Experiment

Description

Table of Contents

I. Problems

Skin Wounds Infected Disease

Bacterial skin wound infections are a significant health concern globally, with various studies highlighting their prevalence. For example, a systematic review in 2019 showed that the age-standardized incidence rate for pyoderma was 146.84 million globally, while cellulitis had an incidence of 0.28 million cases. Bacterial skin infections can occur due to minor skin injuries or weakened immune defenses, and in severe cases, they can spread deeper into tissues, causing significant complications.[1, 2]

Antimicrobial Resistance (AMR) Bacteria

In recent decades, due to the overuse of antibiotics, antibiotic-resistant bacteria have emerged. Antimicrobial resistance (AMR) is a significant global health threat, responsible for 1.27 million deaths in 2019 and contributing to 4.95 million deaths. 

In line with WHO recommendations, Taiwan CDC has also established an Antibiotic Resistance Surveillance System to monitor and combat this growing threat.[3, 4]

Antimicrobial resistance (AMR) in skin wound infections is a significant challenge in healthcare. Bacteria such as methicillin-resistant Staphylococcus aureus (MRSA) and other resistant strains can complicate the wound healing process, making infections more difficult to treat.

Fig.1 The Number Of Deaths by GBD Cause and Those Associated with AMR in 2019

II. Background

Causes & Types of Wound Infections

Human body cannot be completely sterile, and the skin hosts various microorganisms, known as normal flora, which maintain a delicate balance with the host. Injury can turn these microorganisms into opportunistic pathogens, leading to infections. Skin and wound infections occur when harmful bacteria invade, either from the environment or the body’s own flora.[5]

And wound infections are mainly classified into the following five types:

  • Chronic wounds: These wounds persist over time and are often linked to ongoing bacterial infections. They are commonly found in individuals with compromised healing abilities due to conditions like diabetes.
  • Superficial infection: This type of infection occurs at the surface of the skin when a wound is exposed to bacteria and not cleaned properly.
  • Deep infection: As the infection progresses, it spreads to deeper tissues, such as the subcutaneous layer or muscle, becoming more severe.
  • Cellulitis: This is an infection that spreads within the skin, leading to inflammation and tissue swelling.
  • Gangrene: In the most severe cases, poor blood supply and untreated infection result in necrosis.

High-Risk Infection Areas

High-risk Infection environments, such as hospitals, military camps are both prone to skin wound infected disease. Frequent contact with pathogens are usually unavoidable in those areas. 

In hospitals, even in sterile environments and the use of antibiotics, according to the sata, a certain proportion of patients who are hospitalized for more than 3 days preoperatively and 7 days postoperatively develop wound infections.[6]

In military camps, crowded conditions, poor hygiene, and sometimes limited medical resources further promote the spread of skin infection disease. In these high-risk infection environments, skin wounds are more susceptible to bacterial colonization, leading to delayed healing and potential complications.

Project Goal

Our project title is “Pandage – An Individualized Approach to Infection Disease Control on Skin Wound Healing with Probiotics”. Since it integrates monitoring, drug delivery, and wound healing promotion. This wearable device will provide real-time monitoring and treatment for patients. Additionally, it will feature a controlled drug delivery system to administer therapeutic agents precisely when needed, thereby optimizing the healing process. 

Based on data-driven control systems, Pandage offers an individualized approach optimizing drug delivery for different wound states or users’ conditions as we attempt to provide care. By leveraging bioelectronics and biocompatible materials, Pandage may offer a comprehensive solution for the effective management of skin wounds infected disease.

The model uses real-time monitoring to automatically release AMP when the bacterial population exceeds a predefined threshold. This ensures efficient infection control without over-suppressing L.lactis, which is crucial for healing.

III. Our Solution

1. Wound Healing Promotion

Lactococcus lactis

To heal a wound, Lactococcus Lactis is engineered to productively secrete the granulocyte-macrophage colony-stimulating factor (GM-CSF) that facilitates a healing process. 

From a high level, two types of sequences are inserted into Lactococcus lactis

  1. Chaperone-associated sequences improve the protein folding efficiency 
  2. Cell-penetrating peptide (CPP)-associated sequences increase secretion of GM-CSF through improving membrane permeability.

Why did we choose Lactococcus lactis? Link Safety 

Growth Factor (GM-CSF)

  1. GM-CSF (Granulocyte-Macrophage Colony-Stimulating Factor) is a critical cytokine primarily produced by immune and bone marrow cells, with its secretion regulated by various cytokines and inflammatory signals. GM-CSF mainly promotes the production of hematopoietic cells in the bone marrow, especially granulocytes and monocytes. Additionally, it activates neutrophils and macrophages, increasing their ability to engulf pathogens, thereby enhancing overall immune system function[7]. 

    Due to its immune-activating function, it can even promote the upregulation of another growth factor, VEGF, leading to accelerated wound healing. Furthermore, GM-CSF binds to specific receptors, initiating downstream signaling pathways that promote cell proliferation and differentiation, such as epithelial cell migration, and fibroblast phenotypic transformation. These are the primary mechanisms through which it accelerates wound healing[8].

    In terms of safety, GM-CSF has no significant side effects. At most, injection site reactions may include pain, swelling, redness, and warmth. Compared to other growth factors, such as PDGF, which has been reported to have a cancer risk[8][9], GM-CSF is considered to have a higher safety profile.

    In this project, GM-CSF is chosen not only for its ability to quickly promote wound healing while enhancing immune function but also for its safety.

2. Auto Detection

Aptamers

An aptamer is a short nucleic acid molecule that, when properly folded into the correct conformation, exhibits high specificity for binding to a particular biomarker. Its advantage lies in its antibody-antigen-like specificity while being relatively cheaper and more stable.

Biomarkers – Lipopolysaccharide(LPS)

Lipopolysaccharide (LPS) is a biomarker commonly found on the outer membrane of Gram-negative bacteria. For the human immune system, LPS is a key antigen used to identify Gram-negative bacterial infections.

In this project, the selected aptamer specifically binds to LPS. Through this selective binding, combined with appropriate hardware assembly, it is possible to detect the presence and current concentration of Gram-negative bacteria using the electrochemical principles that occur during aptamer binding.

3. Auto Drug Release

Antimicrobial peptides (AMPs)

Antimicrobial peptides (AMPs) are a key component of innate immunity and are produced by all known organisms, from bacteria to mammals. Unlike antibiotics, AMPs do not trigger mutation-inducing responses, which helps minimize the development of resistance. This makes them a promising alternative to traditional antibiotics, especially in combating resistant infections.

Moreover, a balanced community of commensal bacteria plays a critical role in maintaining skin health, especially during wound healing process.These microorganisms are essential for regulating immune responses, maintaining the skin barrier, and preventing the colonization of pathogenic bacteria. When antibiotics are used to treat infections, they not only target harmful pathogens but also inadvertently kill beneficial skin commensals. This disruption in the microbial balance, known as dysbiosis, can negatively affect wound healing.

To minimize this risk, AMPs are most suitable to preserve the beneficial skin microbiome while still combating infection.

Drug Releasing Model

To achieve the goal of auto drug releasing, we develop a model that can control an automated drug delivery system, utilizing bacterial concentration levels to determine when to release AMP in the hydrogel. When the bacterial count surpasses a certain threshold, the system signals the drug release unit to deliver a dose of medication to the wound site for effective treatment.

4. Wireless Mobile Application

This mobile application is designed to monitor and manage a smart bandage system. It provides functionalities for user authentication, data visualization, Bluetooth communication, and HTTP-based communication with a Python server. There are a total of three pages in the app, including the entrance page, main page, and communication platform.

The key features including:

  • User login: Users can create new accounts or log in with existing credentials using Firebase, a cloud-based authentication service.
  • Bluetooth Connectivity: The app connects to a Bluetooth module connected to an Arduino Nano for data transfer.
  • Data Visualization:
    1. Battery Life: Displays the remaining battery power of the smart bandage system.
    2. Usage Time: Tracks the duration for which the bandage has been in use.
    3. Pandage Status: Visualizes the levels of medicine, bacteria, and probiotics using progress bars and percentages. Alerts are triggered when these elements reach critical thresholds.
    4. Bacteria concentration and the remaining amount of medicine: Receives data from the bluetooth module.
    5. Probiotic Lifespan: Retrieves the lifespan of probiotics calculated by a growth curve model on a Python server.
    6. HTTP Communication: Enables communication with a Python server running on a PC. Users can send requests and receive responses related to Probiotic Lifespan and Dosage & Threshold Determination. Additionally, they can send parameters for wound type, expected kill efficiency, and healing time to the server for simulation modeling.

5. Intelligent Treatment Model

The Pandage Intelligent Treatment Model focused on automating drug release for wound care. The core system uses mathematical models (ODEs) to simulate the growth and suppression of Gram bacteria (E. coli) and L.lactis under the influence of antimicrobial peptides (AMPs). The goal is to balance bacterial inhibition and healing promotion through dynamic control of AMP dosing.

Automated AMP Release

The model uses real-time monitoring to automatically release AMP when the bacterial population exceeds a predefined threshold. This ensures efficient infection control without over-suppressing L.lactis, which is crucial for healing.

Simulation Scenarios

Various scenarios, like diabetic patients or high-risk military personnel, were simulated to test how different initial conditions affect healing and infection outcomes. The results help define unique dosing strategies for each patient profile.

Machine Learning Integration

A neural network trained on 3,600 simulation cases learns to predict the best AMP dosage and activation thresholds for each wound condition, making the model adaptable and precise in delivering personalized care.

The result is a flexible system that adjusts treatment dynamically to optimize both infection control and wound healing.

IV. Advantages

Individualized Drug Delivery System

During the process of conducting experiments and designing the system, we realized that simply administering drugs at set intervals and monitoring bacterial concentration is insufficient for all patients with infected wounds under different conditions. Therefore, we developed a data-driven model capable of generating the optimized drug delivery methods based on individual needs. Simulate and individualize the treatment course for different users’ conditions. We aim to further advance our Pandage into a commercially viable product tailored to more types of infected wounds and applications.

V. References

[1] https://www.aafp.org/pubs/afp/issues/1998/0515/p2424.html

[2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084187/

[3] https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance

[4] https://www.cdc.gov.tw/En/Category/ListContent/_P6IYUu810pMdu2FcTPp4g?uaid=BKM8MCw654j8jE0c1u4eEw

[5] Robson, Martin C. “Wound infection: a failure of wound healing caused by an imbalance of bacteria.” Surgical Clinics of North America 77.3 (1997): 637-650.

[6] Ashoobi MT, Asgary MR, Sarafi M, Fathalipour N, Pirooz A, Jafaryparvar Z, Rafiei E, Farzin M, Samidoust P, Delshad MSE. Incidence rate and risk factors of surgical wound infection in general surgery patients: A cross-sectional study. Int Wound J. 2023 Sep;20(7):2640-2648.

[7] Yamakawa, Sho, and Kenji Hayashida. “Advances in surgical applications of growth factors for wound healing.” Burns & trauma 7 (2019).

[8] Barrientos, Stephan, et al. “Growth factors and cytokines in wound healing.” Wound repair and regeneration 16.5 (2008): 585-601.