Patent Publication Number: US-2023140879-A1

Title: Electrochemical measuring of reactive oxygen species (ros) levels in peripheral blood to detect ratio of low-density neutrophils (ldns) to high-density neutrophils (hdns), suitable to alarm presence of cancer in suspicious cases

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation-in-part of International Patent Application PCT/IB2022/051283, filed on Feb. 14, 2022, and entitled “ELECTROCHEMICAL MEASURING OF REACTIVE OXYGEN SPECIES (ROS) LEVELS IN PERIPHERAL BLOOD TO DETECT RATIO OF LOW-DENSITY NEUTROPHILS (LDNS) TO HIGH-DENSITY NEUTROPHILS (HDNS), SUITABLE TO ALARM PRESENCE OF CANCER IN SUSPICIOUS CASES”, which takes priority from U.S. Provisional Patent Application Ser. No. 63/149,282, filed on Feb. 14, 2021, and entitled “ELECTROCHEMICAL MEASURING OF REACTIVE OXYGEN SPECIES LEVELS RELEASED BY LOW-DENSITY NEUTROPHILS IN THE BLOOD, AN ALARM OF CANCER IN SUSPICIOUS CASES”, which are both incorporated herein by reference in their entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure generally relates to cancer diagnosis, and particularly, to a system and method for real-time cancer diagnosis by determining a ratio of low-density neutrophils (LDNs) to high-density neutrophils (HDNs) via measuring reactive oxygen species (ROS) levels in unprocessed blood samples. 
     BACKGROUND 
     Neutrophils are the most abundant (50% to 70%) type of white blood cells circulating leukocytes which are derived from hematopoietic stem cells (HSCs) in bone marrow. Neutrophils release enzymes to remodel an extracellular matrix of a tissues through which neutrophils migrate to reach a site of a wound or an infection. 
     Number of LDN neutrophils in blood and tumor tissues of cancer patients with solid tumors shows an association with disease progression and patient outcome. There are several cell markers for identification of immature neutrophils in human. These markers need further validation to ensure its accuracy. Hence, since neutrophils can show plasticity in response to their environment, certain markers are likely to only be proper in particular models and require efficient validation of them. So, the challenges associated with identifying and isolating populations of neutrophil maturity have limited their study and the current knowledge of their functional properties. 
     Hence, there is a need for a label-free method and system to determine an accurate correlation between abundancy of neutrophils, specially, LNDs in blood sample of patients with a cancer status of the patients. There is also a need for a highly precise and fast method and system for detecting a cancer status of a suspected patient to be cancerous via measuring a level of LDNs in peripheral blood without any need to process a blood sample and/or use a cell marker. 
     SUMMARY 
     This summary is intended to provide an overview of the subject matter of this patent, and is not intended to identify essential elements or key elements of the subject matter, nor is it intended to be used to determine the scope of the claimed embodiments. The proper scope of this patent may be ascertained from the claims set forth below in view of the detailed description below and the drawings. 
     In one general aspect, the present disclosure is directed to a method for real-time detecting cancer. The method may include putting an unprocessed blood sample in contact with sensing parts of a set of a working electrode, a counter electrode, and a reference electrode of a sensor, where the unprocessed blood sample may be drawn from a suspected person to have cancer. The method may further include applying a set of voltages in a sweeping range from −0.8 V to +0.8 V between the reference electrode and the working electrode, measuring a produced set of electrical currents between the counter electrode and the working electrode versus the applied set of voltages utilizing one or more processors, measuring a level of ratio of low-density neutrophils (LDNs) to high-density neutrophils (HDNs) in the unprocessed blood sample utilizing one or more processors, and detecting a cancer status of the suspected person based on the measured level of ratio of LDNs to HDNs in the unprocessed blood sample utilizing one or more processors. 
     In an exemplary embodiment, measuring the level of ratio of LDNs to HDNs in the unprocessed blood sample may include measuring a level of reactive oxygen species (ROS) in the unprocessed blood sample by measuring a maximum electrical current of the measured set of electrical currents and determining the level of ratio of LDNs to HDNs in the unprocessed blood sample based on the measured maximum electrical current of the measured set of electrical currents. In an exemplary embodiment, determining the level of ratio of LDNs to HDNs in the unprocessed blood sample based on the measured maximum electrical current of the measured set of electrical currents may include detecting the level of ratio of LDNs to HDNs in the unprocessed blood sample is more than 1 if the measured maximum electrical current of the measured set of electrical currents is less than a first threshold electrical current value or detecting the level of ratio of LDNs to HDNs in the unprocessed blood sample is less than 1 if the measured maximum electrical current of the measured set of electrical currents is more than a second threshold electrical current value. In an exemplary embodiment, detecting the cancer status of the suspected person may include one of detecting a cancer disease in the suspected person&#39;s body if the level of ratio of LDNs to HDNs in the unprocessed blood sample is more than one or detecting no cancer disease in the suspected person&#39;s body if the level of ratio of LDNs to HDNs in the unprocessed blood sample is less than one. 
     In an exemplary embodiment, the method may further include generating the first threshold electrical current value and the second threshold electrical current value. In an exemplary embodiment, generating the first threshold electrical current value and the second threshold electrical current value may include generating a first dataset of a plurality of unprocessed blood samples associated with a plurality of cancer patients, generating a second dataset of a plurality of unprocessed blood samples associated with a plurality of healthy persons, and determining the first threshold electrical current value and the second threshold electrical current value using the first dataset and the second dataset. In an exemplary embodiment, generating the first dataset of the plurality of unprocessed blood samples associated with the plurality of cancer patients may include measuring a first set of electrical current peaks of the unprocessed blood samples associated with the plurality of cancer patients, measuring a first set of ratio of LDNs to HDNs in the unprocessed blood samples associated with the plurality of cancer patients utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the first set of ratio of LDNs to HDNs to the respective measured electrical current peak of the first set of electrical current peaks. In an exemplary embodiment, generating the second dataset of the plurality of unprocessed blood samples associated with the plurality of healthy persons may include measuring a second set of electrical current peaks of the unprocessed blood samples associated with the plurality of healthy persons, measuring a first set of ratio of LDNs to HDNs in the unprocessed blood samples associated with the plurality of healthy persons utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the second set of ratio of LDNs to HDNs to the respective measured electrical current peak of the second set of electrical current peaks. In an exemplary embodiment, determining the first threshold electrical current value and the second threshold electrical current value may include determining the first threshold electrical current value equal to a maximum electrical current peak among the first set of electrical current peaks and determining the second threshold electrical current value equal to a minimum electrical current peak among the second set of electrical current peaks. 
     In an exemplary embodiment, the first threshold electrical current value is 300 μA for an adult person. In an exemplary embodiment, the first threshold electrical current value is 100 μA for a child. In an exemplary embodiment, the second threshold electrical current value is 450 μA for an adult person. In an exemplary embodiment, the second threshold electrical current value is 300 μA for a child. 
     In an exemplary embodiment, the method may be conducted in less than 30 seconds. In an exemplary embodiment, the method may further include acquiring the unprocessed blood sample from the suspected person to have cancer. 
     In an exemplary embodiment, putting the unprocessed blood sample in contact with the sensing parts of the set of the working electrode, the counter electrode, and the reference electrode of the sensor may include putting the unprocessed blood sample in contact with three respective arrays of multi-walled carbon nanotubes (VAMWCNTs) grown on the sensing parts of the set of the working electrode, the counter electrode, and the reference electrode by dropping the unprocessed blood sample on surface of the sensor. 
     In an exemplary embodiment, applying the set of voltages in the sweeping range from −0.8 V to +0.8 V between the reference electrode and the working electrode may include connecting respective proximal ends of the set of the working electrode, the counter electrode, and the reference electrode of the sensor to an electrical stimulator-analyzer device and applying the set of voltages in a sweeping range from −0.8 V to +0.8 V to the sensor using the electrical stimulator-analyzer device. In an exemplary embodiment, measuring the produced set of electrical currents between the counter electrode and the working electrode versus the applied set of voltages may be done utilizing the electrical stimulator-analyzer device. 
     In another general aspect, the present disclosure is directed to a system for real-time detecting cancer by analyzing unprocessed blood. The system may include a sensor configured to place an unprocessed blood sample drawn from a suspected person to have cancer thereon, an electrical stimulator-analyzer device electrically connected to the sensor, and a processing unit electrically connected to the electrical stimulator-analyzer device. 
     In an exemplary embodiment, the sensor may include a substrate and three electrodes formed on the substrate. In an exemplary embodiment, the three electrodes may include a working electrode, a counter electrode, and a reference electrode. In an exemplary embodiment, each respective electrode may include an electrically conductive layer deposited on the substrate and an array of multi-walled carbon nanotubes (VAMWCNTs). In an exemplary embodiment, the electrically conductive layer may include a proximal end and a circular distal end. In an exemplary embodiment, the array of VAMWCNTs may be grown on the circular distal end. In an exemplary embodiment, the array of VAMWCNTs may be configured to be put in contact with the unprocessed blood sample drawn from the suspected person to have cancer. 
     In an exemplary embodiment, the electrical stimulator-analyzer device may be electrically connected to the sensor at the respective proximal end of each respective electrode of the three electrodes. In an exemplary embodiment, the stimulator-analyzer device may be configured to apply a set of voltages in a sweeping range from −0.8 V to +0.8 V to the sensor comprising the VAMWCNTs being in contact with the unprocessed blood sample and measure a produced set of electrical currents of the sensor responsive to the applied set of voltages. 
     In an exemplary embodiment, the processing unit may include a memory having processor-readable instructions stored therein and a processor. In an exemplary embodiment, the processor may be configured to access the memory and execute the processor-readable instructions. In an exemplary embodiment, when the processor-readable instructions are executed by the processor, configures the processor to perform a method. In an exemplary embodiment, the method may include applying the set of voltages in the sweeping range from −0.8 V to +0.8 V between the reference electrode and the working electrode utilizing the stimulator-analyzer device, measuring the produced set of electrical currents between the counter electrode and the working electrode utilizing the stimulator-analyzer device, measuring a level of a ratio of low-density neutrophils (LDNs) to high-density neutrophils (HDNs) in the unprocessed blood sample by measuring a level of reactive oxygen species (ROS) in the unprocessed blood sample, and detecting a cancer status of the suspected person. In an exemplary embodiment, measuring the level of ROS in the unprocessed blood sample may include measuring a maximum electrical current of the measured set of electrical currents. 
     In an exemplary embodiment, detecting the cancer status of the suspected person may include one of detecting a cancer disease in suspected person&#39;s body if the measured ratio of LDNs to HDNs in the unprocessed blood sample is more than 1 by detecting the measured maximum electrical current of the measured set of electrical currents being less than a first threshold electrical current value or detecting no cancer disease in the suspected person&#39;s body if the measured ratio of LDNs to HDNs in the unprocessed blood sample is less than 1 by detecting the measured maximum electrical current of the measured set of electrical currents being more than a second threshold electrical current value. In an exemplary embodiment, the method may be conducted in a time period of less than 30 seconds. 
     In an exemplary embodiment, detecting the cancer disease in the suspected person&#39;s body may include detecting the cancer disease in the suspected person&#39;s body if the suspected person&#39;s body is an adult and if the measured maximum electrical current of the measured set of electrical currents is less than 300 μA corresponding to a ratio of LDNs to HDNs in the unprocessed blood sample being in a range of more than 1. In another exemplary embodiment, detecting the cancer disease in the suspected person&#39;s body may include detecting the cancer disease in the suspected person&#39;s body if the suspected person&#39;s body is a child and if the measured maximum electrical current of the measured set of electrical currents is less than 100 μA corresponding to a ratio of LDNs to HDNs in the unprocessed blood sample being in a range of more than 1. 
     In an exemplary embodiment, the method may further include detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body if the measured ratio of LDNs to HDNs in the unprocessed blood sample is less than a threshold LDNs/HDNs value of 1. In an exemplary embodiment, detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body may include detecting no cancer disease in the suspected person&#39;s body if the suspected person&#39;s body is an adult and if the measured maximum electrical current of the measured set of electrical currents is more than 450 μA corresponding to a ratio of LDNs to HDNs in the unprocessed blood sample being less than 1. In another exemplary embodiment, detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body may include detecting no cancer disease in the suspected person&#39;s body if the suspected person&#39;s body is a child and if the measured maximum electrical current of the measured set of electrical currents is more than 300 μA corresponding to a ratio of LDNs to HDNs in the unprocessed blood sample being less than 1. 
     In an exemplary embodiment, the method may further include determining the first threshold electrical current value and the second threshold electrical current value. In an exemplary embodiment, determining the first threshold electrical current value and the second threshold electrical current value may include generating a first dataset of a plurality of unprocessed blood samples associated with a plurality of cancer patients, generating a second dataset of a plurality of unprocessed blood samples associated with a plurality of healthy persons, and determining the first threshold electrical current value and the second threshold electrical current value. 
     In an exemplary embodiment, generating the first dataset of the plurality of unprocessed blood samples associated with the plurality of cancer patients may include measuring a first set of electrical current peaks of the unprocessed blood samples associated with the plurality of cancer patients, measuring a first set of ratio of LDNs to HDNs in the unprocessed blood samples associated with the plurality of cancer patients utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the first set of ratio of LDNs to HDNs to the respective measured electrical current peak of the first set of electrical current peaks. In an exemplary embodiment, generating the second dataset of the plurality of unprocessed blood samples associated with the plurality of healthy persons may include measuring a second set of electrical current peaks of the unprocessed blood samples associated with the plurality of healthy persons, measuring a first set of ratio of LDNs to HDNs in the unprocessed blood samples associated with the plurality of healthy persons utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the second set of ratio of LDNs to HDNs to the respective measured electrical current peak of the second set of electrical current peaks. In an exemplary embodiment, determining the first threshold electrical current value and the second threshold electrical current value may include determining the first threshold electrical current value equal to a maximum electrical current peak among the first set of electrical current peaks and determining the second threshold electrical current value equal to a minimum electrical current peak among the second set of electrical current peaks. 
     In an exemplary embodiment, the circular distal end has a diameter in a range of 0.5 mm to 3 mm. In an exemplary embodiment, the circular distal end has a diameter of 2 mm. In an exemplary embodiment, the three respective circular distal ends of the three electrodes may be placed apart from each other by a distance between 1 mm and 5 mm. In an exemplary embodiment, the three respective circular distal ends of the three electrodes may be placed apart from each other by a distance of 5 mm. 
     In an exemplary embodiment, the substrate may include a first layer of silicon dioxide deposited on a layer of silicon. In an exemplary embodiment, the sensor may further include a second layer of silicon dioxide deposited on surface of sensor except surface of the circular distal end and the proximal end of each respective electrode of the three electrodes. 
     In an exemplary embodiment, the electrically conductive layer may include a layer of at least one of nickel, gold, and combinations thereof. In an exemplary embodiment, the electrically conductive layer may have a thickness in a range of 5 nm to 20 nm. 
     In an exemplary embodiment, the array of VAMWCNTs may include VAMWCNTs with a length in a range of 2.5 μm to 5 μm. In an exemplary embodiment, the array of VAMWCNTs may include VAMWCNTs with a diameter in a range of 50 nm to 70 nm. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawing figures depict one or more embodiments in accord with the present teachings, by way of example only, not by way of limitation. In the figures, like reference numerals refer to the same or similar elements. 
         FIG.  1 A  shows an exemplary system for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  1 B  shows a schematic top view of an exemplary sensor for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  1 C  shows a schematic view of an exemplary sensor for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  1 D  shows another schematic view of an exemplary sensor for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  1 E  shows a schematic view of an exemplary sensor with an exemplary holder and an exemplary cap, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  2 A  shows an exemplary flowchart of an exemplary method for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  2 B  shows an exemplary flowchart of another exemplary method for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  2 C  shows a flowchart of an exemplary method for generating an exemplary first threshold electrical current value and an exemplary second threshold electrical current value, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  3 A  shows an exemplary flowchart of an exemplary method for fabricating an exemplary sensor, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  3 B  shows a schematic view of steps of an exemplary method for fabricating an exemplary sensor, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  4    shows comparative cyclic voltammograms of an exemplary cancer patient and an exemplary healthy candidate, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  5    shows an exemplary computer system in which an embodiment of the present disclosure, or portions thereof, may be implemented as computer-readable code, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  6    shows an image of a Field Emission Scanning Electron Microscope (FE-SEM) of exemplary grown CNTs, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  7    shows a chart representing repeatability of an exemplary fabricated sensor obtained by testing three blood samples from normal and cancer patients with a 3-times of test repeat for each blood sample, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  8    shows a chart of measured peak currents associated with ROS levels in blood samples of 160 investigated patients for two groups of G1: normal candidate/patients with non-cancer diseases and G2: patients with newborns cancer, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  9    shows a receiver operating characteristic (ROC) diagram for results obtained by utilizing exemplary method and fabricated sensor versus clinical diagnostics results for blood samples from 160 patients, consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  10 A  shows representative images of ROS/H 2 O 2  related electrochemical current peak, optical microscope images of LDNs and HDNs, fluorescent microscope images of LDNs and HDNs, Giemsa staining images of LDNs and HDNs, and total cell count of LDNs and HDNs isolated by magnetic, negative selection protocol neutrophils isolated from 5 ml blood of normal cases (N=10), consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  10 B  shows representative images of ROS/H 2 O 2  related electrochemical current peak, optical microscope images of LDNs and HDNs, fluorescent microscope images of LDNs and HDNs, Giemsa staining images of LDNs and HDNs, and total cell count of LDNs and HDNs isolated by magnetic, negative selection protocol neutrophils isolated from 5 ml blood of cancer patients (N=10), consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  10 C  shows a chart of LDN/HDN ratio versus measured current peak diagram with a fitted plot for 20 cases, including normal cases (N=10) and cancer patients (N=10), consistent with one or more exemplary embodiments of the present disclosure. 
         FIG.  11    shows a chart of ROS/H 2 O 2  assisted electrochemical current peaks of blood samples of patients with non-cancer diseases (n=15), consistent with one or more exemplary embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. However, it should be apparent that the present teachings may be practiced without such details. In other instances, well known methods, procedures, components, and/or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present teachings. The following detailed description is presented to enable a person skilled in the art to make and use the methods and devices disclosed in exemplary embodiments of the present disclosure. For purposes of explanation, specific nomenclature is set forth to provide a thorough understanding of the present disclosure. However, it will be apparent to one skilled in the art that these specific details are not required to practice the disclosed exemplary embodiments. Descriptions of specific exemplary embodiments are provided only as representative examples. Various modifications to the exemplary embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the scope of the present disclosure. The present disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest possible scope consistent with the principles and features disclosed herein. 
     In cancer patients with solid tumors, neutrophils can paradoxically mediate a broad range of anti- and pro-tumor activities from cancer cell killing (done by HDNs) to tumor cell proliferation, angiogenesis, metastasis, and organizing other immune responses (done by LDNs). Neutrophil density changes due to their increased granularity and variations in cell size during development. Immature neutrophils are typically found in low density (LD) fractions, whereas mature neutrophils are detected in normal/high density (N/HD) fractions. LDNs are either immature with a banded/ring nucleus or mature with segmented nuclei. All LDNs are pro-tumor that present immunosuppressive properties. HDNs (or NDNs) are mature with segmented nuclei which are antitumor. It should be noted that TGF-β could also mediate transition of HDN to LDN (displaying plasticity) in the murine model. 
     An increased number of immature neutrophils in peripheral blood and tissues is a consequence of cancer development in human patients. LDNs may be detectable in peripheral blood of patients with lung cancer, breast cancer, and ovarian cancer. This increase may result from promotion of immature neutrophil production and release due to increased systemic chemokines, (e.g., granulocyte colony-stimulating (G-CSF)). It should be noted that tumors produce granulocyte colony-stimulating factor (G-CSF). G-CSF reduces chemokine receptor type 4 (CXCR4) expression in human myeloid lineage cells, resulting in decreasing their response to the bone marrow retention signal stromal cell-derived factor 1 (SDF-1). 
     Immature neutrophils may have both anti- and pro-tumor properties. These include altered localization resulting from reduced surface chemotactic receptor expression (e.g., CXCR2) and less segmented nuclear morphology compared to mature ones which reduce their immunological functions due to their reduced ROS production and altered cell surface receptor expression. Also, immature neutrophils are unable to kill tumor cell via FcγRI receptors. These differences in properties and functions of immature neutrophils could lead to their negative effect on cancer therapy. ROS production is crucial in several neutrophil effector mechanisms including their microbicidal, phagocytic, suppressive capacity and neutrophil anti, pro-tumor functions. Reduced ROS production may be the main deficiency of immature neutrophils against cancer cells. 
     Herein, an exemplary real-time electrochemical diagnostic sensor, system, and method for detecting cancer by detecting a level of a ratio of LDNs/HDNs in a blood sample via detecting reactive oxygen species (ROS) levels in a small amount (i.e., about 1 cc) of peripheral blood is disclosed. An exemplary sensor may include three disks like electrodes (working electrode (WE), counter electrode (CE), and reference electrode (RE)) covered by Multi-Wall Carbon Nanotubes (MWCNTs) as a ROS detecting agent in a solution. A cancerous status of a suspected person may be determined utilizing exemplary sensor, system, and/or method in a time period of less than about 30 seconds. An exemplary method and system may be utilized for a rapid detection of cancer via a simple procedure using a small amount (i.e., about 1 cc) of an unprocessed blood sample drawn from a person suspected to have cancer. 
       FIG.  1 A  shows an exemplary system  100  for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, system  100  may include an exemplary sensor  102 , an exemplary electrical stimulator-analyzer device  104 , and an exemplary processing unit  106 . In an exemplary embodiment, sensor  102  may be configured to receive a biological sample thereon. In an exemplary embodiment, the biological sample may be acquired from a person suspected to have cancer. In an exemplary embodiment, the biological sample may include a blood sample drawn from a person. In an exemplary embodiment, the biological sample may include an unprocessed blood sample drawn from a person and directly placed on surface of sensor  102 . In an exemplary embodiment, one or more drops of an unprocessed blood sample may be dropped on surface of sensor  102 . In an exemplary embodiment, sensor  102  may be electrically connected to electrical stimulator-analyzer device  104  and electrical stimulator-analyzer device  104  may be electrically connected to processing unit  106 . 
     In an exemplary embodiment, sensor  102  may include an exemplary electrochemical sensor. In an exemplary embodiment, sensor  102  may include substrate  103  and three electrodes  107 ,  108 , and  109  formed on substrate  103 . In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may include a set of electrochemical electrodes configured to be utilized for electrochemical measurements. In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may include a working electrode  107 , a counter electrode  108 , and a reference electrode  109 .  FIG.  1 B  shows a schematic top view of an exemplary sensor  102  for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, each respective electrode of three electrodes  107 ,  108 , and  109  may include a circular sensing part, a connecting pad, and a middle part between the circular sensing part and the connecting pad. In detail, referring to  FIG.  1 B , an exemplary working electrode  107  may include an exemplary circular sensing part  107   a , an exemplary connecting pad  107   b , and an exemplary middle part  107   c . Furthermore, an exemplary counter electrode  108  may include an exemplary circular sensing part  108   a , an exemplary connecting pad  108   b , and an exemplary middle part  108   c . Moreover, an exemplary reference electrode  109  may include an exemplary circular sensing part  109   a , an exemplary connecting pad  109   b , and an exemplary middle part  109   c . In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may be made of an electrically conductive material. In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may be made of a metal. In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may be made of at least one of nickel, gold, and combinations thereof. In an exemplary embodiment, circular sensing parts  107   a ,  108   a , and  109   a  may include three respective circular distal ends of three respective electrodes  107 ,  108 , and  109 . In an exemplary embodiment, circular sensing parts  107   a ,  108   a , and  109   a  may be configured to be put in contact with an exemplary unprocessed blood sample dropped on surface of exemplary sensor  102 . In an exemplary embodiment, connecting pads  107   b ,  108   b , and  109   b  may include three respective proximal ends of three respective electrodes  107 ,  108 , and  109 . In an exemplary embodiment, connecting pads  107   b ,  108   b , and  109   b  may be configured to be electrically connected to electrical stimulator-analyzer device  104  via respective electrically conductive lines  116 ,  118 , and  120  as shown in  FIG.  1 A . 
     In an exemplary embodiment, each respective electrode of three electrodes  107 ,  108 , and  109  may include an electrically conductive layer deposited on substrate  103 . In an exemplary embodiment, an exemplary electrically conductive layer may have a thickness in a range of about 5 nm to about 20 nm. In an exemplary embodiment, an exemplary electrically conductive layer may include a catalyst material for a process of growing carbon nanotubes (CNTs), for example, vertically aligned multi-walled CNTs (VAMWCNTs), thereon. In an exemplary embodiment, an exemplary electrically conductive layer may include a layer of at least one of nickel, gold, and combinations thereof. In an exemplary embodiment, an exemplary electrically conductive layer may include a circular distal end and a proximal end. In an exemplary embodiment, an exemplary circular distal end may form an exemplary circular sensing part similar to circular sensing parts  107   a ,  108   a , and  109   a  and an exemplary proximal end may form an exemplary connecting pad similar to connecting pads  107   b ,  108   b , and  109   b . In an exemplary embodiment, each respective circular sensing part of circular sensing parts  107   a ,  108   a , and  109   a  may have a diameter in a range of about 0.5 mm to about 3 mm. In an exemplary embodiment, each respective circular sensing part of circular sensing parts  107   a ,  108   a , and  109   a  may have a diameter of about 2 mm. In an exemplary embodiment, circular sensing parts  107   a ,  108   a , and  109   a  of three respective electrodes  107 ,  108 , and  109  may be placed on substrate  103  apart from each other by a distance between about 1 mm and about 5 mm. In an exemplary embodiment, circular sensing parts  107   a ,  108   a , and  109   a  of three respective electrodes  107 ,  108 , and  109  may be placed on substrate  103  apart from each other by a triangular distance  110  (illustrated in  FIG.  1 B ) between of about 5 mm. 
     Referring back to  FIG.  1 A , substrate  103  may include a semi-conductive layer  103   a  and a first electrically passivating layer  103   b  deposited on semi-conductive layer  103   a . In an exemplary embodiment, semi-conductive layer  103   a  may include a layer of silicon. In an exemplary embodiment, first electrically passivating layer  103   b  may include a first layer of silicon dioxide (SiO 2 ). In an exemplary embodiment, three electrodes  107 ,  108 , and  109  may include a layer of an electrically conductive material deposited and patterned on first electrically passivating layer  103   b.    
     In an exemplary embodiment, sensor  102  may further include a second electrically passivating layer deposited on surface of sensor  102  except surface of circular sensing parts  107   a ,  108   a , and  109   a  and surface of connecting pads  107   b ,  108   b , and  109   b  of three respective electrodes  107 ,  108 , and  109 .  FIG.  1 C  shows a schematic view of an exemplary sensor  102  for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment with reference to  FIG.  1 C , exemplary sensor  102  may further include a second electrically passivating layer  105  deposited on substrate  103 . In an exemplary embodiment, second electrically passivating layer  103   b  may include a second layer of SiO 2  deposited on first electrically passivating layer  103   b  and three middle parts  107   c ,  108   c , and  109   c  of three respective electrodes  107 ,  108 , and  109 . 
     In an exemplary embodiment, each respective circular sensing part of circular sensing parts  107   a ,  108   a , and  109   a  may be coated with a layer of carbon nanotubes (CNTs) deposited on the respective circular sensing part.  FIG.  1 D  shows another schematic view of exemplary sensor  102  for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, three arrays of CNTs  130   a ,  130   b , and  130   c  may be coated on respective circular sensing parts  107   a ,  108   a , and  109   a . In an exemplary embodiment, arrays of CNTs  130   a ,  130   b , and  130   c  may include three respective arrays of vertically aligned multi-walled carbon nanotubes (VAMWCNTs) grown on respective circular sensing parts  107   a ,  108   a , and  109   a . In an exemplary embodiment, circular sensing parts  107   a ,  108   a , and  109   a  may be configured to be put in contact with an exemplary unprocessed blood sample dropped on surface of exemplary sensor  102 . In an exemplary embodiment, three arrays of CNTs  130   a ,  130   b , and  130   c  may be configured to be put in contact with an exemplary unprocessed blood sample dropped on surface of exemplary sensor  102 . In an exemplary embodiment, each respective array of CNTs of three arrays of CNTs  130   a ,  130   b , and  130   c  may include a respective plurality of VAMWCNTs, where each respective VAMWCNT may have a length in a range of about 2.5 μm to about 5 μm. In an exemplary embodiment, each respective VAMWCNT of an exemplary array of VAMWCNTs may have a diameter in a range of about 50 nm to about 70 nm. 
     In an exemplary embodiment, system  100  may further include a holder and a cap.  FIG.  1 E  shows a schematic view of exemplary sensor  102  with a holder  140  and a cap  142 , consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, exemplary holder  140  may include a hollow cylinder with a diameter equal or more than an outer diameter of sensor  102 . In an exemplary embodiment, exemplary holder  140  may be configured to fix sensor  102  with an exemplary unprocessed blood sample  150  therein, allowing for protecting sensor  102  and unprocessed blood sample  150  while being in contact with each other. In an exemplary embodiment, exemplary holder  140  may include three electrically conductive elements (pins)  144 ,  146 , and  148 , where each respective pin may be in contact with a respective connecting pad of connecting pads  107   b ,  108   b , and  109   b  of sensor  102 , allowing for an electrical connection between three electrodes  107 ,  108 , and  109  of sensor  102  and three pins  144 ,  146 , and  148 . In an exemplary embodiment, three pins  144 ,  146 , and  148  may be configured to connect respective electrodes  107 ,  108 , and  109  of sensor  102  to an exemplary electrical stimulator-analyzer device  104 . In an exemplary embodiment, sensor  102  may be placed inside holder  140  so that each respective pin of three pins  144 ,  146 , and  148  being in contact with a respective electrode of three electrodes  107 ,  108 , and  109  of sensor  102 . In an exemplary embodiment, unprocessed blood sample  150  may be dropped inside holder  140  on surface of sensor  102 . 
     In an exemplary embodiment, an exemplary cap  142  may include a circular element with a diameter equal or more than an outer diameter of holder  140 . In an exemplary embodiment, cap  142  may be placed on a top side of holder  140  above sensor  102  and unprocessed blood sample  150 . In an exemplary embodiment, cap  142  may be configured to protect sensor  102  and unprocessed blood sample  150  being in contact with each other away from pollutants and disturbing factors. 
     In an exemplary embodiment, electrical stimulator-analyzer device  104  may be electrically connected to sensor  102  at respective proximal ends of each respective electrode of three electrodes  107 ,  108 , and  109  of sensor  102 . In an exemplary embodiment, electrical stimulator-analyzer device  104  may be electrically connected to sensor  102  at connecting pads  107   b ,  108   b , and  109   b  of three electrodes  107 ,  108 , and  109  utilizing three respective electrically conductive lines  116 ,  118 , and  120 . In an exemplary embodiment, electrical stimulator-analyzer device  104  may include a potentiostat device. In an exemplary embodiment, electrical stimulator-analyzer device  104  may be configured to apply a set of voltages in a sweeping range from about −3 V to about +3 V, for example, a range of −0.8 V to +0.8 V, to sensor  102  with unprocessed blood sample  150  placed thereon and measure a produced set of electrical currents of sensor  102  responsive to the applied set of voltages. In an exemplary embodiment, electrical stimulator-analyzer device  104  may be electrically connected to processing unit  106  utilizing at least one of an electrically conductive line  122 , a wireless connection (not illustrated), and combinations thereof. In an exemplary embodiment, the wireless connection may include Bluetooth devices or Bluetooth modules, which may be embedded in electrical stimulator-analyzer device  104  and processing unit  106 . In an exemplary embodiment, electrical stimulator-analyzer device  104  may be further configured to send the measured set of electrical currents to processing unit  106 . 
     In an exemplary embodiment, processing unit  106  may include a memory having processor-readable instructions stored therein and a processor. In an exemplary embodiment, the processor may be configured to access the memory and execute the processor-readable instructions. In an exemplary embodiment, executing the processor-readable instructions by the processor may configures the processor to perform a method. In an exemplary embodiment, the method may include an exemplary method for real-time detecting cancer described herein below. 
       FIG.  2 A  shows a flowchart of an exemplary method  200  for real-time cancer detection, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, method  200  may include putting an unprocessed blood sample in contact with sensing parts of a set of electrodes of a sensor (step  204 ), applying a set of voltages to the sensor (step  206 ), measuring a produced set of electrical currents respective to the applied set of voltages (step  208 ), measuring ratio of LDNs to HDNs in the unprocessed blood sample by measuring a maximum level of the set of electrical currents (step  210 ), and detecting a cancer status based on the measured ratio of LDNs to HDNs in the unprocessed blood sample (step  212 ). 
       FIG.  2 B  shows a flowchart of another exemplary method  220  for real-time detecting cancer, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, exemplary method  220  may contain steps similar to exemplary method  200  while further including step  202  of fabricating an exemplary sensor. Steps of exemplary method  200  and  220  are explained below in further detail in combination with the elements of  FIGS.  1 A- 1 E . 
     With further detail in regards to step  202 ,  FIG.  3 A  shows a flowchart of an exemplary method  300  for fabricating an exemplary sensor (step  202 ), consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, exemplary method  300  of fabricating an exemplary sensor (step  202 ) may include cleaning a semi-conductive substrate (step  301 ), forming a first electrically passivating layer on surface of the semi-conductive substrate (step  302 ), depositing a catalyst layer on the first electrically passivating layer (step  303 ), forming three electrodes by patterning the catalyst layer (step  304 ), electrically passivating a surface of an exemplary sensor except three respective circular distal ends of the three electrodes by coating a second electrically passivating layer on surface of an exemplary sensor except the three respective circular distal ends of the three electrodes (step  305 ), forming three arrays of CNTs on three respective circular distal ends of the three electrodes (step  306 ), and removing parts of the second electrically passivating layer coated on three respective proximal ends of the three electrodes (step  307 ).  FIG.  3 B  shows a schematic view of steps of exemplary method  300  for fabricating an exemplary sensor, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, an exemplary sensor may be similar to sensor  102 , and exemplary method  300  may be described herein below in connection with  FIG.  3 B  and  FIGS.  1 A- 1 E  illustrating an exemplary structure of exemplary sensor  102 . 
     With further detail in regards to step  301 , an exemplary semi-conductive substrate may be cleaned. In an exemplary embodiment, an exemplary semi-conductive substrate may include semi-conductive layer  310  shown in part  310  of  FIG.  3 B  (similar to semi-conductive layer  103   a  of  FIGS.  1 A,  1 C, and  1 D ). In an exemplary embodiment, exemplary semi-conductive layer  320  may include an exemplary circular silicon (Si) wafer. In an exemplary embodiment, semi-conductive layer  320  may include a P-type Si wafer. In an exemplary embodiment, cleaning semi-conductive layer  320  (step  301 ) may include cleaning semi-conductive layer  320  allowing for removing contaminations from an exemplary silicon wafer using a standard RCA method. 
     In further detail with respect to step  302 , step  302  may include forming a first electrically passivating layer on surface of an exemplary cleaned semi-conductive substrate. In an exemplary embodiment, an exemplary first electrically passivating layer  322  (similar to first electrically passivating layer  103   b  of  FIGS.  1 A,  1 C, and  1 D ) may be coated on surface of semi-conductive layer  320  in step  302  as shown in part  312  of  FIG.  3 B ; thereby, an exemplary substrate similar to substrate  103  may be formed. In an exemplary embodiment, step  302  may include growing a first silicon dioxide (SiO 2 ) layer as an example of first electrically passivating layer  322  on a cleaned silicon wafer as an example of semi-conductive layer  320  cleaned in step  301 . 
     In further detail with respect to step  303 , step  303  may include depositing a catalyst layer on an exemplary first electrically passivating layer as schematically shown in part  313  of  FIG.  3 B . In an exemplary embodiment, step  303  may include depositing a catalyst layer  324  on exemplary first electrically passivating layer  322 . In an exemplary embodiment depositing catalyst layer  324  on an exemplary first electrically passivating layer  322  (step  303 ) may include depositing a layer of a catalyst to be used for conducting a process of growing CNTs on exemplary first electrically passivating layer  322 . In an exemplary embodiment, catalyst layer  324  may include a layer of an electrically conductive catalyst for a process of growing CNTs thereon. In an exemplary embodiment, depositing exemplary catalyst layer  324  on exemplary first electrically passivating layer  322  (step  303 ) may include depositing a layer of nickel (Ni) on an exemplary first silicon dioxide (SiO 2 ) layer as an example of exemplary first electrically passivating layer  322  formed on an exemplary cleaned silicon wafer as an example of semi-conductive layer  320  obtained via steps  301  and  302 . In an exemplary embodiment, exemplary catalyst layer  324  may have a thickness of less than about 20 nm. In an exemplary embodiment, exemplary catalyst layer  324  may have a thickness of about 10 nm or less. 
     In further detail with respect to step  304 , step  304  may include forming three exemplary electrodes  326 ,  328 , and  330  (similar to exemplary three exemplary electrodes  107 ,  108 , and  109  of  FIGS.  1 A- 1 B ) by patterning exemplary catalyst layer  324  as schematically shown in part  314  of  FIG.  3 B . In an exemplary embodiment, three exemplary electrodes  326 ,  328 , and  330  may form a set of electrodes including an exemplary working electrode  326 , an exemplary counter electrode  328 , and an exemplary reference electrode  330 . In an exemplary embodiment, patterning exemplary catalyst layer  324  may be done via a photolithography technique. In an exemplary embodiment, patterning exemplary catalyst layer  324  may include patterning exemplary catalyst layer  324  in form of three exemplary electrodes  326 ,  328 , and  330 . In an exemplary embodiment, patterning exemplary catalyst layer  324  may include patterning exemplary catalyst layer  324  in shape of three similar structures with circular heads (for example, circular head  328   a  of electrode  328 ) with a diameter of about 2 mm in conformation of three electrodes  326 ,  328 , and  330 , as working, counter, and reference electrodes with a triangular distance of about 5 mm from each other using a standard photolithography process. In an exemplary embodiment, patterning exemplary catalyst layer  324  may further include spin-coating a thin layer of a positive photoresist (e.g., Microchem-S1813) on surface of exemplary catalyst layer  324 , chemically developing semi-conductive layer  320  with first electrically passivating layer  322  and exemplary catalyst layer  324  thereon by illuminating with a Mask-Aligner system, etching parts of exemplary catalyst layer  324  in undesired regions using an etchant solution (e.g., a Ni-etchant solution: HNO 3 :H 3 PO 4 :CH 3 COOH, 3:3:1), and washing the photoresist layer using a solvent, for example, acetone. In an exemplary embodiment, exemplary undesired regions may include parts of exemplary catalyst layer  324  around patterned three exemplary electrodes  326 ,  328 , and  330 . 
     In an exemplary embodiment, each exemplary electrode  328  of three exemplary electrodes  326 ,  328 , and  330  may include a respective circular head  328   a  (similar to each of circular sensing parts  107   a ,  108   a , and  109   a  illustrated in  FIGS.  1 B- 1 D ). Moreover, each exemplary electrode  328  of three exemplary electrodes  326 ,  328 , and  330  may include a respective tail  328   b  similar to each of connecting pads  107   b ,  108   b , and  109   b  illustrated in  FIGS.  1 B- 1 D . In an exemplary embodiment, exemplary circular head  328   a  may include a respective distal end of exemplary electrode  328  of set of electrodes  326 ,  328 , and  330 . In an exemplary embodiment, exemplary tail  328  may include a respective proximal end of exemplary electrode  328  of set of electrodes  326 ,  328 , and  330 . In an exemplary embodiment, each respective electrode of set of electrodes  326 ,  328 , and  330 , for example, exemplary electrode  328  may further include a respective middle part  328   c  between respective circular head  328   a  and respective tail  328   b . In an exemplary embodiment, respective circular heads (e.g., circular head  328   a ) of electrodes  326 ,  328 , and  330  may be configured to be put in contact with a sample (e.g., exemplary unprocessed blood sample  150 ) by placing an exemplary sample thereon. In an exemplary embodiment, respective tails (e.g., tail  328   b ) of electrodes  326 ,  328 , and  330  may be configured to be connected to an electrical device, for example, electrical stimulator-analyzer device  104 . In an exemplary embodiment, respective middle parts (e.g., middle part  328   c ) of electrodes  326 ,  328 , and  330  may be configured to form an electrically conductive path between respective circular heads (e.g., circular head  328   a ) of electrodes  326 ,  328 , and  330 , and similarly, circular sensing parts  107   a ,  108   a , and  109   a  and respective tails (e.g., tail  328   b ) of electrodes  326 ,  328 , and  330 , and similarly, connecting pads  107   b ,  108   b , and  109   b  of electrodes  107 ,  108 , and  109 . 
     In further detail with respect to step  305 , step  305  may include electrically passivating a surface of an exemplary sensor except three respective circular distal ends of exemplary three electrodes by coating a second electrically passivating layer on surface of an exemplary sensor except three respective circular distal ends of three exemplary electrodes. In an exemplary embodiment, step  305  may include electrically passivating a surface of exemplary sensor  102  except three respective circular heads  326   a ,  328   a , and  330   a ) of electrodes  326 ,  328 , and  330  as schematically shown in part  315  of  FIG.  3 B . In an exemplary embodiment, step  305  may include coating entire surface of exemplary sensor  102  with a second electrically passivating layer  332  (similar to second electrically passivating layer  105 ) and removing parts of exemplary second electrically passivating layer  332  coated on circular heads  326   a ,  328   a , and  330   a  of respective electrodes  326 ,  328 , and  330 . In an exemplary embodiment, entire surface of exemplary sensor  102  may include surface of first electrically passivating layer  322  and surface of patterned electrodes  326 ,  328 , and  330 . In an exemplary embodiment, second electrically passivating layer  332  may include a second SiO 2  layer. In an exemplary embodiment, coating entire surface of exemplary sensor  102  with second electrically passivating layer  332  may include passivating exemplary sensor  102  with a 200 nm SiO 2  layer at 0.9 torr, and 20 W (deposition speed &lt;45 nm min −1 ). In an exemplary embodiment, removing parts of an exemplary second SiO 2  layer coated on respective circular heads  326   a ,  328   a , and  330   a  of electrodes  326 ,  328 , and  330  may be carried out by immersing exemplary sensor  102  in a buffered oxide etchant (BOE) solution to prepare circular windows for three electrodes  326 ,  328 , and  330 . In an exemplary embodiment, immersing exemplary sensor  102  in the BOE solution may be done in about 7 seconds. 
     In further detail with respect to step  306 , step  306  may include forming three arrays of CNTs on three respective circular distal ends of three exemplary electrodes of an exemplary sensor as schematically shown in part  316  of  FIG.  3 B . In an exemplary embodiment, step  306  may include forming three exemplary arrays of CNTs  334   a ,  334   b , and  334   c  (similar to three exemplary arrays of CNTs  130   a ,  130   b , and  130   c  of  FIG.  1 D ) on three respective circular heads  326   a ,  328   a , and  330   a  of electrodes  326 ,  328 , and  330 . In an exemplary embodiment, forming three arrays of CNTs  334   a ,  334   b , and  334   c  on respective circular heads  326   a ,  328   a , and  330   a  of electrodes  326 ,  328 , and  330  may include growing a respective plurality of vertically aligned multi-walled carbon nanotubes (VAMWCNTs) on each respective circular head of circular heads  326   a ,  328   a , and  330   a  of electrodes  326 ,  328 , and  330 . In an exemplary embodiment, growing VAMWCNTs may be carried out in a direct current plasma enhance chemical vapor deposition (DC-PECVD) system in C 2 H 2  and H 2  ambient at a temperature of about 680° C. 
     In further detail with respect to step  307 , step  307  may include removing parts of an exemplary second electrically passivating layer coated on three respective proximal ends of exemplary three electrodes of an exemplary sensor as schematically shown in part  317  of  FIG.  3 B . In an exemplary embodiment, step  307  may include removing parts of second electrically passivating layer  332  from surface of three respective proximal ends (tails  326   b ,  328   b , and  330   b ) of three electrodes  326 ,  328 , and  330 . In an exemplary embodiment, step  307  may include removing parts of an exemplary coated second SiO 2  layer from surface of tails  326   b ,  328   b , and  330   b  (similar to connecting pads  107   b ,  108   b , and  109   b  of electrodes  107 ,  108 , and  109 ) using a BOE solution. 
     Referring back to  FIGS.  2 A and  2 B , step  204  may include putting an unprocessed blood sample in contact with sensing parts of electrodes of an exemplary sensor. In an exemplary embodiment, step  204  may include placing or dropping exemplary unprocessed blood sample  150  on surface of exemplary sensor  102 . In an exemplary embodiment, step  204  may include putting exemplary unprocessed blood sample  150  in contact with circular sensing parts  107   a ,  108   a , and  109   a  of three electrodes  107 ,  108 , and  109  of sensor  102 . In an exemplary embodiment, step  204  may include dropping exemplary unprocessed blood sample  150  on respective circular sensing parts  107   a ,  108   a , and  109   a  of electrodes  107 ,  108 , and  109 . In an exemplary embodiment, exemplary unprocessed blood sample  150  may be drawn from a person suspected to have cancer. In an exemplary embodiment, exemplary unprocessed blood sample  150  may be drawn from a person who is not pregnant and/or does not infected with an inflammatory disease. In an exemplary embodiment, exemplary unprocessed blood sample  150  may be drawn from a person suspected to be involved with a cancer having a solid tumor, for example, breast cancer, colon cancer, skin cancer, etc. 
     In further detail with respect to step  206 , step  206  may include applying a set of voltages to sensor  102 . In an exemplary embodiment, applying the set of voltages to sensor  102  may include applying the set of voltages between exemplary reference electrode  109  and exemplary working electrode  107  of electrodes  107 ,  108 , and  109  of sensor  102 . In an exemplary embodiment, applying the set of voltages to sensor  102  may be done utilizing electrical stimulator-analyzer device  104 . In an exemplary embodiment, applying the set of voltages to sensor  102  may include applying the set of voltages in a sweeping range from about −3 V to about +3 V between exemplary reference electrode  109  and exemplary working electrode  107  of electrodes  107 ,  108 , and  109  of sensor  102 . In an exemplary embodiment, applying the set of voltages to sensor  102  may include applying the set of voltages in the sweeping range from about −0.8 V to about +0.8 V between exemplary reference electrode  109  and exemplary working electrode  107  of electrodes  107 ,  108 , and  109  of sensor  102 . 
     In further detail with respect to step  208 , step  208  may include measuring a produced set of electrical currents respective to the applied set of voltages to sensor  102 . In an exemplary embodiment, a set of electrical currents may be generated between an exemplary counter electrode  108  and an exemplary working electrode  107  of the three electrodes  107 ,  108 , and  109  of sensor  102  responsive to the applied set of voltages. In an exemplary embodiment, step  208  may include measuring the produced set of electrical currents between counter electrode  108  and working electrode  107  of three electrodes  107 ,  108 , and  109  of sensor  102  respective to the applied set of voltages. In an exemplary embodiment, measuring the produced set of electrical currents may be carried out utilizing electrical stimulator-analyzer device  104 . In an exemplary embodiment, measuring the produced set of electrical currents may further include sending the measured produced set of electrical currents to processing unit  106  by electrical stimulator-analyzer device  104 . 
     In further detail with respect to step  210 , step  210  may include measuring ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  by measuring a maximum level of the set of electrical currents. In an exemplary embodiment, measuring the maximum level of the set of electrical currents may be carried out by one or more processors similar, for example, processing unit  106 . In an exemplary embodiment, measuring the ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  may include measuring a level of reactive oxygen species (ROS) in the unprocessed blood sample  150  by measuring a maximum electrical current of the measured set of electrical currents. In an exemplary embodiment, measuring the ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  may include receiving the measured produced set of electrical currents, plotting a cyclic voltammetry (CV) diagram by plotting the measured produced set of electrical currents versus the applied set of voltages, and measuring a peak value of electrical currents of the CV diagram. 
     In an exemplary embodiment, measuring the ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  may further include determining a level of ratio of LDNs to HDNs in the unprocessed blood sample using the measured maximum electrical current of the measured set of electrical currents. In an exemplary embodiment, determining the level of ratio of LDNs to HDNs in the unprocessed blood sample may include detecting the level of ratio of LDNs to HDNs in the unprocessed blood sample is more than 1 if the measured maximum electrical current of the measured set of electrical currents is less than a first threshold electrical current value and detecting the level of ratio of LDNs to HDNs in the unprocessed blood sample is less than 1 if the measured maximum electrical current of the measured set of electrical currents is more than a second threshold electrical current value. 
     In an exemplary embodiment, exemplary method  200  may further include generating the first threshold electrical current value and the second threshold electrical current value.  FIG.  2 C  shows a flowchart of a method  230  for generating the first threshold electrical current value and the second threshold electrical current value, consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, exemplary method  230  of generating the first threshold electrical current value and the second threshold electrical current value may include generating a first dataset of a plurality of unprocessed blood samples associated with a plurality of cancer patients (step  232 ), generating a second dataset of a plurality of unprocessed blood samples associated with a plurality of healthy persons (step  234 ), and determining first threshold electrical current value and the second threshold electrical current value based on the first dataset and the second dataset (step  236 ). 
     In further detail with respect to step  232 , step  232  of generating a first dataset of a plurality of unprocessed blood samples associated with a plurality of cancer patients may include measuring a first set of electrical current peaks of the plurality of unprocessed blood samples associated with the plurality of cancer patients, measuring a first set of ratio of LDNs to HDNs in the plurality of unprocessed blood samples associated with the plurality of cancer patients utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the first set of ratio of LDNs to HDNs to the respective measured electrical current peak of the first set of electrical current peaks. 
     In further detail with respect to step  234 , step  234  of generating a second dataset of a plurality of unprocessed blood samples associated with a plurality of healthy persons may include measuring a second set of electrical current peaks of the plurality of unprocessed blood samples associated with the plurality of healthy persons, measuring a second set of ratio of LDNs to HDNs in the unprocessed blood samples associated with the plurality of healthy persons utilizing a cell counter, and assigning each measured ratio of LDNs to HDNs of the second set of ratio of LDNs to HDNs to the respective measured electrical current peak of the second set of electrical current peaks. 
     In further detail with respect to step  236 , step  236  of determining the first threshold electrical current value and the second threshold electrical current value based on the first dataset and the second dataset may include determining the first threshold electrical current value equal to a maximum electrical current peak among the first set of electrical current peaks and determining the second threshold electrical current value equal to a minimum electrical current peak among the second set of electrical current peaks. In an exemplary embodiment, the first threshold electrical current value and the second threshold electrical current value may be equal to each other. 
     In an exemplary embodiment, the first threshold electrical current value and the second threshold electrical current value may depend on age of an exemplary suspected person. In an exemplary embodiment, the first threshold electrical current value may be equal to an electrical current peak of about 300 μA for an adult person. In an exemplary embodiment, the first threshold electrical current value may be equal to an electrical current peak of about 100 μA for a child. In an exemplary embodiment, the second threshold electrical current value may be equal to an electrical current peak of about 450 μA for an adult person. In an exemplary embodiment, the second threshold electrical current value may be equal to an electrical current peak of about 300 μA for a child. 
     Referring back to  FIGS.  2 A and  2 B , step  212  may include detecting a cancer status of an exemplary suspected person based on the measured ratio of LDNs to HDNs in exemplary unprocessed blood sample  150 .  FIG.  4    shows comparative cyclic voltammograms of an exemplary cancer patient (diagram  402 ) and an exemplary healthy candidate (diagram  404 ), consistent with one or more exemplary embodiments of the present disclosure. In an exemplary embodiment, detecting cancer status of an exemplary suspected person may include detecting a cancer disease in suspected person&#39;s body associated with exemplary unprocessed blood sample  150  if the measured ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  is more than a threshold LDNs/HDNs value by detecting the measured maximum electrical current of the measured set of electrical currents being less than the first threshold electrical current value. In an exemplary embodiment, the threshold LDNs/HDNs value may equal to about 1 so that if a level of LDNs is more than HDNs in exemplary unprocessed blood sample  150 , a cancer disease may be detected for an exemplary suspected person. 
     In an exemplary embodiment, the first threshold electrical current value corresponding to a threshold LDNs/HDNs value of 1 may equal to 300 μA for adults and 100 μA for children. In an exemplary embodiment, “adults” as used herein may refer to people who are 18 years old or older. In an exemplary embodiment, “children or pediatrics cohort” as used herein may refer to people who are younger than 18 years, for example, children from new born to 13 years old. In an exemplary embodiment, detecting the cancer disease in the suspected person&#39;s body may include detecting the cancer disease in an adult suspected person&#39;s body if the measured maximum electrical current of the measured set of electrical currents is less than about 300 μA corresponding to a ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  being more than 1. In another exemplary embodiment, detecting the cancer disease in the suspected person&#39;s body may include detecting the cancer disease in a suspected child&#39;s body if the measured maximum electrical current of the measured set of electrical currents is less than about 100 μA corresponding to a ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  being more than 1. 
     In another exemplary embodiment, detecting cancer status of an exemplary suspected person may include detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body if the measured ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  is less than the threshold LDNs/HDNs value. In an exemplary embodiment, no cancer may be detected for an exemplary suspected person if a level of LDNs is less than HDNs in exemplary unprocessed blood sample  150 . In an exemplary embodiment, no cancer may be detected for an exemplary suspected person if a level of ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  is less than about 1 if the measured maximum electrical current of the measured set of electrical currents is more than the second threshold electrical current value. In an exemplary embodiment, detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body may include detecting no cancer disease in the suspected person&#39;s body if the suspected person is an adult and if the measured maximum electrical current of the measured set of electrical currents is more than 450 μA corresponding to a ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  being less than 1. In another exemplary embodiment, detecting no cancer disease (a normal or healthy status) in the suspected person&#39;s body may include detecting no cancer disease in the suspected person&#39;s body if the suspected person is a child and if the measured maximum electrical current of the measured set of electrical currents is more than 300 μA corresponding to a ratio of LDNs to HDNs in exemplary unprocessed blood sample  150  being less than 1. 
       FIG.  5    shows an example computer system  500  in which an embodiment of the present disclosure, or portions thereof, may be implemented as computer-readable code, consistent with one or more exemplary embodiments of the present disclosure. For example, computer system  500  may include an example of processing unit  106  illustrated in  FIG.  1   , and steps  206 - 212  of exemplary methods  200  and  220  presented in  FIGS.  2 A and  2 B  in addition to steps  232 - 236  of exemplary method  230  illustrated in  FIG.  2 C , may be implemented in computer system  500  using hardware, software, firmware, tangible computer readable media having instructions stored thereon, or a combination thereof and may be implemented in one or more computer systems or other processing systems. Hardware, software, or any combination of such may embody any of the modules and components in  FIGS.  1 ,  2 A- 2 C . 
     If programmable logic is used, such logic may execute on a commercially available processing platform or a special purpose device. One ordinary skill in the art may appreciate that an embodiment of the disclosed subject matter can be practiced with various computer system configurations, including multi-core multiprocessor systems, minicomputers, mainframe computers, computers linked or clustered with distributed functions, as well as pervasive or miniature computers that may be embedded into virtually any device. 
     For instance, a computing device having at least one processor device and a memory may be used to implement the above-described embodiments. A processor device may be a single processor, a plurality of processors, or combinations thereof. Processor devices may have one or more processor “cores.” 
     An embodiment of the present disclosure is described in terms of this example computer system  500 . After reading this description, it will become apparent to a person skilled in the relevant art how to implement the invention using other computer systems and/or computer architectures. Although operations may be described as a sequential process, some of the operations may in fact be performed in parallel, concurrently, and/or in a distributed environment, and with program code stored locally or remotely for access by single or multiprocessor machines. In addition, in some embodiments the order of operations may be rearranged without departing from the spirit of the disclosed subject matter. 
     Processor device  504  may be a special purpose or a general-purpose processor device. As will be appreciated by persons skilled in the relevant art, processor device  504  may also be a single processor in a multi-core/multiprocessor system, such system operating alone, or in a cluster of computing devices operating in a cluster or server farm. Processor device  504  may be connected to a communication infrastructure  506 , for example, a bus, message queue, network, or multi-core message-passing scheme. 
     In an exemplary embodiment, computer system  500  may include a display interface  502 , for example a video connector, to transfer data to a display unit  530 , for example, a monitor. Computer system  500  may also include a main memory  508 , for example, random access memory (RAM), and may also include a secondary memory  510 . Secondary memory  510  may include, for example, a hard disk drive  512 , and a removable storage drive  514 . Removable storage drive  514  may include a floppy disk drive, a magnetic tape drive, an optical disk drive, a flash memory, or the like. Removable storage drive  514  may read from and/or write to a removable storage unit  518  in a well-known manner. Removable storage unit  518  may include a floppy disk, a magnetic tape, an optical disk, etc., which may be read by and written to by removable storage drive  514 . As will be appreciated by persons skilled in the relevant art, removable storage unit  518  may include a computer usable storage medium having stored therein computer software and/or data. 
     In alternative embodiments, secondary memory  510  may include other similar means for allowing computer programs or other instructions to be loaded into computer system  500 . Such means may include, for example, a removable storage unit  522  and an interface  520 . Examples of such means may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM, or PROM) and associated socket, and other removable storage units  522  and interfaces  520  which allow software and data to be transferred from removable storage unit  522  to computer system  500 . 
     Computer system  500  may also include a communications interface  524 . Communications interface  524  allows software and data to be transferred between computer system  500  and external devices. Communications interface  524  may include a modem, a network interface (such as an Ethernet card), a communications port, a PCMCIA slot and card, or the like. Software and data transferred via communications interface  524  may be in the form of signals, which may be electronic, electromagnetic, optical, or other signals capable of being received by communications interface  524 . These signals may be provided to communications interface  524  via a communications path  526 . Communications path  526  carries signals and may be implemented using wire or cable, fiber optics, a phone line, a cellular phone link, an RF link or other communications channels. 
     In this document, the terms “computer program medium” and “computer usable medium” are used to generally refer to media such as removable storage unit  518 , removable storage unit  522 , and a hard disk installed in hard disk drive  512 . Computer program medium and computer usable medium may also refer to memories, such as main memory  508  and secondary memory  510 , which may be memory semiconductors (e.g. DRAMs, etc.). 
     Computer programs (also called computer control logic) are stored in main memory  508  and/or secondary memory  510 . Computer programs may also be received via communications interface  524 . Such computer programs, when executed, enable computer system  500  to implement different embodiments of the present disclosure as discussed herein. In particular, the computer programs, when executed, enable processor device  504  to implement the processes of the present disclosure, such as the operations in method  200  illustrated by  FIGS.  2 A- 2 C , discussed above. Accordingly, such computer programs represent controllers of computer system  500 . Where an exemplary embodiment of method  200  is implemented using software, the software may be stored in a computer program product and loaded into computer system  500  using removable storage drive  514 , interface  520 , and hard disk drive  512 , or communications interface  524 . 
     Embodiments of the present disclosure also may be directed to computer program products including software stored on any computer useable medium. Such software, when executed in one or more data processing device, causes a data processing device to operate as described herein. An embodiment of the present disclosure may employ any computer useable or readable medium. Examples of computer useable mediums include, but are not limited to, primary storage devices (e.g., any type of random access memory), secondary storage devices (e.g., hard drives, floppy disks, CD ROMS, ZIP disks, tapes, magnetic storage devices, and optical storage devices, MEMS, nanotechnological storage device, etc.). 
     Example 1: Sensor Fabrication Process 
     In this example, an exemplary sensor similar to sensor  102  was fabricated via a method similar to exemplary method  300  illustrated in  FIGS.  3 A and  3 B  hereinabove. First, p-type Si wafer (100) was cleaned by the standard RCA method (RCA #1 method with NH 4 OH:H 2 O 2 :H 2 O solution and a volume ratio of 1:1:5), rinsed in deionized (DI) water, and dried by compressed air. A thermal oxide was then grown on the wafer in a wet oxide furnace at about 1050° C. for about 2.5 hours to form a substrate. Then, a Ni catalyst layer for CNT growth with a thickness of about 9 nm was deposited on the substrate by E-beam evaporation system, at a temperature of about 120° C. and with a depositing rate of about 0.1 Angstroms/s. Afterward, The Ni layer was patterned in a shape of three circles with a diameter of about 2 mm in an exemplary conformation of three electrodes, as working, counter, and reference with a triangular distance of 5 mm from each other using standard photolithography process. For this process, a thin layer of a positive photoresist (e.g., Microchem-S1813) was spin-coated on the substrate surface. After illumination with the Mask-Aligner system, the substrate chemically developed. Then, a Ni layer in an undesired region (a region except of a region of three electrodes) was etched using a Ni-etchant solution (HNO 3 :H 3 PO 4 :CH 3 COOH, 3:3:1), and after that, the photoresist was washed using acetone. The entire substrate was then passivated with a 200 nm oxide layer at 0.9 torr, and 20 W (deposition speed &lt;45 nm min −1 ). The silicon dioxide layer deposited on the electrodes was removed by immersion of the positive PR-patterned substrate in a buffered oxide etchant (BOE) solution for about 7 s to prepare windows for the formed three-metal thin-film electrodes. Finally, the substrate with the formed electrodes thereon was located in a direct current plasma enhanced chemical vapor deposition (DC-PECVD) system to grow vertically aligned multi-walled carbon nanotubes (VAMWCNTs) on electrodes&#39; heads. The growth of VAMWCNTs has a three-step process named annealing, graining, and growth. At first, the substrate with the formed electrodes was annealed at 680° C. in an H 2  environment with a flow rate of 20 standard cubic centimeters per minute (sccm) for 30 minutes. During the graining, the surface was plasma hydrogenated for 5 minutes with the intensity of 5.5 W·cm −2 , which results in the catalyst graining and formation of Ni Nano-sized islands. In growth step, plasma of C 2 H 2  and H 2  mixture with flow rates of 4.5 and 20 sccm was introduced to the chamber for about 20 minutes. Grown CNT arrays on electrodes were characterized by Field Emission Scanning Electron Microscope (FE-SEM).  FIG.  6    shows an image  600  of a Field Emission Scanning Electron Microscope (FE-SEM) image of exemplary grown CNTs, consistent with one or more exemplary embodiments of the present disclosure. Length and diameter of nanotubes were ranged from about 2.5 μm to about 5 μm and from about 50 nm to about 70 nm, respectively. CNT arrays were used as the work, counter, and reference electrodes. Then, the passivating layer coated on connecting pads of electrodes were removed with BOE and the connecting pads of electrodes were attached to an electrical connector with three pins by conductive paste to form an exemplary final sensor. Afterwards, the electrical connector was connected to a readout system as an example of electrical stimulator-analyzer device  104  by a noiseless cable that handled all three electrodes. 
     Repeatability of the fabricated sensor was examined by testing three blood samples from normal and cancer patients with a 3-times of test repeat on each of them.  FIG.  7    shows a chart  700  representing repeatability of an exemplary fabricated sensor obtained by testing three blood samples from normal and cancer patients with a 3-times of test repeat for each blood sample, consistent with one or more exemplary embodiments of the present disclosure. 
     Example 2: Detecting Cancer by Electrochemical Measuring of Reactive Oxygen Species (ROS) Levels in Blood 
     In this example, one hundred sixty patients of kids (2 months-13 years of age) and adults (20-73 years old) in two groups of newborn cancer with histologically confirmed cancer (n=60) and normal candidates (n=100) were tested here to investigate a correlation between ROS electrochemical peak results and abundancy ratio of HDNs to LDNs in their unprocessed blood samples. All cancer patients had advanced diseases (stages III-IV) in accordance with the American Joint Committee on Cancer criteria. Additionally, some treated patients with chemo/radiotherapy were investigated (n=20). Clinical, laboratory, and radiological characteristics and diagnosis and outcomes data were collected from all patients. Fresh blood samples prepared from 180 candidates were recorded. Also, patients&#39; symptoms and therapeutic steps of cancer patients were recorded. For each patient, about 1 cc blood was used to measure released ROS/H 2 O 2  from HDNs and LDNs in peripheral blood utilizing an exemplary system similar to system  100  including an exemplary sensor fabricated in EXAMPLE 1 hereinabove via an exemplary method similar to method  200 . Furthermore, LDNs and HDNs were isolated from whole blood with magnetic isolation and Percoll gradient. Then, LDN and HDN cells were counted by cell counter. Also, LDN and HDN cells were stained with Giemsa following thin-layer cell preparation and ROS fluorescent assay of LDNs and HDNs was carried out using a fluorescent microscopy system. 
     Neutrophil Isolation from Whole Blood and Quantification: 
     Total circulating neutrophils were isolated from 5 ml cancer patients&#39; blood by negative selection using a Whole Blood Neutrophil Isolation Kit for human. Then, LDN and HDNs were isolated by discontinuous Percoll density gradient method. 9 ml Percoll was added to 1 ml 10×PBS (Stem cell) to create a 100% solution. Then, 2.5 ml of 78% Percoll diluted in 1×PBS was added carefully to a 15 ml falcon tube followed by a 2 ml layer of 66% Percoll and, so total neutrophils resuspended in 2 ml 54% Percoll. Centrifugation at 1545×g without brake was performed for 30 minutes at room temperature. HDNs were recovered from the 78%/66% interface and LDNs from 66%/54% interface. Cell counts were performed using a cell counter. Afterward, HDNs and LDNs cells were fixed by dipping the glass slides in 70% ethanol for 2 min and allowed to dry at room temperature before staining. HDNs and LDNs cells were stained 50 min in Giemsa solution, and washed in Tap water. Finally, glass slides were air-dried shortly and the dried slides were inspected under a light microscope. 
     Ros Assay: 
     ROS generation was analyzed with a 5-chloromethyl-2′-7′-dichlorodihydrofluorescein diacetate (CM-H2DCFDA) assay. This probe is changed to 2′-7′-dichlorofluorescein (DCF) with a green fluorescent property by esterase enzymes in the cells&#39; cytosol. After culturing fibroblast and MCF-7 cells overnight, the cells were washed with PBS, and then 500 μL of CM-H2DCFDA solution was added with a concentration of 20 μM. After 30 min incubation at room temperature in dark ambient, cells were again washed and then imaged with a fluorescent microscope. The cells were incubated with 10 mM of NAC as a ROS scavenger and then treated with CM-H2DCFDA. For positive control, cells were incubated with 100 μM H 2 O 2  and treated by CM-H2DCFDA. Afterwards, samples were imaged with a fluorescent microscopy system. 
     An exemplary sensor fabricated in EXAMPLE 1 hereinabove was used to detect ROS levels in about 1 cc of an unprocessed blood sample from cancer patients and normal cases. The unprocessed blood sample was a residue of conventionally received blood from volunteers due to their checkup by informing them and their satisfaction. Intensity of released ROS levels in peripheral blood was recorded by a cyclic voltammetry procedure via a method similar to method  200  described hereinabove. Coherent results were achieved after categorizing the measured ROS current peaks and comparing them with candidates&#39; clinical diagnostic results and abundancy of LDNs versus HDNs in their blood samples. Table 1 shows baseline characteristics of 160 patients investigated herein, including group 1 (G1) of normal candidate/patients with non-cancer diseases and group 2 (G2) of patients with newborns cancer. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Baseline characteristics of 160 investigated patients (G1: Normal candidate/patients 
               
               
                 with non-cancer diseases, G2: Patients with newborns cancer). 
               
            
           
           
               
               
            
               
                   
                 State of patients 
               
            
           
           
               
               
            
               
                   
                 Normal/Non 
               
            
           
           
               
               
               
               
            
               
                   
                 Characteristic 
                 cancer diseases 
                 Malignant tumor 
               
            
           
           
               
               
               
               
               
               
            
               
                 Candidates 
                 Age 
                 Sex 
                 Race 
                 (n = 80) 
                 (n = 80) 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Children 
                 2 months-13 
                 Female 
                 Male 
                 White 
                 Appendicitis 
                 Ewing sarcoma/neck 
               
               
                   
                 years old 
                 (n = 21) 
                 (n = 39) 
                   
                 (n = 5) 
                 tumor mass (n = 3) 
               
               
                   
                   
                   
                   
                   
                 Abdominal 
                 Rhabdomyosarcoma 
               
               
                   
                   
                   
                   
                   
                 edema (n = 6) 
                 pelvis (n = 6) 
               
               
                   
                   
                   
                   
                   
                 Abdominal hernia 
                 Ewing 
               
               
                   
                   
                   
                   
                   
                 (n = 2) 
                 sarcoma/abdomen 
               
               
                   
                   
                   
                   
                   
                 Left kidney stone 
                 tumor mass 
               
               
                   
                   
                   
                   
                   
                 (n = 1) 
                 (n = 4) 
               
               
                   
                   
                   
                   
                   
                 Liver Hydatid 
                 Brain tumor in the 
               
               
                   
                   
                   
                   
                   
                 cyst (n = 3) 
                 left ventricle (n = 2) 
               
               
                   
                   
                   
                   
                   
                 Hypertrophic 
                 Lung cancer (n = 3) 
               
               
                   
                   
                   
                   
                   
                 pyloric stenosis 
                 Wilms tumor (n = 7) 
               
               
                   
                   
                   
                   
                   
                 (n = 2) 
                 Hepatoblastoma 
               
               
                   
                   
                   
                   
                   
                 Osteocyte foot 
                 (n = 2) 
               
               
                   
                   
                   
                   
                   
                 bone (n = 2) 
                 Neuroblastoma 
               
               
                   
                   
                   
                   
                   
                 Vesicostomy 
                 (n = 2) 
               
               
                   
                   
                   
                   
                   
                 (n = 3) 
                 Osteosarcoma (n = 1) 
               
               
                   
                   
                   
                   
                   
                 Normal (n = 6) 
               
               
                 Adults 
                 20-73 
                 Female 
                 Male 
                 White 
                 Fibrocystic 
                 Phyllodes 
               
               
                   
                   
                 (n = 100) 
                 (n = 0) 
                   
                 changes/ 
                 (cancerous) (n = 5) 
               
               
                   
                   
                   
                   
                   
                 Microcalcification 
                 IDC nuclear grade 2 
               
               
                   
                   
                   
                   
                   
                 (n = 20) 
                 (n = 60) 
               
               
                   
                   
                   
                   
                   
                 Fibroadenoma/ 
                 IDC nuclear grade 3 
               
               
                   
                   
                   
                   
                   
                 Cystic mass 
                 (n = 25) 
               
               
                   
                   
                   
                   
                   
                 (n = 10) 
                 high grade DCIS 
               
               
                   
                   
                   
                   
                   
                 Florid ductal 
                 (n = 7) 
               
               
                   
                   
                   
                   
                   
                 hyperplasia 
                 Low/inter mediate 
               
               
                   
                   
                   
                   
                   
                 (n = 20) 
                 grade DCIS (n = 2) 
               
               
                   
                   
                   
                   
                   
                 Normal (n = 50) 
                 ILC (n = 1) 
               
               
                   
               
            
           
         
       
     
     Also, a calibration pattern was provided between responses measured and obtained by exemplary fabricated sensor and results of pathological state of the patients with tumors.  FIG.  8    shows a chart  800  of measured peak currents associated with ROS levels in blood samples of 160 investigated patients for two groups of G1: normal candidate/patients with non-cancer diseases and G2: patients with newborns cancer, consistent with one or more exemplary embodiments of the present disclosure. As may be seen in  FIG.  8   , 100% of blood samples in all children with advanced cancers (stages III-IV) showed peak currents lower than about 100 μA, while normal and non-cancerous candidates showed current peaks higher than about 300 μA. These ROS/H 2 O 2  assisted current peaks for 90% of adults intended in this study with breast cancer tumors were lower than about 300 μA. In comparison, 98% of normal candidates with no complaint cases (including healthy people or diagnosed benign tumors) showed peak currents higher than about 450 μA. As a result, the ROS/H 2 O 2  assisted electrochemical current peaks of the blood sample in patients with cancer tumors shows significant differences to blood current peaks of the normal/none cancer patients. This gap in pediatrics cohort is about 200 μA so that a ROS current peak for normal cases is more than about 300 μA, whereas a ROS current peak for cancer patients is less than about 100 μA. A gap for adults is about 150 μA so that a ROS current peak for normal cases is more than about 450 μA, whereas a ROS current peak for cancer patients is less than about 300 μA. So, the cut-off between normal/non-cancer disease and cancer cases is well detectable. It should be mentioned that adult cancer cohorts only were selected from breast cancer patients due to available clinical research center&#39;s facility. 
     Furthermore, receiver operating characteristic (ROC) curve analysis was done to compare between peak level responses associated with neutrophil ROS production in blood measured by exemplary fabricated sensor and results of clinical diagnostics (gold standard). The clinical diagnostics, including pathological and radiological evaluation, was considered as the gold standard test for diagnosis cancerous specimens.  FIG.  9    shows a ROC diagram  900  for results obtained by utilizing exemplary method and fabricated sensor versus clinical diagnostics results for blood samples from 160 patients, consistent with one or more exemplary embodiments of the present disclosure. The result showed that an area under ROC curve (AUC) value for exemplary method  200  or method  220  of the present disclosure utilizing exemplary system  100  and sensor  102  was 0.981 (with P-value of less than about 0.0001 and CI99% 0.949-1) as represented in  FIG.  9    and Table 2. Therefore, the obtained AUC value within a range of 0.9 to 1.0 may be an indicator of very high accuracy of exemplary method, system, and fabricated sensor which shows that exemplary method, system, and fabricated sensor is a reliable diagnostic tool and has a good balance of sensitivity and specificity. 
     Moreover, specificity, sensitivity, accuracy, precision, and selectivity was calculated for exemplary method and fabricated sensor as presented in Table 3. Also, true and false positive and negative data are shown in detail in Table 3. Accordingly, exemplary method, system, and sensor described herein can be used as an accurate diagnostic tool for detecting cancer in suspicious cases by real-time testing of peripheral blood. Exemplary fabricated sensor showed selectivity of about 98% and specificity of about 96% for the presence of cancer in patients with a breast mass and no signs of other inflammatory diseases (which may activate cytokine storm). In conclusion, exemplary fabricated sensor has proper sensitivity and specificity and can be used as a diagnostic tool for detecting suspicious cases by real-time testing of peripheral blood. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 AUC for exemplary fabricated sensor and method versus clinical 
               
               
                 diagnostics results for blood samples from 160 patients 
               
               
                 Area Under the Curve 
               
               
                 Test Result Variable(s) for exemplary fabricated sensor 
               
            
           
           
               
               
               
            
               
                   
                 Asymptotic 
                 Asymptotic 99% Confidence Interval 
               
            
           
           
               
               
               
               
               
            
               
                 Area 
                 Std. Error a   
                 Sig. b   
                 Lower Bound 
                 Upper Bound 
               
               
                   
               
               
                 0.981 
                 0.012 
                 0.000 
                 0.949 
                 1.000 
               
               
                   
               
               
                 The test result variable(s): Exemplary fabricated sensor has at least one tie between the positive actual state group and the negative actual state group. Statistics may be biased. 
               
               
                   a Under the nonparametric assumption 
               
               
                   b Null hypothesis: true area = 0.5 
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Cross tabulation results for exemplary fabricated 
               
               
                 sensor, method, and system versus clinical diagnostics 
               
               
                 as a gold standard for blood samples from 160 patients 
               
               
                 Exemplary system/method versus Clinical diagnostics Crosstabulation 
               
            
           
           
               
               
               
            
               
                   
                 Clinical 
                   
               
               
                   
                 diagnostics 
               
            
           
           
               
               
               
               
            
               
                   
                 Nega- 
                 Posi- 
                   
               
               
                   
                 tive 
                 tive 
                 Total 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 Exemplary 
                 Negative 
                 Count 
                 77 
                 1 
                 78 
               
               
                 system/ 
                   
                 % within exemplary 
                 98.7% 
                 1.3% 
                 100.0% 
               
               
                 method 
                   
                 system/method 
               
               
                   
                   
                 % within Clinical 
                 97.5% 
                 1.2% 
                 48.8% 
               
               
                   
                   
                 diagnostics 
               
               
                   
                 Positive 
                 Count 
                 2 
                 80 
                 82 
               
               
                   
                   
                 % within exemplary 
                 2.4% 
                 97.6% 
                 100.0% 
               
               
                   
                   
                 system/method 
               
               
                   
                   
                 % within Clinical 
                 2.5% 
                 98.8% 
                 51.2% 
               
               
                   
                   
                 diagnostics 
                   
               
               
                 Total 
                   
                 Count 
                 79 
                 81 
                 160 
               
               
                   
                   
                 % within exemplary 
                 49.4% 
                 50.6% 
                 100.0% 
               
               
                   
                   
                 system/method 
               
               
                   
                   
                 % within Clinical 
                 100.0% 
                 100.0% 
                 100.0% 
               
               
                   
                   
                 diagnostics 
               
               
                   
               
               
                 Sensitivity = 98.80%, 
               
               
                 Specificity = 97.50%, 
               
               
                 Accuracy = 98.70%, 
               
               
                 Precision = 97.60%, 
               
               
                 Selectivity = 96.33% 
               
            
           
         
       
     
     In addition, isolation and characterization of high-density and low-density Neutrophils in comparison with ROS florescent assay was done to check validity of exemplary method described and conducted herein based on electrochemical measurement of ROS levels in blood samples utilizing exemplary fabricated probe hereinabove. Isolation and counting a ratio of LDNs versus HDNs in patients&#39; blood may reveal better a relation between sensor scores and pathological states of blood volunteers. Mature neutrophils are characterized by a polymorphonuclear nucleus, which is in general large with 2-5 lobes ‘segmented neutrophils’, whereas immature neutrophils are shown by a one-lobed curved or ring-shaped nucleus. LDNs (immature and some mature neutrophils) are more in blood of cancer patients. 
       FIG.  10 A  shows representative images of ROS/H 2 O 2  related electrochemical current peak  1002 , optical microscope images of LDNs  1004  and HDNs  1006 , fluorescent microscope images of LDNs  1008  and HDNs  1010 , Giemsa staining images of LDNs  1012  and HDNs  1014 , and total cell count  1016  of LDNs and HDNs isolated by magnetic, negative selection protocol neutrophils isolated from 5 ml blood of normal cases (N=10), consistent with one or more exemplary embodiments of the present disclosure. Furthermore,  FIG.  10 B  shows representative images of ROS/H 2 O 2  related electrochemical current peak  1020 , optical microscope images of LDNs  1022  and HDNs  1024 , fluorescent microscope images of LDNs  1026  and HDNs  1028 , Giemsa staining images of LDNs  1030  and HDNs  1032 , and total cell count  1034  of LDNs and HDNs isolated by magnetic, negative selection protocol neutrophils isolated from 5 ml blood of cancer patients (N=10), consistent with one or more exemplary embodiments of the present disclosure. A P-value less than 0.05 was considered significant. Data shows means±SEM error bars. The bar in optical microscope images and Giemsa staining images represents 100 μm. As shown in  FIGS.  10 A and  10 B , ROS peak levels recorded by exemplary method and system described herein are correlated well with an elevated ratio of LDNs/HDNs in normal and cancer patients as presented in detail in Table 4. 
     Fluorescent ROS assay may reveal a correlation between ROS/Hypoxic functions of cultured LDNs and HDNs and their recorded current peaks. As shown in  FIGS.  10 A and  10 B , ROS fluorescent intensity showed weaker expression of florescent tagged cells in patients&#39; blood with invasive and malignant cancer versus normal candidates or patients with non-cancer diseases. A direct correlation between down-regulation of ROS fluorescent images and electrochemical measured peaks was observed in all cancer blood samples. 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 Detailed information of HDN and LDN counts and measured current peaks in 
               
               
                 20 normal cases (N = 10) and cancer patients (N = 10) 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                   
                 HDN cell 
                 LDN cell 
                   
                 current 
               
               
                   
                   
                 counts in 
                 counts in 
                   
                 peak (μA) 
               
               
                 Patient 
                   
                 5 ml of 
                 5 ml of 
                 LDN/HDN 
                 for 1 ml of 
               
               
                 ID 
                 State of patients 
                 blood 
                 blood 
                 ratio 
                 blood 
               
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                 1 
                 Normal 
                 2*10 6   
                 0.5*10 6   
                 0.25 
                 1000 
               
               
                 2 
                 Normal 
                 1.5*10 6    
                 0.5*10 6   
                 0.33 
                 730 
               
               
                 3 
                 Normal 
                 2*10 6   
                 0.5*10 6   
                 0.25 
                 810 
               
               
                 4 
                 Normal 
                 2*10 6   
                     1*10 6   
                 0.5 
                 531 
               
               
                 5 
                 Cancer (IDC nuclear grade 2) 
                 2*10 6   
                 3.5*10 6   
                 1.75 
                 255 
               
               
                 6 
                 Cancer (IDC nuclear grade 2) 
                 1.5*10 6    
                     4*10 6   
                 2.67 
                 92 
               
               
                 7 
                 Cancer (IDC nuclear grade 2) 
                 1*10 6   
                     2*10 6   
                 2 
                 149 
               
               
                 8 
                 Cancer (IDC nuclear grade 3) 
                 0.5*10 6    
                 1.5*10 6   
                 3 
                 61 
               
               
                 9 
                 Cancer (IDC nuclear grade 3) 
                 0.5*10 6    
                 1.5*10 6   
                 3 
                 71 
               
               
                 10 
                 Normal 
                 1.5*10 6    
                 0.5*10 6   
                 0.33 
                 609 
               
               
                 11 
                 Normal 
                 1*10 6   
                 0.5*10 6   
                 0.5 
                 489 
               
               
                 12 
                 Normal 
                 6.5*10 6    
                 0.5*10 6   
                 0.08 
                 1085 
               
               
                 13 
                 Cancer (IDC nuclear grade 3) 
                 2*10 6   
                     2*10 6   
                 1 
                 298 
               
               
                 14 
                 Cancer (IDC nuclear grade 2) 
                 1.5*10 6    
                 3.5*10 6   
                 2.33 
                 129 
               
               
                 15 
                 Cancer (IDC nuclear grade 2) 
                 2*10 6   
                     4*10 6   
                 2 
                 202 
               
               
                 16 
                 Normal 
                 2*10 6   
                 0.5*10 6   
                 0.25 
                 997 
               
               
                 17 
                 Cancer (IDC nuclear grade 3) 
                 1*10 6   
                     3*10 6   
                 3 
                 65 
               
               
                 18 
                 Normal 
                 3*10 6   
                     1*10 6   
                 0.33 
                 654 
               
               
                 19 
                 Normal 
                 1*10 6   
                 0.5*10 6   
                 0.5 
                 515 
               
               
                 20 
                 Cancer (IDC nuclear grade 3) 
                 0.5*10 6    
                     2*10 6   
                 4 
                 41 
               
               
                   
               
            
           
         
       
     
       FIG.  10 C  shows a chart  1000  of LDN/HDN ratio versus measured current peak diagram with a fitted plot for 20 cases, including normal cases (N=10) and cancer patients (N=10), consistent with one or more exemplary embodiments of the present disclosure. It may be observed that a level of LDN/HDN ratio may be precisely determined by real-time measuring electrochemical current peak of a 1 cc blood sample drawn from a person utilizing exemplary method, system, and fabricated sensor described herein. 
     Percentage Changes of ROS Level and LDNs/HDNs Ratio: 
     Herein, percentage of changes of ROS level and LDNs/HDNs ratio for cases investigated hereinabove (reported in Table 4) was calculated according to Equations (1) and (2) herein below. 
     
       
         
           
             
               
                 
                   
                     
                       
                         ROS 
                         ⁢ 
                             
                         level 
                         ⁢ 
                             
                         changes 
                         ⁢ 
                             
                         in 
                         ⁢ 
                             
                         cancer 
                         ⁢ 
                             
                         patient 
                       
                       ’ 
                     
                     ⁢ 
                         
                     blood 
                     ⁢ 
                         
                     
                       ( 
                       % 
                       ) 
                     
                   
                   = 
                   
                     
                       
                         
                           
                             
                               - 
                               
                                 ( 
                                 
                                   
                                     average 
                                     ⁢ 
                                         
                                     blood 
                                     ⁢ 
                                         
                                     current 
                                     ⁢ 
                                         
                                     peaks 
                                     ⁢ 
                                         
                                     of 
                                     ⁢ 
                                         
                                     cancer 
                                     ⁢ 
                                         
                                     patients 
                                   
                                   - 
                                 
                               
                             
                           
                         
                         
                           
                             
                               
                                 average 
                                 ⁢ 
                                     
                                 blood 
                                 ⁢ 
                                     
                                 current 
                                 ⁢ 
                                     
                                 peaks 
                                 ⁢ 
                                     
                                 of 
                                 ⁢ 
                                     
                                 Normal 
                                 ⁢ 
                                     
                                 cadidiates 
                               
                               ) 
                             
                           
                         
                       
                       
                         average 
                         ⁢ 
                             
                         blood 
                         ⁢ 
                             
                         current 
                         ⁢ 
                             
                         peaks 
                         ⁢ 
                             
                         of 
                         ⁢ 
                             
                         Normal 
                         ⁢ 
                             
                         candidates 
                       
                     
                     × 
                     100 
                   
                 
               
               
                 
                   Equation 
                   ⁢ 
                       
                   
                     ( 
                     1 
                     ) 
                   
                 
               
             
           
         
       
     
     ROS level changes in cancer patient&#39; blood (%) according to data summarized in Table 4 using Equation (1) is calculated as follow: 
     
       
         
           
             
               
                 
                   
                     
                       
                         ROS 
                         ⁢ 
                             
                         level 
                         ⁢ 
                             
                         changes 
                         ⁢ 
                             
                         in 
                         ⁢ 
                             
                         cancer 
                         ⁢ 
                             
                         patient 
                       
                       ’ 
                     
                     ⁢ 
                         
                     blood 
                     ⁢ 
                         
                     
                       ( 
                       % 
                       ) 
                     
                   
                   = 
                   
                     
                       
                         
                           - 
                           
                             ( 
                             
                               
                                 1 
                                 ⁢ 
                                 3 
                                 ⁢ 
                                 
                                   6 
                                   . 
                                   3 
                                 
                               
                               - 
                               
                                 7 
                                 ⁢ 
                                 4 
                                 ⁢ 
                                 2 
                               
                             
                             ) 
                           
                         
                         
                           7 
                           ⁢ 
                           4 
                           ⁢ 
                           2 
                         
                       
                       × 
                       100 
                     
                     = 
                     
                       82 
                       ⁢ 
                       % 
                     
                   
                 
               
               
                 
                   Equation 
                   ⁢ 
                       
                   
                     ( 
                     2 
                     ) 
                   
                 
               
             
           
         
       
       
         
           
             
               
                 
                   LDNs 
                   / 
                   HDNs 
                   ⁢ 
                       
                   ratio 
                   ⁢ 
                       
                   changes 
                   ⁢ 
                       
                   in 
                   ⁢ 
                       
                   cancer 
                   ⁢ 
                       
                   patients 
                 
                 ’ 
               
               ⁢ 
                   
               blood 
               ⁢ 
                   
               
                 ( 
                 % 
                 ) 
               
             
             = 
             
               
                 
                   
                     
                       
                         - 
                         
                           ( 
                           
                             
                               average 
                               ⁢ 
                                   
                               
                                 LDNs 
                                 HDNs 
                               
                               ⁢ 
                                   
                               ratio 
                               ⁢ 
                                   
                               of 
                               ⁢ 
                                   
                               cancer 
                               ⁢ 
                                   
                               patients 
                             
                             - 
                           
                         
                       
                     
                   
                   
                     
                       
                         
                           average 
                           ⁢ 
                               
                           
                             LDNs 
                             HDNs 
                           
                           ⁢ 
                               
                           ratio 
                           ⁢ 
                               
                           of 
                           ⁢ 
                               
                           Normal 
                           ⁢ 
                               
                           cadidates 
                         
                         ) 
                       
                     
                   
                 
                 
                   average 
                   ⁢ 
                       
                   LDNs 
                   / 
                   HDNs 
                   ⁢ 
                       
                   ratio 
                   ⁢ 
                       
                   of 
                   ⁢ 
                       
                   Normal 
                   ⁢ 
                       
                   candidates 
                 
               
               × 
               100 
             
           
         
       
     
     LDNs/HDNs ratio changes in cancer patients&#39; blood (%) according to data summarized in Table 4 using Equation (2) is calculated as follow: 
     
       
         
           
             
               
                 
                   LDNs 
                   / 
                   HDNs 
                   ⁢ 
                       
                   ratio 
                   ⁢ 
                       
                   chanes 
                   ⁢ 
                       
                   in 
                   ⁢ 
                       
                   cancer 
                   ⁢ 
                       
                   patients 
                 
                 ’ 
               
               ⁢ 
                   
               blood 
               ⁢ 
                   
               
                 ( 
                 % 
                 ) 
               
             
             = 
             
               
                 
                   
                     ( 
                     
                       2.475 
                       - 
                       0.332 
                     
                     ) 
                   
                   0.332 
                 
                 × 
                 1 
                 ⁢ 
                 00 
               
               = 
               
                 65 
                 ⁢ 
                 % 
               
             
           
         
       
     
     A significantly reduced ROS (82%) level in peripheral blood of cancer patients measured by an exemplary fabricated electrochemical sensor, which showed a great correlation with an increased ratio of LDNs/HDNs (65%) in such patients was observed. 
     Example 3: Effect of Chemo/Radiotherapy on Patients&#39; Blood and Sensor Response 
     Table 5 shows detailed information of 20 patients with chemo/radiotherapy and measured electrochemical current peaks utilizing exemplary system, method, and fabricated sensor described hereinabove. As may be observed in Table 5, blood samples of non-treated patients with invasive tumors showed significantly lower levels of CV peaks than their blood after complete response (due to an associated oncologist&#39;s opinion) to chemo/radiotherapy. It revealed that exemplary system, method, and fabricated sensor has a capability of monitoring therapeutic effects on cancer patients by testing a 1 cc blood sample drawn from a patient. As COVID-19 may also increase Neutrophils&#39; levels in blood due to cytokine storm, which may perturb cancer-associated response of exemplary sensor and method here, RT-PCR test and clinical evaluation was done on patients to be ensured from non-COVID involvement in them. 
     
       
         
           
               
             
               
                 TABLE 5 
               
             
            
               
                   
               
               
                 Detailed information of 20 patients with chemo/radiotherapy 
               
               
                 and associated measured electrochemical current peaks. 
               
            
           
           
               
               
               
               
            
               
                   
                   
                 Therapy 
                 current peak 
               
               
                 Patient 
                   
                 (Surgery, Chemo/ 
                 (μA) for 1 ml 
               
               
                 ID 
                 Cancer type 
                 radiotherapy (session)) 
                 of blood 
               
               
                   
               
            
           
           
               
               
               
               
            
               
                 161 
                 IDC nuclear grade 3 
                 Chemo (8) and Surgery (mastectomy) 
                 1090 
               
               
                 162 
                 IDC nuclear grade 2 
                 Chemo (5) 
                 550 
               
               
                 163 
                 IDC nuclear grade 2/3 
                 Chemo (6)/Radio (30) and surgery 
                 939 
               
               
                   
                   
                 (lumpectomy) 
               
               
                 164 
                 IDC nuclear grade 3 
                 Chemo (6)/Radio (28) 
                 731 
               
               
                 165 
                 IDC nuclear grade 
                 Chemo (8) 
                 469 
               
               
                   
                 2/DCIS component 
               
               
                   
                 (20%) 
               
               
                 166 
                 IDC nuclear grade 3 
                 Chemo (6)/Radio (0) 
                 393 
               
               
                 167 
                 IDC nuclear grade 2/3 
                 Chemo (4)/Radio (0) 
                 321 
               
               
                 168 
                 IDC nuclear grade 2 
                 Chemo (5) and Surgery (mastectomy) 
                 498 
               
               
                 169 
                 IDC nuclear grade 2 
                 Chemo (8) 
                 681 
               
               
                 170 
                 IDC nuclear grade 2/3 
                 Chemo (6)/Radio (20) 
                 537 
               
               
                 171 
                 IDC nuclear grade 3 
                 Chemo (6) and Surgery (mastectomy) 
                 786 
               
               
                 172 
                 IDC nuclear grade 
                 Chemo (6) 
                 606 
               
               
                   
                 2/DCIS 
               
               
                 173 
                 IDC nuclear grade 3 
                 Chemo (8) 
                 815 
               
               
                 174 
                 IDC nuclear grade 2 
                 Surgery (lumpectomy) and radio (0) 
                 495 
               
               
                 175 
                 IDC nuclear grade 2 
                 Surgery (lumpectomy) 
                 562 
               
               
                 176 
                 IDC nuclear grade 2 
                 Surgery (lumpectomy) 
                 510 
               
               
                 177 
                 IDC nuclear grade 3 
                 Chemo (8) 
                 840 
               
               
                 178 
                 IDC nuclear grade 3 
                 Chemo (4) 
                 325 
               
               
                 179 
                 IDC nuclear grade 2 
                 Chemo (6) and Surgery (mastectomy) 
                 595 
               
               
                 180 
                 IDC nuclear grade 2/3 
                 Chemo (8) and Surgery (mastectomy) 
                 700 
               
               
                   
               
            
           
         
       
     
     Example 4: Effect of Other Diseases on Sensor Response 
     Different kinds of pediatrics sickness with non-cancer diseases and normal candidates were studied as presented in Table 1. For adult investigation, electrochemical ROS detection was also performed on non-breast cancer diseases. Moreover, blood ROS levels were recorded in some patients with hypertension, heart disease, dyslipidemia, osteoporosis, and diabetes who had no tumoral diseases.  FIG.  11    shows a chart  1100  of ROS/H 2 O 2  assisted electrochemical current peaks of blood samples of patients with non-cancer diseases (n=15), consistent with one or more exemplary embodiments of the present disclosure. As shown in  FIG.  11   , results showed peak currents higher than about 450 μA in all cases. This means that the ROS/H 2 O 2  assisted electrochemical current peaks of the blood sample in patients with non-cancer diseases are significantly different from blood current peaks of the cancer patients. ROS/H 2 O 2  assisted electrochemical current peaks in normal and non-cancer diseases are more than about 450 μA while in cancer diseases are less than about 300 μA. 
     LDNs may be increased in blood due to cancer, infection, and inflammation. One of the inflammatory diseases is COVID-19 as a dangerous viral pandemic. It is often more severe in people over 60 years old or with health conditions like lung or heart disease, diabetes, or conditions that affect their immune system. In COVID-19 patients, a significant increase of immature neutrophil numbers may be observed in acute patients compared to healthy donors/recovered patients, while the number of mature neutrophils decreased. Also, a meaningful shift in a ratio between mature and immature neutrophils may associate with a severity of viral involvement. The presence of “low density inflammatory neutrophils” may be strongly correlated with disease severity, and IL-6 levels. In addition, immature neutrophil numbers may strongly associate with IL-6 and IP-10. IL-6 and IP-10 may be consistently upregulated during cytokine storms and may be correlated with severe acute respiratory distress syndrome (ARDS). In addition to inflammatory monocytes as a source of IL-6, immature neutrophils may also be a non-negligible source of IL-6 through COVID-19 induced cytokine storm. So, an increase in number of LDNs may occur in cytokine storm stage of COVID disease. To evaluate an effect of COVID-19 as the most frequent infectious disease currently on peripheral blood ROS, exemplary system, method, and fabricated sensor was tested on blood sample of 14 patients with COVID-19 who were hospitalized in the intensive care unit (ICU). 
     Table 6 shows electrochemical ROS peak currents measured for blood samples of COVID-19 infected patients with any comorbidity. ROS/H 2 O 2  assisted current peaks for 87% of adults with COVID-19 infection were lower than about 300 μA, same as patients with breast cancer tumors. But it is worth noting that when a patient comes to a medical center for evaluation of her/his breast tumor, COVID-19 involvement is prechecked for her/him, and global vaccination drastically reduces a probability of COVID-19 involvement with cytokine storm in the people. Hence, herein candidates suspicious to have high-risk breast tumors with no trace of inflammatory diseases or pregnancy were evaluated. 
     
       
         
           
               
             
               
                 TABLE 6 
               
             
            
               
                   
               
               
                 Electrochemical ROS peak currents in COVID-19 
               
               
                 infected patients with any comorbidity. 
               
            
           
           
               
               
               
               
               
               
               
               
               
               
            
               
                 Patient 
                   
                   
                 Past disease 
                   
                   
                   
                 RT- 
                 CT- 
                 I 
               
               
                 ID 
                 Age 
                 Gender 
                 history 
                 Symptoms 
                 ESR 
                 CRP 
                 PCR 
                 Scan 
                 (μA) 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
               
               
            
               
                 1 
                 61 
                 Male 
                 Lung 
                 Dyspnoea, 
                 42 
                 24.7 
                 Pos. 
                 Pos. 
                 125 
               
               
                   
                   
                   
                 cancer/DM 
                 Unconscious 
               
               
                 2 
                 72 
                 Male 
                 Colon 
                 Myalgia or 
                 16 
                 20.3 
                 Pos. 
                 Pos. 
                 228 
               
               
                   
                   
                   
                 cancer 
                 fatigue, 
               
               
                   
                   
                   
                   
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 Lack of 
               
               
                   
                   
                   
                   
                 appetite 
               
               
                 3 
                 63 
                 Male 
                 IHD, CVA, 
                 loss of 
                 29 
                 31.3 
                 Pos. 
                 Pos. 
                 355 
               
               
                   
                   
                   
                 DVT 
                 consciousness, 
               
               
                   
                   
                   
                   
                 hypoxemia 
               
               
                 4 
                 79 
                 Male 
                 IHD, DM, 
                 Fever, 
                 24 
                 29.5 
                 Pos. 
                 Pos. 
                 149 
               
               
                   
                   
                   
                 Alzheimer&#39;s 
                 Myalgia or 
               
               
                   
                   
                   
                   
                 fatigue, loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                 5 
                 73 
                 Female 
                 PI, HLP, 
                 Fever, 
                 27 
                 21.3 
                 Pos. 
                 Pos. 
                 194 
               
               
                   
                   
                   
                 DM, HTN, 
                 Myalgia or 
               
               
                   
                   
                   
                 DLP 
                 fatigue, loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                 6 
                 48 
                 Male 
                 HLP, 
                 Fever, 
                 34 
                 28.6 
                 Pos. 
                 Pos. 
                 202 
               
               
                   
                   
                   
                 PMH, IHD, 
                 Myalgia or 
               
               
                   
                   
                   
                 DM 
                 fatigue, 
               
               
                   
                   
                   
                   
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 Chest pain 
               
               
                 7 
                 67 
                 Male 
                 DM, 
                 Fever, 
                 35 
                 20.5 
                 Pos. 
                 Pos. 
                 125 
               
               
                   
                   
                   
                 Parkinson 
                 Myalgia or 
               
               
                   
                   
                   
                   
                 fatigue, 
               
               
                   
                   
                   
                   
                 Vomit, loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                 8 
                 73 
                 Male 
                 HTN, 
                 Fever, Cough, 
                 10 
                 14 
                 Pos. 
                 Pos. 
                 157 
               
               
                   
                   
                   
                 Pneumonia 
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 Diarrhoea 
               
               
                 9 
                 58 
                 Female 
                 DM, HTN 
                 Fever, Cough, 
                 20 
                 25.8 
                 Pos. 
                 Pos. 
                 348 
               
               
                   
                   
                   
                   
                 loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                 10 
                 67 
                 Male 
                 DM, HTN, 
                 Fever, Cough, 
                 26 
                 22.5 
                 Pos. 
                 Pos. 
                 125 
               
               
                   
                   
                   
                   
                 Chest pain 
               
               
                 11 
                 62 
                 Male 
                 DM 
                 Fever, 
                 34 
                 26.5 
                 Pos. 
                 Pos. 
                 149 
               
               
                   
                   
                   
                   
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 fatigue, loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                 12 
                 59 
                 Female 
                 IHD, HTN 
                 Fever, fatigue, 
                 17 
                 20 
                 Pos. 
                 Pos. 
                 251 
               
               
                   
                   
                   
                   
                 chest pain 
               
               
                 13 
                 70 
                 Male 
                 DM, 
                 Fever, 
                 15 
                 19.3 
                 Pos. 
                 Pos. 
                 205 
               
               
                   
                   
                   
                 Parkinson 
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 Chest pain 
               
               
                 14 
                 73 
                 Female 
                 IHD, DM, 
                 Fever, 
                 32 
                 27.3 
                 Pos. 
                 Pos. 
                 188 
               
               
                   
                   
                   
                 Alzheimer&#39;s 
                 Dyspnoea, 
               
               
                   
                   
                   
                   
                 loss of 
               
               
                   
                   
                   
                   
                 consciousness 
               
               
                   
               
               
                 IHD: ischemic heart disease, CVA: Cerebrovascular accident, DVT: Deep vein thrombosis, PI: primary immunodeficiency, HLP: Hyperkeratosis lenticularis perstans, DLP: Dyslipidemia, PMH: Progressive macular hypomelanosis, DM: Diabetes mellitus, and HTN: Hypertension. 
               
            
           
         
       
     
     Furthermore, ESR and CRP (blood tests for detecting inflammation) were investigated in breast cancer patients. ROS peak levels recorded by exemplary system described here, ESR and CRP of these patients are shown in Table 7. 
     
       
         
           
               
             
               
                 TABLE 7 
               
             
            
               
                   
               
               
                 Electrochemical ROS peak currents in 
               
               
                 patients with breast cancer tumor 
               
            
           
           
               
               
               
               
               
               
               
            
               
                 Patient 
                   
                   
                   
                 ESR* 
                 CRP** 
                 I 
               
               
                 ID 
                 Age 
                 Gender 
                 Tumor type 
                 (mm/hr.) 
                 (mg/L) 
                 (μA) 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                 1 
                 39 
                 Female 
                 ILC 
                 22 
                 7 
                 118 
               
               
                 2 
                 38 
                 Female 
                 Papillary with 
                 40 
                 1.9 
                 106 
               
               
                   
                   
                   
                 Atypia 
               
               
                 3 
                 38 
                 Female 
                 IDC 
                 10 
                 2.2 
                 134 
               
               
                 4 
                 38 
                 Female 
                 DCIS 
                 20 
                 3 
                 102 
               
               
                 5 
                 54 
                 Female 
                 IDC 
                 18 
                 4 
                 96 
               
               
                 6 
                 40 
                 Female 
                 IDC 
                 34 
                 10 
                 89 
               
               
                 7 
                 55 
                 Female 
                 IDC 
                 7.3 
                 2 
                 97 
               
               
                 8 
                 46 
                 Female 
                 IDC 
                 0.5 
                 1 
                 104 
               
               
                 9 
                 41 
                 Female 
                 IDC 
                 5.4 
                 5 
                 124 
               
               
                 10 
                 43 
                 Female 
                 IDC 
                 11 
                 3 
                 128 
               
               
                 11 
                 39 
                 Female 
                 IDC 
                 14 
                 0.5 
                 171 
               
               
                 12 
                 72 
                 Female 
                 IDC 
                 19 
                 2 
                 202 
               
               
                 13 
                 39 
                 Female 
                 IDC 
                 21 
                 3 
                 123 
               
               
                 14 
                 50 
                 Female 
                 IDC 
                 41 
                 6 
                 178 
               
               
                 15 
                 42 
                 Female 
                 IDC 
                 45 
                 8 
                 147 
               
               
                   
               
               
                 *The normal range of ESR is 0-29 mm/hr for women 
               
               
                 **The normal range of CRP is less than 10 mg/L 
               
            
           
         
       
     
     Hence, patients with observable mass in their breast but asymptomatic signature about other inflammatory diseases would-be a candidate for exemplary system and method described here to detect their LDNs associated ROS levels in blood in favor of their tumor disease stage. In addition, a cytokine storm occurs when a patient has symptoms. However, there is a tumor in cancer and the suspected person who is referred for diagnosis has no symptoms in favor of inflammatory disease. 
     While the foregoing has described what are considered to be the best mode and/or other examples, it is understood that various modifications may be made therein and that the subject matter disclosed herein may be implemented in various forms and examples, and that the teachings may be applied in numerous applications, only some of which have been described herein. It is intended by the following claims to claim any and all applications, modifications and variations that fall within the true scope of the present teachings. 
     Unless otherwise stated, all measurements, values, ratings, positions, magnitudes, sizes, and other specifications that are set forth in this specification, including in the claims that follow, are approximate, not exact. They are intended to have a reasonable range that is consistent with the functions to which they relate and with what is customary in the art to which they pertain. 
     The scope of protection is limited solely by the claims that now follow. That scope is intended and should be interpreted to be as broad as is consistent with the ordinary meaning of the language that is used in the claims when interpreted in light of this specification and the prosecution history that follows and to encompass all structural and functional equivalents. Notwithstanding, none of the claims are intended to embrace subject matter that fails to satisfy the requirement of Sections 101, 102, or 103 of the Patent Act, nor should they be interpreted in such a way. Any unintended embracement of such subject matter is hereby disclaimed. 
     Except as stated immediately above, nothing that has been stated or illustrated is intended or should be interpreted to cause a dedication of any component, step, feature, object, benefit, advantage, or equivalent to the public, regardless of whether it is or is not recited in the claims. 
     It will be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein. Relational terms such as first and second and the like may be used solely to distinguish one entity or action from another without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “a” or “an” does not, without further constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element. 
     The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments. This is for purposes of streamlining the disclosure, and is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter. 
     While various embodiments have been described, the description is intended to be exemplary, rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and embodiments are possible that are within the scope of the embodiments. Although many possible combinations of features are shown in the accompanying figures and discussed in this detailed description, many other combinations of the disclosed features are possible. Any feature of any embodiment may be used in combination with or substituted for any other feature or element in any other embodiment unless specifically restricted. Therefore, it will be understood that any of the features shown and/or discussed in the present disclosure may be implemented together in any suitable combination. Accordingly, the embodiments are not to be restricted except in light of the attached claims and their equivalents. Also, various modifications and changes may be made within the scope of the attached claims.