阅读说明：本技术 一种荧光定量pcr平台基因智能识别和报告自动化系统 (Fluorescent quantitative PCR platform gene intelligent identification and report automatic system ) 是由 杨鹏程 陈建齐 刘朝辉 曹彦东 周洋 宓开拓 贺昆鹏 于 2021-10-21 设计创作，主要内容包括：本发明提出一种基于荧光定量PCR平台的基因智能识别和报告的自动化系统,该系统与LIS交互信息,自动生成检测报告并回传LIS,适用于药物基因组和新冠核酸检测,具有兼容多种qPCR仪器和LIS系统,能够进行阴性、阳性、纯合、杂合、野生型、异常提醒的智能判别等诸多优势。(The invention provides an automatic system for gene intelligent identification and report based on a fluorescent quantitative PCR platform, which interacts information with LIS, automatically generates a detection report and returns the detection report to the LIS, is suitable for detection of drug genomes and new coronary nucleic acids, is compatible with various qPCR instruments and LIS systems, and can perform intelligent judgment of negative, positive, homozygous, heterozygous, wild and abnormal reminding and the like.)

1. An automated system for gene intelligent identification and reporting based on a fluorescence quantitative PCR platform is characterized by comprising the following modules:

1) a data conversion module;

2) a data interpretation module;

3) a data quality control module;

4) a data reporting module;

5) and the LIS system calls the module.

2. The automated system for gene intelligent identification and reporting based on a fluorescence quantitative PCR platform of claim 1, wherein the system comprises the following modules:

1) a data conversion module: the module analyzes the off-line data file of the qPCR instrument according to the selected type of the qPCR instrument;

2) a data interpretation module: for the offline data file obtained by the data conversion module in the step 1), judging and reading the offline result by using an interpretation rule on the kit specification according to the selected kit type;

3) the data quality control module: the module establishes a discriminant mathematical model based on the data quality control component; predicting the curve shape of the detection result based on an AI intelligent learning component;

4) a data reporting module: the module is internally provided with a plurality of report templates, and the report templates are selected to be used for generating reports according to the requirements of users; or the report template and the sample data discrimination result can be decoupled, and a user can design the report template in a user-defined mode according to the requirement of the user so as to realize report automation.

5) lis System Call Module: the module comprises a plurality of sets of API interfaces for calling the main stream LIS, automatically generating a detection report and returning the detection report to the LIS.

3. The automated system for gene intelligent recognition and reporting based on the fluorescence quantitative PCR platform of claim 2, wherein in 1) the data transformation module, the analysis is performed by python language; the type of the off-line file comprises the reaction hole number, the sample name, the channel name, the Ct value corresponding to the channel and the information of the Delta Rn values of the fluorescence signal.

4. The automated system for gene intelligent recognition and reporting based on the fluorescence quantitative PCR platform of claim 3, wherein the 1) data transformation module is specifically configured as follows: the module decompresses and opens data of a PCR (polymerase chain reaction) instrument by using a python language, extracts file contents by using the python language, and extracts information including a reaction hole number, a sample name, a channel name, a Ct value corresponding to the channel and a fluorescence signal Delta Rn values.

5. The automated system for gene intelligent recognition and reporting based on the fluorescent quantitative PCR platform of any one of claims 2 to 4,

the 3) data quality control module is specifically configured as follows: the module carries out quality control on the data extracted by the data interpretation module: and judging the Ct value of the ROX channel by using python language, and predicting the curve shape by using a random forest algorithm by using an AI intelligent learning component according to the historical fluorescence signal Delta Rn values.

6. The automated gene intelligent recognition and reporting system based on the fluorescence quantitative PCR platform as claimed in claim 5, wherein the data quality control module performs quality control on the data extracted by the data interpretation module: the ROX channel Ct value is less than 38, the S-shaped curve of the fluorescence signal Delta Rn values is a normal result, the ROX channel Ct value is more than or equal to 38, and the non-S-shaped curve of the fluorescence signal Delta Rn values is an abnormal result;

preferably, when the quality control interpretation is an abnormal result, the system is informed of the abnormal classification, so that the iteration of the function of the abnormal result is realized; specifically, for the abnormal result prompted by the system, the module informs the system of abnormal classification through a manual labeling mode based on a discrimination model established by the data quality control module, and the iteration of the function of the abnormal result is realized.

7. The automated system for gene intelligent recognition and reporting based on the fluorescent quantitative PCR platform of any one of claims 2 to 6,

the 4) data reporting module is specifically configured as follows: report templates of various kits are built in the module, and corresponding reports are generated according to the kits selected by a user; the user can also self-define and design a report template according to the requirement;

preferably, the module calls an interface of the hospital LIS by using a queries module of python language and analyzes clinical examination information of the sample by using a json module of python language, including but not limited to order number, name, gender and age, and then corresponds to the interpretation result obtained by the data interpretation module according to the order number, and finally automatically fills the clinical examination information of the sample and the interpretation result into a word report by using a docxtpl module of python, and converts the generated word report into a PDF format and pushes the PDF format back to the LIS system.

8. A gene intelligent identification and report device based on a fluorescence quantitative PCR platform is characterized by comprising: at least one memory for storing a program; at least one processor for loading the program to run the automation system of any one of claims 1 to 7.

9. A storage medium having stored therein processor-executable instructions, wherein the processor-executable instructions, when executed by a processor, are for operating an automation system as claimed in any one of claims 1 to 7.

10. Use of the automated system according to any one of claims 1 to 7, the device according to claim 9 and the storage medium according to claim 9 for the preparation of a pharmaceutical genome or a diagnostic device for a novel corona nucleic acid detection molecule.

Technical Field

The invention relates to a data processing method and a data processing system, in particular to a gene intelligent identification and report automatic system based on a fluorescence quantitative PCR platform.

Background

The fluorescent quantitative PCR is a common PCR technology, and the PCR product is labeled and tracked through a fluorescent dye or a fluorescent labeled probe with specificity, so that the reaction process can be monitored on line in real time, the product can be analyzed by combining with corresponding software, and the initial concentration of a sample template to be detected is calculated. The technology has the advantages of high sensitivity, simple and convenient operation, high speed, intuitive result, good repeatability and the like, and is widely applied to diagnosis and treatment effect evaluation of various clinical diseases, including various cancers, hepatitis, influenza and the like.

Usually, the fluorescent quantitative PCR and the kit are from different manufacturers, and in the case of a small detection amount, a detection person can complete detection through visual interpretation and manual report. Once the daily detection amount exceeds 1000, the system must automatically judge and exchange information with the LIS, and automatically generate a detection report and return the LIS. Unfortunately, only individual closed software corresponding to fixed brand model qPCR instruments and fixed detection kits is available at present, but the software cannot be connected with the LIS system in a hospital, and there are many risks of manual introduction in the link of generating a detection report, such as putting on pangolin plum, and date error.

For clinical detection items with emphasis on repeatability and accuracy, how to identify abnormal results and prompt is very important. The abnormal reasons are various, such as the performance of instruments is reduced, the experimental operation is not standard, and the kit is unqualified. Since abnormal data is rare, and the abnormal data is difficult to find under the condition of insufficient sample data quantity, a software system which simply judges and reads according to specification judging rules cannot give a prompt of the abnormal data, and most of the abnormal data cannot appear in the specification.

The invention is provided in view of the above.

Disclosure of Invention

Based on at least one of the technical problems, the invention provides a novel gene intelligent identification and report method based on a fluorescence quantitative PCR platform and an automatic system.

The invention aims to provide an automatic gene intelligent identification and report system based on a fluorescent quantitative PCR platform.

In order to achieve the purpose, the invention provides the following technical scheme:

the invention provides an automatic gene intelligent identification and report system based on a fluorescent quantitative PCR platform, which comprises the following modules:

1) a data conversion module;

2) a data interpretation module;

3) the data quality control module:

4) a data reporting module;

5) lis system call module.

Further, the system comprises the following modules:

1) a data conversion module: the module analyzes the off-line data file of the qPCR instrument by using a python language according to the selected type of the qPCR instrument;

2) a data interpretation module: the module judges the off-line result by using a corresponding algorithm according to the type of the selected kit aiming at the off-line data file obtained by the data conversion module in the step 1);

3) the data quality control module: the module establishes a discriminant mathematical model based on the data quality control component; predicting the curve shape of the detection result based on the AI intelligent learning component;

4) a data reporting module: the module is internally provided with a plurality of report templates, and the report templates are selected to be used for generating reports according to the requirements of users; or the report template and the sample data discrimination result can be decoupled, and a user can design the report template in a user-defined mode according to the requirement of the user so as to realize report automation.

5) lis System Call Module: the module comprises a plurality of sets of API interfaces for calling the mainstream LIS, realizing information interaction with the LIS, automatically generating a detection report and returning the detection report to the LIS.

In some embodiments, in the 1) data conversion module, the parsing is performed in python language; the type of the off-line file comprises the reaction hole number, the sample name, the channel name, the Ct value corresponding to the channel and the information of the Delta Rn values of the fluorescence signal.

In some embodiments, the 1) data conversion module is specifically configured as follows: the module decompresses and opens data of a PCR (polymerase chain reaction) instrument by using a python language, extracts file contents by using the python language, and extracts information including a reaction hole number, a sample name, a channel name, a Ct value corresponding to the channel and a fluorescence signal Delta Rn values.

In some specific embodiments, the 1) data conversion module is specifically configured as follows: the module decompresses data of a PCR (polymerase chain reaction) instrument by using a zipfile module of python language, opens an analysis _ result.txt or experiment _ data file by using an open function of python language, extracts file contents by using a read method of python language, and extracts information including but not limited to a reaction hole number, a sample name, a channel name, a Ct value corresponding to the channel and a fluorescence signal Delta Rn value.

In some embodiments, the 2) data interpretation module is specifically configured as follows: integrating the reaction hole number, the sample name, the channel name, the Ct value corresponding to the channel and the information of the Delta Rn values of the fluorescence signal by using a python language, and judging the off-line result by using a corresponding algorithm according to the selected kit type.

In some embodiments, the 3) data quality control module is specifically configured as follows: the module carries out quality control on the data extracted by the data interpretation module: and judging the Ct value of the ROX channel by using python language, and predicting the curve shape by using a random forest algorithm by using an AI intelligent learning component according to the historical fluorescence signal Delta Rn values.

In some preferred embodiments, the module performs quality control on the data extracted by the data interpretation module: the judgment of the ROX channel Ct value <38 and the fluorescent signal Delta Rn values in an S-type curve is normal result, and the judgment of the ROX channel Ct value > 38 and the fluorescent signal Delta Rn values in a non-S-type curve is abnormal result.

In some more preferred embodiments, when the quality control is interpreted as an abnormal result, the system is informed of the abnormal classification, and the iteration of the function of the abnormal result is realized; specifically, for the abnormal result prompted by the system, the module informs the system of abnormal classification through a manual labeling mode based on a discrimination model established by the data quality control module, and the iteration of the function of the abnormal result is realized.

In some embodiments, the 4) data reporting module is specifically configured as follows: report templates of various kits are built in the module, and corresponding reports are generated according to the kits selected by a user; the user can also customize and design a report template according to the requirement of the user; the module calls an interface of a hospital LIS by using a requests module of python language and analyzes clinical detection information of a sample by using a json module of python language, wherein the clinical detection information includes but is not limited to order number, name, gender and age, and corresponds to an interpretation result obtained by a data interpretation module according to the order number, and finally, the clinical detection information and the interpretation result of the sample are automatically filled into a word report by using a docxtpl module of python, and the generated word report is converted into PDF format and pushed back to an LIS system.

The invention also provides a gene intelligent identification and report device based on the fluorescent quantitative PCR platform, which comprises: at least one memory for storing a program; at least one processor for loading the program to run the above described automated system.

The present invention also provides a storage medium having stored therein processor-executable instructions for operating an automation system as described above when executed by a processor.

The invention also provides an application of the automated system, the device and the storage medium in the diagnosis of the drug genome or the new corona nucleic acid detection molecule.

The invention also provides an application of the automated system, the device and the storage medium in the preparation of the medicine genome or new corona nucleic acid detection molecular diagnostic equipment.

The invention has the following remarkable technical effects:

1) the invention can be compatible with various qPCR instruments, can automatically carry out interpretation (negative/positive) and quality control on off-line data (reaction pore number, sample name, channel name, Ct value corresponding to the channel and Delta Rn value information of a fluorescence signal) according to the interpretation rule of the detection result of the kit, and automatically judges the type of a PCR amplification curve by using artificial intelligence, and abnormal data can prompt abnormality in a result report, namely the invention can effectively carry out various intelligent judgments such as negative, positive, homozygous, heterozygous, wild type, abnormal reminding and the like on the detection data.

2) The invention can be compatible with various LIS systems, can be connected with the Lis system of a hospital, and automatically uploads the interpretation result to the Lis system of the hospital, thereby reducing manual operation and human errors.

3) The invention can also automatically count historical data, the data comprises the type of the instrument, the type of the kit and the result of each hole, and the performance of the instrument and the experimental quality are monitored by using a big data mode.

4) The invention can be effectively applied to molecular diagnosis and detection items such as drug genome, new crown nucleic acid detection and the like.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a flow diagram of the system of the present invention;

FIG. 2 is a schematic diagram of a custom design report template filling-in edition for a data report module;

FIG. 3 is a schematic diagram of a custom designed report template for a data reporting module;

FIG. 4 System interface FIG. 1;

FIG. 5 System interface FIG. 2;

fig. 6 system report diagram.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The following terms or definitions are provided only to aid in understanding the present invention. These definitions should not be construed to have a scope less than understood by those skilled in the art.

Unless defined otherwise below, all technical and scientific terms used in the detailed description of the present invention are intended to have the same meaning as commonly understood by one of ordinary skill in the art. While the following terms are believed to be well understood by those skilled in the art, the following definitions are set forth to better explain the present invention.

As used herein, the terms "comprising," "including," "having," "containing," or "involving" are inclusive or open-ended and do not exclude additional unrecited elements or method steps. The term "consisting of …" is considered to be a preferred embodiment of the term "comprising". If in the following a certain group is defined to comprise at least a certain number of embodiments, this should also be understood as disclosing a group which preferably only consists of these embodiments.

Where an indefinite or definite article is used when referring to a singular noun e.g. "a" or "an", "the", this includes a plural of that noun.

The terms "about" and "substantially" in the present invention denote an interval of accuracy that can be understood by a person skilled in the art, which still guarantees the technical effect of the feature in question. The term generally denotes a deviation of ± 10%, preferably ± 5%, from the indicated value.

Furthermore, the terms first, second, third, (a), (b), (c), and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments of the invention described herein are capable of operation in other sequences than described or illustrated herein.

The automated system for gene intelligent identification and reporting based on the fluorescence quantitative PCR platform is generally a system comprising the following modules: 1) a data conversion module; 2) a data interpretation module; 3) the data quality control module: 4) a data reporting module; 5) lis system call module.

The automatic system comprises a plurality of sets of API interfaces for domestic mainstream LIS calling, realizes information interaction with the LIS, automatically generates a detection report and returns the LIS. In addition, the automatic system can also be used for butt joint of a plurality of qPCR instruments and detection kits, for example, the qPCR instruments of Roche, Saimer Feishale, Tianlong and other manufacturers can be matched to complete detection of the drug genome and the new crown nucleic acid. The automatic system respectively establishes a discriminant mathematical model for the off-line data of different kits on different detection instruments, and judges the curve type of the detection result in an artificial intelligence mode, such as whether the curve type is a standard S-shaped curve. And (4) telling the system to classify the abnormity through a manual labeling mode for the abnormal result prompted by the system, so as to realize the iteration of the function of the abnormal result. In the automatic system, a report template and a sample data discrimination result are decoupled, a user can design a word report template according to own needs to realize report automation, namely, the report template is automatically filled according to the sample data discrimination result and clinical detection information in an LIS (laser induced breakdown spectroscopy), a generated word report is converted into a PDF (Portable document Format) format and pushed back to the LIS system, communication handshake is completed by a order number in the whole process, and the detection result is ensured not to be worn in a crowned fashion.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as specifically described herein, and thus the scope of the present invention is not limited by the specific embodiments disclosed below.

Example 1 configuration example of an Automation System

The automatic gene intelligent identification and report system based on the fluorescent quantitative PCR platform of the invention as shown in FIG. 1 comprises the following modules:

1) a data conversion module for converting the data into a digital signal,

2) a data interpretation module for interpreting the data,

3) a data quality control module for controlling the quality of the data,

4) a data reporting module for reporting the data of the electronic device,

5) lis system call module.

The data conversion module is configured as follows: the module analyzes a lower computer data file of the qPCR instrument by using a corresponding algorithm according to the selected type of the qPCR instrument, and for lower data of the Sammer Fielder instrument, the module decompresses a lower data file (eds) of the Sammer Fielder instrument with model ABi7500 by using a zipfile module of python language to obtain an aplobio folder, wherein the aplobio folder is internally provided with a sds folder, an analysis _ result.txt file is arranged in a sds folder, an analysis _ result.txt file is opened by using an open function of python language, analysis _ result.txt file content is extracted by using a read method of python language, and information such as reaction hole number, sample name, channel name, Ct value corresponding to channel, fluorescence signal Delta value and the like is extracted. For the offline data of the Tianlong instrument, the module uses a zipfile module of python language to decompress an offline data file (. tlpd) of an instrument with the model of Tianlong Gentier 96E, an experimental _ data file is obtained by decompression, the experimental _ data file is opened by using an open function of python language, the content of the experimental _ data file is extracted by using a read method of python language, and information such as a reaction hole number, a sample name, a channel name, a Ct value corresponding to the channel, a fluorescence signal Delta Rn value and the like is extracted.

The data interpretation module is configured as follows: the module analyzes the off-line data file of the qPCR instrument by using the data conversion module according to the type of the selected qPCR instrument, and judges the off-line result by using the judgment rule on the kit specification according to the type of the selected kit, so that a plurality of types of qPCR instruments and detection kits can be docked, for example, the detection of drug genomes and new crown nucleic acids can be completed by matching with the qPCR instruments of manufacturers such as Roche, Saimer Feishie, Tianlong and the like.

The data interpretation module integrates information such as reaction hole number, sample name, channel name, Ct value corresponding to a channel, fluorescence signal Delta Rn values and the like by using python language, for example, when a certain sample is a wild type sample when the Ct value of an FAM channel is less than or equal to 36, the Ct value of a VIC channel is greater than 36 and the Ct value of an ROX channel is less than 38 in a human MTHFR gene detection kit of the kit; when the Ct value of the FAM channel is less than or equal to 36, the Ct value of the VIC channel is less than or equal to 36 and the Ct value of the ROX channel is less than 38, the channel is a heterozygote; when the Ct value of the FAM channel is greater than 36, the Ct value of the VIC channel is less than or equal to 36 and the Ct value of the ROX channel is less than 38, the model is homozygotic.

The data quality control module is configured as follows: the module establishes a discriminant mathematical model based on the data quality control component; the module also comprises an AI intelligent learning component which can judge the curve shape of the detection result in an artificial intelligence mode, if the curve shape is a standard S-shaped curve.

The module is used for controlling the quality of the data extracted by the data interpretation module, judging that the Ct value of the ROX channel is less than 38 and the Delta Rn values of the fluorescence signals are S-shaped curves as normal results by using python language, judging that the Ct value of the ROX channel is more than or equal to 38 and the Delta Rn values of the fluorescence signals are non-S-shaped curves as abnormal results, informing the system of abnormal classification, and realizing the iteration of the function of the abnormal results.

And for the abnormal result prompted by the system, the module informs the system of abnormal classification in a manual labeling mode based on a discrimination model established by the data quality control module, and realizes the iteration of the function of the abnormal result.

The data reporting module is configured as follows: the module is internally provided with a plurality of report templates, and the report templates are selected to be used for generating reports according to the needs of users: or the report template and the sample data discrimination result can be decoupled, a user can self-define the report template according to own needs, specifically design the word report template to realize report automation, namely, the report template is automatically filled into the report template according to the sample data discrimination result and clinical detection information in the LIS, the generated word report is converted into a PDF format and pushed back to the LIS system, the whole process completes communication handshake by using a order number, and the detection result is ensured not to be worn by the plum tree

The data reporting module is configured as follows: report templates of various kits are built in the module, corresponding reports are generated according to the kits selected by users, and the users can design the report templates in a user-defined mode according to own needs. The module calls an interface of the hospital lis by using a requests module of python language and analyzes clinical detection information of a sample by using a json module of python language: and the order number, the name, the gender, the age and the like are added, the interpretation result obtained by the data interpretation module is corresponded to the order number, finally, a docxtpl module of python is used for automatically filling the clinical detection information and the interpretation result of the sample into a word report, the generated word report is converted into a PDF format and pushed back to an LIS system, the whole process completes communication handshake by the order number, and the detection result is ensured not to be worn by peaceful plum trees.

The report template is designed by the user in a self-defined mode, the user fills variables designed by the report template into corresponding positions of the designed report template, the format of the variables is that an English word is clamped between two braces, and the English word is as follows: { { name } } represents the variable of the name, as shown in fig. 2, the variables required by the report template are all filled in the corresponding positions of the designed report template and then uploaded to the system for report automation, and the report automation can generate the corresponding report, as shown in fig. 3.

The lis system call module is configured as follows: the module comprises a plurality of sets of API interfaces for domestic mainstream LIS calling, realizes information interaction with the LIS, automatically generates a detection report and returns the detection report to the LIS.

Embodiment 2 reporting method based on automated System

As shown in FIG. 1, the invention shows a gene intelligent identification and reporting method based on a fluorescence quantitative PCR platform, the method comprises the following steps:

1. a user leads off-line data of the kit on a detection instrument into an automatic system;

2. the system automatically carries out data interpretation and records the interpretation result in a database;

3. performing data quality control on the interpretation result, and prompting quality control abnormal data;

4. all data will generate a result report;

5. the system automatically exports the results report to the Lis system.

FIG. 3 is a data analysis report specifically generated using the method of the present invention.

qPCR instrument: ABi-7500

The kit comprises: bergey new crown kit

The Lis system: Bio-LIMS

After entering the system, the interface of fig. 4 appears, the left side is a function type navigation bar, and the right side is a function implementation window; the machine model is selected from ABi-7500 in a pull-down mode; pulling down the kit type to select a new GuanjBerger; clicking an input button to upload the eds data file of the new crown _ Bergey from ABi-7500, as shown in FIG. 5; the upper left corner of the function realization window is the display of results in each hole on the ABi-7500 instrument experiment plate, the horizontal axis coordinate is 1 to 12, the vertical axis coordinate is A to H, the total number is 96 holes, the number corresponding to the hole number is A1 to H12, the background of the hole is black to indicate negative, the background of the hole is gray to indicate no data, and the background of the hole is white to indicate abnormal data; the upper right corner of the function realization window is a result amplification S-shaped curve displayed after clicking the hole at the upper left corner; clicking on the generated report may generate a pdf report (one sample), as shown in fig. 6; clicking on the upload report button can upload the pdf report to the Bio-LIMS system.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. The figures are only functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

The foregoing descriptions of specific exemplary embodiments of the present invention have been presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the invention and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the invention and various alternatives and modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.