Private quantum decoupling and secure disposal of information

Given a bipartite system, correlations between its subsystems can be understood as information that each one carries about the other. In order to give a model-independent description of secure information disposal, we propose the paradigm of private quantum decoupling, corresponding to locally reducing correlations in a given bipartite quantum state without transferring them to the environment. In this framework, the concept of private local randomness naturally arises as a resource, and total correlations get divided into eliminable and ineliminable ones. We prove upper and lower bounds on the amount of ineliminable correlations present in an arbitrary bipartite state, and show that, in tripartite pure states, ineliminable correlations satisfy a monogamy constraint, making apparent their quantum nature. A relation with entanglement theory is provided by showing that ineliminable correlations constitute an entanglement parameter. In the limit of infinitely many copies of the initial state provided, we compute the regularized ineliminable correlations to be measured by the coherent information, which is thus equipped with a new operational interpretation. In particular, our results imply that two subsystems can be privately decoupled if their joint state is separable.Comment: Child of 0807.3594 v2: minor changes v3: presentation improved, one figure added v4: extended version with a lot of discussions and examples v5: published versio

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

Discrepancies between transcutaneous and estimated glomerular filtration rates in rats with chronic kidney disease

Accurate assessment of the glomerular filtration rate (GFR) is crucial for researching kidney disease in rats. Although validation of methods that assess GFR is crucial, large-scale comparisons between different methods are lacking. Both transcutaneous GFR (tGFR) and a newly developed estimated GFR (eGFR) equation by our group provide a low-invasive approach enabling repeated measurements. The tGFR is a single bolus method using FITC-labeled sinistrin to measure GFR based on half-life of the transcutaneous signal, whilst the eGFR is based on urinary sinistrin clearance. Here, we retrospectively compared tGFR, using both 1- and 3- compartment models (tGFR_1c and tGFR_3c, respectively) to the eGFR in a historic cohort of 43 healthy male rats and 84 male rats with various models of chronic kidney disease. The eGFR was on average considerably lower than tGFR-1c and tGFR-3c (mean differences 855 and 216 μL/min, respectively) and only 20 and 47% of measurements were within 30% of each other, respectively. The relative difference between eGFR and tGFR was highest in rats with the lowest GFR. Possible explanations for the divergence are problems inherent to tGFR, such as technical issues with signal measurement, description of the signal kinetics, and translation of half-life to tGFR, which depends on distribution volume. The unknown impact of isoflurane anesthesia used in determining mGFR remains a limiting factor. Thus, our study shows that there is a severe disagreement between GFR measured by tGFR and eGFR, stressing the need for more rigorous validation of the tGFR and possible adjustments to the underlying technique.</p

Discrepancies between transcutaneous and estimated glomerular filtration rates in rats with chronic kidney disease

Accurate assessment of the glomerular filtration rate (GFR) is crucial for researching kidney disease in rats. Although validation of methods that assess GFR is crucial, large-scale comparisons between different methods are lacking. Both transcutaneous GFR (tGFR) and a newly developed estimated GFR (eGFR) equation by our group provide a low-invasive approach enabling repeated measurements. The tGFR is a single bolus method using FITC-labeled sinistrin to measure GFR based on half-life of the transcutaneous signal, whilst the eGFR is based on urinary sinistrin clearance. Here, we retrospectively compared tGFR, using both 1- and 3- compartment models (tGFR_1c and tGFR_3c, respectively) to the eGFR in a historic cohort of 43 healthy male rats and 84 male rats with various models of chronic kidney disease. The eGFR was on average considerably lower than tGFR-1c and tGFR-3c (mean differences 855 and 216 μL/min, respectively) and only 20 and 47% of measurements were within 30% of each other, respectively. The relative difference between eGFR and tGFR was highest in rats with the lowest GFR. Possible explanations for the divergence are problems inherent to tGFR, such as technical issues with signal measurement, description of the signal kinetics, and translation of half-life to tGFR, which depends on distribution volume. The unknown impact of isoflurane anesthesia used in determining mGFR remains a limiting factor. Thus, our study shows that there is a severe disagreement between GFR measured by tGFR and eGFR, stressing the need for more rigorous validation of the tGFR and possible adjustments to the underlying technique.</p

Quantum geometry and quantum algorithms

Motivated by algorithmic problems arising in quantum field theories whose dynamical variables are geometric in nature, we provide a quantum algorithm that efficiently approximates the colored Jones polynomial. The construction is based on the complete solution of Chern-Simons topological quantum field theory and its connection to Wess-Zumino-Witten conformal field theory. The colored Jones polynomial is expressed as the expectation value of the evolution of the q-deformed spin-network quantum automaton. A quantum circuit is constructed capable of simulating the automaton and hence of computing such expectation value. The latter is efficiently approximated using a standard sampling procedure in quantum computation.Comment: Submitted to J. Phys. A: Math-Gen, for the special issue ``The Quantum Universe'' in honor of G. C. Ghirard

Faithful Squashed Entanglement

Squashed entanglement is a measure for the entanglement of bipartite quantum states. In this paper we present a lower bound for squashed entanglement in terms of a distance to the set of separable states. This implies that squashed entanglement is faithful, that is, strictly positive if and only if the state is entangled. We derive the bound on squashed entanglement from a bound on quantum conditional mutual information, which is used to define squashed entanglement and corresponds to the amount by which strong subadditivity of von Neumann entropy fails to be saturated. Our result therefore sheds light on the structure of states that almost satisfy strong subadditivity with equality. The proof is based on two recent results from quantum information theory: the operational interpretation of the quantum mutual information as the optimal rate for state redistribution and the interpretation of the regularised relative entropy of entanglement as an error exponent in hypothesis testing. The distance to the set of separable states is measured by the one-way LOCC norm, an operationally-motivated norm giving the optimal probability of distinguishing two bipartite quantum states, each shared by two parties, using any protocol formed by local quantum operations and one-directional classical communication between the parties. A similar result for the Frobenius or Euclidean norm follows immediately. The result has two applications in complexity theory. The first is a quasipolynomial-time algorithm solving the weak membership problem for the set of separable states in one-way LOCC or Euclidean norm. The second concerns quantum Merlin-Arthur games. Here we show that multiple provers are not more powerful than a single prover when the verifier is restricted to one-way LOCC operations thereby providing a new characterisation of the complexity class QMA.Comment: 24 pages, 1 figure, 1 table. Due to an error in the published version, claims have been weakened from the LOCC norm to the one-way LOCC nor

The representation of protein complexes in the Protein Ontology (PRO)

BACKGROUND: Representing species-specific proteins and protein complexes in ontologies that are both human- and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because proteins are often functional only as members of stable protein complexes, the PRO Consortium, in collaboration with existing protein and pathway databases, has launched a new initiative to implement logical and consistent representation of protein complexes. DESCRIPTION: We describe here how the PRO Consortium is meeting the challenge of representing species-specific protein complexes, how protein complex representation in PRO supports annotation of protein complexes and comparative biology, and how PRO is being integrated into existing community bioinformatics resources. The PRO resource is accessible at http://pir.georgetown.edu/pro/. CONCLUSION: PRO is a unique database resource for species-specific protein complexes. PRO facilitates robust annotation of variations in composition and function contexts for protein complexes within and between species

Methylglyoxal down-regulates the expression of cell cycle associated genes and activates the p53 pathway in human umbilical vein endothelial cells

Abstract Although methylglyoxal (MGO) has emerged as key mediator of diabetic microvascular complications, the influence of MGO on the vascular transcriptome has not thoroughly been assessed. Since diabetes is associated with low grade inflammation causing sustained nuclear factor-kappa B (NF-κB) activation, the current study addressed 1) to what extent MGO changes the transcriptome of human umbilical vein endothelial cells (HUVECs) exposed to an inflammatory milieu, 2) what are the dominant pathways by which these changes occur and 3) to what extent is this affected by carnosine, a putative scavenger of MGO. Microarray analysis revealed that exposure of HUVECs to high MGO concentrations significantly changes gene expression, characterized by prominent down-regulation of cell cycle associated genes and up-regulation of heme oxygenase-1 (HO-1). KEGG-based pathway analysis identified six significantly enriched pathways of which the p53 pathway was the most affected. No significant enrichment of inflammatory pathways was found, yet, MGO did inhibit VCAM-1 expression in Western blot analysis. Carnosine significantly counteracted MGO-mediated changes in a subset of differentially expressed genes. Collectively, our results suggest that MGO initiates distinct transcriptional changes in cell cycle/apoptosis genes, which may explain MGO toxicity at high concentrations. MGO did not augment TNF-α induced inflammation

Purine metabolism regulates DNA repair and therapy resistance in glioblastoma

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance. Treatments that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we find that purine metabolites, especially guanylates, strongly correlate with radiation resistance. Inhibiting GTP synthesis radiosensitizes GBM cells and patient-derived neurospheres by impairing DNA repair. Likewise, administration of exogenous purine nucleosides protects sensitive GBM models from radiation by promoting DNA repair. Neither modulating pyrimidine metabolism nor purine salvage has similar effects. An FDA-approved inhibitor of GTP synthesis potentiates the effects of radiation in flank and orthotopic patient-derived xenograft models of GBM. High expression of the rate-limiting enzyme of de novo GTP synthesis is associated with shorter survival in GBM patients. These findings indicate that inhibiting purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease

Serotonin and Dopamine Protect from Hypothermia/Rewarming Damage through the CBS/ H2S Pathway

Biogenic amines have been demonstrated to protect cells from apoptotic cell death. Herein we show for the first time that serotonin and dopamine increase H2S production by the endogenous enzyme cystathionine-β-synthase (CBS) and protect cells against hypothermia/rewarming induced reactive oxygen species (ROS) formation and apoptosis. Treatment with both compounds doubled CBS expression through mammalian target of rapamycin (mTOR) and increased H2S production in cultured rat smooth muscle cells. In addition, serotonin and dopamine treatment significantly reduced ROS formation. The beneficial effect of both compounds was minimized by inhibition of their re-uptake and by pharmacological inhibition of CBS or its down-regulation by siRNA. Exogenous administration of H2S and activation of CBS by Prydoxal 5′-phosphate also protected cells from hypothermic damage. Finally, serotonin and dopamine pretreatment of rat lung, kidney, liver and heart prior to 24 h of hypothermia at 3°C followed by 30 min of rewarming at 37°C upregulated the expression of CBS, strongly reduced caspase activity and maintained the physiological pH compared to untreated tissues. Thus, dopamine and serotonin protect cells against hypothermia/rewarming induced damage by increasing H2S production mediated through CBS. Our data identify a novel molecular link between biogenic amines and the H2S pathway, which may profoundly affect our understanding of the biological effects of monoamine neurotransmitters