There is strong evidence that anesthetics have stereotypical effects on brain state, so that a given anesthetic appears to have a signature in the electroencephalogram (EEG), which may vary with ...dose. This can be usefully interpreted as the anesthetic determining an attractor in the phase space of the brain. How brain activity shifts between these attractors in time remains understudied, as most studies implicitly assume a one-to-one relationship between drug dose and attractor features by assuming stationarity over the analysis interval and analyzing data segments of several minutes in length. Yet data in rats anesthetized with isoflurane suggests that, at anesthetic levels consistent with surgical anesthesia, brain activity alternates between multiple attractors, often spending on the order of 10 min in one activity pattern before shifting to another. Moreover, the probability of these jumps between attractors changes with anesthetic concentration. This suggests the hypothesis that brain state is metastable during anesthesia: though it appears at equilibrium on short timescales (on the order of seconds to a few minutes), longer intervals show shifting behavior. Compelling evidence for metastability in rats anesthetized with isoflurane is reviewed, but so far only suggestive hints of metastability in brain states exist with other anesthetics or in other species. Explicit testing of metastability during anesthesia will require experiments with longer acquisition intervals and carefully designed analytic approaches; some of the implications of these constraints are reviewed for typical spectral analysis approaches. If metastability exists during anesthesia, it implies degeneracy in the relationship between brain state and effect site concentration, as there is not a one-to-one mapping between the two. This degeneracy could explain some of the reported difficulty in using brain activity monitors to titrate drug dose to prevent awareness during anesthesia and should force a rethinking of the notion of depth of anesthesia as a single dimension. Finally, explicit incorporation of knowledge of the dynamics of the brain during anesthesia could offer better depth of anesthesia monitoring.
Silicon quantum dot spin qubits provide a promising platform for large-scale quantum computation because of their compatibility with conventional CMOS manufacturing and the long coherence times ...accessible using
Si enriched material. A scalable error-corrected quantum processor, however, will require control of many qubits in parallel, while performing error detection across the constituent qubits. Spin resonance techniques are a convenient path to parallel two-axis control, while Pauli spin blockade can be used to realize local parity measurements for error detection. Despite this, silicon qubit implementations have so far focused on either single-spin resonance control, or control and measurement via voltage-pulse detuning in the two-spin singlet-triplet basis, but not both simultaneously. Here, we demonstrate an integrated device platform incorporating a silicon metal-oxide-semiconductor double quantum dot that is capable of single-spin addressing and control via electron spin resonance, combined with high-fidelity spin readout in the singlet-triplet basis.
The cheetah and racing greyhound are of a similar size and gross morphology and yet the cheetah is able to achieve a far higher top speed. We compared the kinematics and kinetics of galloping in the ...cheetah and greyhound to investigate how the cheetah can attain such remarkable maximum speeds. This also presented an opportunity to investigate some of the potential limits to maximum running speed in quadrupeds, which remain poorly understood. By combining force plate and high speed video data of galloping cheetahs and greyhounds, we show how the cheetah uses a lower stride frequency/longer stride length than the greyhound at any given speed. In some trials, the cheetahs used swing times as low as those of the greyhounds (0.2 s) so the cheetah has scope to use higher stride frequencies (up to 4.0 Hz), which may contribute to it having a higher top speed that the greyhound. Weight distribution between the animal's limbs varied with increasing speed. At high speed, the hindlimbs support the majority of the animal's body weight, with the cheetah supporting 70% of its body weight on its hindlimbs at 18 m s(-1); however, the greyhound hindlimbs support just 62% of its body weight. Supporting a greater proportion of body weight on a particular limb is likely to reduce the risk of slipping during propulsive efforts. Our results demonstrate several features of galloping and highlight differences between the cheetah and greyhound that may account for the cheetah's faster maximum speeds.
•Controlling for spurious associations in statistical models is essential.•Computationally efficient approaches are critical for large data sets.•Statistical genetic models that predict phenotypes ...help accelerate breeding cycles.•Co-evolution between statistical models and sequencing and phenotyping advances is ongoing.
Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic interactions. Selecting optimal models enables accurate evaluation of associations between marker loci and numerous phenotypes including gene expression. Significant improvements in QTL discovery via association mapping and acceleration of breeding cycles through genomic selection are two successful applications of models using genome-wide markers. Given recent advances in genotyping and phenotyping technologies, further refinement of these approaches is needed to model genetic architecture more accurately and run analyses in a computationally efficient manner, all while accounting for false positives and maximizing statistical power.
The purpose of this work was to quantify the variation of subcanopy spatiotemporal light dynamics over the course of a year and to link it to the physiological ecology of the understory shrub, ...Lindera benzoin L. Blume (northern spicebush). Covering all seven phenoseasons of a deciduous forest, this work utilized a line quantum sensor to measure the variation in subcanopy light levels under all sky conditions at different times of the day. A total of 4,592 individual subcanopy measurements of photosynthetic photon flux density (PPFD, μmol m-2 s-1) were taken as 15-second spatially-integrated one-meter linear averages to better understand the dynamism of light exposure to L. benzoin. Both open (n = 2, one continuous and one instantaneous) and subcanopy location (n = 25) measurements of PPFD were taken on each sampling date in and near the forested plot (Maryland, USA). In addition, we explored the effect of four photointensity-photoperiod combinations on the growth of L. benzoin under controlled conditions to compare to field conditions. On average, understory PPFD was less than 2% of open PPFD during the leafed months and an average of 38.8% of open PPFD during leafless winter months, indicating that: (1) often overlooked woody surfaces intercept large amounts of light; and (2) spicebush within the plot receive limited light even in early spring before canopy leaf-out. Statistical results suggested phenoseason accounted for nearly three-quarters of the variation in incident radiation between the three plant canopy heights. Spicebush under controlled conditions exhibited the highest fitness levels at an intensity of 164.5 μmol m-2 s-1 for 12-hour duration. Similarly, spicebush growth in the field occurred at subcanopy locations receiving higher incidence of PPFD (i.e., >128 μmol m-2 s-1). Results suggest that the ecological niche for these plants is very specific in terms of light intensity.
Ischemia-reperfusion injury (IRI) is one of the major risk factors implicated in morbidity and mortality associated with cardiovascular disease. During cardiac ischemia, the buildup of acidic ...metabolites results in decreased intracellular and extracellular pH, which can reach as low as 6.0 to 6.5. The resulting tissue acidosis exacerbates ischemic injury and significantly affects cardiac function.
We used genetic and pharmacologic methods to investigate the role of acid-sensing ion channel 1a (ASIC1a) in cardiac IRI at the cellular and whole-organ level. Human induced pluripotent stem cell-derived cardiomyocytes as well as ex vivo and in vivo models of IRI were used to test the efficacy of ASIC1a inhibitors as pre- and postconditioning therapeutic agents.
Analysis of human complex trait genetics indicates that variants in the
genetic locus are significantly associated with cardiac and cerebrovascular ischemic injuries. Using human induced pluripotent stem cell-derived cardiomyocytes in vitro and murine ex vivo heart models, we demonstrate that genetic ablation of ASIC1a improves cardiomyocyte viability after acute IRI. Therapeutic blockade of ASIC1a using specific and potent pharmacologic inhibitors recapitulates this cardioprotective effect. We used an in vivo model of myocardial infarction and 2 models of ex vivo donor heart procurement and storage as clinical models to show that ASIC1a inhibition improves post-IRI cardiac viability. Use of ASIC1a inhibitors as preconditioning or postconditioning agents provided equivalent cardioprotection to benchmark drugs, including the sodium-hydrogen exchange inhibitor zoniporide. At the cellular and whole organ level, we show that acute exposure to ASIC1a inhibitors has no effect on cardiac ion channels regulating baseline electromechanical coupling and physiologic performance.
Our data provide compelling evidence for a novel pharmacologic strategy involving ASIC1a blockade as a cardioprotective therapy to improve the viability of hearts subjected to IRI.
Silicon nanoelectronic devices can host single-qubit quantum logic operations with fidelity better than 99.9%. For the spins of an electron bound to a single-donor atom, introduced in the silicon by ...ion implantation, the quantum information can be stored for nearly 1 second. However, manufacturing a scalable quantum processor with this method is considered challenging, because of the exponential sensitivity of the exchange interaction that mediates the coupling between the qubits. Here we demonstrate the conditional, coherent control of an electron spin qubit in an exchange-coupled pair of
P donors implanted in silicon. The coupling strength, J = 32.06 ± 0.06 MHz, is measured spectroscopically with high precision. Since the coupling is weaker than the electron-nuclear hyperfine coupling A ≈ 90 MHz which detunes the two electrons, a native two-qubit controlled-rotation gate can be obtained via a simple electron spin resonance pulse. This scheme is insensitive to the precise value of J, which makes it suitable for the scale-up of donor-based quantum computers in silicon that exploit the metal-oxide-semiconductor fabrication protocols commonly used in the classical electronics industry.
Once the periodic properties of elements were unveiled, chemical behaviour could be understood in terms of the valence of atoms. Ideally, this rationale would extend to quantum dots, and quantum ...computation could be performed by merely controlling the outer-shell electrons of dot-based qubits. Imperfections in semiconductor materials disrupt this analogy, so real devices seldom display a systematic many-electron arrangement. We demonstrate here an electrostatically confined quantum dot that reveals a well defined shell structure. We observe four shells (31 electrons) with multiplicities given by spin and valley degrees of freedom. Various fillings containing a single valence electron-namely 1, 5, 13 and 25 electrons-are found to be potential qubits. An integrated micromagnet allows us to perform electrically-driven spin resonance (EDSR), leading to faster Rabi rotations and higher fidelity single qubit gates at higher shell states. We investigate the impact of orbital excitations on single qubits as a function of the dot deformation and exploit it for faster qubit control.
Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative ...quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering ~20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.
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