Molecular Adaptation of rbcL in the Heterophyllous Aquatic Plant Potamogeton

Heterophyllous aquatic plants show marked phenotypic plasticity. They adapt to environmental changes by producing different leaf types: submerged, floating and terrestrial leaves. By contrast, homophyllous plants produce only submerged leaves and grow entirely underwater. Heterophylly and submerged homophylly evolved under selective pressure modifying the species-specific optima for photosynthesis, but little is known about the evolutionary outcome of habit. Recent evolutionary analyses suggested that rbcL, a chloroplast gene that encodes a catalytic subunit of RuBisCO, evolves under positive selection in most land plant lineages. To examine the adaptive evolutionary process linked to heterophylly or homophylly, we analyzed positive selection in the rbcL sequences of ecologically diverse aquatic plants, Japanese Potamogeton.Phylogenetic and maximum likelihood analyses of codon substitution models indicated that Potamogeton rbcL has evolved under positive Darwinian selection. The positive selection has operated specifically in heterophyllous lineages but not in homophyllous ones in the branch-site models. This suggests that the selective pressure on this chloroplast gene was higher for heterophyllous lineages than for homophyllous lineages. The replacement of 12 amino acids occurred at structurally important sites in the quaternary structure of RbcL, two of which (residue 225 and 281) were identified as potentially under positive selection.Our analysis did not show an exact relationship between the amino acid replacements and heterophylly or homophylly but revealed that lineage-specific positive selection acted on the Potamogeton rbcL. The contrasting ecological conditions between heterophyllous and homophyllous plants have imposed different selective pressures on the photosynthetic system. The increased amino acid replacement in RbcL may reflect the continuous fine-tuning of RuBisCO under varying ecological conditions

Use of brain MRI atlases to determine boundaries of age-related pathology: the importance of statistical method

Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient's brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ± standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer's disease (AD) patients.Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55-90 years), we created: a mean ± SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients.The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25-45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes.To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we conclude that the statistical method used for construction of brain MRI atlases should be selected taking into account the population and aim under study. Parametric methods are generally robust for defining central tendencies, e.g., means, of brain structure. Nonparametric methods are advisable when studying the limits of brain structure in ageing and neurodegenerative disease

Biochemical and biophysical CO2 concentrating mechanisms in two species of freshwater macrophyte within the genus Ottelia (Hydrocharitaceae)

Two freshwater macrophytes, Ottelia alismoides and Ottelia acuminata, were grown at low (mean 5 µmol L-1) and high (mean 400 µmol L-1) CO2 concentrations under natural conditions. The ratio of PEPC to RubisCO was 1.8 in O. acuminata in both treatments. In O. alismoides, this ratio was 2.8 and 5.9 when grown at high and low CO2, respectively, as a result of a 2-fold increase of PEPC activity. The activity of PPDK was similar to and changed in-line with PEPC (1.9-fold change). The activity of the decarboxylating NADP-malic enzyme (ME) was very low in both species while NAD-ME activity was high and increased with PEPC activity in O. alismoides. These results suggest that O. alismoides might perform a type of C4 metabolism with NAD-ME decarboxylation, despite lacking Kranz anatomy. The C4-activity was still present at high CO2 suggesting that it could be constitutive. O. alismoides at low CO2 showed diel acidity variation of up to 34 μequiv g-1 FW indicating it may also operate a form of Crassulacean Acid Metabolism (CAM). pH-drift experiments showed that both species were able to use bicarbonate. In O. acuminata, the kinetics of carbon uptake were altered by CO2 growth conditions, unlike in O. alismoides. Thus the two species appear to regulate their carbon concentrating mechanisms differently in response to changing CO2. The Hydrocharitaceae have many species with evidence for C4, CAM, or a metabolism involving organic acids, and are worthy of further study

Consensus classification of posterior cortical atrophy

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCAwere developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndromeand disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.</p