Enhancing Breast Cancer Prediction through Deep Learning and Comparative Analysis of Gene Expression and DNA Methylation Data using Convolutional Neural Networks

Recent advances in the production of statistics have resulted in an exponential increase in the number of facts, ushering in a whole new era dominated by very large facts. Conventional machine-learning algorithms are unable to handle the most recent aspects of huge data. This is a fact.  In order to make an accurate prognosis of breast cancer, researchers employ and evaluate three distinct computer programmes called Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (DT). Within the context of huge statistics, we explore the question of how breast cancer may be predicted in this particular research. Gene expression and DNA methylation are both taken into consideration as part of the analysis (GE and DM, respectively). The purpose of the work that we are doing is to increase the capacity of the Deep Learning algorithms that are now being used for typing by applying each dataset individually and together. As a result of this decision, the platform of choice is MATLAB. In the process of breast cancer prediction, the Convolutional Neural Network (CNN) algorithm is used. Comparisons of GE, DM, and GE and DM are carried out with the help of this method. The results of the CNN algorithm are compared to those of the RF algorithm. According to findings of the experiments, the scaled system that was presented works better than the other classifiers. This is due to the fact that using the GE dataset; it acquired the best accuracy at the lowest cost

The Boston University Photonics Center annual report 2016-2017

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2016-2017 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has undoubtedly been the Photonics Center’s best year since I became Director 10 years ago. In the following pages, you will see highlights of the Center’s activities in the past year, including more than 100 notable scholarly publications in the leading journals in our field, and the attraction of more than 22 million dollars in new research grants/contracts. Last year I had the honor to lead an international search for the first recipient of the Moustakas Endowed Professorship in Optics and Photonics, in collaboration with ECE Department Chair Clem Karl. This professorship honors the Center’s most impactful scholar and one of the Center’s founding visionaries, Professor Theodore Moustakas. We are delighted to haveawarded this professorship to Professor Ji-Xin Cheng, who joined our faculty this year.The past year also marked the launch of Boston University’s Neurophotonics Center, which will be allied closely with the Photonics Center. Leading that Center will be a distinguished new faculty member, Professor David Boas. David and I are together leading a new Neurophotonics NSF Research Traineeship Program that will provide $3M to promote graduate traineeships in this emerging new field. We had a busy summer hosting NSF Sites for Research Experiences for Undergraduates, Research Experiences for Teachers, and the BU Student Satellite Program. As a community, we emphasized the theme of “Optics of Cancer Imaging” at our annual symposium, hosted by Darren Roblyer. We entered a five-year second phase of NSF funding in our Industry/University Collaborative Research Center on Biophotonic Sensors and Systems, which has become the centerpiece of our translational biophotonics program. That I/UCRC continues to focus on advancing the health care and medical device industries

Piezoelectric Materials for Medical Applications

This chapter describes the history and development strategy of piezoelectric materials for medical applications. It covers the piezoelectric properties of materials found inside the human body including blood vessels, skin, and bones as well as how the piezoelectricity innate in those materials aids in disease treatment. It also covers piezoelectric materials and their use in medical implants by explaining how piezoelectric materials can be used as sensors and can emulate natural materials. Finally, the possibility of using piezoelectric materials to design medical equipment and how current models can be improved by further research is explored. This review is intended to provide greater understanding of how important piezoelectricity is to the medical industry by describing the challenges and opportunities regarding its future development

Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors

Multianalyte Detection of Breast Cancer by Fabrication of Hybridmicroarrays on Polymer-Based Microanalytical Devices

Breast cancer is one of the most common and fatal cancer diseases that affect women worldwide. As is true with most other cancer diseases, early detection of breast cancer is very crucial for proper medical treatment because treatment of advanced breast cancer will be much more difficult and inconsistent. Screening and testing of breast cancer biomarkers, either genetic or proteomic, are among techniques used for diagnosis of breast cancers. Nevertheless, none of the biomarkers is by itself sensitive and selective enough for diagnosis of breast cancer, and thus, multi-analyte assays towards detection of multiple breast cancer biomarkers from different classes are desired for accurate diagnosis of this disease. Described is a methodology with which both genetic and protein biomarkers of breast cancers are detected simultaneously on the same platform. This methodology consists of a novel hybrid biosensor system in a universal Zipcode DNA array format on the platform of polymer-based microfluidic devices. Detection of the genetic mutated material and the protein targeting material is through hybridization events between the arrayed universal Zipcode DNA sequences and the corresponding complementary Zipcode DNA sequences that are incorporated into both biomarkers during materials preparation. Signal generation and detection are through near-IR, laser-induced fluorescence imaging method. The hybrid biosensor system combines the strengths of microfluidic devices—high throughput, low sample consumption, and high kinetics—with that of the universal DNA array format, which uncouples detection from hybridization event, thereby increasing the sensitivity of detection. Near-IR laser-induced fluorescence detection method adds further sensitivity to this system. In this work, surface properties of the microfluidic device substrate, PMMA have been manipulated in surface functionalities, surface topography, and surface wettabilities. Biomolecules including both antibodies and DNA have been successfully immobilized onto the UV-modified PMMA surfaces. The targeting biomarker materials were prepared using distinct protocols: PCR/LDR combined assays were adopted to prepare the breast cancer gene marker BRCA1 mutated material, while the protein antigen CEA targeting complex was achieved by a semi-synthetic method. Monitoring and characterization of surface manipulation, bio-functionalization, and targeting materials preparation were accomplished by unique analytical tools

Re-engineering cardio-oncology testing using biomimetic heart slice cultures.

28% of drug withdrawal from the market are due to unforeseen disruptions in cardiomyocyte contractility and electrophysiology. The most commonly used platforms for drug testing are in vivo animal models and in vitro cell culture models. While both have been of paramount importance for the discovery and detection of many cardiotoxicities and mechanisms of action, they lack the ability to model an intact human myocardium. This work aims to establish cardiac tissue slices, which are 300-micron thin tissue sections taken from the left ventricular myocardium, as an alternative platform for cardio-oncology studies, specifically cardiotoxicity testing. Additionally, this work aims to develop a coculture bioreactor system that can be used in reverse cardio-oncology related studies to investigate the potential crosstalk between cardiovascular disease and tumorigenesis

The Boston University Photonics Center annual report 2015-2016

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2015-2016 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has been a good year for the Photonics Center. In the following pages, you will see that this year the Center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted $18.9M in new research grants/contracts. Faculty and staff also expanded their efforts in education and training, and cooperated in supporting National Science Foundation sponsored Sites for Research Experiences for Undergraduates and for Research Experiences for Teachers. As a community, we emphasized the theme of “Frontiers in Plasmonics as Enabling Science in Photonics and Beyond” at our annual symposium, hosted by Bjoern Reinhard. We continued to support the National Photonics Initiative, and contributed as a cooperating site in the American Institute for Manufacturing Integrated Photonics (AIM Photonics) which began this year as a new photonics-themed node in the National Network of Manufacturing Institutes. Highlights of our research achievements for the year include an ambitious new DoD-sponsored grant for Development of Less Toxic Treatment Strategies for Metastatic and Drug Resistant Breast Cancer Using Noninvasive Optical Monitoring led by Professor Darren Roblyer, continued support of our NIH-sponsored, Center for Innovation in Point of Care Technologies for the Future of Cancer Care led by Professor Cathy Klapperich, and an exciting confluence of new grant awards in the area of Neurophotonics led by Professors Christopher Gabel, Timothy Gardner, Xue Han, Jerome Mertz, Siddharth Ramachandran, Jason Ritt, and John White. Neurophotonics is fast becoming a leading area of strength of the Photonics Center. The Industry/University Collaborative Research Center, which has become the centerpiece of our translational biophotonics program, continues to focus onadvancing the health care and medical device industries, and has entered its sixth year of operation with a strong record of achievement and with the support of an enthusiastic industrial membership base

Development of an electrochemical biosensor for the detection of miRNA-155 in Breast Cancer

Breast cancer is one of the most prevalent forms of cancer in women. Despite all recent advances in early diagnosis and therapy, mortality data is not decreasing. This is an outcome of the inexistence of validated serum biomarkers allowing an early prognosis, out coming from the limited understanding of the natural history of the disease. In this context, miRNAs have been attracting a special interest throughout the scientific community as promising biomarkers in the early diagnosis of cancer. In breast cancer, several miRNAs and their levels of expression are significantly different between normal tissue and tissue with neoplasia, as well as between different molecular subtypes of breast cancer, also associated with prognosis. Thus, this these presents a meta-analysis that allows identifying a reliable miRNA biomarker for the early detection of breast cancer. In this, miRNA-155 was identified as the best one and an electrochemical biosensor was developed for its detection in serum samples. The biosensor was assembled by following three button-up stages: (1) the complementary miRNA sequence thiol terminated (anti-miRNA-155) was immobilized on a commercial gold screen-printed electrode (Au-SPE), followed by (2) blocking non-specific binding with mercaptosuccinic acid and by (3) miRNA hybridization. The biosensor was able to detect miRNA concentrations lying in the 10-18 mol/L (aM) range, displaying a linear response from 10 aM to 1nM. The device showed a limit of detection of 5.7 aM in human serum samples and good selectivity against other biomolecules in serum, such as cancer antigen CA-15.3 and bovine serum albumin (BSA). Overall, this simple and sensitive strategy is a promising approach for the quantitative and/or simultaneous analysis of multiple miRNA in physiological fluids, aiming at further biomedical research devoted to biomarker monitoring and point-of-care diagnosis

Acoustofluidic manipulation of cells

This thesis aims to investigate the manipulation of cells, especially cancer cells, via acoustofluidic techniques at high ultrasound frequencies. This PhD project's motivation and ultimate goal are to separate circulating tumour cells (CTCs) from normal blood cells to achieve CTCs detection via acoustofluidic techniques. At the same time, the acoustofluidics-based manipulation of other types of cells and microparticles have also been investigated. The presence of rare cancer cells in cancer patient blood, called CTCs, has been increasingly researched as an essential biomarker for cancer diagnosis and cancer treatment monitoring. Separation and enrichment of CTCs from cancer patients’ blood samples via liquid biopsy methods have shown excellent compatibility compared with the conventional screening and invasive tissue biopsy methods. As a novel, bio�compatible and label-free technique, acoustofluidics has the potential to become an effective tool to sort CTCs from liquid samples or manipulate other types of cells via the cells physical properties: size, density, and compressibility. In this thesis, acoustofluidic platforms based on standing surface acoustic waves (SSAW) are demonstrated, including the Interdigital transducers (IDTs) design, cleanroom (CR) fabrication, and integration with microfluidics, electronics and mechanics systems. The simulation has been conducted via Governing equations (Continuity and Navier-Stokes equation) and Finite Element Method (FEM) model to understand the working principle and compare it with the microparticles manipulation experiment on the parallel and tilted-angle IDT SSAW devices. Moreover, a conventional tilted-angle (CTA) IDTs acoustofluidic device has been applied to wash the electroporated cells from the original medium, and a higher electroporation efficiency and cell viability are achieved. By optimising the IDTs patterning, a filled tilted-angle (FTA) IDTs design with less electrical input power but higher acoustic energy generated compared with CTA IDTs is demonstrated that achieves around 90% deflection efficiency of Hela cells with the input power of 4.5 W. In addition, to overcome the challenges of frangibility and overheating due to the conventional SSAW substrates, a novel Gallium Nitride (GaN) compound semiconductor film based acoustic tweezer is demonstrated. Cancer cell patterning via the GaN platform has been successfully achieved with excellent thermal stability with high input power. SSAW-based acoustofluidic cell manipulation in this thesis extends understanding of acoustofluidics techniques via the novel IDT design and SSAW generation substrate and will enable further development in high precision cell manipulation and biosensors application