Spectral classification of young stars using conditional invertible neural networks I. Introducing and validating the method

Aims. We introduce a new deep learning tool that estimates stellar parameters (such as effective temperature, surface gravity, and extinction) of young low-mass stars by coupling the Phoenix stellar atmosphere model with a conditional invertible neural network (cINN). Our networks allow us to infer the posterior distribution of each stellar parameter from the optical spectrum. Methods. We discuss cINNs trained on three different Phoenix grids: Settl, NextGen, and Dusty. We evaluate the performance of these cINNs on unlearned Phoenix synthetic spectra and on the spectra of 36 Class III template stars with well-characterised stellar parameters. Results. We confirm that the cINNs estimate the considered stellar parameters almost perfectly when tested on unlearned Phoenix synthetic spectra. Applying our networks to Class III stars, we find good agreement with deviations of at most 5--10 per cent. The cINNs perform slightly better for earlier-type stars than for later-type stars like late M-type stars, but we conclude that estimations of effective temperature and surface gravity are reliable for all spectral types within the network's training range. Conclusions. Our networks are time-efficient tools applicable to large amounts of observations. Among the three networks, we recommend using the cINN trained on the Settl library (Settl-Net), as it provides the best performance across the largest range of temperature and gravity.Comment: 29 pages, 19 figures, Accepted for publication by Astronomy & Astrophysics on 10. Apri

Noise-Net: Determining physical properties of HII regions reflecting observational uncertainties

Stellar feedback, the energetic interaction between young stars and their birthplace, plays an important role in the star formation history of the universe and the evolution of the interstellar medium (ISM). Correctly interpreting the observations of star-forming regions is essential to understand stellar feedback, but it is a non-trivial task due to the complexity of the feedback processes and degeneracy in observations. In our recent paper, we introduced a conditional invertible neural network (cINN) that predicts seven physical properties of star-forming regions from the luminosity of 12 optical emission lines as a novel method to analyze degenerate observations. We demonstrated that our network, trained on synthetic star-forming region models produced by the WARPFIELD-Emission predictor (WARPFIELD-EMP), could predict physical properties accurately and precisely. In this paper, we present a new updated version of the cINN that takes into account the observational uncertainties during network training. Our new network named Noise-Net reflects the influence of the uncertainty on the parameter prediction by using both emission-line luminosity and corresponding uncertainties as the necessary input information of the network. We examine the performance of the Noise-Net as a function of the uncertainty and compare it with the previous version of the cINN, which does not learn uncertainties during the training. We confirm that the Noise-Net outperforms the previous network for the typical observational uncertainty range and maintains high accuracy even when subject to large uncertainties.Comment: 22 pages, 14 figures, Accepted for publication by MNRAS on 04. Januar

Theory and Applications of Non-Relativistic and Relativistic Turbulent Reconnection

Realistic astrophysical environments are turbulent due to the extremely high Reynolds numbers. Therefore, the theories of reconnection intended for describing astrophysical reconnection should not ignore the effects of turbulence on magnetic reconnection. Turbulence is known to change the nature of many physical processes dramatically and in this review we claim that magnetic reconnection is not an exception. We stress that not only astrophysical turbulence is ubiquitous, but also magnetic reconnection itself induces turbulence. Thus turbulence must be accounted for in any realistic astrophysical reconnection setup. We argue that due to the similarities of MHD turbulence in relativistic and non-relativistic cases the theory of magnetic reconnection developed for the non-relativistic case can be extended to the relativistic case and we provide numerical simulations that support this conjecture. We also provide quantitative comparisons of the theoretical predictions and results of numerical experiments, including the situations when turbulent reconnection is self-driven, i.e. the turbulence in the system is generated by the reconnection process itself. We show how turbulent reconnection entails the violation of magnetic flux freezing, the conclusion that has really far reaching consequences for many realistically turbulent astrophysical environments. In addition, we consider observational testing of turbulent reconnection as well as numerous implications of the theory. The former includes the Sun and solar wind reconnection, while the latter include the process of reconnection diffusion induced by turbulent reconnection, the acceleration of energetic particles, bursts of turbulent reconnection related to black hole sources as well as gamma ray bursts. Finally, we explain why turbulent reconnection cannot be explained by turbulent resistivity or derived through the mean field approach.Comment: 66 pages, 24 figures, a chapter of the book "Magnetic Reconnection - Concepts and Applications", editors W. Gonzalez, E. N. Parke

The first report of RPSA polymorphisms, also called 37/67 kDa LRP/LR gene, in sporadic Creutzfeldt-Jakob disease (CJD)

<p>Abstract</p> <p>Background</p> <p>Although polymorphisms of <it>PRNP</it>, the gene encoding prion protein, are known as a determinant affecting prion disease susceptibility, other genes also influence prion incubation time. This finding offers the opportunity to identify other genetic or environmental factor (s) modulating susceptibility to prion disease. Ribosomal protein SA (<it>RPSA</it>), also called 37 kDa laminin receptor precursor (LRP)/67 kDa laminin receptor (LR), acts as a receptor for laminin, viruses and prion proteins. The binding/internalization of prion protein is dependent for LRP/LR.</p> <p>Methods</p> <p>To identify other susceptibility genes involved in prion disease, we performed genetic analysis of <it>RPSA</it>. For this case-control study, we included 180 sporadic Creutzfeldt-Jakob disease (CJD) patients and 189 healthy Koreans. We investigated genotype and allele frequencies of polymorphism on <it>RPSA </it>by direct sequencing or restriction fragment length polymorphism (RFLP) analysis.</p> <p>Results</p> <p>We observed four single nucleotide polymorphisms (SNPs), including -8T>C (rs1803893) in the 5'-untranslated region (UTR) of exon 2, 134-32C>T (rs3772138) in the intron, 519G>A (rs2269350) in the intron and 793+58C>T (rs2723) in the intron on the <it>RPSA</it>. The 519G>A (at codon 173) is located in the direct PrP binding site. The genotypes and allele frequencies of the <it>RPSA </it>polymorphisms showed no significant differences between the controls and sporadic CJD patients.</p> <p>Conclusion</p> <p>These results suggest that these <it>RPSA </it>polymorphisms have no direct influence on the susceptibility to sporadic CJD. This was the first genetic association study of the polymorphisms of <it>RPSA </it>gene with sporadic CJD.</p

Combination treatment with doxorubicin and gamitrinib synergistically augments anticancer activity through enhanced activation of Bim

Background: A common approach to cancer therapy in clinical practice is the combination of several drugs to boost the anticancer activity of available drugs while suppressing their unwanted side effects. In this regard, we examined the efficacy of combination treatment with the widely-used genotoxic drug doxorubicin and the mitochondriotoxic Hsp90 inhibitor gamitrinib to exploit disparate stress signaling pathways for cancer therapy.Methods: The cytotoxicity of the drugs as single agents or in combination against several cancer cell types was analyzed by MTT assay and the synergism of the drug combination was evaluated by calculating the combination index. To understand the molecular mechanism of the drug synergism, stress signaling pathways were analyzed after drug combination. Two xenograft models with breast and prostate cancer cells were used to evaluate anticancer activity of the drug combination in vivo. Cardiotoxicity was assessed by tissue histology and serum creatine phosphokinase concentration.Results: Gamitrinib sensitized various human cancer cells to doxorubicin treatment, and combination treatment with the two drugs synergistically increased apoptosis. The cytotoxicity of the drug combination involved activation and mitochondrial accumulation of the proapoptotic Bcl-2 family member Bim. Activation of Bim was associated with increased expression of the proapoptotic transcription factor C/EBP-homologous protein and enhanced activation of the stress kinase c-Jun N-terminal kinase. Combined drug treatment with doxorubicin and gamitrinib dramatically reduced in vivo tumor growth in prostate and breast xenograft models without increasing cardiotoxicity.Conclusions: The drug combination showed synergistic anticancer activities toward various cancer cells without aggravating the cardiotoxic side effects of doxorubicin, suggesting that the full therapeutic potential of doxorubicin can be unleashed through combination with gamitrinib.open

Facile control of nanoporosity in Cellulose Acetate using Nickel(II) nitrate additive and water pressure treatment for highly efficient battery gel separators

We succeed in fabricating nearly straight nanopores in cellulose acetate (CA) polymers for use as battery gel separators by utilizing an inorganic hexahydrate (Ni(NO3)2??6H2O) complex and isostatic water pressure treatment. The continuous nanopores are generated when the polymer film is exposed to isostatic water pressure after complexing the nickel(II) nitrate hexahydrate (Ni(NO3)2??6H2O) with the CA. These results can be attributed to the manner in which the polymer chains are weakened because of the plasticization effect of the Ni(NO3)2??6H2O that is incorporated into the CA. Furthermore, we performed extensive molecular dynamics simulation for confirming the interaction between electrolyte and CA separator. The well controlled CA membrane after water pressure treatment enables fabrication of highly reliable cell by utilizing 2032-type coin cell structure. The resulting cell performance exhibits not only the effect of the physical morphology of CA separator, but also the chemical interaction of electrolyte with CA polymer which facilitates the Li-ion in the cell.ope

A placebo-controlled trial of Korean red ginseng extract for preventing Influenza-like illness in healthy adults

<p>Abstracts</p> <p>Background</p> <p>Standardized Korean red ginseng extract has become the best-selling influenza-like illness (ILI) remedy in Korea, yet much controversy regarding the efficacy of the Korean red ginseng (KRG) in reducing ILI incidence remains. The aim of the study is to assess the efficacy of the KRG extract on the ILI incidence in healthy adults.</p> <p>Methods/Design</p> <p>We will conduct a randomized, double-blind, placebo-controlled study at the onset of the influenza seasons. A total of 100 subjects 30-70 years of age will be recruited from the general populations. The subjects will be instructed to take 9 capsules per day of either the KRG extract or a placebo for a period of 3 months. The primary outcome measure is to assess the frequency of ILI onset in participated subjects. Secondary variable measures will be included severity and duration of ILI symptoms. The ILI symptoms will be scored by subjects using a 4-point scale.</p> <p>Discussion</p> <p>This study is a randomized placebo controlled trial to evaluate the efficacy of the KRG extract compared to placebo and will be provided valuable new information about the clinical and physiological effects of the KRG extract on reduction of ILI incidence including flu and upper respiratory tract infections. The study has been pragmatically designed to ensure that the study findings can be implemented into clinical practice if KRG extract can be shown to be an effective reduction strategy in ILI incidence.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01478009">NCT01478009</a>.</p

Nosocomial infection in a newborn intensive care unit (NICU), South Korea

BACKGROUND: This study aimed to determine the occurrence of nosocomial infections (NIs), including infection rates, main infection sites, and common microorganisms. Patients included in the study were taken from a newborn intensive care unit (NICU), in a hospital in South Korea. METHODS: A retrospective cohort study was performed by reviewing chart. The subjects were 489 neonates who were admitted to the NICU, survived longer than 72 hours, and not transferred to another unit, between Jan. 1. 1995 to Sep. 30, 1999. NIs were identified according to the NNIS definition. Data were analyzed with descriptive statistics. RESULTS: Cumulative incidence rate for NIs was 30.3 neonates out of 100 admissions, with a total of 44.6 infections. The incidence density was average 10.2 neonates and 15.1 infections per 1000 patient days. The most common infections were pneumonia (28%), bloodstream infection (26%), and conjunctivitis (22%). Major pathogens were Gram-positives such as Staphylococcus aureus and coagulase-negative staphylococci. The factors associated with NI was less than 1500 g of birth weight, less than 32 weeks of gestational age, and less than 8 of apgar score. There's no statistical difference in discharge status between two groups, but hospital stay was longer in subjects with nosocomial infection than those without infection. CONCLUSION: Although the distribution of pathogens was similar to previous reports, a high rate of nosocomial infection and in particular conjunctivitis was observed in this study that merits further evaluation

Refined cut-off for TP53 immunohistochemistry improves prediction of TP53 mutation status in ovarian mucinous tumors: implications for outcome analyses.

TP53 mutations are implicated in the progression of mucinous borderline tumors (MBOT) to mucinous ovarian carcinomas (MOC). Optimized immunohistochemistry (IHC) for TP53 has been established as a proxy for the TP53 mutation status in other ovarian tumor types. We aimed to confirm the ability of TP53 IHC to predict TP53 mutation status in ovarian mucinous tumors and to evaluate the association of TP53 mutation status with survival among patients with MBOT and MOC. Tumor tissue from an initial cohort of 113 women with MBOT/MOC was stained with optimized IHC for TP53 using tissue microarrays (75.2%) or full sections (24.8%) and interpreted using established criteria as normal or abnormal (overexpression, complete absence, or cytoplasmic). Cases were considered concordant if abnormal IHC staining predicted deleterious TP53 mutations. Discordant tissue microarray cases were re-evaluated on full sections and interpretational criteria were refined. The initial cohort was expanded to a total of 165 MBOT and 424 MOC for the examination of the association of survival with TP53 mutation status, assessed either by TP53 IHC and/or sequencing. Initially, 82/113 (72.6%) cases were concordant using the established criteria. Refined criteria for overexpression to account for intratumoral heterogeneity and terminal differentiation improved concordance to 93.8% (106/113). In the expanded cohort, 19.4% (32/165) of MBOT showed evidence for TP53 mutation and this was associated with a higher risk of recurrence, disease-specific death, and all-cause mortality (overall survival: HR = 4.6, 95% CI 1.5-14.3, p = 0.0087). Within MOC, 61.1% (259/424) harbored a TP53 mutation, but this was not associated with survival (overall survival, p = 0.77). TP53 IHC is an accurate proxy for TP53 mutation status with refined interpretation criteria accounting for intratumoral heterogeneity and terminal differentiation in ovarian mucinous tumors. TP53 mutation status is an important biomarker to identify MBOT with a higher risk of mortality.KLG is supported by the Victorian Cancer Agency (MCRF15013) and the Australian National Health and Medical Research Council (APP1045783 and #628434). This study was supported by the Peter MacCallum Cancer Foundation. CS is supported by a University of Melbourne Postgraduate Scholarship. DDB is supported by National Health and Medical Research Council of Australia (NHMRC) grants APP1092856 and APP1117044 and by the US National Cancer Institute U54 programme (U54CA209978-04). ELG and SHK are supported through P50 CA136393-10. The following cohorts that contributed to the GAMuT study were supported as follows: CASCADE: Supported by the Peter MacCallum Cancer Foundation AOCS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID400413 and ID400281). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation. The AOCS also acknowledges the cooperation of the participating institutions in Australia and acknowledges the contribution of the study nurses, research assistants and all clinical and scientific collaborators to the study. The complete AOCS Study Group can be found at www.aocstudy.org. We would like to thank all of the women who participated in these research programs. OVCARE receives core funding from The BC Cancer Foundation and the VGH and UBC Hospital Foundation. The Gynaecological Oncology Biobank at Westmead is a member of the Australasian Biospecimen Network-Oncology group, which was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. COEUR: This study uses resources provided by the Canadian Ovarian Cancer Research Consortium’s - COEUR biobank funded by the Terry Fox Research Institute and managed and supervised by the Centre hospitalier de l’Université de Montréal (CRCHUM). The Consortium acknowledges contributions to its COEUR biobank from Institutions across Canada (for a full list see http://www.tfri.ca/en/research/translational-research/coeur/coeur_biobanks.aspx). The following cohorts that contributed to OTTA were supported as follows: AOV: Canadian Institutes of Health Research (MOP-86727), Cancer Research Society (19319). BAV: ELAN Funds of the University of Erlangen-Nuremberg; DOV: NCI/NIH R01CA168758. Huntsman Cancer Foundation and the National Cancer Institute of the National Institutes of Health under Award Number P30CA042014. HAW: U.S. National 19 Institutes of Health (R01-CA58598, N01-CN-55424 and N01-PC-67001); MAY: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; SEA: SEARCH team: Mitul Shah, Jennifer Alsopp, Mercedes Jiminez-Linan SEARCH funding: Cancer Research UK (C490/A16561), the Cancer Research UK Cambridge Cancer Centre and the National Institute for Health Research Cambridge Biomedical Research Centres. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. JBD: Cancer Research UK Institute Group Award UK A22905 and A15601; STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and årKampMotCancer foundation; TVA: Canadian Institutes of Health Research grant (MOP-86727) and NIH/NCI 1 R01CA160669- 01A1; VAN: M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. The Vancouver study cohort (TVAN) is supported by BC’s Ovarian Cancer Research team (OVCARE), the BC Cancer Foundation and The VGH+UBC Hospital Foundation. WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16