Conductance of a spin-1 quantum dot: the two-stage Kondo effect

We discuss the physics of a of a spin-1 quantum dot, coupled to two metallic leads and develop a simple model for the temperature dependence of its conductance. Such quantum dots are described by a two-channel Kondo model with asymmetric coupling constants and the spin screening of the dot by the leads is expected to proceed via a two-stage process. When the Kondo temperatures of each channel are widely separated, on cooling, the dot passes through a broad cross-over regime dominated by underscreened Kondo physics. A singular, or non-fermi liquid correction to the conductance develops in this regime. At the lowest temperatures, destructive interference between resonant scattering in both channels leads to the eventual suppression of the conductance of the dot. We develop a model to describe the growth, and ultimate suppression of the conductance in the two channel Kondo model as it is screened successively by its two channels. Our model is based upon large-N approximation in which the localized spin degrees of freedom are described using the Schwinger boson formalism.Comment: 16 pages, 10 figure

Causal network inference using biochemical kinetics

Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in nonlinear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. © The Author 2014. Published by Oxford University Press

Haptoglobin frequencies in Jewish communities *

Haptoglobin and transferrin types have been determined by starch gel electrophoresis on blood from 929 subjects belonging to various Jewish communities. The frequency of the Hp 1 gene in 499 Ashkenazic Jews is 0.29 and does not differ significantly from the value of 0–26 found in 345 Jews of Oriental origin. The Hp 1 frequency of Ashkenazic Jews is significantly lower than that reported for the autochthonous populations of Central and Western Europe. Two small samples collected among Sephardic Jews and among the offspring of intercommunity marriages exhibit somewhat higher frequencies of the Hp 1 gene. The modified 2-1 phenotype was found in a single subject from Baghdad. There were three cases of ahaptoglobinaemia among Ashkenazic Jews and three among the Oriental groups. No ahaptoglobinaemia was discovered in a family sample of ninety-two Jews from Kurdistan among whom thalassaemia minor was common and the majority of whom were affeeted with G-6-P-D deficiency. All transferrins were of type C.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66130/1/j.1469-1809.1962.tb01307.x.pd

Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training.

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational "modelling" of test results using published algorithms and secondly a "training" approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a "modelling" approach without reference to real world test results. Simultaneously we show that a "training" approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results

Kallikrein-related peptidase 6 regulates epithelial-to-mesenchymal transition and serves as prognostic biomarker for head and neck squamous cell carcinoma patients

Background: Dysregulated expression of Kallikrein-related peptidase 6 (KLK6) is a common feature for many human malignancies and numerous studies evaluated KLK6 as a promising biomarker for early diagnosis or unfavorable prognosis. However, the expression of KLK6 in carcinomas derived from mucosal epithelia, including head and neck squamous cell carcinoma (HNSCC), and its mode of action has not been addressed so far. Methods: Stable clones of human mucosal tumor cell lines were generated with shRNA-mediated silencing or ectopic overexpression to characterize the impact of KLK6 on tumor relevant processes in vitro. Tissue microarrays with primary HNSCC samples from a retrospective patient cohort (n = 162) were stained by immunohistochemistry and the correlation between KLK6 staining and survival was addressed by univariate Kaplan-Meier and multivariate Cox proportional hazard model analysis. Results: KLK6 expression was detected in head and neck tumor cell lines (FaDu, Cal27 and SCC25), but not in HeLa cervix carcinoma cells. Silencing in FaDu cells and ectopic expression in HeLa cells unraveled an inhibitory function of KLK6 on tumor cell proliferation and mobility. FaDu clones with silenced KLK6 expression displayed molecular features resembling epithelial-to-mesenchymal transition, nuclear β-catenin accumulation and higher resistance against irradiation. Low KLK6 protein expression in primary tumors from oropharyngeal and laryngeal SCC patients was significantly correlated with poor progression-free (p = 0.001) and overall survival (p < 0.0005), and served as an independent risk factor for unfavorable clinical outcome. Conclusions: In summary, detection of low KLK6 expression in primary tumors represents a promising tool to stratify HNSCC patients with high risk for treatment failure. These patients might benefit from restoration of KLK6 expression or pharmacological targeting of signaling pathways implicated in EMT

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer

In Vitro Analysis of Integrated Global High-Resolution DNA Methylation Profiling with Genomic Imbalance and Gene Expression in Osteosarcoma

Genetic and epigenetic changes contribute to deregulation of gene expression and development of human cancer. Changes in DNA methylation are key epigenetic factors regulating gene expression and genomic stability. Recent progress in microarray technologies resulted in developments of high resolution platforms for profiling of genetic, epigenetic and gene expression changes. OS is a pediatric bone tumor with characteristically high level of numerical and structural chromosomal changes. Furthermore, little is known about DNA methylation changes in OS. Our objective was to develop an integrative approach for analysis of high-resolution epigenomic, genomic, and gene expression profiles in order to identify functional epi/genomic differences between OS cell lines and normal human osteoblasts. A combination of Affymetrix Promoter Tilling Arrays for DNA methylation, Agilent array-CGH platform for genomic imbalance and Affymetrix Gene 1.0 platform for gene expression analysis was used. As a result, an integrative high-resolution approach for interrogation of genome-wide tumour-specific changes in DNA methylation was developed. This approach was used to provide the first genomic DNA methylation maps, and to identify and validate genes with aberrant DNA methylation in OS cell lines. This first integrative analysis of global cancer-related changes in DNA methylation, genomic imbalance, and gene expression has provided comprehensive evidence of the cumulative roles of epigenetic and genetic mechanisms in deregulation of gene expression networks

Multimodal Biomarkers That Predict the Presence of Gleason Pattern 4: Potential Impact for Active Surveillance

AbstractPurpose:Latent grade group ≥2 prostate cancer can impact the performance of active surveillance protocols. To date, molecular biomarkers for active surveillance have relied solely on RNA or protein. We trained and independently validated multimodal (mRNA abundance, DNA methylation, and/or DNA copy number) biomarkers that more accurately separate grade group 1 from grade group ≥2 cancers.Materials and Methods:Low- and intermediate-risk prostate cancer patients were assigned to training (n=333) and validation (n=202) cohorts. We profiled the abundance of 342 mRNAs, 100 DNA copy number alteration loci, and 14 hypermethylation sites at 2 locations per tumor. Using the training cohort with cross-validation, we evaluated methods for training classifiers of pathological grade group ≥2 in centrally reviewed radical prostatectomies. We trained 2 distinct classifiers, PRONTO-e and PRONTO-m, and validated them in an independent radical prostatectomy cohort.Results:PRONTO-e comprises 353 mRNA and copy number alteration features. PRONTO-m includes 94 clinical, mRNAs, copy number alterations, and methylation features at 14 and 12 loci, respectively. In independent validation, PRONTO-e and PRONTO-m predicted grade group ≥2 with respective true-positive rates of 0.81 and 0.76, and false-positive rates of 0.43 and 0.26. Both classifiers were resistant to sampling error and identified more upgrading cases than a well-validated presurgical risk calculator, CAPRA (Cancer of the Prostate Risk Assessment; P &lt; .001).Conclusions:Two grade group classifiers with superior accuracy were developed by incorporating RNA and DNA features and validated in an independent cohort. Upon further validation in biopsy samples, classifiers with these performance characteristics could refine selection of men for active surveillance, extending their treatment-free survival and intervals between surveillance.Active surveillance (AS) is recommended for men with low- and favorable intermediate–risk prostate cancer.1 Compared to AS for low-risk men, AS for intermediate-risk men would likely benefit from more intensive surveillance to stave off disease progression. Despite increased use of advanced imaging tools, risk calculators, and molecular biomarkers, a third or more of men initially classified as low risk actually have intermediate or higher risk, heralded by subsequent detection of occult Gleason pattern 4.2,3 Strategies to identify such men have limited accuracy. They include attention to traditional risk factors such as age, tumor size and extent, and PSA level, measured by tests such as digital rectal examination, multiparametric (mp) MRI, and biopsy and blood analyses. Despite its increasing use in prostate cancer risk assessment, expert prostate mpMRI is a limited resource with low (circa 59%) sensitivity for intermediate-risk cases.4 A biomarker that more accurately distinguishes between grade group (GG) 1 and GG ≥2 could be helpful in deintensifying AS for men with truly low-risk cancers.Several commercially available and guideline-approved tests use gene (mRNA or protein) expression levels in prostate cancer biopsies to detect adverse pathology (AP; ie, GG ≥3 or nonorgan-confined disease) in the subsequent prostatectomy. However, no existing molecular test has been adopted in current guidelines as standard of care to distinguish between GG1 and GG ≥2 cancers.1,5,6 Despite indications that such tests could be useful,6,7 uptake has been limited, perhaps because of low accuracy, which in turn may derive from limitations in the number and types of molecular features included in each test. Since cardinal molecular features of early prostate carcinogenesis include not only altered gene expression but also DNA methylation events and copy number alterations (CNAs),8-10 we hypothesized that tests combining these features could provide superior performance in separating low-grade (GG1) cancers from their higher-grade (GG ≥2) counterparts.The personalized risk stratification for patients with early prostate cancer (PRONTO) program is a pan-Canadian effort that aims to develop a GG classifier to stratify risk in prostate cancer and achieve technical and clinical validation in statistically powered cohorts. Here, we report the development of 2 candidate classifiers comprising different types of molecular features. These classifiers, developed and independently validated, achieve superior performance by integrating tumor mRNA abundance, DNA copy number, and/or DNA methylation profiles. We demonstrate that these classifiers could add value above and beyond routinely captured clinical data and are remarkably resistant to sampling error. We discuss how adoption of classifiers with these attributes has the potential to improve current AS approaches without increasing patient morbidity. By identifying men at increased risk of occult GG ≥2 cancer, surveillance biopsies could be taken earlier to confirm the presence and extent of Gleason pattern 4 cancer. By confirming GG1 cancers, such biomarkers could identify men for whom it would be safe to forgo MRI or increase the intervals between surveillance biopsies, reducing burdens on health care systems and patients

Appreciation of 2017 GRL Peer Reviewers

On behalf of the journal, AGU, and the scientific community, the Editors would like to sincerely thank those who reviewed manuscripts for Geophysical Research Letters in 2017. The hours reading and commenting on manuscripts not only improves the manuscripts, but increases the scientific rigor of future research in the field. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics. The refereeing contributions they made contributed to 6,553 individual reviews of 2,782 manuscripts. Thank you again. We look forward to the coming year of exciting advances in the field and communicating those advances to our community and to the broader public

Chemical diplomacy in male tilapia: urinary signal increases sex hormone and decreases aggression

Androgens, namely 11-ketotestosterone (11KT), have a central role in male fish reproductive physiology and are thought to be involved in both aggression and social signalling. Aggressive encounters occur frequently in social species, and fights may cause energy depletion, injury and loss of social status. Signalling for social dominance and fighting ability in an agonistic context can minimize these costs. Here, we test the hypothesis of a 'chemical diplomacy' mechanism through urinary signals that avoids aggression and evokes an androgen response in receiver males of Mozambique tilapia (Oreochromis mossambicus). We show a decoupling between aggression and the androgen response; males fighting their mirror image experience an unresolved interaction and a severe drop in urinary 11KT. However, if concurrently exposed to dominant male urine, aggression drops but urinary 11KT levels remain high. Furthermore, 11KT increases in males exposed to dominant male urine in the absence of a visual stimulus. The use of a urinary signal to lower aggression may be an adaptive mechanism to resolve disputes and avoid the costs of fighting. As dominance is linked to nest building and mating with females, the 11KT response of subordinate males suggests chemical eavesdropping, possibly in preparation for parasitic fertilizations.info:eu-repo/semantics/publishedVersio