Clinically Diagnose Asthma and Monitor Its Severity Using an Ultrasensitive Chemiresistive Nitric Oxide (NO) Gas Sensor via Exhaled Breath Analysis Assisted by Pattern Recognition DOI

Peisi Yin,

Xiaoyu You, Xinyue Cui

и другие.

ACS Sensors, Год журнала: 2025, Номер unknown

Опубликована: Июнь 5, 2025

Fractional exhaled nitric oxide (FeNO) is widely recognized as a reliable biomarker for asthma. FeNO sensors can help diagnose asthma and monitor its severity. In this study, an ultrasensitive chemiresistive gas sensor, sensitive to the key breath biomarkers of asthma─nitric (NO) H2S─was fabricated using Ag-decorated ZnO. The sensor exhibits detection limits 5 ppb NO 50 H2S, it discriminate 10 60 H2S from breaths. Clinically, total 80 samples were collected tested, including 40 patients (APs) healthy control subjects (HCs). AP group was effectively distinguished HC pattern recognition algorithm (PCA), attributed sensor's beneficial cross-sensitivity biomarkers. A diagnostic model distinguishing non-asthma constructed support vector machine (SVM) algorithm, achieving overall accuracy, sensitivity, specificity 0.81, 0.88, 0.75, respectively. area under curve (AUC) value all in receiver operating characteristic (ROC) 0.92. severity three inpatients monitored clinical evaluation method diurnal peak expiratory flow (PEF) variation, alongside our sensor. response values exhibited strong correlation (r = -0.74 (p < 0.05)) with PEF variation values. To validate capability, six both HCs APs tested simultaneously commercial electrochemical utilized clinically. With r -0.98 0.05) R2 0.94, linear relationship between two types observed, confirming accuracy reliability detecting concentrations breath. Theoretical adsorption models on surface DFT calculations elucidate mechanisms driving ultrasensitivity. Overall, demonstrates significant potential use practice

Язык: Английский

ZnO nanowire-decorated 3D printed pyrolytic carbon for solar light–driven photocatalytic degradation of wastewater contaminants DOI
Gulshan Verma, Monsur Islam, Ankur Gupta

и другие.

Advanced Composites and Hybrid Materials, Год журнала: 2025, Номер 8(1)

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

3

Next‐Generation Chemiresistive Wearable Breath Sensors for Non‐Invasive Healthcare Monitoring: Advances in Composite and Hybrid Materials DOI Open Access
Gulshan Verma, Ankur Gupta

Small, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

Abstract Recently wearable breath sensors have received significant attention in personalized healthcare systems by offering new methods for remote, non‐invasive, and continuous monitoring of various health indicators from samples without disrupting daily routines. The rising demand rapid, diagnostics has sparked concerns over electronic waste short‐lived silicon‐based devices. To address this issue, the development flexible sensing applications is a promising approach. Research highlights different flexible, operating with principles, such as chemiresistive to detect specific target analytes due their simple design, high sensitivity, selectivity, reliability. Further, focusing on non‐invasive detection biomarkers through exhaled breath, offer comprehensive environmentally friendly solution. This article presents discussion recent advancement biomarkers. further emphasizes intricate functioning sensor, including selection criteria both substrate advanced functional materials, mechanisms. review then explores potential gas disease detection, modern challenges associated sensors.

Язык: Английский

Процитировано

2

Room Temperature Operated Flexible MWCNTs/Nb2O5 Hybrid Breath Sensor for the Non-Invasive Detection of Exhaled Diabetes Biomarker DOI
Gulshan Verma, Sonu Sarraf, Aviru Kumar Basu

и другие.

Journal of Materials Chemistry B, Год журнала: 2025, Номер 13(10), С. 3460 - 3470

Опубликована: Янв. 1, 2025

Flexible gas/breath sensors have emerged as a transformative solution in personalized healthcare, offering innovative approaches for remote, non-invasive, and continuous monitoring of health indicators from breath samples.

Язык: Английский

Процитировано

0

Vanadium Doping as a Key Factor for Superior NH3 Sensing at room temperature in MoSe2/TiO2 Composites DOI
Veena Choudhary,

Sunil Gangwar,

C. S. Yadav

и другие.

Sensors and Actuators A Physical, Год журнала: 2025, Номер unknown, С. 116501 - 116501

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Clinically Diagnose Asthma and Monitor Its Severity Using an Ultrasensitive Chemiresistive Nitric Oxide (NO) Gas Sensor via Exhaled Breath Analysis Assisted by Pattern Recognition DOI

Peisi Yin,

Xiaoyu You, Xinyue Cui

и другие.

ACS Sensors, Год журнала: 2025, Номер unknown

Опубликована: Июнь 5, 2025

Fractional exhaled nitric oxide (FeNO) is widely recognized as a reliable biomarker for asthma. FeNO sensors can help diagnose asthma and monitor its severity. In this study, an ultrasensitive chemiresistive gas sensor, sensitive to the key breath biomarkers of asthma─nitric (NO) H2S─was fabricated using Ag-decorated ZnO. The sensor exhibits detection limits 5 ppb NO 50 H2S, it discriminate 10 60 H2S from breaths. Clinically, total 80 samples were collected tested, including 40 patients (APs) healthy control subjects (HCs). AP group was effectively distinguished HC pattern recognition algorithm (PCA), attributed sensor's beneficial cross-sensitivity biomarkers. A diagnostic model distinguishing non-asthma constructed support vector machine (SVM) algorithm, achieving overall accuracy, sensitivity, specificity 0.81, 0.88, 0.75, respectively. area under curve (AUC) value all in receiver operating characteristic (ROC) 0.92. severity three inpatients monitored clinical evaluation method diurnal peak expiratory flow (PEF) variation, alongside our sensor. response values exhibited strong correlation (r = -0.74 (p < 0.05)) with PEF variation values. To validate capability, six both HCs APs tested simultaneously commercial electrochemical utilized clinically. With r -0.98 0.05) R2 0.94, linear relationship between two types observed, confirming accuracy reliability detecting concentrations breath. Theoretical adsorption models on surface DFT calculations elucidate mechanisms driving ultrasensitivity. Overall, demonstrates significant potential use practice

Язык: Английский

Процитировано

0