Monitoring bacterial growth using tunable resistive pulse sensing with a pore-based technique.

A novel bacterial growth monitoring method using a tunable resistive pulse sensor (TRPS) system is introduced in this study for accurate and sensitive measurement of cell size and cell concentration simultaneously. Two model bacterial strains, Bacillus subtilis str.168 (BSU168) and Escherichia coli str.DH5α (DH5α), were chosen for benchmarking the growth-monitoring performance of the system. Results showed that the technique of TRPS is sensitive and accurate relative to widely used methods, with a lower detection limit of cell concentration measurement of 5 × 105 cells/ml; at the same time, the mean coefficient of variation from TRPS was within 2 %. The growth of BSU168 and DH5α in liquid cultures was studied by TRPS, optical density (OD), and colony plating. Compared to OD measurement, TRPS-measured concentration correlates better with colony plating (R = 0.85 vs. R = 0.72), which is often regarded as the gold standard of cell concentration determination. General agreement was also observed by comparing TRPS-derived cell volume measurements and those determined from microscopy. We have demonstrated that TRPS is a reliable method for bacterial growth monitoring, where the study of both cell volume and cell concentration are needed to provide further details about the physical aspects of cell dynamics in real time.

Integrated Printed Microfluidic Biosensors.

Integrated printed microfluidic biosensors are one of the most recent point-of-care (POC) sensor developments. Fast turnaround time for production and ease of customization, enabled by the integration of recognition elements and transducers, are key for on-site biosensing for both healthcare and industry and for speeding up translation to real-life applications. Here, we provide an overview of recent progress in printed microfluidics, from the 2D to the 4D level, accompanied by novel sensing element integration. We also explore the latest trends in integrated printed microfluidics for healthcare, especially POC diagnostics, and food safety applications.

Physalin A exerts anti-tumor activity in non-small cell lung cancer cell lines by suppressing JAK/STAT3 signaling.

The signal transducers and activators of transcription 3 (STAT3) signaling pathway plays critical roles in the pathogenesis and progression of various human cancers, including non-small cell lung cancer (NSCLC). In this study, we aimed to evaluate the therapeutic potential of physalin A, a bioactive withanolide derived from Physalis alkekengi var. francheti used in traditional Chinese medicine, was evaluated in human NSCLC cells. Its and determined whether it effect oninhibited both constitutive and induced STAT3 activity, through repressing the phosphorylation levels of JAK2 and JAK3, resulting in anti-proliferation and pro-apoptotic effects on NSCLC cells was also determined, and. theThe antitumor effects of physalin A were also validated usingin an in vivo mouse xenograft models of NSCLC cells. Physalin A had anti-proliferative and pro-apoptotic effects in NSCLC cells with constitutively activated STAT3; it also suppressed both constitutive and induced STAT3 activity by modulating the phosphorylation of JAK2 and JAK3. Furthermore, physalin A abrogated the nuclear translocation and transcriptional activity of STAT3, thereby decreasing the expression levels of STAT3, its target genes, such as Bcl-2 and XIAP. Knockdown of STAT3 expression by small interfering RNA (siRNA) significantly enhanced the pro-apoptotic effects of physalin A in NSCLC cells. Moreover, physalin A significantly suppressed tumor xenograft growth. Thus, as an inhibitor of JAK2/3-STAT3 signaling, physalin A, has potent anti-tumor activities, which may facilitate the development of a therapeutic strategy for treating NSCLC.

The Essential Component in DNA-Based Information Storage System: Robust Error-Tolerating Module.

The size of digital data is ever increasing and is expected to grow to 40,000 EB by 2020, yet the estimated global information storage capacity in 2011 is <300 EB, indicating that most of the data are transient. DNA, as a very stable nano-molecule, is an ideal massive storage device for long-term data archive. The two most notable illustrations are from Church et al. and Goldman et al., whose approaches are well-optimized for most sequencing platforms - short synthesized DNA fragments without homopolymer. Here, we suggested improvements on error handling methodology that could enable the integration of DNA-based computational process, e.g., algorithms based on self-assembly of DNA. As a proof of concept, a picture of size 438 bytes was encoded to DNA with low-density parity-check error-correction code. We salvaged a significant portion of sequencing reads with mutations generated during DNA synthesis and sequencing and successfully reconstructed the entire picture. A modular-based programing framework - DNAcodec with an eXtensible Markup Language-based data format was also introduced. Our experiments demonstrated the practicability of long DNA message recovery with high error tolerance, which opens the field to biocomputing and synthetic biology.