Biohybrid Biosensor
The QDot Patch

Summary

The QDot Patch is designed as a breathable, skin-mounted interface that enables real-time, multiplexed monitoring through specialised sensors capable of detecting neurochemicals, inflammatory biomarkers, metabolic indicators, wound-related signals, and environmental toxins.

Introduction

Wearable biosensors have become central to modern health monitoring, offering real-time insights into heart rate, glucose levels, and physical activity. Yet despite their promise, most commercial devices remain limited in scope and design. These limitations include:

  • Narrow biomarker range. Critical indicators related to mental health, immune response, and environmental exposure have been overlooked (Gao et al., 2016). Neurochemicals, cytokines, and environmental toxins remain largely inaccessible to current platforms, despite their relevance to stress, inflammation, and pollution-related illness.
  • Synthetic construction. Devices typically rely on plastics, silicones, and metals, which are often uncomfortable for extended wear (Bandodkar et al., 2014). These materials offer limited breathability and poor integration with biological systems, especially in wound margins or sensitive skin areas.
  • High cost and limited access. Proprietary platforms such as Dexcom and FreeStyle Libre can cost hundreds of euros per month, making them inaccessible to many users. The broader issue of cost and accessibility is addressed in reviews of wearable biosensor platforms (Vo & Trinh, 2024). Moreover, the reliance on externally synthesised reagents and invasive sampling methods adds to operational expense.
  • Limited adaptability. Rigid electronics struggle to conform to the contours and movement of human skin, which can compromise both comfort and data accuracy (Heikenfeld et al., 2018). This rigidity also limits the potential for multiplexed sensing across dynamic physiological states.

At the same time, the demand for broader biosensing capabilities is growing. Mental health conditions, autoimmune disorders, and pollution-related illnesses are on the rise globally, yet remain under-monitored in everyday life (Safari, 2022; Vo & Trinh, 2024). These conditions often involve fluctuating biomarkers that require continuous, non-invasive tracking, which is something current devices are poorly equipped to deliver.

This raises a provocative possibility: what if biosensors could evolve to become smarter, more sensitive, more affordable, and capable of monitoring a wider spectrum of human health? Imagine a sensing substrate that doesn’t merely host external components but actively participates in the generation of quantum dots—producing nanocrystals within a breathable, biocompatible matrix. Quantum dots are uniquely suited for this role because of their exceptional optical and electronic properties: they offer tunable fluorescence for multiplexed detection, high sensitivity at low concentrations, and remarkable stability compared to traditional dyes or organic markers. By embedding their synthesis directly into the substrate, biosensors could achieve seamless integration, reducing manufacturing complexity while enhancing performance. Such a paradigm shift would redefine wearable biosensing—transforming it from rigid, synthetic assemblies into biologically inspired interfaces that adapt to the dynamic chemistry of the human body.

Proposal for a Biohybrid Biosensor – The QDot Patch

Wearable biosensors are evolving rapidly, yet most platforms remain constrained by synthetic substrates, limited biomarker coverage, and costly fabrication. This proposal introduces a fundamentally different approach: a biohybrid sensor that integrates quantum dot biosensing directly into a living fungal matrix. The QDot Patch is envisioned as a skin-mounted, breathable interface capable of real-time, multiplexed detection of neurochemicals, cytokines, pathogens, environmental toxins, and metabolic markers..

Unlike conventional systems that embed externally synthesised quantum dots into rigid polymers or carbon-based matrices, this concept explores the potential for in situ quantum dot generation within the mycelial substrate itself. Certain fungal strains have demonstrated the ability to biosynthesise nanocrystals such as CdS and carbon-based quantum dots through metabolic pathways involving glutathione and metal precursors (Jin et al., 2023; Safari, 2022). This biosynthetic capacity offers a transformative advantage: the sensing substrate becomes both the structural scaffold and the nanomaterial factory.

In situ quantum dot generation simplifies manufacturing by eliminating the need for external synthesis, purification, and deposition. It enhances uniformity across sensing zones, reduces reagent costs, and supports a more sustainable fabrication process. Biosynthesised quantum dots may also exhibit improved biocompatibility and photostability due to their protein-capped surfaces and integration within the native fungal matrix (Jin et al., 2023; Elsacker et al., 2021). This approach aligns with broader goals in decentralised diagnostics, offering a low-cost, scalable alternative to synthetic platforms.

To support the full range of biosensing applications envisioned for the QDot Patch, a diverse set of quantum dot chemistries must be incorporated. These include CdSe/ZnS and carbon quantum dots for detecting neurochemicals such as cortisol, dopamine, and serotonin (Chen et al., 2025; Safari, 2022); CdTe and CdSe quantum dots for immune markers including IL-6, TNF-α, and histamine (Jin et al., 2023); InP and ZnS quantum dots for pathogen antigens (Safari, 2022); black phosphorus and carbon quantum dots for heavy metal ions such as lead, mercury, and cadmium (Safari, 2022); graphene and carbon quantum dots for volatile organic compounds including benzene and formaldehyde (Lee et al., 2024); neodymium-doped carbon quantum dots for radiation detection in the near-infrared range (Safari, 2022); and CdSe, ZnS, and carbon quantum dots for metabolic markers such as glucose, lactate, pH, electrolytes, and uric acid (Jin et al., 2022; Safari, 2022). Temperature-sensitive quantum dots may also be used for wound monitoring in smart bandage applications (Vo & Trinh, 2024).

These nanocrystals must be functionalised with biomolecular ligands such as antibodies, aptamers, or enzymes to confer specificity for each target analyte. The fibrous architecture of the mycelium provides a high-surface-area scaffold for quantum dot immobilisation, supporting covalent or electrostatic linkages that preserve accessibility and signal fidelity (Elsacker et al., 2021).

Fungal strains capable of biosynthesising quantum dots include Pleurotus, Coprinus, Agaricus, and Fusarium species. These organisms have been shown to produce CdS quantum dots with diameters of 3–7 nanometres, exhibiting broad UV–Vis absorption and stable luminescence (Jin et al., 2023). Their metabolic pathways enable the reduction of metal ions and nucleation of nanocrystals within the fungal biomass. While biosynthesis of more complex quantum dots such as neodymium-doped variants remains under investigation, hybrid strategies involving biosynthetic carbon quantum dots and post-growth doping may offer a viable route (Safari, 2022).

The QDot Patch thus represents more than a wearable sensor. It is a living interface between biology and nanotechnology—one that leverages fungal metabolism to produce functional nanomaterials within a breathable, biocompatible matrix. This biohybrid architecture offers a new paradigm for health monitoring: decentralised, non-invasive, and ecologically grounded. It sets the stage for a development roadmap that integrates cultivation, sterilisation, functionalisation, encapsulation, and electronic interfacing into a unified workflow.

Development Roadmap for the QDot Patch Biosensor

To realise the proposed mycelium-based quantum dot biosensor, development would proceed through a staged integration of biological substrates and nanoscale sensing components. This roadmap builds on the principle of in situ quantum dot generation within the fungal matrix, using mycelial metabolism to produce nanocrystals that are then functionalized and encapsulated for wearable deployment.

Phase 1: Mycelial Biosynthesis and Scaffold Formation

The process begins by cultivating quantum dot-producing fungal strains on nutrient-rich agricultural waste such as straw or sawdust. Four genera—Pleurotus, Coprinus, Agaricus, and Fusarium—have been identified for their ability to biosynthesise semiconductor quantum dots, particularly CdS and carbon-based variants, through intracellular pathways involving glutathione-mediated reduction and metal ion coordination.

  • Pleurotus ostreatus (oyster mushroom) and Agaricus bisporus (button mushroom) are edible fungi known for their biocompatibility and high protein content. They have demonstrated the ability to produce fluorescent carbon quantum dots suitable for live-cell imaging and biosensing applications (Sargin, et al. 2021).
  • Coprinus comatus (shaggy ink cap) exhibits strong oxidative stress responses and metal uptake, facilitating CdS quantum dot formation with tunable optical properties (Cardoso e Bufalo et al. (2024).
  • Fusarium oxysporum, a filamentous fungus, is widely studied for its metal-reducing capabilities and has been used to biosynthesize CdS and CdSe quantum dots with defined excitonic bands and size distributions (Cardoso e Bufalo et al. (2024).

These fungi produce a porous, protein-rich, biopolymeric matrix that supports stable quantum dot immobilization via covalent, electrostatic, or enzymatic anchoring. Their high surface area and fluid permeability enable efficient analyte diffusion for sweat, wound exudate, airborne VOCs, and aquatic contaminants. The scaffold’s breathability and biocompatibility make it suitable for skin-mounted applications, submerged deployment, and long-term wear in clinical, industrial, and environmental settings.

Phase 2: Sterilization and Stabilisation

Once biosynthesis is complete, the mycelial sheet is sterilised using autoclaving or chemical treatment and dried to preserve its mechanical integrity. This step ensures biocompatibility and safe skin contact while retaining the embedded quantum dots within the fibrous matrix.

Phase 3: Quantum Dot Functionalization

The biosynthesised quantum dots are then functionalized with biomolecular ligands such as antibodies, aptamers, or enzymes to confer specificity for target analytes. This is achieved through post-growth surface modification tailored to biomarkers like cortisol, IL-6, dopamine, heavy metals, and VOCs.

Quantum Dot Chemistry Selection

Quantum dots used in the biosensor include CdSe/ZnS, CdTe, InP, ZnS, black phosphorus, graphene, carbon-based, and neodymium-doped variants. Each type is selected based on its emission properties, environmental stability, and compatibility with the sensing context. For instance, cortisol detection typically uses CdSe/ZnS quantum dots emitting around 620 nanometres, while VOCs and uric acid are detected using carbon quantum dots with quenching near 460 nanometres.

Anchoring to the Mycelial Scaffold

The fibrous architecture of the mycelium provides a high-surface-area scaffold for quantum dot immobilization. Covalent or electrostatic linkages are engineered to ensure stability while maintaining accessibility to incoming biomarkers. While conventional stabilisation methods such as polymer coatings and core–shell architectures are well established, the potential for stabilising quantum dots within a mycelial matrix remains largely unexplored. Given mycelium’s porous structure and biopolymeric composition, it may offer a novel route for immobilising quantum dots in breathable, biocompatible substrates.

Phase 4: Encapsulation

To protect the sensor and maintain breathability, the mycelium is encapsulated with a thin waterproof membrane such as polyurethane. This layer allows sweat or exudate to diffuse inward while shielding the sensing zones from mechanical and environmental interference.

Phase 5: Electronics Integration

Miniature electronics are embedded into the patch, including an optical module with a calibrated light source and photodetector to excite and capture quantum dot fluorescence. A microcontroller processes the signal, applying noise filtering and biomarker quantification. Wireless transmission components such as Bluetooth or NFC enable real-time data transfer to external devices.

The result is a compact, flexible biosensor patch that combines biological adaptability with nanoscale precision, capable of continuous, non-invasive monitoring across clinical, environmental, and performance domains.

Sensor-by-Sensor Breakdown

The QDot Patch integrates biosynthesised quantum dots into a breathable fungal scaffold, enabling real-time, multiplexed detection of diverse biomarkers. Each sensing zone is tailored to a specific analyte class, offering distinct advantages over conventional methods.

1. Neurochemical Sensor

Target Analytes and Quantum Dot Composition

The QDot Patch can be designed to monitor key neurochemical biomarkers including cortisol, dopamine, serotonin, epinephrine, and oxytocin. These analytes play critical roles in stress response, mood regulation, and neuroendocrine signaling. To detect them non-invasively, the patch incorporates biosynthesised quantum dots made from CdSe/ZnS, carbon-based materials, and MoS₂, each selected for their tunable fluorescence and compatibility with biological sensing.

Conventional Detection Methods

In conventional diagnostics, cortisol is typically measured via blood, urine, or saliva using ELISA, HPLC, or fluorescence assays (Juliana et al., 2025). Dopamine and serotonin are monitored using microdialysis or voltammetry, primarily in research settings (Movassaghi et al., 2021). Oxytocin detection has advanced through aptamer-based electrochemical assays in saliva, offering high specificity without the need for antibodies (Rana et al., 2023). Epinephrine is measured using differential pulse voltammetry (DPV), chronoamperometry, and amperometric sensors with nanocluster-modified electrodes, which provide high sensitivity and selectivity (Baluta et al., 2022; Priya et al., 2023).

QDot Measurement Mechanism

The QDot Patch would replace these lab-based methods with a fluorescence-based sensing mechanism embedded directly into the mycelial matrix. Each sensing zone is tailored to a specific analyte using quantum dots functionalised with aptamers, antibodies, or enzymes. When a neurochemical binds to its ligand, it alters the quantum dot’s fluorescence intensity or emission wavelength.

Cortisol is typically detected using CdSe/ZnS quantum dots with peak emission around 620 nm (Safari, 2022). Dopamine and serotonin are monitored via carbon-based quantum dots that emit in the blue-green range, approximately 460 to 520 nm, with quenching or spectral shifts upon interaction (Movassaghi et al., 2021). Epinephrine detection involves MoS₂ and carbon quantum dots, which exhibit emission changes near 480 to 540 nm and benefit from chronoamperometric signal enhancement when paired with nanocluster-modified electrodes (Baluta et al., 2022; Priya et al., 2023). Oxytocin is measured using aptamer-functionalised carbon quantum dots tuned to emit near 500 nm, optimised for saliva-based assays (Rana et al., 2023).

2. Immune Sensor

Target Analytes and Quantum Dot Composition

The immune module of the QDot Patch would be engineered to detect key inflammatory biomarkers including interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and histamine. These analytes are central to immune response regulation and are often elevated during infection, autoimmune activity, or wound complications. To enable sensitive and selective detection, the patch incorporates biosynthesised quantum dots composed of CdTe, CdSe, and carbon-based materials, each chosen for their emission stability and compatibility with cytokine sensing.

Conventional Detection Methods

In clinical settings, IL-6 is typically measured using ELISA, chemiluminescent immunoassays, or optical biosensors (Majdinasab et al., 2023). TNF-α is monitored via ELISA, radioimmunoassay, or therapeutic drug monitoring platforms (NICE, 2019). Histamine detection is commonly performed using HPLC, ELISA, or surface-enhanced Raman spectroscopy (Huynh et al., 2020). These methods, while accurate, require blood sampling, laboratory infrastructure, and episodic testing.

QDot Measurement Mechanism

The QDot Patch can replace conventional immune assays with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Each sensing zone is functionalised with antibodies or aptamers specific to IL-6, TNF-α, or histamine. Upon binding, these interactions induce measurable changes in the quantum dot’s fluorescence intensity or emission wavelength.

IL-6 is detected using CdTe or CdSe quantum dots with peak emission around 600–640 nm, where binding events cause fluorescence quenching or red-shifted emission (Majdinasab et al., 2023). TNF-α is typically monitored using CdSe or carbon-based quantum dots emitting in the 580–620 nm range, with signal modulation upon cytokine interaction (NICE, 2019). Histamine detection relies on carbon quantum dots emitting near 500–540 nm, where surface charge alteration leads to fluorescence changes (Huynh et al. (2020).

3. Heavy Metal Sensor

Target Analytes and Quantum Dot Composition

The heavy metal module of the QDot Patch would be engineered to detect toxic metal ions including lead (Pb²⁺), mercury (Hg²⁺), and cadmium (Cd²⁺). These pollutants pose significant risks to neurological, renal, and cardiovascular health, especially in industrial and urban environments. To enable sensitive and selective detection, the patch incorporates biosynthesised quantum dots composed of black phosphorus and carbon-based materials, chosen for their high electron affinity, fluorescence stability, and compatibility with ion-binding ligands.

Conventional Detection Methods

Lead is typically measured using inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectroscopy (AAS), or blood-based HPLC assays (CDC, 2023; Thermo Fisher, 2020; Kelly et al., 2012). Mercury detection relies on similar techniques, including ICP-MS and cold vapor AAS, often requiring lab-based sample preparation (CDC, 2023; Thermo Fisher, 2020). Cadmium is monitored via ICP-MS and electrochemical sensors, with blood and urine as standard matrices (CDC, 2023; Lab Medicine, 2011). These methods, while precise, are invasive, infrastructure-dependent, and unsuitable for continuous exposure monitoring.

QDot Measurement Mechanism

The QDot Patch would replace conventional metal assays with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Quantum dots are functionalised with chelating ligands such as thiol or carboxyl groups that selectively bind heavy metal ions. Upon binding, these interactions induce measurable changes in fluorescence intensity or emission wavelength due to charge transfer or surface energy modulation.

Lead is detected using black phosphorus or carbon quantum dots with emission near 500–540 nm, where binding causes fluorescence quenching due to strong electron affinity (CDC, 2023; Thermo Fisher, 2020). Mercury is monitored via carbon quantum dots emitting around 460–520 nm, with quenching or red-shifted emission resulting from surface complexation (Kelly et al., 2012). Cadmium detection involves CdSe or carbon quantum dots emitting near 580–620 nm, with signal changes reflecting ion binding and altered surface polarity (Lab Medicine, 2011).

4. VOC Sensor

Target Analytes and Quantum Dot Composition

The VOC module of the QDot Patch would be designed to detect volatile organic compounds such as benzene, toluene, formaldehyde, and acetone. These airborne pollutants are commonly found in industrial emissions, household products, and urban environments, and are associated with respiratory irritation, neurotoxicity, and carcinogenic risk. To enable sensitive and selective detection, the patch incorporates biosynthesised quantum dots composed of carbon-based materials, graphene, and black phosphorus, chosen for their high surface reactivity, tuneable fluorescence, and compatibility with gas-phase sensing.

Conventional Detection Methods

VOC detection is typically performed using gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR), proton-transfer-reaction mass spectrometry (PTR-MS), and photoionisation detectors (Haick 2024; D’Arco et al., 2022; EANET, 2024). While these methods offer high sensitivity, they require bulky instrumentation, sample preparation, and controlled environments, making them unsuitable for wearable or real-time field deployment.

QDot Measurement Mechanism

The QDot Patch replaces conventional VOC assays with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Quantum dots are functionalised with surface groups such as hydroxyl, amine, or carboxyl moieties that interact with VOC molecules via hydrogen bonding, dipole interactions, or π–π stacking. These interactions alter the quantum dot’s fluorescence intensity or emission wavelength, enabling analyte-specific detection.

Benzene and toluene are detected using graphene or carbon quantum dots emitting in the 460–520 nm range, where adsorption alters surface polarity and quenches fluorescence (Haick, 2024). Formaldehyde and acetone interact with black phosphorus quantum dots, which exhibit emission shifts near 500–540 nm due to electron transfer and surface oxidation. The emission profile and quenching dynamics are tuned to distinguish between VOC classes based on molecular weight and polarity.

5. Radiation Sensor

Target Analytes and Quantum Dot Composition

The radiation module of the QDot Patch is engineered to detect ionising radiation, specifically gamma rays and X-rays. These high-energy photons pose cumulative risks to DNA integrity, immune function, and long-term cancer susceptibility. To enable wearable, real-time dosimetry, the patch incorporates biosynthesised quantum dots doped with neodymium (Nd³⁺) and embedded in carbon-based matrices. These quantum dots act as scintillators, converting ionising radiation into near-infrared (NIR) fluorescence with high sensitivity and spectral stability (Urdaneta et al., 2011; Safari, 2022).

Conventional Detection Methods

Ionising radiation is conventionally measured using Geiger-Müller counters, scintillation detectors, thermoluminescent dosimeters (TLDs), and film badges. These devices, while accurate, are bulky, require manual readout, and provide only cumulative exposure data. They are not designed for continuous, real-time monitoring in dynamic environments such as medical imaging suites, nuclear facilities, or emergency response zones (Urdaneta et al., 2011; Safari, 2022).

QDot Measurement Mechanism

The QDot Patch replaces conventional dosimetry with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Neodymium-doped carbon quantum dots act as scintillators, absorbing high-energy photons from gamma or X-ray exposure and re-emitting this energy as near-infrared fluorescence. This mechanism does not require external excitation; instead, the quantum dots are directly activated by ionising radiation. The resulting NIR emission, typically in the 880–1060 nm range, is proportional to the radiation dose and can be continuously monitored (Technion, 2024; Science Times, 2023).

Signal Capture and Data Transmission

The radiation module includes a photodetector tuned to the NIR emission range, capable of capturing low-intensity signals with high sensitivity. A microcontroller processes the signal using radiation-specific calibration curves, which account for dose rate, cumulative exposure, and background interference. Unlike the neurochemical and VOC modules, which prioritise analyte specificity, the radiation sensor is optimised for linearity and dose integration. Data is transmitted via Bluetooth or NFC to a paired device or dashboard, enabling real-time exposure tracking and threshold-based alerts.

6. Metabolic Sensor

Target Analytes and Quantum Dot Composition

The metabolic module of the QDot Patch is designed to monitor key biomarkers involved in hydration, energy metabolism, and electrolyte balance. These include glucose, lactate, pH, sodium, potassium, chloride, and uric acid. To enable sensitive and multiplexed detection, the patch incorporates biosynthesised quantum dots composed of CdSe, ZnS, and carbon-based materials. These nanocrystals are selected for their ratiometric fluorescence properties, enzymatic compatibility, and stability in sweat and wound exudate environments (Rashid et al., 2024; Kumar et al., 2023).

Conventional Detection Methods

Glucose is commonly measured using continuous glucose monitors (CGMs), enzymatic electrochemical sensors, and fluorescence-based assays (Rashid et al., 2024; RSC, 2024). Lactate detection relies on electrochemical patches and enzymatic biosensors, often used in sports and critical care (Ding et al., 2025; Springer, 2025). Electrolytes such as sodium, potassium, and chloride are monitored using ion-selective electrodes and wearable electrochemical platforms (OAEPublish, 2022). pH is measured using colorimetric sensors, potentiometric probes, and wearable electronics (Vo & Trinh, 2025). Uric acid detection is achieved via enzymatic assays and electrochemical biosensors (Kumar et al., 2023; MDPI, 2023). These methods, while effective, are often fragmented across devices and require invasive sampling or lab infrastructure.

QDot Measurement Mechanism

The QDot Patch replaces conventional metabolic assays with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Each sensing zone is functionalised with enzymes, ionophores, or aptamers tailored to the target analyte. Upon interaction, these biomolecular ligands induce changes in fluorescence intensity or emission wavelength due to enzymatic reactions, ion exchange, or surface charge modulation.

Glucose is detected using CdSe or carbon quantum dots with peak emission around 580–620 nm. Glucose oxidase functionalisation enables fluorescence quenching proportional to glucose concentration (Rashid et al., 2024). Lactate is monitored via carbon quantum dots emitting near 500–540 nm, with lactate oxidase triggering fluorescence changes through hydrogen peroxide generation (Ding et al., 2025). Electrolytes modulate fluorescence of carbon or ZnS quantum dots, with emission shifts in the 460–520 nm range depending on ion concentration (OAEPublish, 2022). pH-sensitive quantum dots exhibit emission shifts between 480–600 nm, enabling ratiometric sensing (Vo & Trinh, 2025). Uric acid is detected using uricase-functionalised carbon quantum dots with emission near 500 nm, modulated by enzymatic oxidation (Kumar et al., 2023).

7. Smart Bandage

Target Analytes and Quantum Dot Composition

The smart bandage module of the QDot Patch is designed to monitor key wound-related biomarkers including pro-inflammatory cytokines (e.g., IL-6, TNF-α), pH, uric acid, and temperature. These indicators are critical for assessing wound healing, infection risk, and inflammatory status. To enable sensitive, real-time detection, the patch incorporates biosynthesised quantum dots composed of CdSe/ZnS, carbon-based materials, and temperature-sensitive doped nanocrystals. These quantum dots are selected for their stability in moist environments, compatibility with biological ligands, and responsiveness to biochemical and thermal changes (Majdinasab et al., 2023; Kumar et al., 2023; Szunerits et al., 2025).

Conventional Detection Methods

IL-6 and TNF-α are typically measured using ELISA, chemiluminescent immunoassays, or flow cytometry in clinical laboratories (Majdinasab et al., 2023; NICE, 2019). pH is monitored using colorimetric dressings, potentiometric sensors, or handheld probes (Vo & Trinh, 2025). Uric acid is detected via enzymatic assays or electrochemical biosensors, often requiring blood or exudate sampling (Kumar et al., 2023). Temperature is tracked using infrared thermography, thermistors, or wearable thermal sensors (Szunerits et al., 2025). While effective, these methods are episodic, invasive, and not optimised for continuous wound surveillance.

QDot Measurement Mechanism

The QDot Patch replaces conventional wound diagnostics with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Each sensing zone is functionalised with antibodies, enzymes, or pH-sensitive ligands tailored to the target analyte. Upon interaction, these ligands induce changes in fluorescence intensity or emission wavelength, enabling real-time wound monitoring.

IL-6 is detected using CdTe or CdSe quantum dots with peak emission around 600–640 nm, where cytokine binding causes fluorescence quenching or red-shifted emission (Majdinasab et al., 2023). TNF-α is monitored using CdSe or carbon-based quantum dots emitting in the 580–620 nm range, with signal modulation upon cytokine interaction (NICE, 2019). pH is measured using carbon quantum dots that exhibit ratiometric fluorescence shifts between 480–600 nm, enabling precise tracking of wound acidity (Vo & Trinh, 2025). Uric acid is detected using uricase-functionalised carbon quantum dots with emission near 500 nm, modulated by enzymatic oxidation (Kumar et al., 2023). Temperature is tracked using doped CdSe/ZnS quantum dots that shift emission intensity or wavelength in response to local thermal changes, typically within the 500–650 nm range (Szunerits et al., 2025).

8. Water and Wastewater Biosensor

Target Analytes and Quantum Dot Composition

The aquatic module of the QDot Patch is engineered to detect a broad spectrum of waterborne pollutants including heavy metals (e.g., lead, mercury, cadmium), volatile organic compounds (VOCs), pesticides, pharmaceuticals, nitrates, phosphates, and microbial pathogens. These contaminants pose risks to ecological health, drinking water safety, and industrial compliance. To enable sensitive, multiplexed detection, the patch incorporates biosynthesised quantum dots composed of carbon-based materials, CdTe, CdSe, graphene, and black phosphorus. These nanocrystals are selected for their high surface reactivity, fluorescence stability in aqueous environments, and compatibility with ion and molecular binding (Castillo-Henríquez et al., 2020; Charbaji et al., 2021).

Conventional Detection Methods

Heavy metals such as lead, mercury, and cadmium are typically measured using ICP-MS, atomic absorption spectroscopy, and HPLC (CDC, 2023; Thermo Fisher, 2020; Kelly et al., 2012). VOCs are detected via gas chromatography (GC), FTIR spectroscopy, and PTR-MS (D’Arco et al., 2022; Haick, 2024). Pesticides and pharmaceuticals are monitored using GC-MS, LC-MS/MS, and electrochemical sensors (Dubey et al, 2024). Nitrates and phosphates are quantified using colorimetric assays, ion chromatography, and spectrophotometry (Charbaji et al. (2021). Pathogens are detected using PCR, flow cytometry, and biosensors targeting nucleic acids or surface proteins (Castillo-Henríquez et al., 2020). These methods, while accurate, require sample extraction, lab infrastructure, and episodic testing.

QDot Measurement Mechanism

The QDot Patch replaces conventional water quality assays with a fluorescence-based sensing system embedded directly into the mycelial scaffold. Quantum dots are functionalised with chelating ligands, aptamers, enzymes, or antibodies tailored to each pollutant class. Upon interaction, these ligands induce changes in fluorescence intensity or emission wavelength due to ion exchange, enzymatic reactions, or surface energy shifts.

Heavy metals are detected using carbon or black phosphorus quantum dots emitting near 500–540 nm, where ion binding causes fluorescence quenching or red-shifted emission (CDC, 2023; Thermo Fisher, 2020). VOCs such as benzene and toluene interact with graphene or carbon quantum dots emitting in the 460–520 nm range, with adsorption altering surface polarity and fluorescence output (Haick, 2024). Pesticides and pharmaceuticals are monitored via enzyme-functionalised quantum dots with emission near 580–620 nm, modulated by degradation products (Dubey et al. 2024). Nitrates and phosphates induce emission shifts in ion-sensitive quantum dots, typically between 480–540 nm (Charbaji et al., 2021). Pathogens are detected using DNA-conjugated or antibody-functionalised quantum dots emitting near 500–600 nm, with binding events altering fluorescence intensity (Castillo-Henríquez et al., 2020).

Signal Capture and Data Transmission

Each QDot Patch module integrates a miniature optical system designed to convert biochemical or physical interactions into quantifiable fluorescence signals. This system includes a calibrated light source—typically an LED or laser diode—tuned to the excitation wavelength of the embedded quantum dots (usually 350–450 nm). Upon excitation, the quantum dots emit fluorescence in analyte-specific spectral ranges, which are captured by a photodetector positioned within the patch architecture.

The photodetector relays raw optical data to an onboard microcontroller, which applies module-specific calibration curves to filter noise, correct for environmental drift, and translate fluorescence intensity or wavelength shifts into digital readings. These calibration profiles are tailored to the sensing context: for example, neurochemical and immune modules prioritise temporal resolution and threshold-based alerts, while metabolic and aquatic modules focus on dynamic range and trend analysis. The radiation module uniquely captures near-infrared (NIR) emissions triggered directly by ionising radiation, bypassing the need for external excitation.

Processed data is transmitted wirelessly via Bluetooth or NFC to a paired mobile device, dashboard, or cloud-based analytics platform. For aquatic and environmental deployments, LoRa or onboard data logging may be used to support remote access and low-power operation. This modular transmission framework enables continuous monitoring across diverse physiological and environmental domains, supporting both real-time feedback and longitudinal data aggregation.

The integration of optical sensing, embedded processing, and wireless communication within a breathable fungal scaffold ensures that QDot remains compact, responsive, and adaptable—whether worn on skin, embedded in a wound dressing, or deployed in aquatic environments.

Advantages of the QDot Modules

The QDot Patch offers a modular, biosynthetically integrated platform for continuous, non-invasive monitoring across physiological and environmental domains. Each sensor module—whether designed for neurochemical, immune, metabolic, radiation, heavy metal, VOC, smart bandage, or aquatic pollutant detection—shares a common architecture based on biosynthesised quantum dots and a breathable fungal scaffold. This unified design enables seamless deployment on skin, wounds, in air, or water, while supporting analyte-specific sensing strategies.

Shared platform advantages include:

  • Non-invasive sampling: All modules operate without blood draws, invasive probes, or lab processing—relying instead on sweat, wound exudate, ambient air, or water contact.
  • Multiplexed detection: Quantum dots with distinct emission profiles allow simultaneous monitoring of multiple biomarkers within a single patch.
  • Stable, tunable fluorescence: Biosynthesised quantum dots offer high photostability, ratiometric sensing, and compatibility with enzymatic, immunological, and electrostatic binding mechanisms.
  • Biocompatible fungal scaffold: The mycelial matrix enhances breathability, fluid or gas diffusion, and long-term wearability while supporting in situ nanocrystal formation.
  • Compact optical architecture: Integrated light sources, photodetectors, and microcontrollers enable real-time signal capture, calibration, and wireless transmission.
  • Decentralised diagnostics: Data can be streamed to mobile devices or dashboards, supporting remote care, field deployment, and proactive intervention.

Module-specific advantages include:

  • Neurochemical Sensor: Enables real-time tracking of stress, mood, and neuroendocrine function via sweat-based detection of cortisol, dopamine, serotonin, and related biomarkers.
  • Immune Sensor: Provides early warning of inflammation, infection, or autoimmune flare-ups through cytokine and histamine monitoring—ideal for chronic care and wound surveillance.
  • Metabolic Sensor: Tracks hydration, energy metabolism, and electrolyte balance during exercise, recovery, or clinical observation, offering a wearable alternative to fragmented lab tests.
  • Radiation Sensor: Offers compact, wearable dosimetry for gamma and X-ray exposure using neodymium-doped quantum dots with NIR emission—ideal for healthcare, aviation, and emergency response.
  • Heavy Metal Sensor: Detects toxic metals such as lead, mercury, and cadmium through sweat or wound exudate, supporting occupational safety and environmental health.
  • VOC Sensor: Monitors airborne pollutants like benzene, toluene, and formaldehyde in real time, bridging the gap between stationary air monitors and wearable exposure tracking.
  • Smart Bandage Sensor: Enables continuous wound monitoring without disrupting healing. Tracks cytokines, pH, uric acid, and temperature through a breathable fungal scaffold that supports moisture control and stable quantum dot immobilisation. Ideal for post-surgical care, diabetic ulcers, and remote wound management.
  • Water & Wastewater Sensor: Provides in situ detection of chemical and microbial contaminants in aquatic environments, supporting ecological monitoring and regulatory compliance.

Safety and Biocompatibility Considerations

The QDot Patch is designed to operate safely on human skin, including sensitive areas such as wound margins. Although the biosensor originates from fungal mycelium, the material undergoes full sterilisation and processing before deployment. Once cultivated and quantum dot biosynthesis is complete, the mycelial sheet is sterilised via autoclaving or chemical treatment, followed by drying and encapsulation. This process eliminates microbial contamination and ensures that the final substrate is inert, non-pathogenic, and suitable for prolonged skin contact (Elsacker et al., 2021; Haneef et al., 2017).

Importantly, the biosensor is not applied directly into open wounds. Instead, it is designed to monitor wound exudate through passive diffusion. A waterproof yet breathable membrane acts as a protective barrier, allowing molecular biomarkers to reach the sensing zones without exposing the wound to external materials. This layered architecture mirrors that of advanced wound dressings, combining sterility, moisture control, and diagnostic functionality (Vo & Trinh, 2024).

Preclinical studies have demonstrated low cytotoxicity and high biocompatibility of mycelium-based materials. No adverse reactions have been observed in in vitro or animal wound models, and the fibrous structure of mycelium supports moisture retention and gas exchange—key factors in skin safety and wound healing (Elsacker et al., 2021; Haneef et al., 2017; Ruggeri et al., 2023). While human trials have not yet been conducted, the material’s performance in preclinical settings suggests strong potential for safe integration into wearable and clinical workflows.

The embedded quantum dots, particularly those biosynthesised within the fungal matrix, offer additional safety advantages. Biosynthetic QDs are often capped with proteins or peptides that enhance biocompatibility and reduce cytotoxicity compared to synthetic variants. The porous structure of the mycelium allows for stable immobilisation of QDs while maintaining accessibility to biomarkers, reducing the risk of leaching or skin irritation (Jin et al., 2023; Safari, 2022).

As with any wearable device, placement protocols and usage duration must be tailored to minimise irritation and ensure safe operation. The breathable nature of the mycelium substrate, combined with its ability to conform to skin contours, supports extended wear without compromising comfort or hygiene (Heikenfeld et al., 2018).

Veterinary Adaptation: Equine Biosensing

The architecture and sensing modalities of the mycelium-based quantum dot biosensor are well-suited for veterinary applications, particularly in equine care. Horses, as high-value animals in sport, therapy, and agriculture, present a compelling case for continuous, non-invasive biomarker tracking.

Equine physiology and behaviour offer unique opportunities for biosensing. Horses produce substantial sweat during exertion, and wound exudate is readily accessible in clinical settings. The breathable, flexible nature of the mycelium substrate allows for comfortable integration into equine tack, leg wraps, or smart bandages, enabling real-time monitoring without impeding movement or causing irritation (Celeritas Digital, 2023).

Key biomarkers relevant to equine health include:

  • Neurochemicals such as cortisol and serotonin, which reflect stress, fatigue, and behavioural states during transport, training, or competition (Equestrian Space, 2024).
  • Inflammatory cytokines including IL-6 and TNF-α, which support early detection of laminitis, colic, and post-surgical complications (Salem, et al., 2015).
  • Metabolic markers such as lactate, glucose, and electrolytes, which inform hydration status, performance readiness, and recovery (Celeritas Digital, 2023).
  • Pathogen antigens for early screening of equine influenza, strangles, and herpesvirus (Equestrian Space, 2024).
  • Volatile organic compounds (VOCs) linked to stable air quality and respiratory health (Lee et al., 2024).

The biosensor’s modular design would allow sensing zones to be tailored for veterinary use, with quantum dots functionalised to bind equine-specific analytes. Data transmission via Bluetooth or NFC can be paired with stable-side dashboards or mobile apps, enabling veterinarians and trainers to track physiological trends, receive alerts, and adjust care protocols accordingly.

This adaptation supports both clinical and performance domains, offering a non-invasive, scalable solution for equine health monitoring. It aligns with broader goals in veterinary medicine: improving welfare, reducing diagnostic delays, and enhancing decision-making through continuous insight.

How It Works: From Patch to App

The biosensor patch operates through a layered sensing and communication process designed for continuous, non-invasive monitoring.

  • Fluid Diffusion: Sweat or wound exudate enters the patch through the breathable outer membrane and diffuses into the porous mycelium substrate. This layer acts as a sponge, guiding fluid toward the embedded sensing zones (Elsacker et al., 2021; Haneef et al., 2017).
  • Biochemical Interaction: Quantum dots within the sensing zones are functionalised to bind specific biomarkers. When a target molecule interacts with a quantum dot, it alters the dot’s fluorescence intensity or wavelength. These changes are tuned to occur at distinct spectral ranges depending on the analyte. For example, cortisol may trigger emission shifts around 620 nanometres, while lactate or pH changes affect emissions between 500 and 600 nanometres (Safari, 2022; Chen et al., 2025).
  • Optical Detection: A miniature optical module embedded in the patch captures these fluorescence changes. The module includes a photodetector and light source calibrated to excite the quantum dots and record their emission profiles (Vo & Trinh, 2024).
  • Signal Processing: The captured optical data is processed by an onboard microcontroller. Algorithms filter noise, apply calibration curves, and convert the fluorescence signals into digital biomarker readings (Vo & Trinh, 2024).
  • Wireless Transmission: The processed data is transmitted via Bluetooth or near-field communication (NFC) to a paired mobile device or clinical dashboard (Vo & Trinh, 2024).
  • User Interface: On the receiving device, users can view real-time dashboards showing biomarker levels, historical trends, and alerts. Interfaces may include colour-coded indicators, graphs, and personalised recommendations based on threshold values or pattern recognition (Vo & Trinh, 2024).

This integrated workflow allows the biosensor to operate continuously for 8 to 24 hours, providing actionable insights without the need for invasive sampling or bulky equipment.

Cost and Comparison

Compared to conventional commercial biosensors, the mycelium-based quantum dot platform offers several distinct advantages:

  • Lower production costs: Mycelium can be cultivated on low-cost agricultural waste with minimal energy input, significantly reducing material and manufacturing expenses (Haneef et al., 2017; Elsacker et al., 2021; Jones et al., 2017).
  • Reduced operational costs: Biosynthetic quantum dots and passive fluid sampling eliminate the need for expensive reagents or invasive consumables (Jin et al., 2023; Safari, 2022; Bandodkar et al., 2019).
  • Expanded sensing capabilities: Unlike most commercial devices that monitor one or two biomarkers, this platform supports simultaneous detection of multiple analytes including neurochemicals, metabolic markers, and environmental toxins (Vo & Trinh, 2024; Safari, 2022).
  • Improved comfort and compliance: The breathable, flexible structure of the mycelium substrate conforms naturally to the skin, reducing irritation and improving wearability over extended periods (Elsacker et al., 2021; Heikenfeld et al., 2018).
  • Environmental consideration: While not fully compostable due to the inclusion of electronics, the use of biodegradable structural materials helps reduce reliance on petroleum-based components and lowers the environmental footprint (Elsacker et al., 2021; Haneef et al., 2017).
  • Adaptability across domains: The modular sensing zones can be tailored for clinical, athletic, occupational, or environmental applications, offering broad utility beyond traditional health monitoring (Vo & Trinh, 2024).

This combination of affordability, versatility, and user comfort positions the biosensor as a compelling alternative to existing wearable technologies.

Clinical and Ethical Advantages

The mycelium-based quantum dot biosensor offers several advantages that extend beyond technical performance, addressing key concerns in clinical practice, patient comfort, and environmental responsibility.

  • Biocompatibility: The mycelium substrate is naturally breathable and inert, reducing the risk of skin irritation, allergic reactions, or microbial growth. Its fibrous structure allows for prolonged contact with the skin without compromising comfort or hygiene (Elsacker et al., 2021; Haneef et al., 2017).
  • Noninvasive sampling: By relying on sweat or wound exudate rather than blood or interstitial fluid, the sensor eliminates the need for needles, lancets, or implanted probes. This improves patient compliance, especially in paediatric, geriatric, or chronic care settings (Vo & Trinh, 2024; Heikenfeld et al., 2018).
  • Continuous monitoring: The patch is designed for 8 to 24 hours of uninterrupted use, enabling dynamic tracking of physiological changes rather than relying on isolated snapshots. This is particularly valuable for conditions with fluctuating biomarkers such as stress, inflammation, or glucose levels (Chen et al., 2025; Vo & Trinh, 2024).
  • Environmental responsibility: While the inclusion of electronics prevents full biodegradability, the use of mycelium and biosynthetic quantum dots reduces reliance on petroleum-based plastics and toxic reagents. This contributes to a lower environmental footprint compared to conventional wearables (Elsacker et al., 2021; Jin et al., 2023).
  • Alignment with global health goals: The platform supports decentralised diagnostics, remote monitoring, and personalised care, aligning with global health strategies that prioritise improved access, equity, and sustainability (Vo & Trinh, 2024).

These advantages make the biosensor well-suited for integration into clinical workflows, telemedicine platforms, and public health initiatives.

Challenges

While the mycelium-based quantum dot biosensor offers a promising alternative to conventional wearables, several challenges remain before it can be widely adopted.

  • Biomarker validation: Sweat-based sensing must be rigorously correlated with systemic biomarker levels. For neurochemicals and cytokines in particular, establishing reliable thresholds and clinical relevance is essential.
  • Quantum dot stability: Quantum dots must maintain consistent fluorescence under varying temperature, humidity, and mechanical stress. Long-term stability and photobleaching resistance are critical for continuous monitoring.
  • Manufacturing scalability: Cultivating mycelium and integrating quantum dots at scale requires standardised protocols and quality control.
  • Regulatory approval: The biosensor must meet international standards for safety, biocompatibility, and data integrity. This includes ISO 13485 certification and compliance with medical device regulations in multiple jurisdictions (Lee et al., 2017; Vo & Trinh, 2024).
  • Data integration: Seamless transmission of sensor data to mobile apps, clinical dashboards, and electronic health records requires robust interoperability and cybersecurity safeguards.

To address these challenges, the development roadmap includes:

  • Laboratory and clinical validation studies across diverse populations
  • Material optimisation for durability and reproducibility
  • Pilot deployments in healthcare, sports, and environmental monitoring
  • Engagement with regulatory bodies and standards organisations
  • Partnerships with researchers, clinicians, and investors to accelerate translation

This is a collaborative frontier. The biosensor’s success will depend not only on technical innovation but also on interdisciplinary support, drawing from materials science, bioengineering, clinical medicine, and public health.

Patent Landscape and Naming Viability

Based on current search results, no existing patent directly describes a wearable biosensor that integrates quantum dots into a mycelial matrix for real-time, multiplexed detection of biomarkers. However:

  • There are numerous patents on quantum dot biosensors in general, including for detecting neurochemicals, glucose, cancer markers, and environmental toxins.
  • Some patents describe hybrid systems involving quantum dots and nanomaterials like graphene, carbon nanotubes, or polymers — but none mention mycelium or fungal substrates.
  • The name QDot Patch also appears to be free of prior use or trademark conflict in biosensor or wearable contexts.

This strengthens the case for pursuing The QDot Patch as a novel and potentially patentable platform for biohybrid sensing.

Conclusion

This proposal outlines a novel direction in wearable health technology: a mycelium-based quantum dot biosensor designed to integrate biological adaptability with nanoscale precision. If realised, such a platform could monitor a broad spectrum of biomarkers—including stress, inflammation, metabolic activity, and environmental exposure—through a single, skin-mounted patch.

Unlike conventional devices, the envisioned biosensor would prioritise comfort, versatility, and continuous monitoring. Its layered architecture is designed to support real-time data collection without invasive procedures, while modular sensing zones could be tailored for clinical, athletic, or occupational applications.

As research progresses, this concept has the potential to reshape how we understand and respond to our physiological and environmental states. It points toward a future in which health monitoring evolves from reactive interventions to proactive insight, seamlessly integrated into everyday life.

This proposal brings together three well-established domains: quantum dot biosensors, mycelium-based biomaterials, and wearable sensor technologies. Quantum dots have been validated for detecting neurochemicals, pathogens, and pollutants; mycelium has demonstrated biocompatibility and structural versatility; and wearable electronics continue to advance in flexibility and wireless communication. Yet no published study has combined these elements into a unified system—embedding quantum dots directly into a mycelial matrix for real-time, multiplexed biosensing in a wearable patch.

References

Baluta et al. (2022).  Differential pulse voltammetry and chronoamperometry as analytical tools for epinephrine detection using a tyrosinase-based electrochemical biosensor. RSC Advances, Royal Society of Chemistry. https://pubs.rsc.org/en/content/articlelanding/2022/ra/d2ra04045j

Bandodkar, A. J., Jeerapan, I., & Wang, J. (2014). Epidermal tattoo potentiometric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring. ACS Applied Materials & Interfaces, 6(21), 21009–21017. https://pubmed.ncbi.nlm.nih.gov/24333582/

Bandodkar, A. J., Jeerapan, I., & Wang, J. (2019). Wearable chemical sensors: Emerging systems for on-body analytical chemistry. Analytical Chemistry, 91(1), 173-183. https://www.researchgate.net/publication/336662153_Wearable_Chemical_Sensors_Emerging_Systems_for_On-Body_Analytical_Chemistry

Cardoso e Bufalo, T. et al. (2024).  The Role of Fungi in the Green Synthesis of CdS Quantum Dots.  Educational and Scientific Digest, Issue 29, National University of Food Technologies (NUFT), Ukraine.  https://nuft.edu.ua/doi/doc/edsd/2024/29.pdf

Castillo-Henríquez et al. (2020).  Biosensors for the Detection of Bacterial and Viral Clinical Pathogens. MDPI Sensors. https://www.mdpi.com/1424-8220/20/23/6926

CDC (2023).  Blood Cadmium, Lead, Manganese, Mercury, and Selenium Levels in U.S. Populations. Centers for Disease Control and Prevention (CDC). https://stacks.cdc.gov/view/cdc/122193/cdc_122193_DS1.pdf

Celeritas Digital (2023). Wearable tech for equine stress and recovery. https://www.celeritasdigital.com/wearable-tech-for-equine-stress-and-recovery

Charbaji et al. (2021).  Colorimetric Determination of Nitrate after Reduction to Nitrite in a Paper-Based Dip Strip. Chem. Proc. 2021, 5(1), 9; https://doi.org/10.3390/CSAC2021-10459

Chen, Y., Zhang, L., & Wang, J. (2025). Wearable and implantable cortisol sensors: Advances in noninvasive stress monitoring. Advanced Materials, 36(1), 145. https://doi.org/10.1002/adma.202211595

D’Arco et al. (2022).  VOC Analysis in Water Using PTR-MS and GC-MS Techniques. Agilent Environmental Applications. https://www.agilent.com/en/solutions/environmental/water-testing/vocs-analysis-in-water

Ding et al. (2025).  A Comprehensive Review of Advanced Lactate Biosensor Materials, Methods, and Applications in Modern Healthcare. Sensors, 25(4), 1045; https://doi.org/10.3390/s25041045

Dubey et al. (2024).  Role of flexible sensors for the electrochemical detection of organophosphate-based chemical warfare agents. International Journal of Smart and Nano Materials, Volume 15, Issue 3. https://www.tandfonline.com/doi/pdf/10.1080/19475411.2024.2385350

EANET (2024).  General Introduction to VOCs Monitoring and Measurement Methods. Acid Deposition Monitoring Network in East Asia (EANET). https://www.eanet.asia/wp-content/uploads/2024/11/2.-VOCs_Monitoring_Introduction.pdf

Elsacker, E., Vandelook, S., Van Wylick, A., Ruytinx, J., Peeters, E., De Laet, L., & Vets, S. (2021). Current state and future prospects of pure mycelium materials. Fungal Biology and Biotechnology, 8, Article 1. https://doi.org/10.1186/s40694-021-00128-1

Gao, W., et al. (2016). Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature, 529(7587), 509-514. https://www.nature.com/articles/nature16521

Equestrian Space (2024). Wearable technology for horses: The next frontier in equine health monitoring. https://equestrianspace.com/wearable-technology-for-horses-the-next-frontier-in-equine-health-monitoring/

Haick, H. (2024).  Advances in Volatile Organic Compounds Detection: From Fundamental Research to Real-World Applications. Applied Physics Reviews, 11 (4). https://pubs.aip.org/aip/apr/article/11/4/040401/3320021

Haneef, M., Ceseracciu, L., Canale, C., et al. (2017). Advanced materials from fungal mycelium: Fabrication and applications. Scientific Reports, 7, 41292. https://www.nature.com/articles/srep41292

Heikenfeld, J., Jajack, A., Rogers, J., et al. (2018). Wearable sensors: Modalities, challenges, and prospects. Lab on a Chip, 18(2), 217–248. https://pubs.rsc.org/en/content/articlelanding/2018/lc/c7lc00914c

Huynh et al. (2020).  Facile Histamine Detection by Surface-Enhanced Raman Scattering Using SiO₂@Au@Ag Alloy Nanoparticles. Int. J. Mol. Sci. 2020, 21(11), 4048; https://doi.org/10.3390/ijms21114048

Jin, C., Zhang, Y., Li, Y., et al. (2023). Microbial biosynthesis of quantum dots: Regulation and application. and application. Inorganic Chemistry, 14. https://pubs.rsc.org/en/content/articlelanding/2023/qi/d3qi00688c

Jones, M., Huynh, T., Dekiwadia, C., Daver, F., & John, S. (2017). Mycelium composites: A review of engineering characteristics and growth kinetics. Journal of Bioresources and Bioproducts, 2(2), 15–26. https://www.scribd.com/document/389540095

Juliana et al. (2025).  Cortisol Detection Methods and the Hormone’s Role in Evaluating Circadian Rhythm Disruption. International Journal of Molecular Sciences, MDPI. https://www.mdpi.com/1422-0067/26/18/9141

Kelly et al. (2012).  Rapid Determination of Mercury in Contaminated Soil and Plant Samples Using Portable Mercury Direct Analyzer. Water, Air, & Soil Pollution, Springer. https://link.springer.com/article/10.1007/s11270-011-1030-3

Kumar et al. (2023).  Carbon Quantum Dots: Synthesis, Structure, Properties, and Catalytic Applications for Organic Synthesis. Catalysts, MDPI. https://www.mdpi.com/2073-4344/13/2/422

Lab Medicine (2011).  Spectral Interferences in the Analysis of Cadmium in Human Blood by ICP-MS. Journal of Analytical Atomic Spectrometry, RSC Publishing. https://pubs.rsc.org/en/content/articlelanding/2011/ja/c1ja10085h

Lee, H., et al. (2017). Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Science Advances, 3(3). https://doi.org/10.1126/sciadv.1601314

Lee, H., et al. (2024). Wearable volatile organic compound sensors for plant health monitoring. Advanced Sustainable Systems. First published 21 May 2024. https://doi.org/10.1002/adsu.202300634

Majdinasab et al. (2023).  Recent Progresses in Optical Biosensors for Interleukin 6 Detection. Biosensors, MDPI. https://www.mdpi.com/2079-6374/13/9/898

MDPI (2023).  Highly Sensitive Electrochemical Non-Enzymatic Uric Acid Sensor Based on Cobalt Oxide Puffy Balls-like Nanostructure. Biosensors, MDPI. https://www.mdpi.com/2079-6374/13/3/375

Movassaghi et al. (2021).  Simultaneous serotonin and dopamine monitoring across timescales by rapid pulse voltammetry with partial least squares regression. Analytical and Bioanalytical Chemistry, Springer. https://link.springer.com/article/10.1007/s00216-021-03665-1

NICE (2019).  Therapeutic monitoring of TNF-alpha inhibitors in rheumatoid arthritis. Diagnostics Guidance DG36, National Institute for Health and Care Excellence (NICE). https://www.nice.org.uk/guidance/dg36

OAEPublish (2022).  A Dual-Mode Wearable Sensor with Coupled Ion and Pressure Sensing. Soft Science. https://www.oaepublish.com/articles/ss.2023.41

Priya et al. (2023).  Development of an amperometric sensor for epinephrine determination using an Azure A/silver nanocluster modified electrode. Micro and Nano Systems Letters, SpringerOpen. https://mnsl-journal.springeropen.com/articles/10.1186/s40486-023-00174-x

Rana et al. (2023).  Highly Specific Detection of Oxytocin in Saliva. International Journal of Molecular Sciences, MDPI. https://www.mdpi.com/1422-0067/24/5/4832

Rashid et al. (2024).  Advances in Electrochemical Sensors for Real-Time Glucose Monitoring. Sensors & Diagnostics, RSC Publishing. https://pubs.rsc.org/en/content/articlehtml/2024/sd/d4sd00086b

RSC (2024).  The Performance of a Very Sensitive Glucose Sensor Developed with Copper Nanostructure-Supported Nitrogen-Doped Carbon Quantum Dots. RSC Advances. https://pubs.rsc.org/en/content/articlehtml/2024/ra/d4ra06566b

Ruggeri, M. et al. (2023). Mycelium-based biomaterials as smart devices for skin wound healing. Frontiers in Bioengineering and Biotechnology, 11, Article 1225722. https://www.frontiersin.org/articles/10.3389/fbioe.2023.1225722/full

Safari, M. (2022). Recent advances in quantum dots-based biosensors. IntechOpen. https://www.intechopen.com/chapters/84229

Salem S.E. et al (2015). Prevention of post operative complications following surgical treatment of equine colic: Current evidence. https://open.lib.umn.edu/app/uploads/sites/208/2019/12/Post-Operative-colic-complications.pdf

Sargin, I. et al. (2021).  Live Cell Imaging With Biocompatible Fluorescent Carbon Quantum Dots.  Journal of Fluorescence, 31, 2784–2793. Springer. https://link.springer.com/article/10.1007/s10895-021-02784-3

Science Times (2023).  Eco-Friendly Quantum Dot Photosensor for Wearable Health Monitoring. Science Times. https://www.sciencetimes.com/articles/47709/20231218/world-s-highest-performance-eco-friendly-quantum-dot-photosensor-demonstrates.htm

Szunerits et al. (2025).  Biosensors integrated within wearable devices for monitoring chronic wound status. APL Bioengineering, AIP Publishing. https://pubs.aip.org/aip/apb/article/9/1/010901/3333606

Technion Quantum Computing Studies (2024).  Next-generation scintillators based on quantum dots. https://phsites.technion.ac.il/quantum-computing-studies/next-generation-scintillators-based-on-quantum-dots/

Thermo Fisher Scientific (2020).  Metal Analysis Solutions for Trace Elemental Detection Using ICP-MS. Thermo Fisher Scientific. https://www.thermofisher.com/us/en/home/industrial/environmental/environmental-learning-center/contaminant-analysis-information/metal-analysis.html

Urdaneta et al. (2011).  Quantum Dot Composite Radiation Detectors. IntechOpen. DOI:10.5772/10598. https://www.intechopen.com/chapters/17231

Vo, D-K., & Trinh, K. T. L. (2024). Advances in wearable biosensors for healthcare: Current trends, applications, and future perspectives. Biosensors, 14(11), 560. https://www.mdpi.com/2079-6374/14/11/560

If you’re interested in discussing this concept, please get in touch

Share this page

Licence: All ideas and concepts shown on this website are shared under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0) . You are free to use, adapt, and build upon them, provided you give appropriate credit to Dr. Patrick Reynolds and include a link to this website.
© 2026 Patrick Reynolds