of weak matrix elements involving light quarks. I illustrate how, with improved statistical errors, and with calculations of the masses of baryons containing non-degenerate quarks, there is now a clear need for extrapolations of higher order than linear in the quark mass. I describe how QChPT makes predictions for the functional forms to use in such extrapolations, and emphasize the distinction between contributions coming from chiral loops which are similar to those present in unquenched theories, and those from $\eta'$ loops which are pure quenched artifacts. I describe a fit to the baryon masses using the predictions of QChPT. I give a status report on the numerical evidence for $\eta'$ loops, concluding that they are likely present, and are characterized by a coupling $\delta=0.1-0.2$. I use the difference between chiral loops in QCD and quenched QCD to estimate the quenching errors in a variety of quantities. I then turn to results for matrix elements, largely from quenched simulations. Results for quenched decay constants cannot yet be reliably extrapolated to the continuum limit. By contrast, new results for $B_K$ suggest a continuum, ``quenched'' value of $B_K(NDR, 2 GeV) = 0.5977 \pm 0.0064 \pm 0.0166$, based on a quadratic extrapolation in $a$. The theoretical basis for using a quadratic extrapolation has been confirmed. For the first time there is significant evidence that unquenching changes $B_K$, and my estimate for the value in QCD is $B_K(NDR, 2 GeV) = 0.66 \pm 0.02 \pm 0.11$. Here the second error is a conservative estimate of the systematic error due to uncertainties in the effect of quenching. A less conservative viewpoint reduces $0.11$ to $0.03$.Comment: 16 pages, 11 figures, Latex using espcrc2.sty and psfig. Talk presented at LATTICE96(phenomenology

High-global warming potential F-gas emissions in California: comparison of ambient-based versus inventory-based emission estimates, and implications of refined estimates.

To provide information for greenhouse gas reduction policies, the California Air Resources Board (CARB) inventories annual emissions of high-global-warming potential (GWP) fluorinated gases, the fastest growing sector of greenhouse gas (GHG) emissions globally. Baseline 2008 F-gas emissions estimates for selected chlorofluorocarbons (CFC-12), hydrochlorofluorocarbons (HCFC-22), and hydrofluorocarbons (HFC-134a) made with an inventory-based methodology were compared to emissions estimates made by ambient-based measurements. Significant discrepancies were found, with the inventory-based emissions methodology resulting in a systematic 42% under-estimation of CFC-12 emissions from older refrigeration equipment and older vehicles, and a systematic 114% overestimation of emissions for HFC-134a, a refrigerant substitute for phased-out CFCs. Initial, inventory-based estimates for all F-gas emissions had assumed that equipment is no longer in service once it reaches its average lifetime of use. Revised emission estimates using improved models for equipment age at end-of-life, inventories, and leak rates specific to California resulted in F-gas emissions estimates in closer agreement to ambient-based measurements. The discrepancies between inventory-based estimates and ambient-based measurements were reduced from -42% to -6% for CFC-12, and from +114% to +9% for HFC-134a