We then apply the motor position values as inputs and the distanc

We then apply the motor position values as inputs and the distance values as outputs to a regression method and a function model is generated for each sensor. After a function model for each sensor is generated sellectchem by the regression method, distance values corresponding to specific motor position values can be estimated. Note that the distance-measuring sensors used for our experiment are ultrasonic sensors, which are typical
Ovarian cancer is the fifth leading cause of cancer death among women in United States and it has a 1.4% (1 in 71) lifetime risk [1]. Diagnosis of ovarian cancer in the early stages currently accounts for only 30% of all cases, and in most late stages the cancer is lethal. The lack of overt symptoms and the absence of a reliable screening test results in over 70% diagnoses occurring the disease has spread beyond the ovary, so the prognosis is poor [1].
The 5 year survival rate after diagnosis for late stage disease is less than 40%. Currently, pelvic examination, ultrasound and blood levels of serum biomarker CA125 are the standard screening methods for ovarian cancer [2�C4]. However, each of these ovarian cancer detection methods has limitations. Pelvic examination is known to be obstructed by the intraperitoneal location of the ovaries and is typically capable of late-stage disease detection only. Similarly, ultrasonic examination does not possess the capability of distinguishing between benign and malignant cases and is subject to variation in interpretations among sonographers. CA125 is the current standard biomarker for ovarian cancer diagnosis and monitoring [4].
It is present in the blood serum of ovarian cancer patients. However, it has been shown that CA125 levels can also be elevated due to other disorders, including inflammation, benign gynecological disease, or hepatic disease, leading to false positive results [5,6]. There are other biomarkers that have been associated with ovarian cancer such as eosinophil-derived neurotoxin [7], Mesothelin [8], VEGF [9], and HE4 [10]. There also exists a few biochips relying on fluorescence or chemiluminescence for ovarian cancer monitoring based on DNA sequences (testing for ovarian cancer-related mutations) [11,12] and protein biomarkers [13,14]. However, these biosensors use complex reagents such as DNA extraction kits and expensive laboratory equipment including fluorescence microscopes or plate readers, thus, are not suitable for point-of-care testing [15].
Recently, an enzyme-linked immunosorbent assay (ELISA) test based on a cell-phone-coupled optical sensor has been presented for point-of-care quantification of urinary HE4 levels [15]. However, the chemicals and substances used during ELISA tests are still Brefeldin_A fairly expensive, and special attention should be given for storage. The absence of reliable screening methods to detect early ovarian Sorafenib cancer contributes to poor prognosis.

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