Method and system for identifying imbalance state of oral flora
By identifying and filtering the clusters of oral samples, determining the core bacterial flora and building an imbalance model, the problem of difficulty in identifying the imbalance state of oral flora in the prior art is solved, and precise control and risk prediction of oral flora status is achieved.
Patent Information
- Application Number
- CN202411553220.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-01
- Publication Date
- 2025-02-25
AI Technical Summary
The prior art is difficult to effectively identify the imbalance of oral flora, which affects subsequent risk prediction.
By collecting the clusters of oral samples, the oral bacterial equilibrium groups and the imbalance groups are divided, the relative abundance is defined, the core bacterial fertility is determined after filtering, and an imbalance model is constructed based on the core bacterial fertility, and the imbalance coefficient is defined to identify the imbalance state.
Accurate identification and control of oral flora imbalance status is achieved, providing a risk assessment method for predicting oral flora imbalance.
Smart Images
Figure CN119517399A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of oral flora, and in particular to a method and system for identifying an imbalance state of oral flora. Background Art
[0002] With the development of science and technology, the application environment of oral microbiota is inside the oral cavity. Usually, oral microbiota is in a dynamic equilibrium state. However, when the balance of oral microecology is disrupted, potential opportunistic pathogens will overgrow, and the state of oral flora cannot be effectively identified, especially the identification of imbalanced state, which affects the subsequent risk prediction. Summary of the invention
[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a method and system for identifying the imbalance state of oral flora, collecting a flora set of an oral sample, dividing the oral flora balance group and the oral flora imbalance group according to the flora set of the oral sample; defining the relative abundance of the oral flora balance group, and defining the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group; defining the oral core flora according to the filtered oral flora balance group and the oral flora imbalance group, so as to facilitate multi-dimensional control of the filtered oral flora balance group and the oral flora imbalance group, thereby clarifying the oral core flora and ensuring the accuracy of the oral core flora.
[0004] Furthermore, an imbalance model of oral flora is constructed based on the oral core flora; the imbalance coefficient is defined according to the imbalance model of oral flora and the oral core flora; the imbalance state of oral flora is defined according to the identification of the imbalance coefficient, so as to facilitate targeted state identification of the oral flora, thereby introducing the imbalance state of oral flora, realizing the identification and further control of the imbalance state of oral flora, and providing risk prediction for responding to the occurrence of oral flora imbalance.
[0005] The embodiment of the present invention provides a method for identifying an imbalance state of oral flora, which is applied to the identification scenario of an imbalance state of oral flora;
[0006] The method for identifying the imbalance state of oral flora comprises:
[0007] Collecting a flora collection of the oral sample, and dividing the oral flora into a balanced oral flora group and an unbalanced oral flora group according to the flora collection of the oral sample;
[0008] defining the relative abundance of the oral flora balance group, and defining the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group;
[0009] The core oral flora was defined based on the filtered oral flora balance group and oral flora imbalance group;
[0010] Construct an imbalance model of oral flora based on the core oral flora;
[0011] The imbalance coefficient is defined based on the imbalance model of oral flora and the core oral flora;
[0012] The imbalance state of the oral flora is defined based on the identification of the imbalance coefficient.
[0013] Optionally, collecting a flora set of the oral sample and dividing the oral flora balance group and the oral flora imbalance group according to the flora set of the oral sample include:
[0014] Obtain oral microbiome 16S sequencing data of oral samples;
[0015] The bacterial flora collection of oral samples was defined based on the oral microbiome 16S sequencing data of oral samples;
[0016] Collecting a bacterial flora collection of the oral sample, at this time, defining the absolute abundance of different bacterial genera in the oral sample based on the bacterial flora collection of the oral sample;
[0017] Match the corresponding status mark according to the bacterial flora set of the oral sample;
[0018] Based on the bacterial flora collection and status markers of oral samples, the oral flora balance group and oral flora imbalance group were divided.
[0019] Optionally, the defining the relative abundance of the oral flora balance group, and defining the filtered oral flora balance group according to filtering the relative abundance of the oral flora balance group, comprises:
[0020] The absolute abundance of different bacterial genera in oral samples was fixed;
[0021] The relative abundance of the oral flora balance group was defined based on the absolute abundance of different bacterial genera in the oral samples and the oral flora balance group;
[0022] The relative abundance threshold at which the collection is in an eligible state;
[0023] Triggering the filtering of the relative abundance of the oral flora balance group based on the relative abundance of the oral flora balance group and the relative abundance threshold;
[0024] In filtering the relative abundance of the oral flora balance group, oral flora with a relative abundance of less than 0.01% and an occurrence frequency of less than 10% in the oral flora balance group are filtered out to obtain a filtered oral flora balance group.
[0025] Optionally, defining the oral core flora according to the filtered oral flora balance group and oral flora imbalance group includes:
[0026] Oral flora balance group after fixed-frame filtration;
[0027] The oral flora balance group and oral flora imbalance group after correlation filtering;
[0028] Trigger the corresponding difference comparison according to the filtered oral flora balance group and oral flora imbalance group, and output the difference parameters;
[0029] Define the corresponding difference status according to the difference parameters and the difference status table;
[0030] If the difference state is a significant difference state, a differential bacterial combination is constructed according to the filtered oral flora balance group and oral flora imbalance group;
[0031] The core oral flora was defined based on the differential bacterial composition;
[0032] Let the FC value of the i-th difference bacteria in the difference bacteria combination be FC Di , calculated as: FC Di =log2(I Di / B Di ), I Di is the average relative abundance of the differential bacteria Di in the oral flora imbalance group, B Di It is the average relative abundance of Di in the oral flora balance group after filtration; when the absolute value of FC value is greater than 0.5, the oral core flora is obtained.
[0033] Optionally, constructing an imbalance model of oral flora based on the oral core flora includes:
[0034] Determine the core flora of the oral cavity;
[0035] The core oral flora was used as test data;
[0036] Learning and training are performed based on the core oral flora and the corresponding learning model, and an imbalance model of the oral flora is constructed. At this time, the flora set based on the oral sample is divided into multiple data sets, and the multiple data sets are cross-validated and repeatedly validated until an imbalance model of the oral flora is constructed.
[0037] Optionally, the method of constructing an imbalance model of oral flora based on the oral core flora further includes:
[0038] Fitting the imbalance model of oral flora;
[0039] Collect the corresponding ROC curve;
[0040] Match the corresponding AUC value based on the ROC curve;
[0041] The recognition ability of the oral flora imbalance model was defined based on the AUC value.
[0042] Optionally, defining the imbalance coefficient according to the imbalance model of the oral flora and the oral core flora includes:
[0043] Collect the imbalance model of oral flora;
[0044] The imbalance model of oral flora and the core oral flora are related;
[0045] The imbalance model of oral flora and oral core flora triggers multiple authentications and outputs the imbalance coefficient.
[0046] Optionally, defining the imbalance state of the oral flora according to the identification of the imbalance coefficient includes:
[0047] Fixed frame imbalance coefficient;
[0048] associated imbalance coefficients and imbalance coefficient identification table;
[0049] The corresponding identification is triggered according to the imbalance coefficient and the imbalance coefficient identification table.
[0050] Optionally, the method of defining the imbalance state of the oral flora according to the identification of the imbalance coefficient further includes:
[0051] The imbalance state of the oral flora is defined based on the identification of the imbalance coefficient.
[0052] In addition, an embodiment of the present invention further provides a system for identifying an imbalance state of oral flora, and the system for identifying an imbalance state of oral flora includes:
[0053] A collection model, used to collect the flora collection of the oral sample, and divide the oral flora balance group and the oral flora imbalance group according to the flora collection of the oral sample;
[0054] A filtering model is used to define the relative abundance of the oral flora balance group, and to define the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group;
[0055] The core flora model is used to define the core flora of the oral cavity according to the filtered balanced and unbalanced oral flora groups;
[0056] The imbalance module is used to construct an imbalance model of oral flora based on the core oral flora;
[0057] An imbalance coefficient module, used to define the imbalance coefficient according to the imbalance model of oral flora and the core flora of the oral cavity;
[0058] The identification module is used to define the imbalance state of the oral flora according to the identification of the imbalance coefficient.
[0059] In an embodiment of the present invention, through the method in the embodiment of the present invention, the flora set of the oral sample is collected, and the oral flora balance group and the oral flora imbalance group are divided according to the flora set of the oral sample; the relative abundance of the oral flora balance group is defined, and the filtered oral flora balance group is defined according to the filtering of the relative abundance of the oral flora balance group; the oral core flora is defined according to the filtered oral flora balance group and the oral flora imbalance group, so as to facilitate multi-dimensional control of the filtered oral flora balance group and the oral flora imbalance group, thereby clarifying the oral core flora and ensuring the accuracy of the oral core flora.
[0060] Furthermore, an imbalance model of oral flora is constructed based on the oral core flora; the imbalance coefficient is defined according to the imbalance model of oral flora and the oral core flora; the imbalance state of oral flora is defined according to the identification of the imbalance coefficient, so as to facilitate targeted state identification of the oral flora, thereby introducing the imbalance state of oral flora, realizing the identification and further control of the imbalance state of oral flora, and providing risk prediction for responding to the occurrence of oral flora imbalance. BRIEF DESCRIPTION OF THE DRAWINGS
[0061] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0062] Figure 1 is a flow chart of a method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0063] Figure 2 is a flow chart of S11 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0064] Figure 3 is a flow chart of S12 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0065] Figure 4 is a flow chart of S13 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0066] Figure 5 is a flow chart of S14 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0067] Figure 6 is a flow chart of S15 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0068] Figure 7 is a flow chart of S16 in the method for identifying an imbalance state of oral flora in an embodiment of the present invention;
[0069] Figure 8 Schematic diagram of the structure of the system for identifying the imbalance state of oral flora in an embodiment of the present invention;
[0070] Fig. 9 is a hardware diagram of an electronic device according to an exemplary embodiment;
[0071] Fig.10 Schematic diagram of a learning rate curve of an imbalance model of oral flora in a method for identifying an imbalance state of oral flora in an embodiment of the present invention.
[0072] Fig.11 3 is a ROC-AUC curve of the imbalance model of the oral flora in the method for identifying the imbalance state of the oral flora in the embodiment of the present invention. DETAILED DESCRIPTION
[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0074] See also Figures 1 to 11 , a method for identifying an imbalance state of oral flora, which is applied to the identification scenario of an imbalance state of oral flora; the method for identifying an imbalance state of oral flora includes:
[0075] Step S11: collecting a flora collection of the oral sample, and dividing the oral flora into a balanced oral flora group and an unbalanced oral flora group according to the flora collection of the oral sample;
[0076] Step S12: defining the relative abundance of the oral flora balance group, and defining the filtered oral flora balance group according to filtering the relative abundance of the oral flora balance group;
[0077] Step S13: defining the oral core flora according to the filtered oral flora balance group and oral flora imbalance group;
[0078] Step S14: constructing an imbalance model of oral flora based on the oral core flora;
[0079] Step S15: defining an imbalance coefficient according to the imbalance model of the oral flora and the oral core flora;
[0080] Step S16: defining the imbalance state of the oral flora according to the identification of the imbalance coefficient.
[0081] In an embodiment of the present invention, through the method in the embodiment of the present invention, the flora set of the oral sample is collected, and the oral flora balance group and the oral flora imbalance group are divided according to the flora set of the oral sample; the relative abundance of the oral flora balance group is defined, and the filtered oral flora balance group is defined according to the filtering of the relative abundance of the oral flora balance group; the oral core flora is defined according to the filtered oral flora balance group and the oral flora imbalance group, so as to facilitate multi-dimensional control of the filtered oral flora balance group and the oral flora imbalance group, thereby clarifying the oral core flora and ensuring the accuracy of the oral core flora.
[0082] Furthermore, an imbalance model of oral flora is constructed based on the oral core flora; the imbalance coefficient is defined according to the imbalance model of oral flora and the oral core flora; the imbalance state of oral flora is defined according to the identification of the imbalance coefficient, so as to facilitate targeted state identification of the oral flora, thereby introducing the imbalance state of oral flora, realizing the identification and further control of the imbalance state of oral flora, and providing risk prediction for responding to the occurrence of oral flora imbalance.
[0083] refer to Figure 2 In step S11, a flora set of an oral sample is collected, and the oral flora balance group and the oral flora imbalance group are divided according to the flora set of the oral sample;
[0084] In the specific implementation process of the present invention, the specific steps may be:
[0085] S111: Obtain oral microbiome 16S sequencing data of oral samples;
[0086] S112: Define the bacterial flora collection of oral samples based on the oral microbiome 16S sequencing data of oral samples;
[0087] S113: collecting a bacterial flora collection of the oral sample. At this time, the absolute abundance of different bacterial genera in the oral sample is defined based on the bacterial flora collection of the oral sample;
[0088] S114: Matching a corresponding status mark according to the bacterial flora set of the oral sample;
[0089] S115: Divide the oral flora into a balanced oral flora group and an unbalanced oral flora group based on the flora collection and status markers of the oral samples.
[0090] In an embodiment of the present application, oral microbiome 16S sequencing data of an oral sample is obtained, and the oral microbiome 16S sequencing data of the oral sample is further processed to define a flora set of the oral sample based on the oral microbiome 16S sequencing data of the oral sample, introduce the flora set of the oral sample, and realize subsequent processing of the flora set of the oral sample.
[0091] Furthermore, the bacterial flora set of the oral sample is collected. At this time, the absolute abundance of different bacterial genera in the oral sample is defined based on the bacterial flora set of the oral sample. The absolute abundance of different bacterial genera in the oral sample is defined according to further processing of the bacterial flora set of the oral sample. The absolute abundance of different bacterial genera is introduced, thereby achieving further control of the absolute abundance of different bacterial genera.
[0092] Therefore, by matching the corresponding status mark according to the flora set of the oral sample, the flora set of the oral sample and the corresponding status mark are associated, so as to divide the oral flora balance group and the oral flora imbalance group based on the flora set and the status mark of the oral sample, thereby realizing the classification of the oral flora balance group and the oral flora imbalance group, and ensuring the further control of the oral flora balance group and the oral flora imbalance group.
[0093] refer to Figure 3 In step S12, the relative abundance of the oral flora balance group is defined, and the filtered oral flora balance group is defined according to the filtering of the relative abundance of the oral flora balance group;
[0094] In the specific implementation process of the present invention, the specific steps may be:
[0095] S121: absolute abundance of different bacterial genera in fixed-frame oral samples;
[0096] S122: Define the relative abundance of the oral flora balance group based on the absolute abundance of different bacterial genera in the oral samples and the oral flora balance group;
[0097] S123: Collecting the relative abundance threshold in a qualified state;
[0098] S124: triggering filtering of the relative abundance of the oral flora balance group based on the relative abundance of the oral flora balance group and the relative abundance threshold;
[0099] S125: In filtering the relative abundance of the oral flora balance group, oral flora with a relative abundance of less than 0.01% and an occurrence frequency of less than 10% in the oral flora balance group are filtered out to obtain a filtered oral flora balance group.
[0100] In an embodiment of the present application, the absolute abundance of different genera of bacteria in the oral sample is fixed, and the absolute abundance of different genera of bacteria in the oral sample is further controlled, so that the relative abundance of the oral flora balance group is defined based on the absolute abundance of different genera of bacteria in the oral sample and the oral flora balance group, thereby achieving the control of the relative abundance of the oral flora balance group, and performing multi-dimensional control based on the absolute abundance of different genera of bacteria in the oral sample and the oral flora balance group.
[0101] Therefore, the relative abundance threshold in a qualified state is collected in order to introduce the relative abundance threshold in a qualified state, so as to compare the relative abundance of the oral flora balance group with the relative abundance threshold, and then trigger the filtering of the relative abundance of the oral flora balance group based on the relative abundance of the oral flora balance group and the relative abundance threshold, thereby completing the further filtering of the relative abundance of the oral flora balance group.
[0102] Specifically, in filtering the relative abundance of the oral flora balance group, oral flora with a relative abundance of less than 0.01% and an occurrence frequency of less than 10% in the oral flora balance group are filtered out to obtain a filtered oral flora balance group.
[0103] refer to Figure 4 In step S13, the oral core flora is defined according to the filtered oral flora balance group and oral flora imbalance group;
[0104] In the specific implementation process of the present invention, the specific steps may be:
[0105] S131: oral flora balance group after fixed-frame filtration;
[0106] S132: oral flora balance group and oral flora imbalance group after correlation filtering;
[0107] S133: triggering a corresponding difference comparison according to the filtered oral flora balance group and oral flora imbalance group, and outputting a difference parameter;
[0108] S134: defining a corresponding difference state according to the difference parameter and the difference state table;
[0109] S135: If the difference state is a significant difference state, construct a difference bacteria combination according to the filtered oral flora balance group and oral flora imbalance group;
[0110] S136: If the difference state is a significant difference state, construct a difference bacteria combination according to the filtered oral flora balance group and oral flora imbalance group.
[0111] In an embodiment of the present application, the oral flora balance group after freezing filtration is further processed, and the filtered oral flora balance group and the oral flora imbalance group are introduced, so as to associate the filtered oral flora balance group and the oral flora imbalance group, so as to trigger the corresponding difference comparison according to the filtered oral flora balance group and the oral flora imbalance group, and output the difference parameters, thereby ensuring the output of the difference parameters and further controlling the difference parameters.
[0112] At this time, the corresponding difference state is defined according to the difference parameter and the difference state table, and multi-dimensional control is performed on the difference parameter and the difference state table to facilitate the definition of the corresponding difference state, thereby achieving further control of the difference state. ;
[0113] Therefore, if the difference state is a significant difference state, a differential bacterial combination is constructed based on the filtered oral flora balance group and oral flora imbalance group, so as to facilitate multi-dimensional control of the filtered oral flora balance group and oral flora imbalance group, realize the construction of the differential bacterial combination, and ensure the accuracy of the differential bacterial combination. Furthermore, if the difference state is a significant difference state, a differential bacterial combination is constructed based on the filtered oral flora balance group and oral flora imbalance group, so as to further control the differential bacterial combination.
[0114] Furthermore, let the FC value of the i-th differential bacteria in the differential bacteria combination be FC Di , calculated as: FC Di =log2(I Di / B Di ), I Di is the average relative abundance of the differential bacteria Di in the oral flora imbalance group, B Di It is the average relative abundance of Di in the oral flora balance group after filtration; when the absolute value of FC value is greater than 0.5, the oral core flora is obtained.
[0115] refer to Figure 5 , S14: Constructing an imbalance model of oral flora based on the core oral flora;
[0116] In the specific implementation process of the present invention, the specific steps may be:
[0117] S141: Fixed oral core flora;
[0118] S142: Use the core oral flora as test data;
[0119] S143: performing learning and training according to the oral core flora and the corresponding learning model, and constructing an imbalance model of the oral flora. At this time, the flora set based on the oral sample is divided into multiple data sets, and the multiple data sets are cross-validated and repeatedly validated until the imbalance model of the oral flora is constructed;
[0120] S144: Fitting the imbalance model of oral flora;
[0121] S145: collecting the corresponding ROC curve;
[0122] S146: Matching the corresponding AUC value based on the ROC curve; defining the recognition ability of the imbalance model of the oral flora according to the recognition of the AUC value.
[0123] In an embodiment of the present application, the oral core flora is frozen, and the oral core flora is further controlled. In addition, the oral core flora is used as test data, so that learning and training are performed based on the oral core flora and the corresponding learning model, and an imbalance model of the oral flora is constructed. At this time, the flora set based on the oral sample is divided into multiple data, and the multiple data are cross-validated and repeatedly validated until the imbalance model of the oral flora is constructed, thereby ensuring the construction of the imbalance model of the oral flora and improving the accuracy of the imbalance model of the oral flora.
[0124] Furthermore, the imbalance model of the oral flora is fitted; the corresponding ROC curve is collected; the corresponding AUC value is matched based on the ROC curve; and the recognition ability of the imbalance model of the oral flora is defined according to the recognition of the AUC value, so as to facilitate further recognition of the imbalance model of the oral flora.
[0125] refer to Figure 6 , S15: define the imbalance coefficient according to the imbalance model of oral flora and the core oral flora;
[0126] In the specific implementation process of the present invention, the specific steps may be:
[0127] S151: Collect the imbalance model of oral flora;
[0128] S152: Imbalance model of oral flora and core oral flora;
[0129] S153: Trigger multiple authentications based on the imbalance model of oral flora and oral core flora, and output the imbalance coefficient.
[0130] In an embodiment of the present application, an imbalance model of the oral flora is collected, and the imbalance model of the oral flora is further processed. At the same time, the imbalance model of the oral flora and the oral core flora are associated; multiple authentications are triggered based on the imbalance model of the oral flora and the oral core flora, and the imbalance coefficient is output, so as to introduce the imbalance coefficient and further process the imbalance coefficient.
[0131] refer to Figure 7 , S16: defining the imbalance state of the oral flora based on the identification of the imbalance coefficient;
[0132] In the specific implementation process of the present invention, the specific steps may be:
[0133] S161: Fixed frame imbalance coefficient;
[0134] S162: associating imbalance coefficients and imbalance coefficient identification table;
[0135] S163: triggering corresponding identification according to the imbalance coefficient and the imbalance coefficient identification table;
[0136] S164: defining the imbalance state of the oral flora according to the identification of the imbalance coefficient.
[0137] In the specific implementation process of the present invention, an imbalance model of oral flora is constructed based on the oral core flora; the imbalance coefficient is defined according to the imbalance model of oral flora and the oral core flora; the imbalance state of oral flora is defined according to the identification of the imbalance coefficient, so as to facilitate targeted state identification of the oral flora, thereby introducing the imbalance state of oral flora, realizing the identification and further control of the imbalance state of oral flora, and providing risk prediction for responding to the occurrence of oral flora imbalance.
[0138] At this time, the imbalance coefficient is fixed, and the imbalance coefficient and the imbalance coefficient identification table are introduced. The imbalance coefficient and the imbalance coefficient identification table are associated to facilitate the association of the imbalance coefficient and the imbalance coefficient identification table, and then the corresponding identification is triggered according to the imbalance coefficient and the imbalance coefficient identification table. Therefore, the imbalance state of the oral flora is defined according to the identification of the imbalance coefficient, and the imbalance coefficient and the imbalance coefficient identification table of the imbalance state of the oral flora are defined.
[0139] Specific embodiments:
[0140] Acquisition of oral core flora
[0141] 1) Collect samples. Select annotated saliva samples in the research field, obtain the 16S sequencing data of the oral microbiome of the samples, and calculate the number and total number of different genera in the samples to obtain the absolute abundance of different genera in the samples, and obtain set A. At the same time, set A is divided into set B of saliva samples of people with balanced oral flora (this set can be expressed as the balanced oral flora group), B = {B1, B2, B3, ..., B n}. And a sample set I of the population with oral flora imbalance (this set can be expressed as an oral flora imbalance group), I = {I1, I2, I3, ..., I n}. A total of 907 oral samples were collected this time.
[0142] 2) Calculate the relative abundance of bacterial genera in the sample. The relative abundance of oral flora refers to the ratio of the absolute abundance of a certain flora in a sample to the sum of the absolute abundances of all flora in the sample. Assume that the absolute abundance of a certain flora in all samples is R ij , the sample has m bacterial genera, then the relative abundance of the jth bacterial genus in the i-th sample is:
[0143] Here, according to the above method, the digital features of the samples in each set are converted from absolute abundance to relative abundance.
[0144] 3) Filter low-abundance genera. Filter out oral flora with a relative abundance of less than 0.01% and an occurrence frequency of less than 10% in set A, and obtain the combined characteristic genus T, T = {T1, T2, T3, ..., T n}. 72 bacteria were obtained.
[0145] 4) Obtain differential bacterial genus. Based on the Wilcoxon rank sum P value test, calculate the difference of bacterial genus T between set B and set I, and set the P value less than 0.05 to be significant difference, so as to obtain differential bacterial genus set D, D = {D1, D2, D3, ..., D n}. 51 bacteria were obtained.
[0146] 5) Obtain the core bacteria of the oral cavity. Calculate the fold change (FC) of each differential bacteria in the differential bacteria set D between the set B and the set I. Set the FC value of the i-th differential bacteria in set D to be FC Di , calculated as: FC Di =log2(I Di / B Di ), I Di is the average relative abundance of differential bacteria Di in set I, B Di is the average relative abundance of Di in set B. When the absolute value of FC value is greater than 0.5, the oral core bacteria combination C is obtained, C = {C1, C2, C3, ..., C n}. Among them, FC value>0.5 indicates that the bacteria has a clear advantage in set I (oral flora imbalance group); FC value<-0.5 indicates that the bacteria has a clear advantage in set B (oral flora balance group). Finally, 35 bacteria were obtained.
[0147] 6) Taking the above differential flora analysis that satisfies P<0.05 and abs(FC)>0.5, the abundance of core flora between the oral flora balance group and the oral flora imbalance group was compared as follows:
[0148] Example 2 Construction of an oral flora imbalance model
[0149] The oral flora imbalance model was established by machine learning using the 907 oral flora data in Example 1 and 35 core bacteria of oral diseases.
[0150] ① Data selection. According to the combination C obtained in Implementation Case 1, a random forest model that can specifically determine whether the oral cavity is imbalanced is established using the oral sample data of people with oral flora imbalance and oral flora balance. The oral sample data this time will be divided into 8:2 data, with 359 oral flora balance samples and 366 oral flora imbalance samples, a total of 752 sample data for model training data; 90 oral flora balance samples and 92 oral flora imbalance samples, a total of 182 sample data for model testing data;
[0151] ②Training model. The model was trained using the 10-fold cross validation method, specifically setting the random forest model parameter gradient n_estimators = [120, 140, 160, 180]; max_depth = [3, 5, 7, 9, 11]; max_features = ["log2", "sqrt"]; min_samples_leaf = [1, 2, 3, 4]; criterion = ['entropy', 'gini']. The python software sklearn.model_selection.GridSearchCV module was used to search for the best parameters, with a total of 4*5*2*4*2 = 320 parameter combinations. Under each parameter combination, the training set was divided into 10 sub-samples, one separate sub-sample was retained as the data for the validation model, and the other 9 sub-samples were used for training. Repeat 10 times, each sub-sample was validated once, and the average of 10 results was used as the final model result under this parameter combination. The total number of model training times was 3200 times (320*10).
[0152] ③Evaluation model
[0153] According to the training results, the optimal parameters of the random forest model are n_estimators=160; max_depth=11; max_features='log2'; min_samples_leaf=2; criterion='entropy'.
[0154] The accuracy of the model is 82.48%, and the AUC value of the ROC curve is 0.91.
[0155] In an embodiment of the present invention, through the method in the embodiment of the present invention, the flora set of the oral sample is collected, and the oral flora balance group and the oral flora imbalance group are divided according to the flora set of the oral sample; the relative abundance of the oral flora balance group is defined, and the filtered oral flora balance group is defined according to the filtering of the relative abundance of the oral flora balance group; the oral core flora is defined according to the filtered oral flora balance group and the oral flora imbalance group, so as to facilitate multi-dimensional control of the filtered oral flora balance group and the oral flora imbalance group, thereby clarifying the oral core flora and ensuring the accuracy of the oral core flora.
[0156] Furthermore, an imbalance model of oral flora is constructed based on the oral core flora; the imbalance coefficient is defined according to the imbalance model of oral flora and the oral core flora; the imbalance state of oral flora is defined according to the identification of the imbalance coefficient, so as to facilitate targeted state identification of the oral flora, thereby introducing the imbalance state of oral flora, realizing the identification and further control of the imbalance state of oral flora, and providing risk prediction for responding to the occurrence of oral flora imbalance.
[0157] See also Figure 8 , Figure 8 It is a schematic diagram of the structural composition of the system for identifying the imbalance state of oral flora in an embodiment of the present invention.
[0158] like Figure 8 As shown, a system for identifying an imbalance state of oral flora, the system for identifying an imbalance state of oral flora comprising:
[0159] A collection model 21 is used to collect a flora collection of an oral sample, and divide the oral flora into a balanced oral flora group and an unbalanced oral flora group according to the flora collection of the oral sample;
[0160] A filtering model 22, used to define the relative abundance of the oral flora balance group, and to define the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group;
[0161] A core flora model 23, used to define the oral core flora according to the filtered oral flora balance group and oral flora imbalance group;
[0162] An imbalance module 24, used to construct an imbalance model of oral flora based on the oral core flora;
[0163] An imbalance coefficient module 25 is used to define an imbalance coefficient according to an imbalance model of oral flora and an oral core flora;
[0164] The identification module 26 is used to define the imbalance state of the oral flora according to the identification of the imbalance coefficient.
[0165] See also Fig. 9 , refer to the following Fig. 9 The electronic device 40 according to this embodiment of the present invention will be described. Fig. 9 The electronic device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.
[0166] like Fig. 9 As shown, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).
[0167] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.
[0168] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .
[0169] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.
[0170] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
[0171] The electronic device 40 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 40, and / or any device that enables the electronic device 40 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic device 40 via the bus 43. It should be understood that although Fig. 9Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.
[0172] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure 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 flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.
[0173] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.
[0174] In addition, the above is a detailed introduction to the method and system for identifying the imbalance state of the oral flora provided in the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.
Claims
1. A method for identifying an imbalance state of oral flora, characterized in that: Applied to the identification scenario of imbalanced state of oral flora; The method for identifying the imbalance state of oral flora comprises: Collecting a flora collection of the oral sample, and dividing the oral flora into a balanced oral flora group and an unbalanced oral flora group according to the flora collection of the oral sample; defining the relative abundance of the oral flora balance group, and defining the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group; The core oral flora was defined based on the filtered oral flora balance group and oral flora imbalance group; Construct an imbalance model of oral flora based on the core oral flora; The imbalance coefficient is defined based on the imbalance model of oral flora and the core oral flora; The imbalance state of the oral flora is defined based on the identification of the imbalance coefficient.
2. The method for identifying an imbalance state of oral flora according to claim 1, characterized in that: The collecting of the bacterial flora set of the oral sample and dividing the oral flora balance group and the oral flora imbalance group according to the bacterial flora set of the oral sample include: Obtain oral microbiome 16S sequencing data of oral samples; The bacterial flora collection of oral samples was defined based on the oral microbiome 16S sequencing data of oral samples; Collecting a bacterial flora collection of the oral sample, at this time, defining the absolute abundance of different bacterial genera in the oral sample based on the bacterial flora collection of the oral sample; Match the corresponding status mark according to the bacterial flora set of the oral sample; Based on the bacterial flora collection and status markers of oral samples, the oral flora balance group and oral flora imbalance group were divided.
3. The method for identifying an imbalance state of oral flora according to claim 2, characterized in that: The method of defining the relative abundance of the oral flora balance group and defining the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group includes: The absolute abundance of different bacterial genera in oral samples was fixed; The relative abundance of the oral flora balance group was defined based on the absolute abundance of different bacterial genera in the oral samples and the oral flora balance group; The relative abundance threshold at which the collection is in an eligible state; Triggering the filtering of the relative abundance of the oral flora balance group based on the relative abundance of the oral flora balance group and the relative abundance threshold; In filtering the relative abundance of the oral flora balance group, oral flora with a relative abundance of less than 0.01% and an occurrence frequency of less than 10% in the oral flora balance group are filtered out to obtain a filtered oral flora balance group.
4. The method for identifying an imbalance state of oral flora according to claim 3, characterized in that: The method of defining the oral core flora according to the filtered oral flora balance group and oral flora imbalance group includes: Oral flora balance group after fixed-frame filtration; The oral flora balance group and oral flora imbalance group after correlation filtering; Trigger the corresponding difference comparison according to the filtered oral flora balance group and oral flora imbalance group, and output the difference parameters; Define the corresponding difference status according to the difference parameters and the difference status table; If the difference state is a significant difference state, a differential bacterial combination is constructed according to the filtered oral flora balance group and oral flora imbalance group; The core oral flora was defined based on the differential bacterial composition; Let the FC value of the i-th difference bacteria in the difference bacteria combination be FC Di , calculated as: FC Di =log2(I Di / B Di ), I Di is the average relative abundance of the differential bacteria Di in the oral flora imbalance group, B Di It is the average relative abundance of Di in the oral flora balance group after filtration; when the absolute value of FC value is greater than 0.5, the oral core flora is obtained.
5. The method for identifying an imbalance state of oral flora according to claim 4, characterized in that: The method of constructing an imbalance model of oral flora based on the oral core flora comprises: Determine the core flora of the oral cavity; The core oral flora was used as test data; Learning and training are performed based on the core oral flora and the corresponding learning model, and an imbalance model of the oral flora is constructed. At this time, the flora set based on the oral sample is divided into multiple data sets, and the multiple data sets are cross-validated and repeatedly validated until an imbalance model of the oral flora is constructed.
6. The method for identifying an imbalance state of oral flora according to claim 5, characterized in that: The method of constructing an imbalance model of oral flora based on the oral core flora further includes: Fitting the imbalance model of oral flora; Collect the corresponding ROC curve; The corresponding AUC value is matched based on the ROC curve; the recognition ability of the imbalance model of oral flora is defined according to the recognition of the AUC value.
7. The method for identifying an imbalance state of oral flora according to claim 6, characterized in that: The imbalance coefficient is defined according to the imbalance model of oral flora and the core flora of the oral cavity, including: Collect the imbalance model of oral flora; The imbalance model of oral flora and the core oral flora are related; The imbalance model of oral flora and oral core flora triggers multiple authentications and outputs the imbalance coefficient.
8. The method for identifying an imbalance state of oral flora according to claim 7, characterized in that: Defining the imbalance state of the oral flora according to the identification of the imbalance coefficient includes: Fixed frame imbalance coefficient; associated imbalance coefficients and imbalance coefficient identification table; The corresponding identification is triggered according to the imbalance coefficient and the imbalance coefficient identification table.
9. The method for identifying an imbalance state of oral flora according to claim 8, characterized in that: Defining the imbalance state of the oral flora according to the identification of the imbalance coefficient also includes: The imbalance state of the oral flora is defined based on the identification of the imbalance coefficient.
10. A system for identifying an imbalance state of oral flora, characterized in that: The system for identifying the imbalance state of oral flora is applied to the method for identifying the imbalance state of oral flora as claimed in any one of claims 1 to 9, and the system for identifying the imbalance state of oral flora comprises: A collection model, used to collect the flora collection of the oral sample, and divide the oral flora balance group and the oral flora imbalance group according to the flora collection of the oral sample; A filtering model is used to define the relative abundance of the oral flora balance group, and to define the filtered oral flora balance group according to the filtering of the relative abundance of the oral flora balance group; The core flora model is used to define the core flora of the oral cavity according to the filtered balanced and unbalanced oral flora groups; The imbalance module is used to construct an imbalance model of oral flora based on the core oral flora; An imbalance coefficient module, used to define the imbalance coefficient according to the imbalance model of oral flora and the core flora of the oral cavity; The identification module is used to define the imbalance state of the oral flora according to the identification of the imbalance coefficient.