A multi-dating approach to age-modelling long continental records: The 135 ka El Cañizar de Villarquemado sequence (NE Spain)

We present the multidisciplinary dating approach - including radiocarbon, Uranium/Thorium series (U/Th), paleomagnetism, single-grain Optical Stimulated Luminescence (OSL), Infrared Stimulated Luminescence (IRSL) and tephrochronology - used for the development of an age model for the Cañizar de Villarquemado sequence (VIL) for the last ca. 135 ka. We describe the protocols used for each technique and discuss the positive and negative results, as well as their implications for interpreting the VIL sequence and for dating similar terrestrial records. In spite of the negative results of some techniques, particularly due to the absence of adequate sample material or inaccurate analytical precision, the multi-technique strategy employed here is essential to maximize the chances of obtaining robust age models in terrestrial sequences. The final Bayesian age model for VIL sequence includes 16 AMS 14C ages, 9 OSL ages and 5 previously published IRSL ages, and the accuracy and resolution of the model are improved by incorporating information related to changes in accumulation rate, as revealed by detailed sedimentological analyses. The main paleohydrological and vegetation changes in the sequence are coherent with global Marine Isotope Stage (MIS) 6 to 1 transitions since the penultimate Termination, although some regional idiosyncrasies are evident, such as higher moisture variability than expected, an abrupt inception of the last glacial cycle and a resilient response of vegetation in Mediterranean continental Iberia in both Terminations

Indisulam targets RNA splicing and metabolism to serve as a therapeutic strategy for high-risk neuroblastoma

Neuroblastoma is the most common paediatric solid tumour and prognosis remains poor for high-risk cases despite the use of multimodal treatment. Analysis of public drug sensitivity data showed neuroblastoma lines to be sensitive to indisulam, a molecular glue that selectively targets RNA splicing factor RBM39 for proteosomal degradation via DCAF15-E3-ubiquitin ligase. In neuroblastoma models, indisulam induces rapid loss of RBM39, accumulation of splicing errors and growth inhibition in a DCAF15-dependent manner. Integrative analysis of RNAseq and proteomics data highlight a distinct disruption to cell cycle and metabolism. Metabolic profiling demonstrates metabolome perturbations and mitochondrial dysfunction resulting from indisulam. Complete tumour regression without relapse was observed in both xenograft and the Th-MYCN transgenic model of neuroblastoma after indisulam treatment, with RBM39 loss, RNA splicing and metabolic changes confirmed in vivo. Our data show that dual-targeting of metabolism and RNA splicing with anticancer indisulam is a promising therapeutic approach for high-risk neuroblastoma

A few StePS forward in unveiling the complexity of galaxy evolution: Light-weighted stellar ages of intermediate-redshift galaxies with WEAVE

The upcoming new generation of optical spectrographs on four-meter-class telescopes will provide invaluable information for reconstructing the history of star formation in individual galaxies up to redshifts of about 0.7. We aim at defining simple but robust and meaningful physical parameters that can be used to trace the coexistence of widely diverse stellar components: younger stellar populations superimposed on the bulk of older ones. We produce spectra of galaxies closely mimicking data from the forthcoming Stellar Populations at intermediate redshifts Survey (StePS), a survey that uses the WEAVE spectrograph on the William Herschel Telescope. First, we assess our ability to reliably measure both ultraviolet and optical spectral indices in galaxies of different spectral types for typically expected signal-to-noise levels. Then, we analyze such mock spectra with a Bayesian approach, deriving the probability density function of r- and u-band light-weighted ages as well as of their difference. We find that the ultraviolet indices significantly narrow the uncertainties in estimating the r- and u-band light-weighted ages and their difference in individual galaxies. These diagnostics, robustly retrievable for large galaxy samples even when observed at moderate signal-to-noise ratios, allow us to identify secondary episodes of star formation up to an age of ~0.1 Gyr for stellar populations older than ~1.5 Gyr, pushing up to an age of ~1 Gyr for stellar populations older than ~5 Gyr. The difference between r-band and u-band light-weighted ages is shown to be a powerful diagnostic to characterize and constrain extended star-formation histories and the presence of young stellar populations on top of older ones. This parameter can be used to explore the interplay between different galaxy star-formation histories and physical parameters such as galaxy mass, size, morphology, and environment

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

Identification of SERPINA1 as single marker for papillary thyroid carcinoma through microarray meta analysis and quantification of its discriminatory power in independent validation

<p>Abstract</p> <p>Background</p> <p>Several DNA microarray based expression signatures for the different clinically relevant thyroid tumor entities have been described over the past few years. However, reproducibility of these signatures is generally low, mainly due to study biases, small sample sizes and the highly multivariate nature of microarrays. While there are new technologies available for a more accurate high throughput expression analysis, we show that there is still a lot of information to be gained from data deposited in public microarray databases. In this study we were aiming (1) to identify potential markers for papillary thyroid carcinomas through meta analysis of public microarray data and (2) to confirm these markers in an independent dataset using an independent technology.</p> <p>Methods</p> <p>We adopted a meta analysis approach for four publicly available microarray datasets on papillary thyroid carcinoma (PTC) nodules versus nodular goitre (NG) from N2-frozen tissue. The methodology included merging of datasets, bias removal using distance weighted discrimination (DWD), feature selection/inference statistics, classification/crossvalidation and gene set enrichment analysis (GSEA). External Validation was performed on an independent dataset using an independent technology, quantitative RT-PCR (RT-qPCR) in our laboratory.</p> <p>Results</p> <p>From meta analysis we identified one gene (SERPINA1) which identifies papillary thyroid carcinoma against benign nodules with 99% accuracy (n = 99, sensitivity = 0.98, specificity = 1, PPV = 1, NPV = 0.98). In the independent validation data, which included not only PTC and NG, but all major histological thyroid entities plus a few variants, SERPINA1 was again markedly up regulated (36-fold, p = 1:3*10^-10) in PTC and identification of papillary carcinoma was possible with 93% accuracy (n = 82, sensitivity = 1, specificity = 0.90, PPV = 0.76, NPV = 1). We also show that the extracellular matrix pathway is strongly activated in the meta analysis data, suggesting an important role of tumor-stroma interaction in the carcinogenesis of papillary thyroid carcinoma.</p> <p>Conclusions</p> <p>We show that valuable new information can be gained from meta analysis of existing microarray data deposited in public repositories. While single microarray studies rarely exhibit a sample number which allows robust feature selection, this can be achieved by combining published data using DWD. This approach is not only efficient, but also very cost-effective. Independent validation shows the validity of the results from this meta analysis and confirms SERPINA1 as a potent mRNA marker for PTC in a total (meta analysis plus validation) of 181 samples.</p

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

<p>Abstract</p> <p>Background</p> <p>Genome-wide methylation profiling has led to more comprehensive insights into gene regulation mechanisms and potential therapeutic targets. Illumina Human Methylation BeadChip is one of the most commonly used genome-wide methylation platforms. Similar to other microarray experiments, methylation data is susceptible to various technical artifacts, particularly batch effects. To date, little attention has been given to issues related to normalization and batch effect correction for this kind of data.</p> <p>Methods</p> <p>We evaluated three common normalization approaches and investigated their performance in batch effect removal using three datasets with different degrees of batch effects generated from HumanMethylation27 platform: quantile normalization at average β value (QNβ); two step quantile normalization at probe signals implemented in "lumi" package of R (lumi); and quantile normalization of A and B signal separately (ABnorm). Subsequent Empirical Bayes (EB) batch adjustment was also evaluated.</p> <p>Results</p> <p>Each normalization could remove a portion of batch effects and their effectiveness differed depending on the severity of batch effects in a dataset. For the dataset with minor batch effects (Dataset 1), normalization alone appeared adequate and "lumi" showed the best performance. However, all methods left substantial batch effects intact in the datasets with obvious batch effects and further correction was necessary. Without any correction, 50 and 66 percent of CpGs were associated with batch effects in Dataset 2 and 3, respectively. After QNβ, lumi or ABnorm, the number of CpGs associated with batch effects were reduced to 24, 32, and 26 percent for Dataset 2; and 37, 46, and 35 percent for Dataset 3, respectively. Additional EB correction effectively removed such remaining non-biological effects. More importantly, the two-step procedure almost tripled the numbers of CpGs associated with the outcome of interest for the two datasets.</p> <p>Conclusion</p> <p>Genome-wide methylation data from Infinium Methylation BeadChip can be susceptible to batch effects with profound impacts on downstream analyses and conclusions. Normalization can reduce part but not all batch effects. EB correction along with normalization is recommended for effective batch effect removal.</p

Chronic kidney disease in the type 2 diabetic patients: prevalence and associated variables in a random sample of 2642 patients of a Mediterranean area

Background: Kidney disease is associated with an increased total mortality and cardiovascular morbimortality in the general population and in patients with Type 2 diabetes. The aim of this study is to determine the prevalence of kidney disease and different types of renal disease in patients with type 2 diabetes (T2DM). Methods: Cross-sectional study in a random sample of 2,642 T2DM patients cared for in primary care during 2007. Studied variables: demographic and clinical characteristics, pharmacological treatments and T2DM complications (diabetic foot, retinopathy, coronary heart disease and stroke). Variables of renal function were defined as follows: 1) Microalbuminuria: albumin excretion rate & 30 mg/g or 3.5 mg/mmol, 2) Macroalbuminuria: albumin excretion rate & 300 mg/g or 35 mg/mmol, 3) Kidney disease (KD): glomerular filtration rate according to Modification of Diet in Renal Disease < 60 ml/min/1.73 m2 and/or the presence of albuminuria, 4) Renal impairment (RI): glomerular filtration rate < 60 ml/min/1.73 m2, 5) Nonalbuminuric RI: glomerular filtration rate < 60 ml/min/1.73 m2 without albuminuria and, 5) Diabetic nephropathy (DN): macroalbuminuria or microalbuminuria plus diabetic retinopathy. Results: The prevalence of different types of renal disease in patients was: 34.1% KD, 22.9% RI, 19.5% albuminuria and 16.4% diabetic nephropathy (DN). The prevalence of albuminuria without RI (13.5%) and nonalbuminuric RI (14.7%) was similar. After adjusting per age, BMI, cholesterol, blood pressure and macrovascular disease, RI was significantly associated with the female gender (OR 2.20; CI 95% 1.86-2.59), microvascular disease (OR 2.14; CI 95% 1.8-2.54) and insulin treatment (OR 1.82; CI 95% 1.39-2.38), and inversely associated with HbA1c (OR 0.85 for every 1% increase; CI 95% 0.80-0.91). Albuminuria without RI was inversely associated with the female gender (OR 0.27; CI 95% 0.21-0.35), duration of diabetes (OR 0.94 per year; CI 95% 0.91-0.97) and directly associated with HbA1c (OR 1.19 for every 1% increase; CI 95% 1.09-1.3). Conclusions: One-third of the sample population in this study has KD. The presence or absence of albuminuria identifies two subgroups with different characteristics related to gender, the duration of diabetes and metabolic status of the patient. It is important to determine both albuminuria and GFR estimation to diagnose KD

Alcohol-related brain damage in humans

Chronic excessive alcohol intoxications evoke cumulative damage to tissues and organs. We examined prefrontal cortex (Brodmann’s area (BA) 9) from 20 human alcoholics and 20 age, gender, and postmortem delay matched control subjects. H & E staining and light microscopy of prefrontal cortex tissue revealed a reduction in the levels of cytoskeleton surrounding the nuclei of cortical and subcortical neurons, and a disruption of subcortical neuron patterning in alcoholic subjects. BA 9 tissue homogenisation and one dimensional polyacrylamide gel electrophoresis (PAGE) proteomics of cytosolic proteins identified dramatic reductions in the protein levels of spectrin β II, and α- and β-tubulins in alcoholics, and these were validated and quantitated by Western blotting. We detected a significant increase in α-tubulin acetylation in alcoholics, a non-significant increase in isoaspartate protein damage, but a significant increase in protein isoaspartyl methyltransferase protein levels, the enzyme that triggers isoaspartate damage repair in vivo. There was also a significant reduction in proteasome activity in alcoholics. One dimensional PAGE of membrane-enriched fractions detected a reduction in β-spectrin protein levels, and a significant increase in transmembranous α3 (catalytic) subunit of the Na+,K+-ATPase in alcoholic subjects. However, control subjects retained stable oligomeric forms of α-subunit that were diminished in alcoholics. In alcoholics, significant loss of cytosolic α- and β-tubulins were also seen in caudate nucleus, hippocampus and cerebellum, but to different levels, indicative of brain regional susceptibility to alcohol-related damage. Collectively, these protein changes provide a molecular basis for some of the neuronal and behavioural abnormalities attributed to alcoholics

pKa Modulation of the Acid/Base Catalyst within GH32 and GH68: A Role in Substrate/Inhibitor Specificity?

Glycoside hydrolases of families 32 (GH32) and 68 (GH68) belong to clan GH-J, containing hydrolytic enzymes (sucrose/fructans as donor substrates) and fructosyltransferases (sucrose/fructans as donor and acceptor substrates). In GH32 members, some of the sugar substrates can also function as inhibitors, this regulatory aspect further adding to the complexity in enzyme functionalities within this family. Although 3D structural information becomes increasingly available within this clan and huge progress has been made on structure-function relationships, it is not clear why some sugars bind as inhibitors without being catalyzed. Conserved aspartate and glutamate residues are well known to act as nucleophile and acid/bases within this clan. Based on the available 3D structures of enzymes and enzyme-ligand complexes as well as docking simulations, we calculated the pKa of the acid-base before and after substrate binding. The obtained results strongly suggest that most GH-J members show an acid-base catalyst that is not sufficiently protonated before ligand entrance, while the acid-base can be fully protonated when a substrate, but not an inhibitor, enters the catalytic pocket. This provides a new mechanistic insight aiming at understanding the complex substrate and inhibitor specificities observed within the GH-J clan. Moreover, besides the effect of substrate entrance on its own, we strongly suggest that a highly conserved arginine residue (in the RDP motif) rather than the previously proposed Tyr motif (not conserved) provides the proton to increase the pKa of the acid-base catalyst