Intraoperative identification of patient-specific elastic modulus of the meniscus during arthroscopy.

BACKGROUND AND OBJECTIVE: Degenerative meniscus tissue has been associated with a lower elastic modulus and can lead to the development of arthrosis. Safe intraoperative measurement of in vivo elastic modulus of the human meniscus could contribute to a better understanding of meniscus health, and for developing surgical simulators where novice surgeons can learn to distinguish healthy from degenerative meniscus tissue. Such measurement can also support intraoperative decision-making by providing a quantitative measure of the meniscus health condition. The objective of this study is to demonstrate a method for intraoperative identification of meniscus elastic modulus during arthroscopic probing using an adaptive observer method. METHODS: Ex vivo arthroscopic examinations were performed on five cadaveric knees to estimate the elastic modulus of the anterior, mid-body, and posterior regions of lateral and medial menisci. Real-time intraoperative force-displacement data was obtained and utilized for modulus estimation through an adaptive observer method. For the validation of arthroscopic elastic moduli, an inverse parameter identification approach using optimization, based on biomechanical indentation tests and finite element analyses, was employed. Experimental force-displacement data in various anatomical locations were measured through indentation. An iterative optimization algorithm was employed to optimize elastic moduli and Poisson's ratios by comparing experimental force values at maximum displacement with the corresponding force values from linear elastic region-specific finite element models. Finally, the estimated elastic modulus values obtained from ex vivo arthroscopy were compared against optimized values using a paired t-test. RESULTS: The elastic moduli obtained from ex vivo arthroscopy and optimization showcased subject specificity in material properties. Additionally, the results emphasized anatomical and regional specificity within the menisci. The anterior region of the medial menisci exhibited the highest elastic modulus among the anatomical locations studied (9.97±3.20MPa from arthroscopy and 5.05±1.97MPa from finite element-based inverse parameter identification). The paired t-test results indicated no statistically significant difference between the elastic moduli obtained from arthroscopy and inverse parameter identification, suggesting the feasibility of stiffness estimation using arthroscopic examination. CONCLUSIONS: This study has demonstrated the feasibility of intraoperative identification of patient-specific elastic modulus for meniscus tissue during arthroscopy.

Modelling and analysis of cAMP-induced mixed-mode oscillations in cortical neurons: Critical roles of HCN and M-type potassium channels.

Cyclic AMP controls neuronal ion channel activity. For example hyperpolarization-activated cyclic nucleotide-gated (HCN) and M-type K+ channels are activated by cAMP. These effects have been suggested to be involved in astrocyte control of neuronal activity, for example, by controlling the action potential firing frequency. In cortical neurons, cAMP can induce mixed-mode oscillations (MMOs) consisting of small-amplitude, subthreshold oscillations separating complete action potentials, which lowers the firing frequency greatly. We extend a model of neuronal activity by including HCN and M channels, and show that it can reproduce a series of experimental results under various conditions involving and inferring with cAMP-induced activation of HCN and M channels. In particular, we find that the model can exhibit MMOs as found experimentally, and argue that both HCN and M channels are crucial for reproducing these patterns. To understand how M and HCN channels contribute to produce MMOs, we exploit the fact that the model is a three-time scale dynamical system with one fast, two slow, and two super-slow variables. We show that the MMO mechanism does not rely on the super-slow dynamics of HCN and M channel gating variables, since the model is able to produce MMOs even when HCN and M channel activity is kept constant. In other words, the cAMP-induced increase in the average activity of HCN and M channels allows MMOs to be produced by the slow-fast subsystem alone. We show that the slow-fast subsystem MMOs are due to a folded node singularity, a geometrical structure well known to be involved in the generation of MMOs in slow-fast systems. Besides raising new mathematical questions for multiple-timescale systems, our work is a starting point for future research on how cAMP signalling, for example resulting from interactions between neurons and glial cells, affects neuronal activity via HCN and M channels.

Modeling Doxorubicin Pharmacokinetics in Multiple Myeloma Suggests Mechanism of Drug Resistance.

OBJECTIVE: Multiple myeloma (MM) is a plasma cell malignancy often treated with chemotherapy drugs. Among these, doxorubicin (DOXO) is commonly employed, sometimes in combined-drug therapies, but it has to be optimally administered in order to maximize its efficacy and reduce possible side effects. To support DOXO studies and treatment optimization, here we propose an experimental/modeling approach to establish a model describing DOXO pharmacokinetics (PK) in MM cells. METHODS: A series of in vitro experiments were performed in MM1R and MOLP-2 cells. DOXO was administered at two dosages (200 nM, 450 nM) at [Formula: see text] = 0 and removed at [Formula: see text] = 3 hrs. Intracellular DOXO concentration was measured via fluorescence microscopy during both drug uptake ([Formula: see text] = 0-3 hrs) and release phases ([Formula: see text] = 3-8 hrs). Four PK candidate models were identified, and were compared and selected based on their ability to describe DOXO data and numerical parameter identification. RESULTS: The most parsimonious model consists of three compartments describing DOXO distribution between the extracellular space, the cell cytoplasm and the nucleus, and defines the intracellular DOXO efflux rate through a Hill function, simulating a threshold/saturation drug resistance mechanism. This model predicted DOXO data well in all the experiments and provided precise parameter estimates (mean ± standard deviation coefficient of variation: 15.8 ± 12.2%). CONCLUSIONS: A reliable PK model describing DOXO uptake and release in MM cells has been successfully developed. SIGNIFICANCE: The proposed PK model, once integrated with DOXO pharmacodynamics, has the potential of allowing the study and the optimization of DOXO treatment strategies in MM.

Biopsychosocial Rehabilitation for Inflammatory Arthritis and Osteoarthritis Patients: A Systematic Review and Meta-Analysis of Randomized Trials.

OBJECTIVE: To assess the benefits and harms associated with biopsychosocial rehabilitation in patients with inflammatory arthritis and osteoarthritis (OA). METHODS: We performed a systematic review and meta-analysis. Data were collected through electronic searches of Cochrane CENTRAL, MEDLINE, Embase, PsycInfo, and CINAHL databases up to March 2019. Trials examining the effect of biopsychosocial rehabilitation in adults with inflammatory arthritis and/or OA were considered eligible, excluding rehabilitation adjunct to surgery. The primary outcome for benefit was pain and total withdrawals for harm. RESULTS: Of the 27 trials meeting the eligibility criteria, 22 trials (3,750 participants) reported sufficient data to be included in the quantitative synthesis. For patient-reported outcome measures, biopsychosocial rehabilitation was slightly superior to control for pain relief (standardized mean difference [SMD] -0.19 [95% confidence interval (95% CI) -0.31, -0.07]), had a small effect on patient global assessment score (SMD -0.13 [95% CI -0.26, -0.00]), with no apparent effect on health-related quality of life, fatigue, self-reported disability/physical function, mental well-being, and reduction in pain intensity ≥30%. Clinician-measured outcomes displayed a small effect on observed disability/physical function (SMD -0.34 [95% CI -0.57, -0.10]), a large effect on physician global assessment score (SMD -0.72 [95% CI -1.18, -0.26]), and no effect on inflammation. No difference in harms existed in terms of the number of withdrawals, adverse events, or serious adverse events. CONCLUSION: Biopsychosocial rehabilitation produces a significant but clinically small beneficial effect on patient-reported pain among patients with inflammatory arthritis and OA, with no difference in harm. Methodologic weaknesses were observed in the included trials, suggesting low-to-moderate confidence in the estimates of effect.

Patient-reported outcome measures in depression.

AIM: Patient-reported outcome measures (PROMs) are increasingly important as a mean for quality assurance. Feasible estimates of recovery can be achieved through the application of Jacobson plots, which is a simple demonstration of the outcome of each case, recommended for clinical use. We applied this approach with PROMs collected regarding group psychotherapy in a mental health service (MHS) setting. We hypothesized a recovery rate of above 50% of all cases, expecting a lower recovery rate amongst patients with severe depression. METHODS: We made a secondary sub-sample analysis of data from patients with unipolar depression (N = 171) within a pragmatic, non-inferiority, randomized controlled clinical trial comparing two cognitive behavior therapy (CBT) group interventions. The treatment consisted of 14 2-hours weekly group CBT sessions. We collected depression PROMs with the Becks Depression Inventory-II and functional levels PROMs with the Work and Social Adjustment Scale at baseline, end-of-treatment, and at a 6-months follow-up. RESULTS: At follow-up, 35% (N = 43/123) of cases with moderate or severe depression (BDI > 19) at baseline reached scores below the cut-off for moderate depression. Recovery rates in severe cases were significantly lower (26.5 vs 52.5%; p = 0.0004). We observed severe functional impairment in 36% of the patients at baseline (52/144) and observed no changes or worsening in scores at a 6-months follow-up in 44% of the patients (64/144). CONCLUSION: We achieved satisfactory remission rates for patients with moderate depression. Patients with severe depression and patients with functional impairment reached recovery rates below the standard of comparable MHSs. Improved MHSs for these patients are needed.

Machine learning provides insight into models of heterogeneous electrical activity in human beta-cells.

Understanding how heterogeneous cellular responses emerge from cell-to-cell variations in expression and function of subcellular components is of general interest. Here, we focus on human insulin-secreting beta-cells, which are believed to constitute a population in which heterogeneity is of physiological importance. We exploit recent single-cell electrophysiological data that allow biologically realistic population modeling of human beta-cells that accounts for cellular heterogeneity and correlation between ion channel parameters. To investigate how ion channels influence the dynamics of our updated mathematical model of human pancreatic beta-cells, we explore several machine learning techniques to determine which model parameters are important for determining the qualitative patterns of electrical activity of the model cells. As expected, K＋ channels promote absence of activity, but once a cell is active, they increase the likelihood of having action potential firing. HERG channels were of great importance for determining cell behavior in most of the investigated scenarios. Fast bursting is influenced by the time scales of ion channel activation and, interestingly, by the type of Ca2＋ channels coupled to BK channels in BK-CaV complexes. Slow, metabolically driven oscillations are promoted mostly by K(ATP) channels. In summary, combining population modeling with machine learning analysis provides insight into the model and generates new hypotheses to be investigated both experimentally, via simulations and through mathematical analysis.

Experimental Investigation of Mineral Particle Deposition in the Cement Production Process.

This study aims to improve the understanding of the formation and prevention of deposits caused by the introduction of alternative fuels in the cement industry. Experiments were conducted with cement mineral materials in a laboratory-scale entrained flow reactor. To simulate the temperature conditions in a cement calciner, two different deposit probe systems were used: a high probe surface temperature (HPST) deposit system with a probe surface temperature range of 700-1200 °C and a low probe surface temperature (LPST) deposit system with a probe surface temperature range of 500-700 °C. The effects of fed materials (raw meal, hot meal, bypass dust), flue gas temperature (700-1200 °C), deposit probe surface temperature (550-1200 °C), gas velocity (0.9-2.7 m/s), and experimental duration (5-60 min) on the deposit formation rate were investigated. The results revealed that the concentration of KCl in the fed materials has a large influence on deposit formation. In HPST experiments with furnace temperatures ranging from 700 to 1100 °C, the bypass dust has a higher deposition rate than hot and raw meals, due to a large amount of K and Cl (>10 wt %) in the bypass dust, which forms melts and increases the stickiness between impacting particles and deposits. In LPST experiments, the presence of KCl facilitated the deposit formation rate by providing a sticky layer on the deposit probe via condensation, resulting in a higher deposition rate of bypass dust than the raw meal. An increase in gas velocity showed a negative effect on the deposit formation rate due to an increase in rebound. The present study suggests that keeping the calciner wall temperature at 900-1100 °C and a low level of KCl content would effectively reduce the deposit formation, thereby increasing the equipment life and reducing the operating cost during cement production.

A Tunable Hyperspectral Imager for Detection and Quantification of Marine Biofouling on Coated Surfaces.

Fouling control coatings (FCCs) are used to prevent the accumulation of marine biofouling on, e.g., ship hulls, which causes increased fuel consumption and the global spread of non-indigenous species. The standards for performance evaluations of FCCs rely on visual inspections, which induce a degree of subjectivity. The use of RGB images for objective evaluations has already received interest from several authors, but the limited acquired information restricts detailed analyses class-wise. This study demonstrates that hyperspectral imaging (HSI) expands the specificity of biofouling assessments of FCCs by capturing distinguishing spectral features. We developed a staring-type hyperspectral imager using a liquid crystal tunable filter as the wavelength selective element. A novel light-emitting diode illumination system with high and uniform irradiance was designed to compensate for the low-filter transmittance. A spectral library was created from reflectance-calibrated optical signatures of representative biofouling species and coated panels. We trained a neural network on the annotated library to assign a class to each pixel. The model was evaluated on an artificially generated target, and global accuracy of 95% was estimated. The classifier was tested on coated panels (exposed at the CoaST Maritime Test Centre) with visible intergrown biofouling. The segmentation results were used to determine the coverage percentage per class. Although a detailed taxonomic description might be complex due to spectral similarities among groups, these results demonstrate the feasibility of HSI for repeatable and quantifiable biofouling detection on coated surfaces.

Kelp carbon sink potential decreases with warming due to accelerating decomposition.

Cycling of organic carbon in the ocean has the potential to mitigate or exacerbate global climate change, but major questions remain about the environmental controls on organic carbon flux in the coastal zone. Here, we used a field experiment distributed across 28° of latitude, and the entire range of 2 dominant kelp species in the northern hemisphere, to measure decomposition rates of kelp detritus on the seafloor in relation to local environmental factors. Detritus decomposition in both species were strongly related to ocean temperature and initial carbon content, with higher rates of biomass loss at lower latitudes with warmer temperatures. Our experiment showed slow overall decomposition and turnover of kelp detritus and modeling of coastal residence times at our study sites revealed that a significant portion of this production can remain intact long enough to reach deep marine sinks. The results suggest that decomposition of these kelp species could accelerate with ocean warming and that low-latitude kelp forests could experience the greatest increase in remineralization with a 9% to 42% reduced potential for transport to long-term ocean sinks under short-term (RCP4.5) and long-term (RCP8.5) warming scenarios. However, slow decomposition at high latitudes, where kelp abundance is predicted to expand, indicates potential for increasing kelp-carbon sinks in cooler (northern) regions. Our findings reveal an important latitudinal gradient in coastal ecosystem function that provides an improved capacity to predict the implications of ocean warming on carbon cycling. Broad-scale patterns in organic carbon decomposition revealed here can be used to identify hotspots of carbon sequestration potential and resolve relationships between carbon cycling processes and ocean climate at a global scale.

A global dataset of seaweed net primary productivity.

Net primary productivity (NPP) plays a pivotal role in the global carbon balance but estimating the NPP of underwater habitats remains a challenging task. Seaweeds (marine macroalgae) form the largest and most productive underwater vegetated habitat on Earth. Yet, little is known about the distribution of their NPP at large spatial scales, despite more than 70 years of local-scale studies being scattered throughout the literature. We present a global dataset containing NPP records for 246 seaweed taxa at 429 individual sites distributed on all continents from the intertidal to 55 m depth. All records are standardized to annual aerial carbon production (g C m-2 yr-1) and are accompanied by detailed taxonomic and methodological information. The dataset presented here provides a basis for local, regional and global comparative studies of the NPP of underwater vegetation and is pivotal for achieving a better understanding of the role seaweeds play in the global coastal carbon cycle.

Quantification of Structural Integrity and Stability Using Nanograms of Protein by Flow-Induced Dispersion Analysis.

In the development of therapeutic proteins, analytical assessment of structural stability and integrity constitutes an important activity, as protein stability and integrity influence drug efficacy, and ultimately patient safety. Existing analytical methodologies solely rely on relative changes in optical properties such as fluorescence or scattering upon thermal or chemical perturbation. Here, we present an absolute analytical method for assessing protein stability, structure, and unfolding utilizing Taylor dispersion analysis (TDA) and LED-UV fluorescence detection. The developed TDA method measures the change in size (hydrodynamic radius) and intrinsic fluorescence of a protein during in-line denaturation with guanidinium hydrochloride (GuHCl). The conformational stability of the therapeutic antibody adalimumab and human serum albumin were characterized as a function of pH. The simple workflow and low sample consumption (40 ng protein per data point) of the methodology make it ideal for assessing protein characteristics related to stability in early drug development or when having a scarce amount of sample available.

Assessment of immunogenicity and drug activity in patient sera by flow-induced dispersion analysis.

Biopharmaceuticals have revolutionized the treatment of many diseases such as diabetes, cancer, and autoimmune disorders. These complex entities provide unique advantages like high specificity towards their target. Unfortunately, biopharmaceuticals are also prone to elicit undesired immunogenic responses (immunogenicity), compromising treatment efficacy as well as patient safety due to severe adverse effects including life threatening conditions. Current immunogenicity assays are hampered by immobilization procedures, complicated sample pre-treatment, or rely on cell-based methods which all prevent reliable and continuous monitoring of patients. In this work, we present Flow Induced Dispersion Analysis (FIDA) for assessment of immunogenicity and drug activity in serum samples from arthritis patients receiving adalimumab. FIDA is a first principle technique for size-based characterization of biomolecules and their complexes under biologically relevant conditions. The FIDA methodology rely on an absolute and quantitative readout (hydrodynamic radius) thus reducing the need for positive and negative controls. Here, FIDA is applied for evaluating active adalimumab in serum by studying the interaction with its target tumor necrosis factor alpha (TNF-α). We report proof of principle for a quantitative approach for stratifying patients exhibiting presence of neutralizing and non-neutralizing antibodies based on their individual drug activity pattern. Further, it can be applied to any biopharmaceutical having soluble drug targets and it holds potential in a companion diagnostics setting.

Calcium Signaling in the Photodamaged Skin: In Vivo Experiments and Mathematical Modeling.

The epidermis forms an essential barrier against a variety of insults. The overall goal of this study was to shed light not only on the effects of accidental epidermal injury, but also on the mechanisms that support laser skin resurfacing with intra-epidermal focal laser-induced photodamage, a widespread medical practice used to treat a range of skin conditions. To this end, we selectively photodamaged a single keratinocyte with intense, focused and pulsed laser radiation, triggering Ca2+ waves in the epidermis of live anesthetized mice with ubiquitous expression of a genetically encoded Ca2+ indicator. Waves expanded radially and rapidly, reaching up to eight orders of bystander cells that remained activated for tens of minutes, without displaying oscillations of the cytosolic free Ca2+ concentration ([Formula: see text]). By combining in vivo pharmacological dissection with mathematical modeling, we demonstrate that Ca2+ wave propagation depended primarily on the release of ATP, a prime damage-associated molecular patterns (DAMPs), from the hit cell. Increments of the [Formula: see text] in bystander cells were chiefly due to Ca2+ release from the endoplasmic reticulum (ER), downstream of ATP binding to P2Y purinoceptors. ATP-dependent ATP release though connexin hemichannels (HCs) affected wave propagation at larger distances, where the extracellular ATP concentration was reduced by the combined effect of passive diffusion and hydrolysis due to the action of ectonucleotidases, whereas pannexin channels had no role. Bifurcation analysis suggests basal keratinocytes have too few P2Y receptors (P2YRs) and/or phospholipase C (PLC) to transduce elevated extracellular ATP levels into inositol trisphosphate (IP3) production rates sufficiently large to sustain [Formula: see text] oscillations.

Human pancreatic islet miRNA-mRNA networks of altered miRNAs due to glycemic status.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene expression via mRNA targeting, playing important roles in the pancreatic islets. We aimed to identify molecular pathways and genomic regulatory regions associated with altered miRNA expression due to glycemic status, which could contribute to the development of type 2 diabetes (T2D). To this end, miRNAs were identified by a combination of differential miRNA expression and correlation analysis in human islet samples from donors with normal and elevated blood glucose levels. Analysis and clustering of highly correlated, experimentally validated gene targets of these miRNAs revealed two islet-specific clusters, which were associated with key aspects of islet functions and included a high number of T2D-related genes. Finally, cis-eQTLs and public GWAS data integration uncovered suggestive genomic signals of association with insulin secretion and T2D. The miRNA-driven network-based approach presented in this study contributes to a better understanding of impaired insulin secretion in T2D pathogenesis.

Amplitude-modulated spiking as a novel route to bursting: Coupling-induced mixed-mode oscillations by symmetry breaking.

Mixed-mode oscillations consisting of alternating small- and large-amplitude oscillations are increasingly well understood and are often caused by folded singularities, canard orbits, or singular Hopf bifurcations. We show that coupling between identical nonlinear oscillators can cause mixed-mode oscillations because of symmetry breaking. This behavior is illustrated for diffusively coupled FitzHugh-Nagumo oscillators with negative coupling constant, and we show that it is caused by a singular Hopf bifurcation related to a folded saddle-node (FSN) singularity. Inspired by earlier work on models of pancreatic beta-cells [Sherman, Bull. Math. Biol. 56, 811 (1994)], we then identify a new type of bursting dynamics due to diffusive coupling of cells firing action potentials when isolated. In the presence of coupling, small-amplitude oscillations in the action potential height precede transitions to square-wave bursting. Confirming the hypothesis from the earlier work that this behavior is related to a pitchfork-of-limit-cycles bifurcation in the fast subsystem, we find that it is caused by symmetry breaking. Moreover, we show that it is organized by a FSN in the averaged system, which causes a singular Hopf bifurcation. Such behavior is related to the recently studied dynamics caused by the so-called torus canards.

Modeling Pharmacokinetics of Doxorubicin in Multiple Myeloma Cells.

Doxorubicin (DOXO) is a well-established chemotherapy drug for treatment of different tumors, ranging from breast cancer, melanoma to multiple myeloma (MM). Here, we present a coupled experimental/modeling approach to study DOXO pharmacokinetics in MM cells, investigate its distribution among the extracellular and intracellular compartments during time. Three model candidates are considered and identified. Model selection is performed based on its ability to describe the data both qualitatively and in terms of quantitative indexes. The most parsimonious model consists of a nonlinear structure with a saturation-threshold control of intracellular DOXO efflux by the DOXO bound to the cellular DNA. This structure could explain the hypothesis that MM cells are drug-resistant, likely due to the involvement of P-glycoproteins.The proposed model is able to predict the intracellular (free and bound) DOXO and suggests the presence of a saturation-threshold drug-resistant mechanism.Clinical Relevance- The model can be used to properly understand and guide further experimental setup, e.g., to investigate multiple myeloma cell variability among different cell lines.

Evaluating Commutability of Control Materials in Three Nordic External Quality Assessment Schemes for Lipoproteins.

BACKGROUND: The quality of control materials is crucial for evaluating external quality assessment (EQA) results. To detect method differences, the EQA material should behave the same as a patient sample, meaning the material must be commutable. Noncommutable materials may cause misinterpretations of EQA results. Here, we examined the commutability of EQA materials used in 3 Nordic EQA schemes for lipids. METHODS: The study was designed according to the procedures recommended for assessing commutability by the International Federation of Clinical Chemistry and Laboratory Medicine. Commutability was assessed based on the difference in bias between a control material (CM) and clinical samples (CS) consisting of human plasma using 2 different measurement procedures (MPs). Measurands: LDL-cholesterol (LDL-C), total cholesterol (TC), HDL-cholesterol (HDL-C), and triglycerides (TG). Four CMs (CM1-4) were assessed for commutability by using 40 CS and 3 MPs (Abbott Architect, Roche Cobas, and Siemens Atellica). RESULTS: Unmodified native CMs (CM1 and CM3), stored at -80 °C, were commutable for all included measurands, except for LDL-C that was indeterminate, when comparing MPs pairwise. Modified CM2 was noncommutable for HDL-C, LDL-C, non-HDL-C, and LDL-C calculations. Unmodified native CM4, stored at -20°C, was noncommutable for LDL-C. CONCLUSIONS: Unmodified serum samples stored at -80 °C were commutable for lipids on the evaluated MPs, and therefore suitable as CMs in EQA schemes. Moreover, the study demonstrated that minor modifications of samples may lead to noncommutability.

Local flexibility in feeding behaviour and contrasting microhabitat use of an omnivore across latitudes.

As the environment is getting warmer and species are redistributed, consumers can be forced to adjust their interactions with available prey, and this could have cascading effects within food webs. To better understand the capacity for foraging flexibility, our study aimed to determine the diet variability of an ectotherm omnivore inhabiting kelp forests, the sea urchin Echinus esculentus, along its entire latitudinal distribution in the northeast Atlantic. Using a combination of gut content and stable isotope analyses, we determined the diet and trophic position of sea urchins at sites in Portugal (42° N), France (49° N), southern Norway (63° N), and northern Norway (70° N), and related these results to the local abundance and distribution of putative food items. With mean estimated trophic levels ranging from 2.4 to 4.6, omnivory and diet varied substantially within and between sites but not across latitudes. Diet composition generally reflected prey availability within epiphyte or understorey assemblages, with local affinities demonstrating that the sea urchin adjusts its foraging to match the small-scale distribution of food items. A net "preference" for epiphytic food sources was found in northern Norway, where understorey food was limited compared to other regions. We conclude that diet change may occur in response to food source redistribution at multiple spatial scales (microhabitats, sites, regions). Across these scales, the way that key consumers alter their foraging in response to food availability can have important implication for food web dynamics and ecosystem functions along current and future environmental gradients.

Low Birth Weight Increases the Risk of Sudden Cardiac Death in the Young: A Nationwide Study of 2.2 Million People.

Background Sudden cardiac death (SCD) constitutes a major health problem worldwide. We investigated whether birth weight (BW), small for gestational age (SGA), and large for gestational age are associated with altered risk of SCD among the young (aged 1-36 years). Methods and Results We included all people born in Denmark from 1973 to 2008 utilizing the Danish Medical Birth Register. All SCDs in Denmark in 2000 to 2009 have previously been identified. We defined 5 BW groups, SGA, and large for gestational age as exposure and SCD as the outcome. We estimated the age-specific relative risk of SCD with 95% CI. Additionally, we investigated if SGA and large for gestational age are associated with pathological findings at autopsy. The study population for the BW analyses comprised 2 234 501 people with 389 SCD cases, and the SGA and large for gestational age analyses comprised 1 786 281 people with 193 SCD cases. The relative risk for SCD was 6.69 for people with BW between 1500 and 2499 g (95% CI, 2.38-18.80, P<0.001) and 5.89 for people with BW ≥4500 g (95% CI, 1.81-19.12, P=0.003) at age 5 years. BW 2500 to 3400 g was the reference group. Compared with an appropriate gestational age, the relative risk for SGA was 2.85 (95% CI, 1.35-6.00, P=0.006) at age 10 years. For the autopsied cases, the relative risk of sudden arrhythmic death syndrome at age 5 years was 4.19 for SGA (95% CI, 1.08-16.22, P=0.038). Conclusions We found an association between BW and SCD in the young, with an increased risk among SGA infants. In addition, we found an association between SGA and sudden arrhythmic death syndrome.