A Prototype of Graphene E-Nose for Exhaled Breath Detection and Label-Free Diagnosis of Helicobacter Pylori Infection.

Helicobacter pylori (HP), a common microanaerobic bacteria that lives in the human mouth and stomach, is reported to infect ≈50% of the global population. The current diagnostic methods for HP are either invasive, time-consuming, or harmful. Therefore, a noninvasive and label-free HP diagnostic method needs to be developed urgently. Herein, reduced graphene oxide (rGO) is composited with different metal-based materials to construct a graphene-based electronic nose (e-nose), which exhibits excellent sensitivity and cross-reactive response to several gases in exhaled breath (EB). Principal component analysis (PCA) shows that four typical types of gases in EB can be well discriminated. Additionally, the potential of the e-nose in label-free detection of HP infection is demonstrated through the measurement and analysis of EB samples. Furthermore, a prototype of an e-nose device is designed and constructed for automatic EB detection and HP diagnosis. The accuracy of the prototype machine integrated with the graphene-based e-nose can reach 92% and 91% in the training and validation sets, respectively. These results demonstrate that the highly sensitive graphene-based e-nose has great potential for the label-free diagnosis of HP and may become a novel tool for non-invasive disease screening and diagnosis.

Constructing an E-Nose Using Metal-Ion-Induced Assembly of Graphene Oxide for Diagnosis of Lung Cancer via Exhaled Breath.

A flexible electronic-nose (E-nose) was constructed by assembling graphene oxide (GO) using different types of metal ions (Mx+) with different ratio of GO to Mx+. Owing to the cross-linked networks, the Mx+-induced assembly of graphene films resulted in different porous structures. A chemi-resistive sensor array was constructed by coating the GO-M hybrid films on PET substrate patterned with 8 interdigited electrodes, followed by in situ reduction of GO to rGO with hydrazine vapor. Each of the sensing elements on the sensor array showed a cross-reactive response toward different types of gases at room temperature. Compared to bare rGO, incorporation of metal species into rGO significantly improved sensitivity owing to the additional interaction between metal species and gas analyte. Principle component analysis (PCA) showed that four types of exhaled breath (EB) biomarkers including acetone, isoprene, ammonia, and hydrothion in sub-ppm concentrations can be discriminated well. To overcome the interference from humidity in EB, a protocol to collect and analyze EB gases was established and further validated by simulated EB samples. Finally, clinical EB samples collected from patients with lung cancer and healthy controls were analyzed. In a 106 case study, the healthy group can be accurately distinguished from lung cancer patients by linear discrimination analysis. With the assistance of an artificial neural network, a sensitivity of 95.8% and specificity of 96.0% can be achieved in the diagnosis of lung cancer based on the E-nose. We also find that patients with renal failure can be distinguished through comparison of dynamic response curves between patient and healthy samples on some specific sensing elements. These results demonstrate the proposed E-nose will have great potential in noninvasive disease screening and personalized healthcare management.

Self-powered gas sensor based on SiNWs/ITO photodiode.

Silicon nanowires (SiNWs) with a large surface-to-volume ratio and a low reflectivity are exceedingly attractive building blocks for developing high performance light harvesting devices. Herein, a SiNW/ITO heterojunction was fabricated easily by just compressing the SiNWs and ITO electrode together with a suitable pressure. Under light illumination, the SiNWs/ITO with an optimized structure can generate more than 20 µA photocurrent at zero bias voltage. In the mean time, the photocurrent is very sensitive to NO2 infiltration into the forest of SiNWs and displays a non-linear relationship with the concentration of NO2 from 0 to 1000 ppb. In comparison with chemiresistive sensors based on SiNWs only, the sensitivity of the self-powered sensor was improved obviously, showing a limit of detection at ∼5 ppb. The excellent light trapping and sensing performance was attributed to the heterojunction formed between SiNWs and ITO. Since the nano-photodiode device can monitor the surrounding gas without an external power supply, it will ensure that sensor networks can operate independently and sustainably without a battery or at least by extending the life time of a battery. This work may push forward the development of self-powered microsensors using rationally designed nanojunctions.

2D Hybrid Nanomaterials for Selective Detection of NO2 and SO2 Using "Light On and Off" Strategy.

In order to distinguish NO2 and SO2 gas with one sensor, we designed a paper chip assembled with a 2D g-C3N4/rGO stacking hybrid fabricated via a layer-by-layer self-assembly approach. The g-C3N4/rGO hybrid exhibited a remarkable photoelectric property due to the construction of a van der Waals heterostructure. For the first time, we have been able to selectively detect NO2 and SO2 gas using a "light on and off" strategy. Under the "light off" condition, the g-C3N4/rGO sensor exhibited a p-type semiconducting behavior with a low detection limit of 100 ppb of NO2, but with no response toward SO2. In contrast, the sensor showed n-type semiconducting behavior which could detect SO2 at concentration as low as 2 ppm under UV light irradiation. The effective electron transfer among the 2D structure of g-C3N4 and rGO nanosheets as well as highly porous structures could play an important role in gas sensing. The different sensing mechanisms at "light on and off" circumstances were also investigated in detail.

Low Power Consumption Gas Sensor Created from Silicon Nanowires/TiO2 Core-Shell Heterojunctions.

Silicon nanowires/TiO2 (SiNWs/TiO2) array with core-shell nanostructure was created by sol-gel and drop-casting methods. The hybrid material displayed excellent sensing performance for CH4 detection at room temperature. The chemiresistor sensor has a linear response toward CH4 gas in the 30-120 ppm range with a detection limit of 20 ppm, which is well below most CH4 sensors reported before. The enhanced gas sensing performance at room temperature was attributed to the creation of heterojunctions that form a depletion layer at the interface of SiNWs and TiO2 layer. Adsorption of oxygen and corresponding gas analyte on TiO2 layer could induce the change of depletion layer thickness and consequently the width of the SiNWs conductive channel, leading to a sensitive conductive response toward gas analyte. Compared to conventional metal oxide gas sensors, the room temperature gas sensors constructed from SiNWs/TiO2 do not need an additional heating device and work at power at the µW level. The low power consumption feature is of great importance for sensing devices, if they are widely deployed and connected to the Internet of Things. The innovation of room temperature sensing materials may push forward the integration of gas sensing element with wireless device.

Optical nose based on porous silicon photonic crystal infiltrated with ionic liquids.

A photonic-nose for the detection and discrimination of volatile organic compounds (VOCs) was constructed. Each sensing element on the photonic sensor array was formed by infiltrating a specific type of ionic liquid (IL) into the pore channel of a patterned porous silicon (PSi) chip. Upon exposure to VOC, the density of IL dramatically decreased due to the nano-confinement effect. As a result, the IL located in pore channel expanded its volume and protrude out of the pore channel, leading to the formation of microdroplets on the PSi surface. These VOC-stimulated microdroplets could scatter the light reflected from the PSi rugate filter, thereby producing an optical response to VOC. The intensity of the optical response produced by IL/PSi sensor mainly depends on the size and shape of microdroplets, which is related to the concentration of VOC and the physi-chemical propertied of ILs. For ethanol vapor, the optical response has linear relationship with its relative vapor pressure within 0-60%. The LOD of the IL/PSi sensor for ethanol detection is calculated to be 1.3 ppm. It takes around 30 s to reach a full optical response, while the time for recovery is less than 1 min. In addition, the sensor displayed good stability and reproducibility. Owing to the different molecular interaction between IL and VOC, the ILs/PSi sensor array can generate a unique cross-reactive "fingerprint" in response to a specific type of VOC analyte. With the assistance of image technologies and principle components analysis (PCA), rapid discrimination of VOC analyte could be achieved based on the pattern recognition of photonic sensor array. The technology established in this work allows monitoring in-door air pollution in a visualized way.

A vertical tip-tip contact silicon nanowire array for gas sensing.

Novel chemiresistive gas sensors based on a vertical tip-tip contact silicon nanowire (TTC-SiNW) array were constructed. The welding of TTC-SiNWs after joule heating treatment was confirmed by a current-voltage curve (I-V curve). The TTC-SiNW structure not only resolved the problem of electrode contact encountered in conventional nanowire sensors, but also elongated the nanowire length to increase the void space for fast gas diffusion. The TTC-SiNW sensor comprising the same two types of SiNW arrays responded to NO2 very sensitively. The LOD for the p-p and n-n contact SiNW arrays is around 150 ppb and 3 ppb (S/N = 3), respectively. Furthermore, the highly oriented nano-junction formed on the TTC structure provided solid evidence to clarify the contribution of the nanojunction to gas sensing behavior. The TTC-SiNW sensor with a p-n junction displays a significant rectification effect. The sensitive response towards NO2 (LOD is about 18 ppb) was observed at a reverse bias voltage, whereas the response at a forward bias voltage was insignificant. Finally, the mechanism of gas sensing behavior on different types of TTC structures was proposed.

Treatment of obesity and diabetes using oxytocin or analogs in patients and mouse models.

Obesity is important for the development of type-2 diabetes as a result of obesity-induced insulin resistance accompanied by impaired compensation of insulin secretion from pancreatic beta cells. Here, based on a randomized pilot clinical trial, we report that intranasal oxytocin administration over an 8-week period led to effective reduction of obesity and reversal of related prediabetic changes in patients. Using mouse models, we further systematically evaluated whether oxytocin and its analogs yield therapeutic effects against prediabetic or diabetic disorders regardless of obesity. Our results showed that oxytocin and two analogs including [Ser4, Ile8]-oxytocin or [Asu1,6]-oxytocin worked in mice to reverse insulin resistance and glucose intolerance prior to reduction of obesity. In parallel, using streptozotocin-induced diabetic mouse model, we found that treatment with oxytocin or its analogs reduced the magnitude of glucose intolerance through improving insulin secretion. The anti-diabetic effects of oxytocin and its analogs in these animal models can be produced similarly whether central or peripheral administration was used. In conclusion, oxytocin and its analogs have multi-level effects in improving weight control, insulin sensitivity and insulin secretion, and bear potentials for being developed as therapeutic peptides for obesity and diabetes.