Decoherence of matter waves by thermal emission of radiation

Emergent quantum technologies have led to increasing interest in decoherence - the processes that limit the appearance of quantum effects and turn them into classical phenomena. One important cause of decoherence is the interaction of a quantum system with its environment, which 'entangles' the two and distributes the quantum coherence over so many degrees of freedom as to render it unobservable. Decoherence theory has been complemented by experiments using matter waves coupled to external photons or molecules, and by investigations using coherent photon states, trapped ions and electron interferometers. Large molecules are particularly suitable for the investigation of the quantum-classical transition because they can store much energy in numerous internal degrees of freedom; the internal energy can be converted into thermal radiation and thus induce decoherence. Here we report matter wave interferometer experiments in which C70 molecules lose their quantum behaviour by thermal emission of radiation. We find good quantitative agreement between our experimental observations and microscopic decoherence theory. Decoherence by emission of thermal radiation is a general mechanism that should be relevant to all macroscopic bodies.Comment: 5 pages, 4 figure

IL-26 inhibits hepatitis C virus replication in hepatocytes

Publisher Copyright: © 2021 European Association for the Study of the LiverBackground & Aims: Interleukin-26 (IL-26) is a proinflammatory cytokine that has properties atypical for a cytokine, such as direct antibacterial activity and DNA-binding capacity. We previously observed an accumulation of IL-26 in fibrotic and inflammatory lesions in the livers of patients with chronic HCV infection and showed that infiltrating CD3+ lymphocytes were the principal source of IL-26. Surprisingly, IL-26 was also detected in the cytoplasm of hepatocytes from HCV-infected patients, even though these cells do not produce IL-26, even when infected with HCV. Based on this observation and possible interactions between IL-26 and nucleic acids, we investigated the possibility that IL-26 controlled HCV infection independently of the immune system. Methods: We evaluated the ability of IL-26 to interfere with HCV replication in hepatocytes and investigated the mechanisms by which IL-26 exerts its antiviral activity. Results: We showed that IL-26 penetrated HCV-infected hepatocytes, where it interacted directly with HCV double-stranded RNA replication intermediates, thereby inhibiting viral replication. IL-26 interfered with viral RNA-dependent RNA polymerase activity, preventing the de novo synthesis of viral genomic single-stranded RNA. Conclusions: These findings reveal a new role for IL-26 in direct protection against HCV infection, independently of the immune system, and increase our understanding of the antiviral defense mechanisms controlling HCV infection. Future studies should evaluate the possible use of IL-26 for treating other chronic disorders caused by RNA viruses, for which few treatments are currently available, or emerging RNA viruses. Lay summary: This study sheds new light on the body's arsenal for controlling hepatitis C virus (HCV) infection and identifies interleukin-26 (IL-26) as an antiviral molecule capable of blocking HCV replication. IL-26, which has unique biochemical and structural characteristics, penetrates infected hepatocytes and interacts directly with viral RNA, thereby blocking viral replication. IL-26 is, therefore, a new player in antiviral defenses, operating independently of the immune system. It is of considerable potential interest for treating HCV infection and other chronic disorders caused by RNA viruses for which few treatments are currently available, and for combating emerging RNA viruses.Peer reviewe

Mesoscopic Fano Effect in a Quantum Dot Embedded in an Aharonov-Bohm Ring

The Fano effect, which occurs through the quantum-mechanical cooperation between resonance and interference, can be observed in electron transport through a hybrid system of a quantum dot and an Aharonov-Bohm ring. While a clear correlation appears between the height of the Coulomb peak and the real asymmetric parameter $q$ for the corresponding Fano lineshape, we need to introduce a complex $q$ to describe the variation of the lineshape by the magnetic and electrostatic fields. The present analysis demonstrates that the Fano effect with complex asymmetric parameters provides a good probe to detect a quantum-mechanical phase of traversing electrons.Comment: REVTEX, 9 pages including 8 figure

Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters. Results: It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach. Conclusions: To alleviate the effects of data size on information theory based GRN inference algorithms, novel time lag based information theoretic approaches to infer gene regulatory networks have been proposed. The results show that the time lags of regulatory effects between any pair of genes play an important role in GRN inference schemes

Variants at APOE influence risk of deep and lobar intracerebral hemorrhage

Objective Prior studies investigating the association between APOE alleles ε2/ε4 and risk of intracerebral hemorrhage (ICH) have been inconsistent and limited to small sample sizes, and did not account for confounding by population stratification or determine which genetic risk model was best applied. Methods We performed a large-scale genetic association study of 2189 ICH cases and 4041 controls from 7 cohorts, which were analyzed using additive models for ε2 and ε4. Results were subsequently meta-analyzed using a random effects model. A proportion of the individuals (322 cases, 357 controls) had available genome-wide data to adjust for population stratification. Results Alleles ε2 and ε4 were associated with lobar ICH at genome-wide significance levels (odds ratio [OR] = 1.82, 95% confidence interval [CI] = 1.50–2.23, p = 6.6 × 10 −10 ; and OR = 2.20, 95%CI = 1.85–2.63, p = 2.4 × 10 −11 , respectively). Restriction of analysis to definite/probable cerebral amyloid angiopathy ICH uncovered a stronger effect. Allele ε4 was also associated with increased risk for deep ICH (OR = 1.21, 95% CI = 1.08–1.36, p = 2.6 × 10 −4 ). Risk prediction evaluation identified the additive model as best for describing the effect of APOE genotypes. Interpretation APOE ε2 and ε4 are independent risk factors for lobar ICH, consistent with their known associations with amyloid biology. In addition, we present preliminary findings on a novel association between APOE ε4 and deep ICH. Finally, we demonstrate that an additive model for these APOE variants is superior to other forms of genetic risk modeling previously applied. ANN NEUROL 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78478/1/22134_ftp.pd

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Variance of the SGK1 Gene Is Associated with Insulin Secretion in Different European Populations: Results from the TUEF, EUGENE2, and METSIM Studies

HYPOTHESIS:Serum- and Glucocorticoid-inducible Kinase 1 (SGK1) is involved in the regulation of insulin secretion and may represent a candidate gene for the development of type 2 diabetes mellitus in humans. METHODS:Three independent European populations were analyzed for the association of SGK1 gene (SGK) variations and insulin secretion traits. The German TUEF project provided the screening population (N = 725), and four tagging SNPs (rs1763527, rs1743966, rs1057293, rs9402571) were investigated. EUGENE2 (N = 827) served as a replication cohort for the detected associations. Finally, the detected associations were validated in the METSIM study, providing 3798 non-diabetic and 659 diabetic (type 2) individuals. RESULTS:Carriers of the minor G allele in rs9402571 had significantly higher C-peptide levels in the 2 h OGTT (+10.8%, p = 0.04; dominant model) and higher AUC(C-Peptide)/AUC(Glc) ratios (+7.5%, p = 0.04) compared to homozygous wild type TT carriers in the screening population. As interaction analysis for BMIxrs9402571 was significant (p = 0.04) for the endpoint insulin secretion, we stratified the TUEF cohort for BMI, using a cut off point of BMI = 25. The effect on insulin secretion only remained significant in lean TUEF participants (BMI< or =25). This finding was replicated in lean EUGENE2 rs9402571 minor allele carriers, who had a significantly higher AUC(Ins)/AUC(Glc) (TT: 226+/-7, XG: 246+/-9; p = 0.019). Accordingly, the METSIM trial revealed a lower prevalence of type 2 diabetes (OR: 0.85; 95%CI: 0.71-1.01; p = 0.065, dominant model) in rs9402571 minor allele carriers. CONCLUSIONS:The rs9402571 SGK genotype associates with increased insulin secretion in lean non-diabetic TUEF/EUGENE2 participants and with lower diabetes prevalence in METSIM. Our study in three independent European populations supports the conclusion that SGK variability affects diabetes risk