Differences and Risk Factors of Peripheral Blood Immune Cells in Patients with Obstructive Sleep Apnea.

Introduction: Obstructive sleep apnea (OSA) is a respiratory disorder characterized by chronic intermittent hypoxia and fragmented sleep, leading to inflammatory response and oxidative stress. However, the differences in immune inflammatory response in OSA patients with different severity remain unclear. Purpose: This study aims to examine the differences in peripheral blood immune cells and their risk factors in OSA patients. Patients and Methods: A total of 277 snoring patients from the Sleep Respiratory Disorder Monitoring Center of Zhongnan Hospital of Wuhan University were recruited in this study. According to the diagnosis and severity criteria of OSA, the included patients were further divided into simple snoring, mild, moderate, and severe groups. Peripheral blood immune cell counts including white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils, red blood cells, platelets, and polysomnography indicators were collected from the patients. Results: Compared with simple snoring patients, the OSA patients had increased circular monocyte and basophil count levels. In addition, correlation analysis results indicated that monocyte count was positively associated with chronic obstructive pulmonary disease (COPD), smoking, apnea-hypopnea index (AHI), the longest apnea duration, and Oxygen desaturation index (ODI), and negatively correlated with average SpO2 in snoring patients. Finally, multiple linear regression analysis revealed that AHI, COPD, smoking, and maximum heart rate were independent predictors of monocyte count. Conclusion: OSA patients had a significant increase in their peripheral blood monocyte count. AHI, COPD, smoking, and maximum heart rate were risk factors for increased peripheral blood monocyte count in OSA patients. These findings suggest that peripheral blood monocytes can be considered an inflammatory biomarker of OSA.

A cell-impermeable luminogenic probe for near-infrared imaging of prostate-specific membrane antigen in prostate cancer microenvironments.

Prostate-specific membrane antigen (PSMA) imaging probes are a promising tool for the diagnosis and image-guided surgery of prostate cancer (PCa). However, PSMA-specific luminescence probes for PCa detection and heterogeneity studies with high imaging contrast are lacking. Here, we report the first near-infrared (NIR) iridium(III) complex for the wash-free and specific imaging of PSMA in PCa cells and spheroids. The conjugation of a PSMA inhibitor, Lys-urea-Glu, to an iridium(III) complex synergizes the PSMA-specific affinity and biocompatibility of the inhibitor with the desirable photophysical properties of the iridium(III) complex, including NIR emission (670 nm), high photostability and a large Stokes shift. The cellular impermeability of the probe along with its strong binding affinity to PSMA enhances its specificity for PSMA, enabling the washing-free luminescent imaging of membrane PSMA with lower cytotoxicity. The probe was successfully applied for selectively visualizing PSMA-expressing cells and for the imaging of PSMA in a multicellular PCa model with good imaging penetration, indicating its potential use in complicated and heterogeneous tumor microenvironments. Furthermore, the probe showed good imaging performance in the PCa-bearing tumor mice via targeting PSMA in vivo. This work provides a novel strategy for the development of highly sensitive and specific NIR probes for PSMA in biological systems in vitro, which is of great significance for the precise diagnosis of PCa and for elucidating PCa heterogeneity.

Development of a NIR iridium(III) complex for self-calibrated and luminogenic detection of boron trifluoride.

Boron trifluoride (BF3) is a potential environmental pollutant, and excess exposure to it may cause human diseases. However, the sensitive, rapid and accurate detection of BF3 for on-site purposes is still a challenge. In this work, we developed the first NIR iridium(III)-based probe with dual emission and a Stokes shift of 370 nm for self-calibrated and luminogenic detection of BF3. This probe exhibited a strong luminescence enhancement at around 650 nm to BF3 (0-100 µM) with almost no change in luminescence at 475 nm, displaying a 220-fold I650 nm/I475 nm enhancement at 100 µM of BF3 with a detection limit of 0.35 µM. Moreover, the probe showed a fast response time of less than 5 s to BF3 along with an obvious color change under UV irradiation for visual detection. Importantly, the desirable photophysical properties of the iridium(III)-based probe can be harnessed for time-resolved detection of BF3 in the presence of the fluorescence background. The applicability of the probe was further verified in an organic solvent waste-spiked system and on a glass pane. This work will provide a solid basis for the development of sensitive and on-site BF3 sensing toolkits for environmental monitoring.

The Integration of Gold Nanoparticles with Polymerase Chain Reaction for Constructing Colorimetric Sensing Platforms for Detection of Health-Related DNA and Proteins.

Polymerase chain reaction (PCR) is the standard tool in genetic information analysis, and the desirable detection merits of PCR have been extended to disease-related protein analysis. Recently, the combination of PCR and gold nanoparticles (AuNPs) to construct colorimetric sensing platforms has received considerable attention due to its high sensitivity, visual detection, capability for on-site detection, and low cost. However, it lacks a related review to summarize and discuss the advances in this area. This perspective gives an overview of established methods based on the combination of PCR and AuNPs for the visual detection of health-related DNA and proteins. Moreover, this work also addresses the future trends and perspectives for PCR-AuNP hybrid biosensors.

Nicking enzyme-free strand displacement amplification-assisted CRISPR-Cas-based colorimetric detection of prostate-specific antigen in serum samples.

Immunosorbent assay is the gold standard diagnostic technique for the detection of protein biomarkers. However, this technique tends to have low sensitivity and requires laborious manipulation. Although advanced CRISPR-Cas-based biosensors offer advantages of simplicity, low cost and high accuracy, the synergy of using CRISPR-Cas-assisted dual signal amplification system for rapid diagnosis of protein biomarkers remains scarce. In this work, we report a synergetic signal amplification system comprising CRISPR-Cas12a and nicking enzyme-free strand displacement amplification (SDA) technique for accurate detection of prostate-specific antigen (PSA). The presence of PSA will initiate the nicking enzyme-free SDA process, generating amplicons that can be recognized by the CRISPR-Cas12a system. The activated CRISPR-Cas system will then mediate trans-ssDNA cleavage of neighboring linker DNA, which unlocks the gold nanoparticles (AuNPs) signal probes and gives a distance-dependent colorimetric readout. This assay could detect PSA in aqueous buffer sensitively and selectively with a limit of detection (LOD) down to 0.030 ng mL-1. Importantly, this assay was successfully applied for discriminating four blood samples from prostate cancer patients among thirteen blood samples from normal individuals/cancer patients accurately. This work will open an avenue for the development of SDA-CRISPR-AuNPs hybrid sensing systems, offering great potential for the development of non-invasive point-of-care diagnostic tools for prostate cancer.

Adaptive critic autopilot design of bank-to-turn missiles using fuzzy basis function networks.

A new adaptive critic autopilot design for bank-to-turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by online tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot.

An adaptive Hinfinity controller design for bank-to-turn missiles using ridge Gaussian neural networks.

A new autopilot design for bank-to-turn (BTT) missiles is presented. In the design of autopilot, a ridge Gaussian neural network with local learning capability and fewer tuning parameters than Gaussian neural networks is proposed to model the controlled nonlinear systems. We prove that the proposed ridge Gaussian neural network, which can be a universal approximator, equals the expansions of rotated and scaled Gaussian functions. Although ridge Gaussian neural networks can approximate the nonlinear and complex systems accurately, the small approximation errors may affect the tracking performance significantly. Therefore, by employing the Hinfinity control theory, it is easy to attenuate the effects of the approximation errors of the ridge Gaussian neural networks to a prescribed level. Computer simulation results confirm the effectiveness of the proposed ridge Gaussian neural networks-based autopilot with Hinfinity stabilization.