Closely Related Tree Species Differentially Influence the Transfer of Carbon and Nitrogen from Leaf Litter Up the Aquatic Food Web

Decomposing leaf litter in streams provides habitat and nutrition for aquatic insects. Despite large differences in the nutritional qualities of litter among different plant species, their effects on aquatic insects are often difficult to detect. We evaluated how leaf litter of two dominant riparian species (Populus fremontii and P. angustifolia) influenced carbon and nitrogen assimilation by aquatic insect communities, quantifying assimilation rates using stable isotope tracers (13C, 15N). We tested the hypothesis that element fluxes from litter of different plant species better define aquatic insect community structure than insect relative abundances, which often fail. We found that (1) functional communities (defined by fluxes of carbon and nitrogen from leaf litter to insects) were different between leaf litter species, whereas more traditional insect communities (defined by relativized taxa abundances) were not different between leaf litter species, (2) insects assimilated N, but not C, at a higher rate from P. angustifolia litter compared to P. fremontii, even though P. angustifolia decomposes more slowly, and (3) the C:N ratio of material assimilated by aquatic insects was lower for P. angustifolia compared to P. fremontii, indicating higher nutritional quality, despite similar initial litter C:N ratios. These findings provide new evidence for the effects of terrestrial plant species on aquatic ecosystems via their direct influence on the transfer of elements up the food web. We demonstrate how isotopically labeled leaf litter can be used to assess the functioning of insect communities, uncovering patterns undetected by traditional approaches and improving our understanding of the association between food web structure and element cycling

Interleukin-18: A Mediator of Inflammation and Angiogenesis in Rheumatoid Arthritis

Interleukin-18 (IL-18) is a highly regulated inflammatory cytokine that is elevated in synovial tissues and synovial fluids of patients with rheumatoid arthritis (RA) compared with patients with osteoarthritis (OA) and patients with other arthropathies. Within the RA joint, IL-18 can contribute to the inflammatory process by inducing leukocyte extravasation through upregulation of endothelial cell adhesion molecules, the release of chemokines from RA synovial fibroblasts, and directly as a monocytes, lymphocyte, and neutrophil chemoattractant. IL-18 can also help maintain and develop the inflammatory pannus by inducing endothelial cell migration and angiogenesis. IL-18 does this directly by binding and activating endothelial cells and indirectly by inducing RA synovial fibroblasts to produce angiogenic chemokines and vascular endothelial growth factor. IL-18 is present in RA synovial fluid in high levels, where it functions as an angiogenic mediator and leukocyte chemoattractant. IL-18 mediates all these inflammatory processes by binding to its receptor, IL-18 receptor, and initiating the activation of different signaling cascades leading to changes in target cells gene expression and behavior. IL-18 has been identified as a potential therapeutic target in the treatment of RA.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90485/1/jir-2E2011-2E0050.pd

Branching dendrites with resonant membrane: a “sum-over-trips” approach

Dendrites form the major components of neurons. They are complex branching structures that receive and process thousands of synaptic inputs from other neurons. It is well known that dendritic morphology plays an important role in the function of dendrites. Another important contribution to the response characteristics of a single neuron comes from the intrinsic resonant properties of dendritic membrane. In this paper we combine the effects of dendritic branching and resonant membrane dynamics by generalising the “sum-over-trips” approach (Abbott et al. in Biol Cybernetics 66, 49–60 1991). To illustrate how this formalism can shed light on the role of architecture and resonances in determining neuronal output we consider dual recording and reconstruction data from a rat CA1 hippocampal pyramidal cell. Specifically we explore the way in which an Ih current contributes to a voltage overshoot at the soma

The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19

In 2020, the CoViD-19 pandemic spread worldwide in an unexpected way and suddenly modified many life issues, including social habits, social relationships, teaching modalities, and more. Such changes were also observable in many different healthcare and medical contexts. Moreover, the CoViD-19 pandemic acted as a stress test for many research endeavors, and revealed some limitations, especially in contexts where research results had an immediate impact on the social and healthcare habits of millions of people. As a result, the research community is called to perform a deep analysis of the steps already taken, and to re-think steps for the near and far future to capitalize on the lessons learned due to the pandemic. In this direction, on June 09th-11th, 2022, a group of twelve healthcare informatics researchers met in Rochester, MN, USA. This meeting was initiated by the Institute for Healthcare Informatics-IHI, and hosted by the Mayo Clinic. The goal of the meeting was to discuss and propose a research agenda for biomedical and health informatics for the next decade, in light of the changes and the lessons learned from the CoViD-19 pandemic. This article reports the main topics discussed and the conclusions reached. The intended readers of this paper, besides the biomedical and health informatics research community, are all those stakeholders in academia, industry, and government, who could benefit from the new research findings in biomedical and health informatics research. Indeed, research directions and social and policy implications are the main focus of the research agenda we propose, according to three levels: the care of individuals, the healthcare system view, and the population view

Drop Traffic in Microfluidic Ladder Networks with Fore-Aft Structural Asymmetry

We investigate the dynamics of pairs of drops in microfluidic ladder networks with slanted bypasses, which break the fore-aft structural symmetry. Our analytical results indicate that unlike symmetric ladder networks, structural asymmetry introduced by a single slanted bypass can be used to modulate the relative drop spacing, enabling them to contract, synchronize, expand, or even flip at the ladder exit. Our experiments confirm all these behaviors predicted by theory. Numerical analysis further shows that while ladder networks containing several identical bypasses are limited to nearly linear transformation of input delay between drops, mixed combination of bypasses can cause significant non-linear transformation enabling coding and decoding of input delays.Comment: 4 pages, 5 figure

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Urinary biomarker concentrations of captan, chlormequat, chlorpyrifos and cypermethrin in UK adults and children living near agricultural land

There is limited information on the exposure to pesticides experienced by UK residents living near agricultural land. This study aimed to investigate their pesticide exposure in relation to spray events. Farmers treating crops with captan, chlormequat, chlorpyrifos or cypermethrin provided spray event information. Adults and children residing ≤100 m from sprayed fields provided first-morning void urine samples during and outwith the spray season. Selected samples (1–2 days after a spray event and at other times (background samples)) were analysed and creatinine adjusted. Generalised Linear Mixed Models were used to investigate if urinary biomarkers of these pesticides were elevated after spray events. The final data set for statistical analysis contained 1518 urine samples from 140 participants, consisting of 523 spray event and 995 background samples which were analysed for pesticide urinary biomarkers. For captan and cypermethrin, the proportion of values below the limit of detection was greater than 80%, with no difference between spray event and background samples. For chlormequat and chlorpyrifos, the geometric mean urinary biomarker concentrations following spray events were 15.4 μg/g creatinine and 2.5 μg/g creatinine, respectively, compared with 16.5 μg/g creatinine and 3.0 μg/g creatinine for background samples within the spraying season. Outwith the spraying season, concentrations for chlorpyrifos were the same as those within spraying season backgrounds, but for chlormequat, lower concentrations were observed outwith the spraying season (12.3 μg/g creatinine). Overall, we observed no evidence indicative of additional urinary pesticide biomarker excretion as a result of spray events, suggesting that sources other than local spraying are responsible for the relatively low urinary pesticide biomarkers detected in the study population

The role of ongoing dendritic oscillations in single-neuron dynamics

The dendritic tree contributes significantly to the elementary computations a neuron performs while converting its synaptic inputs into action potential output. Traditionally, these computations have been characterized as temporally local, near-instantaneous mappings from the current input of the cell to its current output, brought about by somatic summation of dendritic contributions that are generated in spatially localized functional compartments. However, recent evidence about the presence of oscillations in dendrites suggests a qualitatively different mode of operation: the instantaneous phase of such oscillations can depend on a long history of inputs, and under appropriate conditions, even dendritic oscillators that are remote may interact through synchronization. Here, we develop a mathematical framework to analyze the interactions of local dendritic oscillations, and the way these interactions influence single cell computations. Combining weakly coupled oscillator methods with cable theoretic arguments, we derive phase-locking states for multiple oscillating dendritic compartments. We characterize how the phase-locking properties depend on key parameters of the oscillating dendrite: the electrotonic properties of the (active) dendritic segment, and the intrinsic properties of the dendritic oscillators. As a direct consequence, we show how input to the dendrites can modulate phase-locking behavior and hence global dendritic coherence. In turn, dendritic coherence is able to gate the integration and propagation of synaptic signals to the soma, ultimately leading to an effective control of somatic spike generation. Our results suggest that dendritic oscillations enable the dendritic tree to operate on more global temporal and spatial scales than previously thought

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Background Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson’s Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. Results The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson’s disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. Conclusions Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context

A Vast Thin Plane of Co-rotating Dwarf Galaxies Orbiting the Andromeda Galaxy

Dwarf satellite galaxies are thought to be the remnants of the population of primordial structures that coalesced to form giant galaxies like the Milky Way. An early analysis noted that dwarf galaxies may not be isotropically distributed around our Galaxy, as several are correlated with streams of HI emission, and possibly form co-planar groups. These suspicions are supported by recent analyses, and it has been claimed that the apparently planar distribution of satellites is not predicted within standard cosmology, and cannot simply represent a memory of past coherent accretion. However, other studies dispute this conclusion. Here we report the existence (99.998% significance) of a planar sub-group of satellites in the Andromeda galaxy, comprising approximately 50% of the population. The structure is vast: at least 400 kpc in diameter, but also extremely thin, with a perpendicular scatter <14.1 kpc (99% confidence). Radial velocity measurements reveal that the satellites in this structure have the same sense of rotation about their host. This finding shows conclusively that substantial numbers of dwarf satellite galaxies share the same dynamical orbital properties and direction of angular momentum, a new insight for our understanding of the origin of these most dark matter dominated of galaxies. Intriguingly, the plane we identify is approximately aligned with the pole of the Milky Way's disk and is co-planar with the Milky Way to Andromeda position vector. The existence of such extensive coherent kinematic structures within the halos of massive galaxies is a fact that must be explained within the framework of galaxy formation and cosmology.Comment: Published in the 3rd Jan 2013 issue of Nature. 19 pages, 4 figures, 1 three-dimensional interactive figure. To view and manipulate the 3-D figure, an Adobe Reader browser plug-in is required; alternatively save to disk and view with Adobe Reade