Genetically enhancing mitochondrial antioxidant activity improves muscle function in aging

Age-related skeletal muscle dysfunction is a leading cause of morbidity that affects up to half the population aged 80 or greater. Here we tested the effects of increased mitochondrial antioxidant activity on age-dependent skeletal muscle dysfunction using transgenic mice with targeted overexpression of the human catalase gene to mitochondria (MCat mice). Aged MCat mice exhibited improved voluntary exercise, increased skeletal muscle specific force and tetanic Ca(2+) transients, decreased intracellular Ca(2+) leak and increased sarcoplasmic reticulum (SR) Ca(2+) load compared with age-matched wild type (WT) littermates. Furthermore, ryanodine receptor 1 (the sarcoplasmic reticulum Ca(2+) release channel required for skeletal muscle contraction; RyR1) from aged MCat mice was less oxidized, depleted of the channel stabilizing subunit, calstabin1, and displayed increased single channel open probability (Po). Overall, these data indicate a direct role for mitochondrial free radi! cals in promoting the pathological intracellular Ca(2+) leak that underlies age-dependent loss of skeletal muscle function. This study harbors implications for the development of novel therapeutic strategies, including mitochondria-targeted antioxidants for treatment of mitochondrial myopathies and other healthspan-limiting disorders

Binary search trees for generalized measurement

Generalized quantum measurements (POVMs or POMs) are important for optimally extracting information for quantum communication and computation. The standard realization via the Neumark extension requires extensive resources in the form of operations in an extended Hilbert space. For an arbitrary measurement, we show how to construct a binary search tree with a depth logarithmic in the number of possible outcomes. This could be implemented experimentally by coupling the measured quantum system to a probe qubit which is measured, and then iterating.Comment: 5 pages, 4 figure

The constraint equations for the Einstein-scalar field system on compact manifolds

We study the constraint equations for the Einstein-scalar field system on compact manifolds. Using the conformal method we reformulate these equations as a determined system of nonlinear partial differential equations. By introducing a new conformal invariant, which is sensitive to the presence of the initial data for the scalar field, we are able to divide the set of free conformal data into subclasses depending on the possible signs for the coefficients of terms in the resulting Einstein-scalar field Lichnerowicz equation. For many of these subclasses we determine whether or not a solution exists. In contrast to other well studied field theories, there are certain cases, depending on the mean curvature and the potential of the scalar field, for which we are unable to resolve the question of existence of a solution. We consider this system in such generality so as to include the vacuum constraint equations with an arbitrary cosmological constant, the Yamabe equation and even (all cases of) the prescribed scalar curvature problem as special cases.Comment: Minor changes, final version. To appear: Classical and Quantum Gravit

Thermodynamic and Kinetic Parameters for Calcite Nucleation on Peptoid and Model Scaffolds:A Step toward Nacre Mimicry

The production of novel composite materials, assembled using biomimetic polymers known as peptoids (N-substituted glycines) to nucleate CaCO3, can open new pathways for advanced material design. However, a better understanding of the heterogeneous CaCO3 nucleation process is a necessary first step. We determined the thermodynamic and kinetic parameters for calcite nucleation on self-assembled monolayers (SAMs) of nanosheet-forming peptoid polymers and simpler, alkanethiol analogues. We used nucleation rate studies to determine the net interfacial free energy (γ net) for the peptoid-calcite interface and for SAMs terminated with carboxyl headgroups, amine headgroups, or a mix of the two. We compared the results with γ net determined from dynamic force spectroscopy (DFS) and from density functional theory (DFT), using COSMO-RS simulations. Calcite nucleation has a lower thermodynamic barrier on the peptoid surface than on carboxyl and amine SAMs. From the relationship between nucleation rate (J 0) and saturation state, we found that under low-saturation conditions, i.e. <3.3 (pH 9.0), nucleation on the peptoid substrate was faster than that on all of the model surfaces, indicating a thermodynamic drive toward heterogeneous nucleation. When they are taken together, our results indicate that nanosheet-forming peptoid monolayers can serve as an organic template for CaCO3 polymorph growth

Environmental Sensor Placement with Convolutional Gaussian Neural Processes

Environmental sensors are crucial for monitoring weather conditions and the impacts of climate change. However, it is challenging to maximise measurement informativeness and place sensors efficiently, particularly in remote regions like Antarctica. Probabilistic machine learning models can evaluate placement informativeness by predicting the uncertainty reduction provided by a new sensor. Gaussian process (GP) models are widely used for this purpose, but they struggle with capturing complex non-stationary behaviour and scaling to large datasets. This paper proposes using a convolutional Gaussian neural process (ConvGNP) to address these issues. A ConvGNP uses neural networks to parameterise a joint Gaussian distribution at arbitrary target locations, enabling flexibility and scalability. Using simulated surface air temperature anomaly over Antarctica as ground truth, the ConvGNP learns spatial and seasonal non-stationarities, outperforming a non-stationary GP baseline. In a simulated sensor placement experiment, the ConvGNP better predicts the performance boost obtained from new observations than GP baselines, leading to more informative sensor placements. We contrast our approach with physics-based sensor placement methods and propose future work towards an operational sensor placement recommendation system. This system could help to realise environmental digital twins that actively direct measurement sampling to improve the digital representation of reality.Comment: In review for the Climate Informatics 2023 special issue of Environmental Data Scienc

On reminder effects, drop-outs and dominance: evidence from an online experiment on charitable giving

We present the results of an experiment that (a) shows the usefulness of screening out drop-outs and (b) tests whether different methods of payment and reminder intervals affect charitable giving. Following a lab session, participants could make online donations to charity for a total duration of three months. Our procedure justifying the exclusion of drop-outs consists in requiring participants to collect payments in person flexibly and as known in advance and as highlighted to them later. Our interpretation is that participants who failed to collect their positive payments under these circumstances are likely not to satisfy dominance. If we restrict the sample to subjects who did not drop out, but not otherwise, reminders significantly increase the overall amount of charitable giving. We also find that weekly reminders are no more effective than monthly reminders in increasing charitable giving, and that, in our three months duration experiment, standing orders do not increase giving relative to one-off donations

Leaky ryanodine receptors in β-sarcoglycan deficient mice: a potential common defect in muscular dystrophy

Disruption of the sarcolemma-associated dystrophin-glycoprotein complex underlies multiple forms of muscular dystrophy, including Duchenne muscular dystrophy and sarcoglycanopathies. A hallmark of these disorders is muscle weakness. In a murine model of Duchenne muscular dystrophy, mdx mice, cysteine-nitrosylation of the calcium release channel/ryanodine receptor type 1 (RyR1) on the skeletal muscle sarcoplasmic reticulum causes depletion of the stabilizing subunit calstabin1 (FKBP12) from the RyR1 macromolecular complex. This results in a sarcoplasmic reticular calcium leak via defective RyR1 channels. This pathological intracellular calcium leak contributes to reduced calcium release and decreased muscle force production. It is unknown whether RyR1 dysfunction occurs also in other muscular dystrophies. To test this we used a murine model of Limb-Girdle muscular dystrophy, deficient in β-sarcoglycan (Sgcb−/−). Skeletal muscle RyR1 from Sgcb−/− deficient mice were oxidized, nitrosylated, and depleted of the stabilizing subunit calstabin1, which was associated with increased open probability of the RyR1 channels. Sgcb−/− deficient mice exhibited decreased muscle specific force and calcium transients, and displayed reduced exercise capacity. Treating Sgcb−/− mice with the RyR stabilizing compound S107 improved muscle specific force, calcium transients, and exercise capacity. We have previously reported similar findings in mdx mice, a murine model of Duchenne muscular dystrophy. Our data suggest that leaky RyR1 channels may underlie multiple forms of muscular dystrophy linked to mutations in genes encoding components of the dystrophin-glycoprotein complex. A common underlying abnormality in calcium handling indicates that pharmacological targeting of dysfunctional RyR1 could be a novel therapeutic approach to improve muscle function in Limb-Girdle and Duchenne muscular dystrophies

Memory consolidation in the cerebellar cortex

Several forms of learning, including classical conditioning of the eyeblink, depend upon the cerebellum. In examining mechanisms of eyeblink conditioning in rabbits, reversible inactivations of the control circuitry have begun to dissociate aspects of cerebellar cortical and nuclear function in memory consolidation. It was previously shown that post-training cerebellar cortical, but not nuclear, inactivations with the GABA(A) agonist muscimol prevented consolidation but these findings left open the question as to how final memory storage was partitioned across cortical and nuclear levels. Memory consolidation might be essentially cortical and directly disturbed by actions of the muscimol, or it might be nuclear, and sensitive to the raised excitability of the nuclear neurons following the loss of cortical inhibition. To resolve this question, we simultaneously inactivated cerebellar cortical lobule HVI and the anterior interpositus nucleus of rabbits during the post-training period, so protecting the nuclei from disinhibitory effects of cortical inactivation. Consolidation was impaired by these simultaneous inactivations. Because direct application of muscimol to the nuclei alone has no impact upon consolidation, we can conclude that post-training, consolidation processes and memory storage for eyeblink conditioning have critical cerebellar cortical components. The findings are consistent with a recent model that suggests the distribution of learning-related plasticity across cortical and nuclear levels is task-dependent. There can be transfer to nuclear or brainstem levels for control of high-frequency responses but learning with lower frequency response components, such as in eyeblink conditioning, remains mainly dependent upon cortical memory storage