Microfluidic Concentrator Array for Quantitative Predation Study of Predatory Microbes

Thermofluid & Energy SystemsDespite future impact on the bio-nano-technological application, the study of predatory microbes has been limited due to the complexity associated with co-cultures of prey and predator. In this thesis, to accelerate and simplify the study, we have developed a microfabricated concentrator array device that makes it possible to quantify the predation rate of predator, Bdellovibrio bacteriovorus. Since the concentrator array device can constrain both prey and predator cells within 200 pL chambers at a desired range of cell densities, the predation rates could be quantified indirectly by measuring the time-dependent fluorescent intensity signals from the prey. In addition, we study many different conditions with a single set of cultures because the device can produce a wide range of initial prey to predator density ratios within various concentrator arrays through the use of microfluidic gradient generator structures. We also investigated chemotaxis of B.bacteriovorus strain HD 100 using novel microfluidic concentration gradient generator towards various compounds and prey cell itself. The results were consistent with literatures.ope

A microfluidic concentrator array for quantitative predation assays of predatory microbes

We present a microfabricated concentrator array device that makes it possible to quantify the predation rate of Bdellovibrio bacteriovorus, a predatory microbe, toward its prey, Escherichia coli str. MG1655. The device can accumulate both prey and predator microbes sequentially within a series of concentrator arrays using the motility of the microbes and microfabricated arrowhead-shaped ratchet structures. Since the device can constrain both prey and predator cells within 200 pL chambers at a desired range of cell densities, it was demonstrated that the device cannot only enhance the possibility of studying predation processes/cycles directly at a single cell level but can also quantify the predation rates indirectly by measuring the time-dependent fluorescent intensity signals from the prey. Furthermore, the device can produce a wide range of initial prey to predator density ratios within various concentrator arrays through the use of microfluidic mixer structures on a single array chip, which allows us to study many different conditions with a single set of cultures, and quantitatively characterize the predation behaviour/rate. Lastly, we note that this novel concentrator array device can be a very powerful tool facilitating studies of microbial predations and microbe-microbe interaction and may be broadly used in other microbial biotechnological applications.close6

Microfabricated ratchet structure integrated concentrator arrays for synthetic bacterial cell-to-cell communication assays

We describe a microfluidic concentrator array device that is integrated with microfabricated ratchet structures to concentrate motile bacterial cells in desired destinations with required cell densities. The device consists of many pairs of concentrators with a wide range of spacing distances on a chip, and allows cells in one concentrator to be physically separated from but chemically connected to cells in the other concentrator. Therefore, the device facilitates quantification of the effect of spacing distance on the cell-to-cell communication of synthetically engineered bacterial cells. In addition, the device enables us to control the cell number density in each concentrator unit by adjusting the concentration time and the density of cell suspensions, and the basic concentrator unit of the device can be repeatedly duplicated on a chip. Hence, the device not only facilitates an investigation of the effect of cell densities on cell-to-cell communication, but it can also be further applied to an investigation of cellular communication among multiple types of cells. Lastly, the device can be easily fabricated using a single-layered soft-lithography technology so that we believe it would provide a simple but robust means for many synthetic and systems biologists to simplify and speed up their investigations of the synthetic genetic circuits in bacterial cells.close5

Silicon carbide-free graphene growth on silicon for lithium-ion battery with high volumetric energy density

Silicon is receiving discernable attention as an active material for next generation lithium-ion battery anodes because of its unparalleled gravimetric capacity. However, the large volume change of silicon over charge-discharge cycles weakens its competitiveness in the volumetric energy density and cycle life. Here we report direct graphene growth over silicon nanoparticles without silicon carbide formation. The graphene layers anchored onto the silicon surface accommodate the volume expansion of silicon via a sliding process between adjacent graphene layers. When paired with a commercial lithium cobalt oxide cathode, the silicon carbide-free graphene coating allows the full cell to reach volumetric energy densities of 972 and 700 Whl(-1) at first and 200th cycle, respectively, 1.8 and 1.5 times higher than those of current commercial lithium-ion batteries. This observation suggests that two-dimensional layered structure of graphene and its silicon carbide-free integration with silicon can serve as a prototype in advancing silicon anodes to commercially viable technology.

Microfluidic Technologies for Synthetic Biology

Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis

Machine Learning-Based Heavy Metal Ion Detection Using Surface-Enhanced Raman Spectroscopy

Surface-Enhanced Raman Spectroscopy (SERS) is often used for heavy metal ion detection. However, large variations in signal strength, spectral profile, and nonlinearity of measurements often cause problems that produce varying results. It raises concerns about the reproducibility of the results. Consequently, the manual classification of the SERS spectrum requires carefully controlled experimentation that further hinders the large-scale adaptation. Recent advances in machine learning offer decent opportunities to address these issues. However, well-documented procedures for model development and evaluation, as well as benchmark datasets, are missing. Towards this end, we provide the SERS spectral benchmark dataset of lead(II) nitride (Pb(NO3)2) for a heavy metal ion detection task and evaluate the classification performance of several machine learning models. We also perform a comparative study to find the best combination between the preprocessing methods and the machine learning models. The proposed model can successfully identify the Pb(NO3)2 molecule from SERS measurements of independent test experiments. In particular, the proposed model shows an 84.6% balanced accuracy for the cross-batch testing task

Development of Gene Expression-Based Random Forest Model for Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) response is an important indicator of patient survival in triple negative breast cancer (TNBC), but predicting chemosensitivity remains a challenge in clinical practice. We developed an 86-gene-based random forest (RF) classifier capable of predicting neoadjuvant chemotherapy response (pathological Complete Response (pCR) or Residual Disease (RD)) in TNBC patients. The performance of pCR classification of the proposed model was evaluated by Receiver Operating Characteristic (ROC) curve and Precision Recall (PR) curve. The AUROC and AUPRC of the proposed model on the test set were 0.891 and 0.829, respectively. At a predefined specificity (>90%), the proposed model shows a superior sensitivity compared to the best performing reported NAC response prediction model (69.2% vs. 36.9%). Moreover, the predicted pCR status by the model well explains the distance recurrence free survival (DRFS) of TNBC patients. In addition, the pCR probabilities of the proposed model using the expression profiles of the CCLE TNBC cell lines show a high Spearman rank correlation with cyclophosphamide sensitivity in the TNBC cell lines (SRCC =0.697, p-value =0.031). Associations between the 86 genes and DNA repair/cell cycle mechanisms were provided through function enrichment analysis. Our study suggests that the random forest-based prediction model provides a reliable prediction of the clinical response to neoadjuvant chemotherapy and may explain chemosensitivity in TNBC

Application of Style Transfer in the Vectorization Process of Floorplans (Short Paper)

As the market for indoor spatial information burgeons, the construction of indoor spatial databases consequently gain attention. Since floorplans are portable records of buildings, they are an indispensable source for the efficient construction of indoor environments. However, as previous research on floorplan information retrieval usually targeted specific formats, a system for constructing spatial information must include heuristic refinement steps. This study aims to convert diverse floorplans into an integrated format using the style transfer by deep networks. Our deep networks mimic a robust perception of human that recognize the cell structure of floorplans under various formats. The integrated format ensures that unified post-processing steps are required to the vectorization of floorplans. Through this process, indoor spatial information is constructed in a pragmatic way, using a plethora of architectural floorplans