Finding the optimal design of a passive microfluidic mixer.

The ability to thoroughly mix two fluids is a fundamental need in microfluidics. While a variety of different microfluidic mixers have been designed by researchers, it remains unknown which (if any) of these mixers are optimal (that is, which designs provide the most thorough mixing with the smallest possible fluidic resistance across the mixer). In this work, we automatically designed and rationally optimized a microfluidic mixer. We accomplished this by first generating a library of thousands of different randomly designed mixers, then using the non-dominated sorting genetic algorithm II (NSGA-II) to optimize the random chips in order to achieve Pareto efficiency. Pareto efficiency is a state of allocation of resources (e.g. driving force) from which it is impossible to reallocate so as to make any one individual criterion better off (e.g. pressure drop) without making at least one individual criterion (e.g. mixing performance) worse off. After 200 generations of evolution, Pareto efficiency was achieved and the Pareto-optimal front was found. We examined designs at the Pareto-optimal front and found several design criteria that enhance the mixing performance of a mixer while minimizing its fluidic resistance; these observations provide new criteria on how to design optimal microfluidic mixers. Additionally, we compared the designs from NSGA-II with some popular microfluidic mixer designs from the literature and found that designs from NSGA-II have lower fluidic resistance with similar mixing performance. As a proof of concept, we fabricated three mixer designs from 200 generations of evolution and one conventional popular mixer design and tested the performance of these four mixers. Using this approach, an optimal design of a passive microfluidic mixer is found and the criteria of designing a passive microfluidic mixer are established

p21 is decreased in polycystic kidney disease and leads to increased epithelial cell cycle progression: roscovitine augments p21 levels.

BackgroundAutosomal dominant polycystic kidney disease (ADPKD) is a common genetic disease with few treatment options other than renal replacement therapy. p21, a cyclin kinase inhibitor which has pleiotropic effects on the cell cycle, in many cases acts to suppress cell cycle progression and to prevent apoptosis. Because defects in cell cycle arrest and apoptosis of renal tubular epithelial cells occur in PKD, and in light of earlier reports that polycystin-1 upregulates p21 and that the cyclin-dependent kinase inhibitor roscovitine arrests progression in a mouse model, we asked whether (1) p21 deficiency might underlie ADPKD and (2) the mechanism of the salutary roscovitine effect on PKD involves p21.Methodsp21 levels in human and animal tissue samples as well as cell lines were examined by immunoblotting and/or immunohistochemisty. Apoptosis was assessed by PARP cleavage. p21 expression was attenuated in a renal tubular epithelial cell line by antisense methods, and proliferation in response to p21 attenuation and to roscovitine was assessed by the MTT assay.ResultsWe show that p21 is decreased in human as well as a non-transgenic rat model of ADPKD. In addition, hepatocyte growth factor, which induces transition from a cystic to a tubular phenotype, increases p21 levels. Furthermore, attenuation of p21 results in augmentation of cell cycle transit in vitro. Thus, levels of p21 are inversely correlated with renal tubular epithelial cell proliferation. Roscovitine, which has been shown to arrest progression in a murine model of PKD, increases p21 levels and decreases renal tubular epithelial cell proliferation, with no affect on apoptosis.ConclusionThe novelty of our study is the demonstration in vivo in humans and rat models of a decrement of p21 in cystic kidneys as compared to non-cystic kidneys. Validation of a potential pathogenetic model of increased cyst formation due to enhanced epithelial proliferation and apoptosis mediated by p21 suggests a mechanism for the salutary effect of roscovitine in ADPKD and supports further investigation of p21 as a target for future therapy

TMEM97 and PGRMC1 do not mediate sigma-2 ligand-induced cell death

Abstract Sigma-2 receptors have been implicated in both tumor proliferation and neurodegenerative diseases. Recently the sigma-2 receptor was identified as transmembrane protein 97 (TMEM97). Progesterone receptor membrane component 1 (PGRMC1) was also recently reported to form a complex with TMEM97 and the low density lipoprotein (LDL) receptor, and this trimeric complex is responsible for the rapid internalization of LDL. Sigma-2 receptor ligands with various structures have been shown to induce cell death in cancer cells. In the current study, we examined the role of TMEM97 and PGRMC1 in mediating sigma-2 ligand-induced cell death. Cell viability and caspase-3 assays were performed in control, TMEM97 knockout (KO), PGRMC1 KO, and TMEM97/PGRMC1 double KO cell lines treated with several sigma-2 ligands. The data showed that knockout of TMEM97, PGRMC1, or both did not affect the concentrations of sigma-2 ligands that induced 50% of cell death (EC50), suggesting that cytotoxic effects of these compounds are not mediated by TMEM97 or PGRMC1. Sigma-1 receptor ligands, (+)-pentazocine and NE-100, did not block sigma-2 ligand cytotoxicity, suggesting that sigma-1 receptor was not responsible for sigma-2 ligand cytotoxicity. We also examined whether the alternative, residual binding site (RBS) of 1,3-Di-o-tolylguanidine (DTG) could be responsible for sigma-2 ligand cytotoxicity. Our data showed that the binding affinities (K i) of sigma-2 ligands on the DTG RBS did not correlate with the cytotoxicity potency (EC50) of these ligands, suggesting that the DTG RBS was not fully responsible for sigma-2 ligand cytotoxicity. In addition, we showed that knocking out TMEM97, PGRMC1, or both reduced the initial internalization rate of a sigma-2 fluorescent ligand, SW120. However, concentrations of internalized SW120 became identical later in the control and knockout cells. These data suggest that the initial internalization process of sigma-2 ligands does not appear to mediate the cell-killing effect of sigma-2 ligands. In summary, we have provided evidence that sigma-2 receptor/TMEM97 and PGRMC1 do not mediate sigma-2 ligand cytotoxicity. Our work will facilitate elucidating mechanisms of sigma-2 ligand cytotoxicity

Single-cell transcriptomes reveal the mechanism for a breast cancer prognostic gene panel.

The clinical benefits of the MammaPrint® signature for breast cancer is well documented; however, how these genes are related to cell cycle perturbation have not been well determined. Our single-cell transcriptome mapping (algorithm) provides details into the fine perturbation of all individual genes during a cell cycle, providing a view of the cell-cycle-phase specific landscape of any given human genes. Specifically, we identified that 38 out of the 70 (54%) MammaPrint® signature genes are perturbated to a specific phase of the cell cycle. The MammaPrint® signature panel derived its clinical prognosis power from measuring the cell cycle activity of specific breast cancer samples. Such cell cycle phase index of the MammaPrint® signature suggested that measurement of the cell cycle index from tumors could be developed into a prognosis tool for various types of cancer beyond breast cancer, potentially improving therapy through targeting a specific phase of the cell cycle of cancer cells

Warp Breaks Detection in Jacquard Weaving Using MEMS: Effect of Weave on Break Signals

This paper reports a study to detect warp breaks in terms of weave structure using MEMS accelerometer based detection system. The system is briefly described. The output signals of MEMS sensors, which were mounted on harness cords of a Jacquard machine, at the moment of warp yarn break and after the break for a broad range of basic weaves were acquired during weaving. The weaves investigated are commonly used in Jacquard weaving to form patterns. The strength of the MEMS output acceleration signals was analyzed in time domain. The results show that the system is capable of detecting warp yarn breaks for the broad range of weaves studied

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces

Fatty acid transport protein 4 (FATP4) prevents light-induced degeneration of cone and rod photoreceptors by inhibiting RPE65 isomerase

Although rhodopsin is essential for sensing light for vision, it also mediates light-induced apoptosis of photoreceptors in mouse. RPE65, which catalyzes isomerization of all-trans retinyl fatty acid esters to 11-cis-retinol (11cROL) in the visual cycle, controls the rhodopsin regeneration rate and photoreceptor susceptibility to light-induced degeneration. Mutations in RPE65 have been linked to blindness in affected children. Despite such importance, the mechanism that regulates RPE65 function remains unclear. Through unbiased expression screening of a bovine retinal pigment epithelium (RPE) cDNA library, we have identified elongation of very long-chain fatty acids-like 1 (ELOVL1) and fatty acid transport protein 4 (FATP4), which each have very long-chain fatty acid acyl-CoA synthetase (VLCFA-ACS) activity, as negative regulators of RPE65. We found that the VLCFA derivative lignoceroyl (C24:0)-CoA inhibited synthesis of 11cROL, whereas palmitoyl (C16:0)-CoA promoted synthesis of 11cROL. We further found that competition of FATP4 with RPE65 for the substrate of RPE65 was also involved in the mechanisms by which FATP4 inhibits synthesis of 11cROL. FATP4 was predominantly expressed in RPE, and the FATP4-deficient RPE showed significantly higher isomerase activity. Consistent with these results, the regeneration rate of 11-cis-retinaldehyde and the recovery rate for rod light sensitivity were faster in FATP4-deficient mice than wild-type mice. Moreover, FATP4-deficient mice displayed increased accumulation of the cytotoxic all-trans retinaldehyde and hypersusceptibility to light-induced photoreceptor degeneration. Our findings demonstrate that ELOVL1, FATP4, and their products comprise the regulatory elements of RPE65 and play important roles in protecting photoreceptors from degeneration induced by light damage

Effect of Quantitative Nuclear Image Features on Recurrence of Ductal Carcinoma In Situ (DCIS) of the Breast

BACKGROUND: Nuclear grade has been associated with breast DCIS recurrence and progression to invasive carcinoma; however, our previous study of a cohort of patients with breast DCIS did not find such an association with outcome. Fifty percent of patients had heterogeneous DCIS with more than one nuclear grade. The aim of the current study was to investigate the effect of quantitative nuclear features assessed with digital image analysis on ipsilateral DCIS recurrence.CONCLUSION: Analysis of nuclear features measured by image cytometry may contribute to the classification and prognosis of breast DCIS patients with more than one nuclear grade.Author manuscript. Published in final edited form as: Cancer Informatics 2008:4 99–109.The final published version of this article is located at: http://la-press.com/article.php?article_id=583NIH U56 CA113004; to David E. AxelrodThis work was funded by the New Jersey Commission for Cancer Research 1076-CCRS0, the National Institutes of Health U56 CA113004, the Hyde and Watson Foundation, the Busch Memorial Fund, and the E.B. Fish Research Fund.NJ Commission on Cancer Research 1076-CCR-SO; to David E. Axelro