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A cutting edge therapy for future immuno-oncology is targeting a new series of inhibitory receptors (IRs): LAG-3, TIM-3, and TIGIT. Both immunogenomic analyses and diagnostic platforms to distinguish candidates and predict good responders to these IR-related agents are vital in clinical pathology. By applying an automated single-cell count for immunolabelled LAG-3, TIM-3, and TIGIT, we reveal that individual IR levels with exclusive domination in each tumour can serve as valid biomarkers for profiling human renal cell carcinoma (RCC). We uncover the immunogenomic landscape associated with individual IR levels in human RCC tumours with metastases in various organs and histological subtypes. We then externally validate our results and devise a workflow with optimal biomarker cut-offs for discriminating the LAG-3, TIM-3, and TIGIT tumour profiles. The discrimination of LAG-3, TIM-3, and TIGIT profiles in tumours may have a broad impact on investigations of immunotherapy responses after targeting a new series of IRs. Targeting the inhibitory receptors (IRs) LAG-3, TIM-3 and TIGIT is a promising immune-oncology approach and the identification of biomarkers of response is crucial. Here, the authors apply automated single-cell count for these IRs in human renal cell carcinoma and investigate the immunogenomic landscape of the disease.

Conventional gas direction estimation methods that rely on concentration gradients or time-of-arrival differences typically require multiple spatially dispersed sensors, leading to increased system bulkiness and complexity. Furthermore, previous CMOS-based approaches that relied on gas diffusion struggled to achieve stable direction estimation in high-speed airflow environments. To address these challenges, we propose a streamlined method integrating a pillar onto a single CMOS gas-sensor array, eliminating additional MEMS fabrication. This approach exploits a fluid dynamic phenomenon where the pillar creates a distinct flow “shadow” pattern (a region of localized gas dilution) on the sensor surface. Experimental verification using ammonia gas confirmed that this “shadow” is clearly observable as a localized reduction in sensor output under high-speed turbulent flow. Crucially, the spatial position of this pattern correlates strongly with the direction of gas inflow. This study demonstrates the feasibility of gas direction estimation using a single chip, paving the way for high-precision detection in challenging, rapid-airflow environments.

Recent studies have shown that protons can function as neurotransmitters in cultured neurons. To further investigate regional and neural activity-dependent proton dynamics in the brain, the development of a device with both wide-area detectability and high spatial-ltemporal resolution is necessary. Therefore, we develop an image sensor with a high spatial-temporal resolution specifically designed for measuring protons in vivo. Here, we demonstrate that spatially deferent neural stimulation by visual stimulation induced distinct patterns of proton changes in the visual cortex. This result indicates that our biosensor can detect micrometer and millisecond scale changes of protons across a wide area. Our study demonstrates that a CMOS-based proton image sensor with high spatial and temporal precision can be used to detect pH changes associated with biological events. We believe that our sensor may have broad applicability in future biological studies. Protons have been discovered to play a role in neuronal signaling, but current methods to measure pH in the brain of animal models are limited. Here the authors develop a miniaturized proton image sensor that fits into a living mouse brain and can measure pH changes at micrometer and millisecond resolution scales.

An implantable multi-ion image sensor equipped with magnesium ion (Mg2+)-and calcium ion (Ca2+)-sensitive membranes was fabricated for the selective measurement of extracellular Mg2+ in the brain, and the sensor performance was evaluated. This sensor complements the low selectivity of the Mg2+-sensitive membrane for Ca2+ by depositing a Ca2+-sensitive membrane in addition to the Mg2+-sensitive membrane on a CMOS (Complementary Metal Oxide Semiconductor)-based potentiometric sensor array with 5.65 × 4.39 µm2 pitch, enabling selective measurement of Mg2+ and Ca2+. Characterization of the sensor confirmed a Ca2+ sensitivity of 26.5 mV/dec and Mg2+ sensitivity of 19 mV/dec. Based on validation experiments with varying concentrations of Mg2+ and Ca2+, selective Ca2+ and Mg2+ measurements were successfully achieved. Furthermore, real-time imaging of Mg2+ and Ca2+ and quantification of their concentration changes were performed. The developed sensor may be successfully applied for extracellular multi-ion imaging of Mg2+ and Ca2+ in the living brain.

Demand for the detection of carbon dioxide (CO 2 ) is increasing in various fields, including air-quality monitoring, healthcare, and agriculture. On the other hand, smart gas sensors, in which micromachined gas sensors are integrated with driving circuits, are desirable toward the development of the society of the internet of things. In this study, micromachined hotplate-based CO 2 sensors were fabricated and their characteristics were investigated. The sensors have La 2 O 3 /SnO 2 stacked layers as a sensing material and Pt interdigitated electrodes. A CO 2 response of 2.9 for a CO 2 concentration of 1000 ppm was obtained at 350 °C with low power consumption (approximately 17 mW). A relatively large response was obtained compared with previous studies even though a compact sputtered-SnO 2 film was used. This high response was speculated to be due to a significant contribution of the resistance component near the electrode. Furthermore, CO 2 sensing was successfully performed in the CO 2 range of 200–4000 ppm with at least 200-ppm resolution.

Ethanol (EtOH) gas detection has garnered considerable attention owing to its wide range of applications in industries such as food, pharmaceuticals, medical diagnostics, and fuel management. The development of highly sensitive EtOH-gas sensors has become a focus of research. This study proposes an optical interferometric surface stress sensor for detecting EtOH gas. The sensor incorporates a 100 nm-thick freestanding membrane of Parylene C and gas-sensitive polymethylmethacrylate (PMMA) fabricated within a microcavity on a Si substrate. The results showed that reducing the thickness of the freestanding Parylene C membrane is essential for achieving higher sensitivity. Previously, a 100-nm-thick membrane transfer onto microcavities was achieved using a surfactant-assisted release technique. However, polymerization inhibition caused by the surfactant presented challenges in forming ultrathin membranes of several tens of nanometers. In this study, we employed a surfactant-free release technique using a hydrophilic natural oxide layer to successfully form a 14-nm-thick freestanding Parylene C membrane. In contrast, the optimum thickness of the gas-adsorbed PMMA membrane was approximately 295 nm. Moreover, we demonstrated that this thinner membrane improved EtOH gas detection sensitivity by a factor of eight compared with our previously reported sensor. Thus, this study advances the field of nanoscale materials and sensor technology.

The Belousov–Zhabotinsky (BZ) self-oscillation reaction is an important chemical model to elucidate nonequilibrium chemistry in an open system. However, there are only a few studies on the electrical behavior of pH oscillation induced by the BZ reaction, although numerous studies have been carried out to investigate the mechanisms by which the BZ reaction interacts with redox reactions, which results in potential changes. Needless to say, the electrical characteristic of a self-oscillating polymer gel driven by the BZ reaction has not been clarified. On the other hand, a solution-gated ion-sensitive field-effect transistor (ISFET) has a superior ability to detect ionic charges and includes capacitive membranes on the gate electrode. In this study, we carried out the electrical monitoring of self-oscillation behaviors at the chemoelectrical interface based on the BZ reaction using ISFET sensors, focusing on the pH oscillation and the electrical dynamics of the self-oscillating polymer brush. The pH oscillation induced by the BZ reaction is not only electrically observed using the ISFET sensor, the electrical signals of which results from the interfacial potential between the solution and the gate insulator, but also visualized using a large-scale and high-density ISFET sensor. Moreover, the N -isopropylacrylamide (NIPAAm)-based self-oscillating polymer brush with Ru(bpy) 3 as a catalyst clearly shows a periodic electrical response based on the swelling–deswelling behavior caused by the BZ reaction on the gate insulator of the ISFET sensor. Thus, the elucidation of the electrical self-oscillation behaviors induced by the BZ reaction using the ISFET sensor provides a solution to the problems of nonequilibrium chemistry.

We developed a Fabry–Perot interferometer sensor with a metal-oxide-semiconductor field-effect transistor (MOSFET) circuit for chemical sensing. The novel signal transducing technique was performed in three steps: mechanical deflection, transmittance change, and photocurrent change. A small readout photocurrent was processed by an integrated source follower circuit. The movable film of the sensor was a 350-nm-thick polychloro-para-xylylene membrane with a diameter of 100 µm and an air gap of 300 nm. The linearity of the integrated source follower circuit was obtained. We demonstrated a gas response using 80-ppm ethanol detected by small membrane deformation of 50 nm, which resulted in an output-voltage change with the proposed high-efficiency transduction.

Towards clarifying the spatio-temporal neurotransmitter distribution, potentiometric redox sensor arrays with 23.5-µm resolution were fabricated. The sensor array based on a charge-transfer-type potentiometric sensor comprises 128×128 pixels with gold electrodes deposited on the surface of pixels. The sensor output corresponding to the interfacial potential of the electrode changed logarithmically with the mixture ratio of K3Fe(CN)6 and K4Fe(CN)6, where the redox sensitivity reached 49.9 mV/dec. By employing hydrogen peroxidase as an enzyme and ferrocene as an electron mediator, the sensing characteristics for hydrogen peroxide (H2O2) were investigated. The analyses of the sensing characteristics revealed that the sensitivity was about 44.7 mV/dec., comparable to the redox sensitivity, while the limit of detection (LOD) was achieved to be 1 µM. Furthermore, the oxidation state of the electron mediator can be the key to further lowering the LOD. Then, by immobilizing oxidizing enzyme for H2O2 and glutamate oxidase, glutamate (Glu) measurements were conducted. As a result, similar sensitivity and LOD to those of H2O2 were obtained. Finally, the real-time distribution of 1 µM Glu was visualized, demonstrating the feasibility of our device as a high-resolution bioimaging technique.

Disease screening by exhaled breath diagnosis is less burdensome for patients, and various devices have been developed as promising diagnostic methods. We developed a microelectromechanical system (MEMS) optical interferometric surface stress sensor to detect volatile ethanol gas at room temperature (26~27 °C) with high sensitivity. A sub-micron air gap in the optical interferometric sensor reduces interference orders, leading to increased spectral response associated with nanomechanical deflection caused by ethanol adsorption. The sub-micron cavity was embedded in a substrate using a transfer technique of parylene-C nanosheet. The sensor with a 0.4 µm gap shows a linear stable reaction, with small standard deviations, even at low ethanol gas concentrations of 5–110 ppm and a reversible reaction to the gas concentration change. Furthermore, the possibility of detecting sub-ppm ethanol concentration by optimizing the diameter and thickness of the deformable membrane is suggested. Compared with conventional MEMS surface stress gas sensors, the proposed optical interferometric sensor demonstrated high-sensitivity gas detection with exceeding the detection limit by two orders of magnitude while reducing the sensing area.