Cellular and immunological basis of the host-parasite relationship during infection with Neospora caninum

Neospora caninum is an apicomplexan parasite that is closely related to Toxoplasma gondii, the causative agent of toxoplasmosis in humans and domestic animals. However, in contrast to T. gondii, N. caninum represents a major cause of abortion in cattle, pointing towards distinct differences in the biology of these two species. There are 3 distinct key features that represent potential targets for prevention of infection or intervention against disease caused by N. caninum. Firstly, tachyzoites are capable of infecting a large variety of host cells in vitro and in vivo. Secondly, the parasite exploits its ability to respond to alterations in living conditions by converting into another stage (tachyzoite-to-bradyzoite or vice versa). Thirdly, by analogy with T. gondii, this parasite has evolved mechanisms that modulate its host cells according to its own requirements, and these must, especially in the case of the bradyzoite stage, involve mechanisms that ensure long-term survival of not only the parasite but also of the host cell. In order to elucidate the molecular and cellular bases of these important features of N. caninum, cell culture-based approaches and laboratory animal models are being exploited. In this review, we will summarize the current achievements related to host cell and parasite cell biology, and will discuss potential applications for prevention of infection and/or disease by reviewing corresponding work performed in murine laboratory infection models and in cattle.

Perspectives on periodontal risk factors

The development of a clinical decision tree based on knowledge about risks and reported outcomes of therapy is a necessity for successful planning and outcome of periodontal therapy. This requires a well-founded knowledge of the disease entity and a broad knowledge of how different risk conditions attribute to periodontitis. The infectious etiology, a complex immune response, and influence from a large number of co-factors are challenging conditions in clinical periodontal risk assessment. The difficult relationship between independent and dependent risk conditions paired with limited information on periodontitis prevalence adds to difficulties in periodontal risk assessment. The current information on periodontitis risk attributed to smoking habits, socio-economic conditions, general health and subjects' self-perception of health, is not comprehensive, and this contributes to limited success in periodontal risk assessment. New models for risk analysis have been advocated. Their utility for the estimation of periodontal risk assessment and prognosis should be tested. The present review addresses several of these issues associated with periodontal risk assessment.

Primary perivascular epithelioid cell tumor of the liver not related to hepatic ligaments: hepatic PEComa as an emerging entity

Primary perivascular epithelioid cell tumor (PEComa) of the liver is a very rare example of an emerging family of hepatic PEC tumors. Only few cases have been described so far. We report the case of a large but benign hepatic PEComa in a 53-year-old man without signs of tuberous sclerosis. In contrast to recently described PEC-derived liver tumors in children and young adults, this neoplasm was not related to the hepatic ligaments but had developed deeply within the liver substance. The neoplastic cells displayed the complete phenotype typical for PEComas, i.e. reactivity for several melanoma markers and for smooth muscle actin. The unique relationship of myoid tumor cells to the adventitia of blood vessels prompted us, in comparison with published findings obtained with angiomyolipomas, to comment on the possible origin of the still enigmatic perivascular epithelioid cells.

High level of extracellular potassium and its correlates after severe head injury: relationship to high intracranial pressure

OBJECT: Disturbed ionic and neurotransmitter homeostasis are now recognized as probably the most important mechanisms contributing to the development of secondary brain swelling after traumatic brain injury (TBI). Evidence obtained in animal models indicates that posttraumatic neuronal excitation by excitatory amino acids leads to an increase in extracellular potassium, probably due to ion channel activation. The purpose of this study was therefore to measure dialysate potassium in severely head injured patients and to correlate these results with measurements of intracranial pressure (ICP), patient outcome, and levels of dialysate glutamate and lactate, and cerebral blood flow (CBF) to determine the role of ischemia in this posttraumatic ion dysfunction. METHODS: Eighty-five patients with severe TBI (Glasgow Coma Scale Score < 8) were treated according to an intensive ICP management-focused protocol. All patients underwent intracerebral microdialyis. Dialysate potassium levels were analyzed using flame photometry, and dialysate glutamate and dialysate lactate levels were measured using high-performance liquid chromatography and an enzyme-linked amperometric method in 72 and 84 patients, respectively. Cerebral blood flow studies (stable xenon computerized tomography scanning) were performed in 59 patients. In approximately 20% of the patients, dialysate potassium values were increased (dialysate potassium > 1.8 mM) for 3 hours or more. A mean amount of dialysate potassium greater than 2 mM throughout the entire monitoring period was associated with ICP above 30 mm Hg and fatal outcome, as were progressively rising levels of dialysate potassium. The presence of dialysate potassium correlated positively with dialysate glutamate (p < 0.0001) and lactate (p < 0.0001) levels. Dialysate potassium was significantly inversely correlated with reduced CBF (p = 0.019). CONCLUSIONS: Dialysate potassium was increased after TBI in 20% of measurements. High levels of dialysate potassium were associated with increased ICP and poor outcome. The simultaneous increase in dialysate potassium, together with dialysate glutamate and lactate, supports the concept that glutamate induces ionic flux and consequently increases ICP, which the authors speculate may be due to astrocytic swelling. Reduced CBF was also significantly correlated with increased levels of dialysate potassium. This may be due to either cell swelling or altered vasoreactivity in cerebral blood vessels caused by higher levels of potassium after trauma. Additional studies in which potassium-sensitive microelectrodes are used are needed to validate these ionic events more clearly.

High extracellular potassium and its correlates after severe head injury: relationship to high intracranial pressure

Disturbed ionic and neurotransmitter homeostasis are now recognized to be probably the most important mechanisms contributing to the development of secondary brain swelling after traumatic brian injury (TBI). Evidence obtained from animal models indicates that posttraumatic neuronal excitation via excitatory amino acids leads to an increase in extracellular potassium, probably due to ion channel activation. The purpose of this study was therefore to measure dialysate potassium in severely head injured patients and to correlate these results with intracranial pressure (ICP), outcome, and also with the levels of dialysate glutamate, lactate, and cerebral blood flow (CBF) so as to determine the role of ischemia in this posttraumatic ionic dysfunction. Eighty-five patients with severe TBI (Glasgow Coma Scale score < 8) were treated according to an intensive ICP management-focused protocol. All patients underwent intracerebral microdialyis. Dialysate potassium levels were analyzed by flame photometry, as were dialysate glutamate and dialysate lactate levels, which were measured using high-performance liquid chromatography and an enzyme-linked amperometric method in 72 and 84 patients respectively. Cerebral blood flow studies (stable Xenon--computerized tomography scanning) were performed in 59 patients. In approximately 20% of the patients, potassium values were increased (dialysate potassium > 1.8 mmol). Mean dialysate potassium (> 2 mmol) was associated with ICP above 30 mm Hg and fatal outcome. Dialysate potassium correlated positively with dialysate glutamate (p < 0.0001) and lactate levels (p < 0.0001). Dialysate potassium was significantly inversely correlated with reduced CBF (p = 0.019). Dialysate potassium was increased after TBI in 20% of measurements. High levels of dialysate potassium were associated with increased ICP and poor outcome. The simultaneous increase of potassium, together with dialysate glutamate and lactate, supports the hypothesis that glutamate induces ionic flux and consequently increases ICP due to astrocytic swelling. Reduced CBF was also significantly correlated with increased levels of dialysate potassium. This may be due to either cell swelling or altered potassium reactivity in cerebral blood vessels after trauma.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Dose–effect relationship in routine outpatient psychotherapy: Does treatment duration matter?

Objective: There is an ongoing debate concerning how outcome variables change during the course of psychotherapy. We compared the dose–effect model, which posits diminishing effects of additional sessions in later treatment phases, against a model that assumes a linear and steady treatment progress through termination. Method: Session-by-session outcome data of 6,375 outpatients were analyzed, and participants were categorized according to treatment length. Linear and log-linear (i.e., negatively accelerating) latent growth curve models (LGCMs) were estimated and compared for different treatment length categories. Results: When comparing the fit of the various models, the log-linear LGCMs assuming negatively accelerating treatment progress consistently outperformed the linear models irre- spective of treatment duration. The rate of change was found to be inversely related to the length of treatment. Conclusion: As proposed by the dose–effect model, the expected course of improvement in psychotherapy appears to follow a negatively accelerated pattern of change, irrespective of the duration of the treatment. However, our results also suggest that the rate of change is not constant across various treatment lengths. As proposed by the “good enough level” model, longer treatments are associated with less rapid rates of change.

Social relationship correlates of major depressive disorder and depressive symptoms in Switzerland: nationally representative cross sectional study

BACKGROUND The quality and quantity of social relationships are associated with depression but there is less evidence regarding which aspects of social relationship are most predictive. We evaluated the relative magnitude and independence of the association of four social relationship domains with major depressive disorder and depressive symptoms. METHODS We analyzed a cross-sectional telephone interview and postal survey of a probability sample of adults living in Switzerland (N = 12,286). Twelve-month major depressive disorder was assessed via structured interview over the telephone using the Composite International Diagnostic Interview (CIDI). The postal survey assessed depressive symptoms as well as variables representing emotional support, tangible support, social integration, and loneliness. RESULTS Each individual social relationship domain was associated with both outcome measures, but in multivariate models being lonely and perceiving unmet emotional support had the largest and most consistent associations across depression outcomes (incidence rate ratios ranging from 1.55-9.97 for loneliness and from 1.23-1.40 for unmet support, p's < 0.05). All social relationship domains except marital status were independently associated with depressive symptoms whereas only loneliness and unmet support were associated with depressive disorder. CONCLUSIONS Perceived quality and frequency of social relationships are associated with clinical depression and depressive symptoms across a wide adult age spectrum. This study extends prior work linking loneliness to depression by showing that a broad range of social relationship domains are associated with psychological well-being.

Crossing borders: Ethnic minorities matter? A meta analytic examionation of the alliance-outcome relationship

Objectives: The purpose of this meta analysis was to examine the moderating impact of substance use disorder as inclusion/exclusion criterion as well as the percentage of racial/ethnic minorities on the strength of the alliance-outcome relationship in psychotherapy. It was hypothesized that the presence of a dsm axis i substance use disorders as a criterion and the presence of racial/ethnic minority as a psychosocial indicator are confounded client factors reducing the relationship between alliance and outcome. Methods: A random effects restricted maximum-likelihood estimator was used for omnibus and moderator models (k = 94). results: the presence of (a) substance use disorder and, (b) racial/ethnic minorities (overall and specific to african americans) partially moderated the alliance-outcome correlation. The percentage of substance use disorders and racial/ethnic minority status was highly correlated. Conclusions: Socio-cultural contextual variables should be considered along with dsm axis i diagnosis of substance use disorders in analyzing and interpreting mechanisms of change.

Dominance and the maintenance of polymorphism in multiallelic migration-selection models with two demes

The maintenance of genetic variation in a spatially heterogeneous environment has been one of the main research themes in theoretical population genetics. Despite considerable progress in understanding the consequences of spatially structured environments on genetic variation, many problems remain unsolved. One of them concerns the relationship between the number of demes, the degree of dominance, and the maximum number of alleles that can be maintained by selection in a subdivided population. In this work, we study the potential of maintaining genetic variation in a two-deme model with deme-independent degree of intermediate dominance, which includes absence of G x E interaction as a special case. We present a thorough numerical analysis of a two-deme three-allele model, which allows us to identify dominance and selection patterns that harbor the potential for stable triallelic equilibria. The information gained by this approach is then used to construct an example in which existence and asymptotic stability of a fully polymorphic equilibrium can be proved analytically. Noteworthy, in this example the parameter range in which three alleles can coexist is maximized for intermediate migration rates. Our results can be interpreted in a specialist-generalist context and (among others) show when two specialists can coexist with a generalist in two demes if the degree of dominance is deme independent and intermediate. The dominance relation between the generalist allele and the specialist alleles play a decisive role. We also discuss linear selection on a quantitative trait and show that G x E interaction is not necessary for the maintenance of more than two alleles in two demes.

Motive-Oriented Psychotherapeutic Relationship Facing a Patient Presenting with Narcissistic Personality Disorder: A Case Study

Motive-oriented therapeutic relationship (MOTHER), a prescriptive concept based on an integrative form of case formulation, the Plan Analysis (PA) method (Caspar, in: Eells (ed.), Handbook of psychotherapy case formulations, 2007), has shown to be of particular relevance for the treatment of patients presenting with personality disorders, in particular contributing to better therapeutic outcome and to a more constructive development of the therapeutic alliance over time (Kramer et al., J Nerv Ment Dis 199:244–250, 2011). Several therapy models refer to MOTHER as intervention principle with regard to borderline and Narcissistic Personality Disorder (NPD) (Sachse et al., Clarification-oriented psychotherapy of narcissistic personality disorder, 2011; Caspar and Berger, in: Dulz et al. (eds.), Handbuch der Borderline-Störungen, 2011). The present case study discusses the case of Mark, a 40-year-old patient presenting with NPD, along with anxious, depressive and anger problems. This patient underwent a seven-session long pre-therapy process, based on psychiatric and psychotherapeutic principles complemented with PA and MOTHER, in preparation for further treatment. MOTHER will be illustrated with patient–therapist verbatim from session 4 and the links between MOTHER and confrontation techniques will be discussed in the context of process-outcome hypotheses, in particular the effect of MOTHER on symptom reduction.

Elucidating the Functional Relationship Between Working Memory Capacity and Psychometric Intelligence: A Fixed-Links Modeling Approach for Experimental Repeated-Measures Designs

Numerous studies reported a strong link between working memory capacity (WMC) and fluid intelligence (Gf), although views differ in respect to how close these two constructs are related to each other. In the present study, we used a WMC task with five levels of task demands to assess the relationship between WMC and Gf by means of a new methodological approach referred to as fixed-links modeling. Fixed-links models belong to the family of confirmatory factor analysis (CFA) and are of particular interest for experimental, repeated-measures designs. With this technique, processes systematically varying across task conditions can be disentangled from processes unaffected by the experimental manipulation. Proceeding from the assumption that experimental manipulation in a WMC task leads to increasing demands on WMC, the processes systematically varying across task conditions can be assumed to be WMC-specific. Processes not varying across task conditions, on the other hand, are probably independent of WMC. Fixed-links models allow for representing these two kinds of processes by two independent latent variables. In contrast to traditional CFA where a common latent variable is derived from the different task conditions, fixed-links models facilitate a more precise or purified representation of the WMC-related processes of interest. By using fixed-links modeling to analyze data of 200 participants, we identified a non-experimental latent variable, representing processes that remained constant irrespective of the WMC task conditions, and an experimental latent variable which reflected processes that varied as a function of experimental manipulation. This latter variable represents the increasing demands on WMC and, hence, was considered a purified measure of WMC controlled for the constant processes. Fixed-links modeling showed that both the purified measure of WMC (β = .48) as well as the constant processes involved in the task (β = .45) were related to Gf. Taken together, these two latent variables explained the same portion of variance of Gf as a single latent variable obtained by traditional CFA (β = .65) indicating that traditional CFA causes an overestimation of the effective relationship between WMC and Gf. Thus, fixed-links modeling provides a feasible method for a more valid investigation of the functional relationship between specific constructs.

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

BACKGROUND The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). METHODS We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. RESULTS The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. CONCLUSIONS Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

Global models of planet formation and evolution

Despite the strong increase in observational data on extrasolar planets, the processes that led to the formation of these planets are still not well understood. However, thanks to the high number of extrasolar planets that have been discovered, it is now possible to look at the planets as a population that puts statistical constraints on theoretical formation models. A method that uses these constraints is planetary population synthesis where synthetic planetary populations are generated and compared to the actual population. The key element of the population synthesis method is a global model of planet formation and evolution. These models directly predict observable planetary properties based on properties of the natal protoplanetary disc, linking two important classes of astrophysical objects. To do so, global models build on the simplified results of many specialized models that address one specific physical mechanism. We thoroughly review the physics of the sub-models included in global formation models. The sub-models can be classified as models describing the protoplanetary disc (of gas and solids), those that describe one (proto)planet (its solid core, gaseous envelope and atmosphere), and finally those that describe the interactions (orbital migration and N-body interaction). We compare the approaches taken in different global models, discuss the links between specialized and global models, and identify physical processes that require improved descriptions in future work. We then shortly address important results of planetary population synthesis like the planetary mass function or the mass-radius relationship. With these statistical results, the global effects of physical mechanisms occurring during planet formation and evolution become apparent, and specialized models describing them can be put to the observational test. Owing to their nature as meta models, global models depend on the results of specialized models, and therefore on the development of the field of planet formation theory as a whole. Because there are important uncertainties in this theory, it is likely that the global models will in future undergo significant modifications. Despite these limitations, global models can already now yield many testable predictions. With future global models addressing the geophysical characteristics of the synthetic planets, it should eventually become possible to make predictions about the habitability of planets based on their formation and evolution.