CN119008037A - Data processing system based on bacterial drug resistance monitoring - Google Patents
Data processing system based on bacterial drug resistance monitoring Download PDFInfo
- Publication number
- CN119008037A CN119008037A CN202411471868.XA CN202411471868A CN119008037A CN 119008037 A CN119008037 A CN 119008037A CN 202411471868 A CN202411471868 A CN 202411471868A CN 119008037 A CN119008037 A CN 119008037A
- Authority
- CN
- China
- Prior art keywords
- polysaccharide
- information
- biofilm
- drug resistance
- state
- 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.)
- Granted
Links
Classifications
-
- 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
- G16H70/00—ICT specially adapted for the handling or processing of medical references
- G16H70/40—ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
- G16B15/30—Drug targeting using structural data; Docking or binding prediction
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Theoretical Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Pharmacology & Pharmacy (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Biotechnology (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Biophysics (AREA)
- Medicinal Chemistry (AREA)
- General Physics & Mathematics (AREA)
- Algebra (AREA)
- Genetics & Genomics (AREA)
- Crystallography & Structural Chemistry (AREA)
- Pure & Applied Mathematics (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Analytical Chemistry (AREA)
- Molecular Biology (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Toxicology (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
本申请涉及微生物监测技术领域，尤其是涉及一种基于细菌耐药监测的数据处理系统。该系统包括：获取生物膜标志物信息和致病菌类型信息，分析生物膜标志物信息和致病菌类型信息，判断动物体内的致病菌是否形成生物膜；若致病菌已形成生物膜，分析生物膜标志物信息，确定实时生物膜状态；获取抗生素破坏产物信息，根据抗生素破坏产物信息和致病菌类型信息，确定致病菌的表象耐药性表现；分析实时生物膜状态和表象耐药性表现，确定致病菌的实际耐药性表现，并输出实际耐药性表现，以供兽医参考。本申请避免细菌受到生物膜影响而呈现的表现耐药性表现对兽医的治疗方案调整造成误导，提高后续治疗方案有效性的同时，能够显著减少对抗生素的滥用。
The present application relates to the field of microbial monitoring technology, and in particular to a data processing system based on bacterial resistance monitoring. The system includes: obtaining biofilm marker information and pathogen type information, analyzing biofilm marker information and pathogen type information, and judging whether the pathogens in the animal have formed a biofilm; if the pathogens have formed a biofilm, analyzing the biofilm marker information and determining the real-time biofilm state; obtaining antibiotic destruction product information, and determining the apparent drug resistance performance of the pathogens according to the antibiotic destruction product information and pathogen type information; analyzing the real-time biofilm state and apparent drug resistance performance, determining the actual drug resistance performance of the pathogens, and outputting the actual drug resistance performance for veterinary reference. The present application avoids the misleading effect of the resistance performance of bacteria caused by the influence of biofilm on the adjustment of veterinary treatment plans, and can significantly reduce the abuse of antibiotics while improving the effectiveness of subsequent treatment plans.
Description
Technical Field
The application relates to the technical field of microorganism monitoring, in particular to a data processing system based on bacterial drug resistance monitoring.
Background
With the development of modern medicine, antibiotics are widely applied to animal husbandry, and can effectively treat bacterial infection diseases of the bred animals, reduce morbidity and mortality of the bred animals, improve economic benefits of animal husbandry and ensure food safety.
The widely used antibiotics can cause pathogenic bacteria to generate drug resistance to form drug-resistant strains, so that bacterial infection diseases of cultured animals become difficult to treat, therefore, it is important to accurately evaluate the bacterial drug resistance and take corresponding measures in time, and the existing bacterial drug resistance monitoring technology cannot accurately evaluate the drug resistance of the current bacteria under the condition that objective differences exist between the bacterial drug resistance in animals and the bacterial drug resistance in vitro, so that misjudgment on the drug resistance of the bacteria is caused, and further counter measures are caused, but the effect is extremely limited.
Disclosure of Invention
The application provides a data processing system based on bacterial drug resistance monitoring to solve the technical problems.
In a first aspect, the present application provides a data processing system based on bacterial resistance monitoring, the system comprising:
acquiring biological film marker information and pathogenic bacteria type information, analyzing the biological film marker information and the pathogenic bacteria type information, and judging whether pathogenic bacteria in an animal body form a biological film or not;
if the pathogenic bacteria have formed a biological film, analyzing the biological film marker information to determine a real-time biological film state;
Acquiring information of an antibiotic damage product, and determining the apparent drug resistance performance of the pathogenic bacteria according to the information of the antibiotic damage product and the information of the pathogenic bacteria type;
Analyzing the real-time biofilm status and the apparent resistance performance, determining an actual resistance performance of the pathogenic bacteria, and outputting the actual resistance performance for reference by a veterinarian.
Through the technical scheme, the biological film marker information and the pathogenic bacteria type information are analyzed to judge whether the pathogenic bacteria form biological films, if the pathogenic bacteria form biological films, the biological film marker information is analyzed to determine the real-time biological film state, and then the actual drug resistance performance of the pathogenic bacteria is determined through analyzing the real-time biological film state and the apparent drug resistance performance, so that the actual drug resistance performance of the bacteria in the biological film is determined, misleading caused by the drug resistance performance of the bacteria under the influence of the biological film to the veterinary treatment scheme adjustment is avoided, the abuse of antibiotics can be obviously reduced while the effectiveness of the follow-up treatment scheme is improved, and further the further development of the bacterial drug resistance is restrained.
Optionally, the biofilm marker information includes extracellular polysaccharide information, and analyzing the biofilm marker information and the pathogen type information to determine whether a pathogen in an animal forms a biofilm includes:
screening the extracellular polysaccharide information according to the pathogen type information to determine pathogen polysaccharide information;
analyzing the polysaccharide information of the pathogenic bacteria, and determining polysaccharide quantity information, polysaccharide particle distribution information and polysaccharide crosslinking information of the pathogenic bacteria;
Determining a biofilm index according to the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information;
Comparing the biofilm index with a preset biofilm threshold value, and if the biofilm index is larger than the preset biofilm threshold value, determining that the pathogenic bacteria in the animal body have formed a biofilm.
According to the technical scheme, extracellular polysaccharide information is screened according to pathogen type information, pathogen polysaccharide information is determined, polysaccharide quantity information, polysaccharide particle distribution information and polysaccharide crosslinking information of pathogens are obtained, after comprehensive analysis of the information, a biological film index is determined, the biological film index is compared with a preset biological film threshold value, if the biological film index is larger than the preset biological film threshold value, the formation of a biological film of pathogens in an animal body is determined, the biological film index can comprehensively reflect the formation state of the biological film on the periphery of the current pathogen, accuracy of judging whether the pathogens form the biological film is improved, and further precondition accuracy of subsequent evaluation of actual drug resistance performance of the pathogens in the biological film is guaranteed.
Optionally, the determining the biofilm index according to the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide cross-linking information includes:
Determining an average polysaccharide amount and a maximum polysaccharide amount according to the polysaccharide amount information;
Determining average particle diameter and standard deviation of particle diameter according to the polysaccharide particle distribution information;
Determining an average cross-linking score, a maximum cross-linking score and a minimum cross-linking score according to the polysaccharide cross-linking information;
the determined biofilm index is specifically expressed by the following formula:
；
Wherein, For the index of the biological film to be the same,For the amount of the polysaccharide to be said,In order to achieve the maximum polysaccharide content in question,The weights are influenced for a preset number of times,In order to achieve the above-mentioned average particle diameter,As a standard deviation of the diameter of the particles,For the pre-set particle impact weight,For the average cross-linking score to be given,For the maximum value of the cross-linking score,The cross-linking is scored at a minimum value,The crosslinking influence weight is preset.
According to the technical scheme, the mathematical analysis means is utilized, on the basis of the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide cross-linking information, the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide cross-linking information are subjected to standardization and normalization processing through a mathematical formula, and the biological membrane index is calculated in a weighted sum mode, so that the biological membrane index is more comprehensive and accurate, and the judgment accuracy of whether bacteria form a biological membrane is improved.
Optionally, the analyzing the biomarker information to determine a real-time biofilm state includes:
Analyzing the pathogenic polysaccharide information to determine polysaccharide viscosity, polysaccharide protein content, polysaccharide charge characteristics and polysaccharide hydration index;
determining a real-time structural state index of said pathogenic bacteria based on said polysaccharide viscosity and said polysaccharide protein content;
determining a real-time functional status index of the pathogen based on the polysaccharide charge characteristic and the polysaccharide hydration index;
determining a biological film state index according to the real-time structure state index and the real-time structure state index;
and determining the state of the biological film according to the biological film state index.
By the technical scheme, the polysaccharide viscosity, the polysaccharide protein content, the polysaccharide charge characteristic and the polysaccharide hydration index are analyzed to respectively obtain the real-time structural state index and the real-time functional state index, the real-time structural state index and the real-time functional state index are integrated to determine the biological film index, and further the biological film state is determined, so that the obtained biological film state accords with the actual condition of the biological film on the periphery of the bacteria, and the accuracy of the subsequent actual drug resistance process of the bacteria for analyzing the biological film state is improved.
Optionally, the real-time structural state index of the pathogenic bacteria is determined according to the viscosity of the polysaccharide and the protein content of the polysaccharide, specifically the following formula:
；
Wherein, For the real-time structural state index,In order to preset the state index of the infrastructure,In order to preset the viscosity-affecting coefficient,In order for the polysaccharide to be viscous in nature,In order to preset the protein influence coefficient,For the preset protein impact index,Is the polysaccharide protein content.
By the technical scheme, the nonlinear influence of polysaccharide viscosity and polysaccharide protein content on the structural state of the biological film is comprehensively described through a mathematical formula, so that the real-time structural state index reflecting the real-time structural state of the biological film is obtained, and the accuracy and the comprehensiveness of the determination process of the biological film state are improved.
Optionally, the determining the real-time functional status index of the pathogenic bacteria according to the charge characteristic of the polysaccharide and the hydration index of the polysaccharide is specifically the following formula:
；
Wherein, For the real-time functional status index,In order to preset the charge influence coefficient,In order to preset the charge fluctuation coefficient,In order to provide the charge characteristics of the polysaccharide,In order to preset the hydration influence factor,In order to preset the coefficient of hydration fluctuation,A hydration index for the polysaccharide;
The method comprises the steps of determining a biological film state index according to the real-time structural state index and the real-time functional state index, wherein the biological film state index is determined according to the following formula:
；
Wherein, As an index of the state of the biofilm in question,For the real-time structural state index,Is the real-time functional status index.
According to the technical scheme, on the basis of the polysaccharide charge characteristics and the polysaccharide hydration index, the influence of the periodic fluctuation of the polysaccharide charge characteristics and the stable fluctuation of the polysaccharide hydration index on the real-time functional state index is considered, the mathematical formula is utilized, the influence of the polysaccharide charge characteristics and the polysaccharide hydration index on the real-time functional state index is synthesized, the accurate real-time functional state index is obtained in a quantified mode, and the comprehensiveness of the real-time functional state index is improved.
Optionally, the determining the apparent drug resistance performance of the pathogenic bacteria according to the antibiotic destruction product information and the pathogenic bacteria type information includes:
Screening the antibiotic damage product information according to the pathogen type information to determine pathogen metabolite information;
And carrying out drug resistance correlation analysis on the pathogenic bacteria metabolite information based on the pathogenic bacteria type information, and determining the apparent drug resistance performance.
According to the technical scheme, on the basis of pathogen type information, the antibiotic damage products are screened, pathogen metabolite information is determined, and according to the pathogen metabolite information, the apparent drug resistance performance is determined, so that the apparent drug resistance performance accords with the actual condition of the pathogen, and the accuracy of the apparent drug resistance performance is improved.
Optionally, said analyzing said real-time biofilm status and said apparent resistance profile, determining an actual resistance profile of said pathogenic bacteria comprises:
Determining a plurality of state activity coefficients and biological film state information according to the real-time biological film state;
Based on the apparent drug resistance performance, determining the actual drug resistance performance according to the state activity coefficients and the biofilm state information.
According to the technical scheme, the state activity coefficients and the biological film state information are determined according to the real-time biological film state, the actual drug resistance performance is determined according to the state activity coefficients and the biological film state information on the basis of the apparent drug resistance performance, and the accurate actual drug resistance performance is obtained according to different influences of different biological film states on bacterial drug resistance, so that the actual drug resistance performance accords with the actual situation, and the accuracy and the comprehensiveness of the actual drug resistance performance are improved.
Optionally, the plurality of state activity coefficients include an adhesion state activity coefficient, an aggregation state activity coefficient, a steady state activity coefficient and a diffusion state activity coefficient, the biological film state information includes an adhesion degree, an aggregation degree, an antibiotic effective concentration and a diffusion film amount, and the actual drug resistance performance is determined according to the plurality of state activity coefficients and the biological film state information based on the apparent drug resistance performance, specifically the following formula:
；
Wherein, For the actual resistance performance to be described,For the appearance of a drug resistance manifestation,In order to preset the adhesion-influencing factor,For the adhesion state activity coefficient,In order to achieve the degree of adhesion described,In order to preset the aggregate influence coefficient,In order to achieve the degree of aggregation described,For the aggregate state activity coefficient,In order to preset the stability influence coefficient,In order for the antibiotic to be an effective concentration,For the steady-state activity coefficient,In order to preset the diffusion influence coefficient,For the amount of the diffusion film to be used,And the diffusion state active coefficient.
According to the technical scheme, the current biomembrane state of bacteria is controlled by the adhesion state active coefficient, the aggregation state active coefficient, the steady state active coefficient and the diffusion state active coefficient, the influence of different biomembrane states on the actual drug resistance performance of the bacteria is quantified on the basis of the apparent drug resistance performance, the actual drug resistance performance of the bacteria in the biomembrane is obtained, the obtained actual drug resistance performance is highly matched with the current biomembrane state of the bacteria, and the accuracy of the actual drug resistance performance is improved.
Optionally, the system further comprises:
judging whether antibiotics need to be replaced or not according to the pathogen type information and the actual drug resistance performance;
If the antibiotics need to be replaced, determining the information of replacing the antibiotics according to the pathogen type information;
If the antibiotics do not need to be replaced, determining the difference of the drug resistance performance according to the actual drug resistance performance and the apparent drug resistance performance;
and determining the combined medication information according to the drug resistance performance difference and the pathogenic bacteria type information.
According to the technical scheme, whether the antibiotics need to be replaced or not is judged according to the pathogen type information and the actual drug resistance performance, if the antibiotics need to be replaced, the antibiotic replacement information is determined directly according to the pathogen type information, if the antibiotics do not need to be replaced, the drug resistance performance difference is determined according to the actual drug resistance performance and the apparent drug resistance performance, the combined drug information is determined according to the drug resistance performance difference and the pathogen type information, and the drug strategy is determined according to the actual state of bacteria affected by the biological film, so that the drug strategy for coping with the pathogen is more effective.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application;
FIG. 2 is a flow chart of a data processing system based on bacterial resistance monitoring according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the application are described in further detail below with reference to the drawings.
The existing bacterial drug resistance monitoring technology can not accurately evaluate the drug resistance of the current bacteria under the condition that objective difference exists between the bacterial drug resistance in animals and the bacterial drug resistance in vitro, so that the drug resistance of the bacteria is misjudged, and countermeasures are further caused, but the effect is extremely limited.
Based on the above, the application provides a data processing system based on bacterial drug resistance monitoring. Whether the pathogenic bacteria form a biological film is judged by analyzing biological film marker information and pathogenic bacteria type information, if the pathogenic bacteria form the biological film, the biological film marker information is analyzed, the real-time biological film state is determined, and then the actual drug resistance performance of the pathogenic bacteria is determined by analyzing the real-time biological film state and the apparent drug resistance performance, so that the actual drug resistance performance of the bacteria in the biological film is determined, misleading caused by the expression drug resistance performance of the bacteria influenced by the biological film to the adjustment of a veterinary treatment scheme is avoided, the abuse of antibiotics can be obviously reduced while the effectiveness of a subsequent treatment scheme is improved, and further the further development of bacterial drug resistance is restrained.
Fig. 1 is a schematic view of an application scenario provided by the present application. In the process of monitoring bacterial drug resistance in animals, the system provided by the application is applied to comprehensively analyze the biological film marker information, the pathogenic bacteria type information and the antibiotic damage product information, so as to obtain the actual drug resistance performance of pathogenic bacteria, and provide the actual drug resistance performance to veterinary references.
Specifically, the system provided by the application is carried in any server, the server is communicated with a plurality of implantable biosensors, biofilm marker information and pathogen type information provided by the communication of the implantable biosensors are acquired and analyzed through the server, whether the pathogen forms a biofilm or not is judged, if the pathogen forms a biofilm, the biofilm marker information is analyzed, the real-time biofilm state is determined, the real-time biofilm state and the apparent drug resistance performance are further analyzed, the actual drug resistance performance of the pathogen is determined, and the actual drug resistance performance is output for reference by a veterinarian, so that the actual drug resistance performance of bacteria in the biofilm is determined, misguidance caused by the performance drug resistance performance presented due to the influence of the biofilm on the adjustment of a treatment scheme of the veterinarian is avoided, the abuse of antibiotics can be obviously reduced while the effectiveness of a subsequent treatment scheme is improved, and further development of the drug resistance of the bacteria is further suppressed. Reference may be made to the following examples for specific implementation.
Fig. 2 is a flowchart of a data processing system based on bacterial drug resistance monitoring according to an embodiment of the present application, where the system of the present embodiment may be applied to a server in the above scenario. As shown in fig. 2, the system includes:
S201, acquiring biological film marker information and pathogenic bacteria type information, analyzing the biological film marker information and the pathogenic bacteria type information, and judging whether pathogenic bacteria in an animal body form a biological film or not.
The biofilm marker information may be molecular information or substance information for reflecting characteristics of bacterial biofilms, such as extracellular polysaccharide information, and may be obtained by monitoring animals through a plurality of implantable biosensors.
The pathogen type information may be the type of bacteria currently in need of monitoring, which is obtained by means of several implantable biosensors.
Specifically, when the bacteria are in the animal body, the bacteria are influenced by the characteristics of the bacteria, the availability of nutrients and the local environmental conditions, a biological film can be formed, the biological film generates a barrier effect on the periphery of the bacteria, the permeation of antibiotics into the bacteria is influenced, the bacteria in the biological film are usually in a resting or low-metabolism state, the effect of the antibiotics is further inhibited, because most of the mechanisms of the antibiotics are aimed at actively splitting the bacteria, the drug resistance of the bacteria in the biological film is influenced by the biological film, when the drug resistance of the bacteria is monitored and evaluated, if the drug resistance of the bacteria is directly used as the actual drug resistance of the bacteria, misjudgment that the dosage of the antibiotics is increased or the antibiotics are required to be directly replaced is easy to generate, the misuse of antibiotics is omitted, the abuse of the antibiotics is caused, the bacterial host animal body is increased, the drug resistance is further improved, a series of markers highly related to the bacteria are generated in the process of generating the biological film, and the markers can reflect whether the bacteria of the current type generate the biological film or not, so that the drug resistance information of the bacteria is accurately analyzed according to the actual drug resistance of the bacteria after the bacteria is analyzed by analyzing the type of the bacteria in the biological film.
S202, if the pathogenic bacteria form a biological film, analyzing the biological film marker information to determine the real-time biological film state.
The real-time biofilm state may be a state corresponding to a current stage of development of the bacterial peripheral biofilm, such as an attached state, an aggregated state, and the like.
Specifically, after the bacteria form the biological film, the biological film is not static, but enters different stages along with the development of the bacteria, the states of the biological film in different development stages have obvious differences, the obvious differences influence the drug resistance performance of the bacteria in the biological film, for example, the attached state is the initial development stage of the biological film, the biological film in the attached state has weaker barrier effect on antibiotics, when the biological film is in the attached state, the actual drug resistance performance of the bacteria can be considered to be less influenced by the biological film, the determination of the biological film state can enable the evaluation of the actual drug resistance performance of the bacteria to be more accurate, and the state of the biological film can be reflected by different marker contents in the biological film marker information, so that the biological film marker information needs to be analyzed through a mathematical analysis means, and the real-time biological film state is determined, thereby providing the basis of the biological film state information for the subsequent evaluation of the actual drug resistance performance of the bacteria.
S203, acquiring information of an antibiotic damage product, and determining the apparent drug resistance performance of pathogenic bacteria according to the information of the antibiotic damage product and the information of the pathogenic bacteria type.
The antibiotic-destruction product information may be a number of product information that changes as affected by the antibiotic destruction, and the antibiotic-destruction product information may reflect the effectiveness of the antibiotic.
The apparent drug resistance may be a resistance exhibited by bacteria in animals irrespective of the effects of the biofilm.
Specifically, when the antibiotics destroy and inhibit bacteria, various products are generated, the effect of the current antibiotics on the bacteria corresponding to the pathogenic bacteria type information can be reflected through monitoring and analysis of the products, so that the apparent drug resistance of the bacteria is reversely verified, and an important data basis is provided for determining the accurate actual drug resistance of the bacteria in the subsequent combined biological film state.
S204, analyzing the real-time biomembrane state and the apparent drug resistance performance, determining the actual drug resistance performance of pathogenic bacteria, and outputting the actual drug resistance performance for veterinary reference.
The actual drug resistance may be obtained by taking into consideration the drug resistance of the bacteria by the biofilm state and then expressing the drug resistance of the bacteria.
Specifically, by means of mathematical analysis, on the basis of the apparent drug resistance performance, the influence of the real-time biomembrane state on the bacterial drug resistance performance is quantified, so that the actual drug resistance performance of bacteria in the biomembrane is obtained, the actual drug resistance performance is output through man-machine interaction equipment, and accurate bacterial drug resistance information is provided for the follow-up treatment of a veterinary animal on a bacterial host animal.
By means of the method, whether the pathogenic bacteria form a biological film or not is judged by analyzing the biological film marker information and the pathogenic bacteria type information, if the pathogenic bacteria form the biological film, the biological film marker information is analyzed, the real-time biological film state is determined, and then the actual drug resistance performance of the pathogenic bacteria is determined by analyzing the real-time biological film state and the apparent drug resistance performance, so that the actual drug resistance performance of the bacteria in the biological film is determined, misleading caused by the apparent drug resistance performance of the bacteria influenced by the biological film to the veterinary treatment scheme adjustment is avoided, abuse of antibiotics can be remarkably reduced while the effectiveness of the follow-up treatment scheme is improved, and further development of bacterial drug resistance is restrained.
In some embodiments, the extracellular polysaccharide information is screened according to the pathogen type information to determine pathogen polysaccharide information; analyzing polysaccharide information of pathogenic bacteria, and determining polysaccharide quantity information, polysaccharide particle distribution information and polysaccharide crosslinking information of the pathogenic bacteria; determining a biofilm index according to the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information; comparing the biofilm index with a preset biofilm threshold value, and if the biofilm index is larger than the preset biofilm threshold value, determining that the pathogenic bacteria in the animal body form a biofilm.
The biomarker information includes extracellular polysaccharide information, which may be information of carbohydrate secreted by the cell into its external environment.
The pathogenic polysaccharide information can be polysaccharide substance information secreted by pathogenic bacteria in extracellular polysaccharide information, and can be obtained by matching the extracellular polysaccharide information with information in a preset pathogenic polysaccharide database for storing different types of pathogenic polysaccharide information.
The polysaccharide quantity information may be polysaccharide quantity information in pathogenic polysaccharide information over a fixed analysis period.
The polysaccharide particle distribution information may be the distribution of polysaccharide particles produced by the pathogen within the host over a fixed analysis period.
The polysaccharide cross-linking information may be cross-linking structure information of polysaccharide formation by pathogenic bacteria during a fixed analysis period.
The biofilm index may be a quantitative index for reflecting a state of formation of a bacterial biofilm.
The preset biofilm threshold may be threshold data for determining whether the current biofilm index may represent that bacteria have formed a biofilm, and the preset biofilm threshold may be obtained by analyzing the historical data.
Specifically, the bacterial biofilm component is mainly extracellular polysaccharide secreted by bacteria, whether a biofilm is formed on the surface of the current pathogenic bacteria can be indirectly reflected by analyzing pathogenic bacteria polysaccharide information, wherein the polysaccharide quantity information can directly reflect the biofilm forming capability of the pathogenic bacteria, the large polysaccharide quantity generally means that the biofilm forming capability of the pathogenic bacteria is strong, so that the current pathogenic bacteria can be inferred to form a biofilm with high probability, if the polysaccharide particle diameter uniformity degree in the polysaccharide particle distribution information is higher, the surface of the bacteria can be considered to form a uniform biofilm, further, the polysaccharide crosslinking information can reflect the integrity degree of the peripheral biofilm of the bacteria, if the polysaccharide crosslinking degree secreted by the bacteria is higher, the surface of the bacteria can be considered to form a complete biofilm, therefore, the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information of the pathogenic bacteria are required to be synthesized, and the biofilm index reflecting the biofilm forming state of the pathogenic bacteria is quantified by a mathematical analysis means, and then the biofilm index is compared with a preset biofilm threshold, and if the biofilm index is larger than the preset biofilm threshold, the formed biofilm of the pathogenic bacteria in the animal can be accurately and comprehensively determined.
According to the method provided by the embodiment, extracellular polysaccharide information is screened according to pathogen type information, pathogen polysaccharide information is determined, polysaccharide quantity information, polysaccharide particle distribution information and polysaccharide crosslinking information of pathogens are obtained, after comprehensive analysis of the information, a biological film index is determined, the biological film index is compared with a preset biological film threshold, if the biological film index is larger than the preset biological film threshold, the formation of a biological film of pathogens in an animal body is determined, the biological film index can comprehensively reflect the formation state of the biological film of the periphery of the current pathogen, accuracy of judging whether the pathogens form the biological film is improved, and further precondition accuracy of subsequent evaluation of actual drug resistance performance of the pathogens in the biological film is guaranteed.
In some embodiments, the average polysaccharide amount and the maximum polysaccharide amount are determined based on polysaccharide amount information; determining average particle diameter and standard deviation of particle diameter according to the polysaccharide particle distribution information; determining an average cross-linking score, a maximum cross-linking score and a minimum cross-linking score according to the polysaccharide cross-linking information; determining a biofilm index, specifically the following formula (1):
（1）
Wherein, In order to be a biofilm index,In order to obtain the average polysaccharide content,For the maximum amount of polysaccharide to be obtained,The weights are influenced for a preset number of times,In order to obtain the average particle diameter of the particles,Is the standard deviation of the diameter of the particles,For the pre-set particle impact weight,For the average cross-linking score,For the maximum value of the cross-linking score,For the minimum value of the cross-linking score,The crosslinking influence weight is preset.
The average polysaccharide amount may be an average of the number of polysaccharides over a fixed analysis period, which may be a period of time corresponding to when the blood antibiotic concentration in the animal is at a maximum.
The maximum polysaccharide amount may be the maximum of the polysaccharide amount within a fixed analysis period
The average particle diameter may be an average value of the particle diameters of the polysaccharide within the polysaccharide particle distribution information.
The standard deviation of particle diameters may be data describing the difference between particle diameters of polysaccharides, the smaller the standard deviation of particle diameters, the higher the uniformity of particle diameters.
The average cross-linking score may be an average of the degree of cross-linking of the polysaccharide in the polysaccharide cross-linking information.
The maximum cross-linking score may be the maximum cross-linking degree of the polysaccharide in the polysaccharide cross-linking information.
The minimum cross-linking score may be the minimum cross-linking degree of the polysaccharide in the polysaccharide cross-linking information
The preset number influence weight may be a preset weight coefficient for reflecting the influence degree of the polysaccharide number on the formation of the biofilm, and may be obtained by analyzing experimental data.
The preset particle influence weight can be a preset weight coefficient for reflecting the influence degree of polysaccharide particle distribution on the formation of the biological film, and can be obtained by analyzing experimental data
The preset crosslinking influence weight may be a preset weight coefficient for reflecting the influence degree of the crosslinking degree of the polysaccharide on the formation of the biofilm, and may be obtained by analyzing experimental data.
Specifically, the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information can indirectly reflect the formation of bacterial biofilms by the formula (1)、AndAnd respectively carrying out standardization and normalization treatment on the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information, and calculating out biofilm indexes under the influence of the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information in a weighted sum mode.
It should be noted that the amount of polysaccharide directly affects the ability of the bacteria to form a biofilm, which typically requires a large amount of extracellular polysaccharide that provides a matrix and structural support, and a large amount of polysaccharide that aids in the attachment between bacteria and surfaces, promoting stability of the biofilm, so that the specific gravity of the predetermined number impact weight should be significantly greater than the predetermined particle impact weight and the predetermined cross-linking impact weight.
Meanwhile, as the crosslinking degree of the polysaccharide affects the mechanical strength and stability of the biological film, the highly crosslinked polysaccharide can form a stronger three-dimensional network, better structural support is provided for the biological film, the change of the crosslinking degree can obviously affect the formation and maintenance of the biological film, the distribution of the polysaccharide particles affects the overall function of the polysaccharide particles in the biological film, but compared with the quantity and the crosslinking degree, the polysaccharide with good particle distribution can increase the uniformity and the stability of the biological film, but even if the particle distribution is poor, the biological film can still be formed if the quantity and the crosslinking degree are proper, and therefore, the specific gravity of the preset particle influence weight is obviously larger than the preset crosslinking influence weight.
By means of the method provided by the embodiment, the mathematical analysis means is utilized, on the basis of the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information, the polysaccharide quantity information, the polysaccharide particle distribution information and the polysaccharide crosslinking information are subjected to standardization and normalization processing through a mathematical formula, and the biological film index is calculated through a weighted sum mode, so that the biological film index is more comprehensive and accurate, and the accuracy of judging whether bacteria form biological films is improved.
In some embodiments, pathogenic polysaccharide information is analyzed to determine polysaccharide viscosity, polysaccharide protein content, polysaccharide charge characteristics, and polysaccharide hydration index; determining a real-time structural state index of the pathogenic bacteria according to the polysaccharide viscosity and the polysaccharide protein content; determining a real-time functional state index of the pathogenic bacteria according to the polysaccharide charge characteristics and the polysaccharide hydration index; determining a biological film state index according to the real-time structure state index and the real-time structure state index; determining the state of the biological film according to the biological film state index.
Polysaccharide viscosity may be data reflecting extracellular polysaccharide viscosity secreted by a pathogen.
The polysaccharide protein content may be data reflecting the content of extracellular polysaccharide proteins secreted by the pathogen.
The polysaccharide charge characteristics may be data reflecting the charge characteristics exhibited by extracellular polysaccharides.
The polysaccharide hydration index may be data reflecting the solubility of extracellular polysaccharide in the aqueous phase.
The real-time structural state index may be data reflecting the physical state of the biofilm.
The real-time functional status index may be data reflecting the functional status of the biofilm.
The biofilm state index may be data that points to a current bacterial biofilm state.
Specifically, as can be seen from the foregoing examples, the drug resistance exhibited by bacteria is significantly affected by the state of the biofilm, and the state of the biofilm is mainly affected by the combination of the viscosity of the polysaccharide, the content of the polysaccharide protein, the charge characteristic of the polysaccharide and the hydration index of the polysaccharide, wherein the viscosity of the polysaccharide reflects the stability of the flow characteristic and the internal structure of the biofilm, a higher viscosity value generally means that the state of the biofilm is stable, the content of the polysaccharide protein can affect the overall structure and stability of the biofilm, the structural stability of the biofilm is enhanced by combining the protein with the polysaccharide molecule, and the viscosity of the polysaccharide and the content of the polysaccharide protein can jointly reflect the real-time structural state of the biofilm.
The charge characteristics of the polysaccharide affect the interaction with other molecules, such as the binding capacity with the cell surface, the charge characteristics of the polysaccharide can affect the biocompatibility of the biological membrane and the interaction with host cells, the hydration capacity of the polysaccharide directly affects the solubility of the polysaccharide in a biological environment and the interaction with water molecules, the charge characteristics of the polysaccharide and the hydration index of the polysaccharide simultaneously affect the functional performance of the biological membrane in cell communication, and the charge characteristics of the polysaccharide and the hydration index of the polysaccharide can jointly reflect the real-time functional state of the biological membrane.
By means of mathematical analysis, a real-time structural state index and a real-time functional state index are respectively obtained according to polysaccharide viscosity, polysaccharide protein content, polysaccharide charge characteristics and polysaccharide hydration index, the real-time structural state index and the real-time functional state index are integrated, a biological film index is determined, and a biological film state is determined according to a range interval in which the biological film index is located.
By means of the method provided by the embodiment, the polysaccharide viscosity, the polysaccharide protein content, the polysaccharide charge characteristic and the polysaccharide hydration index are analyzed to respectively obtain the real-time structural state index and the real-time functional state index, the real-time structural state index and the real-time functional state index are integrated to determine the biological film index, and further the biological film state is determined, so that the obtained biological film state accords with the actual situation of the biological film on the periphery of the bacteria, and the accuracy of the subsequent actual drug resistance process of the bacteria for analyzing the biological film state is improved.
In some embodiments, the real-time structural state index of a pathogen is determined based on polysaccharide viscosity and polysaccharide protein content, specifically equation (2) below:
（2）
Wherein, For the real-time structural state index,In order to preset the state index of the infrastructure,In order to preset the viscosity-affecting coefficient,Is a polysaccharide with the viscosity of the polysaccharide,In order to preset the protein influence coefficient,For the preset protein impact index,Is polysaccharide protein content.
The preset basic structure state index may be a basic biofilm structure state index of the current type of bacteria, and may be obtained by analyzing experimental data of different types of bacteria.
The preset viscosity influence coefficient can be preset data for expressing the influence degree of polysaccharide viscosity on the real-time structural state of the biological film, and can be obtained by analyzing experimental data of the biological film.
The preset protein influence coefficient can be preset data for expressing the linear influence degree of the polysaccharide protein content on the real-time structural state of the biological film, and can be obtained by analyzing experimental data of the biological film.
The preset protein influence index can be preset data for expressing the nonlinear influence degree of the polysaccharide protein content on the real-time structural state of the biological film, and can be obtained by analyzing experimental data of the biological film.
Specifically, by the formula (2)Describing the nonlinear effect of linearized polysaccharide viscosity on real-time structural state index, eliminating the effect of excessively high or excessively low polysaccharide viscosity values on the results, and byDescribing the nonlinear rapid growth effect of the polysaccharide protein content on the real-time structural state index, reflecting the key adhesion and architecture action of the polysaccharide protein in the biological film, and synthesizing the nonlinear influence of the polysaccharide viscosity and the polysaccharide protein content on the structural state of the biological film through a formula (2), thereby obtaining the accurate real-time structural state index.
By means of the method provided by the embodiment, nonlinear influences of polysaccharide viscosity and polysaccharide protein content on the structural state of the biological film are comprehensively described through a mathematical formula, so that a real-time structural state index reflecting the real-time structural state of the biological film is obtained, and accuracy and comprehensiveness of a biological film state determining process are improved.
In some embodiments, the real-time functional status index of a pathogen is determined based on the polysaccharide charge characteristics and the polysaccharide hydration index, specifically the following equation (3):
（3）
Wherein, For the real-time function status index,In order to preset the charge influence coefficient,In order to preset the charge fluctuation coefficient,In order to provide the charge characteristics of the polysaccharide,In order to preset the hydration influence factor,In order to preset the coefficient of hydration fluctuation,Is a polysaccharide hydration index; determining a biological film state index according to the real-time structural state index and the real-time functional state index, specifically the following formula (4):
（4）
Wherein, The biological membrane state index is obtained by the method,For the real-time structural state index,Is a real-time functional state index.
The preset charge influence coefficient can be preset data for expressing the influence degree of polysaccharide charge characteristics on the real-time functional state of the biological film, and can be obtained by analyzing experimental data of the biological film.
The preset charge fluctuation coefficient may be preset data for expressing the degree of fluctuation of the charge characteristics of the polysaccharide.
The preset hydration influence coefficient can be preset data for expressing the influence degree of the hydration capacity of the polysaccharide on the real-time functional state of the biological membrane, and can be obtained by analyzing experimental data of the biological membrane.
The preset hydration fluctuation coefficient may be preset data for expressing the degree of fluctuation of the hydration capacity of the polysaccharide.
Specifically, by the formula (3)Describing the effect of periodic fluctuations in polysaccharide charge characteristics induced in biological membranes on real-time functional state index, and byDescribing the non-direct correlation influence of stable fluctuation of the polysaccharide hydration index in the biological film on the real-time functional state index, and synthesizing the influence of the polysaccharide charge characteristic and the polysaccharide hydration index on the real-time functional state index to quantitatively obtain the accurate real-time functional state index.
By means of the method, on the basis of polysaccharide charge characteristics and polysaccharide hydration indexes, the influence of periodic fluctuation of the polysaccharide charge characteristics and stable fluctuation of the polysaccharide hydration indexes on the real-time functional state indexes is considered, a mathematical formula is utilized, the influence of the polysaccharide charge characteristics and the polysaccharide hydration indexes on the real-time functional state indexes is synthesized, the accurate real-time functional state indexes are obtained in a quantified mode, and the comprehensiveness of the real-time functional state indexes is improved.
In some embodiments, the antibiotic damage product information is screened according to pathogen type information to determine pathogen metabolite information; based on the pathogen type information, carrying out drug resistance association analysis on pathogen metabolite information, and determining the apparent drug resistance performance.
The information of the metabolites of the pathogenic bacteria can be compound information generated by metabolic changes of the pathogenic bacteria under the action of antibiotics.
In particular, in determining the apparent resistance performance of a pathogen, pathogen metabolite information may reflect the resistance performance of the pathogen to the current antibiotic, since the pathogen, after being affected by the antibiotic, will degrade or modify the antibiotic by producing a specific enzyme, such as the β -lactam enzyme, thereby causing it to develop resistance performance, while the bacterium will produce more antioxidant substances, such as glutathione, to protect itself from oxidative damage, such enhancement of metabolic response being generally associated with resistance, and thus the resistance of the bacterium to the relevant antibiotic may be indirectly assessed by analyzing the specific metabolite type in the pathogen metabolite information via metabolite analysis techniques, such as biosensors, to determine the apparent resistance performance of the pathogen.
According to the mode provided by the embodiment, on the basis of pathogenic bacteria type information, the antibiotic damage products are screened, pathogenic bacteria metabolite information is determined, and according to the pathogenic bacteria metabolite information, the apparent drug resistance performance is determined, so that the apparent drug resistance performance accords with the actual condition of pathogenic bacteria, and the accuracy of the apparent drug resistance performance is improved.
In some embodiments, a number of state activity coefficients and biofilm state information are determined from real-time biofilm states; based on the apparent drug resistance performance, the actual drug resistance performance is determined according to a plurality of state activity coefficients and the biological state information.
The stateful activity coefficients may be coefficients for expressing the directionality of the biofilm state.
The biofilm state information may be information highly related to the influence of the state in which the biofilm is specifically located on bacterial resistance, and may be acquired by a biosensor according to the biofilm state.
Specifically, the real-time biofilm state comprises an attached state, an aggregation state, a stable state and a diffusion state, the differences of the states of the biofilm can cause the obvious differences of the actual resistance performance based on the apparent resistance performance, and the method is characterized in that when the biofilm state is developed from the attached state to the aggregation state and the stable state, the influence of the biofilm on the resistance is presented to be the strongest, the biofilm is just formed in the stable state, the biofilm is not fully mature, the biofilm in the attached strip only can show the preliminary enhancement of the resistance of bacteria, when the biofilm is developed to the aggregation state, the interaction among bacteria is enhanced, the structure tends to be dense, the matrix tends to be rich, the biofilm can further block the penetration of antibiotics, when the biofilm is developed to the stable state, the biofilm is fully mature, the resistance of the biofilm to the antibiotics is the largest, and further, when the biofilm is developed to the final diffusion state, part of the bacteria can be separated from the biofilm to other areas, the bacteria can not resist the protection of the biofilm any more, the bacteria can accurately show the resistance to the bacteria according to the actual resistance performance coefficient, and the accurate resistance performance can be analyzed according to the actual resistance coefficient under the conditions.
According to the mode provided by the embodiment, a plurality of state activity coefficients and biological film state information are determined according to the real-time biological film state, on the basis of the apparent drug resistance performance, the actual drug resistance performance is determined according to the state activity coefficients and the biological film state information, and the accurate actual drug resistance performance is obtained according to different influences of different biological film states on bacterial drug resistance, so that the actual drug resistance performance accords with the actual situation, and the accuracy and the comprehensiveness of the actual drug resistance performance are improved.
In some embodiments, based on the apparent resistance performance, the actual resistance performance is determined from a number of state activity coefficients and biofilm state information, in particular the following equation (5)
（5）
Wherein, In order to achieve the actual resistance performance of the drug,In order to represent the appearance of drug resistance,In order to preset the adhesion-influencing factor,As the adhesion-state activity coefficient,In order to achieve a degree of adhesion,In order to preset the aggregate influence coefficient,In order to be able to gather the degree of aggregation,In order to aggregate the active coefficients of the states,In order to preset the stability influence coefficient,In order to achieve an effective concentration of the antibiotic,As a result of the steady-state activity coefficient,In order to preset the diffusion influence coefficient,In order to achieve the amount of diffusion film,Is the diffusion state active coefficient.
The plurality of state activity coefficients includes an adhesion state activity coefficient, an aggregation state activity coefficient, a steady state activity coefficient, and a diffusion state activity coefficient.
The biofilm status information includes extent of adhesion, extent of aggregation, antibiotic effective concentration, and amount of diffusion membrane.
The adhesion state activity coefficient may be a coefficient value expressing whether the biofilm state is directed to the biofilm adhesion state.
The aggregation state activity coefficient may be a coefficient value that expresses whether the biofilm state is directed to the biofilm aggregation state.
The steady state activity coefficient may be a coefficient value that expresses whether the biofilm state points to the biofilm steady state.
The diffusion state activity coefficient may be a coefficient value that expresses whether a biological film state points to a biological film diffusion state.
The degree of attachment may be data reflecting the degree of attachment of the biofilm in the host.
The degree of aggregation may be data reflecting the degree of aggregation of the biofilm in the host.
The effective concentration of the antibiotic may be an effective concentration of the antibiotic in the host determined based on the apparent resistance. The amount of diffusion membrane may be data reflecting the amount of diffusion of the biofilm in the host.
The preset adhesion influence coefficient may be a coefficient expressing the degree of influence of the adhesion state of the biological film on the actual drug resistance, and may be obtained by analyzing experimental data of the biological film.
The preset aggregation influence coefficient can be a coefficient for expressing the degree of influence of the aggregation state of the biological film on the actual drug resistance, and can be obtained by analyzing experimental data of the biological film.
The preset stability influence coefficient can be a coefficient for expressing the influence degree of the steady state of the biological film on the actual drug resistance performance, and can be obtained by analyzing experimental data of the biological film.
The preset diffusion influence coefficient can be a coefficient for expressing the degree of influence of the diffusion state of the biological film on the actual drug resistance, and can be obtained by analyzing experimental data of the biological film.
Specifically, through the adhesion state active coefficient, the aggregation state active coefficient, the steady state active coefficient and the diffusion state active coefficient, the calculation process in the formula (5) is controlled, when the biomembrane state is in one of the adhesion state, the aggregation state, the steady state and the diffusion state, the active coefficient corresponding to the biomembrane state is 1, and other active coefficients are 0, so that the formula (5) can perform targeted calculation according to different biomembrane states, and on the basis of the apparent drug resistance performance, the influence of the different biomembrane states on the actual drug resistance performance of bacteria is quantified, and the actual drug resistance performance of bacteria in the biomembrane is obtained.
According to the method provided by the embodiment, the current biomembrane state of bacteria is controlled by the adhesion state active coefficient, the aggregation state active coefficient, the steady state active coefficient and the diffusion state active coefficient, the influence of different biomembrane states on the actual drug resistance performance of the bacteria is quantified on the basis of the apparent drug resistance performance, the actual drug resistance performance of the bacteria in the biomembrane is obtained, the obtained actual drug resistance performance is highly matched with the current biomembrane state of the bacteria, and the accuracy of the actual drug resistance performance is improved.
In some embodiments, determining whether an antibiotic replacement is required based on pathogen type information and actual resistance performance; if the antibiotics need to be replaced, determining the information of replacing the antibiotics according to the information of the pathogen type; if the antibiotics do not need to be replaced, determining the difference of the drug resistance performance according to the actual drug resistance performance and the apparent drug resistance performance; and determining the combined medication information according to the drug resistance performance difference and the pathogenic bacteria type information.
The replacement antibiotic information may be information about the medication of the antibiotic that needs replacement.
The combined medication information can be related medicine information of antibiotics and biomembrane disruption medicines.
Specifically, after the actual drug resistance of pathogenic bacteria is expressed, the information of the type of pathogenic bacteria and the actual drug resistance are matched with the data in a preset drug resistance gradient database for storing the drug resistance gradient data of various pathogenic bacteria, whether the antibiotics need to be replaced or not is determined, if the antibiotics need to be replaced, the preset antibiotic database for storing the corresponding antibiotic drug lists of various pathogenic bacteria is queried according to the information of the type of pathogenic bacteria, the information of the antibiotics need to be replaced is determined, if the antibiotics do not need to be replaced, namely the actual drug resistance of the current pathogenic bacteria can still be treated by adopting the existing antibiotics, the effect is not maximized only because the antibiotics are influenced by the biological membranes, at the moment, the difference between the actual drug resistance and the apparent drug resistance is determined to be the difference of the drug resistance according to the actual drug resistance and the apparent drug resistance, the difference of the drug resistance can be used for measuring the dosage required by the biological membrane damage drugs, and further the preset biological membrane damage drug database for storing the biological membrane damage drugs corresponding to different pathogenic bacteria is queried according to the information of the drug resistance and the type of pathogenic bacteria, and the combined drug application information is determined.
According to the mode provided by the embodiment, whether the antibiotics need to be replaced or not is judged according to the pathogen type information and the actual drug resistance performance, if the antibiotics need to be replaced, the replacement of the antibiotic information is determined directly according to the pathogen type information, if the antibiotics do not need to be replaced, the drug resistance performance difference is determined according to the actual drug resistance performance and the apparent drug resistance performance, the combined drug information is determined according to the drug resistance performance difference and the pathogen type information, and the drug strategy is determined according to the actual state of bacteria affected by the biological film, so that the drug strategy for coping with the pathogen is more effective.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411471868.XA CN119008037B (en) | 2024-10-22 | 2024-10-22 | A data processing system based on bacterial resistance monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411471868.XA CN119008037B (en) | 2024-10-22 | 2024-10-22 | A data processing system based on bacterial resistance monitoring |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119008037A true CN119008037A (en) | 2024-11-22 |
| CN119008037B CN119008037B (en) | 2025-02-07 |
Family
ID=93484647
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411471868.XA Active CN119008037B (en) | 2024-10-22 | 2024-10-22 | A data processing system based on bacterial resistance monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119008037B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030113742A1 (en) * | 2001-04-20 | 2003-06-19 | University Of Iowa Research Foundation | Methods and compositions for the modulation of biofilm formation |
| US20050151971A1 (en) * | 2004-01-13 | 2005-07-14 | Echo Technologies, Inc. | Real-time biofilm monitoring system |
| CN111759796A (en) * | 2019-03-15 | 2020-10-13 | 华东师范大学 | Antibiotic hydrogel against biofilm and preparation method and application thereof |
| CN113873883A (en) * | 2019-03-15 | 2021-12-31 | 轨迹Ip有限责任公司 | Materials and methods for enhanced treatment and prevention of biofilms |
| CN115181338A (en) * | 2022-07-11 | 2022-10-14 | 上海健康医学院 | An antibacterial film based on polysaccharide cross-linking |
| CN115810391A (en) * | 2022-12-22 | 2023-03-17 | 博奥生物集团有限公司 | Data acquisition method, device, equipment and medium of microbial drug resistance sequence |
| CN116313149A (en) * | 2023-03-09 | 2023-06-23 | 深圳市检验检疫科学研究院 | Method and system for detecting bacterial drug resistance |
| CN117045644A (en) * | 2023-08-10 | 2023-11-14 | 兰州大学 | Composition for effectively inhibiting pseudomonas aeruginosa biofilm bacteria |
| CN118416083A (en) * | 2023-12-08 | 2024-08-02 | 中国科学院理化技术研究所 | A method for using Escherichia coli exopolysaccharide to fight biofilm |
-
2024
- 2024-10-22 CN CN202411471868.XA patent/CN119008037B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030113742A1 (en) * | 2001-04-20 | 2003-06-19 | University Of Iowa Research Foundation | Methods and compositions for the modulation of biofilm formation |
| US20050151971A1 (en) * | 2004-01-13 | 2005-07-14 | Echo Technologies, Inc. | Real-time biofilm monitoring system |
| CN111759796A (en) * | 2019-03-15 | 2020-10-13 | 华东师范大学 | Antibiotic hydrogel against biofilm and preparation method and application thereof |
| CN113873883A (en) * | 2019-03-15 | 2021-12-31 | 轨迹Ip有限责任公司 | Materials and methods for enhanced treatment and prevention of biofilms |
| CN115181338A (en) * | 2022-07-11 | 2022-10-14 | 上海健康医学院 | An antibacterial film based on polysaccharide cross-linking |
| CN115810391A (en) * | 2022-12-22 | 2023-03-17 | 博奥生物集团有限公司 | Data acquisition method, device, equipment and medium of microbial drug resistance sequence |
| CN116313149A (en) * | 2023-03-09 | 2023-06-23 | 深圳市检验检疫科学研究院 | Method and system for detecting bacterial drug resistance |
| CN117045644A (en) * | 2023-08-10 | 2023-11-14 | 兰州大学 | Composition for effectively inhibiting pseudomonas aeruginosa biofilm bacteria |
| CN118416083A (en) * | 2023-12-08 | 2024-08-02 | 中国科学院理化技术研究所 | A method for using Escherichia coli exopolysaccharide to fight biofilm |
Non-Patent Citations (4)
| Title |
|---|
| 尹军霞等: "细菌耐药的机理及抗耐药菌药物的开发", 《绍兴文理学院学报》, no. 08, 30 August 2004 (2004-08-30), pages 52 - 55 * |
| 李宗河等: "宏基因组技术在耐药细菌研究中的应用", 《国外医药(抗生素分册)》, vol. 36, no. 5, 15 September 2015 (2015-09-15) * |
| 葛剑平等: "生物膜细菌耐药性机制的研究近况", 《国际口腔医学杂志》, no. 5, 20 September 2004 (2004-09-20) * |
| 赵智颖等: "生物膜定量分析方法研究进展", 《生物技术进展》, vol. 6, no. 5, 25 September 2016 (2016-09-25) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119008037B (en) | 2025-02-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Danby et al. | Effect of pH on in vitro susceptibility of Candida glabrata and Candida albicans to 11 antifungal agents and implications for clinical use | |
| Schmenger et al. | Characterization, cure rates and associated risks of clinical mastitis in Northern Germany | |
| Cardenas et al. | Dietary apigenin exerts immune-regulatory activity in vivo by reducing NF-κB activity, halting leukocyte infiltration and restoring normal metabolic function | |
| Murrell et al. | Application of a modified form of the Glasgow pain scale in a veterinary teaching centre in the Netherlands | |
| Hogeveen et al. | Sensors and clinical mastitis—The quest for the perfect alert | |
| Ullah et al. | The interrelationship between phagocytosis, autophagy and formation of neutrophil extracellular traps following infection of human neutrophils by Streptococcus pneumoniae | |
| Dirpan et al. | Application of an intelligent sensor and active packaging system based on the bacterial cellulose of Acetobacter xylinum to meat products | |
| Gilbert-Girard et al. | Screening of FDA-approved drugs using a 384-well plate-based biofilm platform: The case of fingolimod | |
| Bokma et al. | Rapid identification of Mycoplasma bovis strains from bovine bronchoalveolar lavage fluid with matrix-assisted laser desorption ionization–time of flight mass spectrometry after enrichment procedure | |
| McLoughlin et al. | Staphylococcus aureus‐mediated blood–brain barrier injury: an in vitro human brain microvascular endothelial cell model | |
| Fukuda et al. | Transcriptional profiling of Candida glabrata during phagocytosis by neutrophils and in the infected mouse spleen | |
| Bausewein et al. | Sensitivity and specificity for the detection of clinical mastitis by automatic milking systems in Bavarian dairy herds | |
| Sullivan et al. | Prospective study of the association between exercise‐induced pulmonary haemorrhage and long‐term performance in T horoughbred racehorses | |
| Xu et al. | The critical role of NLRP6 inflammasome in Streptococcus pneumoniae infection in vitro and in vivo | |
| Bao et al. | Proteomic and transcriptomic analyses indicate reduced biofilm-forming abilities in cefiderocol-resistant Klebsiella pneumoniae | |
| Straticò et al. | Retrospective study on risk factors and short-term outcome of horses referred for colic from 2016 to 2022 | |
| Tang et al. | Pre-treatment with ten-minute carbon dioxide inhalation prevents lipopolysaccharide-induced lung injury in mice via down-regulation of toll-like receptor 4 expression | |
| Post et al. | The importance of low daily risk for the prediction of treatment events of individual dairy cows with sensor systems | |
| CN119008037B (en) | A data processing system based on bacterial resistance monitoring | |
| Gao et al. | Sodium butyrate supplementation modulates neuroinflammatory response aggravated by antibiotic treatment in a mouse model of binge-like ethanol drinking | |
| Wheatcroft et al. | Species-specific song responses emerge as a by-product of tuning to the local dialect | |
| de Andrade et al. | Cyclosporine affects the main virulence factors of Cryptococcus neoformans in vitro | |
| Poore et al. | Clinical characteristics of people with cystic fibrosis and frequent fungal infection | |
| Zecconi et al. | Early milk total and differential cell counts as a diagnostic tool to improve antimicrobial therapy protocols | |
| Biggadike et al. | Evaluation of measurements of the conductivity of quarter milk samples for the early diagnosis of mastitis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |