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Yin Li Yueying Ni Rupert A. C. Croft Tiziana Di Matteo Simeon Bird Yu Feng 《Proceedings of the National Academy of Sciences of the United States of America》2021,118(19)
Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in artificial intelligence (AI; specifically deep learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data and then make accurate superresolution (SR) versions of different low-resolution (LR) images. We apply such techniques to LR cosmological N-body simulations, generating SR versions. Specifically, we are able to enhance the simulation resolution by generating 512 times more particles and predicting their displacements from the initial positions. Therefore, our results can be viewed as simulation realizations themselves, rather than projections, e.g., to their density fields. Furthermore, the generation process is stochastic, enabling us to sample the small-scale modes conditioning on the large-scale environment. Our model learns from only 16 pairs of small-volume LR-HR simulations and is then able to generate SR simulations that successfully reproduce the HR matter power spectrum to percent level up to and the HR halo mass function to within down to . We successfully deploy the model in a box 1,000 times larger than the training simulation box, showing that high-resolution mock surveys can be generated rapidly. We conclude that AI assistance has the potential to revolutionize modeling of small-scale galaxy-formation physics in large cosmological volumes.As telescopes and satellites become more powerful, observational data on galaxies, quasars, and the matter in intergalactic space becomes more detailed and covers a greater range of epochs and environments in the Universe. Our cosmological simulations (see, e.g., ref. 1) must also become more detailed and more wide-ranging in order to make predictions and test the effects of different physical processes and different dark-matter candidates. Even with supercomputers, we are forced to decide whether to maximize either resolution or volume, or else compromise on both. These limitations can be overcome through the development of methods that leverage techniques from the artificial intelligence (AI) revolution (see, e.g., ref. 2) and make superresolution (SR) simulations possible. In the present work, we begin to explore this possibility, combining knowledge and existing superscalable codes for petascale-plus cosmological simulations (3) with machine learning (ML) techniques to effectively create representative volumes of the Universe that incorporate information from higher-resolution models of galaxy formation. Our first attempts, presented here, involve simulations with dark matter and gravity only, and extensions to full hydrodynamics will follow. This hybrid approach, which will imply offloading simulations to neural networks (NNs) and other ML algorithms, has the promise to enable the prediction of quasar, supermassive black hole, and galaxy properties in a way that is statistically identical to full hydrodynamic models, but with a significant speed-up.Adding details to images below the resolution scale (SR image enhancement) has become possible with the latest advances in deep learning (DL; ML with NN; ref. 4), including generative adversarial networks (GANs; ref. 5). The technique has applications in many fields, from microscopy to law enforcement (6). It has been used for observational astronomical images by (7), to recover galaxy features from below the resolution scale in degraded Hubble Space Telescope images. Besides SR image enhancement, DL has started to find applications in cosmological simulations. For example, refs. 8 and 9 showed how NNs can predict the nonlinear formation of structures given simple linear theory predictions. NN models have also been trained to predict galaxies (10, 11) and 21-cm emission from neutral hydrogen (12) from simulations that only contain dark matter. GANs have been used in ref. 13 to generate image slices of cosmological models and to generate dark-matter halos from density fields (14). ML techniques other than DL find many applications, too. For example, Kamdar et al. (15) have applied extremely randomized trees to dark-matter simulations to predict hydrodynamic galaxy properties.Generating mocks for future sky surveys requires large volumes and high accuracy, a task that quickly becomes computationally prohibitive. To alleviate the cost, recently, Dai and Seljak (16) developed a Lagrangian-based parametric ML model to predict various hydrodynamical outputs from the dark-matter density field. In other work, Dai et al. (17, 18) sharpened the particle distribution using a potential gradient descent method starting from low-resolution (LR) simulations. Note, however, that these approaches did not aim to enhance the spatial or mass resolution of a simulation.On the DL side, recently, Ramanah et al. (19) explored using the SR technique to map density fields of LR cosmological simulations to that of the high-resolution (HR) ones. While the goal is similar, our work has the following three key differences. First, instead of focusing on the dark-matter density field, we aim to enhance the number of particles and predict their displacements, from which the density fields can be inferred. This approach allows us to preserve the particle nature of the N-body simulations and therefore to interpret the SR outputs as simulations themselves. Second, we test our technique at a higher SR ratio. Compared to ref. 19, which increased the number of Eulerian voxels by 8 times, we increase the number of particles and thus the mass resolution by a factor of 512. Finally, to facilitate future applications of SR on hydrodynamic simulations in representative volumes, we test our method at much smaller scales and in large simulations whose volume is much bigger than that of the training data. 相似文献
3.
Licia Iaccarino Tiziana Ottone Valentina Alfonso Laura Cicconi Mariadomenica Divona Serena Lavorgna Serena Travaglini Aleandra Ferrantini Giulia Falconi Constance Baer Monica Usai Fabio Forghieri Adriano Venditti Maria Ilaria Del Principe William Arcese Maria Teresa Voso Torsten Haferlach Francesco Lo-Coco 《American journal of hematology》2019,94(10):1091-1097
Despite the high probability of cure of patients with acute promyelocytic leukemia (APL), mechanisms of relapse are still largely unclear. Mutational profiling at diagnosis and/or relapse may help to identify APL patients needing frequent molecular monitoring and early treatment intervention. Using an NGS approach including a 31 myeloid gene-panel, we tested BM samples of 44 APLs at the time of diagnosis, and of 31 at relapse. Mutations in PML and RARA genes were studied using a customized-NGS-RNA panel. Patients relapsing after ATRA-chemotherapy rarely had additional mutations (P = .009). In patients relapsing after ATRA/ATO, the PML gene was a preferential mutation target. We then evaluated the predictive value of mutations at APL diagnosis. A median of two mutations was detectable in 9/11 patients who later relapsed, vs one mutation in 21/33 patients who remained in CCR (P = .0032). This corresponded to a significantly lower risk of relapse in patients with one or less mutations (HR 0.046; 95% CI 0.011-0.197; P < .0001). NGS-analysis at the time of APL diagnosis may inform treatment decisions, including alternative treatments for cases with an unfavorable mutation profile. 相似文献
4.
Marta Campagnolo Federica Taioli Mario Cacciavillani Marta Ruiz Marco Luigetti Alessandro Salvalaggio Francesca Castellani Silvia Testi Moreno Ferrarini Tiziana Cavallaro Roberto Gasparotti Gian Maria Fabrizi Chiara Briani 《Journal of the peripheral nervous system : JPNS》2020,25(1):19-26
Hereditary neuropathies may be misdiagnosed with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). A correct diagnosis is crucial for avoiding unnecessary therapies and access genetic counseling. We report on nine patients (seven men, mean age 49.2 ± 16.1) diagnosed with and treated as CIDP, in whom mutations or variants of unknown significance (VUS) in genes associated with hereditary neuropathies were reported. All underwent neurological and neurophysiological examination, eight also cerebrospinal fluid (CSF) analysis. In 4/9, nerve ultrasound and/or MR‐neurography were performed. All the patients complained of progressive upper or lower limbs sensory‐motor symptoms, with heterogeneous disease duration (1‐34 years, mean 8.6 ± 10.8). Neurophysiology showed demyelinating signs in seven patients, mixed findings with predominant axonal damage in two patients. Neuroimaging disclosed diffuse abnormalities at proximal and distal segments. Molecular screening showed PMP22 duplication in two patients, mutations in the MPZ, EGR2, and GJB1 genes were reported in each of the remaining patients. The two patients with mixed neurophysiological findings had p.Val30Met mutation in the transthyretin gene. Two patients had VUS in the MARS and HSPB1 genes. Four patients had partial response to immunomodulant therapies, and CSF and neurophysiological features suggesting an inflammatory condition concomitant with the hereditary neuropathy. Hereditary neuropathy may be misdiagnosed with CIDP. The most common pitfalls are CSF (high protein levels and oligoclonal bands), incorrect interpretation of neurophysiology, and transient benefit from therapies. Neuroimaging may be helpful in cases with atypical presentations or when severe axonal damage complicate the neurophysiological interpretation. 相似文献
5.
Orazio Palmieri Tommaso Mazza Gabrio Bassotti Antonio Merla Salvatore Tolone Tommaso Biagini Antonello Cuttitta Fabrizio Bossa Giuseppina Martino Tiziana Latiano Giuseppe Corritore Domenica Gioffreda Orazio Palumbo Massimo Carella Anna Panza Angelo Andriulli Anna Latiano 《Neurogastroenterology and motility》2020,32(3)
6.
D. Ross Camidge Elizabeth E. Kim Tiziana Usari Anna Polli Iona Lewis Keith D. Wilner 《Journal of thoracic oncology》2019,14(6):1077-1085
IntroductionWe retrospectively analyzed the effects of crizotinib on serum creatinine and creatinine-based estimated glomerular filtration rate (eGFR) in patients with anaplastic lymphoma kinase–positive advanced NSCLC across four trials (NCT00585195, NCT00932451, NCT00932893, and NCT01154140).MethodsChanges from baseline data in serum creatinine and eGFR, calculated using the Chronic Kidney Disease Epidemiology Collaboration creatinine-based equation, were assessed over time. eGFR was graded using standard chronic kidney disease criteria.ResultsMedian serum creatinine increased from 0.79 mg/dL at baseline to 0.93 mg/dL after 2 weeks of treatment (median percentage increase from baseline, 21.2%), was stable from week 12 (0.96 mg/dL) to week 104 (1.00 mg/dL), and decreased to 0.90 mg/dL at 28 days after last dose (median percentage increase from baseline, 13.1%). Median eGFR decreased over time (96.42, 80.23, 78.06 and 75.45 mL/min/1.73 m2 at baseline, week 2, week 12, and week 104, respectively) and increased to 83.02 mL/min/1.73 m2 at 28 days after the last dose. Median percentage decrease from baseline was 14.9%, 17.0%, and 10.4% at week 2, week 12, and 28 days after last dose of crizotinib, respectively. Overall, 12.6% of patients had a shift from eGFR grade less than or equal to 3a (≥45 mL/min/1.73 m2) at baseline to greater than or equal to 3b (<45 mL/min/1.73 m2) post-baseline.ConclusionsCrizotinib resulted in a decline in creatinine-based estimates of renal function mostly over the first 2 weeks of treatment. However, there was minimal evidence of cumulative effects with prolonged treatment and these changes were largely reversible following treatment discontinuation, consistent with previous reports suggesting this may be predominantly an effect on creatinine secretion as opposed to true nephrotoxicity. 相似文献
7.
8.
Milena Villarini Sara Levorato Tania Salvatori Elisabetta Ceretti Sara Bonetta Annalaura Carducci Tiziana Grassi Samuele Vannini Francesco Donato Silvia Bonetta Marco Verani Antonella de Donno Silvia Bonizzoni Alberto Bonetti Massimo Moretti Umberto Gelatti 《International journal of hygiene and environmental health》2018,221(6):883-892
Background
Recent data support the hypothesis that genetic damage occurring early in life during childhood can play an important role in the development of chronic diseases in adulthood, including cancer.Objectives
The objective of this paper, part of the MAPEC_LIFE project, is to describe the frequency of micronuclei and meta-nuclear alterations in exfoliated buccal cells of 6–8year-old Italian children recruited in five Italian towns (i.e., Brescia, Torino, Pisa, Perugia and Lecce) with different air pollution levels.Methods
About 200 children per town were recruited from primary schools. Biological samples were collected twice from the same children, in two different seasons (winter 2014-15 and late spring 2015). Cytogenetic damage was evaluated by the buccal micronucleus cytome assay.Results
Overall,n?=?1046 children represent the final cohort of the MAPEC_LIFE study. On the whole, the results showed a higher mean MN frequency in winter (0.42?±?0.54‰) than late-spring (0.22?±?0.34‰). MN frequency observed among the five Italian towns showed a trend that follows broadly the levels of air pollution in Italy: the highest MN frequency was observed in Brescia during both seasons, the lowest in Lecce (winter) and Perugia (late-spring).Conclusions
To the best of our knowledge, the number of recruited children included in the analysis (n?=?1046) is the highest compared to previous studies evaluating the frequency of MN in exfoliated buccal cells so far. MN frequency was associated with winter season and living in towns at various levels of air pollution, suggesting an important role of this exposure in determining early cytogenetic effects. 相似文献9.
Pisano E Cabras T Montaldo C Piras V Inzitari R Olmi C Castagnola M Messana I 《European journal of oral sciences》2005,113(6):462-468
The acidic-soluble protein content of human gingival crevicular fluid was analyzed by reverse-phase high-performance liquid chromatography (RP-HPLC), and the eluent deriving from the chromatography separation was directly introduced into an ion-trap mass spectrometer through electrospray ionization (ESI-IT MS). By this technique the molecular weight of peptides/proteins was determined with a precision of approximately 1/10,000 amu. On the basis of the chromatographic behavior and the knowledge of the molecular mass value, some peptides and proteins soluble in acidic solution were unambiguously recognized. Besides high quantities of human serum albumin, alpha-defensins 1-4 and minor amounts of cystatin A, statherin, basic PB salivary peptide and other unidentified components were detected. The presence of alpha-defensins in gingival crevicular fluid is in agreement with their relevant contribution to protein composition deriving from granulocyte secretions. Other peptides and proteins abundant in human saliva, such as proline-rich proteins (PRPs) and histatins, were not detected in gingival crevicular fluid. Further investigations will be necessary to establish the origin of statherin and PB salivary peptide in gingival crevicular fluid. 相似文献
10.
Cabras T Castagnola M Inzitari R Ekström J Isola M Riva A Messana I 《Archives of oral biology》2008,53(11):1077-1083