Maria H. Jensen

Molecular phylogeny of selected species of the order dinophysiales (Dinophyceae) - testing the hypothesis of a dinophysioid radiation.

Almost 80 years ago, a radiation scheme based on structural resemblance was first outlined for the marine order Dinophysiales. This hypothetical radiation illustrated the relationship between the dinophysioid genera and included several independent, extant lineages. Subsequent studies have supplied additional information on morphology and ecology to these evolutionary lineages. We have for the first time combined morphological information with molecular phylogenies to test the dinophysioid radiation hypothesis in a modern context. Nuclear‐encoded LSU rDNA sequences including domains D1‐D6 from 27 species belonging to Dinophysis Ehrenb., Ornithocercus F. Stein, Phalacroma F. Stein, Amphisolenia F. Stein, Citharistes F. Stein, and Histioneis F. Stein were obtained from the Indian Ocean. Previously, LSU rDNA has only been determined from one of these. In Bayesian analyses, Amphisolenia formed a long basal clade to the other dinophysioids. These diverged into two separate lineages, the first comprised species with a classical Phalacroma outline, also including the type species P. porodictyum F. Stein. Thus, we propose to reinstate the genus Phalacroma. The relationship between the genera in the second lineage was not well resolved. However, the molecular phylogeny supported monophyly of Histioneis and Citharistes and showed the genus Dinophysis to be polyphyletic and in need of a taxonomic revision. Species of Ornithocercus grouped with Citharistes, but this relationship remained unresolved. The phylogenetic trees furthermore revealed convergent evolution of several morphological characters in the dinophysioids. According to the molecular data, the dinophysioids appeared to have evolved quite differently from the radiation schemes previously hypothesized. Four dinophysioid species had identical LSU rDNA sequences to other well‐established species.

Eurasian ice-sheet interaction in northwestern Russia throughout the late Quaternary

Sediment successions from the Kanin Peninsula and Chyoshskaya Bay in northwestern Russia contain information on the marginal behaviour of all major ice sheets centred in Scandinavia, the Barents Sea and the Kara Sea during the Eemian - Weichselian. Extensive luminescence dating of regional lithostratigraphical units, supported by biostratigraphical evidence, identifies four major ice advances at 100 - 90, 70 - 65, 55 - 45 and 20 - 18 kyr ago interbedded with lacustrine, glaciolacustrine and marine sediments. The widespread occurrence of marine tidal sediments deposited c. 65 - 60 kyr ago allows a stratigraphical division of the Middle Weichselian Barents Sea and Kara Sea ice sheets into two shelf-based glaciations separated by almost complete deglaciation. The first ice dispersal centre was in the Barents Sea and thereafter in the Kara Sea. It is possible to extract both flow patterns from ice marginal landforms inside the southward termination. Accordingly, it is proposed that the Markhida line and its western continuation are asynchronous and originate from two separate glaciations before and after the marine transgression. The marine sedimentation occurred during a eustatic sea-level rise of up to 20 m/1000 yr, i. e. the Mezen Transgression. We speculate that the rapid eustatic sea-level rise triggered a collapse of the Barents Sea Ice Sheet at the MIS ( Marine Isotope Stage) 4 to 3 transition. This is motivated by lack of an early marine highstand, the timing of events, and the marginal position of Arkhangelsk relative to open marine conditions. (Less)

Using nuclear-encoded LSU and SSU rDNA sequences to identify the eukaryotic endosymbiont in Amphisolenia bidentata (Dinophyceae).

The marine dinoflagellate Amphisolenia bidentata possesses complete intracellular symbionts of prokaryotic and eukaryotic origin. This was confirmed ultrastructurally little over 20 years ago when it was showed that the eukaryotic endosymbiont had a nucleus, a chloroplast and mitochondria. We collected Amphisolenia bidentata cells in the Indian Ocean and the identity of the eukaryotic endosymbionts was investigated using both microscopical and molecular methods. Individual specimens of Amphisolenia bidentata were identified by light microscopy and selected for single-cell PCR. Host and endosymbiont nuclear-encoded LSU and SSU rDNA sequences were determined by PCR cloning. Blast searches showed the endosymbiont LSU sequence to have affinity to Pelagophyceae, an algal class within Chromalveolata that also includes dinoflagellates. Since more SSU rDNA sequences from pelagophytes are available we performed a SSU based phylogeny of chromalveolates. The eukaryotic endosymbiont clustered within a clade comprising flagellated and coccoid pelagophytes whereas Amphisolenia bidentata formed a sister taxon to other dinophysioids. Molecular data therefore resolved the endosymbiont in A. bidentata being a pelagophyte and thus identified the ninth novel chloroplast type in dinoflagellates and a new species association. Based on sequence divergence estimates and phylogenetic inference the endosymbiont in A. bidentata likely represents an undescribed genus of pelagophytes.

Two subgroups of antipsychotic-naive, first-episode schizophrenia patients identified with a Gaussian mixture model on cognition and electrophysiology

Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically different disease subgroups. We applied machine learning algorithms on measures of electrophysiology and cognition to identify potential subgroups of schizophrenia. Next, we explored subgroup differences regarding treatment response. Sixty-six antipsychotic-naive first-episode schizophrenia patients and sixty-five healthy controls underwent extensive electrophysiological and neurocognitive test batteries. Patients were assessed on the Positive and Negative Syndrome Scale (PANSS) before and after 6 weeks of monotherapy with the relatively selective D2 receptor antagonist, amisulpride (280.3±159 mg per day). A reduced principal component space based on 19 electrophysiological variables and 26 cognitive variables was used as input for a Gaussian mixture model to identify subgroups of patients. With support vector machines, we explored the relation between PANSS subscores and the identified subgroups. We identified two statistically distinct subgroups of patients. We found no significant baseline psychopathological differences between these subgroups, but the effect of treatment in the groups was predicted with an accuracy of 74.3% (P=0.003). In conclusion, electrophysiology and cognition data may be used to classify subgroups of schizophrenia patients. The two distinct subgroups, which we identified, were psychopathologically inseparable before treatment, yet their response to dopaminergic blockade was predicted with significant accuracy. This proof of principle encourages further endeavors to apply data-driven, multivariate and multimodal models to facilitate progress from symptom-based psychiatry toward individualized treatment regimens.

The impact of schizophrenia and intelligence on the relationship between age and brain volume

Age has been shown to have an impact on both grey (GM) and white matter (WM) volume, with a steeper slope of age-related decline in schizophrenia compared to healthy controls. In schizophrenia, the relation between age and brain volume is further complicated by factors such as lower intelligence, antipsychotic medication, and cannabis use, all of which have been shown to have independent effects on brain volume. In a study of first-episode, antipsychotic-naïve schizophrenia patients (N = 54) and healthy controls (N = 56), we examined the effects of age on whole brain measures of GM and WM volume, and whether these relationships were moderated by schizophrenia and intelligence (IQ). Secondarily, we examined lifetime cannabis use as a moderator of the relationship between age and brain volume. Schizophrenia patients had lower GM volumes than healthy controls but did not differ on WM volume. We found an age effect on GM indicating that increasing age was associated with lower GM volumes, which did not differ between groups. IQ did not have a direct effect on GM, but showed a trend-level interaction with age, suggesting a greater impact of age with lower IQ. There were no age effects on WM volume, but a direct effect of IQ, with higher IQ showing an association with larger WM volume. Lifetime cannabis use did not alter these findings significantly. This study points to effects of schizophrenia on GM early in the illness, before antipsychotic treatment is initiated, suggesting that WM changes may occur later in the disease process.