A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster.

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. To address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). Our study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

BACKGROUND: Published studies have reported conflicting and heterogeneous results regarding the association between human leukocyte antigen (HLA)-DRB1 polymorphisms and alopecia areata (AA). This study aimed to review and quantitatively analyze the association between HLA-DRB1 polymorphisms and AA. METHODS: In this study, all relevant publications were searched through December 2016. Odds ratios (ORs) and confidence intervals (CIs) for comparisons between case and control groups were calculated. Stata 14.0 software was used to perform statistical analysis. This research does not require formal ethical approval because the data used in this analysis do not involve personal information and thus do not affect privacy. RESULTS: Twelve articles were identified. For HLA-DRB1*04 and HLA-DRB1*16 polymorphisms, the OR (95% CIs) was 1.49 (1.24-1.78) and 1.61 (1.08-2.41), and P was <.01 and <.01, respectively. For HLA-DRB1*0301, HLA-DRB1*09, and HLA-DRB1*13 polymorphisms, the OR (95% CIs) was 0.42 (0.28-0.63), 0.74 (0.55-0.99), and 0.62 (0.40-0.98), and P was <.01, <.01, and <.01, respectively. Statistical evidence revealed no publication bias (P > .05). CONCLUSION: The present meta-analysis suggested that HLA-DRB1*04 and HLA-DRB1*16 polymorphisms might be associated with increased AA risk, while HLA-DRB1*0301, HLA-DRB1*09, and HLA-DRB1*13 polymorphisms might decrease the AA risk. Studies with adequate methodological quality on gene-gene and gene-environment interactions are needed to validate the results in the future.

The mussel byssus has long been a source of inspiration for the adhesion community. Recently, adhesive synergy between flanking lysine (Lys, K) and 3,4-Dihydroxyphenylalanine (DOPA, Y) residues in the mussel foot proteins (Mfps) has been highlighted. However, the complex topological relationship of DOPA and Lys as well as the interfacial adhesive roles of other amino acids have been understudied. Herein, we study adhesion of Lys and DOPA-containing peptides to organic and inorganic substrates using single-molecule force spectroscopy (SMFS). We show that a modest increase in peptide length, from KY to (KY)₃, increases adhesion strength to TiO_2. Surprisingly, further increase in peptide length offers no additional benefit. Additionally, comparison of adhesion of dipeptides containing Lys and either DOPA (KY) or phenylalanine (KF) shows that DOPA is stronger and more versatile. We furthermore demonstrate that incorporating a nonadhesive spacer between (KY) repeats can mimic the hidden length in the Mfp and act as an effective strategy to dissipate energy.

In this article, we compare optical light curves of two SN2002es-like Type Ia supernovae (SNe), iPTF14atg and iPTF14dpk, from the intermediate Palomar Transient Factory. Although the two light curves resemble each other around and after maximum, they show distinct early-phase rise behavior in the r-band. On the one hand, iPTF14atg revealed a slow and steady rise that lasted for 22 days with a mean rise rate of 0.2-0.3 mag day-1, before it reached the R-band peak (-18.05 mag). On the other hand, iPTF14dpk rose rapidly to -17 mag within a day of discovery with a rise rate , and then rose slowly to its peak (-18.19 mag) with a rise rate similar to iPTF14atg. The apparent total rise time of iPTF14dpk is therefore only 16 days. We show that emission from iPTF14atg before -17 days with respect to its maximum can be entirely attributed to radiation produced by collision between the SN and its companion star. Such emission is absent from iPTF14dpk probably because of an unfavored viewing angle, provided that SN2002es-like events arise from the same progenitor channel. We further show that an SN2002es-like SN may experience a dark phase after the explosion but before its radioactively powered light curve becomes visible. This dark phase may be lit by radiation from supernova-companion interaction.

Background

Staphylococcus aureus is a leading cause of bacteremia, yet there remains a significant knowledge gap in the identification of relevant biomarkers that predict clinical outcomes. Heterogeneity in the host response to invasive S. aureus infection suggests that specific biomarker signatures could be utilized to differentiate patients prone to severe disease, thereby facilitating earlier implementation of more aggressive therapies.

Methods

To further elucidate the inflammatory correlates of poor clinical outcomes in patients with S. aureus bacteremia, we evaluated the association between a panel of blood proteins at initial presentation of bacteremia and disease severity outcomes using 2 cohorts of patients with S. aureus bacteremia (n = 32 and n = 124).

Results

We identified 13 candidate proteins that were correlated with mortality and persistent bacteremia. Prognostic modeling identified interleukin (IL)-8 and CCL2 as the strongest individual predictors of mortality, with the combination of these biomarkers classifying fatal outcome with 89% sensitivity and 77% specificity (P < .0001). Baseline IL-17A levels were elevated in patients with persistent bacteremia (P < .0001), endovascular (P = .026) and metastatic tissue infections (P = .012).

Conclusions

These results demonstrate the potential utility of selected biomarkers to distinguish patients with the highest risk for treatment failure and bacteremia-related complications, providing a valuable tool for clinicians in the management of S. aureus bacteremia. Additionally, these biomarkers could identify patients with the greatest potential to benefit from novel therapies in clinical trials.

The intermediate Palomar Transient Factory (iPTF) detection of the most recent outburst of the recurrent nova (RN) system RX J0045.4+4154 in the Andromeda galaxy has enabled the unprecedented study of a massive (M > 1.3 M) accreting white dwarf (WD). We detected this nova as part of the near-daily iPTF monitoring of M31 to a depth of R 21 mag and triggered optical photometry, spectroscopy and soft X-ray monitoring of the outburst. Peaking at an absolute magnitude of MR= -6.6 mag, and with a decay time of 1 mag per day, it is a faint and very fast nova. It shows optical emission lines of He/N and expansion velocities of 1900-2600 km s-1 1-4 days after the optical peak. The Swift monitoring of the X-ray evolution revealed a supersoft source (SSS) with kT eff 90-110 eV that appeared within 5 days after the optical peak, and lasted only 12 days. Most remarkably, this is not the first event from this system, rather it is an RN with a time between outbursts of approximately 1 yr, the shortest known. Recurrent X-ray emission from this binary was detected by ROSAT in 1992 and 1993, and the source was well characterized as a M > 1.3 M WD SSS. Based on the observed recurrence time between different outbursts, the duration and effective temperature of the SS phase, MESA models of accreting WDs allow us to constrain the accretion rate to and WD mass >1.30 M. If the WD keeps 30% of the accreted material, it will take less than a Myr to reach core densities high enough for carbon ignition (if made of C/O) or electron capture (if made of O/Ne) to end the binary evolution. © 2014. The American Astronomical Society. All rights reserved..

Purpose

Combined MAPK pathway inhibition using dual BRAF and MEK inhibitors has prolonged the duration of clinical response in patients with BRAF^V600E-driven tumors compared with either agent alone. However, resistance frequently arises.

Experimental design

We generated cell lines resistant to dual BRAF/MEK inhibition and utilized a pharmacologic synthetic lethal approach to identify a novel, adaptive resistance mechanism mediated through the fibroblast growth factor receptor (FGFR) pathway.

Results

In response to drug treatment, transcriptional upregulation of FGF1 results in autocrine activation of FGFR, which potentiates extracellular signal-regulated kinases (ERK) activation. FGFR inhibition overcomes resistance to dual BRAF/MEK inhibitors in both cell lines and patient-derived xenograft (PDX) models. Abrogation of this bypass mechanism in the first-line setting enhances tumor killing and prevents the emergence of drug-resistant cells. Moreover, clinical data implicate serum FGF1 levels in disease prognosis.

Conclusions

Taken together, these results describe a new, adaptive resistance mechanism that is more commonly observed in the context of dual BRAF/MEK blockade as opposed to single-agent treatment and reveal the potential clinical utility of FGFR-targeting agents in combination with BRAF and MEK inhibitors as a promising strategy to forestall resistance in a subset of BRAF-driven cancers.