TH2 cytokines from malignant cells suppress TH1 responses and enforce a global TH2 bias in leukemic cutaneous T-cell lymphoma

PURPOSE In leukemic cutaneous T-cell lymphoma (L-CTCL), malignant T cells accumulate in the blood and give rise to widespread skin inflammation. Patients have intense pruritus, increased immunoglobulin E (IgE), and decreased T-helper (TH)-1 responses, and most die from infection. Depleting malignant T cells while preserving normal immunity is a clinical challenge. L-CTCL has been variably described as a malignancy of regulatory, TH2 and TH17 cells. EXPERIMENTAL DESIGN We analyzed phenotype and cytokine production in malignant and benign L-CTCL T cells, characterized the effects of malignant T cells on healthy T cells, and studied the immunomodulatory effects of treatment modalities in patients with L-CTCL. RESULTS Twelve out of 12 patients with L-CTCL overproduced TH2 cytokines. Remaining benign T cells were also strongly TH2 biased, suggesting a global TH2 skewing of the T-cell repertoire. Culture of benign T cells away from the malignant clone reduced TH2 and enhanced TH1 responses, but separate culture had no effect on malignant T cells. Coculture of healthy T cells with L-CTCL T cells reduced IFNγ production and neutralizing antibodies to interleukin (IL)-4 and IL-13 restored TH1 responses. In patients, enhanced TH1 responses were observed following a variety of treatment modalities that reduced malignant T-cell burden. CONCLUSIONS A global TH2 bias exists in both benign and malignant T cells in L-CTCL and may underlie the infectious susceptibility of patients. TH2 cytokines from malignant cells strongly inhibited TH1 responses. Our results suggest that therapies that inhibit TH2 cytokine activity, by virtue of their ability to improve TH1 responses, may have the potential to enhance both anticancer and antipathogen responses.

A test of genetic association among male nuptial coloration, female mating preference, and male aggression bias within a polymorphic population of cichlid fish

Both inter- and intrasexual selection have been implicated in the origin and maintenance of species-rich taxa with diverse sexual traits. Simultaneous disruptive selection by female mate choice and male-male competition can, in theory, lead to speciation without geographical isolation if both act on the same male trait. Female mate choice can generate discontinuities in gene flow, while male-male competition can generate negative frequency-dependent selection stabilizing the male trait polymorphism. Speciation may be facilitated when mating preference and/or aggression bias are physically linked to the trait they operate on. We tested for genetic associations among female mating preference, male aggression bias and male coloration in the Lake Victoria cichlid Pundamilia. We crossed females from a phenotypically variable population with males from both extreme ends of the phenotype distribution in the same population (blue or red). Male offspring of a red sire were significantly redder than males of a blue sire, indicating that intra-population variation in male coloration is heritable. We tested mating preferences of female offspring and aggression biases of male offspring using binary choice tests. There was no evidence for associations at the family level between female mating preferences and coloration of sires, but dam identity had a significant effect on female mate preference. Sons of the red sire directed significantly more aggression to red than blue males, whereas sons of the blue sire did not show any bias. There was a positive correlation among individuals between male aggression bias and body coloration, possibly due to pleiotropy or physical linkage, which could facilitate the maintenance of color polymorphism.

Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study

BACKGROUND Empirical research has illustrated an association between study size and relative treatment effects, but conclusions have been inconsistent about the association of study size with the risk of bias items. Small studies give generally imprecisely estimated treatment effects, and study variance can serve as a surrogate for study size. METHODS We conducted a network meta-epidemiological study analyzing 32 networks including 613 randomized controlled trials, and used Bayesian network meta-analysis and meta-regression models to evaluate the impact of trial characteristics and study variance on the results of network meta-analysis. We examined changes in relative effects and between-studies variation in network meta-regression models as a function of the variance of the observed effect size and indicators for the adequacy of each risk of bias item. Adjustment was performed both within and across networks, allowing for between-networks variability. RESULTS Imprecise studies with large variances tended to exaggerate the effects of the active or new intervention in the majority of networks, with a ratio of odds ratios of 1.83 (95% CI: 1.09,3.32). Inappropriate or unclear conduct of random sequence generation and allocation concealment, as well as lack of blinding of patients and outcome assessors, did not materially impact on the summary results. Imprecise studies also appeared to be more prone to inadequate conduct. CONCLUSIONS Compared to more precise studies, studies with large variance may give substantially different answers that alter the results of network meta-analyses for dichotomous outcomes.

Chronology of Lake El'gygytgyn sediments – a combined magnetostratigraphic, palaeoclimatic and orbital tuning study based on multi-parameter analyses

A 318-metre-long sedimentary profile drilled by the International Continental Scientific Drilling Program (ICDP) at Site 5011-1 in Lake El’gygytgyn, Far East Russian Arctic, has been analysed for its sedimentologic response to global climate modes by chronostratigraphic methods. The 12 km wide lake is sited off-centre in an 18 km large crater that was created by the impact of a meteorite 3.58 Ma ago. Since then sediments have been continuously deposited. For establishing their chronology, major reversals of the earth’s magnetic field provided initial tie points for the age model, confirming that the impact occurred in the earliest geomagnetic Gauss chron. Various stratigraphic parameters, reflecting redox conditions at the lake floor and climatic conditions in the catchment were tuned synchronously to Northern Hemisphere insolation variations and the marine oxygen isotope stack, respectively. Thus, a robust age model comprising more than 600 tie points could be defined. It could be shown that deposition of sediments in Lake El’gygytgyn occurred in concert with global climatic cycles. The upper �160m of sediments represent the past 3.3 Ma, equivalent to sedimentation rates of 4 to 5 cm ka−1, whereas the lower 160m represent just the first 0.3 Ma after the impact, equivalent to sedimentation rates in the order of 45 cm ka−1. This study also provides orbitally tuned ages for a total of 8 tephras deposited in Lake El’gygytgyn.

A view through gloomy glasses: accuracy and bias in relationships of narcissists

Narcissists’ perception of others is marked by a negative bias in the service of their own self-enhancement. The aim of this study was to determine whether narcissists’ negative bias extends to the perception of romantic partners too. In addition, we explored whether partners of narcissists succumb to specific perception biases as well. During 14 days, 86 couples completed measures of support given to and received from their partners. The results indicated that both male and female narcissists were more accurate in detecting negative support (e.g., blaming the partner for his or her problems) received from their partners, while female narcissists only were less accurate in perceiving altruistic support motives (e.g., truly enjoying to help the partner) of their male partner. Moreover, narcissists as well as their partners displayed a negative bias by underestimating the amount of altruistic support motives reported by each of them. On the other hand, partners of narcissists were positively biased as well and underestimated the negative support given by the narcissists. Results are discussed in relation to the self-regulatory goals of narcissists and of their partners and with respect to the possible impact of their accuracy and biases on the couple wellbeing.

Bias associated with detrital zircon geochronology and thermochronometry

Detrital studies that utilize zircon U–Pb geochronology and fission-track (FT) thermochronometry are subject to a range of potential sources of bias that should be properly evaluated and minimized. Some of them are common to any single-grain mineral analysis (e.g., variable bedrock mineral fertility, hydraulic sorting during transport, selective grain loss during sample processing), whereas others are intrinsic to zircon, and are related to radiation damage and age discordance. In this article, we quantify the impact of intrinsic bias on detrital studies thanks to the analysis of modern detritus shed from the European Alps, and illustrate the general implications on geological interpretations. We show that detrital zircon U–Pb age distributions based on statistically robust datasets are highly reproducible and representative of the parent bedrock ages in the catchment. Arbitrary or selective removal of discordant grain ages can be minimized by using the Kolmogorov–Smirnov test to identify an appropriate cutoff level. Loss of metamict (α-damaged) zircon has a minor impact on data representativeness, and is mainly controlled by regional metamorphism rather than by mechanical abrasion during river transport. Zircon FT grain-age distributions were found to have poor reproducibility, although age spectra are consistent with bedrock data. However, unlike the U–Pb datasets, U-rich zircon grains (> 1000 ppm) are systematically missed, and undatable grains may exceed 50%. We identify two major sources of distribution bias specific to zircon FT datasets: (i) sediment sources dominated by U-rich zircon grains are markedly underrepresented in the detrital record, because such grains often have uncountable high densities of fission tracks (“U concentration bias”); (ii) sediment sources that shed zircon grains with high levels of α-damage are underrepresented, because these grains are lost during chemical etching for FT revelation (“etching bias”). In the case of multimethod dating on the same grains (e.g., FT and U–Pb double dating), bias affecting detrital zircon FT dating propagates to the entire dataset. These effects may not impact on exhumation-rate studies that utilize the youngest grain ages (i.e., lag-time approach). However, they represent a limiting factor for conventional provenance studies, and generally preclude application of zircon FT dating to sediment budget calculations.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA)

OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.

Incidental detection of an occult oral malignancy with autofluorescence imaging: a case report.

BACKGROUND: Autofluorescence imaging is used widely for diagnostic evaluation of various epithelial malignancies. Cancerous lesions display loss of autofluorescence due to malignant changes in epithelium and subepithelial stroma. Carcinoma of unknown primary site presents with lymph node or distant metastasis, for which the site of primary tumour is not detectable. We describe here the use of autofluorescence imaging for detecting a clinically innocuous appearing occult malignancy of the palate which upon pathological examination was consistent with a metastatic squamous cell carcinoma. CASE DESCRIPTION: A submucosal nodule was noted on the right posterior hard palate of a 59-year-old white female during clinical examination. Examination of this lesion using a multispectral oral cancer screening device revealed loss of autofluorescence at 405 nm illumination. An excisional biopsy of this nodule, confirmed the presence of a metastatic squamous cell carcinoma. Four years ago, this patient was diagnosed with metastatic squamous cell carcinoma of the right mid-jugular lymph node of unknown primary. She was treated with external beam irradiation and remained disease free until current presentation. CONCLUSION: This case illustrates the important role played by autofluorescence tissue imaging in diagnosing a metastatic palatal tumour that appeared clinically innocuous and otherwise would not have been biopsied.

Determination of the Weak Axial Vector Coupling λ=g_{A}/g_{V} from a Measurement of the β-Asymmetry Parameter A in Neutron Beta Decay

We report on a new measurement of the neutron beta-asymmetry parameter A with the instrument \perkeo. Main advancements are the high neutron polarization of P=99.7(1) from a novel arrangement of super mirror polarizers and reduced background from improvements in beam line and shielding. Leading corrections were thus reduced by a factor of 4, pushing them below the level of statistical error and resulting in a significant reduction of systematic uncertainty compared to our previous experiments. From the result A0=−0.11996(58), we derive the ratio of the axial-vector to the vector coupling constant λ=gA/gV=−1.2767(16)

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Quantifying uncertainty in cost effectiveness analyses

This study compared four alternative approaches (Taylor, Fieller, percentile bootstrap, and bias-corrected bootstrap methods) to estimating confidence intervals (CIs) around cost-effectiveness (CE) ratio. The study consisted of two components: (1) Monte Carlo simulation was conducted to identify characteristics of hypothetical cost-effectiveness data sets which might lead one CI estimation technique to outperform another. These results were matched to the characteristics of an (2) extant data set derived from the National AIDS Demonstration Research (NADR) project. The methods were used to calculate (CIs) for data set. These results were then compared. The main performance criterion in the simulation study was the percentage of times the estimated (CIs) contained the “true” CE. A secondary criterion was the average width of the confidence intervals. For the bootstrap methods, bias was estimated. ^ Simulation results for Taylor and Fieller methods indicated that the CIs estimated using the Taylor series method contained the true CE more often than did those obtained using the Fieller method, but the opposite was true when the correlation was positive and the CV of effectiveness was high for each value of CV of costs. Similarly, the CIs obtained by applying the Taylor series method to the NADR data set were wider than those obtained using the Fieller method for positive correlation values and for values for which the CV of effectiveness were not equal to 30% for each value of the CV of costs. ^ The general trend for the bootstrap methods was that the percentage of times the true CE ratio was contained in CIs was higher for the percentile method for higher values of the CV of effectiveness, given the correlation between average costs and effects and the CV of effectiveness. The results for the data set indicated that the bias corrected CIs were wider than the percentile method CIs. This result was in accordance with the prediction derived from the simulation experiment. ^ Generally, the bootstrap methods are more favorable for parameter specifications investigated in this study. However, the Taylor method is preferred for low CV of effect, and the percentile method is more favorable for higher CV of effect. ^

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^