Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array.

INTRODUCTION: Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning. METHODS: Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning. RESULTS: Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively. CONCLUSION: Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.

Sorption Kinetic Parameters from Nanomechanical Sensing for Discrimination of 2-Nonenal from Saturated Aldehydes.

Nanomechanical sensors have gained significant attention as promising platforms for artificial olfaction. Since sorption kinetic parameters that can be estimated from the sensing signals of nanomechanical sensors reflect the chemical and physicochemical interactions between the odorant and receptor material, the parameters can be utilized for the direct discrimination of each odorant. In this study, we demonstrated the discrimination of 20 vapors, including hydrocarbons, alcohols, organic acids, ketones, and aldehydes, which are reported as human body odor components, using the parameters extracted in the analytical solution of nanomechanical sensors based on sorption kinetics with viscoelastic behaviors. By using one of the specific nanomechanical sensors─membrane-type surface stress sensor─as a sensing unit, we successfully discriminated trans-2-nonenal known as an aging marker from other saturated aldehydes along with quantifying their concentrations.

Ionic Liquid Interface as a Cell Scaffold.

In sharp contrast to conventional solid/hydrogel platforms, water-immiscible liquids, such as perfluorocarbons and silicones, allow the adhesion of mammalian cells via protein nanolayers (PNLs) formed at the interface. However, fluorocarbons and silicones, which are typically used for liquid cell culture, possess only narrow ranges of physicochemical parameters and have not allowed for a wide variety of cell culturing environments. In this paper, it is proposed that water-immiscible ionic liquids (ILs) are a new family of liquid substrates with tunable physicochemical properties and high solvation capabilities. Tetraalkylphosphonium-based ILs are identified as non-cytotoxic ILs, whereon human mesenchymal stem cells are successfully cultured. By reducing the cation charge distribution, or ionicity, via alkyl chain elongation, the interface allows cell spreading with matured focal contacts. High-speed atomic force microscopy observations of the PNL formation process suggest that the cation charge distribution significantly altered the protein adsorption dynamics, which are associated with the degree of protein denaturation and the PNL mechanics. Moreover, by exploiting dissolution capability of ILs, an ion-gel cell scaffold is fabricated. This enables to further identify the significant contribution of bulk subphase mechanics to cellular mechanosensing in liquid-based culture scaffolds.

Effects of fermentative quality of corn silage on lactation, blood metabolites, and rumen fermentation in dairy cows.

We investigated the effect of fermentation quality of corn silage on dry matter intake (DMI), milk yield, ruminal fermentation, methane (CH4 ) emissions, and plasma metabolites in lactating cows. Six lactating Holstein cows were used in a 2 × 2 crossover design with two dietary treatments containing high quality corn silage with lower pH (high group) or low quality corn silage with higher pH (low group). The cows were fed partial mixed ration (PMR containing 50%DM of each corn silage) ad libitum plus 0.7 kg/day of concentrates at milking. The DMI of cows in the low group (24.8 kg/day) tended to be lower (p < 0.10) than that in the high group (26.8 kg/day). The dietary treatment did not affect milk yield or milk fat, protein, or lactose concentrations. The ruminal acetic acid proportion of the low group was significantly higher (p < 0.05) than that of the high group. The CH4 emission per DMI of the low group tended to be higher (p < 0.10) than that of the high group. The plasma concentration of the total cholesterol (TCHO) and the activity of aspartate aminotransferase and alanine aminotransferase of the low group were significantly higher than those of the high group.

Repetitive Direct Comparison Method for Odor Sensing.

Olfactory sensors are one of the most anticipated applications of gas sensors. To distinguish odors-complex mixtures of gas species, it is necessary to extract sensor responses originating from the target odors. However, the responses of gas sensors tend to be affected by interfering gases with much higher concentrations than target odor molecules. To realize practical applications of olfactory sensors, extracting minute sensor responses of odors from major interfering gases is required. In this study, we propose a repetitive direct comparison (rDC) method, which can highlight the difference in odors by alternately injecting the two target odors into a gas sensor. We verified the feasibility of the rDC method on chocolates with two different flavors by using a sensor system based on membrane-type surface stress sensors (MSS). The odors of the chocolates were measured by the rDC method, and the signal-to-noise ratios (S/N) of the measurements were evaluated. The results showed that the rDC method achieved improved S/N compared to a typical measurement. The result also indicates that sensing signals could be enhanced for a specific combination of receptor materials of MSS and target odors.

Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors.

The measurement of volatile fatty acids (VFAs) is of great importance in the fields of food and agriculture. There are various methods to measure VFAs, but most methods require specific equipment, making on-site measurements difficult. In this work, we demonstrate the measurements of VFAs in a model sample, silage, through its vapor using an array of nanomechanical sensors-Membrane-type Surface stress Sensors (MSS). Focusing on relatively slow desorption behaviors of VFAs predicted with the sorption kinetics of nanomechanical sensing and the dissociation nature of VFAs, the VFAs can be efficiently measured by using features extracted from the decay curves of the sensing response, resulting in sufficient discrimination of the silage samples. Since the present sensing system does not require expensive, bulky setup and pre-treatment of samples, it has a great potential for practical applications including on-site measurements.

Detection of Trace Amounts of Water in Organic Solvents by DNA-Based Nanomechanical Sensors.

The detection of trace amounts of water in organic solvents is of great importance in the field of chemistry and in the industry. Karl Fischer titration is known as a classic method and is widely used for detecting trace amounts of water; however, it has some limitations in terms of rapid and direct detection because of its time-consuming sample preparation and specific equipment requirements. Here, we found that a DNA-based nanomechanical sensor exhibits high sensitivity and selectivity to water vapor, leading to the detection and quantification of trace amounts of water in organic solvents as low as 12 ppm in THF, with a ppb level of LoD through their vapors. Since the present method is simple and rapid, it can be an alternative technique to the conventional Karl Fischer titration.

Visualization of Flow-Induced Strain Using Structural Color in Channel-Free Polydimethylsiloxane Devices.

Measuring flow of gases is of fundamental importance yet is typically done with complex equipment. There is, therefore, a longstanding need for a simple and inexpensive means of flow measurement. Here, gas flow is measured using an extremely simple device that consists of an Ar plasma-treated polydimethylsiloxane (PDMS) slab adhered on a glass substrate with a tight seal. This device does not even have a channel, instead, gas can flow between the PDMS and the glass by deforming the PDMS wall, in other words, by making an interstice as a temporary path for the flow. The formation of the temporary path results in a compressive bending stress at the inner wall of the path, which leads to the formation of well-ordered wrinkles, and hence, the emergence of structural color that changes the optical transmittance of the device. Although it is very simple, this setup works sufficiently well to measure arbitrary gases and analyzes their flow rates, densities, and viscosities based on the change in color. It is also demonstrated that this technique is applicable to the flow-induced display of a pattern such as a logo for advanced applications.

Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction.

Nanomechanical sensors have gained significant attention as powerful tools for detecting, distinguishing, and identifying target analytes, especially odors that are composed of a complex mixture of gaseous molecules. Nanomechanical sensors and their arrays are a promising platform for artificial olfaction in combination with data processing technologies, including machine learning techniques. This paper reviews the background of nanomechanical sensors, especially conventional cantilever-type sensors. Then, we focus on one of the optimized structures for static mode operation, a nanomechanical Membrane-type Surface stress Sensor (MSS), and discuss recent advances in MSS and their applications towards artificial olfaction.

Nanomechanical Sensors for Gas Detection towards Artificial Olfaction.

Humans, as well as other organisms, tend to recognize their surroundings by smells/odors [...].

Statistical Evaluation of Total Expiratory Breath Samples Collected throughout a Year: Reproducibility and Applicability toward Olfactory Sensor-Based Breath Diagnostics.

The endogenous volatile organic compounds (VOCs) in exhaled breath can be promising biomarkers for various diseases including cancers. An olfactory sensor has a possibility for extracting a specific feature from collective variations of the related VOCs with a certain health condition. For this approach, it is important to establish a feasible protocol for sampling exhaled breath in practical conditions to provide reproducible signal features. Here we report a robust protocol for the breath analysis, focusing on total expiratory breath measured by a Membrane-type Surface stress Sensor (MSS), which possesses practical characteristics for artificial olfactory systems. To assess its reproducibility, 83 exhaled breath samples were collected from one subject throughout more than a year. It has been confirmed that the reduction of humidity effects on the sensing signals either by controlling the humidity of purging room air or by normalizing the signal intensities leads to reasonable reproducibility verified by statistical analyses. We have also demonstrated the applicability of the protocol for detecting a target material by discriminating exhaled breaths collected from different subjects with pre- and post-alcohol ingestion on different occasions. This simple yet reproducible protocol based on the total expiratory breath measured by the MSS olfactory sensors will contribute to exploring the possibilities of clinical applications of breath diagnostics.

Determination of quasi-primary odors by endpoint detection.

It is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: "quasi" primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find "extreme" odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.

Autonomous Nanoscale Chemomechanical Oscillation on the Self-Oscillating Polymer Brush Surface by Precise Control of Graft Density.

As a novel functional surface, a self-oscillating polymer brush that undergoes autonomous, periodic swelling/deswelling during the Belousov-Zhabotinsky (BZ) reaction has been developed. Although extensive research has revealed how the fundamental aspects of the BZ reaction can be regulated based on the surface design of the self-oscillating polymer brush, design strategies for the induction of mechanical oscillation remain unexplored. Herein, we investigated the graft density effects on the phase transition behavior, which is an important design parameter for the mechanical oscillation of the modified polymer. The self-oscillating polymer-modified substrates with controlled graft densities were prepared by immobilizing various compositions of an initiator and a noninitiator followed by surface-initiated atom transfer radical polymerization of the self-oscillating polymer chains. In addition to the characterization of each prepared substrate, atomic force microscopy (AFM) and digital holographic microscopy (DHM) were employed to evaluate the density effects on the static and dynamic surface structures. AFM revealed that equilibrium swelling as well as thermoresponsive behavior is profoundly affected by the graft density. Moreover, using DHM, autonomous mechanical oscillation was captured only on the self-oscillating polymer brush with adequate graft density. Notably, the oscillation amplitude (150 nm) and the period (20 s) in this study were superior to those in a previous report on the self-oscillating polymer modified through the grafting-to method by 10- and 3-fold, respectively. This study presents design guidelines for future applications, such as autonomous transport devices.

Finite Element Analysis of Interface Dependence on Nanomechanical Sensing.

Nanomechanical sensors and their arrays have been attracting significant attention for detecting, discriminating and identifying target analytes. The sensing responses can be partially explained by the physical properties of the receptor layers coated on the sensing elements. Analytical solutions of nanomechanical sensing are available for a simple cantilever model including the physical parameters of both a cantilever and a receptor layer. These analytical solutions generally rely on the simple structures, such that the sensing element and the receptor layer are fully attached at their boundary. However, an actual interface in a real system is not always fully attached because of inhomogeneous coatings with low affinity to the sensor surface or partial detachments caused by the exposure to some analytes, especially with high concentration. Here, we study the effects of such macroscopic interfacial structures, including partial attachments/detachments, for static nanomechanical sensing, focusing on a Membrane-type Surface stress Sensor (MSS), through finite element analysis (FEA). We simulate various macroscopic interfacial structures by changing the sizes, numbers and positions of the attachments as well as the elastic properties of receptor layers (e.g., Young's modulus and Poisson's ratio) and evaluate the effects on the sensitivity. It is found that specific interfacial structures lead to efficient sensing responses, providing a guideline for designing the coating films as well as optimizing the interfacial structures for higher sensitivity including surface modification of the substrate.

Adaptive Liquid Interfacially Assembled Protein Nanosheets for Guiding Mesenchymal Stem Cell Fate.

There is a growing interest in the development of dynamic adaptive biomaterials for regulation of cellular functions. However, existing materials are limited to two-state switching of the presentation and removal of cell-adhesive bioactive motifs that cannot emulate the native extracellular matrix (ECM) in vivo with continuously adjustable characteristics. Here, tunable adaptive materials composed of a protein monolayer assembled at a liquid-liquid interface are demonstrated, which adapt dynamically to cell traction forces. An ultrastructure transition from protein monolayer to hierarchical fiber occurs through interfacial jamming. Elongated fibronectin fibers promote formation of elongated focal adhesion structures, increase focal adhesion kinase activation, and enhance neuronal differentiation of stem cells. Cell traction force results in spatial rearrangement of ECM proteins, which feeds back to alter stem cell fate. The reported biomimetic adaptive liquid interface enables dynamic control of stem cell behavior and has potential translational applications.

Modulation of Mesenchymal Stem Cells Mechanosensing at Fluid Interfaces by Tailored Self-Assembled Protein Monolayers.

Mechanical cues of cellular microenvironments can modulate cell functions including cell spreading and differentiation. Most studies of cellular functions are performed using a solid substrate, and it is thought that cells cannot spread on fluid substrates because of rapid relaxation, which cannot resist against actomyosin-based cell contractility. Here, the spreading and growth of anchorage-dependent cells such as human mesenchymal stem cells at the liquid interface between a perfluorocarbon fluid and the culture medium are observed. It is demonstrated that a monomolecular protein nanosheet self-assembled at a fluid interface is sufficiently rigid to support cell spreading without additional treatment. Fine tuning of the packing of these proteins at the liquid interface permits tailoring of the mechanics of the protein layer, ultimately allowing for the regulation of cell spreading. The greater stiffness of the protein nanosheets triggers cell spreading, adhesion growth, and yes-associated protein nuclear translocation. Cell behavior at the fluid interface is explained within the framework of the molecular clutch model. In addition, the freestanding ultrathin protein nanosheets are extremely flexible, easily deformed, and perceived by cells as being much softer. The findings are expected to provide a new perspective for insights into cell-material interactions.

Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis.

A sensing signal obtained by measuring an odor usually contains varied information that reflects an origin of the odor itself, while an effective approach is required to reasonably analyze informative data to derive the desired information. Herein, we demonstrate that quantitative odor analysis was achieved through systematic material design-based nanomechanical sensing combined with machine learning. A ternary mixture consisting of water, ethanol, and methanol was selected as a model system where a target molecule coexists with structurally similar species in a humidified condition. To predict the concentration of each species in the system via the data-driven approach, six types of nanoparticles functionalized with hydroxyl, aminopropyl, phenyl, and/or octadecyl groups were synthesized as a receptor coating of a nanomechanical sensor. Then, a machine learning model based on Gaussian process regression was trained with sensing data sets obtained from the samples with diverse concentrations. As a result, the octadecyl-modified nanoparticles enhanced prediction accuracy for water while the use of both octadecyl and aminopropyl groups was indicated to be a key for a better prediction accuracy for ethanol and methanol. As the prediction accuracy for ethanol and methanol was improved by introducing two additional nanoparticles with finely controlled octadecyl and aminopropyl amount, the feedback obtained by the present machine learning was effectively utilized to optimize material design for better performance. We demonstrate through this study that various information which was extracted from plenty of experimental data sets was successfully combined with our knowledge to produce wisdom for addressing a critical issue in gas phase sensing.

Effects of Center Metals in Porphines on Nanomechanical Gas Sensing.

Porphyrin is one of the most promising materials for realizing a practical artificial olfactory sensor system. In this study, we focus on non-substituted porphyrins—porphines—as receptor materials of nanomechanical membrane-type surface stress sensors (MSS) to investigate the effect of center metals on gas sensing. By omitting the substituents on the tetrapyrrole macrocycle of porphyrin, the peripheral interference by substituents can be avoided. Zinc, nickel, and iron were chosen for the center metals as these metalloporphines show different properties compared to free-base porphine. The present study revealed that iron insertion enhanced sensitivity to various gases, while zinc and nickel insertion led to equivalent or less sensitivity than free-base porphine. Based on the experimental results, we discuss the role of center metals for gas uptake from the view point of molecular interaction. We also report the high robustness of the iron porphine to humidity, showing the high feasibility of porphine-based nanomechanical sensor devices for practical applications in ambient conditions.

Hierarchical Assembly of siRNA with Tetraamino Fullerene in Physiological Conditions for Efficient Internalization into Cells and Knockdown.

Delivery of siRNA is a key technique in alternative gene therapy, where the siRNA cargo must be effectively loaded onto a tailor-designed carrier molecule and smoothly unloaded precisely upon arrival at the target cells or organs. Any toxicity issues also need to be mitigated by suitable choice of the carrier molecule. A water-soluble cationic fullerene, tetra(piperazino)[60]fullerene epoxide (TPFE), was previously shown to be nontoxic and effective for lung-targeted in vivo siRNA delivery by way of agglutination-induced accumulation. We found in this in vitro study that hierarchical reversible assembly of micrometer-sized TPFE-siRNA-serum protein ternary complexes is the key element for effective loading and release, and stabilization of otherwise highly unstable siRNA under the physiological conditions. The amphiphilic TPFE molecule forms a sub-10 nm-sized stable micelle because of strong cohesion between fullerene molecules, and this fullerene aggregate protects siRNA and induces the hierarchical assembly. Unlike popularly used polyamine carriers, TPFE is not toxic at the dose used for the siRNA delivery.

Conformation Manipulation and Motion of a Double Paddle Molecule on an Au(111) Surface.

The molecular conformation of a bisbinaphthyldurene (BBD) molecule is manipulated using a low-temperature ultrahigh-vacuum scanning tunneling microscope (LT-UHV STM) on an Au(111) surface. BBD has two binaphthyl groups at both ends connected to a central durene leading to anti/syn/flat conformers. In solution, dynamic nuclear magnetic resonance indicated the fast interexchange between the anti and syn conformers as confirmed by density functional theory calculations. After deposition in a submonolayer on an Au(111) surface, only the syn conformers were observed forming small islands of self-assembled syn dimers. The syn dimers can be separated into syn monomers by STM molecular manipulations. A flat conformer can also be prepared by using a peculiar mechanical unfolding of a syn monomer by STM manipulations. The experimental STM dI/dV and theoretical elastic scattering quantum chemistry maps of the low-lying tunneling resonances confirmed the flat conformer BBD molecule STM production. The key BBD electronic states for a step-by-step STM inelastic excitation lateral motion on the Au(111) are presented requiring no mechanical interactions between the STM tip apex and the BBD. On the BBD molecular board, selected STM tip apex positions for this inelastic tunneling excitation enable the flat BBD to move controllably on Au(111) by a step of 0.29 nm per bias voltage ramp.