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At least 325 records · Page 18

Expression and structure of the Chlamydia trachomatis DksA ortholog

Chlamydia trachomatis is a bacterial obligate intracellular parasite and a significant cause of human disease, including sexually transmitted infections and trachoma. The bacterial RNA polymerase-binding protein DksA is a transcription factor integral to the multicomponent bacterial stress response pathway known as the stringent response. The genome of C. trachomatis encodes a DksA ortholog (DksA Ct ) that is maximally expressed at 15–20 h post infection, a time frame correlating with the onset of transition between the replicative reticulate body (RB) and infectious elementary body (EB) forms of the pathogen. Ectopic overexpression of DksA Ct in C. trachomatis prior to RB–EB transitions during infection of HeLa cells resulted in a 39.3% reduction in overall replication (yield) and a 49.6% reduction in recovered EBs. While the overall domain organization of DksA Ct is similar to the DksA ortholog of Escherichia coli (DksA Ec ), DksA Ct did not functionally complement DksA Ec . Transcription of dksA Ct is regulated by tandem promoters, one of which also controls expression of nrdR, encoding a negative regulator of deoxyribonucleotide biosynthesis. The phenotype resulting from ectopic expression of DksA Ct and the correlation between dksA Ct and nrdR expression is consistent with a role for DksA Ct in the C. trachomatis developmental cycle.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of overtime phenotypic variation of yeasts in chronic vulvovaginal candidosis cases

Abstract Chronic vulvovaginal candidosis results either from reinfection or from the ability of Candida spp. to persist in the vulva and/or vagina. Persistence is usually associated with increased antifungal (mainly azoles) resistance rates, which can explain treatment failure, and/or increased expression of virulence factors by Candida spp. The aim of this study was to assess the mechanisms leading to Candida spp persistence, by studying sequential isolates from women with chronic vulvovaginal candidosis, focusing on strains genotypes, azole resistance, and ability to form biofilms along the period of clinical evaluation. The strains were identified at species level by automated analysis of biochemical profiles and molecular typing evaluated by polymorphic DNA analysis. The capacity to form biofilm was assessed with a microtiter plate assay. Fluconazole susceptibility was determined by the microdilution broth assay at both pH 7 (following the recommended guideline) and pH 4.5 (as representative of vaginal pH). We studied samples from 17 clinically recurrent cases. In 53% of the chronic cases there were two or more isolates that had a phylogenetic relationship while the remaining (47%) were caused by different species. In those cases where related strains were involved in recurrence, we verified an increase in MIC at pH 7 and also an increased capacity to form biofilms over time. Significant correlation between these two parameters was observed only in cases caused by C. glabrata, evidencing the importance of these two factors to enhance persistence in the vaginal mucosa for this particular species.

Faria-Gonçalves, Paula↗

Slow scrambling and hidden integrability in a random rotor model

In this work, we analyze the out-of-time-order correlation functions of a solvable model of a large number $\textit{N}$ of $\textit{M}$-component quantum rotors coupled by Gaussian-distributed random, infinite-range exchange interactions. We focus on the growth of commutators of operators at a temperature $\textit{T}$ above the zero temperature quantum critical point separating the spin-glass and paramagnetic phases. In the large $\textit{N, M}$ limit, the squared commutators of the rotor fields do not display any exponential growth of commutators, in spite of the absence of any sharp quasiparticlelike excitations in the disorder-averaged theory. We show that in this limit, the problem is integrable and points out interesting connections to random-matrix theory. At leading order in 1/$\textit{M}$, there are no modifications to the critical behavior but an irrelevant term in the fixed-point action leads to a small exponential growth of the squared commutator. We also introduce and comment on a generalized model involving $\textit{p}$-pair rotor interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dirac fast scramblers

In this work, we introduce a family of Gross-Neveu-Yukawa models with a large number of fermion and boson flavors as higher dimensional generalizations of the Sachdev-Ye-Kitaev model. The models may be derived from local lattice couplings and give rise to Lorentz invariant critical solutions in 1+1 and 2+1 dimensions. These solutions imply anomalous dimensions of both bosons and fermions tuned by the number ratio of boson to fermion flavors. In 1+1 dimension the solution represents a stable critical phase, while in 2+1 dimension it governs a quantum phase transition. We compute the out of time order correlators in the 1+1 dimensional model, showing that it exhibits growth with the maximal Lyapunov exponent λ L =2πT in the low temperature limit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Emergence of many-body quantum chaos via spontaneous breaking of unitarity

It is suggested that many-body quantum chaos appears as the spontaneous symmetry breaking of unitarity in interacting quantum many-body systems. It has been shown that many-body level statistics, probed by the spectral form factor (SFF) defined as K(η,t)=$\langle$|Tr exp(-ηH+itH)| 2 $\rangle$, is dominated by a diffuson-type mode in a field theory analysis. The key finding of this Letter is that the “unitary” η = 0 case is different from the η → 0 ± limit, with the latter leading to a finite mass of these modes due to interactions. This mass suppresses a rapid exponential ramp in the SFF, which is responsible for the fast emergence of Poisson statistics in the noninteracting case, and gives rise to a nontrivial random matrix structure of many-body levels. The interaction-induced mass in the SFF shares similarities with the dephasing rate in the theory of weak localization and the Lyapunov exponent of the out-of-time-ordered correlators.

36 MATERIALS SCIENCE↗

Sachdev-Ye-Kitaev model on a noisy quantum computer

Here we study the SYK model -- an important toy model for quantum gravity on IBM's superconducting qubit quantum computers. By using a graph-coloring algorithm to minimize the number of commuting clusters of terms in the qubitized Hamiltonian, we find the gate complexity of the time evolution using the first-order product formula for N Majorana fermions is $\mathscr{O}$(N 5 J 2 t 2 /ε) where J is the dimensionful coupling parameter, t is the evolution time, and ε is the desired precision. With this improved resource requirement, we perform the time evolution for N=6,8 with maximum two-qubit circuit depth of 343. We perform different error mitigation schemes on the noisy hardware results and find good agreement with the exact diagonalization results on classical computers and noiseless simulators. In particular, we compute return probability after time t and out-of-time order correlators (OTOC) which is a standard observable of quantifying the chaotic nature of quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nonlinear dynamics and quantum chaos of a family of kicked p -spin models

Herein we introduce kicked p-spin models describing a family of transverse Ising-like models for an ensemble of spin-1/2 particles with all-to-all p-body interaction terms occurring periodically in time as delta-kicks. This is the natural generalization of the well-studied quantum kicked top (p = 2) [Haake, Kus', and Scharf, Z. Phys. B 65, 381 (1987)]. We fully characterize the classical nonlinear dynamics of these models, including the transition to global Hamiltonian chaos. The classical analysis allows us to build a classification for this family of models, distinguishing between p = 2 and p > 2, and between models with odd and even p's. Quantum chaos in these models is characterized in both kinematic and dynamic signatures. For the latter, we show numerically that the growth rate of the out-of-time-order correlator is dictated by the classical Lyapunov exponent. Finally, we argue that the classification of these models constructed in the classical system applies to the quantum system as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy-Resolved Information Scrambling in Energy-Space Lattices

Here, weakly interacting Fermi gases simulate spin lattices in energy space, offering a rich platform for investigating information spreading and spin coherence in a large many-body quantum system. We show that the collective spin vector can be determined as a function of energy from the measured spin density, enabling general energy-space resolved protocols. We measure an out-of-time-order correlation function in this system and observe the energy dependence of the many-body coherence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Benchmarking Information Scrambling

Information scrambling refers to the rapid spreading of initially localized information over an entire system, via the generation of global entanglement. This effect is usually detected by measuring a temporal decay of the out-of-time order correlators. However, in experiments, decays of these correlators suffer from fake positive signals from various sources, e.g., decoherence due to inevitable couplings to the environment, or errors that cause mismatches between the purported forward and backward evolutions. Here, in this Letter, we provide a simple and robust approach to single out the effect of genuine scrambling. This allows us to benchmark the scrambling process by quantifying the degree of the scrambling from the noisy backgrounds. We also demonstrate our protocol with simulations on IBM cloud-based quantum computers.

97 MATHEMATICS AND COMPUTING↗

Scrambling Transition in a Radiative Random Unitary Circuit

Here we study quantum information scrambling in a random unitary circuit that exchanges qubits with an environment at a rate p. As a result, initially localized quantum information not only spreads within the system, but also spills into the environment. Using the out-of-time-order correlator (OTOC) to characterize scrambling, we find a nonequilibrium phase transition in the directed percolation universality class at a critical swap rate p c : for p < p c the ensemble-averaged OTOC exhibits ballistic growth with a tunable light cone velocity, while for p > p c the OTOC fails to percolate within the system and vanishes uniformly within a finite timescale, indicating that all local operators are rapidly swapped into the environment. To elucidate its information-theoretic consequences, we demonstrate that the transition in operator spreading coincides with a transition in an observer’s ability to decode the system’s initial quantum information from the swapped-out, or “radiated,” qubits. We present a simple decoding scheme which recovers the system’s initial information with perfect fidelity in the nonpercolating phase, and with continuously decreasing fidelity with decreasing swap rate in the percolating phase. Depending on the initial state of the swapped-in qubits, we further observe a corresponding entanglement transition in the coherent information from the system into the radiated qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Single-shot measurement of longitudinal phase space beam profile in an electron storage ring

A novel scheme to measure the longitudinal emittance and phase space profile in an electron storage ring by using correlations between time and the vertical coordinate, and between energy and the horizontal coordinate, is proposed. This longitudinal profile measurement scheme will help to demonstrate recent results of advanced studies for manipulating the longitudinal beam profile and for investigating beam instability in an electron storage ring.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Triacylglycerol, total fatty acid, and biomass accumulation of metabolically engineered energycane grown under field conditions confirms its potential as feedstock for drop‐in fuel production

Abstract Metabolic engineering for hyperaccumulation of lipids in vegetative tissues of high biomass crops promises a step change in oil yields for the production of advanced biofuels. Energycane is the ideal feedstock for this approach due to its exceptional biomass production and persistence under marginal conditions. Here, we evaluated metabolically engineered energycane with constitutive expression of the lipogenic factors WRINKLED 1 ( WRI 1), DIACYLGLYCEROL ACYLTRANSFERASE 1 ( DGAT 1), and OLEOSIN 1 ( OLE 1) for the accumulation of triacylglycerol (TAG), total fatty acid (TFA), and biomass under field conditions at the University of Florida‐IFAS experiment station near Citra, Florida. TAG and TFA accumulation were highest in leaves (up to 9.9% and 12.9% of DW, respectively), followed by juice from crushed stems, stems, and roots. TAG and TFA accumulation increased up to harvest time and correlated highest with OLE 1 and DGAT 1 expression. Biomass dry weight, TAG, and TFA content differed greatly depending on DGAT 1 and OLE 1 expression in transgenic lines with similar WRI 1 expression. Biomass did not significantly differ between WT and line L2 with DAGT 1 and OLE 1 expressed at low levels and TAG and TFA accumulating to 12‐ and 1.6‐fold that of WT leaves, respectively. In contrast, line L13, with intron‐mediated enhancement of DGAT 1 expression, displayed a 245‐ to 330‐fold increase in TAG and a 4.75‐ to 6.45‐fold increase in TFA content compared with WT leaves and a biomass reduction of 52%. These results provide the basis for developing novel feedstocks for expanding plant lipid production and point to new prospects for advanced biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

A New Evaluation Metric for Demand Response-Driven Real-Time Price Prediction Towards Sustainable Manufacturing

Abstract The increasing industry energy demand highlights the urgency of demand response management, while the emerging smart manufacturing technologies pave the way for the implementation of real-time price (RTP)-based demand response management towards sustainable manufacturing. The demand response management requires scheduling of manufacturing systems based on RTP predictions, and thus the prediction quality can directly alter the effectiveness of demand response. However, since the general price prediction algorithms and prediction evaluation metrics are not specifically designed for RTP in demand response problems, a good RTP prediction obtained and evaluated by these algorithms and metrics may not be suitable for demand response scheduling. Therefore, in this study, the relationships between the effectiveness of demand response for manufacturing systems and evaluation results from six commonly used metrics are investigated. Meanwhile, a new metric called k-peak distance (KPD), considering the characteristics of the demand response problem, is proposed and compared with the other six metrics. Furthermore, an encoder-decoder long short-term memory recurrent neural network with KPD is proposed to provide better RTP prediction for manufacturing demand response problems. The case studies indicate that the proposed KPD metric shows a 1.8–3.6 times higher correlation with the demand response effectiveness compared to the other metrics. In addition, the production schedule based on the RTP prediction obtained from the proposed algorithm can improve the effectiveness of demand response by 23.4% on average.

Engineering↗

Improving metrology with quantum scrambling

Quantum scrambling describes the spreading of information into many degrees of freedom in quantum systems, such that the information is no longer accessible locally but becomes distributed throughout the system. This idea can explain how quantum systems become classical and acquire a finite temperature, or how in black holes the information about the matter falling in is seemingly erased. We probe the exponential scrambling of a multiparticle system near a bistable point in phase space and utilize it for entanglement-enhanced metrology. A time-reversal protocol is used to observe a simultaneous exponential growth of both the metrological gain and the out-of-time-order correlator, thereby experimentally verifying the relation between quantum metrology and quantum information scrambling. Our results show that rapid scrambling dynamics capable of exponentially fast entanglement generation are useful for practical metrology, resulting in a 6.8(4)-decibel gain beyond the standard quantum limit.

Science & Technology - Other Topics↗

Seasonality and longer-term development generate temporal dynamics in the Populus microbiome

ABSTRACT Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change. IMPORTANCE Microbiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development.

59 BASIC BIOLOGICAL SCIENCES↗

Towards the web of quantum chaos diagnostics

We study the connections between three quantities that can be used as diagnostics for quantum chaos, i.e., the out-of-time-order correlator (OTOC), Loschmidt echo (LE), and complexity. We generalize the connection between OTOC and LE for infinite dimensions and extend it for higher-order OTOCs and multi-fold LEs. Novel applications of this intrinsic relation are proposed. We also investigated the relationship between a specific circuit complexity and LE by using the inverted oscillator model and made a conjecture about their relationship. These relationships signal a deeper connection between these three probes of quantum chaos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evolution of the Internal Climate Modes under Future Warming

Abstract Climate modes play an important role in weather and climate variability over multiple spatial and temporal scales. This research assesses Earth system model (ESM) projections of the spatiotemporal characteristics of key internal climate modes (NAM, SAM, PNA, ENSO, PDO, and AMO) under high (SSP585) and low (SSP126) radiative forcing scenarios and contextualizes those projections using historical fidelity. Time series analyses are used to assess trends and mode phase characteristics are summarized for the historical period and for the end of the twenty-first century. Spatial patterns are compared to infer morphological changes. Shifts in the power spectra are used to examine changes in variability at subannual, interannual, and interdecadal scales. Changes in time-lagged correlations are used to capture the evolution of first-order interactions. While differences in historical skill are predominantly ESM dependent, changing mode characteristics in a warmer climate also exhibit variability between individual ensemble realizations. NAM, SAM, and ENSO tend to evolve toward increased prevalence of the positive phase up to 2100 across the multimodel ensemble while the PNA and PDO exhibit little trend but increasing phase intensity. AMO characteristics are shown to depend on the method used to remove the external signal. ESMs that show higher historical fidelity tend to show more modest changes in those modes under global nonstationarity. Changes in mode interactions are found to be highly ESM dependent but exhibit broadly similar behavior to historical relationships. These findings have implications for our understanding of internal variability and make clear that the choice of ESM, and even the ESM realization, matters for applications of climate projections. Significance Statement Internal modes of variability are important to understand due to their impact on local, regional, and global weather and climate patterns. Future climate changes will not only be affected by the variability arising from these modes, but the modes will themselves change in response to the changing climate. Spatial and temporal aspects of the modes are assessed from projections of future climate and related to how well they are captured in the historical climate. This yields some measure of confidence in the changes exhibited by the models. In most cases, when historically skillful models exhibit changes that are different from those produced by less skillful models, they tend to produce more modest changes. These results, as well as the variability between model outcomes, mean decisions on which ESM to use for projections of the future climate matter significantly.

Meteorology & Atmospheric Sciences↗

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗