Development of Spectral Nano-Flow Cytometry for High-Throughput Multiparameter Analysis of Individual Biological Nanoparticles.

Correlated analysis of multiple biochemical parameters at the single-particle level and in a high-throughput manner is essential for insights into the diversity and functions of biological nanoparticles (BNPs), such as bacteria and subcellular organelles. To meet this challenge, we developed a highly sensitive spectral nano-flow cytometer (S-nFCM) by integrating a spectral recording module to a laboratory-built nFCM that is 4-6 orders of magnitude more sensitive in side scattering detection and 1-2 orders of magnitude more sensitive in fluorescence detection than conventional flow cytometers. An electron-multiplying charge-coupled device (EMCCD) was used to acquire the full fluorescence spectra of single BNPs upon holographic grating dispersion. Up to 10,000 spectra can be collected in 1 min with 2.1 nm resolution. The precision, linearity, and sensitivity were examined. Complete discernment of single influenza viruses against the background signal, discrimination of different strains of marine cyanobacteria in a mixed sample based on their spectral properties of natural fluorescence, classification of bacterial categories exhibiting different patterns of antigen expression, and multiparameter analysis of single mitochondria for drug discovery were successfully demonstrated.

[A Maternal Health Care System Based on Mobile Health Care].

Wearable devices are used in the new design of the maternal health care system to detect electrocardiogram and oxygen saturation signal while smart terminals are used to achieve assessments and input maternal clinical information. All the results combined with biochemical analysis from hospital are uploaded to cloud server by mobile Internet. Machine learning algorithms are used for data mining of all information of subjects. This system can achieve the assessment and care of maternal physical health as well as mental health. Moreover, the system can send the results and health guidance to smart terminals.

Evidence for self-positivity bias in a subliminal self-cue: An event-related potential study.

Previous studies studies indicate that individuals tend to integrate positive information into their self-concept. However, whether such self-positivity bias would still be observed without an explicit self-related cue is unknown. In the present study, 29 participants were asked to evaluate a series of positive and negative trait adjectives, after the participants were presented with their own name or another name subliminally. During the task, their electroencephalograms were recorded. The results showed participants responded faster to positive traits than to negative traits in the self-name cue conditions. In addition, both the latencies and the amplitudes of the N400 showed significant interaction between name-cue and valence in N400 (240-440 ms) amplitudes. The earlier N400 latencies and smaller N400 amplitudes were associated with positive traits in the self-name cue. These results suggested that the self-positivity bias can also be observed in a subliminally presenting self-cue, indicating the robustness of self-positivity bias.

Morphology and Performance of Polymer Solar Cell Characterized by DPD Simulation and Graph Theory.

The morphology of active layers in the bulk heterojunction (BHJ) solar cells is critical to the performance of organic photovoltaics (OPV). Currently, there is limited information for the morphology from transmission electron microscopy (TEM) techniques. Meanwhile, there are limited approaches to predict the morphology /efficiency of OPV. Here we use Dissipative Particle Dynamics (DPD) to determine 3D morphology of BHJ solar cells and show DPD to be an efficient approach to predict the 3D morphology. Based on the 3D morphology, we estimate the performance indicator of BHJ solar cells by using graph theory. Specifically, we study poly (3-hexylthiophene)/[6, 6]-phenyl-C61butyric acid methyl ester (P3HT/PCBM) BHJ solar cells. We find that, when the volume fraction of PCBM is in the region 0.4 ∼ 0.5, P3HT/PCBM will show bi-continuous morphology and optimum performance, consistent with experimental results. Further, the optimum temperature (413 K) for the morphology and performance of P3HT/PCBM is in accord with annealing results. We find that solvent additive plays a critical role in the desolvation process of P3HT/PCBM BHJ solar cell. Our approach provides a direct method to predict dynamic 3D morphology and performance indicator for BHJ solar cells.