Reliable gene expression measurements from degraded RNA by quantitative real-time PCR depend on short amplicons and a proper normalization

Quantitative reverse transcriptase real-time PCR (QRT-PCR) is a robust method to quantitate RNA abundance. The procedure is highly sensitive and reproducible as long as the initial RNA is intact. However, breaks in the RNA due to chemical or enzymatic cleavage may reduce the number of RNA molecules that contain intact amplicons. As a consequence, the number of molecules available for amplification decreases. We determined the relation between RNA fragmentation and threshold values (Ct values) in subsequent QRT-PCR for four genes in an experimental model of intact and partially hydrolyzed RNA derived from a cell line and we describe the relation between RNA integrity, amplicon size and Ct values in this biologically homogenous system. We demonstrate that degradation-related shifts of Ct values can be compensated by calculating delta Ct values between test genes and the mean values of several control genes. These delta Ct values are less sensitive to fragmentation of the RNA and are unaffected by varying amounts of input RNA. The feasibility of the procedure was demonstrated by comparing Ct values from a larger panel of genes in intact and in partially degraded RNA. We compared Ct values from intact RNA derived from well-preserved tumor material and from fragmented RNA derived from formalin-fixed, paraffin-embedded (FFPE) samples of the same tumors. We demonstrate that the relative abundance of gene expression can be based on FFPE material even when the amount of RNA in the sample and the extent of fragmentation are not known.

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^

Time series of black carbon aerosol measurements from Neumayer Station, 1999-2011

Continuous black carbon (BC) observations were conducted from 1999 through 2009 by an Aethalometer (AE10) and from 2006 through 2011 by a Multi-Angle Absorption Photometer (MAAP) at Neumayer Station (NM) under stringent contamination control. Considering the respective observation period, BC concentrations measured by the MAAP were somewhat higher (median ± standard deviation: 2.1 ± 2.0 ng/m**3) compared to the AE10 results (1.6 ± 2.1 ng/m**3). Neither for the AE10 nor for the MAAP data set a significant long-term trend could be detected. Consistently a pronounced seasonality was observed with both instruments showing a primary annual maximum between October and November and a minimum in April with a maximum/minimum ratio of 4.5/1.6 = 3.8 and 2.7/0.64 = 4.2 for the MAAP and AE10 data, respectively. Occasionally a secondary summer maximum in January/February was visible. With the aim to assess the impact of BC on optical properties of the aerosol at NM, we evaluated the BC data along with particle scattering coefficients measured by an integrating nephelometer. We found the mean single scattering albedo of w550 = 0.992 ± 0.0090 (median: 0.994) at a wavelength of 550 nm with a range of values from 0.95 to 1.0.