No genetic evidence for involvement of Deltaretroviruses in adult patients with precursor and mature T-cell neoplasms

Background The Deltaretrovirus genus comprises viruses that infect humans (HTLV), various simian species (STLV) and cattle (BLV). HTLV-I is the main causative agent in adult T-cell leukemia in endemic areas and some of the simian T-cell lymphotropic viruses have been implicated in the induction of malignant lymphomas in their hosts. BLV causes enzootic bovine leukosis in infected cattle or sheep. During the past few years several new Deltaretrovirus isolates have been described in various primate species. Two new HTLV-like viruses in humans have recently been identified and provisionally termed HTLV-III and HTLV-IV. In order to identify a broad spectrum of Deltaretroviruses by a single PCR approach we have established a novel consensus PCR based on nucleotide sequence data obtained from 42 complete virus isolates (HTLV-I/-II, STLV-I/-II/-III, BLV). The primer sequences were based on highly interspecies-conserved virus genome regions. We used this PCR to detect Deltaretroviruses in samples from adult patients with a variety of rare T-cell neoplasms in Germany. Results: The sensitivity of the consensus PCR was at least between 10-2 and 10-3 with 100% specificity as demonstrated by serial dilutions of cell lines infected with either HTLV-I, HTLV-II or BLV. Fifty acute T-cell lymphoblastic leukemia (T-ALL) samples and 33 samples from patients with various rare mature T-cell neoplasms (T-PLL, Sezary syndrome and other T-NHL) were subsequently investigated. There were no cases with HTLV-I, HTLV-II or any other Deltaretroviruses. Conclusions: The results rule out a significant involvement of HTLV-I or HTLV-II in these disease entities and show that other related Deltaretroviruses are not likely to be involved. The newly established Deltaretrovirus PCR may be a useful tool for identifying new Deltaretroviruses

Using network analysis for the prediction of treatment dropout in patients with mood and anxiety disorders: a methodological proof-of-concept study

There are large health, societal, and economic costs associated with attrition from psychological services. The recently emerged, innovative statistical tool of complex network analysis was used in the present proof-of-concept study to improve the prediction of attrition. Fifty-eight patients undergoing psychological treatment for mood or anxiety disorders were assessed using Ecological Momentary Assessments four times a day for two weeks before treatment (3,248 measurements). Multilevel vector autoregressive models were employed to compute dynamic symptom networks. Intake variables and network parameters (centrality measures) were used as predictors for dropout using machine-learning algorithms. Networks for patients differed significantly between completers and dropouts. Among intake variables, initial impairment and sex predicted dropout explaining 6% of the variance. The network analysis identified four additional predictors: Expected force of being excited, outstrength of experiencing social support, betweenness of feeling nervous, and instrength of being active. The final model with the two intake and four network variables explained 32% of variance in dropout and identified 47 out of 58 patients correctly. The findings indicate that patients’ dynamic network structures may improve the prediction of dropout. When implemented in routine care, such prediction models could identify patients at risk for attrition and inform personalized treatment recommendations.This work was supported by the German Research Foundation National Institute (DFG, Grant nos. LU 660/8-1 and LU 660/10-1 to W. Lutz). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript. The corresponding author had access to all data in the study and had final responsibility for the decision to submit for publication. Dr. Hofmann receives financial support from the Alexander von Humboldt Foundation (as part of the Humboldt Prize), NIH/NCCIH (R01AT007257), NIH/NIMH (R01MH099021, U01MH108168), and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative. (LU 660/8-1 - German Research Foundation National Institute (DFG); LU 660/10-1 - German Research Foundation National Institute (DFG); Alexander von Humboldt Foundation; R01AT007257 - NIH/NCCIH; R01MH099021 - NIH/NIMH; U01MH108168 - NIH/NIMH; James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative)Accepted manuscrip

Guaranteed state estimation using a bundle of interval observers with adaptive gains applied to the induction machine

he scope of this paper is the design of an interval observer bundle for the guaranteed state estimation of an uncertain induction machine with linear, time-varying dynamics. These guarantees are of particular interest in the case of safety-critical systems. In many cases, interval observers provide large intervals for which the usability becomes impractical. Hence, based on a reduced-order hybrid interval observer structure, the guaranteed enclosure within intervals of the magnetizing current’s estimates is improved using a bundle of interval observers. One advantage of such an interval observer bundle is the possibility to reinitialize the interval observers at specified timesteps during runtime with smaller initial intervals, based on previously observed system states, resulting in decreasing interval widths. Thus, unstable observer dynamics are considered so as to take advantage of their transient behavior, whereby the overall stability of the interval estimation is maintained. An algorithm is presented to determine the parametrization of reduced-order interval observers. To this, an adaptive observer gain is introduced with which the system states are observed optimally by considering a minimal interval width at variable operating points. Furthermore, real-time capability and validation of the proposed methods are shown. The results are discussed with simulations as well as experimental data obtained with a test bench

Hybrid simulations of lateral diffusion in fluctuating membranes

In this paper we introduce a novel method to simulate lateral diffusion of inclusions in a fluctuating membrane. The regarded systems are governed by two dynamic processes: the height fluctuations of the membrane and the diffusion of the inclusion along the membrane. While membrane fluctuations can be expressed in terms of a dynamic equation which follows from the Helfrich Hamiltonian, the dynamics of the diffusing particle is described by a Langevin or Smoluchowski equation. In the latter equations, the curvature of the surface needs to be accounted for, which makes particle diffusion a function of membrane fluctuations. In our scheme these coupled dynamic equations, the membrane equation and the Langevin equation for the particle, are numerically integrated to simulate diffusion in a membrane. The simulations are used to study the ratio of the diffusion coefficient projected on a flat plane and the intramembrane diffusion coefficient for the case of free diffusion. We compare our results with recent analytical results that employ a preaveraging approximation and analyze the validity of this approximation. A detailed simulation study of the relevant correlation functions reveals a surprisingly large range where the approximation is applicable.Comment: 12 pages, 9 figures, accepted for publication in Phys. Rev.

The Commercial Consequences of Collective Layoffs: Close the Plant, Lose the Brand?

This article examines the effects of collective layoff announcements on sales and marketing-mix elasticities, accounting for supply-side constraints. The authors study 205 announcements in the automotive industry using a difference-in-differences model. They find that, following collective layoff announcements, layoff firms experience adverse changes in sales, advertising elasticity, and price elasticity. They explore the moderating role of announcement characteristics on these changes and find that collective layoff announcements by domestic firms and announcements that do not mention a decline in demand as a motive are more likely to be followed by adverse marketing-mix elasticity changes. On average, sales for the layoff firm in the layoff country are 8.7% lower following a collective layoff announcement than their predicted levels absent the announcement. Similarly, advertising elasticity is 9.8% lower and price elasticity is 19.2% higher than absent the announcement. Conversely, layoff firms typically decrease advertising spending in the country where collective layoffs have occurred, yet they do not change prices. These findings are relevant t

Identification of a 17-Nucleotide Splicing Enhancer in HPV-16 L1 that Counteracts the Effect of Multiple hnRNP A1-binding Splicing Silencers

Human papillomavirus type 16 (HPV-16) infections can in rare cases persist and cause lesions that may progress to cervical cancer. Cells in the lesions are not permissive for virus production, nor are cervical cancer cells. The intracellular environment is such that it prevents production of the highly immunogenic, viral structural proteins L1 and L2. One may speculate that inhibition of L1 and L2 expression is a prerequisite for persistence and cancer progression.We have therefore investigated how expression of HPV-16 L1 is regulated.We found that the only splice site in the HPV-16 late region, which is used to produce L1 mRNAs, is under control of a splicing enhancer located in the 17 nucleotides immediately downstream of the splice site. However, the function of this enhancer in cervical cancer cells is largely overshadowed by multiple splicing silencers in the late region which bind to hnRNP A1. High levels of hnRNP A1 therefore inhibit HPV-16 L1 expression. Immunohistological analysis of cervical epithelia revealed that hnRNPA1 is expressed primarily in the lower layers of the epithelium. hnRNPA1 is undetectable in terminally differentiated cells that can express HPV-16 late genes, which supports the conclusion that high levels of hnRNP A1 inhibit HPV-16 L1 expression

Local reflexion spaces

A reflexion space is generalization of a symmetric space introduced by O. Loos. We generalize locally symmetric spaces to local reflexion spaces in the similar way. We investigate, when local reflexion spaces are equivalently given by a locally flat Cartan connection of certain type.Comment: 8 pages, submitted to Archivum Mathematicu

Molecular monitoring of minimal residual disease in two patients with MLL-rearranged acute myeloid leukemia and haploidentical transplantation after relapse

This report describes the clinical courses of two acute myeloid leukemia patients. Both had MLL translocations, the first a t(10;11)(p11.2;q23) with MLL-AF10 and the second a t(11;19)(q23;p13.1) with MLL-ELL fusion. They achieved a clinical remission under conventional chemotherapy but relapsed shortly after end of therapy. Both had a history of invasive mycoses (one had possible pulmonary mycosis, one systemic candidiasis). Because no HLA-identical donor was available, a haploidentical transplantation was performed in both cases. Using a specially designed PCR method for the assessment of minimal residual disease (MRD), based on the quantitative detection of the individual chromosomal breakpoint in the MLL gene, all patients achieved complete and persistent molecular remission after transplantation. The immune reconstitution after transplantation is described in terms of total CD3+/CD4+, CD3+/CD8+, CD19+, and CD16+/CD56+ cell numbers over time. The KIR and HLA genotypes of donors and recipients are reported and the possibility of a KIR-mediated alloreactivity is discussed. This report illustrates that haploidentical transplantation may offer a chance of cure without chronic graft-versus-host disease in situations where no suitable HLA-identical donor is available even in a high-risk setting and shows the value of MRD monitoring in the pre- and posttransplant setting