Multi-dimensional data visualization for multiple sample quantification

Abstract

A computer-implemented method for visualizing dye interactions in multiplex biological samples is provided. The method includes receiving fluorescence emission data from each of a plurality of reaction sites. The reaction sites include at least the first, second, and third dyes. The method further includes determining intensity values for at least the first, second, and third dye channels from the fluorescence emission data from each reaction site. The method further includes displaying, on the user interface, a first set of indications corresponding to a plurality of intensity values of the fluorescence emission data of the first, second, and third dyes detected in the first, second, and third dye channels, respectively. The method further includes adjusting a label of fluorescence emission data from the reaction site by comparing the first set of indications.

Description

Background Technology

[0001] Systems for biological and biochemical reactions have been used to monitor, measure, and / or analyze such reactions in real time. These systems are commonly used in sequencing, genotyping, polymerase chain reaction (PCR), and other biochemical reactions to monitor progress and provide quantitative data.

[0002] The growing need for a greater number of reactions per test or experiment has spurred the development of instruments capable of performing a higher number of reactions simultaneously. The increasing number of sampling points in tests or experiments has led to the development of microtiter plates and other sampling formats that provide smaller sample volumes. Furthermore, technologies such as digital PCR (dPCR) have increased the demand for smaller sample volumes that can accommodate zero or even one target nucleotide sequence in all or most of a large number of test samples.

[0003] Digital PCR (dPCR) can be used to detect and quantify the concentration of rare alleles, providing absolute quantification of nucleic acid samples and measuring low-fold changes in nucleic acid concentration. Generally, increasing the number of replicates improves the accuracy and reproducibility of dPCR results.

[0004] In dPCR, a solution containing a relatively small amount of the target polynucleotide or nucleotide sequence can be subdivided into numerous small test samples, such that each sample generally either contains one molecule of the target nucleotide sequence or contains none. When the samples are subsequently thermally cycled in a PCR protocol, procedure, or experiment, samples containing the target nucleotide sequence are amplified and produce a positive detection signal, while samples not containing the target nucleotide sequence are not amplified and do not produce a detection signal. The processor uses fluorescence intensity thresholds to determine which samples are considered positive and which are considered negative.

[0005] However, in samples using multiple dyes, chemical reactions can induce non-specific amplification, posing a challenge to defining threshold fluorescence. Furthermore, the large number of data points collected from dPCR experiments is difficult to integrate and visualize in a user-friendly manner.

[0006] Two-dimensional scatter plots are typically generated for data visualization to view fluorescence intensity detection and adjust thresholds to determine positive and negative fluorescence detection calls. However, scatter plots can only visualize data from one or two dyes. They cannot observe interactions between more than two dyes or multiple dyes. When multiple targets are positively amplified, spectral interactions between dyes can cause changes in the data clusters displayed in the scatter plot or the formation of subclusters. Therefore, typical two-dimensional scatter plots cannot help users better determine positive and negative identification results, thereby improving dPCR results.

[0007] Therefore, there is a need for a data visualization method that can study spectral and chemical interactions and allows for flexible positive and negative detection in a multidimensional space. Summary of the Invention

[0008] In one exemplary embodiment, a computer-executed method is provided for visualizing dye interactions in multiple biological samples. The method includes receiving fluorescence emission data from each of a plurality of reaction sites, wherein the plurality of reaction sites includes at least a first, second, and third dye; the method further includes determining intensity values ​​for at least a first, second, and third dye channel based on the fluorescence emission data from each of the plurality of reaction sites; the method further includes displaying on a user interface a first set of indications a plurality of intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in a first dye channel; a second set of indications a second set of indications a second set of indications a second set of indications a third set of indications a third set of indications a third set of indications a third set of indications a third set of indications a fourth set of indications a fifth set of indications a sixth set of indications a fifth set of indications a sixth set of indications a seventh ...

[0009] In another exemplary embodiment, a system for visualizing dye interactions in multiple biological samples is provided. The system includes: a plurality of reaction sites, each reaction site comprising a biological sample; a detector configured to receive fluorescence emission data from the plurality of reaction sites; a processor configured to determine intensity values ​​of at least a first, second, and third dye channel based on the fluorescence emission data from each of the plurality of reaction sites; and a user interface. The user interface is configured to display a first set of indications of the plurality of intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the first dye channel; a second set of indications of the plurality of intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the second dye channel; and a third set of indications of the plurality of intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the third dye channel.

[0010] In yet another exemplary embodiment, a computer-readable medium encoded with computer-readable instructions is provided. When executed by a computer's processor, the computer-readable instructions cause the computer to perform a method for visualizing dye interactions in multiple biological samples. The method includes receiving fluorescence emission data from each of a plurality of reaction sites, wherein the plurality of reaction sites includes at least a first, second, and third dye; the method further includes determining intensity values ​​for at least a first, second, and third dye channel based on the fluorescence emission data from each of the plurality of reaction sites; the method further includes displaying on a user interface a first set of indications a plurality of intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in a first dye channel; a second set of indications a second set of indications a second set of indications a second set of indications a third set of indications a third set of indications a third set of indications a third set of indications a third set of indications a fourth set of indications a fifth set of indications a sixth set of indications a seventh ... Attached Figure Description

[0011] Figure 1 shows a flowchart of a method for generating multidimensional data visualizations according to various embodiments described herein.

[0012] Figure 2 illustrates an exemplary computing system that can implement the various embodiments described herein.

[0013] Figure 3 is a block diagram illustrating a polymerase chain reaction (PCR) instrument, on which embodiments of the present invention can be implemented.

[0014] Figure 4 illustrates an exemplary optical system that can be used to image a chip according to an embodiment of this teaching.

[0015] Figure 5 shows a chip containing reaction sites from which data is collected and displayed according to various embodiments described herein.

[0016] Figure 6A Figures 6 and 6B illustrate data visualizations of fluorescence intensity at multiple reaction sites obtained according to the various embodiments described herein.

[0017] Figure 7 illustrates a two-dimensional scatter plot data visualization according to the various embodiments described herein.

[0018] Figure 8A , 8B Figures 8C and 8D illustrate data visualizations of fluorescence intensity at multiple reaction sites obtained according to the various embodiments described herein.

[0019] Figure 9 illustrates a two-dimensional scatter plot data visualization according to the various embodiments described herein.

[0020] Figure 10 illustrates a two-dimensional scatter plot data visualization according to various embodiments described herein.

[0021] Figure 11 illustrates a multidimensional data visualization according to the various embodiments described herein.

[0022] Figure 12 illustrates a multidimensional data visualization according to the various embodiments described herein.

[0023] Figure 13 illustrates the user interface according to various embodiments described herein.

[0024] Figure 14 illustrates the user interface according to various embodiments described herein.

[0025] Figure 15A illustrates a two-dimensional scatter plot data visualization according to various embodiments described herein.

[0026] Figure 15B shows a multidimensional data visualization corresponding to Figure 15A according to the various embodiments described herein.

[0027] Figure 16 illustrates the user interface selection menu according to various embodiments described herein.

[0028] Figure 17A Figures 17B and 17B illustrate user interface tools according to various embodiments described herein.

[0029] Figure 18 illustrates a user interface for visualizing two-dimensional scatter plot data according to various embodiments described herein.

[0030] Figure 19 illustrates a two-dimensional scatter plot data visualization according to various embodiments described herein.

[0031] Figure 20 illustrates multidimensional data visualizations according to various embodiments described herein.

[0032] Figure 21 shows a visualization of two-dimensional scatter plot data obtained according to the various embodiments described herein.

[0033] Figure 22 illustrates a multidimensional data visualization according to the various embodiments described herein.

[0034] Figure 23 illustrates a two-dimensional scatter plot data visualization according to the various embodiments described herein.

[0035] Figure 24 illustrates a multidimensional data visualization according to the various embodiments described herein.

[0036] Figure 25 illustrates a visualization of two-dimensional scatter plot data obtained according to the various embodiments described herein.

[0037] Figure 26 illustrates a multidimensional data visualization according to the various embodiments described herein.

[0038] Detailed description

[0039] To provide a more thorough understanding of the invention, the following description sets forth many specific details, such as specific configurations, parameters, instances, etc. However, it should be understood that such description is not intended to be a limitation on the scope of the invention, but rather to provide a better description of exemplary embodiments.

[0040] As mentioned above, biological analysis typically involves multiple repeated measurements to improve accuracy. Understanding the massive amounts of data received and how to use that data to determine accurate results is a challenging task. Therefore, data visualization is needed to help users understand the data and make adjustments to generate better results.

[0041] For example, oncology assays often exhibit chemical crosstalk or nonspecific binding between repeated samples, making it difficult to determine whether a reaction site is considered dye-fluorescently positive. Establishing a single intensity threshold for positive or negative identification may not yield more accurate results.

[0042] Furthermore, if multiple target dyes are used in the assay, the interactions between the dyes cannot be determined. Previously used two-dimensional data visualizations could not display the full picture of interactions between three, four, or five dyes. Multiple two-dimensional views need to be combined to gain a comprehensive understanding of what is happening.

[0043] Therefore, according to the embodiments described herein, there is a need to generate multidimensional data visualizations for viewing multiple data sets in order to generate better and more accurate results from bioassays.

[0044] The embodiments described herein are particularly suitable for digital PCR (dPCR). In digital PCR, a solution containing a relatively small amount of target polynucleotide or nucleotide sequence can be subdivided into a large number of small test samples, such that each sample generally contains one molecule of the target nucleotide sequence or none at all. When the samples are subsequently thermally cycled in a PCR protocol, procedure, or experiment, samples containing the target nucleotide sequence are amplified and produce a positive detection signal, while samples not containing the target nucleotide sequence are not amplified and do not produce a detection signal. Using Poisson statistics, the number of target nucleotide sequences in the original solution can be correlated with the number of samples that produce a positive detection signal.

[0045] However, for typical dPCR protocols, procedures, or experiments, it is advantageous to divide the initial sample solution into tens or hundreds of thousands of test samples in a simple and economical manner, each test sample having a volume of a few nanoliters, one nanoliter, about one nanoliter, or less than one nanoliter. Because the number of target nucleotide sequences may be extremely small, in such cases it is also crucial to ensure that the entire contents of the initial solution are fully accounted for and contained across multiple reaction sites.

[0046] In various embodiments, the apparatuses, instruments, systems, and methods described herein can be used to detect one or more types of biological components of interest. These biological components of interest may include, but are not limited to, DNA sequences, RNA sequences, genes, oligonucleotides, or cells (e.g., circulating tumor cells). In various embodiments, such biological components can be used in conjunction with various PCR, qPCR, and / or dPCR methods or systems in applications such as: fetal diagnostics, multiplex dPCR, viral detection and quantitative standards, genotyping, sequencing validation, mutation detection, transgenic organism detection, rare allele detection, and / or copy number changes.

[0047] Figure 1 illustrates a flowchart of method 100 according to various embodiments described herein, used to generate multidimensional data visualization to visualize dye interactions in multiple biological samples. Step 102: Receive fluorescence emission data from each of a plurality of reaction sites, wherein the plurality of reaction sites includes at least a first, second, and third dye. An optical system, such as the optical system described with reference to FIG4, is used to detect the fluorescence emission of the reaction sites. Multiplex analysis may use more than two dyes. According to various embodiments, three, four, five, or more dyes may be used. In step 104, intensity values ​​of at least the first, second, and third dye channels are determined based on the fluorescence emission data from each of the plurality of reaction sites;

[0048] Method 100 further includes step 106, wherein a first set of indications is displayed on a user interface, showing a plurality of intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the first dye channel. According to embodiments of the teachings, the indications may include colors, shapes, colored shapes, labels, or patterned lines, etc. According to various embodiments, the indications are visual indicators that allow a user to differentiate datasets. For example, a single color may be used to display data initially identified as fluorescently positive. The indication of multiple intensity values ​​includes a line connecting the intensity values ​​to the next intensity value in the next dye channel. According to various embodiments, connecting intensity values ​​with lines helps to show variations in the emission data of the same data in different dye channels. The indication of multiple intensity values ​​can be viewed as a data band across dye channels. Variations in the data bands between channels provide valuable information to the user that would not be understood by a user using only a two-dimensional scatter plot data visualization.

[0049] The user interface displays the intensity data of fluorescence emission, including data from the three dyes used in the assay and detected in the first dye channel. This allows for comparison of fluorescence intensity differences between different categories of data. Fluorescence caused by crosstalk or spectral interactions may be more easily observed and can be adjusted to affect the assay results. For example, the first dye channel might be FAM.

[0050] Similarly, in step 108, a second set of indications of multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the second dye channel is displayed on the user interface. According to the example, the second dye channel may be VIC.

[0051] Similarly, in step 110, a third set of indications of multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the third dye channel is displayed on the user interface. According to the example, the third dye channel might be ABY.

[0052] Method 100 further includes a step 112 of adjusting the labeling of fluorescence emission data from the reaction site by comparing a first set of indicators. The labeling may be for a FAM-positive detection, but after reviewing the multidimensional data visualization, based on the various embodiments described herein, it may be determined that the detected fluorescence is likely due to spectral interactions, and the labeling is adjusted to a FAM-negative detection. Adjusting the label may result in different data visualizations generated by this assay, leading to more accurate and different visualizations. Furthermore, a final result of the assay (e.g., concentration) may be generated and improved based on more accurate identification data.

[0053] For example, changing the labels in a multidimensional data visualization might generate a new or improved two-dimensional scatter plot. The scatter plot might include adjusted negative or positive identification, now producing more accurate results. Similarly, changes to the two-dimensional scatter plot can also lead to changes in the multidimensional data visualization.

[0054] Those skilled in the art will recognize that the operation of various embodiments can be implemented using hardware, software, firmware, or, where appropriate, combinations thereof. For example, some processing can be performed using a processor or other digital circuitry under the control of software, firmware, or hardwired logic. (The term "logic" herein refers to fixed hardware, programmable logic, and / or suitable combinations thereof, as is well known to those skilled in the art, for performing the described functions.) Software and firmware can be stored on a computer-readable medium. Other processes can be implemented using analog circuitry, as is known to those of ordinary skill in the art. Furthermore, storage devices or other storage devices and communication components may be employed in embodiments of the invention.

[0055] Figure 2 is a block diagram of a computing system 200 that can be used to perform processing functions according to various embodiments, on which an embodiment of a thermal cycler system (Figure 2) can be used. The computing system 200 may include one or more processors, such as processor 204. Processor 204 may be implemented using a general-purpose or special-purpose processing engine (such as a microprocessor, controller, or other control logic). In this example, processor 204 is connected to bus 202 or other communication medium.

[0056] In addition, it should be understood that Figure 2 The computing system 200 can take the form of any of several forms, such as rack-mounted computers, mainframes, supercomputers, servers, clients, desktop computers, laptop computers, tablet computers, handheld computing devices (e.g., PDAs, cellular phones, smartphones, PDAs, etc.), cluster grids, netbooks, embedded systems, or any other type of dedicated or general-purpose computing device that may be necessary or suitable for a given application or environment. Additionally, the computing system 200 may include a conventional network system comprising a client / server environment and one or more database servers, or integrated with a LIS / LIMS infrastructure. Various conventional network systems, including local area networks (LANs) or wide area networks (WANs), and incorporating wireless and / or wired components, are known in the art. Furthermore, client / server environments, database servers, and networks are all well documented in the art.

[0057] The computing system 200 may include a bus 202 or other communication mechanism for conveying information, and a processor 204 coupled to the bus 202 for processing information.

[0058] The computing system 200 also includes a memory 206, which may be random access memory (RAM) or other dynamic memory, coupled to the bus 202 to store instructions to be executed by the processor 204. The memory 206 can also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor 204. The computing system 200 further includes a read-only memory (ROM) 208 or other static storage device coupled to the bus 202 for storing static information and instructions for the processor 204.

[0059] The computing system 200 may also include a storage device 210, such as a hard disk, optical disk, or solid-state drive (SSD), which is provided and coupled to the bus 202 for storing information and instructions. The storage device 210 may include a media drive and a removable storage interface. The media drive may include a drive or other mechanism for supporting fixed or removable storage media, such as a hard disk drive, floppy disk drive, magnetic tape drive, optical disk drive, CD or DVD drive (R or RW), flash drive, or other removable or fixed media drive. As illustrated in these examples, the storage media may include computer-readable storage media in which specific computer software, instructions, or data are stored.

[0060] In an alternative embodiment, storage device 210 may include other similar tools for allowing computer programs or other instructions or data to be loaded into computing system 200. Such tools may include, for example, removable storage units and interfaces (e.g., program cassettes and cassette interfaces), removable memory (e.g., flash memory or other removable memory modules), and memory slots, as well as other removable storage units and interfaces that allow software and data to be transferred from storage device 210 to computing system 200.

[0061] The computing system 200 may also include a communication interface 218. The communication interface 218 allows software and data to be transferred between the computing system 200 and external devices. Examples of the communication interface 218 may include a modem, a network interface (e.g., Ethernet or other NIC cards), a communication port (e.g., a USB port, an RS-232C serial port), a PCMCIA slot and card, Bluetooth, etc. Software and data transmitted via the communication interface 218 may be in the form of electronic, electromagnetic, optical, or other signals that can be received by the communication interface 218. These signals may be transmitted and received via channels through the communication interface 218, such as wireless media, wires or cables, optical fibers, or other communication media. Examples of channels include telephone lines, cellular telephone links, RF links, network interfaces, local area networks (LANs) or wide area networks (WANs), and other communication channels.

[0062] The computing system 200 may be coupled to a display 212, such as a cathode ray tube (CRT) or liquid crystal display (LCD), via a bus 202 for displaying information to a computer user. An input device 214, including alphanumeric and other keypads, is coupled to the bus 202 for transmitting information and command selections to the processor 204, for example. The input device may also be a display configured with touchscreen input capabilities, such as an LCD. Another type of user input device is a cursor controller 216, such as a mouse, trackball, or arrow keys, for transmitting directional information and command selections to the processor 204 and for controlling cursor movement on the display 212. This input device typically has two degrees of freedom on two axes (a first axis (e.g., x) and a second axis (e.g., y)), allowing the device to specify a position in a plane. The computing system 200 provides data processing and provides a confidence level regarding such data. Consistent with certain embodiments of the teachings of this invention, the computing system 200 provides data processing and confidence values ​​in response to the processor 204 executing one or more sequences of one or more instructions contained in memory 206. Such instructions can be read into memory 206 from another computer-readable medium (e.g., storage device 210). Execution of the instruction sequence contained in memory 206 enables processor 204 to perform the processing state described herein. Alternatively, hard-wired circuitry can be used in place of or in combination with software instructions to implement the embodiments taught in this invention. Therefore, implementations of the embodiments taught in this invention are not limited to any particular combination of hardware circuitry and software.

[0063] As used herein, the terms "computer-readable medium" and "computer program product" generally refer to any medium relating to providing processor 204 with one or more sequences or instructions for execution. Such instructions, generally referred to as "computer program code" (which may be grouped in the form of a computer program or other groups), when executed, cause computing system 200 to perform features or functions of embodiments of the present invention. These and other forms of computer-readable media can take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, solid-state drives, optical disks, or magnetic disks, such as storage device 210. Volatile media include dynamic memory, such as memory 206. Transmission media include coaxial cables, copper wires, and optical fibers, including conductors including bus 202.

[0064] Common forms of computer-readable media include, for example, floppy disks, floppy disks, hard disks, magnetic tapes or any other magnetic media, CD-ROMs, any other optical media, punched cards, paper tapes, any other physical media with a perforated pattern, RAM, PROMs and EPROMs, FLASH-EEPROMs, any other memory chips or cassettes, carrier waves as described below, or any other media from which a computer may read.

[0065] Various forms of computer-readable media can be used to load one or more sequences of one or more instructions to processor 204 for execution. For example, the instructions may first be carried on the disk of a remote computer. The remote computer may load the instructions into its dynamic memory and transmit the instructions over a telephone line using a modem. A modem local to computing system 200 may receive data over the telephone line and convert the data into an infrared signal using an infrared transmitter. An infrared detector coupled to bus 202 may receive the data carried in the infrared signal and place the data on bus 202. Bus 202 loads the data to memory 206, from which processor 204 retrieves and executes the instructions. The instructions received by memory 206 may optionally be stored on storage device 210 before or after execution by processor 204.

[0066] It should be understood that, for clarity, embodiments of the invention have been described above with reference to different functional units and processors. However, it will be apparent that any suitable functional distribution among different functional units, processors, or domains can be used without departing from the invention. For example, the illustrated functions that would be implemented by separate processors or controllers can be implemented by the same processor or controller. Therefore, references to specific functional units should be considered only as references to appropriate means for providing the described functions, and not as indications of a strict logical or physical structure or organization.

[0067] In the various embodiments, the devices, instruments, systems, and methods described herein can be used to detect one or more types of biological components of interest. These biological components of interest can be any suitable biological target, including but not limited to DNA sequences (including cell-free DNA), RNA sequences, genes, oligonucleotides, molecules, proteins, biomarkers, cells (e.g., circulating tumor cells), or any other suitable target biomolecule.

[0068] In various embodiments, such biological components can be used in conjunction with various PCR, qPCR, and / or dPCR methods or systems in applications such as fetal diagnostics, multiplex dPCR, viral detection and quantification standards, genotyping, sequencing validation, mutation detection, transgenic organism detection, rare allele detection, and / or copy number changes. Embodiments of the present invention generally relate to apparatus, instruments, systems, and methods for monitoring or measuring biological responses in large volumes of small samples. As used herein, a sample may be referred to, for example, as a sample volume or a reaction volume.

[0069] While generally applicable to quantitative polymerase chain reaction (qPCR) in which large numbers of samples are processed, it should be recognized that any suitable PCR method may be used according to the various embodiments described herein. Suitable PCR methods include, but are not limited to, digital PCR, allele-specific PCR, asymmetric PCR, ligation-mediated PCR, multiplex PCR, nested PCR, qPCR, genome walking, and bridging PCR.

[0070] for Figure 3 In an embodiment of the PCR instrument 300, the control system 320 can be used to control the functions of the detection system, heating cap, and heater module components. The control system 320 can... Figure 3 The user interface 322 of the PCR instrument 300 is accessible to the end user. Furthermore, as depicted in Figure 2, the computing system 200 can be used to control... Figure 3 The functions of the PCR instrument 300 and its user interface. Additionally, Figure 2 The computing system 200 can provide data processing, display, and report preparation functions. All such instrument control functions may be local to the PCR instrument, or the computing system 200 shown in Figure 2 may provide some or all of the control, analysis, and reporting functions remotely, as will be discussed in more detail later. Instrument control functions are available on the instrument and can be accessed via a graphical user interface (GUI). Furthermore, in various embodiments, data analysis controls may be provided on the instrument and accessed via a GUI. In various embodiments, data analysis of system results can be performed at a local computer system connected to the instrument. In other embodiments, data analysis functions may be accessible to a user via a network. According to various embodiments, data from the system performing biological reactions may be stored on a server system accessible to the user via a network.

[0071] As mentioned above, the instruments that can be used according to various embodiments are (but are not limited to) polymerase chain reaction (PCR) instruments. Figure 3This is a block diagram illustrating a PCR instrument 300 on which embodiments of the teachings of this invention can be implemented. The PCR instrument 300 may include a heating cap 310 placed on a plurality of samples 312 contained in a sample support device (not shown). In various embodiments, the sample support device may be a chip, glass, or plastic slide having multiple reaction sites with a cover between the reaction sites and the heating cap 310. Examples of sample support devices may include, but are not limited to, chips, multiwell plates (e.g., standard 96-well microplates, 384-well plates, or microcards) or substantially planar carriers (such as glass or plastic slides) according to embodiments of this teaching. In various embodiments of the sample support device, the reaction sites may include depressions, indentations, ridges, and combinations thereof, forming a regular or irregular array pattern on a substrate surface.

[0072] Various embodiments of the PCR instrument include a sample block 314, elements 316 for heating and cooling, a heat exchanger 318, a control system 320, and a user interface 322. Various embodiments of the thermal cycler module assembly according to the teachings of the present invention include components 314-318 of the PCR instrument 300 of FIG3.

[0073] According to other embodiments of this teaching, the thermal circulator module integrates thermoelectric devices to ensure sufficiently uniform heat transfer throughout the module.

[0074] As described above, target detection can include, for example, fluorescence detection, positive or negative ion detection, pH detection, voltage detection, or current detection. Therefore, according to the various embodiments described herein, the detection system can include, for example, an optical system, an electrical detection system, an ion detection system, or a pH detection system. According to various embodiments, the detection system can be integrated into a chip.

[0075] See Figure 4 As described above, system 400 can be used for optical observation, inspection, detection, or measurement of one or more targets contained in a reaction site. The reaction site may be included in chip 408, which may be contained in a carrier. According to various embodiments, chip 408 may be chip 500 (…). Figure 5 System 400 includes an optical head or system 402. System 400 may also include a controller, computer, or processor 404 configured to, for example, operate various components of optical system 402 or acquire and / or process data provided by system 400. For example, processor 404 may be used to acquire and / or process optical data provided by one or more photodetectors of optical system 402. In other embodiments, processor 404 may transmit data to one or more computing systems for further processing. In some embodiments, data may be transmitted from processor 404 to computing systems via a network.

[0076] In some embodiments, system 400 further includes a temperature control system 406, including, for example, a thermal cycler configured to perform PCR programs or protocols on at least some samples contained in chip 408. Systems 402 and 406 may be combined or coupled together to form a single unit, for example, to perform qPCR and / or dPCR programs or protocols on at least some samples contained in chip 408. In such embodiments, computer 404 may be used to control system 402 and 406 and / or collect or process data provided or obtained by one or both of systems 402 and 406. In other embodiments, system 402 and system 406 may be separate units.

[0077] In some embodiments, the optical system 402 includes a light source 410 and an associated excitation optics 412 configured to illuminate at least some samples contained in the reaction sites of the chip 408. The excitation optics 412 may include one or more lenses 414 and / or one or more filters 416 for modulating the light directed toward the sample. The optical system 402 may also include a photodetector 420 and an associated emission optics 422 configured to receive optical data emitted by at least some of the samples contained in the reaction sites of the chip 408. For example, when the system 400 is configured to perform qPCR and / or dPCR procedures, the sample may contain a fluorescent dye that provides a fluorescence signal that varies depending on the amount of target nucleotide sequence contained in each well of the chip 408. The excitation optics 422 may include one or more lenses 424 and / or one or more filters 426 for modulating the light directed toward the sample.

[0078] According to various embodiments, the optical system 402 may have a focal length of 15mm and a working distance of 60mm, wherein the working distance is the distance from the chip to the camera lens. Furthermore, in various embodiments, the overall system F-number is less than or equal to 3.

[0079] In the embodiment shown in Figure 4, excitation / emission optical systems 412 and 422 both include one or more common optical elements. For example, excitation / emission optical systems 412 and 422 both include a beam splitter 430 that reflects the excitation light and transmits the emitted light from the sample to the photodetector 420. In some embodiments, excitation / emission optical systems 412 and 422 both include a field mirror (not shown) disposed between the beam splitter 430 and the chip 408, which can be used to improve optical performance, such as achieving more uniform illumination and detection for the excitation light illumination and emission light readout of the sample within the chip 408. In some embodiments, such as where uniform illumination is less important (e.g., some dPCR applications), the common field mirror can be omitted, as in the embodiment shown in Figure 4. Omitting the field mirror helps reduce the size and complexity of the optical system 402.

[0080] As described below, according to the various embodiments described herein, the reaction site may include, but is not limited to, through-holes, holes, notches, spots, pits, sample holding areas, and reaction chambers.

[0081] Furthermore, as used herein, thermal cycling may include the use of, for example, thermal cyclers, isothermal amplification, thermal rule, infrared-mediated thermal cycling, or hemolytic enzyme-dependent amplification. In some embodiments, the chip may be integrated with a built-in heating element. In various embodiments, the chip may be integrated with a semiconductor.

[0082] According to various embodiments, the detection of the target may include, but is not limited to: fluorescence detection, positive and negative ion detection, pH detection, voltage detection or current detection, and these detection methods may be used alone or in combination.

[0083] refer to Figure 5 In some embodiments taught in this invention, chip 500 includes a substrate 502 and a plurality of reaction sites. Chip 500 may also be referred to as, for example, an object, device, array, wafer, or platen.

[0084] According to various embodiments of the present invention, the reaction site may be, but is not limited to, a hole, recess, notch, spot, reaction chamber, sample holding area, or through-hole located in the substrate 502. The reaction site may be any structure that allows a sample to be independent of other samples located on the substrate. The substrate 502 includes a first pore surface 510 and an opposing second pore surface 512.

[0085] The reaction site 504 is configured to provide sufficient surface tension through capillary action to immobilize the corresponding liquid sample containing the biological sample to be processed or tested.

[0086] The substrate 502 can be a flat plate or include any form suitable for a particular application or design. The substrate can be wholly or partially comprised of any of the various materials known in manufacturing techniques, including, but not limited to, metals, glass, ceramics, silicon, etc. Alternatively or additionally, the substrate 502 can include polymeric materials such as acrylates, styrene-based materials, polyethylene, polycarbonate, and polypropylene. The substrate 502 and the reaction site 504 can be formed by one or more of machining, injection molding, hot pressing, laser drilling, photolithography, etc.

[0087] Figure 6A Figures 600 and 602 illustrate data visualizations according to various embodiments described herein, which can be generated and displayed on a user interface to show which reaction sites detected fluorescence emission in a dual reaction (using two dyes). In data visualization 600 (Figure 6A), the intensity of FAM dye detection is displayed on the y-axis, and the reaction site index is displayed on the x-axis. Referring to Figure 6B, in data visualization 602, the y-axis represents the intensity of VIC dye detection, and the x-axis represents the reaction site index. Both data visualizations 600 and 602 clearly show that some fluorescence emission was detected at multiple reaction sites. The indications of intensity values ​​604 (Figure 6A) and 608 (Figure 6B) indicate that fluorescence emission was detected, which can be determined as positive for their respective corresponding dye fluorescence. Similarly, the indications of intensity values ​​606 (Figure 6A) and 610 (Figure 6B) indicate that fluorescence emission was not detected, which can be determined as negative for their respective corresponding dye fluorescence. However, outlier data points were observed for intensity values ​​of 604, 606, 608, and 610, and an intensity threshold for simultaneously determining positivity for both FAM and VIC should be established. Furthermore, as mentioned above, spectral interactions between dyes may affect the threshold determination.

[0088] Referring to Figure 7, the generated two-dimensional scatter plot data visualization, showing a comparison of VIC and FAM intensities, reveals multiple data clusters. Some clusters show negative fluorescence emission, some show positive FAM fluorescence emission, and some show positive VIC fluorescence emission. Cluster 702 appears to be negative fluorescence, cluster 704 appears to be FAM positive, cluster 706 appears to be VIC positive, and cluster 708 may be positive for both FAM and VIC. However, other sub-clusters and data points cannot be definitively identified as positive, which may be due to spectral interactions. Furthermore, data clusters showing positive or negative fluorescence may be affected by spectral crosstalk, which is difficult to determine from the two-dimensional scatter plot data visualization.

[0089] In another example, referring to Figures 8A, 8B, 8C, and 8D, data from a quadruple reaction (using four dyes) are shown. Curves 800 (Figure 8A), 802 (Figure 8B), 804 (Figure 8C), and 806 (Figure 8D) show the detection of FAM, VIC, ABY, and JUN dyes. Similar to Figures 6A and 6B, some reaction sites show obvious positive fluorescence, but others are less defined. Figure 802 even shows two distinct VIC fluorescence detection bands.

[0090] Visualize the comparison of the two dyes by observing the same data in the two-dimensional scatter plots in Figures 9 and 10. Figure 900 shows the contrast between the fluorescence intensity of FAM and VIC. For VIC, cluster 902 is labeled as negative and cluster 906 as positive. However, it is unclear whether cluster 904 is positive or negative.

[0091] Therefore, according to the embodiments described herein, there is a need to allow for flexible cluster identification data visualization in a multidimensional space so that users can better study spectral and chemical reactions.

[0092] Figure 11 illustrates a multidimensional data visualization 1100 according to various embodiments described herein. The fluorescence emission intensity values ​​for each dye channel are plotted in the multidimensional data visualization 1100 for comparison and to more easily identify and interpret spectral interference. Fluorescence emission intensity is displayed on the y-axis 1112. Data for each optical dye channel is plotted. Axis 1102 shows fluorescence detection in the FAM channel. Axis 1104 shows fluorescence emission detection in the VIC channel. Axis 1106 shows fluorescence emission detection in the ABY channel. Axis 1108 shows fluorescence emission detection in the JUN channel. Axis 1110 shows fluorescence emission detection in the ROX channel. Data points in each dye channel are connected by lines to better show the intensity value variations detected in each dye channel. Thus, visualization is achieved based on the intensity values ​​detected in each dye channel according to fluorescence emission data (including information on all dyes used).

[0093] Referring to Figure 9, data cluster 906 corresponds to the indication of intensity value 1114. Data cluster 904 corresponds to the indication of intensity value 1116. Data cluster 902 corresponds to the indication of intensity value 1118.

[0094] Axis 1104, which displays the intensity values ​​detected in the VIC channel, indicates that some data 1116 may have been affected by true positive JUN detection, as seen on the JUN axis 1108. The processor or user can then determine that the fluorescence emission data 1116 from multiple reaction sites did not show a VIC positive result due to spectral interference from high-intensity JUN fluorescence. The user or processor can then select the data identified as non-positive for VIC fluorescence based on the multidimensional data visualization 1100. Then, based on the information determined in the multidimensional data visualization 1100, the labels of the corresponding data in the two-dimensional scatter plot data visualization 900 are changed to positive or negative.

[0095] Figure 12 illustrates another exemplary multidimensional data visualization 1200, based on the various embodiments described herein. Referring back to Figure 10, the multidimensional data visualization 1200 corresponds to the two-dimensional scatter plot data visualization 1000.

[0096] Axis 1202 shows fluorescence detection in the FAM channel. Axis 1204 shows fluorescence emission detection in the VIC channel. Axis 1206 shows fluorescence emission detection in the ABY channel. Axis 1208 shows fluorescence emission detection in the JUN channel. Axis 1210 shows fluorescence emission detection in the ROX channel.

[0097] Data cluster 1002 corresponds to the indication of intensity value 1218. Data cluster 1004 corresponds to the indication of intensity value 1214. Data cluster 1006 corresponds to the indication of intensity value 1216.

[0098] Data cluster 1002 has a negative fluorescent label and appears to be generally insignificant / low-intensity in the multidimensional data visualization 1200, as indicated by intensity value 1218. Intensity value 1218 indicates that the negative labeling appears correct. Data cluster 1004 is labeled as positive for ABY and JUN dyes, as indicated by intensity value 1216. Intensity value 1216 appears to indicate that the positive labeling is correct. Data cluster 1004 appears negative in the 2D scatter plot data visualization 1200, but appears as a separate cluster from data cluster 1002. However, looking at the corresponding intensity value 1214, the user might find spectral crosstalk from VIC in the ABY channel. The high intensity fluorescence of VIC causes crosstalk in the ABY channel. Multidimensional data visualization 1200 helps explain why data cluster 1004 differs from data cluster 1002.

[0099] In various embodiments, the initial labels for data clusters are user-defined. In other embodiments, the computational system may provide initial labels based on predefined thresholds. According to various embodiments, after viewing a multidimensional data visualization 1200, a user can adjust the labels of some data, dynamically changing the labels on the two-dimensional scatter plot data visualization 1000. Furthermore, according to various embodiments, changes to data labels will affect the results generated by the computational system. In one example of a dPCR system, the results generated by the dPCR system (e.g., target concentration) vary based on the data labels. In this example, changing the labels based on information from the multidimensional data visualization also changes the results generated by the dPCR system, thus providing better results.

[0100] Figure 13 illustrates the user interface according to various embodiments described herein. When analyzing biological samples, the user can access user interface 1300. In user interface 1300, the user can indicate the sample name, for example, the experimental setup using the amount of dye, and the dye combination the user wants to display. The user can also choose to download a summary file of all labels for each sample in user interface 1300. For example, a file containing intensity values ​​and labels for each reaction site in all samples can be downloaded. Another type of file that can be downloaded is a summary of all labels for each sample. This file can be downloaded in CSV file format. Figure 16 shows an exemplary drop-down menu box 1600 for selecting dye combinations. When fluorescence emission is detected, an initial determination of positive and negative fluorescence detection is displayed as shown in user interface 1400 with reference to Figure 14. The user can also choose to download a summary file of all labels for each sample in user interface 1400. This file can be downloaded in CSV file format.

[0101] The user interface can also display two-dimensional scatter plot data visualizations and multidimensional data visualizations generated from fluorescence emission data. Figures 15A and 15B illustrate exemplary two-dimensional scatter plot data visualization 1500 and multidimensional data visualization 1502, respectively.

[0102] Figure 17AFigures 17A and 17B illustrate user interface tools according to various embodiments described herein. Figure 17A shows a box selection tool 1700 for quickly selecting data points. Figure 17B shows a lasso selection tool for drawing shapes around data points for selection. Selected data points can have their labels changed, for example, from positive to negative or from negative to positive. Labels can indicate the level of detected dye intensity values. For example, labels may include: “VIC High Positive, FAM High Positive”, “VIC Medium Positive, FAM Medium Positive”, “VIC Low Positive, FAM High Positive”, “VIC Low Positive, FAM Medium Positive”, “VIC High Positive, FAM Low Positive”, “VIC Medium Positive, FAM Low Positive”, or “VIC Negative, FAM Negative”. However, those skilled in the art will recognize that other markings exist that can be used according to the various embodiments described herein, such as markings for determining other dyes or data not included in the quantitative results. Selected data points can also be excluded from the result calculation. Figure 18 The image shows data selected by the box selection tool 1700, which serves as an exemplary user interface for visualizing two-dimensional scatter plot data. Users can also choose to download a summary file of all labels for each sample in the user interface 1800. This file can be downloaded, for example, in CSV file format.

[0103] A table can also be displayed on the user interface, showing, for example, positive counts, total number of data points for each dye, total number of data points for each label, quantitative values, or concentration values. As mentioned above, multiple dyes can be used.

[0104] According to various embodiments, the user interface 1200 may also have tools for downloading the results to a file (such as a CSV file).

[0105] The colors, labels, and other indicators in the user interface 1200 can also be adjusted. The displayed intensity range can be changed. The display order of the dye channels may also be changed.

[0106] Figure 19 shows a two-dimensional scatter plot data visualization according to the various embodiments described herein. Figure 20 shows a corresponding multidimensional data visualization according to the various embodiments described herein. Data subcluster 1902 shows data that are positive for VIC and FAM. However, by reviewing the multidimensional data visualization 2000, it can be determined that some of the positive VIC and FAM data in the two-dimensional scatter plot 1900 may be affected by fluorescence from other reaction sites.

[0107] Figure 21 illustrates a two-dimensional scatter plot data visualization 2100 according to various embodiments described herein. Figure 22 illustrates a corresponding multidimensional data visualization 2200 according to various embodiments described herein. In the two-dimensional scatter plot data visualization 2100, data cluster 2102 is shown labeled as VIC negative, even though it appears that two data clusters are labeled as VIC negative. When reviewing the multidimensional data visualization 2200, the user can determine by observing the indication of intensity 2202 that the second negative data cluster 2102 is likely due to a high-intensity JUN detection. Therefore, the user can determine that the automatic determination of the data is negative. In this example, four dyes were used in the multiple experiments. According to various embodiments, multidimensional data visualizations may use at least two dyes.

[0108] Figure 23 illustrates a two-dimensional scatter plot data visualization 2300 according to the various embodiments described herein. Figure 24 illustrates a corresponding multidimensional data visualization 2400 according to the various embodiments described herein. In the two-dimensional scatter plot data visualization 2300, data cluster 2302 is labeled as high values ​​for JUN and ABY. According to various embodiments, high fluorescence indicates a positive fluorescence detection. For example, data cluster 2302 may also be labeled as positive for JUN and ABY. However, when reviewing the indication of intensity 2402, the indication of intensity 2402 in the JUN channel is very high. The user may be able to see a positive VIC detection due to the high intensity of JUN in this data. Positive detections of ABY and JUN are shown as true positive detections. In this example, four dyes were used in the multiple experiments.

[0109] Figure 25 illustrates a two-dimensional scatter plot data visualization obtained according to the various embodiments described herein. Two dyes (FAM and VIC) are used in this example, but with two intensity levels. Therefore, several clusters are generated in the two-dimensional scatter plot data visualization 2600. Various combinations of high, medium, and no dye intensity are shown.

[0110] Based on the various embodiments discussed herein, a corresponding multidimensional data visualization 2600 is shown in Figure 26. Example

[0111] The following numbered examples are implementation examples:

[0112] 1. A computer-executed method for visualizing dye interactions in multiple biological samples, the method comprising:

[0113] Fluorescence emission data are received from each of a plurality of reaction sites, wherein the plurality of reaction sites include at least a first, a second, and a third dye;

[0114] Intensity values ​​of at least the first, second, and third dye channels were determined based on fluorescence emission data from each of the multiple reaction sites.

[0115] The user interface displays a first set of indicators that characterize multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the first dye channel.

[0116] The user interface displays a second set of indicators that characterize multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the second dye channel.

[0117] The third set of indicators on the user interface represents multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the third dye channel; and

[0118] The fluorescence emission data tags of the reaction sites are adjusted by comparing the first set of indicators.

[0119] 2. The computer-executed method of Example 1, wherein the fluorescence emission data further includes a fourth dye.

[0120] 3. The computer-executed method of Example 1 or Example 2 further includes:

[0121] The user interface displays a fourth set of indicators, which characterizes multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the fourth dye channel.

[0122] 4. The computer-executed method of any one of Examples 1 to 3, wherein the marker is a positive amplification marker.

[0123] 5. The computer-executed method as described in any one of Examples 1 to 4, wherein the fluorescence emission data is generated by polymerase chain reaction (PCR) of a biological sample.

[0124] 6. The computer-executed method as described in any one of Examples 1 to 5, wherein a first group, a second group, and a third group of indicators are displayed in a graph having an x-axis and a y-axis, wherein the x-axis represents dye channels and the y-axis represents intensity values.

[0125] 7. The computer-executed method according to Example 6, wherein the graph visualizes the intensity of the first, second, and third dyes in each dye channel.

[0126] 8. A computer-executed method as described in Example 6 or Example 7, wherein a line is displayed on a user interface connecting the intensity indications in each dye channel of fluorescence emission data from the same reaction site.

[0127] 9. A system for visualizing dye interactions in multiple biological samples, comprising:

[0128] Multiple reaction sites, each of which includes a biological sample;

[0129] The detector is configured to receive fluorescence emission data from multiple reaction sites;

[0130] The processor is configured to determine intensity values ​​of at least a first, second, and third dye channel based on fluorescence emission data from each of a plurality of reaction sites; and

[0131] User interface, configured as follows:

[0132] A first set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the first dye channel;

[0133] A second set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the second dye channel;

[0134] The third set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the third dye channel.

[0135] 10. The system of Example 1, wherein the fluorescence emission data also include a fourth dye.

[0136] 11. The system of Example 9 or Example 10, wherein the user interface is further configured as follows:

[0137] The fourth set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the fourth dye channel.

[0138] 12. The system of any one of Examples 9 to 11, wherein the marker is a positive amplification marker.

[0139] 13. The system of any one of Examples 9 to 12, wherein the fluorescence emission data is generated by polymerase chain reaction (PCR) of a biological sample.

[0140] 14. The system of any one of Examples 9 to 13, wherein a first group, a second group, and a third group of indicators are displayed in a graph having an x-axis and a y-axis, wherein the x-axis is the dye channel and the y-axis is the intensity value.

[0141] 15. The system described in Example 14, wherein the figure provides a visualization of the intensity of the first, second, and third dyes in each dye channel.

[0142] 16. The system described in Example 14 or Example 15, wherein a line is displayed on the user interface connecting the intensity indications in each dye channel of fluorescence emission data from the same reaction site.

[0143] 17. A computer-readable medium encoded with computer-readable instructions, which, when executed by a computer's processor, causes the computer to perform any one of Examples 1 to 8.

[0144] 18. A system comprising a processor and a storage medium storing instructions, the instructions, when executed by the processor, causing the system to perform the method as described in any one of Examples 1 to 8.

[0145] Although certain exemplary embodiments, examples, and applications have been described in relation to the present invention, it will be apparent to those skilled in the art that various modifications and alterations can be made thereto without departing from the present invention.

Claims

1. A computer-executed method for visualizing dye interactions in multiple biological samples, the method comprising: Fluorescence emission data are received from each of a plurality of reaction sites, wherein the plurality of reaction sites include at least a first, a second, and a third dye; Intensity values ​​of at least the first, second, and third dye channels were determined based on fluorescence emission data from each of the multiple reaction sites. The user interface displays a first set of indicators that characterize multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the first dye channel. The user interface displays a second set of indicators that characterize multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the second dye channel. The third set of indicators on the user interface represents multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the third dye channel; as well as The fluorescence emission data tags of the reaction sites are adjusted by comparing the first set of indicators.

2. The computer-executed method according to claim 1, wherein the fluorescence emission data further includes a fourth dye.

3. The computer execution method according to claim 2, further comprising: The user interface displays a fourth set of indicators, which characterizes multiple intensity values ​​of the fluorescence emission data of the first, second, and third dyes detected in the fourth dye channel.

4. The computer-executed method of claim 1, wherein the marker is a positive amplification marker.

5. The computer-executed method of claim 1, wherein the fluorescence emission data is generated by polymerase chain reaction (PCR) of a biological sample.

6. The computer-executed method of claim 1, wherein the first, second, and third sets of indications are displayed in a graph having an x-axis and a y-axis, wherein the x-axis is a dye channel and the y-axis is an intensity value.

7. The computer-executed method of claim 6, wherein the figure provides a visualization of the intensity of the first, second, and third dyes in each dye channel.

8. The computer-executed method of claim 7, wherein a line is displayed on the user interface connecting the intensity indications of fluorescence emission data from the same reaction site in each dye channel.

9. A system for visualizing dye interactions in multiple biological samples, comprising: Multiple reaction sites, each of which includes a biological sample; The detector is configured to receive fluorescence emission data from multiple reaction sites; The processor is configured to determine intensity values ​​of at least a first, second, and third dye channel based on fluorescence emission data from each of a plurality of reaction sites; as well as User interface, configured as follows: A first set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the first dye channel; A second set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the second dye channel; The third set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the third dye channel.

10. The system of claim 9, wherein the fluorescence emission data further includes a fourth dye.

11. The system of claim 10, wherein the user interface is further configured to: The fourth set of indicators displays multiple intensity values ​​of fluorescence emission data of the first, second, and third dyes detected in the fourth dye channel.

12. The system of claim 9, wherein the marker is a positive amplification marker.

13. The system of claim 9, wherein the fluorescence emission data is generated by polymerase chain reaction (PCR) of a biological sample.

14. The system of claim 9, wherein the first, second, and third sets of indicators are displayed in a graph having an x-axis and a y-axis, wherein the x-axis is a dye channel and the y-axis is an intensity value.

15. The system of claim 14, wherein the figure provides a visualization of the intensity of the first, second, and third dyes in each dye channel.

16. The system of claim 14, wherein a line is displayed on the user interface connecting the intensity indications of fluorescence emission data from the same reaction site in each dye channel.

17. A computer-readable medium encoded with computer-readable instructions, which, when executed by a computer's processor, causes the computer to perform the method of claim 1.

18. A system comprising a processor and a storage medium storing instructions, the instructions, when executed by the processor, causing the system to perform the method of claim 1.

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