The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis

OBJECTIVE: To meta-analyse the diagnostic accuracy of US, CT, MRI and (1)H-MRS for the evaluation of hepatic steatosis. METHODS: From a comprehensive literature search in MEDLINE, EMBASE, CINAHL and Cochrane (up to November 2009), articles were selected that investigated the diagnostic performance imaging techniques for evaluating hepatic steatosis with histopathology as the reference standard. Cut-off values for the presence of steatosis on liver biopsy were subdivided into four groups: (1) >0, >2 and >5% steatosis; (2) >10, >15 and >20%; (3) >25, >30 and >33%; (4) >50, >60 and >66%. Per group, summary estimates for sensitivity and specificity were calculated. The natural-logarithm of the diagnostic odds ratio (lnDOR) was used as a single indicator of test performance. RESULTS: 46 articles were included. Mean sensitivity estimates for subgroups were 73.3-90.5% (US), 46.1-72.0% (CT), 82.0-97.4% (MRI) and 72.7-88.5% ((1)H-MRS). Mean specificity ranges were 69.6-85.2% (US), 88.1-94.6% (CT), 76.1-95.3% (MRI) and 92.0-95.7% ((1)H-MRS). Overall performance (lnDOR) of MRI and (1)H-MRS was better than that for US and CT for all subgroups, with significant differences in groups 1 and 2. CONCLUSION: MRI and (1)H-MRS can be considered techniques of choice for accurate evaluation of hepatic steatosi

Teacher Wellbeing: The Importance of Teacher–Student Relationships

Many studies have examined the importance of teacher-student relationships for the development of children. Much less is known, however, about how these relationships impact the professional and personal lives of teachers. This review considers the importance of teacher-student relationships for the wellbeing of teachers guided by the Transactional Model of Stress and Coping of Lazarus (1991). Based on theories on interpersonal relationships, it is postulated that teachers have a basic need for relatedness with the students in their class that originates from the close proximity between teacher and student. It is discussed that teachers internalize experiences with students in representational models of relationships that guide emotional responses in daily interactions with students, and changes teacher wellbeing in the long run. In addition, the notion of mental representations of relationships at different levels of generalization could offer a window to understand how individual teacher-student relationships may affect the professional and personal self-esteem of teachers. Lastly, it is argued that the influence of student misbehavior on teacher stress may be more fully understood from a relationship perspective. The review shows that few studies have directly tested these propositions and offers suggestions for future research

Challenges and opportunities for integrating lake ecosystem modelling approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem model

Microbial Ecology of Lake Kivu

peer reviewedWe review available data on archaea, bacteria and small eukaryotes in an attempt to provide a general picture of microbial diversity, abundances and microbe-driven processes in Lake Kivu surface and intermediate waters (ca. 0–100 m). The various water layers present contrasting physical and chemical properties and harbour very different microbial communities supported by the vertical redox structure. For instance, we found a clear vertical segregation of archaeal and bacterial assemblages between the oxic and the anoxic zone of the surface waters. The presence of specific bacterial (e.g. Green Sulfur Bacteria) and archaeal (e.g. ammonia-oxidising archaea) communities and the prevailing physico-chemical conditions point towards the redoxcline as the most active and metabolically diverse water layer. The archaeal assemblage in the surface and intermediate water column layers was mainly composed by the phylum Crenarchaeota , by the recently defined phylum Thaumarchaeota and by the phylum Euryarchaeota . In turn, the bacterial assemblage comprised mainly ubiquitous members of planktonic assemblages of freshwater environments (Actinobacteria, Bacteroidetes and Betaproteobacteria among others) and other less commonly retrieved phyla (e.g. Chlorobi, Clostridium and Deltaproteobacteria). The community of small eukaryotes (<5 µm) mainly comprised Stramenopiles , Alveolata , Cryptophyta , Chytridiomycota , Kinetoplastea and Choanoflagellida, by decreasing order of richness. The total prokaryotic abundance ranged between 0.5 × 10^6 and 2.0 × 10^6 cells mL−1 , with maxima located in the 0–20 m layer, while phycoerythrin-rich Synechococcus-like picocyanobacteria populations were comprised between 0.5 × 10^5 and 2.0 × 10^5 cells mL−1 in the same surface layer. Brown-coloured species of Green Sulfur Bacteria permanently developed at 11m depth in Kabuno Bay and sporadically in the anoxic waters of the lower mixolimnion of the main basin. The mean bacterial production was estimated to 336 mg C m−2 day−1 . First estimates of the re-assimilation by bacterioplankton of dissolved organic matter excreted by phytoplankton showed high values of dissolved primary production (ca. 50% of total production). The bacterial carbon demand can totally be fuelled by phytoplankton production. Overall, recent studies have revealed a high microbial diversity in Lake Kivu, and point towards a central role of microbes in the biogeochemical and ecological functioning of the surface layers, comprising the mixolimnion and the upper chemocline