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Brain signaling occurs across a wide range of spatial and temporal scales, and analysis of brain signal variability and synchrony has attracted recent attention as markers of intelligence, cognitive states, and brain disorders. However, current technologies to measure brain signals in humans have limited resolutions either in space or in time and cannot fully capture spatiotemporal variability, leaving it untested whether temporal variability and spatiotemporal synchrony are valid and reliable proxy of spatiotemporal variability in vivo. Here we used optical voltage imaging in mice under anesthesia and wakefulness to monitor cortical voltage activity at both high spatial and temporal resolutions to investigate functional connectivity (FC, a measure of spatiotemporal synchronization), Multi-Scale Entropy (MSE, a measure of temporal variability), and their relationships to Regional Entropy (RE, a measure of spatiotemporal variability). We observed that across cortical space, MSE pattern can largely explain RE pattern at small and large temporal scales with high positive and negative correlation respectively, while FC pattern strongly negatively associated with RE pattern. The time course of FC and small scale MSE tightly followed that of RE, while large scale MSE was more loosely coupled to RE. fMRI and EEG data simulated by reducing spatiotemporal resolution of the voltage imaging data or considering hemodynamics yielded MSE and FC measures that still contained information about RE based on the high resolution voltage imaging data. This suggested that MSE and FC could still be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. Our results support the notion that FC and MSE are effective biomarkers for brain states, and provide a promising viewpoint to unify these two principal domains in human brain data analysis. • Validated multiscale entropy and functional connectivity as proxy of spatiotemporal variability with voltage imaging. • Demonstrated that multiscale entropy and functional connectivity can reflect similar brain state differences. • Addressed the practical signal resolution of EEG and fMRI on the spatiotemporal variability assessments. • Provided a unified interpretation of multiscale entropy and functional connectivity measures. [ABSTRACT FROM AUTHOR]

A novel heterotrophic nitrification and aerobic denitrification (HNAD) bacteria, identified as Bacillus thuringiensis strain WXN-23, was isolated from husk feed filtrate of a pig farm. It was the first report of Bacillus thuringiensis with the capability for HNAD and could adapt to the condition of low Carbon/Nitrogen (C/N) ratio. Nitrogen could be efficiently removed by the strain WXN-23 in simulated wastewater, be it in single or mixed form nitrogen sources. The nitrogen balance revealed that 63.5% of the initial nitrogen (5.32 mg) was lost in the form of N 2. The conditions for maximum total nitrogen (TN) removal efficiency (95.996%) were shaking speed of 126.89 r/min, a carbon C/N ratio of 5.91, the temperature of 32.81 °C, and a pH value of 8.17. The nitrification-denitrification metabolic pathway (NH 4 +–N→NH 2 OH→NO 2 −-N→NO 3 −-N→NO 2 −-N→NO→N 2 O→N 2) under aerobic conditions was determined on the basic of characteristic of N removal, N balance analysis, enzyme assay and functional genes amplification results. Strain WXN-23 was effective at wastewater treatment, with TN, NH 4 +-N, NO 3 −-N and NO 2 −-N removal efficiencies of 82.12%, 86.74%, 90.74% and 100%, respectively. • Found a heterotrophic nitrifying and aerobic denitrification Bacillus thuringiensis strain. • Bacillus thuringiensis strain WXN-23 can adapt to the condition of low C/N ratio. • Strain WXN-23 can efficiently remove nitrogen from water under aerobic conditions. • Hardly any greenhouse gas was generated by strain WXN-23 during nitrogen removal. [ABSTRACT FROM AUTHOR]