Age assessment method, device, electronic device and computer-readable storage medium

Abstract

The present application provides an age assessment method, device, electronic device and computer-readable storage medium, the method comprising: obtaining microbial species information of a test object; determining that the test object contains at least one reference microorganism, and the number of gene sequences corresponding to each reference microorganism; determining a first ratio and / or a second ratio; the first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism, and the second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism and the fourth microorganism includes probiotics, and at least one includes neutral bacteria and / or harmful bacteria; based on the number of gene sequences corresponding to the reference microorganisms, the first ratio and / or the second ratio, the age of the test object is determined. The present application can accurately assess the age of the test object.

Description

Technical Field

[0001] The present application relates to the field of biotechnology, and in particular to an age assessment method, device, electronic device, and computer-readable storage medium. Background Art

[0002] Many organs in the human body, such as the intestines, stomach, skin, lungs, nose, etc., contain a wide variety of microorganisms. The characteristics of the microorganisms in the organs are closely related to human health. As the human body ages, the characteristics of the microorganisms contained in each organ will also change significantly.

[0003] Organ age can reflect the health status of the organ to a certain extent, and it is of great significance to the development of evaluating the health status of the organ and the health status of the human body. Therefore, how to accurately evaluate the age of the organ has become an important research topic in the field. Summary of the invention

[0004] The embodiments of the present application provide an age assessment method, device, electronic device and computer-readable storage medium, which are conducive to improving the accuracy of age assessment of organs.

[0005] In a first aspect, an embodiment of the present application provides an age assessment method, which can be applied to an age assessment device. The method includes: obtaining microbial species information of a test object, the microbial species information including the species type of microorganisms contained in the test object, and the number of gene sequences of microorganisms corresponding to each species type; based on the microbial species information, determining that the test object contains at least one reference microorganism, and the number of gene sequences corresponding to each reference microorganism; based on the microbial species information, determining a first ratio and / or a second ratio; wherein the first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism, and the second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes probiotics, and at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes neutral bacteria and / or harmful bacteria; the number of gene sequences corresponding to at least one reference microorganism, and the first ratio and / or the second ratio are input into an age assessment model to obtain an output result of the age assessment model; and the age of the test object is determined based on the output result of the age assessment model.

[0006] It can be seen that the present application can determine the age of the object to be tested based on the reference microorganisms contained in the object to be tested, the first ratio and / or the second ratio. Among them, the types and quantities of probiotics, neutral bacteria and harmful bacteria contained in the object to be tested, as well as the types and quantities of reference microorganisms, are used to evaluate the age of the organ corresponding to the object to be tested, which can more comprehensively determine the state of the microorganisms in the object to be tested, thereby improving the accuracy of the age assessment of the object to be tested.

[0007] In a possible implementation, the species type of the microorganism is used to indicate the taxonomic level to which the microorganism belongs. The taxonomic level to which the microorganism belongs includes one or more of the following: kingdom, phylum, class, order, family, genus, and species.

[0008] In one possible implementation, the gene sequences corresponding to the phylum classification level, the gene sequences corresponding to the genus classification level, and the gene sequences corresponding to the family classification level are determined from the microbial species information; the number of gene sequences of a first microorganism and the number of gene sequences of a second microorganism are determined from the gene sequences corresponding to the phylum classification level; the number of gene sequences of a third microorganism is determined from the gene sequences corresponding to the genus classification level; and the number of gene sequences of a fourth microorganism is determined from the gene sequences corresponding to the family classification level.

[0009] In a possible implementation, the first microorganism includes Firmicutes, the second microorganism includes Bacteroidetes, the third microorganism includes Bifidobacterium, and the fourth microorganism includes Enterobacteriaceae.

[0010] Bifidobacterium is a probiotic, while Bacteroidetes, Firmicutes and Enterobacteriaceae include probiotics, neutral bacteria and harmful bacteria. It can be seen that the first ratio and the second ratio can be used to more comprehensively evaluate the state of the microorganisms of the object to be tested, thereby more comprehensively evaluating the age of the object to be tested based on the state of the microorganisms.

[0011] In a possible implementation, the above-mentioned method of obtaining the microbial species information of the object to be tested may include: obtaining a gene sequence set of the object to be tested, the gene sequence set including multiple gene sequences; performing clustering processing on the gene sequence set to determine that the gene sequence set includes at least one type of gene sequence, the number of gene sequences belonging to each type of gene sequence, and the representative sequence of each type of gene sequence; based on the correspondence between the gene sequence and the species type, and the representative sequence of each type of gene sequence, determine the species type corresponding to each type of gene sequence, one type of gene sequence corresponds to one species type.

[0012] In one possible implementation, the number of species of at least one reference microorganism is K, where K is a positive integer; the method further includes: obtaining M training subjects and the age of each training subject; M>1 and M is an integer; determining a microbial species information set, the microbial species information set including the microbial species information of the M training subjects, the number of species types of microorganisms in the microbial species information set being N, where N is a positive integer; and determining K reference microorganisms from the microorganisms contained in the M training subjects based on the microbial species information set and the ages of the M training subjects.

[0013] In one possible implementation, based on a set of microbial species information and the ages of M training objects, a method for determining K reference microorganisms from the microorganisms contained in the M training objects may include: determining a first age coefficient for each of the N microorganisms; determining a microorganism from the N microorganisms, wherein the first age coefficient of a microorganism is greater than a first threshold; determining b microorganisms from the a microorganisms; the microbial species information of at least P training objects among the M training objects includes b microorganisms, and P is greater than a second threshold; determining K reference microorganisms from the b microorganisms, wherein the second age coefficients of the K reference microorganisms are greater than a third threshold; wherein a, b, and P are positive integers.

[0014] It can be seen that based on the above method, age-related reference microorganisms can be screened out layer by layer, thereby more accurately reflecting the age characteristics of the subjects to be tested.

[0015] In a second aspect, an embodiment of the present application provides an age assessment device, comprising an acquisition unit, a processing unit and an assessment unit. The acquisition unit is used to acquire microbial species information of the object to be tested, the microbial species information including the species type of the microorganism contained in the object to be tested, and the number of gene sequences of the microorganism corresponding to each species type;

[0016] A processing unit is used to determine, based on the microbial species information, that the object to be tested contains at least one reference microorganism and the number of gene sequences corresponding to each reference microorganism; based on the microbial species information, determine a first ratio and / or a second ratio; wherein the first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism, and the second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes probiotics, and at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes neutral bacteria and / or harmful bacteria,

[0017] The evaluation unit is used to input the number of gene sequences corresponding to at least one reference microorganism, as well as the first ratio and / or the second ratio, into the age evaluation model to obtain an output result of the age evaluation model; and determine the age of the object to be tested based on the output result of the age evaluation model.

[0018] In one possible manner, the species type of a microorganism is used to indicate the taxonomic level to which the microorganism belongs, and the taxonomic level to which the microorganism belongs includes one or more of the following: kingdom, phylum, class, order, family, genus, and species.

[0019] In one possible embodiment, the processing unit is also used to determine the gene sequence corresponding to the phylum classification level, the gene sequence corresponding to the genus classification level, and the gene sequence corresponding to the family classification level from the microbial species information; determine the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism from the gene sequence corresponding to the phylum classification level; determine the number of gene sequences of the third microorganism from the gene sequence corresponding to the genus classification level; and determine the number of gene sequences of the fourth microorganism from the gene sequence corresponding to the family classification level.

[0020] In one possible embodiment, the first microorganism includes Firmicutes, the second microorganism includes Bacteroidetes, the third microorganism includes Bifidobacterium, and the fourth microorganism includes Enterobacteriaceae.

[0021] In one possible manner, the acquisition unit is also used to obtain a gene sequence set of the object to be tested, where the gene sequence set includes multiple gene sequences; clustering is performed on the gene sequence set to determine that the gene sequence set includes at least one category of gene sequences, the number of gene sequences belonging to each category of gene sequences, and representative sequences of each category of gene sequences; based on the correspondence between gene sequences and species types, and representative sequences of each category of gene sequences, the species types corresponding to each category of gene sequences are determined, where one category of gene sequences corresponds to one species type.

[0022] In one possible manner, the number of species of at least one reference microorganism is K, where K is a positive integer; the acquisition unit is further used to acquire M training objects and the age of each training object; M>1 and M is an integer; the processing unit is further used to determine a microbial species information set, the microbial species information set includes the microbial species information of the M training objects, the number of species types of microorganisms in the microbial species information set is N, and N is a positive integer; based on the microbial species information set and the ages of the M training objects, K reference microorganisms are determined from the microorganisms contained in the M training objects.

[0023] In one possible embodiment, the processing unit is further used to determine the first age coefficient of each of N types of microorganisms; determine a type of microorganism from the N types of microorganisms, and the first age coefficient of a type of microorganism is greater than a first threshold; determine b type of microorganism from a type of microorganism; the microbial species information of at least P training objects among the M training objects includes b type of microorganism, and P is greater than a second threshold; determine K types of reference microorganisms from the b types of microorganisms, and the second age coefficients of the K types of reference microorganisms are greater than a third threshold; wherein a, b, and P are positive integers.

[0024] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory for storing programs; a processor for executing the programs stored in the memory, and when the programs are executed by the processor, the processor executes the method in the first aspect and any possible implementation of the first aspect.

[0025] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor, the processor executes the method in the first aspect and any possible implementation of the first aspect.

[0026] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes: instructions or computer programs; when the instructions or the computer programs are executed, the method in the first aspect and any possible implementation method in the first aspect is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of a flow chart of an age assessment method provided in an embodiment of the present application;

[0028] Figure 2 A flowchart of a method for constructing an age assessment model provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the structure of an age assessment device provided in an embodiment of the present application;

[0030] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0032] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0033] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] The terms "component", "module", "system", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program and / or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on a computer and / or distributed between two or more computers. In addition, these components may be executed from various computer-readable media having various data structures stored thereon. Components may, for example, communicate through local and / or remote processes according to signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system and / or a network, such as the Internet interacting with other systems through signals).

[0036] First, some terms in this application are explained to facilitate understanding by those skilled in the art.

[0037] 1. The hierarchy of biological classification

[0038] In biological taxonomy, organisms can be classified hierarchically from large to small through seven main classification levels: kingdom, phylum, class, order, family, genus, and species.

[0039] 2. Gut Microbes

[0040] Gut microbes refer to the collection of all microorganisms in the intestine, including bacteria, archaea, fungi (such as yeast and mold), viruses, and protists. These microorganisms form a complex ecosystem in the intestine, which is closely related to the health of the host (i.e., humans or other animals). For example, as the human body ages, the diversity of intestinal microorganisms may decrease, and the abundance (microbial abundance) of some intestinal microorganisms may increase or decrease. These changes can affect food digestion, nutrient absorption, immune system function, and many other aspects. Among them, the abundance of a certain intestinal microorganism is used to describe the number or density of this intestinal microorganism in the intestine.

[0041] In this application, intestinal microorganisms including bacteria in the intestine are used as an example for explanation. The bacteria in the intestine can be called intestinal bacteria.

[0042] 3. Intestinal bacteria

[0043] Intestinal bacteria refer to bacteria that exist in the human intestine and are interdependent with the human body for a long time. There are many types of intestinal bacteria and their number is huge. In this application, the intestinal bacteria in the human intestine can be classified based on the above seven classification levels.

[0044] For example, please refer to Table 1 for examples of the kingdom, phylum, class, order, family, genus, and species to which intestinal bacteria belong based on the seven classification levels.

[0045] For example, as shown in Table 1, the "genus" to which Lactobacillus delbrueckii belongs is Lactobacillus, the "family" to which it belongs is Lactobacillaceae, the "order" to which it belongs is Lactobacilales, etc. It can be seen that when a certain taxonomic level to which a certain intestinal bacteria belongs is known, a taxonomic level higher than the taxonomic level to which the intestinal bacteria belongs can be determined.

[0046] Table 1 Examples of intestinal bacteria

[0047] boundary Door Outline Head division Genus kind Bacteria Firmicutes Bacillus Lactobacillales Lactobacillusaceae Lactobacillus Lactobacillus delbrueckii Bacteria Actinobacteria Actinomycetes Bifidobacteriales Bifidobacteriaceae Bifidobacterium Bifidobacterium bifidum Bacteria Firmicutes Bacillus Bacilales Bacilaceae Bacillus Bacillus thuringiensis

[0048] Among them, if the intestinal bacteria are classified according to the classification level of "species", each intestinal bacteria can be called a species, such as Lactobacillus delbrueckii, Bifidobacterium bifidum, Bacillus thuringiensis, etc. in Table 1. Correspondingly, if the intestinal bacteria are classified according to the classification level of "genus", intestinal bacteria of different genera can be divided into different genera, such as Lactobacillus genus, Bifidobacterium genus, etc. shown in Table 1.

[0049] In addition, flora is also a term commonly used to describe intestinal bacteria. Flora refers to a general term for a variety of bacteria that can interact with each other in a certain environment, also known as bacterial community or bacterial colony. In this application, intestinal flora refers to a community composed of a variety of intestinal bacteria in the human body.

[0050] Intestinal flora has an important impact on human health, affecting the body's nutrient absorption, antibacterial, metabolism, and immune enhancement. If the intestinal flora is unbalanced, it may lead to the occurrence of a variety of intestinal diseases. Therefore, studying intestinal flora is crucial to maintaining human health.

[0051] 4. Organ age

[0052] Organ age refers to the age status of various organs in the human body relative to their normal physiological functions and developmental status.

[0053] Some organs of the human body, such as the intestines, stomach, skin, lungs, and nose, contain a variety of microorganisms. The characteristics of these microorganisms are closely related to human health. As the human body ages, the characteristics of the microorganisms contained in each organ will also change significantly. In other words, the age of the organ is closely related to the microorganisms contained in the organ.

[0054] Organ age can reflect the health status of the organ to a certain extent, and it is of great significance to the development of the evaluation of organ health status, human health status, etc. For example, the intestinal age can be used to understand the health status of the intestine, and further, the intestinal age can be used to evaluate the health status of the human body.

[0055] 5. Gut age

[0056] Gut age, also known as intestinal age, is an indicator used to measure the balance of various bacteria in the intestine. Gut age can be used to predict the aging state of the intestine and the incidence of modern life diseases, thereby assessing a person's health status.

[0057] The embodiments of the present application provide an age assessment method, device, electronic device and computer-readable storage medium for determining organ age and improving the accuracy of assessing organ age, thereby facilitating research on organ health status and human health status.

[0058] For example, see Figure 1 , Figure 1 A flowchart of an age assessment method provided in an embodiment of the present application.

[0059] S101, obtaining the microbial species information of the object to be tested.

[0060] The object to be tested refers to an organ. The microbial species information of the object to be tested can be obtained from a sample of the organ, such as a content sample or a surface sample. The sample of the organ refers to a microbial community sample collected from the organ, which contains at least one microorganism and can reflect the actual state of the microorganisms contained in the organ.

[0061] For example, if the age of the stomach needs to be evaluated, the object to be tested is the stomach. The microbial species information of the stomach can be obtained through gastric mucosal samples, gastric juice samples and other gastric content samples. Among them, gastric mucosa and gastric juice are components of the stomach and contain a variety of microorganisms. Gastric mucosal samples or gastric juice samples can be collected through gastroscopy and other methods.

[0062] For another example, if the intestinal age is evaluated, the object to be tested is the intestine. Information on intestinal microbial species can be obtained from intestinal content samples. Among them, intestinal contents are mainly composed of undigested food residues, water, intestinal cells, and a large number of intestinal microorganisms, and contain a variety of effective information related to intestinal flora, which is important for understanding human health status, diagnosing diseases, and studying the functions and changes of intestinal flora. For example, through intestinal content samples, the types and quantities of various bacteria in the intestine can be analyzed to understand the diversity, stability and function of the intestinal flora. Therefore, through a person's intestinal content sample, their intestinal microorganisms can be studied, thereby realizing the assessment of intestinal age.

[0063] The microbial species information of the object to be tested includes the species types of microorganisms contained in the object to be tested, and the number of gene sequences of microorganisms corresponding to each species type. For example, when the object to be tested is the intestine, the microbial species information of the object to be tested may refer to the species information of intestinal microorganisms, including the species types of intestinal microorganisms contained in the intestinal content sample, and the number of gene sequences of intestinal microorganisms corresponding to each species type.

[0064] The species type of microorganisms can be classified according to any one of the seven classification levels: kingdom, phylum, class, order, family, genus, and species. In actual research scenarios, the classification level can be determined according to the object to be tested, and this application does not limit this.

[0065] Exemplarily, if the microorganisms of the object to be tested are classified according to the classification level of "species", the species type of the microorganisms is each "species". In the case of classification according to the classification level of "species", for example, if the object to be tested is the intestine, the species type of intestinal microorganisms can be called bacterial species, and intestinal bacterial species can include various bacterial species such as Lactobacillus bulgaricus and Bifidobacterium bifidum. Optionally, in the present application, the microorganisms of the object to be tested can be classified according to the classification level of "species", so that more detailed information of the microorganisms can be determined, which is helpful for a more detailed study of the microorganisms of the object to be tested.

[0066] The gene sequence of a microorganism refers to a continuous nucleotide sequence in a deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) molecule that is used to encode one or more specific proteins or RNA molecules.

[0067] In a possible implementation, the method for obtaining the microbial species information of the object to be tested may include the following steps: first, a gene sequence set of the object to be tested is obtained, and the gene sequence set includes multiple gene sequences. Then, the gene sequence set is clustered to determine that the gene sequence set includes at least one type of gene sequence, the number of gene sequences belonging to each type of gene sequence, and the representative sequence of each type of gene sequence. Furthermore, based on the correspondence between the gene sequence and the species type, and the representative sequence of each type of gene sequence, each type of gene sequence is annotated with species, so that the species type corresponding to each type of gene sequence can be determined, and one type of gene sequence corresponds to one species type.

[0068] Exemplarily, the species information of the object to be tested may be as shown in Table 2.

[0069] Table 2 Schematic diagram of microbial species information

[0070]

[0071] Optionally, a primer can be used to sequence the object to be tested, so as to obtain a gene sequence set of the object to be tested. In an embodiment of the present application, through primers, it is theoretically possible to activate the amplification of all gene sequences contained in the object to be tested to form a gene sequence set with more DNA sequences, which is convenient for statistical analysis. Exemplarily, the amplification multiple can be 2 to the power of 10, etc. In theory, the gene sequence set contains all gene sequences obtained after the object to be tested is amplified by gene sequence. Optionally, the gene sequencing method can be a 16S rDNA sequencing method in macrogene sequencing, or it can be other sequencing methods that can achieve the same effect, and the present application does not limit this.

[0072] Optionally, the DADA2 algorithm can be used to cluster the gene sequence set. Exemplarily, the DADA2 algorithm can be used to calculate the similarity between every two gene sequences in the gene sequence set, and similar gene sequences can be clustered into one category according to a certain threshold. This process will continue to iterate until all gene sequences in the gene sequence set are assigned to appropriate gene categories, and a clustering result can be obtained. Among them, the clustering result may include at least one category of gene sequences included in the gene sequence set, the number of gene sequences belonging to each category of gene sequences, and representative sequences of each category of gene sequences.

[0073] Optionally, the correspondence between the gene sequence and the species type can be determined from a reference species annotation database. The reference species annotation database can be constructed based on public databases such as Silva and NCBI. For example, if the object to be tested is the intestine, the reference gene sequence related to the object to be tested and the species annotation information corresponding to each reference gene sequence (i.e., the kingdom, phylum, class, order, family, genus, and species to which each reference gene sequence belongs) can be downloaded from a public database. The reference gene sequence needs to be a full-length 16S sequence, and the gene sequence of the species with a genome sequence retained is preferably selected from the public database as the reference gene sequence.

[0074] Among them, the genome sequence refers to the complete DNA sequence of all the genetic information of an organism. It includes the DNA sequences of all genes of an organism, as well as non-coding DNA sequences. The gene sequence refers to the DNA sequence or RNA sequence of a specific gene.

[0075] Exemplarily, when the object to be tested is the intestine, the reference species annotation database can be an intestinal genome database. The intestinal genome database contains genome sequences, species annotation information, gene function annotation information, metabolic pathway information, and other relevant biological data of intestinal microorganisms from different human intestines. From the intestinal genome data, the correspondence between gene sequences and species types can be read, that is, the species type corresponding to each gene sequence.

[0076] Optionally, a machine learning algorithm can be used to compare representative sequences of various gene sequences with a reference species annotation database, thereby achieving species annotation for each type of gene sequence. For example, the classify-sklearn algorithm of the naive Bayes classifier can be used to accomplish this.

[0077] S102, based on the microbial species information, determining whether the object to be tested contains at least one reference microorganism and the number of gene sequences corresponding to each reference microorganism.

[0078] The reference microorganisms include one or more microorganisms associated with the age of the organ. For example, if the object to be tested is the intestine, the reference microorganisms may be called marker intestinal bacteria, indicating intestinal bacteria species associated with the age of the intestine. The reference microorganisms may be pre-set, and the types of reference microorganisms may include K species, where K is a positive integer

[0079] Optionally, the K reference microorganisms may be K microorganisms selected based on any one of the seven classification levels. For example, they may be K microorganisms of different “genuses” or K microorganisms of different “species”. Figure 2 The description in S206 shown.

[0080] The object to be tested contains at least one reference microorganism, which can be understood as the sample of the object to be tested contains at least one reference microorganism. Exemplarily, when the object to be tested is the intestine, assuming that the preset reference microorganisms include 5 species of bacteria ae, then the intestinal content sample of the object to be tested contains at least one species of bacteria ae.

[0081] For ease of description, "at least one reference microorganism" is hereinafter referred to as T reference microorganisms, where T is a positive integer.

[0082] S103, determining a first ratio and / or a second ratio based on the microbial species information.

[0083] The first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism. The second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism. At least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes probiotics; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes neutral bacteria and / or harmful bacteria.

[0084] Among them, probiotics, neutral bacteria and harmful bacteria are the three main types of bacteria in intestinal microorganisms. Probiotics can also be called beneficial bacteria, which refers to the genus of bacteria that has a beneficial effect on the health of the host. A probiotic genus contains at least one probiotic species, and the probiotic genus includes Bacteroides, Eubacterium, and Bifidobacterium. Neutral bacteria, also known as conditional pathogens, refer to bacteria that are harmless to health under normal conditions, but may cause health problems under specific conditions (such as dysbiosis, decreased human immunity, etc.). For example, the neutral genus may include the genus Escherichia coli. Harmful bacteria refers to the general term for bacteria that can cause harm to health. For example, harmful bacteria may include Listeria, etc.

[0085] In a possible implementation, the gene sequence corresponding to the phylum classification level, the gene sequence corresponding to the genus classification level, and the gene sequence corresponding to the family classification level can be determined from the microbial species information. Further, the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism can be determined from the gene sequence corresponding to the phylum classification level; the number of gene sequences of the third microorganism can be determined from the gene sequence corresponding to the genus classification level; and the number of gene sequences of the fourth microorganism can be determined from the gene sequence corresponding to the family classification level.

[0086] Optionally, the first microorganism includes firmicutes, the second microorganism includes bacteroidetes, the third microorganism includes bifidobacterium, and the fourth microorganism includes enterobacteriaceae. Based on this, the first ratio can be the ratio between the number of gene sequences of firmicutes and the number of gene sequences of bacteroidetes, which can be referred to as the firmicutes / bacteroidetes index. The second ratio is the ratio between the number of gene sequences of bifidobacterium and the number of gene sequences of enterobacteriaceae, which can be referred to as the bifidobacterium / enterobacteriaceae index.

[0087] Among them, Bifidobacterium is one of the clear probiotics, while Bacteroidetes, Firmicutes and Enterobacteriaceae need to be judged as probiotics based on their specific genus or species. For example, in Firmicutes, Bifidobacterium is a probiotic, Streptococcus, Lactobacillus and others are neutral bacteria, and Listeria is a harmful bacteria.

[0088] Some studies have found that as people age, their intestinal age usually increases. As age changes, the number of Firmicutes in the intestine may gradually increase, while the number of Bacteroidetes may gradually decrease, and the first ratio will increase with age. Also, as age increases, the number of Bifidobacteria in the intestine may gradually decrease, while the number of Enterobacteriaceae may gradually increase, and the second ratio will decrease with age. Therefore, it can be said that the first ratio and the second ratio are closely related to the intestinal age, and the intestinal age can be measured by the first ratio and the second ratio of the intestine.

[0089] In a possible implementation, the species richness index and community diversity index of the object to be tested can also be determined based on the microbial species information. The species richness index may include the Chao1 index, and the community diversity index may include the Shannon index. Among them, the species richness index, the community diversity index, the first ratio and the second ratio can be referred to as core indicators for evaluating the state of the flora. Furthermore, the state of the microorganisms contained in the object to be tested can be more comprehensively evaluated through the above-mentioned core indicators, so that the age of the object to be tested can be more comprehensively evaluated based on the state of the microorganisms contained in the object to be tested, thereby improving the accuracy of age assessment.

[0090] The following uses the intestine as an example to explain how to obtain the Chao1 index and the Shannon index.

[0091] Among them, Chao1 index is related to the number of intestinal bacteria species. Shannon index is related to the number of intestinal bacteria species contained in the intestinal content sample and the uniformity of the distribution of individual species. With the increase of age, Chao1 index and / or Shannon index in intestinal content samples will change significantly. Chao1 index and Shannon index can be used to assess the age of the subject to be tested.

[0092] For example, Chao1 index (S Chao1 ) is calculated as follows:

[0093] S Chaol =S obs +S uobs Formula 1

[0094]

[0095] Among them, S obsis the number of observed intestinal bacteria species, that is, the number of intestinal bacteria species included in the microbial species information. is the estimated number of unobserved intestinal bacteria species. T1 is the number of species types of intestinal bacteria with a gene sequence of 1 in the microbial species information, and T2 is the number of species types of intestinal bacteria with a gene sequence of 2 in the microbial species information.

[0096] Shannon index (H Shannon ) is calculated as follows:

[0097]

[0098] Where i represents the i-th species among all species types included in the microbial species information, and the value of i is greater than or equal to 1 and less than or equal to S obs An integer; n i is the number of gene sequences of the i-th species in the microbial species information; W is the total number of gene sequences included in the microbial species information; is the ratio of the gene sequences of the i-th species to the total number of gene sequences.

[0099] S104, inputting the number of gene sequences corresponding to each reference microorganism contained in the object to be tested, as well as the first ratio and / or the second ratio, into the age assessment model to obtain an output result of the age assessment model.

[0100] Among them, the number of gene sequences corresponding to each reference microorganism (i.e., the T reference microorganisms mentioned above) contained in the object to be tested, as well as the first ratio and / or the second ratio, are respectively vectorized to obtain the number of gene sequences corresponding to each reference microorganism, and the input feature vectors corresponding to the first ratio and / or the second ratio.

[0101] The above-mentioned multiple input feature vectors are input into the age assessment model to obtain the output result of the age assessment model. The output result of the age assessment model is an output result in the form of a feature vector, which represents the feature vector corresponding to the age of the object to be measured.

[0102] Optionally, the age assessment model may include one or more models.

[0103] In a possible implementation, the age assessment model may include a first model. Optionally, the first model may be a multiple linear regression model. The output result of the first model is the output result of the age assessment model. Through the multiple linear regression model, the mapping relationship between the feature vector corresponding to the age of the object to be measured and the above-mentioned input feature vectors can be described more accurately. Based on this, when the core indicators of the object to be measured are known, the age of the object to be measured can be accurately determined through the first model.

[0104] Exemplarily, the formula corresponding to the first model can be expressed as:

[0105] Y=β0+β1*X1+β2*X2+…+β n *X n Formula 4

[0106] Among them, Y is the output result, which represents the feature vector corresponding to the age of the object to be tested; β0 is the intercept, where β n For X n The regression coefficient (slope) of X1, X2, X n represents multiple input feature vectors, including the number of gene sequences corresponding to the K reference microorganisms, the first ratio, and the input feature vectors corresponding to the second ratio. Optionally, the multiple input feature vectors may also include the Chao1 index and Shannon index of the object to be tested.

[0107] In a possible implementation, the age assessment model may include a first model and a second model, and the output result of the age assessment model includes a first output result and a second output result. The number of gene sequences corresponding to T reference microorganisms, as well as the first ratio and / or the second ratio, are input into the first model to obtain a first output result. The number of gene sequences corresponding to T reference microorganisms, as well as the first ratio and / or the second ratio, are input into the second model to obtain a second output result. Both the first output result and the second output result are output results in vector form. Optionally, the second model may be a random forest regression model.

[0108] It can be seen that using the first model and the second model to assess the age of the subject is beneficial to reducing the possible errors in age assessment using a single model.

[0109] The age assessment model is a model constructed based on multiple training objects. Optionally, the construction process of the age assessment model can be found in Figure 2 The process shown will not be repeated here.

[0110] S105, determining the age of the subject to be measured based on the output result of the age assessment model.

[0111] Optionally, the output result of the age assessment model is converted into a natural language or other form to determine the age of the subject to be tested.

[0112] For example, if the age assessment model includes a first model and a second model, first, the first output result and the second output result are respectively converted to obtain the first age and the second age corresponding to the first model. Further, the mean of the first age and the second age is calculated, so that the obtained mean can be determined as the age of the subject to be measured.

[0113] It can be seen that through the embodiments of the present application, the microbial species information of the object to be tested can be determined, and based on the microbial species information, the type and quantity of the reference microorganisms included in the object to be tested, as well as the first ratio and / or the second ratio of the object to be tested can be determined, so that the age of the object to be tested can be accurately evaluated. Moreover, through the first ratio and the second ratio, the probiotics, neutral bacteria and harmful bacteria contained in the object to be tested can be used to evaluate the age, which can improve the accuracy of the age evaluation, thereby facilitating the evaluation of the health status of the organs corresponding to the object to be tested and the health status of the human body.

[0114] Next, a method for constructing an age assessment model provided in an embodiment of the present application is introduced.

[0115] For example, taking the construction of an age assessment model for assessing intestinal age as an example, Figure 2 A schematic flow chart of a method for constructing an age assessment model provided in an embodiment of the present application.

[0116] like Figure 2 As shown, the method may include but is not limited to the following steps:

[0117] S201, construct a reference species annotation database.

[0118] For details, please refer to Figure 1 This corresponds to the description in S101 in the embodiment.

[0119] S202, obtaining a training data set of healthy people, where the training data set includes intestinal content samples of M training subjects and the age of each training subject.

[0120] The training object is the intestine of a healthy person. In this application, the actual age of a healthy person can be regarded as the intestinal age. Based on this, the actual age of the healthy person to whom the training object belongs can be used to represent the age of the training object, that is, the intestinal age.

[0121] Wherein, M is a positive integer. It is understandable that a large number of different intestinal content samples can help the age assessment model to better learn the distribution of data, thereby helping to improve the accuracy, credibility and other properties of the age assessment model. Therefore, in this application, the value of M can be a larger value such as 1000, 2000, etc.

[0122] S203, obtaining a gene sequence training set for each training object.

[0123] The gene sequence training set includes M gene sequence sets of training objects, and each gene sequence set includes one or more gene sequences.

[0124] Specifically, based on the same principle, the method of obtaining the gene sequence training set of the training object is the same as the method of obtaining the gene sequence set of the object to be tested in S101, which will not be repeated here.

[0125] Optionally, after obtaining the gene sequence training set of each training object, the gene sequence training set can be clustered to determine at least one type of gene sequence included in the gene sequence training set, the number of gene sequences belonging to each type of gene sequence, and the representative sequence of each type of gene sequence.

[0126] S204, determining the microbial species information of the training object based on the reference species annotation database and the gene sequence training set.

[0127] Among them, based on the reference species annotation database, the gene sequence training set can be annotated with species. This can be understood as determining the species type corresponding to each type of gene sequence in the gene sequence training set based on the correspondence between gene sequences and species types, as well as the representative sequences of each type of gene sequence. One type of gene sequence corresponds to one species type.

[0128] The microbial species information of the training object includes the species types of microorganisms contained in the training object and the number of gene sequences of microorganisms corresponding to each species type. Optionally, the microbial species information of M training objects can be called a microbial species information set, and the number of species types of microorganisms in the microbial species information set is N, indicating that the M training objects contain a total of N intestinal microorganisms. Where N is a positive integer.

[0129] Specifically, the specific implementation method of determining the microbial species information of the training object can be found in Figure 1 This corresponds to the description of S101 in the embodiment.

[0130] S205: Determine a first ratio and a second ratio of the training object based on the microbial species information of the training object.

[0131] For details, please refer to Figure 1 The description of the first ratio and the second ratio in S103 in the corresponding embodiment will not be repeated here.

[0132] It should be noted that the execution order between S205 and S206 can be arbitrary, and this application does not limit this. For example, S205 can be executed first, and then S206; S206 can be executed first, and then S205; or S205 and S206 can be executed at the same time.

[0133] S206, determining K reference microorganisms based on the microbial species information of the training objects and the age of each training object.

[0134] Wherein, K is a positive integer.

[0135] Exemplary methods for determining reference microorganisms may include, but are not limited to, the following steps:

[0136] A. Determine a first age coefficient of each of N microorganisms, and determine a type of microorganism from the N types of microorganisms, where the first age coefficient of a type of microorganism is greater than a first threshold.

[0137] Optionally, the first age coefficient may be %IncMSE. For example, a regression model of the species and age contained in the intestinal content sample corresponding to the intestine is constructed by a random forest algorithm, and the %IncMSE of each microorganism may be determined based on the regression model. From N types of microorganisms, a type of microorganism whose %IncMSE is greater than a first threshold is screened out. In this way, the selected a type of microorganism has a strong correlation with age.

[0138] B. From type a microorganism, identify type b microorganism.

[0139] Among them, the microbial species information of at least P training objects among the M training objects includes b kinds of microorganisms, and P is greater than the second threshold. In other words, at least P training objects all include b kinds of microorganisms. Among them, a, b, and P are positive integers.

[0140] For example, assuming that M=100 and the second threshold is 60, then among 100 training subjects, the intestinal content samples of at least 60 training subjects all include the above-mentioned b types of microorganisms. This is helpful to avoid the situation where a certain microorganism only exists in the intestinal content samples of a small number of training subjects, so as to eliminate accidental errors.

[0141] Optionally, a local interpretation algorithm SHAP can be used to interpret each of the b types of microorganisms to remove some species that differ greatly in different training objects, and only retain microorganisms that play a role in intestinal content samples greater than a second threshold.

[0142] C. From b types of microorganisms, determine K types of reference microorganisms.

[0143] Among them, the second age coefficient of K reference microorganisms is greater than the third threshold.

[0144] Optionally, the second age coefficient of B kinds of microorganisms can be calculated by the Spearman algorithm. The second age coefficient includes the Spearman correlation coefficient. Accordingly, the third threshold value may include a correlation coefficient threshold value (represented by r0). For example, the correlation coefficient threshold value r0=0.3 can be set. In other words, the second age coefficient of K kinds of reference microorganisms is greater than the third threshold value. It can be understood that the absolute value of the correlation coefficient (represented by r) of each microorganism in the K kinds of reference microorganisms is greater than the third threshold value. For example, the correlation coefficient of K kinds of microorganisms satisfies the following condition: |r|>0.3.

[0145] Optionally, a significance level threshold (represented by p0) can be pre-set, and based on the correlation coefficient of each microorganism in the b microorganisms, the significance level value (represented by p) of each microorganism is determined. From the b microorganisms, K microorganisms are screened out whose absolute value of the correlation coefficient is greater than the third threshold (such as |r|>0.3) and whose significance level is less than the significance level threshold (such as p<0.05). In this way, each microorganism in the K microorganisms can be regarded as a microorganism with a significant correlation with age. In other words, the K microorganisms need to meet the following conditions: |r|>r0, and p<p0.

[0146] Based on this, it can be indicated that the selected K microorganisms are the K microorganisms with the strongest correlation with intestinal age among all intestinal microorganisms contained in the M intestinal content samples. Therefore, the above K microorganisms can be determined as K reference microorganisms.

[0147] Optionally, the K kinds of microorganisms may be K kinds of intestinal bacteria species, K kinds of intestinal bacteria genera, etc.

[0148] For example, Table 3 is an example of reference microorganisms provided in this application. The reference microorganisms shown in Table 3 are intestinal bacteria genera screened at the classification level of "genus", which can be called reference genera. The types and quantities of reference microorganisms shown in Table 3 are only used as examples and do not constitute a limitation on the embodiments of this application.

[0149] Optional, Figure 1 The T reference microorganisms in S102 and S104 in the corresponding embodiments may include one or more of the K microorganisms, 1≤T≤K.

[0150] Table 3 Examples of reference microorganisms

[0151]

[0152] S207, determining the number of gene sequences corresponding to each reference microorganism contained in each training object.

[0153] Among them, for each training object among the M training objects, such as training object 1, based on the microbial species information of training object 1, it can be determined which reference microorganisms training object 1 includes and the number of gene sequences corresponding to each reference microorganism included.

[0154] S208, vectorizing the number of gene sequences corresponding to each reference microorganism contained in each training object, and the first ratio and the second ratio of each training object to obtain a training input vector set.

[0155] The training input vector set includes an input vector corresponding to each training object. The input vector corresponding to each training object includes a feature vector corresponding to the number of gene sequences corresponding to each reference microorganism contained in the training object, a feature vector corresponding to the first ratio, and a feature vector corresponding to the second ratio.

[0156] Optionally, the input vector corresponding to each training object may also include a feature vector corresponding to the Chao1 index of the training object and a feature vector corresponding to the Shannon index of the training object.

[0157] S209, performing vectorization processing on the age of each training object to obtain a training output vector set.

[0158] The training output vector set includes a feature vector corresponding to the age of each training object.

[0159] S210, constructing a first model based on the training input vector set, the training output vector set and the first initial model.

[0160] By training the input vector set and the output vector set, the first initial model is trained to obtain the first model, wherein the first initial model may be a regression model.

[0161] Optionally, the first initial model may be a multiple linear regression model. By training the input vector set and the output vector set, the initial multiple linear regression model is trained to obtain the first model. Exemplarily, the first model may be represented by the above formula 4.

[0162] S211, constructing a second model based on the training input vector set, the training output vector set and the second initial model.

[0163] Based on the training input vector set and the training output vector set, the second initial model can be trained, so that the second model can be determined.

[0164] Optionally, the second initial model can be a random forest regression model. The random forest regression model is an integrated machine learning algorithm based on decision trees. The random forest regression model makes predictions by constructing multiple decision trees, each of which is trained on a random subset. The random subset refers to a subset of training data in the training data set, including intestinal content samples of some training subjects in the training data set, and the age of the training subjects.

[0165] S212: Determine an age assessment model based on the first model and the second model.

[0166] The age assessment model may include a first model and a second model, and the output result of the age assessment model may include a first output result and a second output result.

[0167] Optionally, the output result of the age assessment model may be a mean of the first output result and the second output result.

[0168] It can be seen that the two age assessment models constructed in this application based on the first ratio, the second ratio and the reference microorganism can improve the accuracy of the age assessment model in estimating age. Using the first model and the second model to assess the age of the subject to be tested is conducive to reducing the possible errors in age assessment using a single model.

[0169] An age assessment device provided in an embodiment of the present application is introduced below.

[0170] See also Figure 3 , is a schematic diagram of the structure of an age assessment device provided in an embodiment of the present application. Figure 3 As shown, the age assessment device 300 may include an acquisition unit 310 , a processing unit 320 and an assessment unit 330 .

[0171] The acquisition unit 310 is used to acquire the microbial species information of the object to be tested, where the microbial species information includes the species types of the microorganisms contained in the object to be tested and the number of gene sequences of the microorganisms corresponding to each species type.

[0172] The processing unit 320 is used to determine, based on the microbial species information, that the object to be tested contains at least one reference microorganism and the number of gene sequences corresponding to each reference microorganism; based on the microbial species information, determine a first ratio and / or a second ratio; wherein the first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism, and the second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes probiotics, and at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes neutral bacteria and / or harmful bacteria,

[0173] The evaluation unit 330 is used to input the number of gene sequences corresponding to at least one reference microorganism, as well as the first ratio and / or the second ratio, into the age evaluation model to obtain the output result of the age evaluation model; and determine the age of the object to be tested based on the output result of the age evaluation model.

[0174] In one possible manner, the species type of a microorganism is used to indicate the taxonomic level to which the microorganism belongs, and the taxonomic level to which the microorganism belongs includes one or more of the following: kingdom, phylum, class, order, family, genus, and species.

[0175] In one possible manner, the processing unit 320 is also used to determine, from the microbial species information, the gene sequence corresponding to the phylum classification level, the gene sequence corresponding to the genus classification level, and the gene sequence corresponding to the family classification level; determine the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism from the gene sequence corresponding to the phylum classification level; determine the number of gene sequences of the third microorganism from the gene sequence corresponding to the genus classification level; and determine the number of gene sequences of the fourth microorganism from the gene sequence corresponding to the family classification level.

[0176] In one possible embodiment, the first microorganism includes Firmicutes, the second microorganism includes Bacteroidetes, the third microorganism includes Bifidobacterium, and the fourth microorganism includes Enterobacteriaceae.

[0177] In one possible manner, the acquisition unit 310 is also used to obtain a gene sequence set of the object to be tested, where the gene sequence set includes multiple gene sequences; clustering is performed on the gene sequence set to determine that the gene sequence set includes at least one category of gene sequences, the number of gene sequences belonging to each category of gene sequences, and representative sequences of each category of gene sequences; based on the correspondence between gene sequences and species types, and the representative sequences of each category of gene sequences, the species types corresponding to each category of gene sequences are determined, where one category of gene sequences corresponds to one species type.

[0178] In one possible manner, the number of species of at least one reference microorganism is K, where K is a positive integer; the acquisition unit 310 is further used to acquire M training objects and the age of each training object; M>1 and M is an integer; the processing unit 320 is further used to determine a microbial species information set, the microbial species information set includes the microbial species information of the M training objects, the number of species types of microorganisms in the microbial species information set is N, and N is a positive integer; based on the microbial species information set and the ages of the M training objects, K reference microorganisms are determined from the microorganisms contained in the M training objects.

[0179] In one possible manner, the processing unit 320 is further used to determine the first age coefficient of each of the N types of microorganisms; determine a type of microorganism from the N types of microorganisms, and the first age coefficient of a type of microorganism is greater than a first threshold; determine b type of microorganism from a type of microorganism; the microbial species information of at least P training objects among the M training objects includes b type of microorganism, and P is greater than a second threshold; determine K types of reference microorganisms from the b types of microorganisms, and the second age coefficients of the K types of reference microorganisms are greater than a third threshold; wherein a, b, and P are positive integers.

[0180] It should be noted that the specific implementation process can be found in Figure 1 or Figure 2 The specific description of the method embodiment shown is not repeated in this application.

[0181] The present application also provides an electronic device. Figure 4 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0182] like Figure 4 As shown, the electronic device 400 may include: one or more processors 410, one or more memories 420, one or more communication interfaces 430, and a bus 440, wherein the processors 410, memories 420, and communication interfaces 430 are connected via the bus 440. The electronic device 400 may be the age assessment device 300 in the foregoing description.

[0183] Among them, the memory 420 is used to store programs; the processor 410 is used to execute the above-mentioned program stored in the above-mentioned memory. When the above-mentioned program is executed, the above-mentioned processor 410 executes a method in any possible implementation manner of the above-mentioned age assessment method.

[0184] It should be understood that in the embodiment of the present application, the above-mentioned memory 420 includes but is not limited to random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or portable read-only memory (CDROM), as well as external memory other than computer memory and processor cache. A part of the above-mentioned memory 420 may also include a non-volatile random access memory. For example, the memory 420 may also store information about the device type.

[0185] The processor 410 may be one or more central processing units (CPUs). When the processor 410 is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor 410 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0186] The steps performed in the above embodiments can be based on the above Figure 4 The structure of the electronic device 400 shown in the figure is implemented, and the processor 410 can execute the implementation described in any optional embodiment of the age assessment method provided in the embodiment of the present application, and can also execute the implementation of the age assessment device 300 described in the embodiment of the present application. Specifically, the processor 410 can implement Figure 3 The communication interface 430 can implement the functions of the processing unit 320 in the age assessment device 300 shown in the figure. The memory 420 can provide a storage function when the processor 410 executes the implementation of the age assessment device 300 described in the embodiment of the present application, such as storing microbial species information, and can also store the computer program required for the processor 410 to execute the implementation of the age assessment device 300 described in the embodiment of the present application.

[0187] The embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor can implement the above Figure 1 or Figure 2 The method in the corresponding embodiment.

[0188] The present application also provides a computer program product, which includes: instructions or computer programs; when the instructions or computer programs are executed, the above-mentioned Figure 1 or Figure 2 The method in the corresponding embodiment.

[0189] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by hardware related to the computer program, and the above-mentioned computer program can be stored in a computer-readable storage medium. When the above-mentioned computer program is executed, the processes in the above-mentioned method embodiments can be implemented. The aforementioned computer-readable storage medium includes: a read-only memory ROM or a random access memory RAM, a magnetic disk or an optical disk, and other media that can store computer program codes.

Claims

1. An age assessment method, characterized in that: The method comprises: Acquire microbial species information of the object to be tested, wherein the microbial species information includes species types of microorganisms contained in the object to be tested, and the number of gene sequences of microorganisms corresponding to each species type; Based on the microbial species information, determining that the object to be tested contains at least one reference microorganism and the number of gene sequences corresponding to each reference microorganism; Based on the microbial species information, a first ratio and / or a second ratio is determined; wherein the first ratio is a ratio between the number of gene sequences of a first microorganism and the number of gene sequences of a second microorganism, and the second ratio is a ratio between the number of gene sequences of a third microorganism and the number of gene sequences of a fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes a probiotic, and at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes a neutral bacteria and / or a harmful bacteria; Inputting the number of gene sequences corresponding to the at least one reference microorganism, and the first ratio and / or the second ratio into an age assessment model to obtain an output result of the age assessment model; The age of the subject to be tested is determined based on the output result of the age assessment model.

2. The method according to claim 1, characterized in that The species type of a microorganism is used to indicate the taxonomic level to which the microorganism belongs. The taxonomic level to which the microorganism belongs includes one or more of the following: kingdom, phylum, class, order, family, genus, and species.

3. The method according to claim 2, characterized in that The method further comprises: Determine, from the microbial species information, a gene sequence corresponding to the phylum classification level, a gene sequence corresponding to the genus classification level, and a gene sequence corresponding to the family classification level; Determining the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism from the gene sequences corresponding to the phylum classification level; Determining the number of gene sequences of the third microorganism from the gene sequences corresponding to the taxonomic level; The number of gene sequences of the fourth microorganism is determined from the gene sequences corresponding to the family classification level.

4. The method according to any one of claims 1 to 3, characterized in that The first microorganism includes Firmicutes, the second microorganism includes Bacteroidetes, the third microorganism includes Bifidobacterium, and the fourth microorganism includes Enterobacteriaceae.

5. The method according to any one of claims 1 to 3, characterized in that: The step of obtaining the microbial species information of the object to be tested includes: Obtaining a gene sequence set of an object to be tested, wherein the gene sequence set includes a plurality of gene sequences; Performing clustering processing on the gene sequence set to determine that the gene sequence set includes at least one type of gene sequence, the number of gene sequences belonging to each type of gene sequence, and representative sequences of each type of gene sequence; Based on the correspondence between gene sequences and species types, as well as the representative sequences of each type of gene sequence, the species types corresponding to each type of gene sequence are determined, and one type of gene sequence corresponds to one species type.

6. The method according to any one of claims 1 to 3, characterized in that The number of the at least one reference microorganism is K, where K is a positive integer; the method further comprises: Get M training subjects and the age of each training subject; M>1 and M is an integer; Determine a microbial species information set, wherein the microbial species information set includes microbial species information of M training objects, and the number of species types of microorganisms in the microbial species information set is N, where N is a positive integer; Based on the microbial species information set and the ages of the M training subjects, K reference microorganisms are determined from the microorganisms contained in the M training subjects.

7. The method according to claim 6, characterized in that The step of determining K reference microorganisms from the microorganisms contained in the M training objects based on the microorganism species information set and the ages of the M training objects comprises: Determine the first age coefficient of each microorganism in N microorganisms; Determine a type of microorganism from N types of microorganisms, wherein the first age coefficient of the a type of microorganism is greater than a first threshold; From the a type of microorganisms, determine b type of microorganisms; the microbial species information of at least P training objects among the M training objects includes the b type of microorganisms, and P is greater than a second threshold; From the b types of microorganisms, K types of reference microorganisms are determined, and the second age coefficients of the K types of reference microorganisms are greater than a third threshold value; wherein a, b, and P are positive integers.

8. An age assessment device, characterized in that: The device comprises: An acquisition unit, used to acquire microbial species information of the object to be tested, wherein the microbial species information includes species types of microorganisms contained in the object to be tested, and the number of gene sequences of microorganisms corresponding to each species type; A processing unit, for determining, based on the microbial species information, that the object to be tested contains at least one reference microorganism and the number of gene sequences corresponding to each reference microorganism; determining a first ratio and / or a second ratio based on the microbial species information; wherein the first ratio is the ratio between the number of gene sequences of the first microorganism and the number of gene sequences of the second microorganism, and the second ratio is the ratio between the number of gene sequences of the third microorganism and the number of gene sequences of the fourth microorganism; at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes probiotics, and at least one of the first microorganism, the second microorganism, the third microorganism, and the fourth microorganism includes neutral bacteria and / or harmful bacteria; An evaluation unit is used to input the number of gene sequences corresponding to the at least one reference microorganism, as well as the first ratio and / or the second ratio, into an age evaluation model to obtain an output result of the age evaluation model; and determine the age of the object to be tested based on the output result of the age evaluation model.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores program instructions; when the program instructions are executed by the processor, the processor executes the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program; when the computer program runs on one or more processors, the method according to any one of claims 1 to 7 is executed.

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