PROCESS, USE AND SYSTEM FOR IDENTIFYING THE HEALTH STATUS OF GALLERIA MELLONELLA LARVAE THROUGH COMPUTATIONAL ANALYSIS OF EPIDERMAL MELANIZATION IN DIGITAL IMAGES

Description

/ 19 “PROCESS, USE AND SYSTEM FOR IDENTIFYING THE HEALTH STATUS OF GALLERIA MELLONELLA LARVAE THROUGH COMPUTATIONAL ANALYSIS OF EPIDERMAL MELANIZATION IN DIGITAL IMAGES” Field of invention

[001] The present invention relates to a process for identifying the health status of Galleria mellonella larvae by means of computational analysis of digital images that show different intensities of melanization of the larvae's epidermis, solving the limitations found in the manual analysis of the visualization of this melanization, being especially relevant for rapid screenings in pharmaceutical research and pathogenicity studies.

[002] More specifically, the present invention belongs to the field of biotechnology and bioinformatics, with relevant industrial applications in the pharmaceutical, biomedical research and quality control of biological products. The described process is particularly useful in identifying and monitoring the health status of Galleria mellonella larvae, widely used as models in studies of innate immunity, pathogenicity, toxicity, as well as in the discovery and testing present in the development stages of drugs or other bioactive compounds. The invention stands out for automating the analysis of larval melanization, a crucial indicator of immune response, using digital image processing, which facilitates large-scale screenings with greater precision and reproducibility. Fundamentals of the invention

[003] Galleria mellonella larvae, also known as wax moths, have become established as a widely used experimental biological model in pathogenicity and immunology studies since 1938 [Minireview Petition 870240111523, 12 / 31 / 2024, p. 5 / 33 / 19 Pathogens and Disease, 79, 2021 (doi: 10.1093 / femspd / ftab006)], making them a valuable model system for studying pathogen-host interactions and developing new drugs. This is due to the similarity of their immune response to that of mammals. This makes them an excellent alternative for research aimed at reducing the use of vertebrate models in experimentation.

[004] In addition to Galleria mellonella, other invertebrate models, such as the fruit fly (Drosophila melanogaster) and the nematode (Caenorhabditis elegans), are used in similar research. However, Galleria mellonella larvae offer significant advantages, including the ability to survive at 37°C, a temperature close to that of the human body, and the absence of stringent ethical requirements. These characteristics make them more practical and economical, since they also do not require high investments in laboratory infrastructure.

[005] The prophenoloxidase (PO) pathway in Galleria mellonella larvae plays a crucial role in the immune system of these insects, which share some similarities with the immune system of mammals. PO is an enzyme that, when activated, initiates a cascade of reactions leading to melanization, a process in which melanin is deposited around invading pathogens. This encapsulation helps neutralize microorganisms, performing a function similar to the complement system in mammals. The existence of this pathway makes G. mellonella an effective model for studies of innate immunity, especially since melanization can be easily observed and quantified in experiments.

[006] Thus, the use of Galleria mellonella as an experimental model is widely validated due to the aforementioned functional similarity of its immunity to the innate immune response of mammals. The larvae possess hemocytes, which are equivalent to the phagocytic cells of mammals, and a hemolymph rich in antimicrobial peptides and pattern recognition proteins. The simplicity of its immune system, along Petition 870240111523, dated 12 / 31 / 2024, page 6 / 33 / 19, with the ability to withstand temperatures similar to those of the human body, allows G. mellonella to be a practical and ethical substitute for preclinical studies of pathogenicity and efficacy of antimicrobial compounds. The prophenoloxidase pathway is, therefore, one of the key aspects that reinforces the relevance of this organism as an experimental model for the study of pathogen-host interactions and immune response.

[007] Traditionally, the identification of the health status of Galleria mellonella larvae has been carried out manually, with researchers observing visual changes, such as melanization of the epidermis. This process involves direct inspection of the larvae, where the degree of darkening of their surface is assessed, an indication of an active immune response and, consequently, of a compromised health status. This method, although used for decades, has considerable limitations, such as subjectivity in the analysis, variability between observers, and the difficulty of standardizing the results. Scientific articles, such as that of Tsai et al. [Tsai, CJ-Y., Loh, JM, & Proft, T. (2016). Galleria mellonella infection models for the study of bacterial diseases and for antimicrobial drug testing. Virulence, 7(3), 214-229. doi:10.1080 / 21505594.2015.[1135289], discuss these challenges and the need for greater standardization and objectivity in assessing the health status of larvae, especially in studies that require high reproducibility.

[008] In the global context, tests performed with Galleria mellonella have increasing economic importance. Estimates indicate that the market for research and development of new drugs moves billions of dollars annually, and the use of alternative models, such as Galleria mellonella, has proven fundamental to accelerating the process of discovery and testing of new compounds, reducing costs and time associated with the use of vertebrate models in early screening stages. Petition 870240111523, dated 12 / 31 / 2024, page 7 / 33 / 19

[009] Due to its increasing importance, efforts have been directed towards solving the limitations found in the manual analysis of melanization in G. mellonella larvae, regardless of its application. As we can observe in the article by Champion et al. [Champion OL et al. Standardization of G. mellonella Larvae to Provide Reliable and Reproducible Results in the Study of Fungal Pathogens. Journal of Fungi 2018], which discusses the use of Galleria mellonella as an infection model, mentioning melanization as a health indicator. Champion uses the change in the appearance of the larvae (epidermal coloration) to infer the level of pathogenicity, when compared to the appearance of healthy larvae. However, he does not address the application of image processing technologies for this analysis, remaining focused on manual methods and experimental protocols that have great subjectivity and lack of homogeneity between different analyses.

[0010] The article by Kavanagh et al. [Aaron Curtis, Ulrike Binder and Kevin Kavanagh. G. mellonella Larvae as a Model to Investigate Fungal-Host Interactions. Front. Fungal Biol., vol. 3, April 25, 2022] explores fungus-host interaction and the relevance of melanization for in vivo toxicity testing and the efficacy of antifungal agents. However, it presents a “cryovisualization” of microscopy images and, again, does not mention a computational method for analyzing the results.

[0011] Finally, the article by Serrano et al. [Isa Serrano, Cláudia Verdial, Luís Tavares and Manuela Oliveira. The Virtuous Galleria mellonella Model for Scientific Experimentation - Antibiotics 2023, 12, 505] provides a comprehensive review of the use of larvae in scientific experiments, including melanization as a marker of immune response. It highlights the correlation between the speed of melanization and the degree of virulence, stating that melanization covers the larva's cuticle with black spots until it is dead and completely melanized. The main objective of the article is to Petition 870240111523, dated 12 / 31 / 2024, page 8 / 33 / 19, discusses the development of a standardization of the parameters used in the protocols of different studies that use G. mellonella. This would allow for a better comparison between different experiments conducted in different laboratories. It even reports on the "health index scoring system" introduced in 2013 by Loh et al., which classifies the larva as "survival," "mobility," "melanization," and "coccon formation." The higher the score, the healthier the larva. This has great application in drug screening in different areas. However, it does not address any use of computational image processing or any technique that would allow for greater automation of this analysis.

[0012] These documents show that, although the correlation between melanization and the health status of larvae is well established, the use of digital image processing to perform this task in an automated way has not been previously proposed. This gap opens up space for the development of new solutions that offer greater speed, more homogeneous results and reduced subjectivity, increasing the reliability of experiments, which is fundamental for the development of drugs and other applications in a sector so critical to human and animal health.

[0013] Given this scenario, despite all the progress, there are still technical problems to be solved, and it is possible to observe that the development of automated tests to identify the health status of G. mellonella larvae would be of great value to the field of bioinformatics and biotechnology, obtaining results with less error and greater speed, without substantial increases in investment in existing laboratory infrastructure. Brief Description of the Invention

[0014] The present invention relates to the PROCESS, USE AND SYSTEM FOR IDENTIFYING THE HEALTH STATUS OF GALLERIA MELLONELLA LARVAE BY MEANS OF COMPUTATIONAL ANALYSIS OF Petition 870240111523, dated 12 / 31 / 2024, page 9 / 33 / 19 EPIDERMAL MELANIZATION IN DIGITAL IMAGES thus emerges as a solution to the limitations associated with traditional analysis methods, proposing an automated process that uses digital image processing to identify the health status of larvae, based on the analysis of the degree of epidermal melanization. This process not only increases the accuracy of the analysis, mitigating subjectivity, but also allows for robust standardization of results, essential for large-scale screenings.

[0015] Thus, the first embodiment of the invention relates to an automated process for identifying the health status of Galleria mellonella larvae by means of epidermal melanization analysis. Using digital image processing software, the system isolates and analyzes the melanized areas of the larvae from digital photographs, correlating the intensity of melanization with the health status of the larvae.

[0016] More specifically, this first method refers to a process for identifying the percentage of melanization of each larva present in a digital image and its correlation with its health status. To perform the melanization identification, the larvae are infected with different concentrations of pathogenic bacteria in order to promote an immune response. According to the infective dose and the pathogenicity of the microorganism chosen for the test, pigmentation begins and spreads over the animal's surface, with patterns related to the infection model adopted. The digital images are captured under controlled lighting conditions and are then subjected to morphological operations that allow the identification, delimitation, and analysis of the epidermal color characteristics of the larvae.

[0017] The intensity of melanization is measured and compared with reference parameters to classify larvae into different health states, indicating their immune response. The presence of pigments on the epidermal surface demonstrates an insect's response against the presence and virulence factors of Petition 870240111523, dated 12 / 31 / 2024, page 10 / 33 / 19 bacteria. Bacteria that express more virulence factors such as enzymes and toxins are more pathogenic and require a smaller number of colony-forming units to stimulate host defenses in an attempt to control infection. Thus, a greater number of melanization points characterizes a more severe state of health in experimental biomodels.

[0018] In general, we can describe the process of identifying the health status of Galleria mellonella larvae as an automated processing of digital images of the larvae, capable of identifying melanized areas and measuring their intensity in each larva present in the image, comparing them with experimental reference parameters. This can generate a percentage value of melanization that correlates as a direct indicator of the immunological response of these experimental biomodels, classifying the different health states of the larvae after exposure to different pathogens, compounds, and / or other experimental conditions of interest. This allows it to be applied in studies of pathogen-host interactions, in the evaluation of the efficacy and toxicity of antimicrobial and antineoplastic compounds, and in other phases of preclinical testing for the development of bioactive compounds. It can be defined by the following general steps: a) Preparation of samples and larvae, according to the desired experimental design, exposing the larvae to the pathogens and / or compounds to be studied; b) capturing digital images of Galleria mellonella larvae using digital cameras in a controlled experimental environment; c) computational image processing, configured to perform morphological operations that allow for the precise identification of melanized areas; d) Melanization analysis, evaluating the epidermal color characteristics of the larvae and comparing them with tolerance reference parameters; (e) classification of the health status of the larvae based on the intensity of melanization; and Petition 870240111523, dated 12 / 31 / 2024, page 11 / 33 / 19 f) generation of results for the user, adjusted so that the greater the number of melanization points, the more severe the health status of the experimental biomodels.

[0019] The second embodiment of the present invention involves the use of digital images of Galleria mellonella larvae for scientific and experimental modeling analysis. In vivo experiments can be conducted using various routes of administration, such as oral, intrahemocoelic or subcutaneous, allowing the exploration of different aspects of the host-parasite relationship, including the amount of pathogens in the inoculum and the routes of administration. In addition, different sites and cellular components, such as hemolymph, hemocytes, fat body, trachea and intestine, can be analyzed.Therefore, sample preparation and experimental conditions will depend on the exact assay proposed by the user, which is not limiting to the scope of the present invention, and can be easily adapted by a person skilled in the art to the automated biomodel proposed herein, which focuses on the computational analysis of digital images, providing a faster and more objective study with regard to the reproducibility of results.

[0020] In other words, the captured images are used to create a more reliable, automated in vivo experimental model, replacing human visual and subjective analysis, and becoming capable of converting, in a more homogeneous and direct way, the intensity of melanization into a marker of the immunological health of the larvae and, subsequently, obtaining a model of the pathogen-host interaction or even a model of pathogenicity or toxicity, which can be used in different applications, such as in the evaluation of the toxicity of drugs or even in the effectiveness of antimicrobial, antifungal, antineoplastic compounds, among others.

[0021] Thus, in general, we can state that the use of computational analysis of digital images of Galleria mellonella larvae can be briefly described as being for the generation or fabrication of a Petition 870240111523, dated 12 / 31 / 2024, page 12 / 33 / 19 automated experimental biomodel, aimed at studying pathogen-host interactions, as well as evaluating the efficacy and toxicity of bioactive compounds, pathogens or drugs / medicines, in which larvae are exposed, altering their health status, which is monitored through the analysis of the epidermal melanization process, using a computational system capable of correlating the intensity of melanization with an indicator of the larvae's immune response, and can even be applied in pre-clinical testing stages for the development of new drugs, foods or cosmetics.

[0022] The third embodiment refers to a computational identification system for the health status of larvae developed to implement the process described in the first embodiment. The system consists of at least one module for image capture, image processing, analysis, data storage, and a user interface. It is designed to capture images of the larvae, process them to isolate the epidermis, calculate the intensity of melanization, and finally classify the health status of the larvae based on predefined criteria, presenting the results in a clear and accessible way to the user, as illustrated in the flowchart (Figure 4).

[0023] The flowchart illustrated in Figure 4 represents the operational sequence of the proposed system for identifying the health status of Galleria mellonella larvae through computational analysis of epidermal melanization. Initially, the user configures the software on a computer or compatible device in a standardized experimental environment. The larvae are placed in a Petri dish, and the camera or smartphone is adjusted to capture images with uniform lighting and a neutral background, ensuring consistency in capture conditions.

[0024] After adjusting the camera, the user takes one or more photographs of Galleria mellonella larvae, and can calibrate the software's tolerance and contrast parameters to optimize the quality of the analysis. These images are Petition 870240111523, dated 12 / 31 / 2024, page 13 / 33 / 19 processed in real time by the software, which applies algorithms to identify and quantify the melanized areas, correlating the intensity of melanization with the health status of the larvae.

[0025] The system immediately displays the analysis results and offers options for archiving the data in various formats, which facilitates future access and comparison between experiments. The software thus allows the user to adjust the output parameters as needed for different experimental conditions, ensuring flexibility and accuracy in identifying the health status of the larvae.

[0026] This simplified system described in the flowchart offers an automated solution that minimizes human error and promotes more homogeneous results, essential for large-scale studies and rapid screenings of bioactive compounds.

[0027] The system may include other components and processes present in the state of the art or that may yet be developed, provided that they do not alter the immune response of the automated in vivo experimental model that is the basis of this process. Brief Description of the Figures • Figure 1 shows a photographic image of Galleria mellonella larvae after infection. • Figure 2 shows an image after computational analysis of melanization intensity (expressed as a percentage) and its classification into healthy (green), diseased (yellow), and dead (red). • Figure 3 presents a table containing the calculated brightness values ​​for each of the infected larvae from Figure 2. Petition 870240111523, dated 12 / 31 / 2024, page 14 / 33 / 19 • Figure 4, item (a), presents a flowchart representing a main computer running the software, which receives photographic information produced by a digital camera or smartphone within the standardized lighting experimental environment. This environment contains the studied Galleria mellonella specimens, whose photographs are processed by the software in question, producing results based on parameters adjustable in real time. Item (b) of Figure 4 presents a flowchart representing the usual operation flow of the software, from the production of the digital photograph to the production of real-time results, parametric adjustment, and subsequent storage of the obtained data. Detailed Description of the Invention

[0028] The present invention therefore relates to a process, use and system for identifying the health status of Galleria mellonella larvae by analyzing the melanization process of the epidermis, using digital images processed by a computer system.

[0029] More specifically, the invention comprises a process for identifying the health status of larvae, the use of digital images of larvae for experimental and scientific purposes (Figures 1 and 2), and a computational system that implements the identification process, capable of generating an indicator of the larvae's immune response after exposure to pathogenic agents and / or target compounds of study, by quantifying the intensity of melanization of the larvae's epidermis (Figures 2 and 3), and thus enabling faster, more precise and reproducible classification of the larvae's health status. This solves the limitations found in the manual analysis of (human) visualization of this melanization, being especially relevant for rapid screenings in pharmaceutical research, or even in other industries such as cosmetics and food. As well as Petition 870240111523, dated 12 / 31 / 2024, page 15 / 33 / 19 in studies of pathogen-host interaction and procedures in biomedical and biotechnological research laboratories.

[0030] Like other insects, G. mellonella does not possess an adaptive immune system. However, its innate immune system is considered highly similar to that of mammals, particularly in relation to the cellular immune response, mediated by hemocytes, cells similar to mammalian neutrophils. Insects possess anatomical and physiological barriers that protect them against invading microorganisms. G. mellonella is externally protected by the cuticle, a hardened covering formed by a single layer of epithelium (epidermis) impregnated with chitin. In addition, internal organs such as the trachea and intestine also contain chitin, providing additional protection against invading pathogens. When these barriers are breached, the immune system's defense mechanisms are activated, which are exclusively innate in insects, depending solely on elements encoded by the germline.

[0031] This innate immune response is divided into two pathways: cellular and humoral. The cellular pathway is mediated by hemocytes, which perform phagocytosis of invaders or group them into multicellular structures called nodules or capsules, playing a role analogous to neutrophils and macrophages in mammals. On the other hand, the humoral pathway involves processes such as melanization, coagulation, production of antimicrobial peptides (AMPs) and reactive oxygen and nitrogen molecules.

[0032] Melanins are pigmented biopolymers derived from phenolic compounds, such as tyrosine, with an estimated origin of over 500 million years ago, found in insects and mammals, performing distinct primary functions in each group. In mammals, melanin production is essential for the pigmentation of hair, eyes, and skin, as well as contributing to protection against solar radiation. In insects, melanin is crucial for the functioning Petition 870240111523, dated 12 / 31 / 2024, page 16 / 33 / 19 of the innate immune system, exoskeleton coloration, sclerotization and wound healing.

[0033] Melanin can be deposited on the surface of pathogens, facilitating their elimination, generally accompanying the hemolymph coagulation process, making the clot harder and preventing hemolymph efflux until the epidermis is restored. Furthermore, it can be present in the encapsulation process (cellular encapsulation) or capsule formation without the presence of hemocytes (humoral encapsulation), being involved in immunity and wound healing. After injury or infection, the phenol oxidase system is released from hemocytes (oenocytoids). It contains prophenol oxidase, which is a proenzyme that needs to be digested by serine proteases into the active enzyme (PO). In parallel, serpins (serine protease inhibitors), which are part of the phenoloxidase complex, prevent enzymatic hyperactivation, which can be dangerous to the host due to the release of free radicals in melanin synthesis.In insects, melanin production is directly linked to the activation of the prophenoloxidase (proPO) system, which is rapidly triggered in response to pathogen invasion or cuticle damage. Oenocytoids secrete prophenoloxidase (inactive form), which, once activated, has the ability to eliminate pathogens by producing highly toxic compounds, inducing mechanisms such as phagocytosis, encapsulation, or hemolymph coagulation in response to invasion.

[0034] The proPO system cascade, culminating in melanin production, is mediated by the redox enzyme phenoloxidase. Interestingly, in mammals, melanin production is catalyzed by tyrosinase, an enzyme with activities similar to insect phenoloxidase, although they share little homology. Activation of the proPO system can be triggered by pathogen-associated molecular patterns (PAMPs), such as bacterial lipopolysaccharides and peptidoglycans, or other stimuli, such as wounds or altered cell apoptosis. In G. mellonella, apolipophorin III generally activates the proPO system. Petition 870240111523, dated 12 / 31 / 2024, page 17 / 33 / 19 converting pro-phenoloxidase (proP) into phenoloxidase (PO), which plays an essential role in melanin production through quinone polymerization.

[0035] In this context, the captured images were used to fabricate an automated in vivo experimental model, capable of evaluating the intensity of melanization as a marker of the immunological health of larvae and, subsequently, as a model of pathogen-host interaction and / or in the evaluation of drug toxicity and / or the efficacy of antimicrobial, antifungal, antineoplastic compounds, among others.

[0036] Given this mechanism of action, the automated identification process of melanization in Galleria mellonella larvae is able to identify their state of health.

[0037] More specifically, the process comprises the following steps: a) Image Capture: Initially, digital images of Galleria mellonella larvae are captured using a digital camera under controlled lighting conditions (Figures 1 and 2), with uniform capture angle and light source throughout the photographs used in the same experiment, as well as a high-contrast monochromatic background and the absence of any unnecessary external elements. The lighting conditions are adjusted to highlight the characteristics of the larvae's epidermis, facilitating subsequent analysis. The existence of a tolerance control parameter in the program's processing stage allows flexibility in adjusting light and focus levels to the circumstantial limitations of each laboratory environment, provided there is consistency between the photographs used in the same experiment. b) Image Processing: The captured images undergo morphological processing, in which a succession of algorithms is applied to intensify the contrast between the colors that make up the larvae and the other colors present in the image (a step that highlights the Petition 870240111523, dated 12 / 31 / 2024, page 18 / 33 / 19 (requirement of a controlled environment for taking photographs), makes it possible to trace outlines (which may have different colors depending on the health of the larva - see Figure 2) relating to the surface of the larvae in the image, delimiting their entirety and identifying the position of their centroid, or geometric center, in a coordinate system. c) Melanization Analysis: After processing, a mask containing all the pixels of each larva is created, allowing the calculation of the arithmetic mean brightness (sum of the individual brightness of each pixel divided by the total number of pixels within the outline) of the specimens' epidermis, used to determine the intensity of melanization. The intensity of melanization is compared with the tolerance reference parameter, adjustable to suit the lighting and contrast conditions of the experimental environment, according to reference specimens selected by the operator, which correspond to different health states of the larvae (Figure 2). The user can optionally use a larva of known health status to calibrate the tolerance to light and contrast levels of the images produced on their bench with their own equipment. d) Health Status Classification: Based on melanization analysis, larvae are classified into different health categories, such as healthy, moderately compromised, and severely compromised. This classification aids in understanding the immune response of the larvae and in estimating risk through the use of specimens in future trials.

[0038] The use of digital images of larvae for experimental purposes focuses on the study of pathogen-host interactions and the evaluation of antimicrobial, antifungal, or antineoplastic compounds. This use is based on images captured and processed as described in the first modality.

[0039] In the case of pathogen-host interactions, processed images of larvae can be used to monitor the immune response of larvae when exposed to different pathogens. The intensity of melanization Petition 870240111523, dated 12 / 31 / 2024, page 19 / 33 / 19 serves as a direct indicator of the immune response, allowing researchers to assess the virulence of the pathogen and the effectiveness of immune responses.

[0040] In the case of evaluating the effectiveness of antimicrobial or antifungal compounds, the use of images focuses on the reduction of melanization in treated larvae, which may indicate the effectiveness of the compound in reducing the pathogenic load or in modulating the immune response.

[0041] In the case of toxicity assessments, such as with antineoplastic drugs, the introduction of these products into the environment may cause changes in the health status of larvae, indicating the risk of using such a drug candidate in vertebrates.

[0042] The computational system for implementing the process of identifying the health status of Galleria mellonella larvae is capable of implementing the process described in the first embodiment. This system operates through the following modules, as illustrated in the flowchart in Figure 4: a) Image Capture Module: Configured to capture digital images of Galleria mellonella larvae in a standardized and controlled experimental environment, with uniform lighting and a neutral background. This module can be operated automatically or allows the user to make camera and lighting adjustments to ensure image quality and consistency of experimental conditions. b) Image Processing Module: Responsible for performing morphological operations on captured images, identifying and delimiting the epidermal area of ​​the larvae. This module primarily uses the HSV (Hue, Saturation, Value) color system, but can be replaced by other computational algorithms to extract color characteristics that indicate the presence and intensity of melanization. c) Analysis Module: Configured to calculate the average brightness of pixels in the segmented area of ​​the larvae's epidermis, allowing for the evaluation of... Petition 870240111523, dated 12 / 31 / 2024, page 20 / 33 / 19 intensity of melanization. Based on adjustable tolerance parameters, the module automatically classifies larvae into different health states, such as healthy, moderately compromised, or severely compromised. These parameters can be calibrated for each experimental environment, optimizing the accuracy of the analysis. d) Data Storage Module: Stores processed images and analysis results, allowing the user to retrieve and compare data in future experiments. This module can be integrated with databases to facilitate information management and sharing, as well as allowing comparison of results between different experiments, ensuring traceability and consistency in the data. e) User Interface Module: Provides a user-friendly and intuitive interface so that users (e.g., researchers) can interact with the system in real time, viewing analysis results and adjusting experiment parameters. The interface may include graphical visualizations of images and health status classification results. It may also include controls to calibrate the system's tolerance to lighting and contrast conditions as needed, in addition to offering a clear and accessible visualization of information. f) Automated Operational Flow: As described in the flowchart, the system begins with the user configuring and calibrating the equipment, followed by image capture, automatic data processing and analysis, and concluding with the display and archiving of results. Examples Example 1: Evaluation of health status through mechanization of larvae infected with Staphylococcus aureus using computational analysis of digital images.

[0043] Galleria mellonella larvae weighing between 0.2 - 0.3 g, fed ad libitum in the dark at 30°C, were inoculated with 5 microliters and of Petition 870240111523, dated 12 / 31 / 2024, page 21 / 33 / 19 suspensions of bacteria of the species Staphylococcus aureus at concentrations of 102, 103 and 104 colony-forming units per milliliter, using a syringe with a 31 G intradermal needle in its last proleg. After inoculation, the larvae were kept fasting, at a temperature of 30 degrees Celsius and photographed at 10-minute intervals for 18 hours (Figure 1).

[0044] The larvae were classified as dead, diseased, and healthy (Figure 2). Uninfected larvae were used as a control. Table 1: Percentage of healthy larvae Concentration 24 h 48 h 72 h 96 h 102 CFU / mL 80 60 0 0 103 CFU / mL 80 80 60 20 104 CFU / mL 100 100 80 80 Negative control 100 100 100 100

[0045] The number of microorganisms used for infection was expressed in colony-forming units per milliliter (CFU / mL).

[0046] A correlation was established between the arithmetic mean brightness intensity (sum of the individual brightness of each pixel divided by the total number of pixels inside the contour) of the epidermis of infected larvae from each experimental group, used to determine the intensity of melanization and the survival of the larvae at different time periods (Figure 3). A direct relationship was observed between the intensity of melanization and survival of G. mellonella, allowing the assessment of its health status.

[0047] The examples presented and the preferred and optional descriptions given serve only to illustrate or better define the invention and should not be interpreted as limiting its scope. It is important to note that minor modifications, alterations, and variations may be introduced by Petition 870240111523, dated 12 / 31 / 2024, page 22 / 33 / 19 those skilled in the art without deviating from the scope of the invention, as defined in the appended claims. Petition 870240111523, dated 12 / 31 / 2024, page 23 / 33

Claims

1 / 4 Claims 1. PROCESS FOR IDENTIFYING THE HEALTH STATUS OF Galleria mellonella LARVAE characterized by being an automated processing of digital images of Galleria mellonella larvae, capable of identifying melanized areas and measuring their intensity in each larva present in the image, comparing with experimental reference parameters, and generating a percentage value of melanization that becomes a direct indicator of the immunological response of these experimental biomodels, classifying more quickly and accurately between the different health states of the larvae, after infection or exposure to different pathogens, compounds and / or other experimental conditions of interest, allowing it to be applied in studies of pathogen-host interactions, in the evaluation of the efficacy and toxicity of antimicrobial and antineoplastic compounds, and in other phases of preclinical testing for the development of bioactive compounds,comprising the following steps: a) Preparation of samples and larvae according to experimental design; b) capture of digital images of Galleria mellonella larvae using digital cameras; c) computational processing of the images, configured to perform morphological operations that allow the identification of melanized areas; d) melanization analysis, evaluating the epidermal color characteristics of the larvae by comparing them with tolerance reference parameters; e) classification of the health status of the larvae based on the intensity of melanization; f) generation of results for the user, adjusted so that the greater the number of melanization points, the more severe the health status of the experimental biomodels. Petition 870240111523, dated 12 / 31 / 2024, page 24 / 33 2 / 4, 2. PROCESS, according to claim 1, characterized by the image processing as defined in step c, being able to apply a succession of algorithms that intensify the contrast between the colors that make up the larvae with the other colors present in the image, preferably converting the image captured in a controlled environment to the HSV (Hue, Saturation, Value) color space, performing the segmentation of the area corresponding to the epidermis of the larva, and generating the calculation of the average brightness of the pixels in the segmented area, making it possible to trace contours referring to the surface of the larvae in the image, delimiting its totality and identifying the position of its centroid, or geometric center, in a coordinate system.

3. PROCESS, according to claim 1, characterized by the melanization analysis, as defined in step d, preferably creating a mask containing all the pixels of each larva, with which it is possible to calculate the arithmetic mean brightness, this being the sum of the individual brightness of each pixel divided by the total number of pixels inside the epidermal contour of the specimens, used to determine the intensity of melanization and, subsequently, infer the intensity of melanization by comparison with the tolerance reference parameter, adjustable to the lighting and contrast conditions of the experimental environment.

4. PROCESS, according to claim 1, characterized by the classification of the health status of the larvae, as defined in step e, being carried out using a calibratable tolerance parameter, correlating melanization with the level of immune response, classifying them into different health categories, which may be: a) healthy, moderately compromised and severely compromised; b) dead, diseased and healthy; or as per desired experimental design.

5. PROCESS, according to any of the preceding claims, characterized by the fact that studies of the pathogen-host relationship can be used to analyze the virulence of the pathogen, the effectiveness of immune responses and other parameters of pathogenicity tests and rapid screenings in research in the pharmaceutical, cosmetic and food industries, or even in biomedical and biotechnological research procedures.

6. USE OF DIGITAL IMAGES OF Galleria mellonella LARVAE characterized by being for the fabrication of an automated experimental biomodel for the study of pathogen-host interactions and evaluation of the efficacy and toxicity of bioactive compounds, such as antibiotics, fungicides and antineoplastics, in which the larvae are exposed in a test phase and their health status is monitored through the analysis of the epidermal melanization process, as defined in claims 1 to 5, using a computational system, as defined in claim 7, in which the intensity of melanization becomes an indicator of the larvae's immune response, and can be applied in pre-clinical testing stages for the development of medicines or even food or cosmetics.

7. SYSTEM FOR IDENTIFYING THE HEALTH STATUS OF Galleria mellonella LARVAE characterized by being based on the analysis of the epidermal melanization process, as defined in claims 1 to 5, comprising: a) one or more image capture modules configured to obtain digital images of Galleria mellonella larvae under controlled lighting conditions; b) an image processing module, configured to perform morphological operations on the obtained images, including the identification and delimitation of larvae in the images and the extraction of color characteristics using, preferably, the HSV (Hue, Saturation, Value) color system; c) an analysis module, configured to calculate the average brightness of the pixels corresponding to the epidermis of the larvae and to classify the larvae into different health states based on intensity. Petition 870240111523, dated 12 / 31 / 2024, p.26 / 33 4 / 4 of melanization, using previously established tolerance parameters; d) one or more data storage modules, configured to record the processed images and the results of the analyses performed; e) one or more user interface modules, configured to display the results of the classification of the health status of the larvae and allow user interaction with the system. Petition 870240111523, dated 12 / 31 / 2024, page 27 / 33.

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