The engineering of a home-made portable double-layer filtration and concentration device with the common syringe for rapid analysis of water samples is reported. The core elements of the device were two installed filtration membranes with different pore sizes for respective functions. The upper filtration membrane was used for preliminary intercepting large interfering impurities (interception membrane), while the lower filtration membrane was used for collecting multiple target pathogens (enrichment membrane) for determination. This combination can make the contaminated environmental water, exemplified by surface water, filtrated quickly through the device and just retained the target bacteria of Escherichia coli O157:H7, Staphylococcus aureus, and Listeria monocytogenes on the lower enrichment membrane. Integrating with surface-enhanced Raman spectra (SERS) platform to decode the SERS-Tags (SERS-TagCVa, SERS-TagR6G, and SERS-TagMB) already labeled on each of the enriched bacteria based the antibody-mediated immuno-recognition effect, fast separation, concentration, and detection of multiple pathogenic bacteria from the bulk of contaminated environmental water were realized. Results show that within 30 min, all target bacteria in the lake water can be simultaneously and accurately measured in the range from 101 to 106 CFU mL-1 with detection limit of 10.0 CFU mL-1 without any pre-culture procedures. This work highlights the simplicity, rapidness, cheapness, selectivity, and the robustness of the constructed method for simultaneous detecting multiple pathogens in aqueous samples. This protocol opens a new avenue for facilitating the development of versatile analytical tools for drinking water and food safety monitoring in underdeveloped or developing countries.

Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.

With the advantage of providing more natural and flexible control manner, brain-computer interface systems based on motor imagery electroencephalogram (EEG) have been widely used in the field of human-machine interaction. However, due to the lower signal-noise ratio and poor spatial resolution of EEG signals, the decoding accuracy is relative low. To solve this problem, a novel convolutional neural network based on temporal-spatial feature learning (TSCNN) was proposed for motor imagery EEG decoding. Firstly, for the EEG signals preprocessed by band-pass filtering, a temporal-wise convolution layer and a spatial-wise convolution layer were respectively designed, and temporal-spatial features of motor imagery EEG were constructed. Then, 2-layer two-dimensional convolutional structures were adopted to learn abstract features from the raw temporal-spatial features. Finally, the softmax layer combined with the fully connected layer were used to perform decoding task from the extracted abstract features. The experimental results of the proposed method on the open dataset showed that the average decoding accuracy was 80.09%, which is approximately 13.75% and 10.99% higher than that of the state-of-the-art common spatial pattern (CSP) + support vector machine (SVM) and filter bank CSP (FBCSP) + SVM recognition methods, respectively. This demonstrates that the proposed method can significantly improve the reliability of motor imagery EEG decoding.
基于运动想象脑电（EEG）的脑-机接口系统能够为用户提供更为自然、灵活的控制方式，已广泛应用到人机交互领域。然而，由于目前运动想象脑电的信噪比及空间分辨率较低，导致信号解码正确率较低。针对这一问题，本文提出一种基于时空特征学习卷积神经网络（TSCNN）的运动想象脑电解码方法。首先，针对经过带通滤波预处理的脑电信号，依次设计时间和空间维度上的卷积层，构造出运动想象脑电的时空特征；然后，利用 2 层二维卷积结构对脑电的时空特征进行抽象学习；最后，通过全连接层和 Softmax 层对 TSCNN 学习的抽象特征进行解码。利用公开数据集对该方法进行实验测试，结果表明，所提方法的平均解码精度达到 80.09%，分别比经典的解码方法共空间模式（CSP） + 支持向量机（SVM）和滤波器组 CSP（FBCSP） + SVM 提高了 13.75% 和 10.99%，显著提升了运动想象脑电解码的可靠性。.

The Notch signaling pathway comprises multiple ligands that are used in distinct biological contexts. In principle, different ligands could activate distinct target programs in signal-receiving cells, but it is unclear how such ligand discrimination could occur. Here, we show that cells use dynamics to discriminate signaling by the ligands Dll1 and Dll4 through the Notch1 receptor. Quantitative single-cell imaging revealed that Dll1 activates Notch1 in discrete, frequency-modulated pulses that specifically upregulate the Notch target gene Hes1. By contrast, Dll4 activates Notch1 in a sustained, amplitude-modulated manner that predominantly upregulates Hey1 and HeyL. Ectopic expression of Dll1 or Dll4 in chick neural crest produced opposite effects on myogenic differentiation, showing that ligand discrimination can occur in vivo. Finally, analysis of chimeric ligands suggests that ligand-receptor clustering underlies dynamic encoding of ligand identity. The ability of the pathway to utilize ligands as distinct communication channels has implications for diverse Notch-dependent processes.

The RAF-MEK-ERK signalling pathway controls fundamental, often opposing cellular processes such as proliferation and apoptosis. Signal duration has been identified to play a decisive role in these cell fate decisions. However, it remains unclear how the different early and late responding gene expression modules can discriminate short and long signals. We obtained both protein phosphorylation and gene expression time course data from HEK293 cells carrying an inducible construct of the proto-oncogene RAF By mathematical modelling, we identified a new gene expression module of immediate-late genes (ILGs) distinct in gene expression dynamics and function. We find that mRNA longevity enables these ILGs to respond late and thus translate ERK signal duration into response amplitude. Despite their late response, their GC-rich promoter structure suggested and metabolic labelling with 4SU confirmed that transcription of ILGs is induced immediately. A comparative analysis shows that the principle of duration decoding is conserved in PC12 cells and MCF7 cells, two paradigm cell systems for ERK signal duration. Altogether, our findings suggest that ILGs function as a gene expression module to decode ERK signal duration.

Mitochondrial Ca2+ uptake through the Ca2+ uniporter supports cell functions, including oxidative metabolism, while meeting tissue-specific calcium signaling patterns and energy needs. The molecular mechanisms underlying tissue-specific control of the uniporter are unknown. Here, we investigated a possible role for tissue-specific stoichiometry between the Ca2+-sensing regulators (MICUs) and pore unit (MCU) of the uniporter. Low MICU1:MCU protein ratio lowered the [Ca2+] threshold for Ca2+ uptake and activation of oxidative metabolism but decreased the cooperativity of uniporter activation in heart and skeletal muscle compared to liver. In MICU1-overexpressing cells, MICU1 was pulled down by MCU proportionally to MICU1 overexpression, suggesting that MICU1:MCU protein ratio directly reflected their association. Overexpressing MICU1 in the heart increased MICU1:MCU ratio, leading to liver-like mitochondrial Ca2+ uptake phenotype and cardiac contractile dysfunction. Thus, the proportion of MICU1-free and MICU1-associated MCU controls these tissue-specific uniporter phenotypes and downstream Ca2+ tuning of oxidative metabolism.