Delayed and significant hypercalcaemia due to teriparatide therapy: a case report and review.

INTRODUCTION: Transient hypercalcaemia due to teriparatide occurs in up to 11% of patients though delayed hypercalcaemia (> 24 h post injection) is rare. We report the case of a female who developed significant delayed hypercalcaemia after teriparatide treatment for osteoporosis and review other cases in the literature to date. CASE REPORT: A 72-year-old female on teriparatide for the treatment of osteoporosis was found to have hypercalcaemia (3.30 mmol/l) on routine testing approximately 3 months after starting therapy. Serum calcium pretreatment was normal at 2.39 mmol/l. She was admitted to the hospital for investigations which identified a serum 25-hydroxyvitamin D of 94 nmol/l, a low parathyroid hormone of 6.0 pg/ml, and normal test results for 1,25 dihydroxyvitamin D (115 pmol/l), parathyroid hormone-related peptide (< 1.4 pmol/ml), serum electrophoresis and angiotensin-converting enzyme (39 IU/l). CT abdomen, pelvis, and thorax revealed no evidence of malignancy and an isotope bone scan ruled out skeletal metastases. Serum calcium normalised (2.34 mmol/l) several days after stopping teriparatide and calcium supplements and administering intravenous fluid. On restarting teriparatide, delayed hypercalcaemia reoccurred and treatment was switched to denosumab. DISCUSSION: Delayed moderate to severe hypercalcaemia (serum calcium > 3.0 mmol/l) due to teriparatide is rare but may lead to therapy withdrawal. The underlying predisposing risk factors remain unclear and highlight the importance of a routine serum calcium assessment on therapy.

Measurement of the ν_{e}-Nucleus Charged-Current Double-Differential Cross Section at ⟨E_{ν}⟩=2.4 GeV Using NOvA.

The inclusive electron neutrino charged-current cross section is measured in the NOvA near detector using 8.02×10^{20} protons-on-target in the NuMI beam. The sample of GeV electron neutrino interactions is the largest analyzed to date and is limited by ≃17% systematic rather than the ≃7.4% statistical uncertainties. The double-differential cross section in final-state electron energy and angle is presented for the first time, together with the single-differential dependence on Q^{2} (squared four-momentum transfer) and energy, in the range 1 GeV≤E_{ν}<6 GeV. Detailed comparisons are made to the predictions of the GENIE, GiBUU, NEUT, and NuWro neutrino event generators. The data do not strongly favor a model over the others consistently across all three cross sections measured, though some models have especially good or poor agreement in the single differential cross section vs Q^{2}.

Optimizing memory in reservoir computers.

A reservoir computer is a way of using a high dimensional dynamical system for computation. One way to construct a reservoir computer is by connecting a set of nonlinear nodes into a network. Because the network creates feedback between nodes, the reservoir computer has memory. If the reservoir computer is to respond to an input signal in a consistent way (a necessary condition for computation), the memory must be fading; that is, the influence of the initial conditions fades over time. How long this memory lasts is important for determining how well the reservoir computer can solve a particular problem. In this paper, I describe ways to vary the length of the fading memory in reservoir computers. Tuning the memory can be important to achieve optimal results in some problems; too much or too little memory degrades the accuracy of the computation.

Search for Active-Sterile Antineutrino Mixing Using Neutral-Current Interactions with the NOvA Experiment.

This Letter reports results from the first long-baseline search for sterile antineutrinos mixing in an accelerator-based antineutrino-dominated beam. The rate of neutral-current interactions in the two NOvA detectors, at distances of 1 and 810 km from the beam source, is analyzed using an exposure of 12.51×10^{20} protons-on-target from the NuMI beam at Fermilab running in antineutrino mode. A total of 121 of neutral-current candidates are observed at the far detector, compared to a prediction of 122±11(stat.)±15(syst.) assuming mixing only between three active flavors. No evidence for ν[over ¯]_{µ}→ν[over ¯]_{s} oscillation is observed. Interpreting this result within a 3+1 model, constraints are placed on the mixing angles θ_{24}<25° and θ_{34}<32° at the 90% C.L. for 0.05 eV^{2}≤Δm_{41}^{2}≤0.5 eV^{2}, the range of mass splittings that produces no significant oscillations at the near detector. These are the first 3+1 confidence limits set using long-baseline accelerator antineutrinos.

Low dimensional manifolds in reservoir computers.

A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network. The nodes are all driven by a common driving signal. Reservoir computers can contain hundreds to thousands of nodes, resulting in a high dimensional dynamical system, but the reservoir computer variables evolve on a lower dimensional manifold in this high dimensional space. This paper describes how this manifold dimension depends on the parameters of the reservoir computer, and how the manifold dimension is related to the performance of the reservoir computer at a signal estimation task. It is demonstrated that increasing the coupling between nodes while controlling the largest Lyapunov exponent of the reservoir computer can optimize the reservoir computer performance. It is also noted that the sparsity of the reservoir computer network does not have any influence on performance.

Improved Constraints on Sterile Neutrino Mixing from Disappearance Searches in the MINOS, MINOS+, Daya Bay, and Bugey-3 Experiments.

Searches for electron antineutrino, muon neutrino, and muon antineutrino disappearance driven by sterile neutrino mixing have been carried out by the Daya Bay and MINOS+ collaborations. This Letter presents the combined results of these searches, along with exclusion results from the Bugey-3 reactor experiment, framed in a minimally extended four-neutrino scenario. Significantly improved constraints on the θ_{µe} mixing angle are derived that constitute the most constraining limits to date over five orders of magnitude in the mass-squared splitting Δm_{41}^{2}, excluding the 90% C.L. sterile-neutrino parameter space allowed by the LSND and MiniBooNE observations at 90% CL_{s} for Δm_{41}^{2}<13 eV^{2}. Furthermore, the LSND and MiniBooNE 99% C.L. allowed regions are excluded at 99% CL_{s} for Δm_{41}^{2}<1.6 eV^{2}.

Precision Constraints for Three-Flavor Neutrino Oscillations from the Full MINOS+ and MINOS Dataset.

We report the final measurement of the neutrino oscillation parameters Δm_{32}^{2} and sin^{2}θ_{23} using all data from the MINOS and MINOS+ experiments. These data were collected using a total exposure of 23.76×10^{20} protons on target producing ν_{µ} and ν[over ¯]_{µ} beams and 60.75 kt yr exposure to atmospheric neutrinos. The measurement of the disappearance of ν_{µ} and the appearance of ν_{e} events between the Near and Far detectors yields |Δm_{32}^{2}|=2.40_{-0.09}^{+0.08}(2.45_{-0.08}^{+0.07})×10^{-3} eV^{2} and sin^{2}θ_{23}=0.43_{-0.04}^{+0.20}(0.42_{-0.03}^{+0.07}) at 68% C.L. for normal (inverted) hierarchy.

Path length statistics in reservoir computers.

Because reservoir computers are high dimensional dynamical systems, designing a good reservoir computer is difficult. In many cases, the designer must search a large nonlinear parameter space, and each step of the search requires simulating the full reservoir computer. In this work, I show that a simple statistic based on the mean path length between nodes in the reservoir computer is correlated with better reservoir computer performance. The statistic predicts the diversity of signals produced by the reservoir computer, as measured by the covariance matrix of the reservoir computer. This statistic by itself is not sufficient to predict reservoir computer performance because not only must the reservoir computer produce a diverse set of signals, it must be well matched to the training signals. Nevertheless, this path length statistic allows the designer to eliminate some network configurations from consideration without having to actually simulate the reservoir computer, reducing the complexity of the design process.

Do reservoir computers work best at the edge of chaos?

It has been demonstrated that cellular automata had the highest computational capacity at the edge of chaos [N. H. Packard, in Dynamic Patterns in Complex Systems, edited by J. A. S. Kelso, A. J. Mandell, and M. F. Shlesinger (World Scientific, Singapore, 1988), pp. 293-301; C. G. Langton, Physica D 42(1), 12-37 (1990); J. P. Crutchfield and K. Young, in Complexity, Entropy, and the Physics of Information, edited by W. H. Zurek (Addison-Wesley, Redwood City, CA, 1990), pp. 223-269], the parameter at which their behavior transitioned from ordered to chaotic. This same concept has been applied to reservoir computers; a number of researchers have stated that the highest computational capacity for a reservoir computer is at the edge of chaos, although others have suggested that this rule is not universally true. Because many reservoir computers do not show chaotic behavior but merely become unstable, it is felt that a more accurate term for this instability transition is the "edge of stability." Here, I find two examples where the computational capacity of a reservoir computer decreases as the edge of stability is approached: in one case because generalized synchronization breaks down and in the other case because the reservoir computer is a poor match to the problem being solved. The edge of stability as an optimal operating point for a reservoir computer is not in general true, although it may be true in some cases.

Dimension of reservoir computers.

A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network. The nodes are all driven by a common driving signal. In this work, three dimension estimation methods, false nearest neighbor, covariance dimension, and Kaplan-Yorke dimension, are used to estimate the dimension of the reservoir dynamical system. It is shown that the signals in the reservoir system exist on a relatively low dimensional surface. Changing the spectral radius of the reservoir network can increase the fractal dimension of the reservoir signals, leading to an increase in a testing error.

First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA.

The NOvA experiment has seen a 4.4σ signal of ν[over ¯]_{e} appearance in a 2 GeV ν[over ¯]_{µ} beam at a distance of 810 km. Using 12.33×10^{20} protons on target delivered to the Fermilab NuMI neutrino beamline, the experiment recorded 27 ν[over ¯]_{µ}→ν[over ¯]_{e} candidates with a background of 10.3 and 102 ν[over ¯]_{µ}→ν[over ¯]_{µ} candidates. This new antineutrino data are combined with neutrino data to measure the parameters |Δm_{32}^{2}|=2.48_{-0.06}^{+0.11}×10^{-3} eV^{2}/c^{4} and sin^{2}θ_{23} in the ranges from (0.53-0.60) and (0.45-0.48) in the normal neutrino mass hierarchy. The data exclude most values near δ_{CP}=π/2 for the inverted mass hierarchy by more than 3σ and favor the normal neutrino mass hierarchy by 1.9σ and θ_{23} values in the upper octant by 1.6σ.

Search for Sterile Neutrinos in MINOS and MINOS+ Using a Two-Detector Fit.

A search for mixing between active neutrinos and light sterile neutrinos has been performed by looking for muon neutrino disappearance in two detectors at baselines of 1.04 and 735 km, using a combined MINOS and MINOS+ exposure of 16.36×10^{20} protons on target. A simultaneous fit to the charged-current muon neutrino and neutral-current neutrino energy spectra in the two detectors yields no evidence for sterile neutrino mixing using a 3+1 model. The most stringent limit to date is set on the mixing parameter sin^{2}θ_{24} for most values of the sterile neutrino mass splitting Δm_{41}^{2}>10^{-4} eV^{2}.

Interlimb transfer and generalisation of learning in the context of persistent failure to accomplish a visuomotor task.

Transfer, in which capability acquired in one situation influences performance in another is considered, along with retention, as demonstrative of effectual learning. In this regard, interlimb transfer of functional capacity has commanded particular attention as a means of gauging the generalisation of acquired capability. Both theoretical treatments and prior empirical studies suggest that the successful accomplishment of a physical training regime is required to bring about generalised changes that extend to the untrained limb. In the present study, we pose the following question: Does interlimb transfer occur if and only if the training movements are executed? We report findings from JG-an individual recruited to a larger scale trial, who presented with (unilateral) deficits of motor control. We examined whether changes in the performance of the untrained right limb arose following practice undertaken by the impaired left limb, wherein the majority of JG's attempts to execute the training task were unsuccessful. Comparison was made with a group of "control" participants drawn from the main trial, who did not practice the task. For JG, substantial gains in the performance of the untrained limb (registered 3 days, 10 days and 1 year following training) indicated that effective learning had occurred. Learning was, however, expressed principally when the unimpaired (i.e. untrained) limb was utilised to perform the task. When the impaired limb was used, marked deficiencies in movement execution remained prominent throughout.

Network structure effects in reservoir computers.

A reservoir computer is a complex nonlinear dynamical system that has been shown to be useful for solving certain problems, such as prediction of chaotic signals, speech recognition, or control of robotic systems. Typically, a reservoir computer is constructed by connecting a large number of nonlinear nodes in a network, driving the nodes with an input signal and using the node outputs to fit a training signal. In this work, we set up reservoirs where the edges (or connections) between all the network nodes are either +1 or 0 and proceed to alter the network structure by flipping some of these edges from +1 to -1. We use this simple network because it turns out to be easy to characterize; we may use the fraction of edges flipped as a measure of how much we have altered the network. In some cases, the network can be rearranged in a finite number of ways without changing its structure; these rearrangements are symmetries of the network, and the number of symmetries is also useful for characterizing the network. We find that changing the number of edges flipped in the network changes the rank of the covariance of a matrix consisting of the time series from the different nodes in the network and speculate that this rank is important for understanding the reservoir computer performance.

Parallel in vivo and in vitro transcriptomics analysis reveals calcium and zinc signalling in the brain as sensitive targets of HBCD neurotoxicity.

Hexabromocyclododecane (HBCD) is a brominated flame retardant (BFR) that accumulates in humans and affects the nervous system. To elucidate the mechanisms of HBCD neurotoxicity, we used transcriptomic profiling in brains of female mice exposed through their diet to HBCD (199 mg/kg body weight per day) for 28 days and compared with those of neuronal N2A and NSC-19 cell lines exposed to 1 or 2 µM HBCD. Similar pathways and functions were affected both in vivo and in vitro, including Ca2+ and Zn2+ signalling, glutamatergic neuron activity, apoptosis, and oxidative stress. Release of cytosolic free Zn2+ by HBCD was confirmed in N2A cells. This Zn2+ release was partially quenched by the antioxidant N-acetyl cysteine indicating that, in accordance with transcriptomic analysis, free radical formation is involved in HBCD toxicity. To investigate the effects of HBCD in excitable cells, we isolated mouse hippocampal neurons and monitored Ca2+ signalling triggered by extracellular glutamate or zinc, which are co-released pre-synaptically to trigger postsynaptic signalling. In control cells application of zinc or glutamate triggered a rapid rise of intracellular [Ca2+]. Treatment of the cultures with 1 µM of HBCD was sufficient to reduce the glutamate-dependent Ca2+ signal by 50%. The effect of HBCD on zinc-dependent Ca2+ signalling was even more pronounced, resulting in the reduction of the Ca2+ signal with 86% inhibition at 1 µM HBCD. Our results show that low concentrations of HBCD affect neural signalling in mouse brain acting through dysregulation of Ca2+ and Zn2+ homeostasis.

The repeated bout effect can occur without mechanical and neuromuscular changes after a bout of eccentric exercise.

Changes in muscle fascicle mechanics have been postulated to underpin the repeated bout effect (RBE) observed following exercise-induced muscle damage (EIMD). However, in the medial gastrocnemius (MG), mixed evidence exists on whether fascicle stretch amplitude influences the level of EIMD, thus questioning whether changes in fascicle mechanics underpin the RBE. An alternative hypothesis is that neural adaptations contribute to the RBE in this muscle. The aim of this study was to investigate the neuromechanical adaptations during and after repeated bouts of a highly controlled muscle lengthening exercise that aimed to maximize EIMD in MG. In all, 20 subjects performed two bouts of 500 active lengthening contractions (70% of maximal activation) of the triceps surae, separated by 7 days. Ultrasound constructed fascicle length-torque (L-T) curves of MG, surface electromyography (EMG), maximum torque production, and muscle soreness were assessed before, 2 hours and 2 days after each exercise bout. The drop in maximum torque (4%) and the increase in muscle soreness (24%) following the repeated bout were significantly less than following the initial bout (8% and 59%, respectively), indicating a RBE. However, neither shift in the L-T curve nor changes in EMG parameters were present. Furthermore, muscle properties during the exercise were not related to the EIMD or RBE. Our results show that there are no global changes in gastrocnemius mechanical behavior or neural activation that could explain the observed RBE in this muscle. We suggest that adaptations in the non-contractile elements of the muscle are likely to explain the RBE in the triceps surae.

Testing dynamical system variables for reconstruction.

Analyzing data from dynamical systems often begins with creating a reconstruction of the trajectory based on one or more variables, but not all variables are suitable for reconstructing the trajectory. The concept of nonlinear observability has been investigated as a way to determine if a dynamical system can be reconstructed from one signal or a combination of signals [L. A. Aguirre, IEEE Trans. Educ. 38, 33 (1995); C. Letellier, L. A. Aguirre, and J. Maquet, Phys. Rev. E 71, 066213 (2005); L. A. Aguirre, S. B. Bastos, M. A. Alves, and C. Letellier, Chaos 18, 013123 (2008); L. A. Aguirre and C. Letellier, Phys. Rev. E 83, 066209 (2011); and E. Bianco-Martinez, M. S. Baptista, and C. Letellier, Phys. Rev. E 91, 062912 (2015)]; however, nonlinear observability can be difficult to calculate for a high dimensional system. In this work, I compare the results from nonlinear observability to a continuity statistic that indicates the likelihood that there is a continuous function between two sets of multidimensional points-in this case, two different reconstructions of the same attractor from different signals are simultaneously measured. Without a metric against which to test the ability to reconstruct a system, the predictions of nonlinear observability and continuity are ambiguous. As an additional test on how well different signals can predict the ability to reconstruct a dynamical system, I use the fitting error from training a reservoir computer.

Dimension from covariance matrices.

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

Search for Sterile Neutrinos Mixing with Muon Neutrinos in MINOS.

We report results of a search for oscillations involving a light sterile neutrino over distances of 1.04 and 735 km in a ν_{µ}-dominated beam with a peak energy of 3 GeV. The data, from an exposure of 10.56×10^{20} protons on target, are analyzed using a phenomenological model with one sterile neutrino. We constrain the mixing parameters θ_{24} and Δm_{41}^{2} and set limits on parameters of the four-dimensional Pontecorvo-Maki-Nakagawa-Sakata matrix, |U_{µ4}|^{2} and |U_{τ4}|^{2}, under the assumption that mixing between ν_{e} and ν_{s} is negligible (|U_{e4}|^{2}=0). No evidence for ν_{µ}→ν_{s} transitions is found and we set a world-leading limit on θ_{24} for values of Δm_{41}^{2}≲1 eV^{2}.

Limits on Active to Sterile Neutrino Oscillations from Disappearance Searches in the MINOS, Daya Bay, and Bugey-3 Experiments.

Searches for a light sterile neutrino have been performed independently by the MINOS and the Daya Bay experiments using the muon (anti)neutrino and electron antineutrino disappearance channels, respectively. In this Letter, results from both experiments are combined with those from the Bugey-3 reactor neutrino experiment to constrain oscillations into light sterile neutrinos. The three experiments are sensitive to complementary regions of parameter space, enabling the combined analysis to probe regions allowed by the Liquid Scintillator Neutrino Detector (LSND) and MiniBooNE experiments in a minimally extended four-neutrino flavor framework. Stringent limits on sin^{2}2θ_{µe} are set over 6 orders of magnitude in the sterile mass-squared splitting Δm_{41}^{2}. The sterile-neutrino mixing phase space allowed by the LSND and MiniBooNE experiments is excluded for Δm_{41}^{2}<0.8 eV^{2} at 95% CL_{s}.