Low frequency radio properties of the z>5 quasar population

Optically luminous quasars at z > 5 are important probes of super-massive black hole (SMBH) formation. With new and future radio facilities, the discovery of the brightest low-frequency radio sources in this epoch would be an important new probe of cosmic reionization through 21-cm absorption experiments. In this work, we systematically study the low-frequency radio properties of a sample of 115 known spectroscopically confirmed z > 5 quasars using the second data release of the Low Frequency Array (LOFAR) Two Metre Sky survey (LoTSS-DR2), reaching noise levels of ∼80 µJy beam−1 (at 144 MHz) over an area of ∼ 5720 deg2 . We find that 41 sources (36%) are detected in LoTSS-DR2 at > 2σ significance and we explore the evolution of their radio properties (power, spectral index, and radio loudness) as a function of redshift and rest-frame ultra-violet properties. We obtain a median spectral index of −0.29+0.10 −0.09 by stacking 93 quasars using LoTSS-DR2 and Faint Images of the Radio Sky at Twenty Centimetres (FIRST) data at 1.4 GHz, in line with observations of quasars at z < 3. We compare the radio loudness of the high-z quasar sample to a lower-z quasar sample at z ∼ 2 and find that the two radio loudness distributions are consistent with no evolution, although the low number of high-z quasars means that we cannot rule out weak evolution. Furthermore, we make a first order empirical estimate of the z = 6 quasar radio luminosity function, which is used to derive the expected number of high-z sources that will be detected in the completed LoTSS survey. This work highlights the fact that new deep radio observations can be a valuable tool in selecting high-z quasar candidates for follow-up spectroscopic observations by decreasing contamination of stellar dwarfs and reducing possible selection biases introduced by strict colour cuts

Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of ' easy to apply ' probability models

To establish an efficient, reliable and easy to apply risk assessment tool to select families with breast and/or ovarian cancer patients for BRCA mutation testing, using available probability models. In a retrospective study of 263 families with breast and/or ovarian cancer patients, the utility of the Frank (Myriad), Gilpin (family history assessment tool) and Evans (Manchester) model was analysed, to select 49 BRCA mutation-positive families. For various cutoff levels and combinations, the sensitivity and specificity were calculated and compared. The best combinations were subsequently validated in additional sets of families. Comparable sensitivity and specificity were obtained with the Gilpin and Evans models. They appeared to be complementary to the Frank model. To obtain an optimal sensitivity, five ‘additional criteria' were introduced that are specific for the selection of small or uninformative families. The optimal selection is made by the combination ‘Frank ⩾16% or Evans2 ⩾12 or one of five additional criteria'. The efficiency of the selection of families for mutation testing of BRCA1 and BRCA2 can be optimised by using a combination of available easy to apply risk assessment models