This study examined the effects of linguistic task demands on the neuroanatomical localization of the neural response related to automatic semantic processing of concrete German nouns combining the associative priming paradigm with functional magnetic resonance imaging (fMRI). To clarify the functional role of the inferior frontal gyrus (IFG) for semantic processing with respect to semantic decision making compared to semantic processing per se, we used a linguistic task that involved either a binary decision process (i.e., semantic categorization; Experiment 1) or not (i.e., silently thinking about a word's meaning; Experiment 2). We observed associative priming effects indicated as neural suppression in bilateral superior temporal gyri (STG), anterior cingulate cortex (ACC), occipito-temporal brain areas, and in medial frontal brain areas independently of the linguistic task. Inferior parietal brain areas were more active for silently thinking about a word's meaning compared to semantic categorization. A conjunction analysis of linguistic task revealed that both tasks activated the same left-lateralized occipito-temporo-frontal network including the IFG. Contrasting neural associative priming effects across linguistic task demands, we found a significant interaction in the right IFG. The present fMRI data give rise to the assumption that activation of the left inferior frontal gyrus (LIFG) in the semantic domain might be important for semantic processing in general and not only for semantic decision making. These findings contrast with a recent study regarding the role of the LIFG for binary decision making in the lexical domain (Wright et al. 2011).

Changes in gene expression programs play a central role in cancer. Chromosomal aberrations such as deletions, duplications and translocations of DNA segments can lead to highly significant positive correlations of gene expression levels of neighboring genes. This should be utilized to improve the analysis of tumor expression profiles. Here, we develop a novel model class of autoregressive higher-order Hidden Markov Models (HMMs) that carefully exploit local data-dependent chromosomal dependencies to improve the identification of differentially expressed genes in tumor. Autoregressive higher-order HMMs overcome generally existing limitations of standard first-order HMMs in the modeling of dependencies between genes in close chromosomal proximity by the simultaneous usage of higher-order state-transitions and autoregressive emissions as novel model features. We apply autoregressive higher-order HMMs to the analysis of breast cancer and glioma gene expression data and perform in-depth model evaluation studies. We find that autoregressive higher-order HMMs clearly improve the identification of overexpressed genes with underlying gene copy number duplications in breast cancer in comparison to mixture models, standard first- and higher-order HMMs, and other related methods. The performance benefit is attributed to the simultaneous usage of higher-order state-transitions in combination with autoregressive emissions. This benefit could not be reached by using each of these two features independently. We also find that autoregressive higher-order HMMs are better able to identify differentially expressed genes in tumors independent of the underlying gene copy number status in comparison to the majority of related methods. This is further supported by the identification of well-known and of previously unreported hotspots of differential expression in glioblastomas demonstrating the efficacy of autoregressive higher-order HMMs for the analysis of individual tumor expression profiles. Moreover, we reveal interesting novel details of systematic alterations of gene expression levels in known cancer signaling pathways distinguishing oligodendrogliomas, astrocytomas and glioblastomas.

Background: General anesthesia usually requires mechanical ventilation, which is traditionally accomplished with constant tidal volumes in volume- or pressure-controlled modes. Experimental studies suggest that the use of variable tidal volumes (variable ventilation) recruits lung tissue, improves pulmonary function and reduces systemic inflammatory response. However, it is currently not known whether patients undergoing open abdominal surgery might benefit from intraoperative variable ventilation. Methods/Design: The PROtective VARiable ventilation trial ('PROVAR') is a single center, randomized controlled trial enrolling 50 patients who are planning for open abdominal surgery expected to last longer than 3 hours. PROVAR compares conventional (non-variable) lung protective ventilation (CV) with variable lung protective ventilation (VV) regarding pulmonary function and inflammatory response. The primary endpoint of the study is the forced vital capacity on the first postoperative day. Secondary endpoints include further lung function tests, plasma cytokine levels, spatial distribution of ventilation assessed by means of electrical impedance tomography and postoperative pulmonary complications. Discussion: We hypothesize that VV improves lung function and reduces systemic inflammatory response compared to CV in patients receiving mechanical ventilation during general anesthesia for open abdominal surgery longer than 3 hours. PROVAR is the first randomized controlled trial aiming at intra- and postoperative effects of VV on lung function. This study may help to define the role of VV during general anesthesia requiring mechanical ventilation.

Tumors exhibit complex organization and contain a variety of cell populations. The realization that the regenerative properties of a tumor may be largely confined to a cell subpopulation (cancer stem cell) is driving a new era of anti-cancer research. Cancer stem cells from Glioblastoma Multiforme tumors express markers that are also expressed in non-cancerous neural stem cells, including nestin and Sox2. We previously showed that the transcription factor Hes3 is a marker of neural stem cells, and that its expression is inhibited by JAK activity. Here we show that Hes3 is also expressed in cultures from glioblastoma multiforme which express neural stem cell markers, can differentiate into neurons and glia, and can recapitulate the tumor of origin when transplanted into immunocompromised mice. Similar to observations in neural stem cells, JAK inhibits Hes3 expression. Hes3 RNA interference reduces the number of cultured glioblastoma cells suggesting a novel therapeutic strategy.

Background: Surgery remains the only curative option for the treatment of pancreatic adenocarcinoma (PDAC). The goal of this study was to investigate the clinical outcome and prognostic factors in patients after resection for ductal adenocarcinoma of the pancreatic head. Methods: The data from 195 patients who underwent pancreatic head resection for PDAC between 1993 and 2011 in our center were retrospectively analyzed. The prognostic factors for survival after operation were evaluated using multivariate analysis. Results: The head resection surgeries included 69.7% pylorus-preserving pancreatoduodenectomies (PPPD) and 30.3% standard Kausch-Whipple pancreatoduodenectomies (Whipple). The overall mortality after pancreatoduodenectomy (PD) was 4.1%, and the overall morbidity was 42%. The actuarial 3- and 5-year survival rates were 31.5% (95% CI, 25.04%-39.6%) and 11.86% (95% CI, 7.38%-19.0%), respectively. Univariate analyses demonstrated that elevated CEA (p = 0.002) and elevated CA 19–9 (p = 0.026) levels, tumor grade (p = 0.001) and hard texture of the pancreatic gland (p = 0.017) were significant predictors of a poor survival. However, only CEA >3 ng/ml (p < 0.005) and tumor grade 3 (p = 0.027) were validated as significant predictors of survival in multivariate analysis. Conclusions: Our results suggest that tumor marker levels and tumor grade are significant predictors of poor survival for patients with pancreatic head cancer. Furthermore, hard texture of the pancreatic gland appears to be associated with poor survival.

Like all other viruses, a successful egress of functional particles from infected cells is a prerequisite for foamy virus (FV) spread within the host. The budding process of FVs involves steps, which are shared by other retroviruses, such as interaction of the capsid protein with components of cellular vacuolar protein sorting (Vps) machinery via late domains identified in some FV capsid proteins. Additionally, there are features of the FV budding strategy quite unique to the spumaretroviruses. This includes secretion of non-infectious subviral particles and a strict dependence on capsid-glycoprotein interaction for release of infectious virions from the cells. Virus-like particle release is not possible since FV capsid proteins lack a membrane-targeting signal. It is noteworthy that in experimental systems, the important capsid-glycoprotein interaction could be bypassed by fusing heterologous membrane-targeting signals to the capsid protein, thus enabling glycoprotein-independent egress. Aside from that, other systems have been developed to enable envelopment of FV capsids by heterologous Env proteins. In this review article, we will summarize the current knowledge on FV budding, the viral components and their domains involved as well as alternative and artificial ways to promote budding of FV particle structures, a feature important for alteration of target tissue tropism of FV-based gene transfer systems.

Alerting signals often serve to reduce temporal uncertainty by predicting the time of stimulus onset. The resulting response time benefits have often been explained by facilitated translation of stimulus codes into response codes on the basis of established stimulus-response (S-R) links. In paradigms of masked S-R priming alerting signals also modulate response activation processes triggered by subliminally presented prime stimuli. In the present study we tested whether facilitation of visuo-motor translation processes due to alerting signals critically depends on established S-R links. Alerting signals resulted in significantly enhanced masked priming effects for masked prime stimuli that included and that did not include established S-R links (i.e., target vs. novel primes). Yet, the alerting-priming interaction was more pronounced for target than for novel primes. These results suggest that effects of alerting signals on masked priming are especially evident when S-R links between prime and target exist. At the same time, an alerting-priming interaction also for novel primes suggests that alerting signals also facilitate stimulus-response translation processes when masked prime stimuli provide action-trigger conditions in terms of programmed S-R links.

Background: Multimorbidity is defined as suffering from coexistent chronic conditions. Multimorbid patients demand highly complex patient-centered care which often includes polypharmacy, taking an average of six different drugs per day. Adverse drug reactions, adverse drug events and medication errors are all potential consequences of polypharmacy. Our study aims to detect the status quo of the health care situation in Saxony’s general practices for multimorbid patients receiving multiple medications. We will identify the most common clinical profiles as well as documented adverse drug events and reactions that occur during the treatment of patients receiving multiple medications. We will focus on exploring the motives of general practitioners for the prescription of selected drugs in individual cases where there is evidence of potential drug-drug-interactions and potentially inappropriate medications in elderly patients. Furthermore, the study will explore general practitioners’ opinions on delegation of skills to other health professions to support medical care and monitoring of patients receiving multiple medications. Methods/design: This is a retrospective cross sectional study using mixed methods. Socio-demographic data as well as diagnoses, medication regimens and clinically important events will be analyzed retrospectively using general practitioners documentation in patients’ records. Based on these data, short vignettes will be generated and discussed by general practitioners in qualitative telephone interviews. Discussion: To be able to improve outpatient health care management for patients receiving multiple medications, the current status quo of care, risk factors for deficient treatment and characteristics of concerned patients must be investigated. Furthermore, it is necessary to understand the physicians’ decision making process regarding treatment.

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

Introduction: The quality of neonatal care is mainly determined by long-term neurodevelopmental outcome. The neurodevelopment of preterm infants is related to postnatal head growth and depends on medical interventions such as nutritional support. Head circumference (HC) is currently used as a two-dimensional measure of head growth. Since head deformities are frequently found in preterm infants, HC may not always adequately reflect head growth. Laser aided head shape digitizers offer semiautomatic acquisition of HC and cranial volume (CrV) and could thus be useful in describing head size more precisely. Aims: 1) To evaluate reproducibility of a 3D digital capture system in newborns. 2) To compare manual and digital HC measurements in a neonatal cohort. 3) To determine correlation of HC and CrV and predictive value of HC. Methods: Within a twelve-month period data of head scans with a laser shape digitizer were analysed. Repeated measures were used for method evaluation. Manually and digitally acquired HC was compared. Regression analysis of HC and CrV was performed. Results: Interobserver reliability was excellent for HC (bias-0.005%, 95% Limits of Agreement (LoA) −0.39–0.39%) and CrV (bias1.5%, 95%LoA-0.8–3.6%). Method comparison data was acquired from 282 infants. It revealed interchangeability of the methods (bias-0.45%; 95%LoA-4.55–3.65%) and no significant systematic or proportional differences. HC and CrV correlated (r2 = 0.859, p<0.001), performance of HC predicting CrV was poor (RSD ±24 ml). Correlation was worse in infants with lower postmenstrual age (r2 = 0.745) compared to older infants (r2 = 0.843). Discussion: The current practice of measuring HC for describing head growth in preterm infants could be misleading since it does not represent a 3D approach. CrV can vary substantially in infants of equal HC. The 3D laser scanner represents a new and promising method to provide reproducible data of CrV and HC. Since it does not provide data on cerebral structures, additional imaging is required.