Application of BioMEMS, Optics, and Electronics to Bioenergy

Today, the development of eco-friendly and renewable energy sources is imperative because we are facing a severe global warming and energy depletion. In this regard, the microalgae that absorb carbon dioxide from the atmosphere and convert it into a high-energy carrier which can be used as biofuel are in the spotlight. Microalgae have been considered as a next-generation energy source in that it is not only extremely renewable and reducing carbon dioxide but also highly productive even with non-arable lands, seawater or wastewater. However, its applicability to next-generation energy sources still faces practical limitations, such as the higher unit cost of producing microalgae-based biofuel compared to fossil fuels. The reason is that technologies essential to efficient and economically competitive production of microalgae-based biofuel have not yet been fully developed. The representative bottlenecks include the lack of technologies as follows; 1) methods for screening the most productive microalgae strain from the hundreds of thousands of natural and genetically engineered strains rapidly and efficiently. 2) on-site, real-time, and non-invasive methods for monitoring of mass production of microalgae over the extensive area. In this respect, this thesis discusses the novel methods for superior microalgal species selection and real-time microalgal cultivation monitoring utilizing various technologies of BioMEMS, optics, and electronics.First, we demonstrate a buoyancy-based cell separation method that can easily sort out the best microalgal strain accumulating the largest amount of lipids using BioMEMS technology. Our simple microfluidic channel structure inducing hydraulic jumps of incoming cells allows the selection of only the lightest species (i.e., superior one which accumulates the largest amount of lipid) among numerous microalgae cells having various densities depending on their lipid amount. This method has the advantage of being able to select superior species easily and rapidly without additional labeling process and observation of the entire microalgal growth process.Second, we demonstrate an integrated microalgae analysis photobioreactor for rapid strain selection using optics. Our photobioreactor, hemispherical cavity embedded with metal nanostructures, scatters specific wavelengths favored by microalgae, which will increase the photosynthetic efficiency of microalgae, resulting in shorter screening times through rapid growth. Besides, the additional optical property (i.e., light focusing) provided by the geometry of a hemispherical cavity helps rapid screening even with naked-eye by facilitating rapid growth through cell gathering and cell-cell interactions.Lastly, we demonstrate a novel electrical sensor that can effectively monitor microalgae in the real field. Our approach utilizes electric signal, photocurrent, derived from the channel-rhodopsin, a unique feature of microalgae. This new method overcomes the limitations in terms of the field application that other existing approaches have not solved in that it can monitor microalgae in real-time and in-situ even with low cost without the need for additional sample processing steps.We believe this series of new approaches can elevate the productivity in real fields of microalgae-based biofuel production by contributing to the superior strain selection and production management and are expected to provide an opportunity to step closer to the realization of microalgae as a next-generation energy source

Rapid Optical Cavity PCR.

Recent outbreaks of deadly infectious diseases, such as Ebola and Middle East respiratory syndrome coronavirus, have motivated the research for accurate, rapid diagnostics that can be administered at the point of care. Nucleic acid biomarkers for these diseases can be amplified and quantified via polymerase chain reaction (PCR). In order to solve the problems of conventional PCR--speed, uniform heating and cooling, and massive metal heating blocks--an innovative optofluidic cavity PCR method using light-emitting diodes (LEDs) is accomplished. Using this device, 30 thermal cycles between 94 °C and 68 °C can be accomplished in 4 min for 1.3 μL (10 min for 10 μL). Simulation results show that temperature differences across the 750 μm thick cavity are less than 2 °C and 0.2 °C, respectively, at 94 °C and 68 °C. Nucleic acid concentrations as low as 10(-8) ng μL(-1) (2 DNA copies per μL) can be amplified with 40 PCR thermal cycles. This simple, ultrafast, precise, robust, and low-cost optofluidic cavity PCR is favorable for advanced molecular diagnostics and precision medicine. It is especially important for the development of lightweight, point-of-care devices for use in both developing and developed countries

Genome-Wide Association Study of Lung Adenocarcinoma in East Asia and Comparison With a European Population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium.

BACKGROUND: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. METHODS: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. RESULTS: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests). CONCLUSIONS: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease

The motivations for the adoption of management innovation by local governments and its performance effects

This article analyses the economic, political and institutional antecedents and performance effects of the adoption of shared Senior Management Teams (SMTs) – a management innovation (MI) that occurs when a team of senior managers oversees two or more public organizations. Findings from statistical analysis of 201 English local governments and interviews with organizational leaders reveal that shared SMTs are adopted to develop organisational capacity in resource‐challenged, politically risk‐averse governments, and in response to coercive and mimetic institutional pressures. Importantly, sharing SMTs may reduce rather than enhance efficiency and effectiveness due to redundancy costs and the political transaction costs associated with diverting resources away from a high‐performing partner to support their lower‐performing counterpart

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction  = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications

Risk prediction and interaction analysis using polygenic risk score of type 2 diabetes in a Korean population

Abstract Joint modelling of genetic and environmental risk factors can provide important information to predict the risk of type 2 diabetes (T2D). Therefore, to predict the genetic risk of T2D, we constructed a polygenic risk score (PRS) using genotype data of one Korean cohort, KARE (745 cases and 2549 controls), and the genome-wide association study summary statistics of Biobank Japan. We evaluated the performance of PRS in an independent Korean cohort, HEXA (5684 cases and 35,703 controls). Individuals with T2D had a significantly higher mean PRS than controls (0.492 vs. − 0.078, p $$\approx 0$$ ≈ 0 ). PRS predicted the risk of T2D with an AUC of 0.658 (95% CI 0.651–0.666). We also evaluated interaction between PRS and waist circumference (WC) in the HEXA cohort. PRS exhibited a significant sub-multiplicative interaction with WC (ORinteraction 0.991, 95% CI 0.987–0.995, p interaction = 4.93 × 10–6) in T2D. The effect of WC on T2D decreased as PRS increased. The sex-specific analyses produced similar interaction results, revealing a decreased WC effect on T2D as the PRS increased. In conclusion, the risk of WC for T2D may differ depending on PRS and those with a high PRS might develop T2D with a lower WC threshold. Our findings are expected to improve risk prediction for T2D and facilitate the identification of individuals at an increased risk of T2D