Characterization of the effect of nitrogen deficiency on above-ground plant phenotypes in relation to root complexity in maize

Nitrogen (N) is an essential plant nutrient in maize production, and if considering only natural sources, is often the limiting factor world-wide in terms of a plant’s grain yield. For this reason, many farmers around the world supplement available soil N with synthetic man-made forms. Years of over-application of N fertilizer have led to increased N in groundwater and streams due to leaching and run-off from agricultural sites. In the Midwest Corn Belt much of this excess N eventually makes its way to the Gulf of Mexico leading to eutrophication (increase of phytoplankton) and a hypoxic (reduced oxygen) dead zone. Growing concerns about these types of problems and desire for greater input use efficiency have led to demand for crops with improved N use efficiency (NUE) to allow reduced N fertilizer application rates and subsequently lower N pollution. It is well known that roots are responsible for N uptake by plants, but it is relatively unknown how root architecture affects this ability. This research was conducted to better understand the influence of root complexity (RC) in maize on a plant’s response to N stress as well as the influence of RC on other above-ground plant traits. Thirty-one above-ground plant traits were measured for 64 recombinant inbred lines (RILs) from the intermated B73 & Mo17 (IBM) population and their backcrosses (BCs) to either parent, B73 and Mo17, under normal (182 kg N ha-1) and N deficient (0 kg N ha-1) conditions. The RILs were selected based on results from an earlier experiment by Novais et al. (2011) which screened 232 RILs from the IBM to obtain their root complexity measurements. The 64 selected RILs were comprised of 31 of the lowest complexity RILs (RC1) and 33 of the highest complexity RILs (RC2) in terms of root architecture (characterized as fractal dimensions). The use of the parental BCs classifies the experiment as Design III, an experimental design developed by Comstock and Robinson (1952) which allows for estimation of dominance significance and level. Of the 31 traits measured, 12 were whole plant traits chosen due to their documented response to N stress. The other 19 traits were ear traits commonly measured for their influence on yield. Results showed that genotypes from RC1 and RC2 significantly differ for several above-ground phenotypes. We also observed a difference in the number and magnitude of N treatment responses between the two RC classes. Differences in phenotypic trait correlations and their change in response to N were also observed between the RC classes. RC did not seem to have a strong correlation with calculated NUE (ΔYield/ΔN). Quantitative genetic analysis utilizing the Design III experimental design revealed significant dominance effects acting on several traits as well as changes in significance and dominance level between N treatments. Several QTL were mapped for 26 of the 31 traits and significant N effects were observed across the majority of the genome for some N stress indicative traits (e.g. stay-green). This research and related projects are essential to a better understanding of plant N uptake and metabolism. Understanding these processes is a necessary step in the progress towards the goal of breeding for better NUE crops.

Safety and complexity: the inter-departmental threats to patient safety in the operating department

Purpose: Current thinking about ‘patient safety’ emphasises the causal relationship between the work environment and the delivery of clinical care. This research draws on the theory of Normal Accidents to extend this analysis and better understand the ‘organisational factors’ that threaten safety. Methods: Ethnographic research methods were used, with observations of the operating department setting for 18 month and interviews with 80 members of hospital staff. The setting for the study was the Operating Department of a large teaching hospital in the North-West of England. Results: The work of the operating department is determined by inter-dependant, ‘tightly coupled’ organisational relationships between hospital departments based upon the timely exchange of information, services and resources required for the delivery of care. Failures within these processes, manifest as ‘breakdowns’ within inter-departmental relationships lead to situations of constraint, rapid change and uncertainty in the work of the operating department that require staff to break with established routines and work with increased time and emotional pressures. This means that staff focus on working quickly, as opposed to working safely. Conclusion: Analysis of safety needs to move beyond a focus on the immediate work environment and individual practice, to consider the more complex and deeply structured organisational systems of hospital activity. For departmental managers the scope for service planning to control for safety may be limited as the structured ‘real world’ situation of service delivery is shaped by inter-department and organisational factors that are perhaps beyond the scope of departmental management.

TcT: Tyrolean Complexity Tool

International audience

Food-Web Complexity in Guaymas Basin Hydrothermal Vents and Cold Seeps

In the Guaymas Basin, the presence of cold seeps and hydrothermal vents in close proximity, similar sedimentary settings and comparable depths offers a unique opportunity to assess and compare the functioning of these deep-sea chemosynthetic ecosystems. The food webs of five seep and four vent assemblages were studied using stable carbon and nitrogen isotope analyses. Although the two ecosystems shared similar potential basal sources, their food webs differed: seeps relied predominantly on methanotrophy and thiotrophy via the Calvin-Benson-Bassham (CBB) cycle and vents on petroleum-derived organic matter and thiotrophy via the CBB and reductive tricarboxylic acid (rTCA) cycles. In contrast to symbiotic species, the heterotrophic fauna exhibited high trophic flexibility among assemblages, suggesting weak trophic links to the metabolic diversity of chemosynthetic primary producers. At both ecosystems, food webs did not appear to be organised through predator-prey links but rather through weak trophic relationships among co-occurring species. Examples of trophic or spatial niche differentiation highlighted the importance of species-sorting processes within chemosynthetic ecosystems. Variability in food web structure, addressed through Bayesian metrics, revealed consistent trends across ecosystems. Food-web complexity significantly decreased with increasing methane concentrations, a common proxy for the intensity of seep and vent fluid fluxes. Although high fluid-fluxes have the potential to enhance primary productivity, they generate environmental constraints that may limit microbial diversity, colonisation of consumers and the structuring role of competitive interactions, leading to an overall reduction of food-web complexity and an increase in trophic redundancy. Heterogeneity provided by foundation species was identified as an additional structuring factor. According to their biological activities, foundation species may have the potential to partly release the competitive pressure within communities of low fluid-flux habitats. Finally, ecosystem functioning in vents and seeps was highly similar despite environmental differences (e.g. physico-chemistry, dominant basal sources) suggesting that ecological niches are not specifically linked to the nature of fluids. This comparison of seep and vent functioning in the Guaymas basin thus provides further supports to the hypothesis of continuity among deep-sea chemosynthetic ecosystems.

Compounds, creativity and complexity in climate change communication: the case of ‘carbon indulgences’

This article deals with climate change from a linguistic perspective. Climate change is an extremely complex issue that has exercised the minds of experts and policy makers with renewed urgency in recent years. It has prompted an explosion of writing in the media, on the internet and in the domain of popular science and literature, as well as a proliferation of new compounds around the word ‘carbon’ as a hub, such as ‘carbon indulgence’, a new compound that will be studied in this article. Through a linguistic analysis of lexical and discourse formations around such ‘carbon compounds’ we aim to contribute to a broader understanding of the meaning of climate change. Lexical carbon compounds are used here as indicators for observing how human symbolic cultures change and adapt in response to environmental threats and how symbolic innovation and transmission occurs.

The complexity in the implementation process of empowerment-based chronic kidney care: a case study

Background: This study is part of an interactive improvement intervention aimed to facilitate empowerment-based chronic kidney care using data from persons with CKD and their family members. There are many challenges to implementing empowerment-based care, and it is therefore necessary to study the implementation process. The aim of this study was to generate knowledge regarding the implementation process of an improvement intervention of empowerment for those who require chronic kidney care. Methods: A prospective single qualitative case study was chosen to follow the process of the implementation over a two year period. Twelve health care professionals were selected based on their various role(s) in the implementation of the improvement intervention. Data collection comprised of digitally recorded project group meetings, field notes of the meetings, and individual interviews before and after the improvement project. These multiple data were analyzed using qualitative latent content analysis. Results: Two facilitator themes emerged: Moving spirit and Encouragement. The healthcare professionals described a willingness to individualize care and to increase their professional development in the field of chronic kidney care. The implementation process was strongly reinforced by both the researchers working interactively with the staff, and the project group. One theme emerged as a barrier: the Limitations of the organization. Changes in the organization hindered the implementation of the intervention throughout the study period, and the lack of interplay in the organization most impeded the process. Conclusions: The findings indicated the complexity of maintaining a sustainable and lasting implementation over a period of two years. Implementing empowerment-based care was found to be facilitated by the cooperation between all involved healthcare professionals. Furthermore, long-term improvement interventions need strong encouragement from all levels of the organization to maintain engagement, even when it is initiated by the health care professionals themselves.

Caveat Fractal: Dissecting the Body of Indexing Theory, Uncovering Complexity, and Moving Toward Performativity

Research poster about indexing theory

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.

The theory of complexity adapted to international relations: the behaviour of the visegrad-ukraine complex adaptive system since November 2013

La teoría de la complejidad, propia del estudio de fenómenos relativos a las ciencias naturales, se muestra como un marco alternativo para comprender los eventos emergentes que surgen en el sistema internacional. Esta monografía correlaciona el lenguaje de la complejidad con las relaciones internacionales, enfocándose en la relación Visegrad—Ucrania, ya que ha sido escenario de una serie de eventos emergentes e inesperados desde las protestas civiles de noviembre de 2013 en Kiev. El sistema complejo que existe entre el Grupo Visegrad y Ucrania se ve , desde entonces, en la necesidad de adaptarse ante los recurrentes eventos emergentes y de auto organizarse. De ese modo, podrá comportarse en concordancia con escenarios impredecibles, particularmente en lo relacionado con sus interacciones energéticas y sus interconexiones políticas.

A complexity-based diagnostic on the democratic unity roundtable mud: problems and alternatives (2008-2016)

Este trabajo exploratorio estudia al movimiento político Mesa de la Unidad Democrática (MUD), creada con el fin de oponerse la Gobierno socialista existente en venezuela. La crítica que este documento realiza, parte desde el punto de vista de la Ciencia de la Complejidad. Algunos conceptos clave de sistemas complejos han sido utilizados para explicar el funcionamiento y organización de la MUD, esto con el objetivo de generar un diagnóstico integral de los problemas que enfrenta, y evidenciar las nuevas percepciones sobre comportamientos perjudiciales que el partido tiene actualmente. Con el enfoque de la complejidad se pretende ayudar a comprender mejor el contexto que enmarca al partido y, para, finalmente aportar una serie de soluciones a los problemas de cohesión que presen

Fractal descriptors for quantifying brain complexity in MRI

Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot’s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.

A take on complexity: bio-molecules and human metabolism interaction modelling for health and nutrition with machine learning

The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.

Harnessing the cellular and molecular complexity of high-risk neuroblastoma to investigate novel potential treatment approaches

Neuroblastoma (NB) is the most common type of tumor in infants and the third most common cancer in children. Current clinical practices employ a variety of strategies for NB treatment, ranging from standard chemotherapy to immunotherapy. Due to a lack of knowledge about the molecular mechanisms underlying the disease's onset, aggressive phenotype, and therapeutic resistance, these approaches are ineffective in the majority of instances. MYCN amplification is one of the most well-known genetic alterations associated with high risk in NB. The following work is divided into three sections and aims to provide new insights into the biology of NB and hypothetical new treatment strategies. First, we identified RUNX1T1 as a key gene involved in MYCN-driven NB onset in a transgenic mouse model. Our results suggested that that RUNX1T1 may recruit the Co-REST complex on target genes that regulate the differentiation of NB cells and that the interaction with RCOR3 is essential. Second, we provided insights into the role of MYCN in dysregulating the CDK/RB/E2F pathway controlling the G1/S transition of the cell cycle. We found that RB is dispensable in regulating MYCN amplified NB's cell cycle, providing the rationale for using cyclin/CDK complexes inhibitors in NBs carrying MYCN amplification and relatively high levels of RB1 expression. Third, we generated an M13 bacteriophage platform to target GD2-expressing cells in NB. Here, we generated a recombinant M13 phage capable of binding GD2-expressing cells selectively (M13GD2). Our results showed that M13GD2 chemically conjugated with the photosensitizer ECB04 preserves the retargeting capability, inducing cell death even at picomolar concentrations upon light irradiation. These results provided proof of concept for M13 phage employment in targeted photodynamic therapy for NB, an exciting strategy to overcome resistance to classical immunotherapy.

Characterization of ENSO changes under idealised radiative forcing in an intermediate complexity general circulation model

Intermediate-complexity general circulation models are a fundamental tool to investigate the role of internal and external variability within the general circulation of the atmosphere and ocean. The model used in this thesis is an intermediate complexity atmospheric general circulation model (SPEEDY) coupled to a state-of-the-art modelling framework for the ocean (NEMO). We assess to which extent the model allows a realistic simulation of the most prominent natural mode of variability at interannual time scales: El-Niño Southern Oscillation (ENSO). To a good approximation, the model represents the ENSO-induced Sea Surface Temperature (SST) pattern in the equatorial Pacific, despite a cold tongue-like bias. The model underestimates (overestimates) the typical ENSO spatial variability during the winter (summer) seasons. The mid-latitude response to ENSO reveals that the typical poleward stationary Rossby wave train is reasonably well represented. The spectral decomposition of ENSO features a spectrum that lacks periodicity at high frequencies and is overly periodic at interannual timescales. We then implemented an idealised transient mean state change in the SPEEDY model. A warmer climate is simulated by an alteration of the parametrized radiative fluxes that corresponds to doubled carbon dioxide absorptivity. Results indicate that the globally averaged surface air temperature increases of 0.76 K. Regionally, the induced signal on the SST field features a significant warming over the central-western Pacific and an El-Niño-like warming in the subtropics. In general, the model features a weakening of the tropical Walker circulation and a poleward expansion of the local Hadley cell. This response is also detected in a poleward rearrangement of the tropical convective rainfall pattern. The model setting that has been here implemented provides a valid theoretical support for future studies on climate sensitivity and forced modes of variability under mean state changes.