The 3D-HST and CANDELS programs have provided WFC3 and ACS spectroscopy and photometry over approximate900 arcmin super(2) in five fields: AEGIS, COSMOS, GOODS-North, GOODS-South, and the UKIDSS UDS ...field. All these fields have a wealth of publicly available imaging data sets in addition to the Hubble Space Telescope (HST) data, which makes it possible to construct the spectral energy distributions (SEDs) of objects over a wide wavelength range. In this paper we describe a photometric analysis of the CANDELS and 3D-HST HST imaging and the ancillary imaging data at wavelengths 0.3-8Mum. Objects were selected in the WFC3 near-IR bands, and their SEDs were determined by carefully taking the effects of the point-spread function in each observation into account. A total of 147 distinct imaging data sets were used in the analysis. The photometry is made available in the form of six catalogs: one for each field, as well as a master catalog containing all objects in the entire survey. We also provide derived data products: photometric redshifts, determined with the EAZY code, and stellar population parameters determined with the FAST code. We make all the imaging data that were used in the analysis available, including our reductions of the WFC3 imaging in all five fields. 3D-HST is a spectroscopic survey with the WFC3 and ACS grisms, and the photometric catalogs presented here constitute a necessary first step in the analysis of these grism data. All the data presented in this paper are available through the 3D-HST Web site (http://3dhst.research.yale.edu).
•A GPU implementation of the swept time–space decomposition rule is presented.•Three versions of the scheme are considered.•The shared-memory implementation outperforms the other versions.•The best ...swept scheme outperforms the classic method by 2–9 times.
The expedient design of precision components in aerospace and other high-tech industries requires simulations of physical phenomena often described by partial differential equations (PDEs) without exact solutions. Modern design problems require simulations with a level of resolution difficult to achieve in reasonable amounts of time—even in effectively parallelized solvers. Though the scale of the problem relative to available computing power is the greatest impediment to accelerating these applications, significant performance gains can be achieved through careful attention to the details of memory communication and access. The swept time–space decomposition rule reduces communication between sub-domains by exhausting the domain of influence before communicating boundary values. Here we present a GPU implementation of the swept rule, which modifies the algorithm for improved performance on this processing architecture by prioritizing use of private (shared) memory, avoiding interblock communication, and overwriting unnecessary values. It shows significant improvement in the execution time of finite-difference solvers for one-dimensional unsteady PDEs, producing speedups of 2–9× for a range of problem sizes, respectively, compared with simple GPU versions and 7–300× compared with parallel CPU versions. However, for a more sophisticated one-dimensional system of equations discretized with a second-order finite-volume scheme, the swept rule performs 1.2–1.9× worse than a standard implementation for all problem sizes.
We present Hubble Space Telescope NIC2 morphologies of a spectroscopic sample of massive galaxies at z approx 2.3 by extending our sample of 9 compact quiescent galaxies (r{sub e} approx 0.9 kpc) ...with 10 massive emission-line galaxies. The emission-line galaxies are classified by the nature of their ionized emission; there are six star-forming galaxies and four galaxies hosting an active galactic nucleus (AGN). The star-forming galaxies are the largest among the emission-line galaxies, with a median size of r{sub e} = 2.8 kpc. The three galaxies with the highest star formation rates (approx>100 M {sub sun} yr{sup -1}) have irregular and clumpy morphologies. The AGN host galaxies are more similar to the compact quiescent galaxies in terms of their structures (r{sub e} approx 1.1 kpc) and spectral energy distributions. The total sample clearly separates into two classes in a color-mass diagram: the large star-forming galaxies that form the blue cloud, and the compact quiescent galaxies on the red sequence. However, it is unclear how or even if the two classes are evolutionary related. Three out of six massive star-forming galaxies have dense cores and thus may passively evolve into compact galaxies due to fading of outer star-forming regions. For these galaxies, a reverse scenario in which compact galaxies grow inside-out by star formation is also plausible. We do caution though that the sample is small. Nonetheless, it is evident that a Hubble sequence of massive galaxies with strongly correlated galaxy properties is already in place at z > 2.
There is a need to develop and validate biomarkers for treatment response and survival in tubo-ovarian high-grade serous carcinoma (HGSC). The chemotherapy response score (CRS) stratifies patients ...into complete/near-complete (CRS3), partial (CRS2), and no/minimal (CRS1) response after neoadjuvant chemotherapy (NACT). Our aim was to review current evidence to determine whether the CRS is prognostic in women with tubo-ovarian HGSC treated with NACT.
We established an international collaboration to conduct a systematic review and meta-analysis, pooling individual patient data from 16 sites in 11 countries. Patients had stage IIIC/IV HGSC, 3–4 NACT cycles and >6-months follow-up. Random effects models were used to derive combined odds ratios in the pooled population to investigate associations between CRS and progression free and overall survival (PFS and OS).
877 patients were included from published and unpublished studies. Median PFS and OS were 15 months (IQR 5–65) and 28 months (IQR 7–92) respectively. CRS3 was seen in 249 patients (28%). The pooled hazard ratios (HR) for PFS and OS for CRS3 versus CRS1/CRS2 were 0·55 (95% CI, 0·45–0·66; P < 0·001) and 0·65 (95% CI 0·50–0·85, P = 0·002) respectively; no heterogeneity was identified (PFS: Q = 6·42, P = 0·698, I2 = 0·0%; OS: Q = 6·89, P = 0·648, I2 = 0·0%). CRS was significantly associated with PFS and OS in multivariate models adjusting for age and stage. Of 306 patients with known germline BRCA1/2 status, those with BRCA1/2 mutations (n = 80) were more likely to achieve CRS3 (P = 0·027).
CRS3 was significantly associated with improved PFS and OS compared to CRS1/2. This validation of CRS in a real-world setting demonstrates it to be a robust and reproducible biomarker with potential to be incorporated into therapeutic decision-making and clinical trial design.
•The Chemotherapy response score (CRS) assesses histological effect in ovarian cancer after neoadjuvant chemotherapy (NACT).•The CRS is associated with progression-free and overall survival.•CRS could provide useful information to estimate a patient's probability of early vs. late relapse.•The CRS is an appealing primary endpoint in clinical trials as a surrogate for survival as it can be measured earlier.•We recommend the CRS be incorporated as an endpoint in clinical trials of novel therapeutic agents that have a NACT arm.
FOLFOX, FOLFIRI, or FOLFOXIRI chemotherapy with bevacizumab is considered standard first-line treatment option for patients with metastatic colorectal cancer (mCRC). We developed and validated a ...molecular signature predictive of efficacy of oxaliplatin-based chemotherapy combined with bevacizumab in patients with mCRC.
A machine-learning approach was applied and tested on clinical and next-generation sequencing data from a real-world evidence (RWE) dataset and samples from the prospective TRIBE2 study resulting in identification of a molecular signature, FOLFOX
. Algorithm training considered time-to-next treatment (TTNT). Validation studies used TTNT, progression-free survival, and overall survival (OS) as the primary endpoints.
A 67-gene signature was cross-validated in a training cohort (
= 105) which demonstrated the ability of FOLFOX
to distinguish FOLFOX-treated patients with mCRC with increased benefit from those with decreased benefit. The signature was predictive of TTNT and OS in an independent RWE dataset of 412 patients who had received FOLFOX/bevacizumab in first line and inversely predictive of survival in RWE data from 55 patients who had received first-line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOX
was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR, 0.629;
= 0.04 and FOLFOXIRI HR, 0.483;
= 0.02). FOLFOX
was also predictive of treatment benefit from oxaliplatin-containing regimens in advanced esophageal/gastro-esophageal junction cancers, as well as pancreatic ductal adenocarcinoma.
Application of FOLFOX
could lead to improvements of treatment outcomes for patients with mCRC and other cancers because patients predicted to have less benefit from oxaliplatin-containing regimens might benefit from alternative regimens.
Ancestral state reconstructions in Bayesian phylogeography of virus pandemics have been improved by utilizing a Bayesian stochastic search variable selection (BSSVS) framework. Recently, this ...framework has been extended to model the transition rate matrix between discrete states as a generalized linear model (GLM) of genetic, geographic, demographic, and environmental predictors of interest to the virus and incorporating BSSVS to estimate the posterior inclusion probabilities of each predictor. Although the latter appears to enhance the biological validity of ancestral state reconstruction, there has yet to be a comparison of phylogenies created by the two methods. In this paper, we compare these two methods, while also using a primitive method without BSSVS, and highlight the differences in phylogenies created by each. We test six coalescent priors and six random sequence samples of H3N2 influenza during the 2014-15 flu season in the U.S. We show that the GLMs yield significantly greater root state posterior probabilities than the two alternative methods under five of the six priors, and significantly greater Kullback-Leibler divergence values than the two alternative methods under all priors. Furthermore, the GLMs strongly implicate temperature and precipitation as driving forces of this flu season and nearly unanimously identified a single root state, which exhibits the most tropical climate during a typical flu season in the U.S. The GLM, however, appears to be highly susceptible to sampling bias compared with the other methods, which casts doubt on whether its reconstructions should be favored over those created by alternate methods. We report that a BSSVS approach with a Poisson prior demonstrates less bias toward sample size under certain conditions than the GLMs or primitive models, and believe that the connection between reconstruction method and sampling bias warrants further investigation.
Applications that exploit the architectural details of high-performance computing (HPC) systems have become increasingly invaluable in academia and industry over the past two decades. The most ...important hardware development of the last decade in HPC has been the general purpose graphics processing unit (GPGPU), a class of massively parallel devices that now contributes the majority of computational power in the top 500 supercomputers. As these systems grow, small costs such as latency—due to the fixed cost of memory accesses and communication—accumulate in a large simulation and become a significant barrier to performance. The swept time-space decomposition rule is a communication-avoiding technique for time-stepping stencil update formulas that attempts to reduce latency costs. This work extends the swept rule by targeting heterogeneous, CPU/GPU architectures representing current and future HPC systems. We compare our approach to a naive decomposition scheme with two test equations using an MPI+CUDA pattern on 40 processes over two nodes containing one GPU. The swept rule produces a factor of 1.9 to 23 speedup for the heat equation and a factor of 1.1 to 2.0 speedup for the Euler equations, using the same processors and work distribution, and with the best possible configurations. These results show the potential effectiveness of the swept rule for different equations and numerical schemes on massively parallel compute systems that incur substantial latency costs.
The use of generalized linear models in Bayesian phylogeography has enabled researchers to simultaneously reconstruct the spatiotemporal history of a virus and quantify the contribution of predictor ...variables to that process. However, little is known about the sensitivity of this method to the choice of the discrete state partition. Here we investigate this question by analyzing a data set containing 299 sequences of the West Nile virus envelope gene sampled in the United States and fifteen predictors aggregated at four spatial levels. We demonstrate that although the topology of the viral phylogenies was consistent across analyses, support for the predictors depended on the level of aggregation. In particular, we found that the variance of the predictor support metrics was minimized at the most precise level for several predictors and maximized at more sparse levels of aggregation. These results suggest that caution should be taken when partitioning a region into discrete locations to ensure that interpretable, reproducible posterior estimates are obtained. These results also demonstrate why researchers should use the most precise discrete states possible to minimize the posterior variance in such estimates and reveal what truly drives the diffusion of viruses.
Environmental and genetic activation of a brain-adipocyte axis inhibits cancer progression. Leptin is the primary peripheral mediator of this anticancer effect in a mouse model of melanoma. In this ...study we assessed the effect of a leptin receptor antagonist on melanoma progression. Local administration of a neutralizing nanobody targeting the leptin receptor at low dose adjacent to tumor decreased tumor mass with no effects on body weight or food intake. In contrast, systemic administration of the nanobody failed to suppress tumor growth. Daily intraperitoneal injection of high-dose nanobody led to weight gain, hyperphagia, increased adiposity, hyperleptinemia, and hyperinsulinemia, and central effects mimicking leptin deficiency. The blockade of central actions of leptin by systemic delivery of nanobody may compromise its anticancer effect, underscoring the need to develop peripherally acting leptin antagonists coupled with efficient cancer-targeting delivery.
•CUP occurs in as many as 3–5% of patients when standard diagnostic tests are not able to determine the origin of cancer.•MI GPSai (Genomic Prevalence Score) is an AI that uses genomic and ...transcriptomic data to elucidate tumor origin.•The algorithm was trained on molecular data from 57,489 cases and validated on 19,555 cases.•MI GPSai predicted the tumor type out of 21 options in the labeled data set with an accuracy of over 94% on 93% of cases.•When also considering the second highest prediction, the accuracy increases to 97%.
Cancer of Unknown Primary (CUP) occurs in 3–5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted the tumor type in the labeled data set with an accuracy of over 94% on 93% of cases while deliberating amongst 21 possible categories of cancer. When also considering the second highest prediction, the accuracy increases to 97%. Additionally, MI GPSai rendered a prediction for 71.7% of CUP cases. Pathologist evaluation of discrepancies between submitted diagnosis and MI GPSai predictions resulted in change of diagnosis in 41.3% of the time. MI GPSai provides clinically meaningful information in a large proportion of CUP cases and inclusion of MI GPSai in clinical routine could improve diagnostic fidelity. Moreover, all genomic markers essential for therapy selection are assessed in this assay, maximizing the clinical utility for patients within a single test.
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