Molecular study of PKD1 & PKD2 genes by linkage analysis and determining the genotype/phenotype correlations in several Iranian families with autosomal dominant polycystic kidney disease

Background: Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder with genetic heterogeneity. Up to three loci are involved in this disease, PKD1 on chromosome 16p 13.3, PKD2 on 4q21, and a third locus of unknown location. Methods: Here we report the first molecular genetic study of ADPKD and the existence of locus heterogeneity for ADPKD in the Iranian population by performing linkage analysis on 15 affected families. Results: Eleven families showed linkage to PKD1 and two families showed linkage to PKD2. In two families, PKD1 markers are common in all affected members but PKD2 markers were not informative. Conclusion: The results of this study demonstrate significant locus heterogeneity in autosomal dominant PKD in Iran. Analysis of clinical data confirms a milder ADPKD phenotype for PKD2 families. Our results showed relatively high heterozygosity rates and PIC values for some markers, while the most informative markers were KG8 and 16AC2.5 for PKD1 gene and AFM224x6 for PKD2 gene

Hypermethylation of Tumor Suppressor Genes Involved in Critical Regulatory Pathways for Developing a Blood-Based Test in Breast Cancer

Aberrant DNA methylation patterns might be used as a biomarker for diagnosis and management of cancer patients

Mitochondrial DNA Copy Number Is Associated with Breast Cancer Risk

Mitochondrial DNA (mtDNA) copy number in peripheral blood is associated with increased risk of several cancers. However, data from prospective studies on mtDNA copy number and breast cancer risk are lacking. We evaluated the association between mtDNA copy number in peripheral blood and breast cancer risk in a nested case-control study of 183 breast cancer cases with pre-diagnostic blood samples and 529 individually matched controls among participants of the Singapore Chinese Health Study. The mtDNA copy number was measured using real time PCR. Conditional logistic regression analyses showed that there was an overall positive association between mtDNA copy number and breast cancer risk (Ptrend = 0.01). The elevated risk for higher mtDNA copy numbers was primarily seen for women with <3 years between blood draw and cancer diagnosis; ORs (95% CIs) for 2nd, 3rd, 4th, and 5th quintile of mtDNA copy number were 1.52 (0.61, 3.82), 2.52 (1.03, 6.12), 3.12 (1.31, 7.43), and 3.06 (1.25, 7.47), respectively, compared with the 1st quintile (Ptrend = 0.004). There was no association between mtDNA copy number and breast cancer risk among women who donated a blood sample ≥3 years before breast cancer diagnosis (Ptrend = 0.41). This study supports a prospective association between increased mtDNA copy number and breast cancer risk that is dependent on the time interval between blood collection and breast cancer diagnosis. Future studies are warranted to confirm these findings and to elucidate the biological role of mtDNA copy number in breast cancer risk. © 2013 Thyagarajan et al

Hexokinase 3 enhances myeloid cell survival via non-glycolytic functions.

The family of hexokinases (HKs) catalyzes the first step of glycolysis, the ATP-dependent phosphorylation of glucose to glucose-6-phosphate. While HK1 and HK2 are ubiquitously expressed, the less well-studied HK3 is primarily expressed in hematopoietic cells and tissues and is highly upregulated during terminal differentiation of some acute myeloid leukemia (AML) cell line models. Here we show that expression of HK3 is predominantly originating from myeloid cells and that the upregulation of this glycolytic enzyme is not restricted to differentiation of leukemic cells but also occurs during ex vivo myeloid differentiation of healthy CD34+ hematopoietic stem and progenitor cells. Within the hematopoietic system, we show that HK3 is predominantly expressed in cells of myeloid origin. CRISPR/Cas9 mediated gene disruption revealed that loss of HK3 has no effect on glycolytic activity in AML cell lines while knocking out HK2 significantly reduced basal glycolysis and glycolytic capacity. Instead, loss of HK3 but not HK2 led to increased sensitivity to ATRA-induced cell death in AML cell lines. We found that HK3 knockout (HK3-null) AML cells showed an accumulation of reactive oxygen species (ROS) as well as DNA damage during ATRA-induced differentiation. RNA sequencing analysis confirmed pathway enrichment for programmed cell death, oxidative stress, and DNA damage response in HK3-null AML cells. These signatures were confirmed in ATAC sequencing, showing that loss of HK3 leads to changes in chromatin configuration and increases the accessibility of genes involved in apoptosis and stress response. Through isoform-specific pulldowns, we furthermore identified a direct interaction between HK3 and the proapoptotic BCL-2 family member BIM, which has previously been shown to shorten myeloid life span. Our findings provide evidence that HK3 is dispensable for glycolytic activity in AML cells while promoting cell survival, possibly through direct interaction with the BH3-only protein BIM during ATRA-induced neutrophil differentiation

Detector Fabrication Yield for SuperCDMS Soudan

The SuperCDMS collaboration is presently operating a 9 kg Ge payload at the Soudan Underground Laboratory in their direct search for dark matter. The Ge detectors utilize double-sided athermal phonon sensors with an interdigitated electrode structure (iZIPs) to reject near-surface electron-recoil events. These detectors each have a mass of 0.6 kg and were fabricated with photolithographic techniques. The detector fabrication advances required and the production yield encountered are described.United States. Dept. of EnergyNational Science Foundation (U.S.

Do Two Machine-Learning Based Prognostic Signatures for Breast Cancer Capture the Same Biological Processes?

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question

Demonstration of surface electron rejection with interleaved germanium detectors for dark matter searches

The SuperCDMS experiment in the Soudan Underground Laboratory searches for dark matter with a 9-kg array of cryogenic germanium detectors. Symmetric sensors on opposite sides measure both charge and phonons from each particle interaction, providing excellent discrimination between electron and nuclear recoils, and between surface and interior events. Surface event rejection capabilities were tested with two 210 Pb sources producing ∼130 beta decays/hr. In ∼800 live hours, no events leaked into the 8–115 keV signal region, giving upper limit leakage fraction 1.7 × 10−5 at 90% C.L., corresponding to < 0.6 surface event background in the future 200-kg SuperCDMS SNOLAB experiment

Demonstration of surface electron rejection with interleaved germanium detectors for dark matter searches

The following article appeared in Applied Physics Letters 103.16 (2013): 164105 and may be found at http://scitation.aip.org/content/aip/journal/apl/100/26/10.1063/1.4729825The SuperCDMS experiment in the Soudan Underground Laboratory searches for dark matter with a 9-kg array of cryogenic germanium detectors. Symmetric sensors on opposite sides measure both charge and phonons from each particle interaction, providing excellent discrimination between electron and nuclear recoils, and between surface and interior events. Surface event rejection capabilities were tested with two 210 Pb sources producing ∼130 beta decays/hr. In ∼800 live hours, no events leaked into the 8–115 keV signal region, giving upper limit leakage fraction 1.7 × 10−5 at 90% C.L., corresponding to < 0.6 surface event background in the future 200-kg SuperCDMS SNOLAB experiment.This work is supported in part by the National Science Foundation (Grant Nos. AST-9978911, NSF-0847342, PHY-1102795,NSF-1151869, PHY-0542066, PHY-0503729, PHY-0503629, PHY-0503641, PHY-0504224, PHY-0705052,PHY-0801708, PHY-0801712, PHY-0802575, PHY-0847342, PHY-0855299, PHY-0855525, and PHY-1205898), by the Department of Energy (Contract Nos. DE-AC03-76SF00098, DE-FG02-92ER40701, DE-FG02-94ER40823,DE-FG03-90ER40569, DE-FG03-91ER40618, and DESC0004022),by NSERC Canada (Grant Nos. SAPIN 341314 and SAPPJ 386399), and by MULTIDARK CSD2009-00064 and FPA2012-34694. Fermilab is operated by Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359, while SLAC is operated under Contract No. DE-AC02-76SF00515 with the United States Department of Energy

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations