Density dependent hadron field theory for neutron stars with antikaon condensates

We investigate $K^-$ and $\bar K^0$ condensation in $\beta$-equilibrated hyperonic matter within a density dependent hadron field theoretical model. In this model, baryon-baryon and (anti)kaon-baryon interactions are mediated by the exchange of mesons. Density dependent meson-baryon coupling constants are obtained from microscopic Dirac Brueckner calculations using Groningen and Bonn A nucleon-nucleon potential. It is found that the threshold of antikaon condensation is not only sensitive to the equation of state but also to antikaon optical potential depth. Only for large values of antikaon optical potential depth, $K^-$ condensation sets in even in the presence of negatively charged hyperons. The threshold of $\bar K^0$ condensation is always reached after $K^-$ condensation. Antikaon condensation makes the equation of state softer thus resulting in smaller maximum mass stars compared with the case without any condensate.Comment: 20 pages, 7 figures; final version to appear in Physical Review

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

The management of diabetic ketoacidosis in children

The object of this review is to provide the definitions, frequency, risk factors, pathophysiology, diagnostic considerations, and management recommendations for diabetic ketoacidosis (DKA) in children and adolescents, and to convey current knowledge of the causes of permanent disability or mortality from complications of DKA or its management, particularly the most common complication, cerebral edema (CE). DKA frequency at the time of diagnosis of pediatric diabetes is 10%–70%, varying with the availability of healthcare and the incidence of type 1 diabetes (T1D) in the community. Recurrent DKA rates are also dependent on medical services and socioeconomic circumstances. Management should be in centers with experience and where vital signs, neurologic status, and biochemistry can be monitored with sufficient frequency to prevent complications or, in the case of CE, to intervene rapidly with mannitol or hypertonic saline infusion. Fluid infusion should precede insulin administration (0.1 U/kg/h) by 1–2 hours; an initial bolus of 10–20 mL/kg 0.9% saline is followed by 0.45% saline calculated to supply maintenance and replace 5%–10% dehydration. Potassium (K) must be replaced early and sufficiently. Bicarbonate administration is contraindicated. The prevention of DKA at onset of diabetes requires an informed community and high index of suspicion; prevention of recurrent DKA, which is almost always due to insulin omission, necessitates a committed team effort

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Measurement of the cross section for isolated-photon plus jet production in pp collisions at √s=13 TeV using the ATLAS detector

The dynamics of isolated-photon production in association with a jet in proton–proton collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset with an integrated luminosity of 3.2 fb−1. Photons are required to have transverse energies above 125 GeV. Jets are identified using the anti- algorithm with radius parameter and required to have transverse momenta above 100 GeV. Measurements of isolated-photon plus jet cross sections are presented as functions of the leading-photon transverse energy, the leading-jet transverse momentum, the azimuthal angular separation between the photon and the jet, the photon–jet invariant mass and the scattering angle in the photon–jet centre-of-mass system. Tree-level plus parton-shower predictions from Sherpa and Pythia as well as next-to-leading-order QCD predictions from Jetphox and Sherpa are compared to the measurements