Targeting human apurinic/apyrimidinic endonuclease 1 (APE1) in phosphatase and tensin homolog (PTEN) deficient melanoma cells for personalized therapy

Phosphatase and tensin homolog (PTEN) loss is associated with genomic instability. APE1 is a key player in DNA base excision repair (BER) and an emerging drug target in cancer. We have developed small molecule inhibitors against APE1 repair nuclease activity. In the current study we explored a synthetic lethal relationship between PTEN and APE1 in melanoma. Clinicopathological significance of PTEN mRNA and APE1 mRNA expression was investigated in 191 human melanomas. Preclinically, PTEN-deficient BRAF-mutated (UACC62, HT144, and SKMel28), PTEN-proficient BRAF-wildtype (MeWo), and doxycycline-inducible PTEN-knockout BRAF-wildtype MeWo melanoma cells were DNA repair expression profiled and investigated for synthetic lethality using a panel of four prototypical APE1 inhibitors. In human tumours, low PTEN mRNA and high APE1 mRNA was significantly associated with reduced relapse free and overall survival. Pre-clinically, compared to PTEN-proficient cells, PTEN-deficient cells displayed impaired expression of genes involved in DNA double strand break (DSB) repair. Synthetic lethality in PTEN-deficient cells was evidenced by increased sensitivity, accumulation of DSBs and induction of apoptosis following treatment with APE1 inhibitors. We conclude that PTEN deficiency is not only a promising biomarker in melanoma, but can also be targeted by a synthetic lethality strategy using inhibitors of BER, such as those targeting APE1

Technology assessment and feasibility study of high-throughput single cell force spectroscopy

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 72-83).In the last decade, the field of single cell mechanics has emerged with the development of high resolution experimental and computational methods, providing significant amount of information about individual cells instead of the averaged characteristics provided by classical assays from large populations of cells. These single cell mechanical properties correlate closely with the intracellular organelle arrangement and organization, which are determined by load bearing cytoskeleton network comprised of biommolecules. This thesis will assess the feasibility of a high throughput single cell force spectroscopy using an atomic force microscopy (AFM)-based platform. A conventional AFM set-up employs a single cantilever probe for force measurement by using laser to detect the deflection of the cantilever structure, and usually can only handle one cell at a time. To improve the throughput of the device, a modified scheme to make use of cantilever based array is proposed and studied in this project. In addition, to complement the use of AFM array, a novel cell chip design is also presented for the fine positioning of cells in coordination with AFM cantilevers. The advantages and challenges of the system are analyzed too. To assess the feasibility of developing this technology, the commercialization possibility is discussed with intellectual property research, market analysis, cost modeling and supply chain positioning. Conclusion about this technology and its market prospect is drawn at the end of the thesis.by He Cheng.M.Eng

Applications of reference cycle building and K-shape clustering for anomaly detection in the semiconductor manufacturing process

Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 68-69).Early and accurate anomaly detection plays a key role in reducing costs and improving benefits, especially for complicated and time-consuming manufacturing such as semiconductor production. A case study of detecting anomalies from several monitored parameters during one plasma etching process is presented in this thesis. The thesis focuses on optimized ways to build reference cycles, or centroids of univariate parameters, a critical component to determine clustering accuracy and to facilitate process engineers' offline anomaly detections and diagnoses. Three time series centroid building methods are discussed and evaluated in the thesis, arithmetic, the Dynamic Time Warping Barycenter Averaging (DBA), and the soft-DTW-based centroid. As a result, DBA is chosen considering its comprehensive performance of accuracy and calculation time. Optimizations on DBA is further discussed to reduce calculation time. The window constraint, as well as the recalculation method of combining the previous centroid and new datasets, substantially reduce calculation time with slight accuracy loss. Based upon one centroid building method, shape extraction, a novel clustering method, k-shape, is implemented and applied to the plasma etching process. It is found that it achieves great accuracy with substantially shorter calculation time than one mainstream clustering method, k-means.by Han He.M. Eng. in Advanced Manufacturing and Desig

An optimization grouping method in a multi-line manufacturing system

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 59).A tailored product grouping method using binary integer linear program for optimization is developed for two production lines in a food packaging manufacturer. A mathematical model is created to assign products to the two dedicated production lines with an objective to minimize the total setup times. The optimization model is subject to capacity constraints on each line. With the demand of each product entered, the model is able to generate an optimal production grouping and sequence as well as the minimal total setup time required. Compared with CAS current fixed grouping method, this linear program grouping method reduces total setup time generally by 17% and prevents both production lines from overloading. Also, this grouping method allows the Make-to-Order food packaging manufacturer to respond to changes in demand volume and product mix by changing the product grouping accordingly.by He Xi.M.Eng

An Artificial Intelligence Approach for Tunnel Construction Performance

As massive tunneling projects become more and more popular, predicting the performance of Tunnel Boring Machine (TBM) has been a problem that arose recently. A TBM is a modern piece of machinery that is specially assembled to excavate a tunnel more efficiently and safely. However, the performance of TBM is very difficult to estimate due to the different geological formations and geotechnical factors. This research aims to predict the penetration rate (PR) of TBM utilizing statistical and artificial intelligence methods that are based on the rock mass and rock material properties: rock mass rating, rock quality designation, and rock strength. To achieve this goal, we used two neural network-based models: artificial neural network (ANN) and group method of data handling (GMDH), to forecast the TBM PR values. Then, we compared the performance of these two models using the well-known indices and a ranking system and selected the model with the highest degree of performance. As a result, an ANN model with one hidden layer and seven neurons showed the highest level of capability in predicting TBM PR. Correlation coefficient values of 0.947 and 0.921 for the training and testing phases, respectively, were obtained for the best model in this study. Our research can serve as a fundamental study for future geotechnical engineers or researchers who would like to predict TBM performance with similar rock mass and material properties to this study

How should indicators be found for scenario monitoring ?

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 76-78).Scenario planning is a widely used approach for developing long-term strategies. The typical scenario process involves developing scenarios, identifying strategies whose success is contingent on the scenario, and monitoring the environment regularly to know which scenario(s) may become more likely. Hence it becomes necessary to find a way to monitor the business environment in order to inform the process of making strategic decisions under uncertainty. This thesis proposes to use a set of nested indicators to monitor environment. The approach consists of a seven-step process to build composite indicators and link them with scenarios. Individual indicators are selected based on intuitive theoretical frameworks. Different weights are assigned to individual indicators using factor analysis. And then composite indicators are built by linear aggregation of individual indicators. The composite indicators are used to assess the changes in the driving forces over time. Such changes serve as the basis for judging whether the level of the driving forces is high or low. Those levels are then used to infer which scenario is likely to come to pass. This thesis used a set of four scenarios to illustrate the application of the approach. Those scenarios were built for a chemical company's supply chain in Asian/Pacific region in 2025. The result suggested that the environment of the sub-region in the monitoring year was more like a "Collaborative World" or a mix of "Collaborative World" and "Demanding World". And it is more possible that the environment was evolving into those two scenarios instead of the others.by Zheng He.M.Eng.in Logistic

Combination of Electroacupuncture and Grafted Mesenchymal Stem Cells Overexpressing TrkC Improves Remyelination and Function in Demyelinated Spinal Cord of Rats

10.1038/srep09133Scientific Reports

Germline SDHx variants modify breast and thyroid cancer risks in Cowden and Cowden-like syndrome via FAD/NAD-dependant destabilization of p53

Cowden syndrome (CS), a Mendelian autosomal-dominant disorder, predisposes to breast, thyroid and other cancers. Germline mutations in phosphatase and tensin homolog (PTEN) have been recently reported in 23% of a large series of classic CS. Here, we validated our small (n = 10) pilot study in a large patient series that germline variations in succinate dehydrogenase genes (SDHx) occur in 8% (49/608) of PTEN mutation-negative CS and CS-like (CSL) individuals (SDHvar+). None of these SDHx variants was found in 700 population controls (P < 0.0001). We then found that SDHx variants also occur in 6% (26/444) of PTEN mutation-positive (PTENmut+) CS/CSL individuals (PTENmut+/SDHvar+). Of 22 PTENmut+/SDHvar+ females, 17 had breast cancers compared with 34/105 PTENmut+ (P < 0.001) or 27/47 SDHvar+ patients (P = 0.06). Notably, individuals with SDHvar+ alone had the highest thyroid cancer prevalence (24/47) compared with PTENmut+ patients (27/105, P = 0.002) or PTENmut+/SDHvar+ carriers (6/22, P = 0.038). Patient-derived SDHvar+ lymphoblastoid cells had elevated cellular reactive oxygen species, highest in PTENmut+/SDHvar+ cells, correlating with apoptosis resistance. SDHvar+ cells showed stabilized and hyperactivated hypoxia inducible factor (HIF)1α signaling. Most interestingly, we also observed the loss of steady-state p53 in the majority of SDHvar+ cells. This loss of p53 was regulated by MDM2-independent NADH quinone oxidoreductase 1-mediated protein degradation, likely due to the imbalance of flavin adenine dinucleotide/nicotinamide adenine dinucleotide in SDHvar+ cells. Our data suggest the potential regulation of HIF1α, p53 and PTEN signaling by mitochondrial metabolism in CS/CSL tumorigenesis. Together, our findings suggest the importance of considering SDHx as candidate predisposing and modifier genes for CS/CSL-related malignancy risks, and a mechanism which suggests ways of therapeutic reversal or prevention

Red Wine Polyphenols for Cancer Prevention

Conventional cancer therapies, the second leading cause of death worldwide, result in serious side effects and, at best, merely extend the patient's lifespan by a few years. Searching for effective prevention is of high priority in both basic and clinical sciences. In recent decades natural products have been considered to be an important source of cancer chemopreventive agents. Red wine polyphenols, which consisted of various powerful antioxidants such as flavonoids and stilbenes, have been implicated in cancer prevention and that promote human health without recognizable side effects. Since resveratrol, a major component of red wine polyphenols, has been studied and reviewed extensively for its chemopreventive activity to interfere with the multi-stage carcinogenesis, this review focuses on recent progress in studies on cancer chemopreventive activities of red wine polyphenol extracts and fractions as well as other red wine polyphenols, like procyanidin B5 analogues and myricetin