We investigated the subfossil chironomid fauna of 150 lakes situated in Yakutia, northeastern Russia. The objective of this study was to assess the relationship between chironomid assemblage composition and the environment and to develop chironomid inference models for quantifying past regional climate and environmental changes in this poorly investigated area of northern Russia. The environmental data and sediment samples for chironomid analysis were collected in 5 consecutive years, [2003][2004][2005][2006][2007], from several regions of Yakutia. The lakes spanned wide latitudinal and longitudinal ranges and were distributed through several environmental zones (arctic tundra, typical tundra, steppetundra, boreal coniferous forest), but all were situated within the zone of continuous permafrost. Mean July temperature (T July ) varied from 3.4°C in the Laptev Sea region to 18.8°C in central Yakutia near Yakutsk. Water depth (WD) varied from 0.1 to 17.1 m. T July and WD were identified as the strongest predictor variables explaining the chironomid communitiy composition and distribution of the taxa in our data set. Quantitative transfer functions were developed using two unimodal regression calibration techniques: simple weighted averaging (WA) and weighted averaging partial least squares (WA-PLS). The two-component T July WA-PLS model had the best performance. It produced a strong coefficient of determination (r 2 boot = 0.87), root mean square error of prediction (RMSEP = 1.93), and max bias (max bias boot = 2.17). For WD, the one-component WA-PLS model had the best performance (r 2 boot = 0.62, RMSEP = 0.35, max bias boot = 0.47).

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The analysis of spatial variability of lake sediment properties in Lake Lama, Central Siberia is presented. The aims were to characterize the spatial structure in lake sediment composition, to determine major spatial patterns of sediment properties by calculating estimates at locations where no samples were available, and to assess the main processes determining these patterns. Sediment properties were measured at 71 spatially distributed locations in the lake, comprising particle size distribution, biogeochemical properties such as total organic carbon, total nitrogen or stable carbon isotopes, as well as geochemical distribution of major and trace elements. Spatial analysis consisted of a principal components analysis and, subsequently, calculation and modelling of variograms to describe the spatial structure in the data as well as determination of spatial estimates using block-kriging to map spatial structure. The results showed that particle Aquat. Sci. 67 (2005) 86 -96 Aquatic Sciences size, biogenic silica, CaO, d 13 C org , Zr and TOC/TN ratio were a major source of variability in sediment properties and, thus, dominate the sediment structure in Lake Lama. Major anomalies occurred near river inlets, depending on river size and its position as well as slope of the river bed. Other anomalies were associated with water depths, morphology of the lake basins, and wind-induced currents and re-suspension in the shallow part of the western basin. The spatial structure in sediment properties indicate that several processes act at different spatial scales. Moreover, there was a considerable amount of smallscale variability that could not be quantified due to sampling design. The results showed that heterogeneity in lake sediment composition is a main characteristic of large lake systems, and must be taken into account, especially in paleolimnological and environmental applications.

Background Identification of predictive clinical factors of long-term treatment response may contribute to improved management of non-radiographic axSpA (nr-axSpA) patients. This analysis aims to identify whether any baseline characteristics or Week 12 clinical outcomes in nr-axSpA patients with elevated C-reactive protein (CRP) and/or sacroiliitis on magnetic resonance imaging (MRI) enrolled in the C-axSpAnd study are predictive of achieving clinical response after 1 year of certolizumab pegol (CZP). Methods C-axSpAnd (NCT02552212) was a phase 3, multicentre study, including a 52-Week double-blind, placebo-controlled period. Enrolled patients were randomised to CZP 200 mg Q2W or placebo. Predictors of Week 12 (CZP group only) and Week 52 clinical response were identified using a multivariate stepwise logistic regression analysis. Response variables included Ankylosing Spondylitis Disease Activity Score major improvement (ASDAS-MI), Assessment of SpondyloArthritis International Society 40% response (ASAS40), Bath Ankylosing Spondylitis Disease Activity Index 50% response (BASDAI50) and ASDAS inactive disease (ASDAS-ID). Predictive factors assessed included demographic and baseline characteristics and clinical outcomes at Week 12. A p-value <0.05 was required for forward selection into the model and p ≥0.1 for backward elimination. Missing data or values collected after switching to open-label treatment were accounted for using non-responder imputation. Sensitivity analyses accounted for patients with changes in non-biologic background medication. Results Of 317 enrolled patients, 159 and 158 were randomised to CZP and placebo, respectively. Younger age and male sex were identified as predictors of Week 12 response across all assessed efficacy outcomes in CZP-treated patients. Consistent predictors of Week 52 response, measured by ASDAS-MI, ASAS40 and BASDAI50, included human leukocyte antigen (HLA)-B27 positivity and sacroiliitis on MRI at baseline. MRI positivity was also predictive of achieving ASDAS-ID at Week 52. Sensitivity analyses were generally consistent with the primary analysis. In placebo-treated patients, no meaningful predictors of Week 52 response were identified. Conclusions In this 52-Week, placebo-controlled study in nr-axSpA patients with elevated CRP and/or active sacroiliitis on MRI at baseline, MRI sacroiliitis and HLA-B27 positivity, but not elevated CRP or responses at Week 12, were predictive of long-term clinical response to CZP. Findings may support rheumatologists to identify patients suitable for TNFi treatment. Trial registration ClinicalTrials.gov, NCT02552212. Registered on 15 September 2015