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.

Quantitative perfusion and water transport time model from multi b-value diffusion magnetic resonance imaging validated against neutron capture microspheres.

Intravoxel Incoherent Motion (IVIM) is a non-contrast magnetic resonance imaging diffusion-based scan that uses a multitude of b-values to measure various speeds of molecular perfusion and diffusion, sidestepping inaccuracy of arterial input functions or bolus kinetics in quantitative imaging. We test a new method of IVIM quantification and compare our values to reference standard neutron capture microspheres across normocapnia, CO2 induced hypercapnia, and middle cerebral artery occlusion in a controlled animal model. Perfusion quantification in ml/100g/min compared to microsphere perfusion uses the 3D gaussian probability distribution and defined water transport time as when 50% of the molecules remain in the tissue of interest. Perfusion, water transport time, and infarct volume was compared to reference standards. Simulations were studied to suppress non-specific cerebrospinal fluid (CSF). Linear regression analysis of quantitative perfusion returned correlation (slope = .55, intercept = 52.5, $R^2$= .64). Linear regression for water transport time asymmetry in infarcted tissue was excellent (slope = .59, intercept = .3, $R^2$ = .93). Strong linear agreement also was found for infarct volume (slope = 1.01, $R^2$= .79). Simulation of CSF suppression via inversion recovery returned blood signal reduced by 82% from combined T1 and T2 effects. Intra-physiologic state comparison of perfusion shows potential partial volume effects which require further study especially in disease states. The accuracy and sensitivity of IVIM provides evidence that observed signal changes reflect cytotoxic edema and tissue perfusion. Partial volume contamination of CSF may be better removed during post-processing rather than with inversion recovery to avoid artificial loss of blood signal.

Organotypic human lung bud microarrays identify BMP-dependent SARS-CoV-2 infection in lung cells.

Although lung disease is the primary clinical outcome in COVID-19 patients, how SARS-CoV-2 induces lung pathology remains elusive. Here we describe a high-throughput platform to generate self-organizing and commensurate human lung buds derived from hESCs cultured on micropatterned substrates. Lung buds resemble human fetal lungs and display proximodistal patterning of alveolar and airway tissue directed by KGF. These lung buds are susceptible to infection by SARS-CoV-2 and endemic coronaviruses and can be used to track cell type-specific cytopathic effects in hundreds of lung buds in parallel. Transcriptomic comparisons of infected lung buds and postmortem tissue of COVID-19 patients identified an induction of BMP signaling pathway. BMP activity renders lung cells more susceptible to SARS-CoV-2 infection and its pharmacological inhibition impairs infection by this virus. These data highlight the rapid and scalable access to disease-relevant tissue using lung buds that recapitulate key features of human lung morphogenesis and viral infection biology.

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}.

Functional and Behavioral Trade-Offs between Terrestrial and Aquatic Locomotion in the Amphibious Fish Kryptolebias marmoratus.

The mangrove rivulus (Kryptolebias marmoratus) is a phenotypically plastic teleost fish that can spend considerable time on land and traverse the terrestrial realm through a behavior termed the tail-flip jump. The tail-flip jump is a transitional stage between fully aquatic and terrestrial lifestyles. Therefore, understanding this behavior can provide insight into how organisms adapt to new environments over evolutionary time. Studies of K. marmoratus show that terrestrial acclimation and exercise improve tail-flip jumping performance due to muscle remodeling, but the implications of these muscular changes on aquatic locomotion are unknown. In the present study, we hypothesized that (1) terrestrial acclimation and exercise lead to physiological changes, such as changes to muscle fiber type, muscle mass distribution, or body shape, that optimize tail-flip jump distance and endurance while negatively impacting swimming performance in K. marmoratus, and (2) plasticity of the brain (which has been demonstrated in response to a variety of stimuli in K. marmoratus) allows terrestrial emersion and exercise to cause behavioral changes that promote survival and long-term reproductive success. To test these hypotheses, we measured the critical swimming speed (Ucrit), tail-flip jump distance, terrestrial endurance, and undisturbed aquatic behavior of age- and size-matched K. marmoratus before and after a terrestrial exercise period. This period consisted of six 3-min exercise sessions spread over 12 days, during which the fish were prompted to jump continuously. To isolate the effects of air exposure, a separate group was exposed to air for an equivalent period but not allowed to jump. Air exposure improved maximum jump distance but negatively affected swimming performance (Ucrit). Terrestrial endurance (number of jumps) improved in the exercised group, but Ucrit showed no significant change. Contrary to our first hypothesis, a trade-off exists between jump distance and Ucrit but not between jump endurance and Ucrit. Exercised individuals were more active following exercise, resulting either from the onset of dispersion behavior or a heightened stress response.

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.

Contralateral Effects of Unilateral Strength and Skill Training: Modified Delphi Consensus to Establish Key Aspects of Cross-Education.

BACKGROUND: Cross-education refers to increased motor output (i.e., force generation, skill) of the opposite, untrained limb following a period of unilateral exercise training. Despite extensive research, several aspects of the transfer phenomenon remain controversial. METHODS: A modified two-round Delphi online survey was conducted among international experts to reach consensus on terminology, methodology, mechanisms of action, and translational potential of cross-education, and to provide a framework for future research. RESULTS: Through purposive sampling of the literature, we identified 56 noted experts in the field, of whom 32 completed the survey, and reached consensus (75% threshold) on 17 out of 27 items. CONCLUSION: Our consensus-based recommendations for future studies are that (1) the term 'cross-education' should be adopted to refer to the transfer phenomenon, also specifying if transfer of strength or skill is meant; (2) functional magnetic resonance imaging, short-interval intracortical inhibition and interhemispheric inhibition appear to be promising tools to study the mechanisms of transfer; (3) strategies which maximize cross-education, such as high-intensity training, eccentric contractions, and mirror illusion, seem worth being included in the intervention plan; (4) study protocols should be designed to include at least 13-18 sessions or 4-6 weeks to produce functionally meaningful transfer of strength, and (5) cross-education could be considered as an adjuvant treatment particularly for unilateral orthopedic conditions and sports injuries. Additionally, a clear gap in views emerged between the research field and the purely clinical field. The present consensus statement clarifies relevant aspects of cross-education including neurophysiological, neuroanatomical, and methodological characteristics of the transfer phenomenon, and provides guidance on how to improve the quality and usability of future cross-education studies.

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.

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.

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}.

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.

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.

Diagnostic Accuracy of High-Resolution Black-Blood MRI in the Evaluation of Intracranial Large-Vessel Arterial Occlusions.

BACKGROUND AND PURPOSE: 3D high-resolution black-blood MRI or MR vessel wall imaging allows evaluation of the intracranial arterial wall and extraluminal pathology. We investigated the diagnostic accuracy and reliability of black-blood MRI for the intraluminal detection of large-vessel arterial occlusions. MATERIALS AND METHODS: We retrospectively identified patients with intracranial arterial occlusions, confirmed by CTA or DSA, who also underwent 3D black-blood MRI with nonenhanced and contrast-enhanced T1 sampling perfection with application-optimized contrasts by using different flip angle evolution (T1 SPACE) sequences. Black-blood MRI findings were evaluated by 2 independent and blinded neuroradiologists. Large-vessel intracranial arterial segments were graded on a 3-point scale (grades 0-2) for intraluminal baseline T1 hyperintensity and contrast enhancement. Vessel segments were considered positive for arterial occlusion if focal weak (grade 1) or strong (grade 2) T1-hyperintense signal and/or enhancement replaced the normal intraluminal black-blood signal. RESULTS: Thirty-one patients with 38 intracranial arterial occlusions were studied. The median time interval between black-blood MRI and CTA/DSA reference standard studies was 2 days (range, 0-20 days). Interobserver agreement was good for T1 hyperintensity (κ = 0.63) and excellent for contrast enhancement (κ = 0.89). High sensitivity (100%) and specificity (99.8%) for intracranial arterial occlusion diagnosis was observed with either intraluminal T1 hyperintensity or contrast-enhancement imaging criteria on black-blood MRI. Strong grade 2 intraluminal enhancement was maintained in >80% of occlusions irrespective of location or chronicity. Relatively increased strong grade 2 intraluminal T1 hyperintensity was noted in chronic/incidental versus acute/subacute occlusions (45.5% versus 12.5%, P = .04). CONCLUSIONS: Black-blood MRI with or without contrast has high diagnostic accuracy and reliability in evaluating intracranial large-vessel arterial occlusions with near-equivalency to DSA and CTA.

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.

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.