Molecular epidemiological characteristics of the virus in 96 children with acute diarrhea in Changdu of Tibet, China. / 西藏昌都地区96ä¾‹å„¿ç«¥æ€¥æ€§è ¹æ³»ç— æ¯’åˆ†å­æµè¡Œç— å­¦åˆ†æž.

OBJECTIVES: To study the molecular epidemiological characteristics of the virus in children with acute viral diarrhea in Changdu of Tibet, China. METHODS: Fecal specimens were collected from 96 children with acute diarrhea who visited the People's Hospital of Changdu, Tibet, from November 2018 to November 2020 and were tested for adenovirus, norovirus, astrovirus, sapovirus, and rotavirus. Gene sequencing was performed for the genotypes of these viruses. RESULTS: The overall positive rate of the five viruses was 39% (37/96), among which astrovirus had the highest positive rate of 17%, followed by norovirus (9%), rotavirus (8%), adenovirus (7%), and sapovirus (5%). There was no significant difference in the positive rate of the five viruses among different age groups (P>0.05). Only the positive rate of astrovirus was significantly different among the four seasons (P<0.05). For adenovirus, 6 children had F41 type and 1 had C2 type; for norovirus, 6 had GⅠ.3 type, 1 had GⅠ.7 type, 1 had GⅡ.3 type, and 2 had GⅡ.4 Sydney_2012 type; HAstrV-1 type was observed in all children with astrovirus infection; for sapovirus, 1 child each had sporadic GⅠ.2, GⅠ.6, and GⅡ.1 sapovirus and 2 children had unknown type; 6 children had rotavirus G9[P8]. CONCLUSIONS: Astrovirus and norovirus are important pathogens in children with acute diarrhea in Changdu, Tibet. The positive rate of adenovirus, norovirus, astrovirus, sapovirus, and rotavirus is not associated with age, and only the positive rate of astrovirus has obvious seasonality. F41 type is the dominant genotype of adenovirus; GⅠ.3 is the dominant genotype of norovirus; HAstrV-1 is the dominant genotype of astrovirus; sporadic GⅠ.2, GⅠ.6, and GⅡ.1 are the dominant genotypes of sapovirus; G9[P8] is the dominant genotype of rotavirus.

Interaction variability shapes succession of synthetic microbial ecosystems.

Cellular interactions are a major driver for the assembly and functioning of microbial communities. Their strengths are shown to be highly variable in nature; however, it is unclear how such variations regulate community behaviors. Here we construct synthetic Lactococcus lactis consortia and mathematical models to elucidate the role of interaction variability in ecosystem succession and to further determine if casting variability into modeling empowers bottom-up predictions. For a consortium of bacteriocin-mediated cooperation and competition, we find increasing the variations of cooperation, from either altered labor partition or random sampling, drives the community into distinct structures. When the cooperation and competition are additionally modulated by pH, ecosystem succession becomes jointly controlled by the variations of both interactions and yields more diversified dynamics. Mathematical models incorporating variability successfully capture all of these experimental observations. Our study demonstrates interaction variability as a key regulator of community dynamics, providing insights into bottom-up predictions of microbial ecosystems.

Identification and characterization of core sludge and biofilm microbiota in anaerobic membrane bioreactors.

An analysis of sludge (i.e., 63 samples) and biofilm (i.e., 79 samples) sampled from 13 anaerobic membrane bioreactors (AnMBR) was conducted. Predominant microbial community identification and multivariate analysis indicate that these reactors showed different microbial community structure, but these differences had no impact on the overall AnMBR performance. Instead, core microbial genera which occurred in ≥90% of sludge (20 genera) and biofilm (12 genera) samples could potentially account for the AnMBR performance. A further calculation on net growth rate (NGR) of core genera in sludge suggested distribution into two main groups (i.e., I: low relative abundance and NGR, II: high relative abundance or high NGR). Consistent positive correlations between bacterial genera were observed among those that exhibited either high relative abundance or high NGR. The anaerobic microbial consortium in both sludge and biofilm were largely affected by stochastic dispersal and migration processes (i.e., neutral assembly). However, Acinetobacter spp. and Methanobacterium spp. occurred consistently in higher frequency in the biofilm but in lower occurrence frequency in the AnMBR permeate. Findings from this study suggest first, specific core microorganisms exist in the sludge regardless of the operating conditions of the AnMBRs, and second, prevention of biofoulant layer on anaerobic membranes can be devised by minimizing attachment of microbes on surfaces in a non-selective manner.

Synthetic, Context-Dependent Microbial Consortium of Predator and Prey.

Synthetic microbial consortia are a rapidly growing area of synthetic biology. So far, most consortia are designed without considering their environments; however, in nature, microbial interactions are constantly modulated by cellular contexts, which, in principle, can dramatically alter community behaviors. Here we present the construction, validation, and characterization of an engineered bacterial predator-prey consortium that involves a chloramphenicol (CM)-mediated, context-dependent cellular interaction. We show that varying the CM level in the environment can induce success in the ecosystem with distinct patterns from predator dominance to prey-predator crossover to ecosystem collapse. A mathematical model successfully captures the essential dynamics of the experimentally observed patterns. We also illustrate that such a dependence enriches community dynamics under different initial conditions and further test the resistance of the consortium to invasion with engineered bacterial strains. This work exemplifies the role of the context dependence of microbial interactions in modulating ecosystem dynamics, underscoring the importance of including contexts into the design of engineered ecosystems for synthetic biology applications.

Pair Interaction of Catalytical Sphere Dimers in Chemically Active Media.

We study the pair dynamics of two self-propelled sphere dimers in the chemically active medium in which a cubic autocatalytic chemical reaction takes place. Concentration gradient around the dimer, created by reactions occurring on the catalytic sphere surface and responsible for the self-propulsion, is greatly influenced by the chemical activities of the environment. Consequently, the pair dynamics of two dimers mediated by the concentration field are affected. In the particle-based mesoscopic simulation, we combine molecular dynamics (MD) for potential interactions and reactive multiparticle collision dynamics (RMPC) for solvent flow and bulk reactions. Our results indicate three different configurations between a pair of dimers after the collision, i.e., two possible scenarios of bound dimer pairs and one unbound dimer pair. A phase diagram is sketched as a function of the rate coefficients of the environment reactions. Since the pair interactions are the basic elements of larger scale systems, we believe the results may shed light on the understanding of the collective dynamics.

Population-Dynamic Modeling of Bacterial Horizontal Gene Transfer by Natural Transformation.

Natural transformation is a major mechanism of horizontal gene transfer (HGT) and plays an essential role in bacterial adaptation, evolution, and speciation. Although its molecular underpinnings have been increasingly revealed, natural transformation is not well characterized in terms of its quantitative ecological roles. Here, by using Neisseria gonorrhoeae as an example, we developed a population-dynamic model for natural transformation and analyzed its dynamic characteristics with nonlinear tools and simulations. Our study showed that bacteria capable of natural transformation can display distinct population behaviors ranging from extinction to coexistence and to bistability, depending on their HGT rate and selection coefficient. With the model, we also illustrated the roles of environmental DNA sources-active secretion and passive release-in impacting population dynamics. Additionally, by constructing and utilizing a stochastic version of the model, we examined how noise shapes the steady and dynamic behaviors of the system. Notably, we found that distinct waiting time statistics for HGT events, namely a power-law distribution, an exponential distribution, and a mix of the both, are associated with the dynamics in the regimes of extinction, coexistence, and bistability accordingly. This work offers a quantitative illustration of natural transformation by revealing its complex population dynamics and associated characteristics, therefore advancing our ecological understanding of natural transformation as well as HGT in general.

Cues for Diotic and Dichotic Detection of a 500-Hz Tone in Noise Vary with Hearing Loss.

Hearing in noise is a challenge for all listeners, especially for those with hearing loss. This study compares cues used for detection of a low-frequency tone in noise by older listeners with and without hearing loss to those of younger listeners with normal hearing. Performance varies significantly across different reproducible, or "frozen," masker waveforms. Analysis of these waveforms allows identification of the cues that are used for detection. This study included diotic (N0S0) and dichotic (N0Sπ) detection of a 500-Hz tone, with either narrowband or wideband masker waveforms. Both diotic and dichotic detection patterns (hit and false alarm rates) across the ensembles of noise maskers were predicted by envelope-slope cues, and diotic results were also predicted by energy cues. The relative importance of energy and envelope cues for diotic detection was explored with a roving-level paradigm that made energy cues unreliable. Most older listeners with normal hearing or mild hearing loss depended on envelope-related temporal cues, even for this low-frequency target. As hearing threshold at 500 Hz increased, the cues for diotic detection transitioned from envelope to energy cues. Diotic detection patterns for young listeners with normal hearing are best predicted by a model that combines temporal- and energy-related cues; in contrast, combining cues did not improve predictions for older listeners with or without hearing loss. Dichotic detection results for all groups of listeners were best predicted by interaural envelope cues, which significantly outperformed the classic cues based on interaural time and level differences or their optimal combination.

Tone-in-noise detection using envelope cues: comparison of signal-processing-based and physiological models.

Tone-in-noise detection tasks with reproducible noise maskers have been used to identify cues that listeners use to detect signals in noisy environments. Previous studies have shown that energy, envelope, and fine-structure cues are significantly correlated to listeners' performance for detection of a 500-Hz tone in noise. In this study, envelope cues were examined for both diotic and dichotic tone-in-noise detection using both stimulus-based signal processing and physiological models. For stimulus-based envelope cues, a modified envelope slope model was used for the diotic condition and the binaural slope of the interaural envelope difference model for the dichotic condition. Stimulus-based models do not include key nonlinear transformations in the auditory periphery such as compression, rate and dynamic range adaptation, and rate saturation, all of which affect the encoding of the stimulus envelope. For physiological envelope cues, stimuli were passed through models for the auditory nerve (AN), cochlear nucleus, and inferior colliculus (IC). The AN and cochlear nucleus models included appropriate modulation gain, another transformation of the stimulus envelope that is not typically included in stimulus-based models. A model IC cell was simulated with a linear band-pass modulation filter. The average discharge rate and response fluctuations of the model IC cell were compared to human performance. Previous studies have predicted a significant amount of the variance across reproducible noise maskers in listeners' detection using stimulus-based envelope cues. In this study, a physiological model that includes neural mechanisms that affect encoding of the stimulus envelope predicts a similar amount of the variance in listeners' performance across noise maskers.

Slow and steady wins the race: a bacterial exploitative competition strategy in fluctuating environments.

One promising frontier for synthetic biology is the development of synthetic ecologies, whereby interacting species form an additional layer of connectivity for engineered gene circuits. Toward this goal, an important step is to understand different types of bacterial interactions in natural settings, among which competition is the most prevalent. By constructing a two-species population dynamics model, here, we mimicked bacterial growth in nature with resource-limited fluctuating environments and searched for optimal strategies for bacterial exploitative competition. In a simple game with two strategy options (constant or susceptible growth), we found that the species playing the constant growth strategy always outplays or is evenly matched with its competitor, suggesting that constant growth is a "no-loss" good bet. We also showed that adoption of sophisticated strategies enables a species to maximize its fitness when its competitor grows susceptibly. The pursuit of fitness maximization is, however, associated with potential loss if both species are capable of strategy adjustment, indicating an intrinsic risk-return trade-off. These findings offer new insights into bacterial competition and may also facilitate the engineering of microbial consortia for synthetic biology applications.

Binaural detection with narrowband and wideband reproducible noise maskers. IV. Models using interaural time, level, and envelope differences.

The addition of out-of-phase tones to in-phase noises results in dynamic interaural level difference (ILD) and interaural time difference (ITD) cues for the dichotic tone-in-noise detection task. Several models have been used to predict listeners' detection performance based on ILD, ITD, or different combinations of the two cues. The models can be tested using detection performance from an ensemble of reproducible-noise maskers. Previous models cannot predict listeners' detection performance for reproducible-noise maskers without fitting the data. Here, two models were tested for narrowband and wideband reproducible-noise experiments. One model was a linear combination of ILD and ITD that included the generally ignored correlation between the two cues. The other model was based on a newly proposed cue, the slope of the interaural envelope difference (SIED). Predictions from both models explained a significant portion of listeners' performance for detection of a 500-Hz tone in wideband noise. Predictions based on the SIED approached the predictable variance in the wideband condition. The SIED represented a nonlinear combination of ILD and ITD, with the latter cue dominating. Listeners did not use a common strategy (cue) to detect tones in the narrowband condition and may use different single frequencies or different combinations of frequency channels.

Predictions of diotic tone-in-noise detection based on a nonlinear optimal combination of energy, envelope, and fine-structure cues.

Tone-in-noise detection has been studied for decades; however, it is not completely understood what cue or cues are used by listeners for this task. Model predictions based on energy in the critical band are generally more successful than those based on temporal cues, except when the energy cue is not available. Nevertheless, neither energy nor temporal cues can explain the predictable variance for all listeners. In this study, it was hypothesized that better predictions of listeners' detection performance could be obtained using a nonlinear combination of energy and temporal cues, even when the energy cue was not available. The combination of different cues was achieved using the logarithmic likelihood-ratio test (LRT), an optimal detector in signal detection theory. A nonlinear LRT-based combination of cues was proposed, given that the cues have Gaussian distributions and the covariance matrices of cue values from noise-alone and tone-plus-noise conditions are different. Predictions of listeners' detection performance for three different sets of reproducible noises were computed with the proposed model. Results showed that predictions for hit rates approached the predictable variance for all three datasets, even when an energy cue was not available.

Dynamical phase of driven colloidal systems with short-range attraction and long-range repulsion.

We study the nonequilibrium dynamics of colloidal system with short-range depletion attraction and screened electrostatic repulsion on a disordered substrate. We find a growth-melting process of the clusters as the temperature is increased. By strengthening the screened electrostatic repulsion, a depinning transition from moving cluster to plastic flow is observed, which is characterized by a peak in threshold depinning force. The corresponding phase diagram is then mapped out. Due to the influences of disorder from substrate, the clusters are polarized by the strong external force, accompanied by the appearance of interesting orientational order parallel to the force and translational order perpendicular to the force. Under the condition of strong external force, the influences of density of pins and temperature are also studied.

Diffusion over a fluctuating barrier in underdamped dynamics.

We apply a Langevin model by imposing additive and multiplicative noises to study thermally activated diffusion over a fluctuating barrier in underdamped dynamics. The barrier fluctuation is characterized by Gaussian colored noise with exponential correlation. We present the exact solutions for the first and second moments. Furthermore, we use direct simulations to calculate the asymptotic probability for a Brownian particle passing over the fluctuating barrier. The results indicate that the correlation of the fluctuating barrier is crucial for barrier crossing dynamics.

Noise-induced anomalous diffusion over a periodically modulated saddle.

We study analytically and numerically the anomalous diffusion across periodically modulated parabolic potential within Langevin and Fokker-Planck descriptions. We find that the probability of particles passing over the saddle is affected strikingly by the periodical modulation with average zero bias. Particularly, the initial phase plays an important role in the modulation effect. The effect of the correlation time of external Ornstein-Uhlenbeck noise on dynamical process is also discussed. A reduction in overpassing probability is observed due to finite correlation time.

Suppression of spirals and turbulence in inhomogeneous excitable media.

Suppression of spiral and turbulence in inhomogeneous media due to local heterogeneity with higher excitability is investigated numerically. When the inhomogeneity is small, control tactics by boundary periodic forcing (BPF) is effective against the existing spiral and turbulence. When the inhomogeneity of excitability is large, a rotating electric field (REF) is utilized to "smooth" regional heterogeneity based on driven synchronization. Consequently, a control approach combining BPF with REF is proposed to suppress the spiral and turbulence. The underlying mechanism of successful suppression is discussed in terms of dispersion relation.

Model study of prionlike folding behavior in aggregated proteins.

We investigate the folding behavior of protein sequences by numerically studying all sequences with a maximally compact lattice model through exhaustive enumeration. We get the prionlike behavior of protein folding. Individual proteins remaining stable in the isolated native state may change their conformations when they aggregate. We observe the folding properties as the interfacial interaction strength changes and find that the strength must be strong enough before the propagation of the most stable structures happens.

Medium effects on the selection of sequences folding into stable proteins in a simple model.

We study the medium effects on the selection of sequences in protein folding by taking into account surface potential in hydrophobic-polar model. Our numerical calculation demonstrates that the surface potential enhances the average gap for the highly designable structures. It also shows that the most stable structure may be no longer the most stable one if the medium is changed.

Role of chaos in one-dimensional heat conductivity.

We investigate the heat conduction in a quasi-one-dimensional gas model with various degrees of chaos. Our calculations indicate that the heat conductivity kappa is independent of system size when the chaos of the channel is strong enough. The different diffusion behaviors for the cases of chaotic and nonchaotic channels are also studied. The numerical results of divergent exponent alpha of heat conduction and diffusion exponent beta are consistent with the formula alpha = 2 - 2/beta. We explore the temperature profiles numerically and analytically, which show that the temperature jump is primarily attributed to superdiffusion for both nonchaotic and chaotic cases, and for the latter case of superdiffusion the finite size affects the value of beta remarkably.