The research, funded by the charity Tour de Cure, was led by Professor Chamindie Punyadeera of Griffith’s Institute for Biomedicine and Glycomics and conducted by PhD student Waqar Ahmed Afridi, with clinical guidance from Adjunct Associate Professor David Fielding, a staff thoracic physician at the Royal Brisbane and Women’s Hospital, and collaboration with Dr David Paas of Queensland Health. The team set out to address one of the most common dilemmas in modern lung medicine: what to do about the indeterminate pulmonary nodule.

Lung cancer remains one of the world’s deadliest malignancies, with approximately 2.5 million new cases diagnosed each year. Low-dose computed tomography screening has improved early detection by picking up small nodules in the lungs, but the technology has an inherent limitation. It can reveal that a nodule exists, yet it cannot reliably tell whether that nodule is malignant. The result is a diagnostic gray zone in which patients and clinicians must decide whether to watch, biopsy, or operate.

The statistics behind that dilemma are striking. According to the research team, roughly 95 percent of pulmonary nodules identified on low-dose CT scans are ultimately found to be non-cancerous. Yet because the stakes of missing an early lung cancer are so high, many of those patients still undergo invasive procedures. A CT-guided lung biopsy may be performed to obtain tissue for diagnosis, a bronchoscopy may be used to sample suspicious nodules, and in some cases surgery is undertaken to remove or investigate lesions that may turn out to be harmless.

Those procedures are not trivial. Dr Xi Zhang, a co-author of the study, explained that biopsying lung nodules can be technically challenging, particularly when lesions are small or difficult to access. Complications can include pneumothorax, commonly known as a collapsed lung, which occurs when air leaks into the space between the lung and the chest wall. For a patient whose nodule was never cancerous in the first place, the risk-benefit calculus of such interventions is difficult to justify, which is precisely the problem the breath-based approach is designed to solve.

The Griffith study evaluated two complementary technologies operating on very different analytical principles. The first was an electronic nose, or eNose, a device fitted with arrays of chemical sensors that respond to the mixture of volatile compounds in exhaled air. Rather than identifying individual molecules one by one, the eNose captures the overall pattern of breath chemicals, generating a composite profile that machine-learning models can be trained to associate with particular disease states. In this study, those patterns were used to discriminate between breath samples from patients with malignant nodules and those with benign ones.

The second technology was gas chromatography-mass spectrometry, or GC-MS, a gold-standard analytical technique that separates the individual volatile organic compounds in a breath sample and identifies each one by its molecular mass and chemical behavior. Where the eNose reads the forest, GC-MS reads the trees, pinpointing specific compounds that may originate from cancer metabolism. Tumors are known to produce distinctive volatile metabolites, and identifying which of these compounds appear in the breath of patients with malignant nodules offers both diagnostic power and potential biological insight.

Professor Punyadeera reported that both breath-based approaches showed substantially better discrimination between malignant and benign nodules than models built on standard clinical information alone. In practical terms, this means that adding a breath profile to the data clinicians already collect, such as nodule size on CT and patient risk factors, improved the accuracy with which cancerous nodules could be separated from harmless ones. The complementary nature of the two technologies is central to the finding: the pattern-based eNose and the compound-specific GC-MS each contribute independent information, and together they form a more robust diagnostic picture than either could alone.

Importantly, the researchers are careful about what the breath test can and cannot do. Dr Zhang emphasized that while the simple breath test is showing promise in identifying which nodules are most likely to be malignant, it is not intended to replace biopsies. Instead, its role is triage: helping clinicians decide who needs invasive intervention most urgently. Patients whose breath profiles suggest a benign nodule could potentially be spared unnecessary procedures, while those whose profiles flag malignancy could be prioritized for definitive testing. The team hopes the non-invasive test could eventually be incorporated into routine clinical care, reducing the burden of unnecessary interventions for patients with benign nodules.

The implications extend beyond individual patients. A validated breath test is fast, repeatable, and essentially risk-free, making it well suited to monitoring nodules over time and to triaging the growing volume of findings generated by lung cancer screening programs worldwide. The paper, titled Complementary Breath Profiling Using eNose and Gas Chromatography-Mass Spectrometry for Noninvasive Triage of Indeterminate Pulmonary Nodules, was published in MedComm under DOI 10.1002/mco2.71012. As breath research moves from the laboratory toward the clinic, the air we exhale, once considered little more than waste, is emerging as a rich diagnostic medium, and this study offers a concrete step toward a future in which lung cancer triage could begin with nothing more than a breath.

Subject of Research: Breath-based profiling with eNose and GC-MS for non-invasive diagnosis of lung cancer nodules

Article Title: Can your breath help diagnose lung cancer?

Article References: Can your breath help diagnose lung cancer?. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: lung cancer, breath analysis, electronic nose, gas chromatography-mass spectrometry, pulmonary nodules, non-invasive diagnostics, volatile organic compounds, biopsy, low-dose CT, Griffith University, MedComm, early detection

The stakes are more than academic. VOCs such as ammonia, acetone, ethanol, and nitrogen dioxide are not only industrial pollutants linked to respiratory disorders, neurological damage, and cancer; several are also biomarkers that leak out of the body in exhaled breath. Ammonia in breath, for example, rises in chronic kidney disease, while acetone tracks lipid metabolism, and volatile sulfur compounds signal oral disease. Humidity, meanwhile, shapes health in its own right—high levels foster microbial growth and respiratory difficulty, low levels dry out airways, and both extremes affect indoor air quality, pharmaceutical stability, and the reliability of electronic products. A wearable that can read these variables continuously, comfortably, and cheaply would open the door to non-invasive diagnostics that today require clinic visits, blood draws, or bulky analytical instruments.

The physical platform matters as much as the chemistry. The review organizes wearable sensors by substrate: polymers such as polydimethylsiloxane (PDMS), polyethylene terephthalate (PET), polyimide (PI), and thermoplastic polyurethane (TPU), which are elastic, transparent, lightweight, and conform comfortably to skin thanks to their low glass transition temperatures; textiles, whose intrinsic roughness and porosity boost analyte adsorption and which can be functionalized by dip-coating, spray deposition, or screen printing; and paper, a biodegradable, porous, low-cost medium whose fast vapor diffusion makes it ideal for disposable point-of-care devices. Each choice involves trade-offs—polymers raise disposal concerns, textiles remain underexplored for VOC and humidity detection despite their comfort, and paper suffers from limited mechanical durability. Strikingly, most 2D-material sensors demonstrated so far still live on polymer or paper rather than fabric, a gap the authors flag as an emerging research frontier.

Underneath the variety of devices lies a common transduction principle. In chemiresistive sensors, the dominant architecture for wearables because of its simplicity and microwatt-to-milliwatt power draw, adsorbed VOC or water molecules donate or accept electrons depending on their molecular orbital energies relative to the Fermi level of the 2D material. Ammonia donates electrons to p-type graphene or WS2, reducing hole concentration and raising resistance; nitrogen dioxide withdraws electrons and lowers it. Surface chemistry fine-tunes this interaction: hydroxyl, carboxyl, and epoxy groups on graphene oxide act as preferential hydrogen-bonding sites for polar VOCs and water, while engineered defects and edge sites serve as high-energy binding locations that amplify sensitivity. In polyaniline (PANI) hybrids, a reversible protonation and deprotonation mechanism dominates—the insulating emeraldine base converts to conductive emeraldine salt—with the 2D material providing parallel conduction pathways that sharpen the response.

Heterostructures push performance further still. Stacking two 2D materials, such as WS2 on MoS2 or MXene on reduced graphene oxide, creates a built-in electric field at the junction; gas adsorption then modulates the width of the depletion region, magnifying the resistance change beyond what either material could deliver alone. Impedance-based readout offers an alternative to DC resistance, using AC complex impedance to decouple bulk and interfacial contributions and thereby resist humidity artifacts. These engineering levers—heterostructure formation, conductive polymer incorporation, defect engineering, and integration with metal-organic frameworks (MOFs)—form the review’s core toolkit for turning exotic nanomaterials into practical sensors.

The concrete devices are where the field’s momentum becomes vivid. For breath-based ammonia sensing, one team coated a graphene/PANI hybrid onto disposable polypropylene masks, achieving a 250 percent response at 50 ppm ammonia with a 100 parts-per-billion detection limit and—critically—a stable response across 20 to 100 percent relative humidity. Another group built an organic field-effect transistor sensor from oleylamine-functionalized graphene oxide blended with a DPP polymer and SEBS elastomer, reaching 67.01 percent per ppm sensitivity and a 9.19 ppb limit of detection while remaining stable up to 95 percent RH, because the hydrophobic oleylamine chains suppress water adsorption. A dual-signal sensor combining resistive and visual readouts tolerated 99 percent RH, and an rGO/polypyrrole composite fabric doubles as both an ammonia detector and a wearable Joule heater for responsive therapy.

MXenes and TMDs bring their own strengths. A termination-modified Ti3C2Tx MXene sensor on polyimide uses hydrocarbon surface groups to repel water while amplifying ethanol sensitivity for real-time breath alcohol monitoring, responding in 14 seconds and recovering in 37.5. A directionally freeze-cast, vertically aligned MXene/PEDOT:PSS aerogel provides a mechanically robust chemiresistive platform for wide-range breath analysis. A WS2/MoS2 heterostructure on conductive foam detected nitrogen dioxide at 0.01 ppm—51.5 percent response—while simultaneously monitoring occlusal force and maxillofacial movement for oral disease diagnosis. On the humidity side, an rGO/MoS2 composite achieved a 0.65-second response across 11 to 95 percent RH, the fastest among all sensors reviewed, and MXene/SWCNT and MXene/silk devices on laser-induced graphene delivered sub-two-second and even 0.1-second responses for respiration and touch-free sensing.

MOF composites add molecular selectivity to the mix. Although MOFs are not themselves 2D materials, pairing their porous, size-selective cages with graphene’s conductivity yields striking results: a nickel-MOF-on-graphene ethanol sensor detected 1 ppm with 1.03-second response times and survived 100,000 bending cycles, while a ZIF-8/laser-scribed graphene sensor exploited a molecular sieving effect plus machine learning to discriminate lung cancer biomarker VOCs with 96.5 percent accuracy at room temperature. Yet the review is candid about the field’s soft spots. Many VOC sensors were never tested under humid conditions or degrade badly when they are; response and recovery times are often unreported; MXenes drift more than graphene in humid air and risk oxidizing into potentially toxic byproducts; and explicit wireless transmission via Bluetooth or NFC remains experimentally rare, even as neural networks and machine learning accelerate data processing.

The authors’ roadmap for the next decade is correspondingly concrete. Selectivity, the stubborn weakness of broadly responsive 2D materials, should be attacked with selective surface receptors and electronic-nose sensor arrays coupled to pattern recognition. Energy harvesting via triboelectric or piezoelectric nanogenerators could yield self-powered wearables, while biocompatible encapsulation and dermal irritation studies must precede any real skin deployment. Scalable fabrication—inkjet printing, screen printing, roll-to-roll processing, and laser-induced graphene—will determine whether laboratory heroes reach the market, and the authors estimate current technology readiness at only TRL 3 to 4. Standardized testing protocols with defined humidity levels, analyte concentrations, flow rates, and deformation conditions, plus rigorous clinical validation in human cohorts, are urgently needed. If those pieces fall into place, the destination is clear: biodegradable substrates, self-healing electronics, AI-assisted data fusion, and multifunctional patches that turn the moisture and molecules we exhale every second into a continuous, personalized stream of medical and environmental intelligence.

Subject of Research: Wearable VOC and humidity sensors based on two-dimensional materials such as graphene, MXenes, and TMDs

Article Title: Recent advances in 2D-material-based wearable VOC and humidity sensors

Article References: Kashyap, A., Lahkar, R., & Kalita, H. (2026). Recent advances in 2D-material-based wearable VOC and humidity sensors. Frontiers in Sensors, 7, Article 1883762. https://doi.org/10.3389/fsens.2026.1883762

Image Credits: AI Generated

DOI: 10.3389/fsens.2026.1883762

Keywords: wearable sensors, 2D materials, graphene, MXene, transition metal dichalcogenides, volatile organic compounds, humidity sensing, breath analysis, flexible electronics, chemiresistive sensors, metal-organic frameworks, health monitoring

The research, conducted by Abdullah of the Department of Electronics Engineering at the Indian Institute of Technology Jodhpur, compares two straight micro gas chromatography columns that differ only in their cross-sectional geometry: one circular, one trapezoidal. Both columns were simulated in COMSOL Multiphysics under strictly identical operating conditions, with helium as the carrier gas and polyethylene glycol, or PEG, as the polar stationary phase suited to oxygen-containing compounds such as ketones and alcohols. Column lengths ranged from 10 to 100 centimeters, and hydraulic diameters spanned 50 to 600 micrometers. Performance was judged by the metrics chromatographers care about most: retention time, the number of theoretical plates, the height equivalent to a theoretical plate known as HETP, and the chromatographic resolution.

The numerical model itself was carefully grounded. The author solved the continuity and Navier-Stokes equations for the laminar, incompressible carrier-gas flow, with Reynolds numbers below 10, and coupled it to a transient convection-diffusion equation describing how acetone and ethanol molecules travel through the channel. Molecular diffusion coefficients were fixed at 2.5 x 10^-10 square meters per second for acetone and 2.0 x 10^-10 for ethanol, and the inlet injection was modeled as a Gaussian pulse at a concentration of 4.4 x 10^-5 moles per cubic meter. The crucial chromatographic interaction, the reversible partitioning of analytes between the flowing helium and the PEG-coated wall, was captured with a Robin boundary condition, using partition coefficients of 90 for acetone and 190 for ethanol, values held constant across every simulation so that geometry alone would determine the outcome.

Before any comparison was made, the model was validated against a previously published finite-element microGC simulation. The reproduced velocity field matched the published maximum velocity closely, 0.45 meters per second versus 0.48, and the outlet concentration profile for a hexane-benzene test mixture reproduced retention times of 21.40 and 28.89 seconds, within a few percent of the reference values. With roughly 1.2 million degrees of freedom per model, an ultrafine physics-controlled mesh with boundary-layer refinement, and mesh independence confirmed by outlet-concentration variations below 0.5 percent, the framework was judged accurate enough to capture the transport phenomena that govern separation in microchannels.

The hydrodynamic results followed classical microfluidic theory with striking clarity. In the circular channel with a fixed inner diameter of 250 micrometers, velocity stayed nearly constant at about 0.6 meters per second regardless of length, while pressure climbed from roughly 300 to nearly 500 pascals as the channel stretched from 20 to 100 centimeters, a 65 to 70 percent increase consistent with the Hagen-Poiseuille law. Diameter proved far more consequential than length: shrinking the circular channel from 600 micrometers down to 100 micrometers sent velocity soaring to about 9 meters per second and pressure drop up to roughly 80,000 pascals, changes of 95 to 97 percent, reflecting the inverse fourth-power dependence of pressure drop on diameter. The trapezoidal channel obeyed the same physics but with greater resistance; at a hydraulic diameter of 250 micrometers its velocity held near 0.4 meters per second while pressure rose almost eightfold, from about 500 to approximately 4,000 pascals, across the same length range.

When the two geometries were put head to head on the acetone-ethanol separation task, the differences became dramatic. The straight circular column delivered theoretical plate numbers between 0.5 and 3.9 thousand plates, HETP values of 0.027 to 0.035 centimeters, and resolutions below 1.25, all achieved at a modest pressure drop of 280 to 500 pascals and a brisk flow rate near 0.5 meters per second. The trapezoidal column, by contrast, reached up to 125,000 theoretical plates, cut HETP to between 0.010 and 0.015 centimeters, and pushed resolution as high as 1.90, comfortably above the threshold needed to distinguish two neighboring peaks. Retention times in the trapezoidal design stretched from 4.2 to as much as 39 seconds, compared with 3.0 to 8.2 seconds in the circular channel, reflecting the longer effective residence of analytes interacting with the wall.

The physical explanation lies in how each cross-section shapes the flow. Circular channels produce perfectly symmetric parabolic Poiseuille profiles, with velocity highest at the center and zero at the wall, which is efficient for transport but leaves analytes spending unequal times at different radial positions, promoting band broadening. Non-circular geometries disturb this symmetry, and the trapezoidal shape in particular offers a higher surface-to-volume ratio and a more favorable flow distribution, enhancing mass transfer between the mobile and stationary phases and reducing the spread of the analyte bands. The concentration profiles told the same story: in the trapezoidal channel, residence times increased by roughly 80 to 100 percent and peak concentrations dropped by about 60 to 70 percent relative to the circular case, evidence of stronger dispersion and diffusive mixing that ultimately sharpens the separation.

Length and diameter also mattered differently in the two designs. In the circular column, extending the channel from 10 to 100 centimeters raised acetone retention from 3.2 to 7.3 seconds and ethanol from 3.5 to 8.2 seconds, while plate numbers grew four- to five-fold, from 700 to 2,900 for acetone and 900 to 4,300 for ethanol. In the trapezoidal column, the same length increase multiplied retention times ten- to twelve-fold, with acetone rising from about 3 to 33 seconds and ethanol from roughly 4 to nearly 38 seconds, and plate numbers exploded by a factor of 40 to 50, from about 2,000 to 90,000 for acetone and 3,000 to 125,000 for ethanol. For both geometries, increasing the diameter from 50 micrometers produced an exponential rise in retention time and plate count up to around 300 micrometers, after which performance saturated, suggesting an optimum window for future designs.

The author emphasizes that none of these gains came from different operating conditions. Both models used the same hydraulic diameter, length, carrier-gas flow rate, stationary-phase film thickness, inlet concentration, Gaussian pulse injection, boundary conditions, and material properties, so the divergence in retention, plate number, HETP, and resolution is attributable purely to cross-sectional geometry. The price of the trapezoid’s superior performance is real but quantified: a pressure drop of roughly 3.8 x 10^3 pascals and a lower average carrier-gas velocity of about 0.35 meters per second, consequences of the modified cross-section at the same volumetric flow rate.

The implications reach well beyond acetone and ethanol. As breathomics advances toward early diagnosis of diabetes, lung and colorectal cancers, liver and neurodegenerative diseases, and infectious conditions, reviews in the field have repeatedly called for higher selectivity, standardized sampling, and proper separation of chemically similar compounds before detection. Miniaturized gas chromatography, with its microfabricated columns, small injectors, and mini-detectors, promises laboratory-grade separation in a portable package, and the rise of machine learning, electronic noses, and wearable sensors only increases the demand for high-resolution separation on a chip. The study points to the trapezoidal cross-section as a promising geometry for such devices, and the author’s stated next step is to fabricate an optimized trapezoidal column on a silicon wafer using MEMS technology, validate its chromatographic performance experimentally, and integrate it into a microGC system for rapid VOC detection in breath samples.

Subject of Research: Comparative simulation of circular and trapezoidal micro gas chromatography column geometries for acetone-ethanol separation in breath analysis

Article Title: Performance comparison of straight circular and trapezoidal µGC columns for acetone–ethanol separation

Article References: Abdullah (2026). Performance comparison of straight circular and trapezoidal µGC columns for acetone–ethanol separation. Frontiers in Sensors, 7, Article 1900358. https://doi.org/10.3389/fsens.2026.1900358

Image Credits: AI Generated

DOI: 10.3389/fsens.2026.1900358

Keywords: micro gas chromatography, breath analysis, volatile organic compounds, acetone, ethanol, trapezoidal microchannel, COMSOL simulation, theoretical plates, HETP, chromatographic resolution, MEMS, PEG stationary phase

In a study published in Holistic Integrative Oncology, investigators at Shanghai Pulmonary Hospital affiliated with Tongji University, working with collaborators at Jiangxi University of Chinese Medicine and Jilin University, enrolled 410 participants — 308 lung cancer patients and 102 healthy individuals — and analyzed the gases they exhaled using a technique called extractive electrospray ionization mass spectrometry, or EESI-MS. Their machine learning model, built on the molecular fingerprints of breath, distinguished cancer patients from healthy controls with accuracy exceeding 90 percent in both positive and negative ion modes. The work was registered as a clinical trial (NCT06086587) before data collection, lending additional rigor to the design.

The underlying biology is elegantly simple. Tumors are metabolic engines, and their altered chemistry releases volatile organic compounds, or VOCs, that diffuse from cancer cell membranes and surrounding tissue into the bloodstream. Once in the blood, these molecules travel to the lungs, cross the alveolar membrane, and are exhaled. Each breath therefore carries a chemical record of what is happening at the tissue level — a molecular signature that, in principle, can be read without a single needle, scalpel, or X-ray. Previous studies have shown that compounds such as pentane, hexane, heptane, and nonane are elevated in the breath of lung cancer patients, but small sample sizes and the absence of independent validation cohorts have kept breath analysis out of the clinic.

The Shanghai-led team addressed both problems. Participants were recruited between January and August 2024 and randomly allocated into three independent cohorts using computer-generated random numbers. Cohorts 1 and 2, which together contained 216 lung cancer patients and 74 healthy individuals, were used for metabolite screening, model training, and internal cross-validation. Cohort 3 — 92 cancer patients and 28 healthy controls — was held back as a completely independent testing set to evaluate how well the final model generalized to unseen data. Strict exclusion criteria filtered out anyone with a history of other malignancies, active lung infections, or prior anti-cancer treatment, while healthy volunteers had to show no respiratory symptoms and normal chest imaging.

Sample collection itself was re-engineered from the ground up. Conventional breath studies rely on collection bags such as Tedlar, which fail to concentrate trace compounds and can lose VOCs to condensation on their inner walls, or on thermal desorption tubes, which risk contamination and cross-infection because exhaled breath carries aerosol particles, proteins, nucleic acids, and even viruses. The team fabricated an in-house collector fitted with unidirectional valves and a 0.45-micrometer silver nanoparticle filter on both the blowing and exhausting ports, with an extraction liquid inside the bottle to enrich volatile compounds and an automatic virus inactivation function. Participants fasted for at least six hours, avoided spicy food, alcohol, and coffee the night before, and breathed normally through a latex mouthpiece for five minutes under tightly controlled temperature and humidity. Ambient air was sampled before and after each session and subtracted as background.

The analytical engine, EESI-MS, is where the technique departs sharply from established methods. Gas chromatography-mass spectrometry, the traditional workhorse of VOC analysis, demands complex pretreatment and often takes more than 30 minutes per sample. Commercial sensor arrays detect only single compounds and are notoriously destabilized by water vapor. In EESI, two sprayers converge in front of the mass spectrometer inlet: one delivers neutral sample, the other delivers charged reagent droplets. Through collision and liquid-liquid extraction, analyte molecules are extracted into the reagent and ionized within seconds, with no enrichment or pretreatment required. Crucially, the method captures both volatile and non-volatile compounds — a capability most breath technologies lack entirely. The instrument operated at a resolution of 70,000, scanning masses from 50 to 750 m/z in both positive and negative ion modes.

To distill meaning from the resulting spectral fingerprints, the researchers applied partial least squares discriminant analysis, cross-validated with permutation testing to guard against overfitting. The models separated patients from controls with exceptional fit — R-squared values of 0.998 or higher and Q-squared values above 0.987 in both ion modes across both screening cohorts. Intersecting the significant hits from Cohorts 1 and 2 yielded 17 characteristic compounds in positive ion mode and 11 in negative ion mode, 28 significantly differential metabolites in total, each identified against the Human Metabolome Database at Level 2 confidence. A support vector machine algorithm then built the final diagnostic model, which was tested on the untouched Cohort 3.

The results were remarkable. In positive ion mode, the 17-compound panel achieved an area under the ROC curve of 0.98, with 92.50 percent accuracy, 92.39 percent sensitivity, and 92.86 percent specificity. In negative ion mode, the 11-compound panel reached an AUC of 0.92, with 90.83 percent accuracy and an even higher sensitivity of 94.57 percent, though specificity dropped to 78.57 percent. Cross-validation in the training cohorts was even stronger: AUC values surpassed 0.97, accuracy exceeded 97 percent in positive ion mode, and specificity hit 100 percent in several configurations. Because smoking is the dominant risk factor for lung cancer and a potential confounder of breath chemistry, the team stratified participants by smoking status and found no significant difference in model performance between smokers and non-smokers — evidence that the biomarkers reflect the metabolic reprogramming of cancer cells themselves rather than residues of tobacco exposure.

Among the detected molecules were non-volatile compounds rarely explored in breath research, including adenylosuccinic acid, a key intermediate in purine metabolism whose dysregulation has been linked to tumor growth and drug-tolerant persister states in lung cancer, and lipids such as lysophosphatidylcholine, monoglyceride, and phosphatidic acid. Lysophosphatidylcholine can be converted by phospholipase D into lysophosphatidic acid, a potent proliferation-signaling molecule implicated in tumorigenesis, and plasma levels of LPC are known to be diminished in lung adenocarcinoma patients. Their appearance in exhaled breath opens a new window onto cancer metabolism that conventional VOC-only approaches cannot provide.

The authors are candid about the limitations. This was a single-center, exploratory study, and the control group consisted only of healthy individuals — the far harder clinical challenge of distinguishing lung cancer from benign pulmonary diseases such as COPD or pneumonia remains untested. Breath composition is also sensitive to diet, medications, and environmental exposures. Still, the team argues that the diagnostic threshold can be tuned to clinical purpose: a lower cutoff to maximize sensitivity for mass population screening, and a higher cutoff to maximize specificity in outpatient nodule clinics, reducing unnecessary invasive procedures. With high initial instrument costs offset by reagent-free, seconds-per-sample throughput in centralized hub laboratories, the researchers now plan a prospective, multi-center trial to validate the approach — and to determine whether a simple breath test can truly become the stethoscope of cancer’s earliest whispers.

Subject of Research: Non-invasive lung cancer detection through mass spectrometry-based analysis of exhaled breath biomarkers

Article Title: Mass spectrometry-based analysis of exhaled gases: a promising diagnostic tool for lung cancer detection

Article References: Zhao, W., Li, Y., Chen, X., Zhang, N., Liu, X., Zhao, L., Wang, H., Ye, L., Xu, K., Zhang, W., Chen, Z., Liu, Y., Zhang, Q., Liu, B., Chen, H., Su, R., & He, Y. (2026). Mass spectrometry-based analysis of exhaled gases: a promising diagnostic tool for lung cancer detection. Holistic Integrative Oncology, 5(1), Article 34. https://doi.org/10.1007/s44178-026-00247-y

Image Credits: AI Generated

DOI: 10.1007/s44178-026-00247-y

Keywords: lung cancer, breath analysis, mass spectrometry, EESI-MS, volatile organic compounds, early detection, machine learning, support vector machine, biomarkers, non-invasive diagnosis, metabolomics, clinical study

The biological premise behind the sensor is well established. Tumours rewire cellular metabolism, and the chemical fingerprints of that rewiring escape the body in exhaled breath as volatile organic compounds, or VOCs. Previous studies, including work cited by the team from breath research literature, have shown that patients with lung cancer exhale altered profiles of compounds such as isopropyl alcohol compared with healthy individuals. The clinical appeal is obvious: breath testing is non-invasive, painless and potentially cheap enough for repeated population-level screening. The technical challenge, however, is that these biomarkers circulate at parts-per-million concentrations and below, demanding sensors that combine extreme sensitivity with the ability to operate without heating the sensing material to hundreds of degrees Celsius, as many conventional metal oxide sensors require.

The Indian team’s answer to that challenge begins with the sensing material itself. Graphene quantum dots, or GQDs, are nanoscale fragments of graphene, typically only a few nanometres across, that retain much of graphene’s exceptional electrical conductivity while gaining new properties from their tiny size and abundant edge sites. The researchers synthesised their GQDs using a pyrolysis-reduction method, a process that involves heating a carbon precursor to break it down into small graphitic domains and then chemically reducing the resulting material. This route is attractive because it is relatively simple and scalable compared with more exotic synthesis techniques, and it produces dots decorated with oxygen-containing functional groups on their surfaces, which turn out to be the secret ingredient for gas sensing.

Before any sensing could happen, the team had to confirm exactly what they had made, and they did so with a standard battery of characterisation techniques. Ultraviolet-visible spectroscopy revealed the optical absorption signature of the quantum dots, while photoluminescence measurements confirmed the characteristic blue fluorescence that GQDs are known for, a property tied to their quantum confinement and surface states. Transmission electron microscopy provided the most direct evidence, imaging the dots directly and confirming their nanometre-scale dimensions. These measurements matter because the sensing performance of GQDs depends critically on their size, their degree of carbonisation and the density of functional groups on their surface, so knowing the material’s structure is essential to understanding why it behaves the way it does when gas molecules land on it.

The sensor architecture is equally considered. The researchers fabricated an interdigitated electrode array, the comb-like metallic structure onto which the GQDs are deposited and across which electrical resistance is measured, using ultraviolet lithography with a dry film photoresist, or DFR. This is a notable choice. Traditional photolithography relies on liquid photoresists and cleanroom processes that are expensive and generate significant chemical waste. Dry film photoresist, by contrast, comes as a solid laminate that is applied, exposed and developed with far less fuss, and it has gained popularity in microfluidics and sensor prototyping precisely because it enables rapid, environmentally friendlier fabrication without sacrificing patterning precision. For a technology whose ultimate ambition is cheap point-of-care diagnostics, keeping the manufacturing simple and low-cost is not a cosmetic detail; it is central to the design philosophy.

The sensing mechanism itself is a story of electrons and adsorbed molecules. In a chemiresistive sensor, the quantity being measured is simply the electrical resistance of the sensing film. When oxygen molecules from ambient air adsorb onto the surface of the GQDs, they capture electrons from the material, forming a surface layer of adsorbed oxygen species and modulating the conductivity of the film. When a target VOC such as isopropyl alcohol arrives, it reacts with these adsorbed oxygen species, releasing captured electrons back into the carbon network and shifting the resistance in a measurable way. Because GQDs present an enormous surface-area-to-volume ratio, with functionalised edges offering abundant adsorption sites, even a small number of gas molecules produces a detectable electrical change. The oxygen functional groups identified in prior theoretical and experimental work on GQD sensing are understood to play a decisive role in this response, acting as the primary reaction sites for incoming analyte molecules.

The headline result is the sensor’s response to isopropyl alcohol. At a concentration of just 0.8 parts per million, the device produced a response of 29.6 percent at room temperature, a figure the authors describe as exceptional sensitivity. To put that in context, many commercial and laboratory gas sensors require operating temperatures of 150 to 400 degrees Celsius to achieve comparable responses, which means continuous power consumption from an integrated heater. A sensor that works at ambient temperature can run on a battery, which is precisely what a wearable or handheld breath analyser would need. The team also evaluated the sensor against three lung cancer-related VOCs at various ppm concentrations, probing the device’s dynamic range and its limits, and found that the GQD film maintained useful sensitivity across the concentration range relevant to breath analysis.

The researchers frame the work explicitly as an evaluation of sensing limits rather than a demonstration of a finished diagnostic, and that framing is scientifically honest in ways that matter. Real breath contains a complex cocktail of water vapour, carbon dioxide and dozens of interfering VOCs, and any sensor destined for clinical use must discriminate its targets from that background. The study’s systematic testing across multiple compounds and concentrations is a step toward mapping that selectivity landscape, and the strong response to IPA suggests the GQD surface has genuine chemical affinity for alcohol-type molecules. Still, the path from a characterised sensor in a laboratory gas-testing setup to a validated clinical screening tool runs through humid breath samples, patient cohorts and comparison against gold-standard techniques such as gas chromatography-mass spectrometry, which remains the reference method for breath VOC analysis.

Even so, the broader significance of the study is hard to overstate. Lung cancer remains one of the deadliest malignancies worldwide, with global burden estimates projecting continued rises in incidence and mortality through mid-century, and the great majority of cases are detected only after the disease has advanced beyond curable stages. Low-dose CT screening exists but is expensive, resource-intensive and targeted at high-risk populations. A cheap, room-temperature, breath-based sensor would not need to replace CT; it would sit upstream as a triage tool, flagging individuals whose breath chemistry warrants imaging. The authors argue that the combination of precise DFR patterning and the high surface area of their GQDs provides a scalable and cost-effective approach that effectively bridges nanotechnology and point-of-care medical diagnostics, and the numbers they report lend that claim real weight.

What happens next will determine whether graphene quantum dots make the leap from promising laboratory material to the sensing layer in a device that doctors actually use. The immediate research agenda implied by this work includes optimising the functional group chemistry for selectivity, testing long-term stability and drift, and integrating the sensor into arrays that can read patterns of multiple VOCs simultaneously, the approach known as electronic nose sensing. The funding for this study came from India’s RUSA 2.0 programme, with instrumentation support from the G.N. Ramachandran centre at the University of Madras, a reminder that significant sensor research is flourishing well beyond the traditional hubs of Silicon Valley and Western Europe. If the sensing limits mapped here hold up under the harsher conditions of real human breath, the humble graphene quantum dot, a speck of carbon a few nanometres wide, may end up playing an outsized role in catching one of the world’s deadliest cancers while it is still treatable.

Subject of Research: Graphene quantum dot chemiresistive sensors for detecting lung cancer biomarker volatile organic compounds in exhaled breath

Article Title: Evaluating the sensing limits of GQD-based chemiresistive sensor for lung cancer VOC detection

Article References: Ishwariya, P. S. A., Shylaja, R., Kamalarasan, V., Nedumaran, D., & Venkateswaran, C. (2026). Evaluating the sensing limits of GQD-based chemiresistive sensor for lung cancer VOC detection. Journal of Nanoparticle Research, 28(10), Article 255. https://doi.org/10.1007/s11051-026-06758-z

Image Credits: AI Generated

DOI: 10.1007/s11051-026-06758-z

Keywords: graphene quantum dots, chemiresistive gas sensor, lung cancer, volatile organic compounds, breath analysis, isopropyl alcohol, interdigitated electrodes, dry film photoresist, nanosensors, point-of-care diagnostics, room-temperature sensing, pyrolysis-reduction synthesis

The technical foundation of the dispute lies in two biomarkers. Ethylene is a simple gaseous molecule that humans both produce internally and inhale from the environment, including from combustion sources and ripening fruit. Inside the body, a fraction of inhaled ethylene is converted by cytochrome P450 enzymes into ethylene oxide, a more reactive epoxide that can bind to hemoglobin and DNA. The specific biomarker used to track this chemistry is N-(2-hydroxyethyl)valine, abbreviated HEV, an adduct formed when ethylene oxide reacts with the N-terminal valine residue of hemoglobin proteins. Because red blood cells circulate for roughly four months, HEV provides an integrated record of ethylene oxide exposure over time. Lin and colleagues compiled a database of breath ethylene measurements and, using physiologically based pharmacokinetic modeling, sought to estimate how much endogenous ethylene oxide production contributes to total HEV burdens in the general population.

What Kirman and Bus highlight in their correspondence is a fundamental analytical problem embedded in that database. Breath ethylene concentrations reported across the literature are extraordinarily variable, and the variability appears to track with the measurement technology rather than with genuine differences between study populations. Studies employing laser-based photoacoustic spectrometry, a technique that detects gas absorption of laser light, reported mean ethylene concentrations of roughly 61 parts per billion with a standard deviation of 130 ppb, an enormous spread. By contrast, studies relying on gas chromatography reported a mean of approximately 20 ppb with a standard deviation of 16 ppb, far tighter and consistently lower. Even within the subset of studies that Lin and colleagues designated as high confidence, mean ethylene levels hovered around just 0.5 ppb, orders of magnitude below the values coming from the laser-based literature.

This is not a new concern, and Kirman and Bus invoke a striking historical precedent. More than two decades ago, Berkelmans and colleagues, working with online laser photoacoustic detection, observed that endogenous ethylene production rates derived from laser-based studies were significantly lower than published values based on gas chromatography, an inconsistency they attributed to fundamental differences between the two analytical approaches. When Berkelmans’s team attempted to fit a physiologically based pharmacokinetic model to their laser-derived data, they found they had to modify measured physiological and biochemical parameters to make the model work, indicating that the laser measurements were inconsistent with the well-established understanding of ethylene toxicokinetics built on gas chromatography. Kirman and Bus argue that this methodological fault line has not been resolved, and that Lin and colleagues’ database largely inherits the problem rather than correcting it.

The PBPK modeling itself is the second pillar of the critique. Physiologically based pharmacokinetic models are mathematical descriptions of how a chemical moves through the body, incorporating blood flow, tissue partitioning, metabolic rates, and ventilation. The model used by Lin and colleagues traces back to the foundational work of Filser and Klein, who developed a toxicokinetic model for inhaled ethylene and ethylene oxide across mouse, rat, and human species, and to earlier work by Csanády and colleagues, who modeled the formation of 2-hydroxyethyl adducts with hemoglobin and DNA from both exogenous and endogenous sources. Running the model with the breath ethylene data, Lin’s team concluded that endogenous production pathways account for less than 20 percent of total HEV in nonsmokers, leaving more than 80 percent unexplained. Kirman and Bus point out that this large unexplained fraction is itself a signal that something in the exposure reconstruction may be missing, whether it be analytical bias in breath measurements, unrecognized internal sources, or contributions from pathways not captured by the model.

Exogenous exposure, meaning ethylene and ethylene oxide inhaled from outside sources such as ambient and indoor air, is the other candidate explanation for the unaccounted adduct burden. Here, Kirman and Bus note that available air monitoring data, including large-scale studies such as Health Canada’s Windsor Exposure Assessment Study, indicate that environmental contributions to total ethylene oxide body burden are expected to be small for the general population. This conclusion aligns with their own prior publications, including a 2021 comprehensive review characterizing total ethylene oxide exposure from endogenous and exogenous pathways and a 2025 assessment of background exposures in the United States that questioned theoretical health risks for populations living near industrial sources. The implication is that the apparent gap between modeled endogenous production and measured HEV cannot simply be closed by invoking ambient air pollution, contrary to some popular narratives about ethylene oxide risk.

The broader context makes this technical disagreement consequential beyond the laboratory. Ethylene oxide is used industrially to sterilize roughly half of all medical devices in the United States, and the Environmental Protection Agency’s recent regulatory actions targeting sterilization facilities have relied on risk estimates derived from inhalation unit risk values. If a substantial fraction of the population’s hemoglobin adduct burden derives from endogenous biology rather than industrial emissions, then the margin between background internal exposure and levels associated with elevated cancer risk is narrower than many assume, and any risk assessment that fails to account for endogenous background risks mischaracterizing the true incremental danger of industrial emissions. Kirman and Bus have argued elsewhere that recognizing endogenous ethylene oxide formation is essential for a coherent risk management framework, since regulatory limits that ignore the body’s own production of the chemical cannot meaningfully protect public health in proportion to actual incremental exposure.

They also point to emerging molecular dosimetry work that helps interpret HEV data. Recent studies by Liu and colleagues on hemoglobin adduct formation in mice exposed to ethylene oxide, and Lin’s own companion work integrating PBPK modeling with tobacco biomarkers to interpret HEV levels in the U.S. population, demonstrate that smoking contributes substantially to measured adduct burdens, since tobacco smoke contains both ethylene and ethylene oxide directly. In nonsmokers, however, the origin of the remaining adduct burden remains contested. Classical biomonitoring studies from the 1990s and 2000s, including molecular dosimetry work by Walker, Fennell, Upton, and Swenberg in rodents exposed to ethylene oxide, established the dose-response framework that still underpins modern interpretation, and those studies consistently emphasized the importance of distinguishing background from incremental exposure when translating adduct measurements into cancer risk.

Neither the correspondence nor the original analysis settles the question of how much endogenous metabolism contributes to human ethylene oxide body burdens, but the exchange underscores a lesson that resonates across exposure science: the quality of a risk assessment is bounded by the quality of the exposure data fed into it. When two analytical technologies applied to the same biological matrix differ by more than an order of magnitude, as laser-based photoacoustic spectrometry and gas chromatography evidently do for breath ethylene, downstream models, no matter how sophisticated, inherit that uncertainty. Kirman and Bus contend that progress requires reconciling the methodological discrepancy, validating breath ethylene measurements against gas-chromatographic benchmarks, and ensuring that PBPK models are fit to data consistent with established toxicokinetics. Until that reconciliation occurs, estimates of how much ethylene oxide in the average person’s blood comes from industry versus biology will remain contested, and the regulatory debate over one of the world’s most widely used sterilants will continue to be fought on contested ground.

Subject of Research: Human exposure to ethylene and endogenous ethylene oxide assessed through breath biomarkers and pharmacokinetic modeling

Article Title: Regarding ethylene exposure and endogenous ethylene oxide levels in humans (Lin et al., 2025)

Article References: Kirman, C. R., & Bus, J. S. (2026). Regarding ethylene exposure and endogenous ethylene oxide levels in humans (Lin et al., 2025). Journal of Exposure Science & Environmental Epidemiology. https://doi.org/10.1038/s41370-026-00967-3

Image Credits: AI Generated

DOI: 10.1038/s41370-026-00967-3

Keywords: ethylene, ethylene oxide, hemoglobin adducts, PBPK modeling, breath analysis, biomonitoring, exposure science, risk assessment, photoacoustic spectrometry, gas chromatography, environmental epidemiology, Regarding