Impaired balance in developmental dyslexia? A meta-analysis of the contending evidence

Background: Developmental dyslexia is typically defined by deficits in phonological skills, but it is also associated with anomalous performance on measures of balance. Although balance assessments are included in several screening batteries for dyslexia, the association between impairments in literacy and deficits in postural stability could be due to the high co-occurrence of dyslexia with other developmental disorders in which impairments of motor behaviour are also prevalent. Methods: We identified 17 published studies that compared balance function between dyslexia and control samples and obtained effect-sizes for each. Contrast and association analyses were used to quantify the influence of hypothesised moderator variables on differences in effects across studies. Results: The mean effect-size of the balance deficit in dyslexia was .64 (95% CI = .44-.78) with heterogeneous findings across the population of studies. Probable co-occurrence of other developmental disorders and variability in intelligence scores in the dyslexia samples were the strongest moderator variables of effect-size. Conclusions: Balance deficits are associated with dyslexia, but these effects are apparently more strongly related to third variables other than to reading ability. Deficits of balance may indicate increased risk of developmental disorder, but are unlikely to be uniquely associated with dyslexia.

Language against the odds, or rather not:the weak central coherence hypothesis and language

EV is a child with a talent for learning language combined with Asperger syndrome. EV’s talent is evident in the unusual circumstances of her acquisition of both her first (Bulgarian) and second (German) languages and the unique patterns of both receptive and expressive language (in both the L1 and L2), in which she shows subtle dissociations in competence and performance consistent with an uneven cognitive profile of skills and abilities. We argue that this case provides support for theories of language learning and usage that require more general underlying cognitive mechanisms and skills. One such account, the Weak Central Coherence (WCC) hypothesis of autism, provides a plausible framework for the interpretation of the simultaneous co-occurrence of EV’s particular pattern of cognitive strengths and weaknesses. Furthermore, we show that specific features of the uneven cognitive profile of Asperger syndrome can help explain the observed language talent displayed by EV. Thus, rather than demonstrating a case where language learning takes place despite the presence of deficits, EV’s case illustrates how a pattern of strengths within this profile can specifically promote language learning.

Are poor mathematics skills associated with visual deficits in temporal processing?

Developmental learning disabilities such as dyslexia and dyscalculia have a high rate of co-occurrence in pediatric populations, suggesting that they share underlying cognitive and neurophysiological mechanisms. Dyslexia and other developmental disorders with a strong heritable component have been associated with reduced sensitivity to coherent motion stimuli, an index of visual temporal processing on a millisecond time-scale. Here we examined whether deficits in sensitivity to visual motion are evident in children who have poor mathematics skills relative to other children of the same age. We obtained psychophysical thresholds for visual coherent motion and a control task from two groups of children who differed in their performance on a test of mathematics achievement. Children with math skills in the lowest 10% in their cohort were less sensitive than age-matched controls to coherent motion, but they had statistically equivalent thresholds to controls on a coherent form control measure. Children with mathematics difficulties therefore tend to present a similar pattern of visual processing deficit to those that have been reported previously in other developmental disorders. We speculate that reduced sensitivity to temporally defined stimuli such as coherent motion represents a common processing deficit apparent across a range of commonly co-occurring developmental disorders.

The role of pragmatics for grammatical change: the case of preverbal non

What is the role of pragmatics in the evolution of grammatical paradigms? It is to maintain marked candidates that may come to be the default expression. This perspective is validated by the Jespersen cycle, where the standard expression of sentential negation is renewed as pragmatically marked negatives achieve default status. How status changes are effected, however, remains to be documented. This is what is achieved in this paper that looks at the evolution of preverbal negative non in Old and Middle French. The negative, which categorically marks pragmatic activation (Dryer 1996) with finite verbs in Old French, loses this value when used with non-finite verbs in Middle French. This process is accompanied by competing semantic reanalyses of the distribution of infinitives negated in this way, and by the co-occurrence with a greater lexical variety of verbs. The absence of pragmatic contribution should lead the marker to take on the role of default, which is already fulfilled by a well-established ne ... pas, pushing non to decline. Hard empirical evidence is thus provided that validates the assumed role of pragmatics in the Jespersen cycle, supporting the general view of pragmatics as supporting alternative candidates that may or may not achieve default status in the evolution of a grammatical paradigm.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent on conservation interventions. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We explore this issue with a simulation study involving two agents sequentially purchasing land for the conservation of multiple species using three scenarios comprising either divergent or partially overlapping objectives between the agents. The first scenario investigates the situation where both agents are targeting different sets of threatened species. The second and third scenarios represent a case where a government agency attempts to implement a complementary conservation network representing 200 species, while a non-government organisation is focused on achieving additional protection for the ten rarest species. Simulated input data was generated using distributions taken from real data to model the cost of parcels, and the rarity and co-occurrence of species. We investigated three types of collaborative interactions between agents: acting in isolation, sharing information and pooling resources with the third option resulting in the agents combining their resources and effectively acting as a single entity. In each scenario we determine the cost savings when an agent moves from acting in isolation to either sharing information or pooling resources with the other agent. The model demonstrates how the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. Our model demonstrates a method for determining the range of costs that would result in collaboration providing an efficient use of scarce conservation resources.

Automatic summary assessment for intelligent tutoring systems

Summary writing is an important part of many English Language Examinations. As grading students' summary writings is a very time-consuming task, computer-assisted assessment will help teachers carry out the grading more effectively. Several techniques such as latent semantic analysis (LSA), n-gram co-occurrence and BLEU have been proposed to support automatic evaluation of summaries. However, their performance is not satisfactory for assessing summary writings. To improve the performance, this paper proposes an ensemble approach that integrates LSA and n-gram co-occurrence. As a result, the proposed ensemble approach is able to achieve high accuracy and improve the performance quite substantially compared with current techniques. A summary assessment system based on the proposed approach has also been developed.

Contextual semantics for sentiment analysis of Twitter

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.

Topic Segmentation: How Much Can We Do by Counting Words and Sequences of Words

In this paper, we present an innovative topic segmentation system based on a new informative similarity measure that takes into account word co-occurrence in order to avoid the accessibility to existing linguistic resources such as electronic dictionaries or lexico-semantic databases such as thesauri or ontology. Topic segmentation is the task of breaking documents into topically coherent multi-paragraph subparts. Topic segmentation has extensively been used in information retrieval and text summarization. In particular, our architecture proposes a language-independent topic segmentation system that solves three main problems evidenced by previous research: systems based uniquely on lexical repetition that show reliability problems, systems based on lexical cohesion using existing linguistic resources that are usually available only for dominating languages and as a consequence do not apply to less favored languages and finally systems that need previously existing harvesting training data. For that purpose, we only use statistics on words and sequences of words based on a set of texts. This solution provides a flexible solution that may narrow the gap between dominating languages and less favored languages thus allowing equivalent access to information.

Patterns of diagnostic comorbidity in children and adolescents with anxiety

Comorbidity is defined as the co-occurrence of two or more psychological disorders and has been identified as one of the most pressing issues facing child psychologists today. Unfortunately, research on comorbidity in anxious children is rare. The purpose of this research was to examine how specific comorbid patterns in children and adolescents referred with anxiety disorders affected clinical presentation. In addition, the effects of gender, age and total number of diagnoses were also examined.^ Three hundred fifty-five children and adolescents (145 girls and 210 boys, hereafter referred to as "children") aged 6 to 17 who presented to the Child Anxiety and Phobia Program during the years 1987 through 1996 were assessed through a structured clinical interview administered to both the children and their families. Based on information from both children and parents, children were assigned up to five DSM diagnoses. Global ratings of severity were also obtained. While children were interviewed, parents completed a number of questionnaires pertaining to their child's overall functioning, anxiety, thoughts and behaviors. Similarly, while parents were interviewed, children completed a number of self-report questionnaires concerning their own thoughts, feelings and behaviors.^ In general, children with only anxiety disorders were rated as severe as children who met criteria for both anxiety and externalizing disorders. Children with both anxiety and externalizing disorders were mostly young (i.e. age 6 through 11) and mostly male. These children tended to rate themselves (and be rated by their parents) equally as anxious as children with only anxiety disorders. Global ratings of severity tended to be associated with the type of comorbid pattern versus the number of diagnoses assigned to a child. The theoretical, development and clinical implications of these findings will be discussed. ^

N2 fixation in eddies of the eastern tropical South Pacific Ocean

Mesoscale eddies play a major role in controlling ocean biogeochemistry. By impacting nutrient availability and water column ventilation, they are of critical importance for oceanic primary production. In the eastern tropical South Pacific Ocean off Peru, where a large and persistent oxygen-deficient zone is present, mesoscale processes have been reported to occur frequently. However, investigations into their biological activity are mostly based on model simulations, and direct measurements of carbon and dinitrogen (N2) fixation are scarce. We examined an open-ocean cyclonic eddy and two anticyclonic mode water eddies: a coastal one and an open-ocean one in the waters off Peru along a section at 16°S in austral summer 2012. Molecular data and bioassay incubations point towards a difference between the active diazotrophic communities present in the cyclonic eddy and the anticyclonic mode water eddies. In the cyclonic eddy, highest rates of N2 fixation were measured in surface waters but no N2 fixation signal was detected at intermediate water depths. In contrast, both anticyclonic mode water eddies showed pronounced maxima in N2 fixation below the euphotic zone as evidenced by rate measurements and geochemical data. N2 fixation and carbon (C) fixation were higher in the young coastal mode water eddy compared to the older offshore mode water eddy. A co-occurrence between N2 fixation and biogenic N2, an indicator for N loss, indicated a link between N loss and N2 fixation in the mode water eddies, which was not observed for the cyclonic eddy. The comparison of two consecutive surveys of the coastal mode water eddy in November 2012 and December 2012 also revealed a reduction in N2 and C fixation at intermediate depths along with a reduction in chlorophyll by half, mirroring an aging effect in this eddy. Our data indicate an important role for anticyclonic mode water eddies in stimulating N2 fixation and thus supplying N offshore.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Radiotherapy Assessment Using Diffusion Weighted MRI

Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.

Parental Bereavement: Looking Beyond Grief - Challenges and Health

For most parents there is no imaginable event more devastating than the death of their child. Nevertheless, while bereaved parents grieve they are also expected to carry on with their life. The day-to-day activities that were once routine for these parents may now be challenging due to the emotional turmoil they are experiencing. To date parental bereavement has been described as complex, intense, individualized, and life-long and their grief responses are interwoven with their daily activities, but the nature of their daily life challenges are not known.

This dissertation highlights the significance of how parents respond to their bereavement challenges because bereaved parents have higher morbidity and mortality rates than non-bereaved parents or adults who have lost their spouse or parents. Many bereaved parents in their daily routines include activities that allow them to maintain a relationship with their deceased child. These behaviors have been described as “continuing bonds”, but with this dissertation the continuing bonds concept is analyzed to provide a clear conceptual definition, which can be used for future research.

Using the Adaptive Leadership Framework as the theoretical lens and a mixed method, multiple case study design, the primary study in this dissertation aims to provides knowledge about the challenges parents face in the first six months following the death of their child, the work they use to meet these challenges, and the co-occurrence of the challenges, and work with their health status. Bereaved parents challenges are unique to their individual circumstances, complex, interrelated and adaptive, as they have no easy fix. Their challenges were pertaining to their everyday life without their child and classified as challenges related to: a) grief, b) continuing bonds, c) life demands, d) health concerns, f) interactions, and g) gaps in the health care system. Parents intuitively responded to the challenges and attempted to care for themselves. However, the role of the healthcare system to assist bereaved parents during this stressful time so that their health is not negatively impacted was also recognized. This study provides a foundation about parental bereavement challenges and related work that can lead to the development and testing of interventions that are tailored to address the challenges with a goal of improving bereaved parents health outcomes.

Nitrogen fixation and nitrogen gene abundance of METEOR cruises M77/3 and M77/4

Nitrogen fixation, the biological reduction of dinitrogen gas (N2) to ammonium (NH4+), is quantitatively the most important external source of new nitrogen (N) to the open ocean. Classically, the ecological niche of oceanic N2 fixers (diazotrophs) is ascribed to tropical oligotrophic surface waters, often depleted in fixed N, with a diazotrophic community dominated by cyanobacteria. Although this applies for large areas of the ocean, biogeochemical models and phylogenetic studies suggest that the oceanic diazotrophic niche may be much broader than previously considered, resulting in major implications for the global N-budget. Here, we report on the composition, distribution and abundance of nifH, the functional gene marker for N2 fixation. Our results show the presence of eight clades of diazotrophs in the oxygen minimum zone (OMZ) off Peru. Although proteobacterial clades dominated overall, two clusters affiliated to spirochaeta and archaea were identified. N2 fixation was detected within OMZ waters and was stimulated by the addition of organic carbon sources supporting the view that non-phototrophic diazotrophs were actively fixing dinitrogen. The observed co-occurrence of key functional genes for N2 fixation, nitrification, anammox and denitrification suggests that a close spatial coupling of N-input and N-loss processes exists in the OMZ off Peru. The wide distribution of diazotrophs throughout the water column adds to the emerging view that the habitat of marine diazotrophs can be extended to low oxygen/high nitrate areas. Furthermore, our statistical analysis suggests that NO2- and PO43- are the major factors affecting diazotrophic distribution throughout the OMZ. In view of the predicted increase in ocean deoxygenation resulting from global warming, our findings indicate that the importance of OMZs as niches for N2 fixation may increase in the futur

Nitrite consumption and associated isotope changes during a river flood event in the Elbe river

In oceans, estuaries, and rivers, nitrification is an important nitrate source, and stable isotopes of nitrate are often used to investigate recycling processes (e.g. remineralisation, nitrification) in the water column. Nitrification is a two-step process, where ammonia is oxidised via nitrite to nitrate. Nitrite usually does not accumulate in natural environments, which makes it difficult to study the single isotope effect of ammonia oxidation or nitrite oxidation in natural systems. However, during an exceptional flood in the Elbe River in June 2013, we found a unique co-occurrence of ammonium, nitrite, and nitrate in the water column, returning towards normal summer conditions within 1 week. Over the course of the flood, we analysed the evolution of d15N-[NH4]+ and d15N-[NO2]- in the Elbe River. In concert with changes in suspended particulate matter (SPM) and d15N SPM, as well as nitrate concentration, d15N-NO3 - and d18O-[NO3] -, we calculated apparent isotope effects during net nitrite and nitrate consumption. During the flood event, > 97 % of total reactive nitrogen was nitrate, which was leached from the catchment area and appeared to be subject to assimilation. Ammonium and nitrite concentrations increased to 3.4 and 4.4 µmol/l, respectively, likely due to remineralisation, nitrification, and denitrification in the water column. d15N-[NH4]+ values increased up to 12 per mil, and d15N-[NO2]- ranged from -8.0 to -14.2 per mil. Based on this, we calculated an apparent isotope effect 15-epsilon of -10.0 ± 0.1 per mil during net nitrite consumption, as well as an isotope effect 15-epsilon of -4.0 ± 0.1 per mil and 18-epsilon of -5.3 ± 0.1 per mil during net nitrate consumption. On the basis of the observed nitrite isotope changes, we evaluated different nitrite uptake processes in a simple box model. We found that a regime of combined riparian denitrification and 22 to 36 % nitrification fits best with measured data for the nitrite concentration decrease and isotope increase.