Natural killer cell mediated missing-self recognition can protect mice from primary chronic myeloid leukemia in vivo.

Background: Natural Killer (NK) cells are thought to protect from residual leukemic cells in patients receiving stem cell transplantation. However, multiple retrospective analyses of patient data have yielded conflicting conclusions regarding a putative role of NK cells and the essential NK cell recognition events mediating a protective effect against leukemia. Further, a NK cell mediated protective effect against primary leukemia in vivo has not been shown directly.Methodology/Principal Findings: Here we addressed whether NK cells have the potential to control chronic myeloid leukemia (CML) arising based on the transplantation of BCR-ABL1 oncogene expressing primary bone marrow precursor cells into lethally irradiated recipient mice. These analyses identified missing-self recognition as the only NK cell-mediated recognition strategy, which is able to significantly protect from the development of CML disease in vivo.Conclusion: Our data provide a proof of principle that NK cells can control primary leukemic cells in vivo. Since the presence of NK cells reduced the abundance of leukemia propagating cancer stem cells, the data raise the possibility that NK cell recognition has the potential to cure CML, which may be difficult using small molecule BCR-ABL1 inhibitors. Finally, our findings validate approaches to treat leukemia using antibody-based blockade of self-specific inhibitory MHC class I receptors.

Missed appointments in an adolescent outpatient clinic : descriptive analyses of consultations over eight years ; et, Missed appointments in an outpatient clinic for adolescents, an approache to predict the risk of missing

Rapport de synthèse: Les rendez-vous manqués représentent un problème important, tant du point de vue de la santé des patients que du point de vue économique. Pourtant peu d'études se sont penchées sur le sujet, particulièrement dans une population d'adolescents. Les buts de cette étude étaient de caractériser les adolescents qui sont à risque de manquer ou d'annuler leurs rendez-vous dans une clinique ambulatoire de santé pour adolescents, de comparer les taux des rendez-vous manqués et annulés entre les différents intervenants et d'estimer l'efficacité d'une politique de taxation des rendez-vous manqués non excusés. Finalement, un modèle multi-niveau markovien a été utilisé afin de prédire le risque de manquer un rendez-vous. Ce modèle tient compte du passé de l'adolescent en matière de rendez-vous manqués et d'autres covariables et permet de grouper les individus ayant un comportement semblable. On peut ensuite prédire pour chaque groupe le risque de manquer ou annuler et les covariables influençant significativement ce risque. Entre 1999 et 2006, 32816 rendez-vous fixés pour 3577 patients âgés de 12 à 20 ans ont été analysés. Le taux de rendez-vous manqués était de 11.8%, alors que 10.9% avaient été annulés. Soixante pour cent des patients n'ont pas manqué un seul de leur rendezvous et 14% en ont manqué plus de 25%. Nous avons pu mettre en évidence plusieurs variables associées de manière statistiquement significative avec les taux de rendez-vous manqués et d'annulations (genre, âge, heure, jour de la semaine, intervenant thérapeutique). Le comportement des filles peut être catégorisé en 2 groupes. Le premier groupe inclut les diagnostiques psychiatriques et de trouble du comportement alimentaire, le risque de manquer dans ce groupe étant faible et associé au fait d'avoir précédemment manqué un rendez-vous et au délai du rendez-vous. Les autres diagnostiques chez les filles sont associés à un second groupe qui montre un risque plus élevé de manquer un rendez-vous et qui est associé à l'intervenant, au fait d'avoir précédemment manqué ou annulé le dernier rendez-vous et au délai du rendez-vous. Les garçons ont tous globalement un comportement similaire concernant les rendez-vous manqués. Le diagnostic au sein de ce groupe influence le risque de manquer, tout comme le fait d'avoir précédemment manqué ou annulé un rendez-vous, le délai du rendez-vous et l'âge du patient. L'introduction de la politique de taxation des rendez-vous non excusés n'a pas montré de différence significative des tàux de rendez-vous manqués, cependant cette mesure a permis une augmentation du taux d'annulations. En conclusion, les taux de présence des adolescents à leurs rendez-vous sont dépendants de facteurs divers. Et, même si les adolescents sont une population à risque concernant les rendez-vous manqués, la majorité d'entre eux ne manquent aucun de leurs rendez-vous, ceci étant vrai pour les deux sexes. Etudier les rendez-vous manqués et les adolescents qui sont à risque de rater leur rendez-vous est un pas nécessaire vers le contrôle de ce phénomène. Par ailleurs, les moyens de contrôle concernant les rendez-vous manqués devraient cibler les patients ayant déjà manqué un rendez-vous. La taxation des rendez-vous manqués permet d'augmenter les rendez-vous annulés, ce qui a l'avantage de permettre de fixer un nouveau rendez-vous et, de ce fait, d'améliorer la continuité des soins.

Is (1→3)-β-D-glucan the missing link from bedside assessment to pre-emptive therapy of invasive candidiasis?

ABSTRACT: Invasive candidiasis is a frequent life-threatening complication in critically ill patients. Early diagnosis followed by prompt treatment aimed at improving outcome by minimizing unnecessary antifungal use remains a major challenge in the ICU setting. Timely patient selection thus plays a key role for clinically efficient and cost-effective management. Approaches combining clinical risk factors and Candida colonization data have improved our ability to identify such patients early. While the negative predictive value of scores and predicting rules is up to 95 to 99%, the positive predictive value is much lower, ranging between 10 and 60%. Accordingly, if a positive score or rule is used to guide the start of antifungal therapy, many patients may be treated unnecessarily. Candida biomarkers display higher positive predictive values; however, they lack sensitivity and are thus not able to identify all cases of invasive candidiasis. The (1→3)-β-D-glucan (BG) assay, a panfungal antigen test, is recommended as a complementary tool for the diagnosis of invasive mycoses in high-risk hemato-oncological patients. Its role in the more heterogeneous ICU population remains to be defined. More efficient clinical selection strategies combined with performant laboratory tools are needed in order to treat the right patients at the right time by keeping costs of screening and therapy as low as possible. The new approach proposed by Posteraro and colleagues in the previous issue of Critical Care meets these requirements. A single positive BG value in medical patients admitted to the ICU with sepsis and expected to stay for more than 5 days preceded the documentation of candidemia by 1 to 3 days with an unprecedented diagnostic accuracy. Applying this one-point fungal screening on a selected subset of ICU patients with an estimated 15 to 20% risk of developing candidemia is an appealing and potentially cost-effective approach. If confirmed by multicenter investigations, and extended to surgical patients at high risk of invasive candidiasis after abdominal surgery, this Bayesian-based risk stratification approach aimed at maximizing clinical efficiency by minimizing health care resource utilization may substantially simplify the management of critically ill patients at risk of invasive candidiasis.

Cre recombinase-mediated inactivation of H-2Dd transgene expression: evidence for partial missing self-recognition by Ly49A NK cells.

We have established H-2D(d)-transgenic (Tg) mice, in which H-2D(d) expression can be extinguished by Cre recombinase-mediated deletion of an essential portion of the transgene (Tg). NK cells adapted to the expression of the H-2D(d) Tg in H-2(b) mice and acquired reactivity to cells lacking H-2D(d), both in vivo and in vitro. H-2D(d)-Tg mice crossed to mice harboring an Mx-Cre Tg resulted in mosaic H-2D(d) expression. That abrogated NK cell reactivity to cells lacking D(d). In D(d) single Tg mice it is the Ly49A+ NK cell subset that reacts to cells lacking D(d), because the inhibitory Ly49A receptor is no longer engaged by its D(d) ligand. In contrast, Ly49A+ NK cells from D(d) x MxCre double Tg mice were unable to react to D(d)-negative cells. These Ly49A+ NK cells retained reactivity to target cells that were completely devoid of MHC class I molecules, suggesting that they were not anergic. Variegated D(d) expression thus impacts specifically missing D(d) but not globally missing class I reactivity by Ly49A+ NK cells. We propose that the absence of D(d) from some host cells results in the acquisition of only partial missing self-reactivity.

Missing value imputation in longitudinal measures of alcohol consumption

Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003-2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, "real" observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered. Copyright (C) 2011 John Wiley & Sons, Ltd.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

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