Mechanisms contributing to the deep chlorophyll maximum in Lake Superior

The seasonal appearance of a deep chlorophyll maximum (DCM) in Lake Superior is a striking phenomenon that is widely observed; however its mechanisms of formation and maintenance are not well understood. As this phenomenon may be the reflection of an ecological driver, or a driver itself, a lack of understanding its driving forces limits the ability to accurately predict and manage changes in this ecosystem. Key mechanisms generally associated with DCM dynamics (i.e. ecological, physiological and physical phenomena) are examined individually and in concert to establish their role. First the prevailing paradigm, “the DCM is a great place to live”, is analyzed through an integration of the results of laboratory experiments and field measurements. The analysis indicates that growth at this depth is severely restricted and thus not able to explain the full magnitude of this phenomenon. Additional contributing mechanisms like photoadaptation, settling and grazing are reviewed with a one-dimensional mathematical model of chlorophyll and particulate organic carbon. Settling has the strongest impact on the formation and maintenance of the DCM, transporting biomass to the metalimnion and resulting in the accumulation of algae, i.e. a peak in the particulate organic carbon profile. Subsequently, shade adaptation becomes manifest as a chlorophyll maximum deeper in the water column where light conditions particularly favor the process. Shade adaptation mediates the magnitude, shape and vertical position of the chlorophyll peak. Growth at DCM depth shows only a marginal contribution, while grazing has an adverse effect on the extent of the DCM. The observed separation of the carbon biomass and chlorophyll maximum should caution scientists to equate the DCM with a large nutrient pool that is available to higher trophic levels. The ecological significance of the DCM should not be separated from the underlying carbon dynamics. When evaluated in its entirety, the DCM becomes the projected image of a structure that remains elusive to measure but represents the foundation of all higher trophic levels. These results also offer guidance in examine ecosystem perturbations such as climate change. For example, warming would be expected to prolong the period of thermal stratification, extending the late summer period of suboptimal (phosphorus-limited) growth and attendant transport of phytoplankton to the metalimnion. This reduction in epilimnetic algal production would decrease the supply of algae to the metalimnion, possibly reducing the supply of prey to the grazer community. This work demonstrates the value of modeling to challenge and advance our understanding of ecosystem dynamics, steps vital to reliable testing of management alternatives

CLIMATE ANOMALIES AND PRIMARY PRODUCTION IN LAKE SUPERIOR

This dissertation supports the modeling of primary production in Lake Superior by offering site specific kinetics and algorithms developed from lab experiments performed on the natural phytoplankton assemblage of Lake Superior. Functions, developed for temperature, light and nutrient conditions and the maximum specific rate of primary production, were incorporated in a 1D specific primary production model and confirmed to published in-situ measured rates of primary production. An extensive data set (supporting model calibration and confirmation), with a fine spatiotemporal resolution, was developed from field measurements taken bi-weekly during the sampling seasons of 2011, 2012 and 2014; considered to be meteorologically average, extremely warm and cold years, respectively. Samplings were taken at 11 stations along a 26 km transect extending lakeward from Michigan’s Keweenaw Peninsula covering the nearshore to offshore gradient. Measurements included: temperature, solar radiation, transparency, beam attenuation, chlorophyll-a fluorescence, colored dissolved organic matter, suspended solids and phosphorus and carbon constituents. Based on these measurements and application of the developed primary production model, patterns in primary production and driving forces (i.e. temperature, light and nutrients) are described in a seasonal, spatial, and interannual fashion. The signal feature in 2011 was the development of a mid-summer “desert” in the offshore surface waters (a period of suboptimal temperatures coincident with a high degree of phosphorus limitation). The manifestation of the “summer desert”, however, was most extreme during the warm year and nonexistent during the cold year. Offshore primary production in all years manifested a subsurface maximum in the upper area of the metalimnion, distinctly above the deep chlorophyll maximum, with rates of production being highest In 2011 (~20 mg C m-3 d-1) followed by 2012 (~17 mg Cm-3 d-1) and lowest in 2014 (~12 mg Cm-3 d-1). Driven by variances in biomass and forcing conditions, offshore areal primary production manifested differences in seasonal patterns between years as well. In 2011 and 2014 a negatively skewed bell-shape pattern was observed, differing in magnitude and timing. The pattern in 2012 differed from these years in magnitude and timing, manifesting elevated production in April and decreased production in September. Greatest areal production in 2012 occurred in July and August (~320 mg Cm-2 d-1), in 2014 in August (~265 mg Cm-2 d-1) and in 2011 production was greatest in July (253 mg C m-2 d-1). Areal production in the summer of 1998, calculated for EPA’s 19 offshore stations in Lake Superior, manifested comparable rates and averaged 224 ± 90 mg C m-2·d-1. Although in all years the development of the thermal bar (TB) occurred after the spring runoff event, an increase in chlorophyll-a concentration during the presence of the TB was observed in 2012. Rates of primary production during this period, however, decreased while the opposite occurred in 2014, signifying that changes in chlorophyll-a concentration should be interpreted carefully (especially if used to identify spring blooms). The information presented in this work not only offers site specific kinetics, appropriate algorithms in support of primary production modeling and an extensive dataset supporting model calibration and confirmation, it also offers new insights into the dynamics of the Lake Superior ecosystem and the forces driving its function

Home care nurses’ perceptions about their role in interprofessional collaborative practice in clinical medication reviews

Regular clinical medication reviews (CMRs) are recommended for monitoring and addressing potential drug-related problems, especially in elderly people. Interprofessional collaborative practice (ICP) by general practitioners, community pharmacists, and nurses in a CMR is recommended and expected to produce more efficient CMRs. Involving home care nurses in ICP is not yet well implemented, and their perspectives are unclear. This study explores how they perceive their role in ICP in CMRs and the requirements to assume that role. Structured interviews were performed, using case-vignettes; data were analyzed with a thematic analysis approach. Twelve home care nurses were interviewed. Three themes regarding the nurses' role were identified: (1) observing, recognizing, and communicating information for a CMR to prescribers and community pharmacists (2); helping to provide patient information and education about implemented changes in the pharmaceutical care plan; and (3) the nurses’ level of involvement in ICP. Three themes regarding requirements were identified: (1) nursing competences, (2) periodic interprofessional consultation and ad hoc interprofessional communication, and (3) guidelines describing the role of nurses. Home care nurses could provide additional support in a CMR. Nursing competences, periodic interprofessional consultation and ad hoc interprofessional communication, and guidelines describing the role of home care nurses are required

Tethering Cells via Enzymatic Oxidative Crosslinking Enables Mechanotransduction in Non-Cell-Adhesive Materials

Cell–matrix interactions govern cell behavior and tissue function by facilitating transduction of biomechanical cues. Engineered tissues often incorporate these interactions by employing cell-adhesive materials. However, using constitutively active cell-adhesive materials impedes control over cell fate and elicits inflammatory responses upon implantation. Here, an alternative cell–material interaction strategy that provides mechanotransducive properties via discrete inducible on-cell crosslinking (DOCKING) of materials, including those that are inherently non-cell-adhesive, is introduced. Specifically, tyramine-functionalized materials are tethered to tyrosines that are naturally present in extracellular protein domains via enzyme-mediated oxidative crosslinking. Temporal control over the stiffness of on-cell tethered 3D microniches reveals that DOCKING uniquely enables lineage programming of stem cells by targeting adhesome-related mechanotransduction pathways acting independently of cell volume changes and spreading. In short, DOCKING represents a bioinspired and cytocompatible cell-tethering strategy that offers new routes to study and engineer cell–material interactions, thereby advancing applications ranging from drug delivery, to cell-based therapy, and cultured meat

Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry for biological data analysis is an active field of research, providing an efficient way of high-throughput proteome screening. A popular variant of mass spectrometry is SELDI, which is often used to measure sample populations with the goal of developing (clinical) classifiers. Unfortunately, not only is the data resulting from such measurements quite noisy, variance between replicate measurements of the same sample can be high as well. Normalisation of spectra can greatly reduce the effect of this technical variance and further improve the quality and interpretability of the data. However, it is unclear which normalisation method yields the most informative result.</p> <p>Results</p> <p>In this paper, we describe the first systematic comparison of a wide range of normalisation methods, using two objectives that should be met by a good method. These objectives are minimisation of inter-spectra variance and maximisation of signal with respect to class separation. The former is assessed using an estimation of the coefficient of variation, the latter using the classification performance of three types of classifiers on real-world datasets representing two-class diagnostic problems. To obtain a maximally robust evaluation of a normalisation method, both objectives are evaluated over multiple datasets and multiple configurations of baseline correction and peak detection methods. Results are assessed for statistical significance and visualised to reveal the performance of each normalisation method, in particular with respect to using no normalisation. The normalisation methods described have been implemented in the freely available MASDA R-package.</p> <p>Conclusion</p> <p>In the general case, normalisation of mass spectra is beneficial to the quality of data. The majority of methods we compared performed significantly better than the case in which no normalisation was used. We have shown that normalisation methods that scale spectra by a factor based on the dispersion (e.g., standard deviation) of the data clearly outperform those where a factor based on the central location (e.g., mean) is used. Additional improvements in performance are obtained when these factors are estimated locally, using a sliding window within spectra, instead of globally, over full spectra. The underperforming category of methods using a globally estimated factor based on the central location of the data includes the method used by the majority of SELDI users.</p

An Evaluation of the Fe-N Phase Diagram Considering Long-Range Order of N Atoms in γ'-Fe4N1-x and ε-Fe2N1-z

The chemical potential of nitrogen was described as a function of nitrogen content for the Fe-N phases α-Fe[N], γ'-Fe4N1-x, and ε-Fe2N1-z. For α-Fe[N], an ideal, random distribution of the nitrogen atoms over the octahedral interstices of the bcc iron lattice was assumed; for γ'-Fe4N1-x and ε-Fe2N1-z, the occurrence of a long-range ordered distribution of the nitrogen atoms over the octahedral interstices of the close packed iron sublattices (fcc and hcp, respectively) was taken into account. The theoretical expressions were fitted to nitrogen-absorption isotherm data for the three Fe-N phases. The α/α + γ', α + γ'/γ', γ'/γ' + ε, and γ' + ε/ε phase boundaries in the Fe-N phase diagram were calculated from combining the quantitative descriptions for the absorption isotherms with the known composition of NH3/H2 gas mixtures in equilibrium with coexisting α and γ' phases and in equilibrium with coexisting γ' and ε phases. Comparison of the present phase boundaries with experimental data and previously calculated phase boundaries showed a major improvement as compared to the previously calculated Fe-N phase diagrams, where long-range order for the nitrogen atoms in the γ' and ε phases was not accounted for

Energy expenditure during egg laying is equal for early and late breeding free-living female great tits

In many bird populations, variation in the timing of reproduction exists but it is not obvious how this variation is maintained as timing has substantial fitness consequences. Daily energy expenditure (DEE) during the egg laying period increases with decreasing temperatures and thus perhaps only females that can produce eggs at low energetic cost will lay early in the season, at low temperatures. We tested whether late laying females have a higher daily energy expenditure during egg laying than early laying females in 43 great tits (Parus major), by comparing on the same day the DEE of early females late in their laying sequence with DEE of late females early in their egg laying sequence. We also validated the assumption that there are no within female differences in DEE within the egg laying sequence. We found a negative effect of temperature and a positive effect of female body mass on DEE but no evidence for differences in DEE between early and late laying females. However, costs incurred during egg laying may have carry-over effects later in the breeding cycle and if such carry-over effects differ for early and late laying females this could contribute to the maintenance of phenotypic variation in laying dates

Patch: platelet transfusion in cerebral haemorrhage: study protocol for a multicentre, randomised, controlled trial

<p>Abstract</p> <p>Background</p> <p>Patients suffering from intracerebral haemorrhage have a poor prognosis, especially if they are using antiplatelet therapy. Currently, no effective acute treatment option for intracerebral haemorrhage exists. Limiting the early growth of intracerebral haemorrhage volume which continues the first hours after admission seems a promising strategy. Because intracerebral haemorrhage patients who are on antiplatelet therapy have been shown to be particularly at risk of early haematoma growth, platelet transfusion may have a beneficial effect.</p> <p>Methods/Design</p> <p>The primary objective is to investigate whether platelet transfusion improves outcome in intracerebral haemorrhage patients who are on antiplatelet treatment. The PATCH study is a prospective, randomised, multi-centre study with open treatment and blind endpoint evaluation. Patients will be randomised to receive platelet transfusion within six hours or standard care. The primary endpoint is functional health after three months. The main secondary endpoints are safety of platelet transfusion and the occurrence of haematoma growth. To detect an absolute poor outcome reduction of 20%, a total of 190 patients will be included.</p> <p>Discussion</p> <p>To our knowledge this is the first randomised controlled trial of platelet transfusion for an acute haemorrhagic disease.</p> <p>Trial registration</p> <p>The Netherlands National Trial Register (NTR1303)</p

Comparative analysis of the human hepatic and adipose tissue transcriptomes during LPS-induced inflammation leads to the identification of differential biological pathways and candidate biomarkers

<p>Abstract</p> <p>Background</p> <p>Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation, obesity, and deregulation of total body energy homeostasis. We induced inflammation in adipose and liver tissues <it>in vitro </it>in order to mimic inflammation <it>in vivo </it>with the aim to identify tissue-specific processes implicated in IR and to find biomarkers indicative for tissue-specific IR.</p> <p>Methods</p> <p>Human adipose and liver tissues were cultured in the absence or presence of LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for secretome were performed using publicly available bioinformatics tools (DAVID, STRING, SecretomeP). The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome.</p> <p>Results</p> <p>LPS treatment significantly affected 667 and 483 genes in adipose and liver tissues respectively. The GO analysis revealed that during inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes and the remaining genes were the differential candidate biomarkers indicative for inflamed adipose or liver tissue. The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data.</p> <p>Conclusions</p> <p>The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver tissue, suggests that adipose tissue is the major organ contributing to the development of systemic inflammation observed in IR. The identified tissue-specific functional clusters and biomarkers might be used in a strategy for the development of tissue-targeted treatment of insulin resistance in patients.</p