Peculiar-velocity surveys of the low-redshift universe have significant leverage to constrain the growth rate of cosmic structure and test gravity. Wide-field imaging surveys combined with ...multiobject spectrographs e.g., ZTF2, Large Synoptic Survey Telescope (LSST), DESI, and 4MOST can use type Ia supernovae as informative tracers of the velocity field, reaching few percent constraints on the growth rate fσ8 at z≲0.2 where density tracers cannot do better than ∼10%. Combining the high-redshift DESI survey mapping redshift space distortions with a low-redshift supernova peculiar velocity survey using LSST and DESI can determine the gravitational growth index to σ(γ)≈0.02, testing general relativity. We study the characteristics needed for the peculiar velocity survey, and how its complementarity with clustering surveys improves when going from a ΛCDM model assumption to a w0–wa cosmology.
ABSTRACT
Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. ...Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the probabilistic auto-encoder, to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae, and overlapping objects. Conditional modelling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available.
Introduction: In the era of precision medicine and sophisticated modern genetics, the discovery of the BRAF
V600
inhibitor, vemurafenib, quickly became the model for targeted therapy in melanomas. As ...early as 2002, the majority of metastatic melanomas were described to harbor the BRAF
V600
mutation, setting the stage for an explosion of interest for targeting this protein as a novel therapeutic strategy. The highly selective BRAF
V600
inhibitor, vemurafenib, was identified initially through a large-scale drug screen.
Areas covered: Here we examine vemurafenib's journey from discovery to clinical use in metastatic melanoma. Topics covered include preclinical data, single agent Phase 1,2 and 3 clinical trials, resistance issues and mechanisms, adverse effects including the development of squamous cell cancers, and combination trials.
Expert opinion: Due to its tolerance, low toxicity profile, rapid tumor response, and improved outcomes in melanoma patients with BRAF
V600
mutations, vemurafenib was advanced rapidly through clinical trials to receive FDA approval in 2011. While its efficacy is well documented, durability has become an issue for most patients who experience therapeutic resistance in approximately 6-8 months. In addition, a concerning toxicity observed in patients taking the drug include development of localized cutaneous squamous cell carcinomas (SCCs). It is hypothesized that drug resistance and SCC development result from a similar paradoxical activation of protein signaling pathways, specifically MAPK. Identification of these mechanisms has led to additional treatment strategies involving new combination therapies.
Abstract
We examine the Pantheon supernovae distance data compilation in a model independent analysis to test the validity of cosmic history reconstructions beyond the concordance ΛCDM cosmology. ...Strong deviations are allowed by the data at z ≳ 1 in the reconstructed Hubble parameter, Om diagnostic, and dark energy equation of state. We explore three interpretations: 1) possibility of the true cosmology being far from ΛCDM, 2) supernovae property evolution, and 3) survey selection effects. The strong (and theoretically problematic) deviations at z ≳ 1 vanish and good consistency with ΛCDM is found with a simple Malmquist-like linear correction. The adjusted data is robust against the model independent iterative smoothing reconstruction. However, we caution that while by eye the original deviation from ΛCDM is striking, χ2 tests do not show the extra linear correction parameter is statistically significant, and a model-independent Gaussian Process regression does not find significant evidence for the need for correction at high-redshifts.
Abstract
Gravitationally lensed Type Ia supernovae (SNe Ia) may be the next frontier in cosmic probes, able to deliver independent constraints on dark energy, spatial curvature, and the Hubble ...constant. Measurements of time delays between the multiple images become more incisive due to the standardized candle nature of the source, monitoring for months rather than years, and partial immunity to microlensing. While currently extremely rare, hundreds of such systems should be detected by upcoming time domain surveys. Others will have the images spatially unresolved, with the observed lightcurve a superposition of time-delayed image fluxes. We investigate whether unresolved images can be recognized as lensed sources given only lightcurve information, and whether time delays can be extracted robustly. We develop a method that we show can identify these systems for the case of lensed SNe Ia with two images and time delays exceeding ten days. When tested on such an ensemble, without microlensing, the method achieves a false-positive rate of ≲5%, and measures the time delays with a completeness of ≳93% and with a bias of ≲0.5% for Δ
t
fit
≳ 10 days. Since the method does not assume a template of any particular type of SN, the method has the (untested) potential to work on other types of lensed SNe systems and possibly on other transients as well.
ABSTRACT
Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their ...time delayed and magnified fluxes may be unresolved, however, blended into a single light curve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100 per cent success for determining the number of images for time delays greater than ∼10 d.
Background Aspirin-exacerbated respiratory disease (AERD) is characterized by tissue eosinophilia and mast cell activation, including abundant production of prostaglandin D2 (PGD2 ). Group 2 innate ...lymphoid cells (ILC2s), which promote tissue eosinophilia and mast cell responses, undergo chemotaxis and cytokine production in response to PGD2 , but it is unknown whether ILC2s are active in patients with AERD. Objective We sought to determine whether ILC2 numbers change in peripheral blood and the nasal mucosa during COX-1 inhibitor–induced reactions in patients with AERD. Methods Blood and nasal scrapings were collected at baseline, during reactions, and after completion of ketorolac/aspirin challenge/desensitization in 12 patients with AERD. ILC2s and eosinophils were quantitated by means of flow cytometry. Urine was also collected, and quantification of PGD2 metabolite and leukotriene E4 levels was done by using ELISA. Baseline and nonsteroidal anti-inflammatory drug reaction clinical data were correlated with cell changes. Results ILC2 numbers significantly increased in nasal mucosal samples and decreased in blood at the time of COX-1 inhibitor reactions in 12 patients with AERD. These changes were not observed in 2 patients without AERD. Furthermore, eosinophil numbers decreased in blood concurrently with significant increases in urinary PGD2 metabolite and leukotriene E4 levels. The magnitude of increases in nasal mucosal ILC2 numbers positively correlated with maximum symptom scores during challenges. Furthermore, blood ILC2 numbers during the reaction correlated with time for the reaction to resolve, possibly reflecting reaction severity. Conclusions ILC2s are recruited to the nasal mucosa during COX-1 inhibitor–induced reactions in patients with AERD, correlating with enhanced production of prostaglandins and leukotrienes.
We use Gaussian processes to map the expansion history of the universe in a model-independent manner from the Union2.1 supernovae data and then apply these reconstructed results to solve for the ...growth history. By comparing this to Baryon Oscillation Spectroscopic Survey and WiggleZ large-scale structure data we examine whether growth is determined wholly by expansion, with the measured gravitational growth index testing gravity without assuming a model for dark energy. A further model-independent analysis looks for redshift-dependent deviations of growth from the general relativity solution without assuming the growth index form. Both approaches give results consistent with general relativity.
ABSTRACT
In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to ...which the 4-m Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching rAB ≈ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint high-redshift supernovae observed from larger spectroscopic facilities; the algorithms’ range of average area under receiver operator characteristic curve (AUC) scores over 10 runs increases from 0.547–0.628 to 0.946–0.969 and purity of the classified sample reaches 95 per cent in all runs for two of the four algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having ‘true’ faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimization of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.
Background
There is a paucity of targeted therapies for patients with pseudomyxoma peritonei (PMP) secondary to low-grade appendiceal mucinous neoplasms (LAMNs). Dysregulated metabolism has emerged ...as a hallmark of cancer, and the relationship of metabolomics and cancer is an area of active scientific exploration. We sought to characterize phenotypic differences found in peritoneal metastases (PM) derived from LAMN versus adenocarcinoma.
Methods
Tumors were washed with phosphate-buffered saline (PBS), microdissected, then dissociated in ice-cold methanol dried and reconstituted in pyridine. Samples were derivatized in tert-butyldimethylsilyl (TBDMS) and subjected to gas chromatography-coupled mass spectrometry. Metabolites were assessed based on a standard library. RNA sequencing was performed, with pathway and network analyses on differentially expressed genes.
Results
Eight peritoneal tumor samples were obtained and analyzed: LAMNs (4), and moderate to poorly differentiated adenocarcinoma (colon 1, appendix 3). Decreases in pyroglutamate, fumarate, and cysteine in PM from LAMNs were found compared with adenocarcinoma. Analyses showed the differential gene expression was dominated by the prevalence of metabolic pathways, particularly lipid metabolism. The gene retinol saturase (
RETSAT
), downregulated by LAMN, was involved in the multiple metabolic pathways that involve lipids. Using network mapping, we found IL1B signaling to be a potential top-level modulation candidate.
Conclusions
Distinct metabolic signatures may exist for PM from LAMN versus adenocarcinoma. A multitude of genes are differentially regulated, many of which are involved in metabolic pathways. Additional research is needed to identify the significance and applicability of targeting metabolic pathways in the potential development of novel therapeutics for these challenging tumors.
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