Mixing Optimization in Grooved Serpentine Microchannels

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Computational fluid dynamics modeling at Reynolds numbers ranging from 10 to 100 was used to characterize the performance of a new type of micromixer employing a serpentine channel with a grooved surface. The new topology exploits the overlap between the typical Dean flows present in curved channels due to the centrifugal forces experienced by the fluids, and the helical flows induced by slanted groove-ridge patterns with respect to the direction of the flow. The resulting flows are complex, with multiple vortices and saddle points, leading to enhanced mixing across the section of the channel. The optimization of the mixers with respect to the inner radius of curvature (Rin) of the serpentine channel identifies the designs in which the mixing index quality is both high (M \u3e 0.95) and independent of the Reynolds number across all the values investigated

Can a leader be seen as too ethical? The curvilinear effects of ethical leadership

Ethical leadership predicts important organizational outcomes such as decreased deviant and increased organizational citizenship behavior (OCB). We argued that due to the distinct nature of these two types of employee behaviors, ethical leadership decreases deviance in a linear manner (i.e., more ethical leadership leading to less deviance), but we expected ethical leadership to reveal a curvilinear relationship with respect to OCB. Specifically, we expected that, at lower levels, ethical leadership promotes OCB. However, at high levels, ethical leadership should lead to a decrease in these behaviors. We also examined a mechanism that explains this curvilinear pattern, that is, followers’ perceptions of moral reproach. Our predictions were supported in three organizational field studies and an experiment. These findings offer a better understanding of the processes that underlie the workings of ethical leadership. They also imply a dilemma for organizations in which they face the choice between limiting deviant employee behavior and promoting OCB

Employing machine learning for reliable miRNA target identification in plants

<p>Abstract</p> <p>Background</p> <p>miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.</p> <p>Result</p> <p>In the present work, a Support Vector Regression (SVR) approach has been implemented for plant miRNA target identification, utilizing position specific dinucleotide density variation information around the target sites, to yield highly reliable result. It has been named as p-TAREF (plant-Target Refiner). Performance comparison for p-TAREF was done with other prediction tools for plants with utmost rigor and where p-TAREF was found better performing in several aspects. Further, p-TAREF was run over the experimentally validated miRNA targets from species like <it>Arabidopsis</it>, <it>Medicago</it>, Rice and Tomato, and detected them accurately, suggesting gross usability of p-TAREF for plant species. Using p-TAREF, target identification was done for the complete Rice transcriptome, supported by expression and degradome based data. miR156 was found as an important component of the Rice regulatory system, where control of genes associated with growth and transcription looked predominant. The entire methodology has been implemented in a multi-threaded parallel architecture in Java, to enable fast processing for web-server version as well as standalone version. This also makes it to run even on a simple desktop computer in concurrent mode. It also provides a facility to gather experimental support for predictions made, through on the spot expression data analysis, in its web-server version.</p> <p>Conclusion</p> <p>A machine learning multivariate feature tool has been implemented in parallel and locally installable form, for plant miRNA target identification. The performance was assessed and compared through comprehensive testing and benchmarking, suggesting a reliable performance and gross usability for transcriptome wide plant miRNA target identification.</p

Small RNA and Degradome Deep Sequencing Reveals Drought-and Tissue-Specific Micrornas and Their Important Roles in Drought-Sensitive and Drought-Tolerant Tomato Genotypes

Drought stress has adverse impacts on plant production and productivity. MicroRNAs (miRNAs) are one class of noncoding RNAs regulating gene expression post‐transcriptionally. In this study, we employed small RNA and degradome sequencing to systematically investigate the tissue‐specific miRNAs responsible to drought stress, which are understudied in tomato. For this purpose, root and upground tissues of two different drought‐responsive tomato genotypes (Lycopersicon esculentum as sensitive and L. esculentum var. cerasiforme as tolerant) were subjected to stress with 5% polyethylene glycol for 7 days. A total of 699 conserved miRNAs belonging to 578 families were determined and 688 miRNAs were significantly differentially expressed between different treatments, tissues and genotypes. Using degradome sequencing, 44 target genes were identified associated with 36 miRNA families. Drought‐related miRNAs and their targets were enriched functionally by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Totally, 53 miRNAs targeted 23 key drought stress‐ and tissue development‐related genes, including DRP (dehydration‐responsive protein), GTs (glycosyltransferases), ERF (ethylene responsive factor), PSII (photosystem II) protein, HD‐ZIP (homeodomain‐leucine zipper), MYB and NAC‐domain transcription factors. miR160, miR165, miR166, miR171, miR398, miR408, miR827, miR9472, miR9476 and miR9552 were the key miRNAs functioning in regulation of these genes and involving in tomato response to drought stress. Additionally, plant hormone signal transduction pathway genes were differentially regulated by miR169, miR172, miR393, miR5641, miR5658 and miR7997 in both tissues of both sensitive and tolerant genotypes. These results provide new insight into the regulatory role of miRNAs in drought response with plant hormone signal transduction and drought‐tolerant tomato breeding

Alternating Current Voltammetry at a Bipolar Electrode with Smartphone Luminescence Imaging for Point‐of‐Need Sensing

Bipolar electrochemistry allows for facile arraying of tens to thousands of electrochemical sensors that can be controlled by a single pair of driving electrodes. While bipolar electrodes (BPEs) have been applied to many sensing motifs, their sensitivity and specificity are limited by the lack of diversity in voltammetric methods that have been developed for these wireless electrodes. In this study, electrochemiluminescence (ECL) from the co‐oxidation of Ru(bpy) 3 2+ and tripropylamine (TPA) is evaluated as a reporting reaction for alternating current voltammetry (ACV) on a BPE at frequencies of 1.0 Hz and 5.0 Hz. We observe sinusoidal alternating luminescence that follows a similar trend to that of the simultaneously monitored current – a plot of the amplitude versus potential approximates a bell‐shaped curve. Notably, the luminescent response to the current is detected with a smartphone, which underscores the portability of this method. The fidelity of the transduced signal is determined both in a traditional 3‐electrode configuration and at a BPE. These experimental results indicate that the alternating luminescence follows the current sufficiently for quantitative sensing but is diminished at higher frequencies and peaks at a shifted potential. These results are significant because they demonstrate the potential for application of ACV at BPE arrays for multiplexed point‐of‐need sensors and provide guidance for the selection of reporting reactions in this context.This is the peer-reviewed version of the following article: Anand, Robbyn K., Kira L. Rahn, and Tyler D. Rhoades. "Alternating Current Voltammetry at a Bipolar Electrode with Smartphone Luminescence Imaging for Point‐of‐Need Sensing." ChemElectroChem (2020), which has been published in final form at DOI: 10.1002/celc.202000079. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Posted with permission.</p

Generation of Oxygenating Fluorinated Methacrylamide Chitosan Microparticles to Increase Cell Survival and Function in Large Liver Spheroids

Despite advances in the development of complex culture technologies, the utility, survival, and function of large 3D cell aggregates, or spheroids, are impeded by mass transport limitations. The incorporation of engineered microparticles into these cell aggregates offers a promising approach to increase spheroid integrity through the creation of extracellular spaces to improve mass transport. In this study, we describe the formation of uniform oxygenating fluorinated methacrylamide chitosan (MACF) microparticles via a T-shaped microfluidic device, which when incorporated into spheroids increased extracellular spacing and enhanced oxygen transport via perfluorocarbon substitutions. The addition of MACF microparticles into large liver cell spheroids supported the formation of stable and large spheroids (\u3e500 μm in diameter) made of a heterogeneous population of immortalized human hepatoma (HepG2) and hepatic stellate cells (HSCs) (4 HepG2/1 HSC), especially at a 150:1 ratio of cells to microparticles. Further, as confirmed by the albumin, urea, and CYP3A4 secretion amounts into the culture media, biological functionality was maintained over 10 days due to the incorporation of MACF microparticles as compared to controls without microparticles. Importantly, we demonstrated the utility of fluorinated microparticles in reducing the number of hypoxic cells within the core regions of spheroids, while also promoting the diffusion of other small molecules in and out of these 3D in vitro models