AU2020102040A4 - A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing - Google Patents
A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing Download PDFInfo
- Publication number
- AU2020102040A4 AU2020102040A4 AU2020102040A AU2020102040A AU2020102040A4 AU 2020102040 A4 AU2020102040 A4 AU 2020102040A4 AU 2020102040 A AU2020102040 A AU 2020102040A AU 2020102040 A AU2020102040 A AU 2020102040A AU 2020102040 A4 AU2020102040 A4 AU 2020102040A4
- Authority
- AU
- Australia
- Prior art keywords
- patients
- acarbose
- intestinal
- gut
- stratification
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
- C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6869—Methods for sequencing
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/156—Polymorphic or mutational markers
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
Abstract
Acarbose, as one of the main antidiabetics, plays an important role in type 2 diabetes (T2D)
patients. According to a survey, antidiabetic medication may modulate the gut microbiota and after
receiving acarbose treatment, patients with rich intestinal Bacteroides receive more metabolic
benefits than patients with a gut microbiota dominated by Prevotella. So stratification of T2D
patients based on their gut microbiota prior to treatment can effectively increase the curative
effects. This invention includes the Acarbose guidance of the T2D population based on a quick
and precise stratification of gut types. Based on second-generation sequencing, the invention has
the advantages of relatively low cost and high sequencing speed. During the design process, we
collect fecal samples and extract total DNA of intestinal microorganisms. Using 16SrDNA
amplicon sequencing technology and qiime2 visualization, we can find microbial composition and
abundance of each sample. Thenceforth, after the process of analyzing their dominant species, we
get the intestinal type of the patient and give each patient a report. Through this innovation, people
can quickly predict the response of diabetic patients to acarbose, so that the purpose of
personalized medication can be achieved, and the response of Acarbose can be accurately
predicted.
1
Description
A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing
The present invention relates to the prediction of the effect of intestinal microorganisms in different patients on the treatment of diabetes with acarbose.Through 16SrRNA amplicon sequencing technology of patients'intestinal microorganisms, personalized medication treatment scheme is provided for patients and side effects are reduced.
Diabetes is a common disease that is divided into type 1 diabetes(TlD) and type 2 diabetes(T2D). Statistics show that 1 in 11 adults worldwide suffers from diabetes, with 425 million patients in 2015. By 2045, this number will increase to 629 million[1]. Among them, type 2 diabetes patients account for 90% of diabetes patients. With the development of medical research, in Asia, doctors recommend the use of acarbose (a pseudotetrasaccharide produced by actinomycetes and an a-glycosidase inhibitor) for the first-line T2D treatment[2-3]. Acarbose inhibits enzymes (glycoside hydrolases) needed to digest carbohydrates Inhibition of these enzyme systems reduces the rate of digestion of complex carbohydrates. Less glucose is absorbed because the carbohydrates are not broken down into glucose molecules.[4-6] After Acarbose is taken, it enters the human body's gut to affect. So how effective is it depends largely on how well it is absorbed by our gut. The gut microbiota has been considered a cornerstone of maintaining the health status which can produce numerous metabolites that can regulate host metabolism. The bile acids, one kind of metabolism, can regulate diverse metabolic pathways in the host and gut microbial composition both directly and indirectly by activation of innate immune response genes in the small intestine.[7] Previous studies show that intestinal flora is closely related to the health of the host. Patients with T2D have disorders of intestinal flora and may cause the development of diseases. According to the research team of Gu et al.[8] found that the commonly used hypoglycemic drug acarbose can significantly change the level of bile acid metabolism of intestinal commensal bacteria and intestinal commensal bacteria in patients with newly diagnosed type 2 diabetes; while patients with rich intestinal Bacteroides after receiving acarbose treatment, it will show more metabolic benefits, such as weight loss, lipid reduction and improvement of insulin resistance. In addition to hypoglycemia, the metabolic benefit of acarbose treatment may be achieved by changing the intestinal flora of patients with type 2 diabetes and the bile acid metabolism of the intestinal flora, and the degree of metabolic benefit is closely related to the characteristics of the intestinal flora. On the contrary, patients with a gut microbiota dominated by Prevotella exhibit fewer changes in plasma BAs and little improvement in metabolic parameters after Acarbose treatment compared to patients with rich Bacteroides. The different responses between these two groups of people show the potential for stratification of T2D patients based on their gut microbiota prior to treatment. So our invention intends to quickly predict the response of diabetic patients to Acarbose based on this finding. The main technology we use in this invention is Next-generation sequencing. It refers to non-Sanger-based high-throughput DNA sequencing technologies. Millions or billions of DNA strands can be sequenced in parallel, yielding substantially more throughput and minimizing the need for the fragment-cloning methods that are often used in Sanger sequencing of genomes. What's more, in modem biotechnology, based on genomics, amplicon sequencing technology is more and more widely used. Amplicon sequencing is a highly targeted method for analyzing gene variation in specific genomic regions, and it is an ideal method for discovering single nucleotide polymorphisms so that we apply it to procedures. In this invention, we extract 16SrRNA from gene sequences. The 16SrDNA is ubiquitous in prokaryotes. It contains both highly conserved sequence regions and moderately conserved regions. And the amount of information contained is moderate, about 1.5kb, which is convenient for sequence analysis. So the 16s rRNA-based sequencing is widely used. Although there are a lot of researches about the topic that gut microbiota and plasma bile acids enable stratification of patients for antidiabetic treatment. Meanwhile, the technology of Next-generation sequencing and Amplicon sequencing are mature and applied widely in basic research. However, current researches about the stratification of T2D patients based on their gut microbiota prior to treatment has rarely been used for clinical application. What's more, laboratories have developed Next-generation sequencing to a high level and apply them for thousands of experiments, but hospitals in fact don't use them to a large range of patients for diagnosis. In order to fill in the gaps between theoretical findings and clinical application, our invention includes a quick and precise stratification of gut types which provides Acarbose guidance of the T2D population. This invention, based on second-generation sequencing, has the advantages of relatively low cost and high sequencing speed. This invention is innovative since there are few applications that combine the mature findings of pharmacomicrobiomics with DNA sequencing. We also promote the newest technology which stands the test of laboratories into our daily clinical diagnosis. Besides, microbes are more used to predict disease susceptibility in the early stage. In this patent, we use intestinal microbes to predict acarbose drug response. It belongs to pharmaceutical microbiology which embodies the interaction between humans, drugs, and microorganisms for a century. The pharmaceutical microbiome can be simply defined as the (system) study of the interaction between drugs and the microbiome. More specifically, it studies how differences in the microbiome within and between individuals affect the effect, distribution, curative effect, and toxicity of drugs. The human microbiome has huge metabolic potential. Its metabolic capacity exceeds the body's metabolic capacity, but it also expands the human body's metabolic capacity. The human microbiome can regulate drug therapy by affecting the pharmacokinetics and pharmacodynamics of drug molecules. So in this patent, we stratified the gut microbes of individuals with type 2 diabetes and studied the response of different microbiomes to acarbose, aiming to provide diabetic patients with the most effective treatment method. Not only does it reduces blood glucose, but it also brings other metabolic benefits. All in all, during our invention, accurate classification of patients based on the development of genetic diagnosis and personalized medicine can not only improve the most effective drugs for different patients but also provide more specific plans. As a result, it will be more likely to maximize the curing effect and minimize side effects. In this project, we conduct research and use 16s rRNA-based sequencing to classify the gut microbiota. The method quickly predicts the response of diabetic patients to acarbose, so that the purpose of personalized medication can be achieved, and the medication can be accurately predicted.
Acarbose is a kind of drug used for type 2 diabetes. According to s survey, patients with different dominate microorganisms receive benefits to varying degrees. So we can stratify T2D patients into two groups based on their gut microbiota prior to treatment. Based on Preliminary research, we design this invention by using second-generation sequencing and qiime2 visualization. Combining the mature findings about pharmacomicrobiomics with sequencing technology, we first collect fecal samples and extract total DNA of intestinal microorganisms and then use16SrDNA amplicon sequencing technology to find microbial composition and abundance of each sample. Thirdly, Taxonomic analysis are applied to classify. Lastly, intestinal type of the patients corresponding to the sample is given. Then the results are reported and the medication is guided. The analysis process based on the panel contains the following steps:
1. Raw data acquisition & Metadata construction This step is to extract the total DNA of the patient's intestinal microorganisms and construct a library. 2. Data import This step is to import patients' information into the Linux system to facilitate subsequent analysis. 3. Qiime2 visualization This step is to view the corresponding detailed data results on the qiime2 website. 4. Quality Control (Denoising) This step is to omit inaccurate data and truncate the base of the front primer and the tail sequence with too low quality value. 5. Taxonomic analysis This step is to correspond gene fragments to microbial species in the gene bank and obtain the proportion and abundance of microorganisms in different species. 6. Intestinal type identification This step is to extract the target bacterial genus Prevotella&Bacteroides and then stratify patients into two groups since medication can be given individually. 7. Drug response relationship This step is to clarify the specific corresponding relationship between intestinal type and drug reaction, that is, type B is suitable for acarbose. And give personalized medication guidance to patients.
However, this invention still has some limitations which may hinder its application.
1. If the dominate microorganism is neither Bacteroides nor Prevotella, we can not exactly tell how these patients will response after using Acarbose. 2. Our patent results can only be used as a reference, not directly as a patient's medication guide which should be followed by the doctor's advice.
Figure: Panel design shows the whole design process of the patent Figure2: Procedure of Collecting and analyzing intestinal microbial information briefly summarizes methods and applications used for the procedure of Collecting and analyzing intestinal microbial information
Panel design
First, we will collect fecal samples from patients to extract the total DNA of intestinal microorganisms and construct a library. The DNA sequence of V4 region obtained by 16SrDNA amplicon sequencing technology is imported into the Linux system and visualized by qiime2 to obtain the microbial composition and abundance of each sample. Finally, we annotate the flora of each individual and extract the target bacterial genera to analyze their dominant species to get the intestinal type of the patient and give a report. If necessary, standardization is needed before comparing the different intestinal types of patients. All of them have guiding significance for the personalized use of acarbose in patients.
Procedures:
1. Raw data acquisition & Metadata construction i. Original sequence acquisition (16srdna) Take individual fecal samples, extract the total DNA of the patient's intestinal microorganisms and construct a library. According to a number of studies, the sequence information of V4-V6 region is complete and has good specificity. It is often used for the phylogenetic and taxonomic identification of bacteria, including the types of microorganisms, the abundance of different species and so on. Considering comprehensively, we selected primer 515F& 806R for double-end high-throughput sequencing of V4 region to obtain sequence information which is exported to FASTQ format. [FASTQ format is a text format for storing biological sequences and corresponding quality evaluations. Its sequence and quality information are all labeled using an ASCII character, that is the standard format for high-throughput sequencing.] ii. Metadata includes sample information, such as grouping information, time, location, sampling location, sampling ID (unique), etc. These data are the basis for later grouping and analysis.
2. Data import
After obtaining the original data, we need to import it into the Linux system (compressed form) and output it in the form of qza. to facilitate subsequent analysis.
3. Qiime2 visualization Converting the file in qza.format into qZV format can view the corresponding detailed data results on the qiime2 website. Qiime demux summar--i-dataDemux.qza--o-visualizationDemux.qzv
4. Quality Control (Denoising) Each sequence will have a corresponding quality value. With the influence of the length of the sequence, etc., considering that it will affect the accuracy of data analysis, if the quality value is lower than 20, it is omitted. This step can truncate the base of the front primer and the tail sequence with too low-quality value, and generate three important files (statistical data):
* representative sequence (as a standard to generate out-to-NCBI nucleic acid library), * feature table (statistical information), and calculation of statistical results. And visualize the three files. Qiime dada2 denoise-single\ --i-demultiplexed-seqsDemux.qza\ --p-trim-left 0\ --p-trunc-len 120\ -- o-representative-sequences rep-seqs-dada2.qza\ -- o-table table-dada2.qza \ -- o-denoising-stats stats-dada2.qza Qiime feature-table summar --i-table-dada2.qza \ -- o-visualizationTable.qzv\ --m-sample-metadata-file sample-Metadata.tsv Qiime feature-table tabulate-seqs\ --i-data rep-seqs-dada2.qza \ -- o-visualization rep-Seqs.qzv Qiime metadata tabulate \ --m-input-file stats-dada2.qza\ -- o-visualization stats-dada2.qzv
5. Taxonomic analysis The 16SrDNA gene fragments obtained after primer shearing corresponds to the corresponding microbial species in the gene bank, and an interactive bar chart is generated to view the classification composition of the sample. We focused on the typing of intestinal microorganisms on genera. The proportion and abundance of microorganisms in different species can be obtained. Qiime feature-classifier classify-skleam\ --i-classifier gg-13-8-99-515-806-nb-Classifier.qza\ --i-reads rep-Seqs.qza\ -- o-classification Taxonomy.qza
Qiime metadata tabulate \ --m-input-fileTaxonomy.qza\ -- o-visualizationTaxonomy.qzv Qiime taxa barplot\ --i-tableTable.qza\ --i-taxonomyTaxonomy.qza\ --m-metadata-file sample-Metadata.tsv\ -- o-visualization taxa-bar-Plots.qzv
6. Intestinal type identification& Drug response relationship After obtaining the proportion of microbial distribution in the sample, the results of extracting the target bacterial genus Prevotella & Bacteroides were obtained. According to the results, the intestinal type of the patients corresponding to the sample is given. Then the results are reported and the medication is guided. Considering the different intestinal microbial composition in different patients, we judged the intestinal type according to the following criteria: there were Prevotella & Bacteroides in the top three microbial abundance, and the dominant abundances of the two were judged to be this type of the intestine. If the "Prevotella&Bacteroides" in the results did not exist in the top three abundances, it was judged as other types of intestine, not as the target intestinal type for drug guidance. According to the research results, patients in Cluster B exhibited significantly greater improvements in GO (FBG), insulin, C peptide levels and thus, HOMA-IR over baseline levels than patients in Cluster P. Therefore, patients with type B intestinal tract are more suitable to use acarbose for the treatment of diseases.
7. Standardization Because of the different numbers of samples from different patients. If intestinal types need to be compared between different patients, standardization is required before comparison.
8. Report According to the results of bacterial genera in patient samples, a standard report was obtained for personalized treatment of patients with medication.
Claims (2)
- Claim 1. A technique for predicting acarbose treatment based on stratification of gut by using 16SrRNA sequencing, it can be applied in laboratories, hospitals, pharmaceutical factories and other fields, wherein, predict the intestinal medication microenvironment of patients, greatly enhance the precise medical treatment for different patients, reduce the risk of side effects of drugs, and make medication more precise and scientific.
- 2. According to method of claim 1, wherein said analysis process based on the panel contains the following steps: 1) Raw data acquisition & Metadata construction; 2) Data import; 3) Qiime2 visualization; 4) Quality Control; 5) Taxonomic analysis; 6) Intestinal type identification; 7) Drug response relationship.Figure1Figure2
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2020102040A AU2020102040A4 (en) | 2020-08-28 | 2020-08-28 | A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2020102040A AU2020102040A4 (en) | 2020-08-28 | 2020-08-28 | A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| AU2020102040A4 true AU2020102040A4 (en) | 2020-10-08 |
Family
ID=72663851
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| AU2020102040A Ceased AU2020102040A4 (en) | 2020-08-28 | 2020-08-28 | A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing |
Country Status (1)
| Country | Link |
|---|---|
| AU (1) | AU2020102040A4 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116434840A (en) * | 2022-10-19 | 2023-07-14 | 佛山科学技术学院 | Method for predicting pig feed conversion rate |
-
2020
- 2020-08-28 AU AU2020102040A patent/AU2020102040A4/en not_active Ceased
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116434840A (en) * | 2022-10-19 | 2023-07-14 | 佛山科学技术学院 | Method for predicting pig feed conversion rate |
| CN116434840B (en) * | 2022-10-19 | 2024-04-19 | 佛山科学技术学院 | Method for predicting pig feed conversion rate |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Karstens et al. | Community profiling of the urinary microbiota: considerations for low-biomass samples | |
| US11001900B2 (en) | Method and system for characterization for female reproductive system-related conditions associated with microorganisms | |
| Gardner et al. | The neuropathic diabetic foot ulcer microbiome is associated with clinical factors | |
| CA3006059A1 (en) | Method and system for microbiome-derived diagnostics and therapeutics for oral health | |
| WO2019046347A9 (en) | Method and system for characterization for female reproductive system-related conditions associated with microorganisms | |
| WO2008147879A1 (en) | Automated method and device for dna isolation, sequence determination, and identification | |
| WO2017044885A1 (en) | Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with cerebro-craniofacial health | |
| WO2019051130A1 (en) | Nasal-related characterization associated with the nose microbiome | |
| CN110283903A (en) | Intestinal microflora for Diagnosis of Pancreatic inflammation | |
| CN107835692A (en) | For the sign in the microorganism group source of integumentary system situation, diagnosis and the method and system for the treatment of | |
| CN114898808A (en) | Method and system for predicting sensitivity of Klebsiella pneumoniae to cefepime | |
| Whitman | The need for change: embracing the genome | |
| AU2020102040A4 (en) | A Technique for Predicting Acarbose Treatment Based on Stratification of Gut by Using 16SrRNA Sequencing | |
| CN109475305A (en) | Method and system for microbial medicine genomics | |
| Bhattacharyya et al. | The conserved phylogeny of blood microbiome | |
| Wani et al. | Advances and applications of Bioinformatics in various fields of life | |
| Leite et al. | Defining small intestinal bacterial overgrowth by culture and high throughput sequencing | |
| Walters et al. | Technology and techniques for microbial ecology via DNA sequencing | |
| Hopf | Molecular diagnostics of injury and repair responses in critical illness: What is the future of “monitoring” in the intensive care unit? | |
| Moreno-Indias et al. | Metagenomics | |
| Brunklaus et al. | Time to move beyond genetics towards biomedical data-driven translational genomic research in severe paediatric epilepsies | |
| Cebrián et al. | Optimization of genotypic and biochemical methods to profile P. acnes isolates from a patient population | |
| CN113337630A (en) | Microbial marker for evaluating curative effect of fecal bacteria transplantation of type II diabetic patients and application of microbial marker | |
| Radjabzadeh et al. | Microbiome measurement: Possibilities and pitfalls | |
| CN112877416A (en) | Biomarker capable of detecting polycystic ovarian syndrome and application thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FGI | Letters patent sealed or granted (innovation patent) | ||
| PC | Assignment registered |
Owner name: CENTRAL SOUTH UNIVERSITY Free format text: FORMER OWNER(S): LIU, HAOLIN; CHEN, XINGYU; LAN, DONGYU |
|
| MK22 | Patent ceased section 143a(d), or expired - non payment of renewal fee or expiry |