El diagnóstico final de la mayoría de tipos de cáncer lo realiza un médico experto en anatomía patológica que examina muestras tisulares o celulares sospechosas extraídas del paciente. Actualmente, esta evaluación depende en gran medida de la experiencia del médico y se lleva a cabo de forma cualitativa mediante técnicas de imagen tradicionales como la microscopía óptica. Esta tarea tediosa está sujeta a altos grados de subjetividad y da lugar a niveles de discordancia inadecuados entre diferentes patólogos, especialmente en las primeras etapas de desarrollo del cáncer. La espectroscopía infrarroja por Transformada de Fourier (siglas FTIR en inglés) es una tecnología ampliamente utilizada en la industria que recientemente ha demostrado una capacidad creciente para mejorar el diagnóstico de diferentes tipos de cáncer. Esta técnica aprovecha las propiedades del infrarrojo medio para excitar los modos vibratorios de los enlaces químicos que forman las muestras biológicas. La principal señal generada consiste en un espectro de absorción que informa sobre la composición química de la muestra iluminada. Los microespectrómetros FTIR modernos, compuestos por complejos componentes ópticos y detectores matriciales de alta sensibilidad, permiten capturar en un laboratorio de investigación común imágenes hiperespectrales de alta calidad que aúnan información química y espacial. Las imágenes FTIR son estructuras de datos ricas en información que se pueden analizar individualmente o junto con otras modalidades de imagen para realizar diagnósticos patológicos objetivos. Por lo tanto, esta técnica de imagen emergente alberga un alto potencial para mejorar la detección y la graduación del riesgo del paciente en el cribado y vigilancia de cáncer. Esta tesis estudia e implementa diferentes metodologías y algoritmos de los campos interrelacionados de procesamiento de imagen, visión por ordenador, aprendizaje automático, reconocimiento de patrones, análisis multivariante y quimiometría para el procesamiento y análisis de imágenes hiperespectrales FTIR. Estas imágenes se capturaron con un moderno microscopio FTIR de laboratorio a partir de muestras de tejidos y células afectadas por cáncer colorrectal y de piel, las cuales se prepararon siguiendo protocolos alineados con la práctica clínica actual. Los conceptos más relevantes de la espectroscopía FTIR se investigan profundamente, ya que deben ser comprendidos y tenidos en cuenta para llevar a cabo una correcta interpretación y tratamiento de sus señales especiales. En particular, se revisan y analizan diferentes factores fisicoquímicos que influyen en las mediciones espectroscópicas en el caso particular de muestras biológicas y pueden afectar críticamente su análisis posterior. Todos estos conceptos y estudios preliminares entran en juego en dos aplicaciones principales. La primera aplicación aborda el problema del registro o alineación de imágenes hiperespectrales FTIR con imágenes en color adquiridas con microscopios tradicionales. El objetivo es fusionar la información espacial de distintas muestras de tejido medidas con esas dos modalidades de imagen y centrar la discriminación en las regiones seleccionadas por los patólogos, las cuales se consideran más relevantes para el diagnóstico de cáncer colorrectal. En la segunda aplicación, la espectroscopía FTIR se lleva a sus límites de detección para el estudio de las entidades biomédicas más pequeñas. El objetivo es evaluar las capacidades de las señales FTIR para discriminar de manera fiable diferentes tipos de células de piel que contienen fenotipos malignos. Los estudios desarrollados contribuyen a la mejora de métodos de decisión objetivos que ayuden al patólogo en el diagnóstico final del cáncer. Además, revelan las limitaciones de los protocolos actuales y los problemas intrínsecos de la tecnología FTIR moderna, que deberían abordarse para permit / The final diagnosis of most types of cancers is performed by an expert clinician in anatomical pathology who examines suspicious tissue or cell samples extracted from the patient. Currently, this assessment largely relies on the experience of the clinician and is accomplished in a qualitative manner by means of traditional imaging techniques, such as optical microscopy. This tedious task is subject to high degrees of subjectivity and gives rise to suboptimal levels of discordance between different pathologists, especially in early stages of cancer development. Fourier Transform infrared (FTIR) spectroscopy is a technology widely used in industry that has recently shown an increasing capability to improve the diagnosis of different types of cancer. This technique takes advantage of the ability of mid-infrared light to excite the vibrational modes of the chemical bonds that form the biological samples. The main generated signal consists of an absorption spectrum that informs of the chemical composition of the illuminated specimen. Modern FTIR microspectrometers, composed of complex optical components and high-sensitive array detectors, allow the acquisition of high-quality hyperspectral images with spatially-resolved chemical information in a common research laboratory. FTIR images are information-rich data structures that can be analysed alone or together with other imaging modalities to provide objective pathological diagnoses. Hence, this emerging imaging technique presents a high potential to improve the detection and risk stratification in cancer screening and surveillance. This thesis studies and implements different methodologies and algorithms from the related fields of image processing, computer vision, machine learning, pattern recognition, multivariate analysis and chemometrics for the processing and analysis of FTIR hyperspectral images. Those images were acquired with a modern benchtop FTIR microspectrometer from tissue and cell samples affected by colorectal and skin cancer, which were prepared by following protocols close to the current clinical practise. The most relevant concepts of FTIR spectroscopy are thoroughly investigated, which ought to be understood and considered to perform a correct interpretation and treatment of its special signals. In particular, different physicochemical factors are reviewed and analysed, which influence the spectroscopic measurements for the particular case of biological samples and can critically affect their later analysis. All these knowledge and preliminary studies come into play in two main applications. The first application tackles the problem of registration or alignment of FTIR hyperspectral images with colour images acquired with traditional microscopes. The aim is to fuse the spatial information of distinct tissue samples measured by those two imaging modalities and focus the discrimination on regions selected by the pathologists, which are meant to be the most relevant areas for the diagnosis of colorectal cancer. In the second application, FTIR spectroscopy is pushed to their limits of detection for the study of the smallest biomedical entities. The aim is to assess the capabilities of FTIR signals to reliably discriminate different types of skin cells containing malignant phenotypes. The developed studies contribute to the improvement of objective decision methods to support the pathologist in the final diagnosis of cancer. In addition, they reveal the limitations of current protocols and intrinsic problems of modern FTIR technology, which should be tackled in order to enable its transference to anatomical pathology laboratories in the future. / El diagnòstic final de la majoria de tipus de càncer ho realitza un metge expert en anatomia patològica que examina mostres tissulars o cel¿lulars sospitoses extretes del pacient. Actualment, aquesta avaluació depèn en gran part de l'experiència del metge i es porta a terme de forma qualitativa mitjançant tècniques d'imatge tradicionals com la microscòpia òptica. Aquesta tasca tediosa està subjecta a alts graus de subjectivitat i dóna lloc a nivells de discordança inadequats entre diferents patòlegs, especialment en les primeres etapes de desenvolupament del càncer. L'espectroscòpia infraroja per Transformada de Fourier (sigles FTIR en anglès) és una tecnologia àmpliament utilitzada en la indústria que recentment ha demostrat una capacitat creixent per millorar el diagnòstic de diferents tipus de càncer. Aquesta tècnica aprofita les propietats de l'infraroig mitjà per excitar els modes vibratoris dels enllaços químics que formen les mostres biològiques. El principal senyal generat consisteix en un espectre d'absorció que informa sobre la composició química de la mostra il¿luminada. Els microespectrómetres FTIR moderns, compostos per complexos components òptics i detectors matricials d'alta sensibilitat, permeten capturar en un laboratori d'investigació comú imatges hiperespectrals d'alta qualitat que uneixen informació química i espacial. Les imatges FTIR són estructures de dades riques en informació que es poden analitzar individualment o juntament amb altres modalitats d'imatge per a realitzar diagnòstics patològics objectius. Per tant, aquesta tècnica d'imatge emergent té un alt potencial per a millorar la detecció i la graduació del risc del pacient en el cribratge i vigilància de càncer. Aquesta tesi estudia i implementa diferents metodologies i algoritmes dels camps interrelacionats de processament d'imatge, visió per ordinador, aprenentatge automàtic, reconeixement de patrons, anàlisi multivariant i quimiometria per al processament i anàlisi d'imatges hiperespectrals FTIR. Aquestes imatges es van capturar amb un modern microscopi FTIR de laboratori a partir de mostres de teixits i cèl¿lules afectades per càncer colorectal i de pell, les quals es van preparar seguint protocols alineats amb la pràctica clínica actual. Els conceptes més rellevants de l'espectroscòpia FTIR s'investiguen profundament, ja que han de ser compresos i tinguts en compte per dur a terme una correcta interpretació i tractament dels seus senyals especials. En particular, es revisen i analitzen diferents factors fisicoquímics que influeixen en els mesuraments espectroscòpiques en el cas particular de mostres biològiques i poden afectar críticament la seua anàlisi posterior. Tots aquests conceptes i estudis preliminars entren en joc en dues aplicacions principals. La primera aplicació aborda el problema del registre o alineació d'imatges hiperespectrals FTIR amb imatges en color adquirides amb microscopis tradicionals. L'objectiu és fusionar la informació espacial de diferents mostres de teixit mesurades amb aquestes dues modalitats d'imatge i centrar la discriminació en les regions seleccionades pels patòlegs, les quals es consideren més rellevants per al diagnòstic de càncer colorectal. En la segona aplicació, l'espectroscòpia FTIR es porta als seus límits de detecció per a l'estudi de les entitats biomèdiques més xicotetes. L'objectiu és avaluar les capacitats dels senyals FTIR per discriminar de manera fiable diferents tipus de cèl¿lules de pell que contenen fenotips malignes. Els estudis desenvolupats contribueixen a la millora de mètodes de decisió objectius que ajuden el patòleg en el diagnòstic final del càncer. A més, revelen les limitacions dels protocols actuals i els problemes intrínsecs de la tecnologia FTIR moderna, que haurien d'abordar per permetre la seva transferència als laboratoris d'anatomia patològica en el futur. / Peñaranda Gómez, FJ. (2018). Application of artificial vision algorithms to images of microscopy and spectroscopy for the improvement of cancer diagnosis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/99748 / TESIS

abstract: Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated through the double invagination of the lipid bilayer membrane of cell. Therefore, they mirror the cell membrane proteins and contain proteins, RNAs, and DNAs that can represent the phenotypic state of their cell of origin, hence considered promising biomarker candidates. Importantly, in most pathological conditions, such as cancer and infection, diseased cells secrete more EVs and the disease associated exosomes have shown great potential to serve as biomarkers for early diagnosis, disease staging, and treatment monitoring. However, using EVs as diagnostic or prognostic tools in the clinic is hindered by the lack of a rapid, sensitive, purification-free technique for their isolation and characterization. Developing standardized assays that can translate the emerging academic EV biomarker discoveries to clinically relevant procedures is a bottleneck that have slowed down advancements in medical research. Integrating widely known immunoassays with plasmonic sensors has shown the promise to detect minute amounts of antigen present in biological sample, based on changes of ambient optical refractive index, and achieve ultra-sensitivity. Plasmonic sensors take advantage of the enhanced interaction of electromagnetic radiations with electron clouds of plasmonic materials at the dielectric-metal interface in tunable wavelengths. / Dissertation/Thesis / Doctoral Dissertation Biomedical Engineering 2020

京都大学 / 0048 / 新制・論文博士 / 博士(社会健康医学) / 乙第13358号 / 論社医博第15号 / 新制||社医||11(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 川上 浩司, 教授 小川 修, 教授 松村 由美 / 学位規則第4条第2項該当 / Doctor of Public Health / Kyoto University / DFAM

Thesis (MSc (Radiography))--Cape Peninsula University of Technology, 2019 / INTRODUCTION: The Breast Imaging Reporting and Data System (BI-RADS) was developed by the American College of Radiology (ACR). The BI-RADS is an internationally accepted method of assessing and reporting on mammograms and breast ultrasound images. The BI-RADS consists of a lexicon (descriptors) and assessment categories. The ACR aimed to standardise mammography reporting and placing the findings in the appropriate assessment category. The aim of this study was to establish the accuracy of the BI-RADS assessment categories for mammography and breast ultrasound images in women diagnosed with breast cancer. METHOD: Data were retrieved from 77 patients who were diagnosed with breast cancer from 1 January 2013 to 31 December 2014. Seven did not meet the inclusion criteria and were excluded. The study sample size was 70 (n=70) patients. All mammography reports included a BI-RADS assessment category of all patients diagnosed with breast cancer within the study period. These reports were analysed and compared with histopathology results. The BI-RADS assessment category and descriptors were collected from the mammogram reports; the histopathology report indicated the type of breast cancer. All reports were obtained from the patients' folders at the research site. In addition, questionnaires were distributed among radiologists to assess whether their experience and training had an influence on the accuracy of reporting in the BI-RADS assessment categories. Descriptive and inferential statistical analysis was used for data analysis. RESULTS: The most common malignancy diagnosed was invasive ductal carcinoma with a total of 70% (n=54), followed by ductal carcinoma in situ with 10.4% (n=8) and invasive lobular carcinoma with 9.1% (n=7). The histology results confirmed breast cancer for all BI-RADS 4 and 5 assessment categories. The mammogram was able to detect 93.5% of abnormalities and breast ultrasound 84.4% of abnormalities in this study sample. Breast ultrasound was used as an adjunct to mammography and hence an overall combined diagnostic rate was 100%. Mammography descriptors: The more common malignancy findings were spiculated mass margin, 35.1% (n=27). Ultrasound descriptors: The more common malignancy findings were hypoechoic echo pattern, 55.8% (n=43). There was no significant association (p=0.152) between the radiologists' years of experience and BI-RADS 3, 4 and 5 assessment category reporting. Of the 15 responses, 67% agreed that the BI-RADS standardises breast imaging reporting and reduces confusion, 33% agreed that the BI-RADS allows better communication between radiologists and referring physicians, and 40% agreed that the BI-RADS clarifies further management for patients by helping to stratify risk management. CONCLUSION: The outcome of this study indicated that the use of BI-RADS assessment categories is useful for predicting the likelihood of malignancy when used correctly. The outcome of BI-RADS 4 and BI-RADS 5 had a positive predictive value of 100%, which corresponded well with histology results. The descriptor findings suggested that spiculated mass margins, irregular-shaped masses, hypoechoic echo pattern and posterior shadowing were high predictors of malignancy and warranted a placement in the BI-RADS 5 assessment category.

Solid tumors can hijack many of the same programs used in neurogenesis to enhance tumor growth and metastasis, thereby generating a plethora of neurogenesis-related molecules including semaphorins Among them, we have identified Semaphorin7A (SEMA7A) in breast cancer We first used to the DA-3 mammary tumor model to determine the effect of tumor-derived SEMA7A on immune cells We found that tumor-derived SEMA7A can modulate the production of proangiogenic chemokines CXCL2/MIP-2 and CXCL 1, and prometastatic MMP-9 in macrophages We next aimed to determine the expression and function of SEMA7A in mammary tumor cells We found that SEMA7A is highly expressed in both metastatic human and murine breast cancer cells We show that both TGF-β and hypoxia elicits the production of SEMA 7 A in mammary cells SEMA7 A shRNA silencing in 4T1 cells resulted in decreased mesenchymal markers MMP-3, MMP-13, Vimentin and TGF-β) SEMA7A silenced cells show increased stiffness with reduced migratory and proliferative potential In vivo, SEMA7A silenced 4T1 tumor bearing mice showed decreased tumor growth and metastasis Genetic ablation of host-derived SEMA7A synergized to further decrease the growth and metastasis of 4T1 cells Our findings suggest novel functional roles for SEMA7A in breast cancer and that SEMA7A could be a novel therapeutic target to limit tumor growth and metastasis / Includes bibliography / Dissertation (PhD)--Florida Atlantic University, 2016 / FAU Electronic Theses and Dissertations Collection

No description available.

Bakgrund: Varje år drabbas cirka 9000 personer i Sverige av bröstcancer. Chansen för överlevnad är stor och idag finns det bra behandlingsalternativ. Vid besked av cancer och under behandlingsperioden kan man vara i behov av stöd, både från familj och sjukvården. Det kan vara svårt att veta vilket stöd man vill ha och hur man får det. Syfte: Syftet med denna litteraturstudie är att undersöka vilket typ av stöd som kvinnor behöver i samband med sin bröstcancer. Metod: Syftet har besvarats med en allmän litteraturöversikt med beskrivande design. De artiklar som inkluderats är av kvalitativ metod. Artiklarna har kvalitetsgranskats och de studier som anses vara av medelhög- och hög kvalitet inkluderades. Resultat: I resultatet uttryckte patienter både goda egenskaper och brister i stöd som de fick. Bland annat sågs patienternas delaktighet, sjuksköterskornas uppmuntran och familjens stöd som en positiv faktor. De brister som uppmärksammades var bland annat för lite information om behandlingen och bristande tillgänglighet från sjukvårdens sida.  Slutsats: Resultaten som framkom var att stöd är olika mottaget och olika uppskattat av kvinnorna. Informationsstöd ansågs vara mycket viktigt men brister av detta stöd var tydliga. Familjestödet var helt avgörande för att få en trygghetskänsla. Nätverksstöd var uppskattat för tillgängligheten men vissa kvinnor upplevde att detta stöd inte passade dem. Sjukvårdens stöd gav kvinnorna delaktighet men detta stöd hade mycket brister och stor förbättringspotential enligt kvinnorna. / Background: Every year, approximately 9,000 people in Sweden is diagnosed with breast cancer. The chance of survival is great and there are good treatment options. When the cancer diagnosis is given and during the treatment period, you may be in need of support, both from family and healthcare. It can be difficult to know what support you want and how to get it. Aim: The aim of this literature study is to investigate the type of support women need in connection with their breast cancer. Method: The purpose has been answered with a general literature review with descriptive design. The articles included are of a qualitative approach. The articles has undergone quality analysis and the studies that are considered to be of medium and high quality were included. Results: In the result, patients expressed both good qualities and deficiency in the support they received. For instance, patients participation, nurses encouragement and family support were seen as a positive factor. The shortcomings that were highlighted included too little information about the treatment and lack of accessibility on the part of the health service. Conclusion: The results that emerged were that support is differently received and differently appreciated by women. Information support was considered very important but shortcomings of this support were clear. Family support was absolutely crucial to get a sense of security. Network support was appreciated for its availability, but some women felt that this support did not suit them. The health care support gave the women participation, but this support had many shortcomings and great potential for improvement according to the women.

Nasopharyngeal Carcinoma (NPC) as a typical malignancy that occurs in high-incidence areas, e.g. southern China region, including Hong Kong, and it has aroused wide interests for local researchers to study. The Epstein-Barr virus (EBV) was reported as a vital herpes virus for the growth of NPC. Two significant proteins in EBV, namely Epstein-Barr Nuclear Antigen 1 (EBNA1) and latent infection membrane protein 1 (LMP1) are crucial for virus maintenance and EBV-infected cell development, and essential for cell proliferation and differentiation of EBV latent life cycle, respectively. Thus, inhibition of EBNA1 and LMP1 can be regarded as effective and potent therapy on EBV-associated cancers. In this thesis, the conjugation of core-shell structured upconversion nanoparticles (UCNPs) with distinct EBV-specific peptides including EBNA1 and LMP1 targeting peptides to achieve both impressive inhibition on EBV-positive cancers in vitro/in vivo and visualization on EBV-positive cells with responsive upconversion emission signals were investigated. Taking advantage of lanthanide-based UCNPs, their unique photophysical properties offer deep tissue penetration depth, negligible photobleaching and photocytotoxicity, and therefore provides a solid foundation for convincible theranostic studies. Furthermore, desired inhibitory performance was achieved, it was shown that ~50 mg/mL of nanoprobes can inhibit half of EBV-infected cell viability and only 0.25 mg/tumor of nanoprobes dosage via intravenous injection can prohibit 64.7% of growth inhibition of an EBV-positive tumor

Over the last two decades, the concept of precision medicine has remained more of a promise than a reality. While there has been significant advancement in the field in terms of scientific discovery, precision medicine has yet to truly permeate standard clinical practice. There are a few individual examples, such as the treatment of breast cancer, in which the precision medicine approach has been ubiquitously adopted, but for most applications it remains exploratory. This barrier can arguably be attributed to the lack of accessible technology. That is, highly laborious, costly, and time-consuming methods that inhibit the integration of precision medicine techniques into the current clinical paradigm. In this dissertation, we aim to develop new technology, for both therapeutics and diagnostics, that would enable access to precision medicine by considering factors such as scalability, manufacturability, cost, turnaround time and integration. In Aim 1, we developed a direct tissue engineering approach to increase endogenous brown fat for the treatment of obesity. This method capitalized on the use of brown adipose tissue (BAT), a highly metabolic tissue that expends energy via uncoupled respiration and has been shown to correlate with a lean phenotype and decreased risk of metabolic disease. Existing methods that seek to increase BAT mass include either the use of pharmacologic agents, which often exhibit detrimental off-target effects, or cold exposure, which is obviously unsustainable in practice. Cell therapies that involve the isolation of adipocyte progenitor cells have also been explored but are not easily scaled and are difficult to implement. Here, we developed a method to convert a patient’s own white adipose tissue (WAT) en masse to thermogenic BAT in a single ex vivo step, followed by reimplantation back into the patient. We demonstrated that this method, called exBAT, was able to convert full fragments of WAT to a BAT-like tissue, which sustained its phenotype up to 8-weeks after reimplantation in a mouse model. Further, allogeneic transplantation of exBAT in a diet-induced obesity mouse model exhibited a trend toward weight loss which should further be explored with additional dosing experiments. This method is highly scalable, patient-specific, and easily implemented with current clinical practice and has the potential to provide a precise method to combat the growing challenge of obesity. In Aim 2, we shifted our focus to the development of a point-of-care (POC) diagnostic device for precision oncology. Here, we developed a device capable of performing a POC liquid biopsy for the detection of resistance mutations in non-small cell lung cancer (NSCLC). While liquid biopsies, which seek to identify tumor fragments in a patient’s blood, hold significant promise and advantages over traditional tissue biopsies, there are still several challenges including long turnaround time, high cost, and challenges with sensitivity. We sought to build a fully integrated device that can reduce the turnaround time for liquid biopsies from 2 weeks to one hour, enabling much higher throughput for important genotyping tests in NSCLC patients, and thereby enabling faster access to treatment. We demonstrated the ability to isolate plasma from undiluted whole blood at the POC, purify and concentrate circulating nucleic acids, and perform detection of low variant allelic frequency (VAF) mutations down to 1% in a microfluidic chip using a low-cost thermocycler. The device was initially designed to identify the presence or absence of T790M mutations, an important gatekeeper mutation with a clear clinical use case that confers sensitivity toward specific tyrosine kinase inhibitors (TKIs) in advanced NSCLC patients. However, the device can be easily extrapolated toward any type of molecular profiling and has the potential to significantly increase access to precision oncology diagnostics and therapeutics. Finally, in Aim 3, we sought to develop a molecular diagnostic for detection of SARS-CoV-2 that would provide a qualitative result in less than 15 minutes at the POC. As the COVID-19 pandemic has continued to spread rapidly throughout the world, there is still an unmet need for high-throughput, ultrafast diagnostics that are sensitive, specific and accessible to all. To meet this challenge, we developed a molecular diagnostic that performs RT-PCR off of crude lysate from patient specimens in 15 minutes or less. To achieve this, we built upon previously demonstrated photothermal amplification techniques and extended its capabilities to perform ultrafast RT-PCR using a low-power infrared LED. We also sought to integrate sample preparation methods for both nasopharyngeal (NP) swabs and saliva samples to eliminate the need for labor-intensive RNA extraction and enable full automation for POC testing. Testing of our device using purified SARS-CoV-2 RNA showed high sensitivity and a limit of detection down to 500 copies/mL. We also demonstrated preliminary results showing the ability to detect SARS-CoV-2 RNA in unpurified saliva and further testing of clinical specimens in the POC device is ongoing. With a significantly faster and low-cost test that maintains gold-standard sensitivity and specificity, this device has the potential to drastically increase testing throughput and help contain the spread of COVID-19. Underlying this work is the development of accessible technology for precision medicine. Aim 1 focuses on a simple, patient-specific tissue engineering approach to treating obesity, which is significantly more scalable than other cell and tissue engineering methods. Aim 2 demonstrates the ability to perform a highly sensitive liquid biopsy at the POC down to 1% VAF. Aim 3 demonstrates a new POC diagnostic for SARS-CoV-2 that provides a result in less than 15 minutes. Both Aims 2 and 3 focus on the development of POC diagnostics and were designed to be user-friendly, scalable, and easily integrated into current clinical paradigms. In Appendix I, we expand the discussion of POC diagnostics and present a design framework based on cost and budget constraints that was used for the development of these POC devices. Overall, the sum of this work illustrates examples of thoughtful engineering for the development of impactful new technologies for precision therapeutics and diagnostics.

Electronic biosensors utilizing micron-scale interdigitate electrodes (IDEs) in an SD card format have been developed with the objective of fast, sensitive detection of ovarian cancer biomarkers CA-125, CEA, and He4. The signal generated by the biosensors is a result of electrochemical impedance spectroscopy (EIS), a technique which probes changes that occur in the biosensor's electrical properties when the biosensor has detected one of the target biomarkers. A label-free biosensor has been developed to detect CA-125 in spiked buffer at concentrations between 10 and 80units/mL. A similar label-free biosensor was developed to detect CEA at concentrations between 10ug/mL and 10mg/mL. A biosensor employing a protein-enzyme conjugated label was developed to detect He4 at concentrations ranging from 1.56 to 100ng/mL in spiked buffer. All concentration ranges of CA-125, CEA, and He4 detected by the biosensors include the serum concentration currently used for clinical diagnosis of ovarian cancer. Efforts to improve the signals generated by the biosensors included altering the dimensions and composition of the IDEs used in the initial biosensors through software-created models. Modeled alterations included the size of the electrodes, the shape of the electrodes, and the incorporation of nanomaterials into the IDEs. An ideal geometry for the IDEs was developed through the models and IDEs with those dimensions were fabricated and tested against the IDEs used in the biosensors initially with the model-developed geometry improving the signal generated by the biosensor. Another attempt to improve the biosensor's signal was to generate a single strand of DNA (ssDNA) that would bind to CA-125, called an aptamer, that could be easily incorporated into the sensing layer on the IDEs. Through a multistep selection process nine different aptamers that exhibited binding to CA-125 were identified.