Patent Publication Number: US-2019178832-A1

Title: Portable microbial load detection

Description:
BACKGROUND 
     The present disclosure generally relates to a portable detection system of small molecule compounds. With advancements in microprocessors, battery technology, and electronic miniaturization, come possibilities for convenient, portable medical devices with capabilities previously reserved for large laboratory based equipment. Many diseases in humans as well as domesticated animals are caused by microbes, such as fungi, bacteria, and viruses. An accurate assessment of a concentration of infectious microbe in a given patient may be beneficial for both diagnosis and treatment of disease caused by such microbes. A fast and convenient test for such concentrations of infectious microbes in patient samples may improve treatment options and prognosis. A test for small molecule compounds may be implemented to indicate the presence and/or concentration of specific microbes. 
     SUMMARY 
     The present disclosure provides a new and innovative system, methods and apparatus for portable microbial load detection. In an example, a test strip includes a calibration well associated with first, second, and third calibration traces and a sample well associated with first, second, and third test traces. A reader includes an amplifier and a processor configured to execute to detect a connection with the test strip. A drive signal is applied to the first calibration trace and the first test trace. A first voltage of the second calibration trace is measured indicating that a reagent has been added to the calibration well. A second voltage of the third calibration trace is measured over a calibration time period associated with the reagent. The reader is calibrated to the reagent on the test strip based on the second voltage. An addition of a test sample in the sample well is detected based on measuring a third voltage on the second test trace, where the first test sample includes the first reagent. A fourth voltage of the third test trace is measured over a test time period. A concentration of the compound in the test sample is calculated. A diagnosis state is reported based on the concentration of the compound. 
     Additional features and advantages of the disclosed method and apparatus are described in, and will be apparent from, the following Detailed Description and the Figures. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         FIG. 1  is a block diagram of a portable microbial load detection system according to an example of the present disclosure. 
         FIG. 2A  is block diagram of a test strip in a portable microbial load detection system according to an example of the present disclosure. 
         FIG. 2B-D  are time-lapse block diagrams of a test strip in a portable microbial load detection system during a microbial load test according to an example of the present disclosure. 
         FIG. 3  is a flowchart illustrating reader procedures in an example of portable microbial load detection according to an example of the present disclosure. 
         FIG. 4  is a flowchart illustrating operator procedures during portable microbial load detection according to an example of the present disclosure. 
         FIG. 5  is a flowchart illustrating an example of portable microbial load detection according to an example of the present disclosure. 
         FIG. 6  is a flow diagram illustrating an example system employing portable microbial load detection according to an example of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS 
     In typical medical, veterinary, or botanical diagnostic procedures, confirmation of infection by a particular microbe may result in significantly improved treatment options for a patient, whether human, animal, or plant. Typically, computing the actual microbial concentration in the patient may allow for even better dosing of medication to combat the infection. However, typically, such tests may be expensive and may be performed by large laboratory based equipment that may be unavailable at a doctor&#39;s, veterinarian&#39;s, or botanist&#39;s office or in the field anywhere where an infectious outbreak may occur. Therefore, in many typical scenarios, a test is only ordered after a patient does not respond to generic treatment options, which presents an inefficient solution for both doctor and patient, requiring extra doctor visits and disruptions to the patient&#39;s schedule. Typically, microbial load testing is standard procedure only where such testing is a vital part of a given treatment regime for a chronic condition. For example, monitoring of the concentration of virus or viral load in human immunodeficiency virus (“HIV”) positive patients is standard procedure, while testing for influenza virus may not be conducted until a follow-up visit after a patient with flu-like symptoms does not initially recover. 
     In a typical example, microbial load, especially viral load may be measured through some form of nucleic acid testing, where Deoxyribose Nucleic Acid (“DNA”) or Ribonucleic Acid (“RNA”) is extracted from a biological sample (e.g., blood, saliva, mucus, biopsy, etc.) and then a measurement of the DNA/RNA concentration of the microbe is converted into a measurement of microbial concentration. For example, known sections of microbial DNA/RNA may be amplified in a controlled manner (e.g., polymerase chain reaction) and then probes (e.g., radioactive or optical probes) may be attached to the amplified nucleic acid to be measured. In another example, a probe may be attached to unamplified DNA/RNA samples, and after removal of unbound probes, the remaining probes may instead be amplified to measurable levels. In other examples, large amounts of secondary probes may be flooded in that bind to primary probes binding DNA/RNA to reach measurable concentrations. In all of these examples, large, dedicated laboratory equipment (e.g., thermocyclers, centrifuges, nucleic acid extraction equipment, etc.) are required, along with significant hands-on preparation time in order to measure microbial load. In addition, typical nucleic acid based microbial load testing may require specialized training in techniques and equipment outside the skill set of a typical nurse or clinician, adding another potential impediment to broad deployment. 
     It is possible through various biological and/or chemical assays to cause infectious microbes to generate detectable byproducts through catalyzed reactions. In an example, a microbe in the presence of certain reagents and certain incubation conditions may generate glucose, which may be detectable through a glucose meter. In the example, the concentration of glucose measured may then be converted into a corresponding microbial load measurement. However, while glucose measurements may be useful in a sterile laboratory environment, glucose is typically present in vastly larger quantities inside of living organisms than the amounts typically generated by such microbial assays, and therefore isolating for microbial related glucose readings in a clinical environment may be impractical. In addition, typical glucose meters (e.g., for diabetic patients) lack the sensitivity to measure such low quantities of glucose, which may be produced by the biochemical assay. In an example, an alternative product may be generated by the biological and/or chemical assays, for example, a small compound such as paracetamol or an electrochemically active molecule. However, portable, clinical testing of the concentration of such small molecule compounds may be unavailable as well, due to the equipment typically required. For example, the levels of signal generated from such reactions may typically be below the threshold for background noise in a typical portal detector, such as a glucose meter for diabetic patients. 
     The present disclosure aims to address the detection and monitoring of microbial load in clinical settings, accurately and efficiently. For example, a high-sensitivity reader device of a form factor between the size of a smart phone and a laptop may be combined with specialized test strips and reagent dispensers to allow for minimally or non-invasive microbial load tests to be conducted during a typical doctor&#39;s visit. In an example, a test strip may be individually calibrated to a background noise level associated with a particular sample of catalyzing reagent and/or a background level of detectable compound in a biological sample from a patient. Precise calibration allows for detection of signal levels that may be similar in magnitude to background noise in typical detector devices. The reader and/or the test strip may then provide stimuli to drive forward the reaction generating the detectable compound, for example, through enzymes and/or a drive signal such as electricity or light. In the example, measurements of the generated detectable compound may be template matched to known control measurements and a microbial load may then be calculated. Calibration on a particular test strip and a particular aliquot of reagent allows for background noise that may affect results to be filtered out. As a result, the doctor may provide better diagnosis and better treatment options for the type of infection affecting the patient. With a highly portable form factor and power requirements low enough to be supplied by batteries or solar power, microbial load detection may be brought as needed to the patient, anywhere in the world without worrying about transportation of samples to a laboratory. A test that may typically take a three day turn around and require expedited temperature controlled shipping may be performed in 15 minutes on a reader that a doctor carries in a backpack on house calls. By using the presently disclosed system and methods, doctors may improve patient outcomes by reducing the spread of disease, better treating infectious disease, and potentially saving lives. 
       FIG. 1  is a block diagram of a portable microbial load detection system according to an example of the present disclosure. The system  100  may include a reader  140 , which may be include one or more physical processors (e.g., CPU  120 ) communicatively coupled to memory devices (e.g., MD  125 ) and input/output devices (e.g., I/O  130 ). As used herein, physical processor or processors (Central Processing Units “CPUs”)  120  refer to devices capable of executing instructions encoding arithmetic, logical, and/or I/O operations. In one illustrative example, a processor may follow Von Neumann architectural model and may include an arithmetic logic unit (ALU), a control unit, and a plurality of registers. In an example, a processor may be a single core processor which is typically capable of executing one instruction at a time (or process a single pipeline of instructions), or a multi-core processor which may simultaneously execute multiple instructions. In another example, a processor may be implemented as a single integrated circuit, two or more integrated circuits, or may be a component of a multi-chip module (e.g., in which individual microprocessor dies are included in a single integrated circuit package and hence share a single socket). A processor may also be referred to as a central processing unit (CPU). 
     As discussed herein, a memory device  125  refers to a volatile or non-volatile memory device, such as RAM, ROM, EEPROM, or any other device capable of storing data. As discussed herein, I/O device  130  refers to a device capable of providing an interface between one or more processor pins and an external device, the operation of which is based on the processor inputting and/or outputting binary data. CPU  120  may be interconnected using a variety of techniques, ranging from a point-to-point processor interconnect, to a system area network, such as an Ethernet-based network. Local connections within reader  140 , including the connections between a CPU  120  and memory device  125  and between CPU  120  and an I/O device  130  may be provided by one or more local buses of suitable architecture, for example, peripheral component interconnect (PCI). In an example, display  141  may be a visual display output interface (e.g., liquid crystal display (“LCD”)). In an example, display  141  may be an input interface (e.g., touchscreen), connected to I/O device  130 . In another example, display  141  may both be a visual output LCD and a input touch screen. In an example, a separate keyboard may be provided as an input device. 
     In an example, biomeasurement engine  144  may be software or hardware configured to take measurement values from transimpedance amplifier  145  and to compute a compound concentration based on voltage readings generated by transimpedance amplifier  145 . In an example, biomeasurement engine  144  may be implemented via any form of executable code (e.g., executable file, script, application, service, daemon). In an example, the biomeasurement engine  144  may be implemented as an application-specific integrated circuit (“ASIC”). In an example, biomeasurement engine  144  may be further configured to perform template matching to correlate detectable molecule concentrations with medical diagnosis. In an example, transimpedance amplifier  145  may be a hardware device that converts current to voltage for reader  140 . In an example, transimpedance amplifier  145  may be implemented with an operational amplifier. In some examples, reader  140  may be equipped with alternative components to transimpedance amplifier  145  for receiving readings from test strip  150 . In an example, any suitable component of sufficient sensitivity for measuring current or voltage may be substituted for transimpedance amplifier  145  (e.g., picoammeter, ammeter, voltmeter, oscilloscope, current transformer, isolation amplifier, etc.). In another example, reader  140  may measure a different input other than electrical current and/or amperage. For example, if test strip  150  is configured for a light based drive signal rather than an electrical drive signal, transimpedance amplifier  145  may be replaced with a photosensor if a photosensitive probe is used. If a radioactive probe is used, an appropriate radiation detector may also be substituted. In an example, the drive signal may be of a different type of energy than the detection device. For example, a light catalyzed reaction may be implemented with a laser for a drive signal but may still measure electrical charge, (e.g., via transimpedance amplifier  145 ) for the output of the reaction. In an example, multiple types of drive signal may be combined to create specific conditions for a given reaction, and the one or more drive signals may be modulated and/or scaled during the course of a test to progress the reaction. For example, a reaction may perform best with heating and cooling cycles (e.g., polymerase chain reaction). Another reaction may perform best with both heat and light as drive signals. In an example, transimpedance amplifier  145  receives input from test port  142 , which may be any form of suitable connection port into which test strip  150  may be connected via connector  152 . In an example, test port  142  may have separate electrical traces to different channels in transimpedance amplifier  145 , each associated with separate electrical traces in test strip  150  exposed by connector  152 . In the example with an optical or photosensitive test strip, test port  142  and its mating piece, connector  152  may be any form of suitable optical interface. In an example, test port  142  and connector  152  may be implemented with a fiber-optic connection. 
     In an example, test strip  150  may be a disposable, biologically sealed, sterile test strip with electrical traces leading to at least two wells in which samples may be placed (e.g., calibration well  160  and test well  165 ). In an example, calibration well  160  and test well  165  may be biologically isolated from each other, for example, to avoid cross contamination. In an example, reagent vial  180  may be a single use reagent container containing a suitable reagent which, when reacted with a biological sample on sample swab  190 , may generate a detectable small organic molecule. In an example, the reagent in reagent vial  180  may be in liquid form. In another example, the reagent may be reconsitutable with a suitable solvent (e.g., water, alcohol, etc.) or with a liquid biological sample (e.g., blood, mucus, tears). In an example, a solid biological sample (e.g., skin cells, biopsy sample, etc.) may be immersed in reagent vial  180 . In an example, reagent vial  180  may include a lid seal  185  which may have a one-way entrance through which sample swab  190  may be inserted. In an example, dispenser  182  may be configured to mate with calibration well  160  and/or test well  165 . In an example, test strip  150  may have a separate injection port that may mate with dispenser  182  for channeling reagent and/or sample to calibration well  160  and test well  165 . In an example, an automated fluidics system may channel reagent and/or sample to calibration well  160  and/or test well  165 . In an example, incubation of the biological sample may occur in reagent vial  180 . In another example, incubation of the biological sample may occur in a separate incubation chamber, for example, on test strip  150  or reader  140 . In an example, dispenser  182  may be configured to accurately dose injection amounts into calibration well  160  and/or test well  165 . For example, a proper amount of reagent and/or sample may be dispensed with a twist of reagent vial  180 , or a press of a button, etc. 
       FIG. 2A  is block diagram of a test strip in a portable microbial load detection system according to an example of the present disclosure. Example system  200  may be an enlarged illustration of test strip  150  from system  100 . In an example, at least three electrical traces lead from connector  152  to each of calibration well  160  and test well  165 . In some examples, a test strip may have multiple test wells each with their own respective set of electrical traces. In some examples, each well may have additional traces for additional measurements beyond three traces shown in system  200 . In an example, calibration well  160  is connected to drive voltage trace  230 , reagent detection trace  232 , and wet calibration trace  234 . In an example, test well  165  is connected to drive voltage trace  250 , sample detection trace  252 , and measurement trace  254 . In an example, each trace (e.g., drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254 ) may be constructed of any suitable conductive material. In an example, each of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254  may be insulated from each other trace. In an example, each of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254  may be wired to a separate connection device (e.g., pin) in connector  152 . In an example, each of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254  may correspond to a separate channel in transimpedance amplifier  145 . In other examples, signals from multiple traces may be multiplexed together via any suitable method, for example, where there are more traces in test strip  150  than there are channels in transimpedance amplifier  145 . 
       FIG. 2B-D  are time-lapse block diagrams of a test strip in a portable microbial load detection system during a viral load test according to an example of the present disclosure. System  201  as illustrated in  FIG. 2B  depicts the test strip  150  from system  200  after test strip  150  is plugged into test port  142  of reader  140 . In an example, reader  140  detects that test strip  150  has been plugged in. For example, reader  140  may detect a transient electrical pulse (e.g., from static electricity) indicating that test strip  150  has been plugged into test port  142 . In an example, the transient electrical pulse may be detected on any of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254 . In an example, in response to detecting that test strip  150  is plugged in, reader  140  begins sending a drive voltage through drive voltage trace  230 . In some examples, drive voltage trace  250  may begin receiving the drive voltage as well. In an example, drive voltage traces  230  and  250  may be connected to a same trace. In another example, where the drive signal is not a drive voltage, the alternative drive signal may be applied (e.g., a laser or other light source). 
       FIG. 2C  and system  202  illustrate system  201  as reagent is added to calibration well  160 . In an example, when a first drop of reagent is dispensed from dispenser  182  to calibration well  160 , the drive voltage from drive voltage trace  230  shorts to reagent detection trace  232  and/or wet calibration trace  234 . In the example, upon detection of voltage from reagent detection trace  232  by transimpedance amplifier  145 , or alternatively upon a user confirmation that calibration reagent has been added to calibration well  160 , a timer  244  is started for when a sample should be added to test well  165 . In addition, biomeasurement engine  144  may begin recording a series of voltage or current readings from transimpedance amplifier  145  and wet calibration trace  234  over a calibration window. In the example, the voltage or current from wet calibration trace  234  may then be factored into any later readings from test well  165  and measurement trace  254  to calibrate for background noise generated by, for example, manufacturing differences between tests strips or between reagent batches. In an example, if the measurements from wet calibration trace  234  are too far off from a set baseline, test strip  150  may be rejected as defective. In an example, sample swab  190  may be inserted into reagent vial  180  before the reagent is added to calibration well  160 . For example, in a slow acting reaction, introducing biological sample into the calibration well may be undetectable during the calibration time period, but may allow the wet calibration process to factor in any variations between different sample swabs. In another example, reagent may be dispensed through dispenser  182  to calibration well  160  before sample swab  190  is inserted into reagent vial  180  to ensure that only background noise from the reagent and test strip are factored in, and that any biological sample cannot affect the calibration process. For example, if the observed reaction is fast, early insertion of the biological sample may significantly skew the calibration data. In an example, drive voltage may be applied to drive voltage trace  250  after calibration is complete, for example, to detect early sample injection in test well  165 . In another example, drive voltage  250  may be activated as timer  244  elapses. 
       FIG. 2D  and system  203  illustrate system  201  where timer  244  has sounded. In an example, timer  244  alerts an operator to deposit incubated reagent/biological sample mix from reagent vial  180  to test well  165 , for example, after 15 minutes. In an example, dispensing reagent/sample mix into test well  165  shorts the drive voltage from drive trace  250  to sample detection trace  252  and measurement trace  254 . In an example, upon detecting voltage from sample detection trace  252 , biomeasurement engine  144  begins recording voltage or amperage readings from measurement trace  254  over a measurement window. In an example, any time after test strip  150  is calibrated based on wet calibration trace  234 , drive voltage trace  230  may be turned off, for example, to conserve battery power. In the example, the recorded readings from measurement trace  254  may be compared with existing known values after adjustments based on the wet calibration process in system  202 . In an example, biomeasurement engine  144  computes a microbial load value for the sample on sample swab  190  and reports a diagnosis on display  141 . 
       FIG. 3  is a flowchart illustrating reader procedures in an example of portable microbial load detection according to an example of the present disclosure. Although the example method  300  is described with reference to the flowchart illustrated in  FIG. 3 , it will be appreciated that many other methods of performing the acts associated with the method  300  may be used. For example, the order of some of the blocks may be changed, certain blocks may be combined with other blocks, and some of the blocks described are optional. The method  300  may be performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software, or a combination of both. In an example, the method is performed by reader  140 . 
     In an example, reader  140  is powered on (block  310 ). In the example, reader  140  detects the insertion of test strip  150  into test port  142 , for example, due to a transient electrical pulse (block  312 ). In an example, reader  140  feeds in a drive voltage on drive voltage trace  230  and validates whether the test strip  150  is genuine and free of defects (block  314 ). For example, the drive voltage may be measured to ensure that there is no short between any of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254 . In an example, a wiring short may be distinguishable from a short due to liquid in a well because a wiring short may be between traces that would not short to each other from a sample. In an example, if drive voltage trace  230  shorts to, for example, wet calibration trace  234  but not to reagent detection trace  232 , the test strip  150  is rejected as defective (block  316 ). Additional security measures may be present, such as an RFID for authentication between reader  140  and test strip  150 . In an example, upon successful validation of test strip  150 , a user is prompted to place sample swab  190  into reagent vial  180  (block  320 ). The user may additionally be prompted to mix per instructions on display  141  and/or to dispense reagent into calibration well  160 . In an example, reader  140  may detect liquid in calibration well  160  (block  322 ). In the example, reader  140  may detect whether a voltage of wet calibration trace  234 , now shorted to drive voltage trace  230 , is within bounds (block  324 ). In an example, if water is spilled into calibration well  160 , the conductive properties may be different from the reagent/sample mixture in reagent vial  180 . In an example, reagent vial  180  may have been previously contaminated with microbes and the detectable compound may already be present in high concentration leading to unrealistic readings. In the example, reagent vial  180  may be rejected as defective (block  326 ). In an example, biomeasurement engine  144  may determine that calibration trace  234  is measuring a voltage within calibration limits, and may calibrate reader  140  to the reagent/test strip combination (block  330 ). 
     In an example, the user is prompted via a count down to deposit reagent/sample mix into test well  265 , for example, via timer  244  on display  141  (block  334 ). Reader  144  may apply drive voltage to drive voltage trace  250  any time after test strip  150  is inserted into test port  142 . In an example, reader  140  applies drive voltage to catalyze a reaction between the biological sample and the reagent, measuring the voltage on measurement trace  254  over time (block  336 ). In an example, test well  165  and/or any of the traces connected to test well  165  (e.g., drive voltage trace  250 , sample detection trace  252 , and/or measurement trace  254 ) may be coated with a catalyst such as an enzyme that aids the reaction between the biological sample and the reagent in test well  165 . In an example, any form of catalyst or other additive for speeding up the reaction may be introduced to test well  165  (e.g., organic, inorganic, etc.), including both additives that are consumed by the reaction and additives that are unaffected by the reaction. In an example, the voltage readings from measurement trace  254  are plotted over time, and a resulting voltage curve is compared to a control waveform for an infectious disease for which reader  140  is configured to detect (block  338 ). In the example, if the voltage curve does not match the control waveform(s), reader  140  presents an error (block  340 ). In an example, the voltage curve is normalized with the control waveform(s), for example, after factoring in the reader calibration (block  350 ). In an example, compound concentration is computed from the normalized voltage curve (block  352 ). In an example, a medical diagnosis result is displayed on display  141  (block  354 ). In an example, the actual measured microbial load concentration and compound concentration may be obfuscated, with only a computed diagnosis displayed. For example, possible outputs may be infected, not infected, and inconclusive. In some examples, where a certain threshold of microbial load may be a threshold for differential treatment, such thresholding may additionally be displayed. 
       FIG. 4  is a flowchart illustrating operator procedures during portable microbial load detection according to an example of the present disclosure. Although the example method  400  is described with reference to the flowchart illustrated in  FIG. 4 , it will be appreciated that many other methods of performing the acts associated with the method  400  may be used. For example, the order of some of the blocks may be changed, certain blocks may be combined with other blocks, and some of the blocks described are optional. The method  400  may be performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software, or a combination of both. In an example, the method is performed by an operator operating reader  140 . 
     In example system  400 , an operator (e.g., medical technician, nurse, doctor, etc.) may power on reader  140  (block  410 ). The operator may then configure reader  140  for the proper disease being tested (e.g., in relation to reagent vial  180  and/or test strip  150 ) (block  415 ). For example, the reader  140  may be configured to an influenza viral load test, or an HIV viral load test, a  Staphylococcus aureus  bacterial load test, an  E. coli  bacterial load test, a  Candida  fungal load test, etc. In an example, the operator inserts test strip  150  into reader  140  (block  420 ). In an example, the operator swabs a patient for a sample (e.g., in a nostril, on the inside of the cheek, or another mucus membrane) (block  425 ). In another example, a biological sample may be obtained from an alternative source (e.g., blood, urine, stool, biopsy, etc.). In an example, the sample swab  190  is inserted into a new, sterile reagent vial  180  (block  430 ). In an example, the fresh reagent-sample mix is dispensed in calibration well  160  from reagent vial  180  (block  435 ). In the example, the operator then waits the prompted amount of time (block  440 ). The operator then dispenses the reagent-sample mix into test well  165  (block  445 ). In an example, the operator finally reads the medical diagnosis from display  141  (block  450 ). 
       FIG. 5  is a flowchart illustrating an example of portable microbial load detection according to an example of the present disclosure. Although the example method  500  is described with reference to the flowchart illustrated in  FIG. 5 , it will be appreciated that many other methods of performing the acts associated with the method  500  may be used. For example, the order of some of the blocks may be changed, certain blocks may be combined with other blocks, and some of the blocks described are optional. The method  500  may be performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software, or a combination of both. In an example, the method is performed by reader  140 . 
     The example method  500  may begin with detecting a connection with a test strip, where the test strip includes a calibration well associated with at least a first calibration trace, a second calibration trace, and a third calibration trace and at least a first sample well associated with at least a first test trace, a second test trace, and a third test trace (block  510 ). In an example, reader  140  detects a connection through test port  142  and connector  152  with test strip  150 , for example, due to measuring a transient electrical pulse from static electricity. As a result, reader  140  may begin applying a drive signal to the test strip  150 , where the drive signal is applied to the first calibration trace (e.g., drive voltage trace  230 ) and the first test trace (e.g., drive voltage trace  250 ) (block  515 ). In an example, the drive signal may be applied sequentially to drive voltage trace  230  and then to drive voltage trace  250  as needed rather than concurrently, for example, to conserve power. In an example, drive signal may be shut off to calibration well  160  any time after calibration is complete, and drive signal may be started for test well  165  any time before testing is set to occur, for example, based on timer  244 . In some examples, multiple drive signals may be implemented and may be configured to optimally catalyze a reaction. For example, certain reactions may be catalyzed by light, electricity, heat, etc. or a combination of factors. In various examples, the drive signal may be an electrical pulse, an optical pulse, or any other motive force and/or catalytic force applied to test strip  150 . In an example, multiple drive signals may be turned on sequentially or concurrently in a combination most suited to the reaction being tested. In an example, reader  140  measures a first voltage of the second calibration trace (e.g., reagent detection trace  232 ), where the first voltage indicates that a first reagent has been added to the calibration well  160  (block  520 ). In an example, adding dissolved reagent to calibration well  160  shorts drive voltage trace  230  to reagent detection trace  232 . In an example, reagent in reagent vial  180  may be in any suitable form, including liquid, gel, solid, lyophilized, etc., and may be reactive or may serve a labeling purpose (e.g., colormetric dye). In an example, reagent vial  180  may contain necessary ingredients in the form of organic precursor molecules for a reaction catalyzed in test well  165 . In an example, reagent vial  180  may contain photo or radioactive probes detectable via optical or radiation sensors rather than electrical sensors. 
     In an example, the drive voltage may be of any suitable magnitude. In a typical example, a drive voltage producing 100 nanoamps to 100 milliamps of current in drive voltage trace  230  and/or drive voltage trace  250  may be preferential depending on the underlying assay being measured. Certain reactions may perform optimally with lower or higher drive voltages. In an example, a 200 millivolt drive voltage producing around 2 milliamps of current on drive voltage traces  230  and  250  may be effective for the quantification of influenza viral load with a reaction generating paracetamol as the measured small molecule organic compound. In an example, a glucose generating reaction may produce higher yield with a 0.4 volt drive voltage than a 0.2 volt drive voltage. In an example, a staged and/or tiered drive voltage may provide better yield from the tested reaction, for example, 10 minutes at 0.4 volts, 2 minutes at 0.2 volts, then 3 minutes at 0.5 volts. In an example, an operational amplifier such as transimpedance amplifier  145  may be configured to convert current to voltage for the measurement of voltages on the various traces in test strip  150  (e.g., drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254 ). In an example, transimpedance amplifier  145  may be scaled to convert 10 nanoamps to 1 millivolt, so the transimpedance amplifier may be configured to generate readings of 1 millivolt to 1 volt. In an example, the output of the transimpedance amplifier may be filtered with a low pass filter (e.g., 8 hertz). In an example, each of drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254  is connected to a separate channel in the transimpedance amplifier  145 . In another example, at least two signals corresponding respectively to at least two of the drive voltage trace  230 , reagent detection trace  232 , wet calibration trace  234 , drive voltage trace  250 , sample detection trace  252 , and measurement trace  254  are multiplexed together in the transimpedance amplifier  145 . In an example, transimpedance amplifier  145  in a first configuration mode measures a first signal type associated with a first tested medical condition (e.g., influenza) associated with the first biological sample, and the transimpedance amplifier  145  in a second configuration mode measures a second signal type associated with a second tested medical condition (e.g., HIV, Ebola, tuberculosis, etc.) associated with a second biological sample. 
     In an example, reader  140  measures a second voltage of the third calibration trace (e.g., wet calibration trace  234 ) over a first calibration time period, where the third calibration trace is associated with the first reagent (block  525 ). In an example, the wet calibration trace  234  generates a baseline measurement factoring in the specific aliquot of reagent in reagent vial  180 , the specific electrical peculiarities of test strip  150 , and any background affecting factors from sample swab  190  and a biological sample (e.g., saliva, blood, urine, stool, etc.) collected on sample swab  190  for a calibration reading, which may be a series of voltage or amperage readings over a calibration time period. In an example, reader  140  is calibrated to the first reagent (e.g., the reagent in reagent vial  180 ) on the first test strip (e.g., test strip  150 ) based on the second voltage (block  530 ). In an example, a second reading of calibration well  160  may be taken at a later, intermediate time as a validation reading against contamination. For example, for a test that takes 15 minutes, if a 5 minute reading is already high, at least one of test strip  150 , reagent vial  180 , and reader  140  is likely defective. In some examples, an initial incubation or settling period may be taken after a sample is added to sample vial  180  before the calibration well  160  is filled. 
     In an example, reader  140  detects an addition of a first test sample (e.g., a mixture of biological sample and reagent from reagent vial  180 ) in the first sample well (e.g., test well  165 ) based on measuring a third voltage on the second test trace (e.g., sample detection trace  252 , which may be shorted to drive voltage trace  250  via the first test sample), where the first test sample includes the first reagent (block  535 ). In an example, an incubation period elapses before the first test sample is added to test well  165 , and the biological sample is in contact with the first reagent during the incubation period. In an example, a non-liquid reagent may first be dissolved with an appropriate solvent. In an example, reader  140  measures a fourth voltage of the third test trace (e.g., measurement trace  254 ) over a first test time period (block  540 ). In an example, the reagent-sample mix in test well  165  shorts drive voltage trace  250  to measurement trace  254 . In an example, a reaction between a biological sample and the reagent in reagent vial  180  generates the compound being measured by biomeasurement engine  144 . In an example, the reaction is further catalyzed by a catalyst (e.g., enzyme) in test well  165  and/or any of the traces on test strip  150 . In an example, the catalyst is also in calibration well  160  so that the catalyst may be calibrated for. For example, a sample reagent/enzyme combination may generate paracetamol when in the presence of influenza and the reaction may be sped up by the application of a electrical drive signal. In an example, a reagent/enzyme combination may generate any detectable electrochemically active molecule in the presence of the microbe being tested for. In an example, reagent/enzyme/current combinations may be customized for different microbes including viruses, bacterial, and fungi. In another example, reagent/enzyme/drive signal combinations may be customized for diagnosis of other biological disorders and/or drug monitoring. 
     In an example, reader  140  calculates a concentration of the compound in the first test sample (block  545 ). In an example, the compound being detected is glucose. In another example, the compound being detected is paracetamol. In an example, a compound less likely to be naturally occurring in the patient organism may be preferred. In an example, any organic compound generated over time based on the combination of reagent, catalyst, biological sample, and drive signal may be the detected compound. 
     In an example, biomeasurement engine  144  of reader  140  may be configured to execute to plot the fourth voltage (e.g. of measurement trace  254 ) as a sample voltage waveform, and the sample voltage waveform may be compared to one or more control waveforms (e.g., for the condition appropriate infectious agent) to determine whether the measured voltage waveform corresponds to a medical diagnosis. In an example, if the measured sample voltage waveform aligns with the control waveform, a medical diagnosis is made and reported via display  141 . In another example, if the sample voltage curve or waveform fails to align with any control waveform, an error may be displayed on display  141 . In an example, a complete failure to align with any waveform may be indicative of a defect in at least one of reagent vial  180 , test strip  150 , and reader  140 . For example, one of the control wave forms may typically be a control for a non-infected patient, so a failure to align with a baseline control may indicate some form of contamination of the assay. In an example, control waveforms may cover a broader than optimal incubation period, so that slight timing errors in the incubation period (e.g., sample being deposited in test well  165  early or late) may be accounted for by biomeasurement engine  144 . In an example, reader  140  reports a diagnosis state based on the concentration of the compound (block  550 ). In an example, the diagnosis state is reported in a graphical report, and the graphical report abstracts numerical measurements of the fourth voltage and the concentration of the small molecule. For example, for ease of use and to guard against misinterpretation, rather than displaying any raw values for compound or microbe concentration, the significance of which may differ depending on the assay, a diagnosis may be computed by biomeasurement engine  144  and displayed unambiguously. 
     In an example, reader  140  may be configured to recalibrate with a second test strip and a second reagent on the second test strip, and after recalibrating, a second test sample is measured on the second test strip. In an example, the second test sample may be for a second patient for the same microbe as the first test sample. In another example, the second test sample may be for a different microbe for the same patient or a new patient. In an example, the second reagent may be a separate aliquot of the first reagent, kept sterile and biologically isolated from the first reagent. In an example, the second reagent may be in a second sealed reagent vial. In an example, a given test strip may have multiple test and/or calibration wells. In an example, each test well and calibration well pairing may be allocated to a different assay. In an example where multiple samples are tested for the same microbial infection, the multiple samples may be treated with a common stock of reagent that is calibrated once on a multi-test well test strip. For example, a common stock of reagent may be pipette into a plurality of reagent vials with different sample swabs and also onto the calibration well of the multi-well test strip. In the example, a second sample or test well of the multi-test well strip may measure compound concentration in a second sample biologically isolated from the first sample well. In an example, reader  140  may require a firmware and/or bios update to be reconfigured for a different assay for a different infectious microbe. In the example, such updates may be delivered wirelessly. In an example, a multi-well test strip may be configured to test for different infectious agents on different wells, potentially with separate calibration wells where necessary. For example, if two infectious diseases may be tested with the same reagent, but, for example, with different enzymes in different test wells, both may potentially be tested with the same sample-reagent mix from reagent vial  180 . 
       FIG. 6  is a flow diagram illustrating an example system employing portable microbial load detection according to an example of the present disclosure. Although the examples below are described with reference to the flowchart illustrated in  FIG. 6 , it will be appreciated that many other methods of performing the acts associated with  FIG. 6  may be used. For example, the order of some of the blocks may be changed, certain blocks may be combined with other blocks, and some of the blocks described are optional. The methods may be performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software, or a combination of both. In example system  600 , a reader  140  executes portable viral load detection on a sample on a test strip  150 . 
     In an example, reader  140  is powered on and configured to test for influenza (block  610 ). In the example, test strip  150  is unpacked from sterile packaging and inserted into reader  140  (block  612 ). In an example, reader  140  detects test strip  150 &#39;s insertion, and begins applying the drive voltage to drive voltage traces  230  and  250  (block  614 ). In another example drive voltage may only be applied to drive voltage trace  230  to conserve power until the drive voltage is needed in the test well  165 . In an example, drive voltage trace  230 , and therefore calibration well  160  of test strip  150  is charged (block  616 ). In an example, reader  140  may validate an RFID on test strip  150  to ensure that test strip  150  is a genuine test strip (block  620 ). In an example, reader  140  may validate that there are no unexpected electrical readings from test strip  150  (e.g., unexpected shorts or other signals) (block  624 ). In an example, test strip  150  has sterile reagent deposited in calibration well  160  from reagent vial  180  (block  626 ). In another example, reagent vial  180  may have sample swab  190  inserted shortly prior to depositing reagent-sample mixture into calibration well  160 . In an example, the reagent triggers a short of the trigger trace (e.g., reagent detection trace  232 ) allowing reader  140  to detect that reagent has been added to test strip  150  (block  630 ). 
     In an example, reader  140  determines whether a voltage plot over time of wet calibration trace  234 &#39;s voltage measurements is within acceptable bounds (block  532 ). In an example, reader  140  is successfully calibrated to test strip  150  and reagent vial  180  (block  634 ). In an example, reader  140  prompts a user to swab the patient and to place the swab in calibrated reagent vial  180 , and then to wait for a reaction countdown timer  244  shown on display  141  (block  636 ). In some examples, the swabbing of the patient may occur before calibration. In an example, reader  140  prompts the user with countdown timer  244  for depositing reagent-sample mixture into test well  165  (block  638 ). In an example, test strip  150  has reagent-sample mix deposited in test well  165 , which may be coated with a paracetamol releasing enzyme (block  640 ). In an example, reader  140  may detect that a sample has been added to test strip  150  via a short between drive voltage trace  250  and sample detection trace  252  (block  642 ). In an example, reader  140  may continue to apply drive voltage or a separate test voltage of a different magnitude to drive the paracetamol releasing reaction in test well  165 , while measuring voltage and/or current on measurement trace  154  over time (block  644 ). In an example, drive voltage may be scaled, varied, and/or modulated based on a particular reaction in test well  165 . In an example, biomeasurement engine  144  may determine that the voltage/amperage curve/waveform measured from measurement trace  154  for test strip  150  aligns with a control waveform for paracetamol release due to the enzyme reacting with influenza virus (block  646 ). In an example, biomeasurement engine  144  may compute the measured paracetamol concentration from a normalized voltage curve generated by comparing the raw measurement data (e.g., voltage waveform) from test strip  150  with known controls (block  648 ). In an example, reader  140 , specifically biomeasurement engine  144  may compute and display a corresponding influenza viral load on display  141  (block  650 . 
     In an example, portable microbial load detection may provide an alternative to nucleic acid based microbial load testing. By enabling precise calibration on a per test strip, per reagent vial basis, portable microbial load detection enables detection of reactions generating signals that would otherwise likely be considered noise in a typical reader. In an example, portable microbial load detection may be performed without cryogenic or chemical means for nucleic acid extraction from samples, and without centrifuges and thermocyclers which may severely impact transportability and availability for microbial load testing equipment. In an example, while sterility is still crucial, portable microbial load detection may have reduced likelihood of cross contamination as compared to nucleic acid based testing. Therefore, portable microbial load detection may be flexibly brought to the patient as needed enabling better diagnosis and treatment options. 
     It will be appreciated that all of the disclosed methods and procedures described herein can be implemented using one or more computer programs or components. These components may be provided as a series of computer instructions on any conventional computer readable medium or machine readable medium, including volatile or non-volatile memory, such as RAM, ROM, flash memory, magnetic or optical disks, optical memory, or other storage media. The instructions may be provided as software or firmware, and/or may be implemented in whole or in part in hardware components such as ASICs, FPGAs, DSPs or any other similar devices. The instructions may be executed by one or more processors, which when executing the series of computer instructions, performs or facilitates the performance of all or part of the disclosed methods and procedures. 
     It should be understood that various changes and modifications to the example embodiments described herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present subject matter and without diminishing its intended advantages. It is therefore intended that such changes and modifications be covered by the appended claims.