A precisely-dated lake-level rise marked by diatomite formation in northeastern Ireland

The intercorrelation of palaeoclimate events from various studies is often hindered by a lack of precise chronological control. Tephra isochrons can overcome this problem by providing direct site linkages. This paper outlines a study of Holocene peat and diatomite deposits that accumulated within the floodplain of Lough Neagh, Northern Ireland. The Icelandic Hekla 4 tephra has been identified at the base of diatomite deposits at a number of sites and provides firm dating evidence for a widespread flooding event in the area at ca. 2300 BC. The evidence is consistent with other studies in Ireland and elsewhere for increased wetness at this time. The results demonstrate that the terrestrial deposits around Lough Neagh contain an important record of Holocene lake-level change. Dendrochronological evidence from the Lough Neagh area provides additional information about lake-level fluctuations over the past two millennia.

BRCA1 Regulates IFN-γ Signaling through a Mechanism Involving the Type I IFNs

BRCA1 encodes a tumor suppressor gene that is mutated in the germ line of women with a genetic predisposition to breast and ovarian cancer. BRCA1 has been implicated in a number of important cellular functions including DNA damage repair, transcriptional regulation, cell cycle control, and ubiquitination. Using an Affymetrix U95A microarray, IRF-7 was identified as a BRCA1 transcriptional target and was also shown to be synergistically up-regulated by BRCA1 specifically in the presence of IFN-gamma, coincident with the synergistic induction of apoptosis. We show that BRCA1, signal transducer and activator of transcription (STAT)-1, and STAT2 are all required for the induction of IRF-7 following stimulation with IFN-gamma. We also show that the induction of IRF-7 by BRCA1 and IFN-gamma is dependent on the type I IFNs, IFN-alpha and IFN-beta. We show that BRCA1 is required for the up-regulation of STAT1, STAT2, and the type I IFNs in response to IFN-gamma. We show that BRCA1 is localized at the promoters of the molecules involved in type I IFN signaling leading to their up-regulation. Blocking this intermediary type I IFN step using specific antisera shows the requirement for IFN-alpha and IFN-beta in the induction of IRF-7 and apoptosis. Finally, we outline a mechanism for the BRCA1/IFN-gamma regulation of target genes involved in the innate immune response, which is dependent on type I IFN signaling.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.