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Background: There is a need to develop accurate and reliable non-invasive methods to evaluate chronic kidney disease (CKD) status and assess disease progression. Given it is recognized that dysregulation in metabolic pathways occur from early CKD, there is a basis in utilizing metabolomic biomarkers to monitor CKD progression. Volatile Organic Compounds (VOCs), a form of metabolomic biomarker, are gaseous products of metabolic processes in organisms which are typically released with greater abundance in disease conditions when there is dysregulation in metabolism. How urinary VOCs reflect the abnormal metabolic profile of patients with CKD status is unknown. Our study aimed to explore this. Methods: Individuals aged 18–75 years undergoing kidney biopsy were included. Pre-biopsy urine samples were collected. All biopsy samples had an interstitial fibrosis and tubular atrophy (IFTA) grade scored by standardized assessment. Urine supernatant was extracted from residue and sampled for stir bar sorptive extraction followed by Gas chromatography–mass spectrometry (GC-MS) analysis. Post-processing of GC-MS data separated complex mixtures of VOCs based on their volatility and polarity. Mass-to-charge ratios and fragment patterns were measured for individual VOCs identification and quantification. Linear discriminant analysis (LDA) was performed to assess the ability of urinary VOCs in discriminating between IFTA 0 ('no or minimal IFTA' i.e. <10%, IFTA), IFTA 1 ('mild IFTA' i.e. 10–25% IFTA) and IFTA ≥ 2 ('moderate or severe IFTA' i.e. >25% IFTA). Linear regression analysis adjusting for age, sex, estimated glomerular filtration rate, diabetes mellitus (DM) status, and albuminuria was conducted to determine significantly regulated urinary VOCs amongst the groups. Results: 64 study participants (22 individuals IFTA 0, 15 individuals IFTA 1, 27 individuals IFTA ≥ 2) were included. There were 34 VOCs identified from GC-MS which were statistically associated with correct classification between the IFTA groups, and LDA demonstrated individuals with IFTA 0, IFTA 1 and IFTA ≥ 2 could be significantly separated by their urinary VOCs profile (p < 0.001). Multivariate linear regression analysis reported 4 VOCs significantly upregulated in the IFTA 1 compared to the IFTA 0 group, and 2 VOCs significantly upregulated in the IFTA ≥ 2 compared to the IFTA 1 group (p < 0.05). Significantly upregulated urinary VOCs belonged to one of four functional groups - aldehydes, ketones, hydrocarbons, or alcohols. Conclusions: We report novel links between urinary VOCs and tubulointerstitial histopathology. Our findings suggest the application of urinary VOCs as a metabolomic biomarker may have a useful clinical role to non-invasively assess CKD status during disease progression. [ABSTRACT FROM AUTHOR]

The intelligent sensing network is one of the key components in the construction of the Internet of Things, and the power supply technology of sensor communication nodes needs to be solved urgently. As a new field combining tribo-potential with semiconductor devices, tribotronics, based on the contact electrification (CE) effect, realizes direct interaction between the external environment and semiconductor devices by combining triboelectric nanogenerator (TENG) and field-effect transistor (FET), further expanding the application prospects of micro/nano energy. In this paper, the research progress of tribotronics is systematically reviewed. Firstly, the mechanism of the CE effect and the working principles of TENG are introduced. Secondly, the regulation theory of tribo-potential on carrier transportation in semiconductor devices and the research status of tribotronic transistors are summarized. Subsequently, the applications of tribotronics in logic circuits and memory devices, smart sensors, and artificial synapses in recent years are demonstrated. Finally, the challenges and development prospects of tribotronics in the future are projected. [ABSTRACT FROM AUTHOR]

A Lamb wave is a guided wave that propagates within plate-like structures, with its vibration mode resulting from the coupling of a longitudinal wave and a shear vertical wave, which can be applied in sensors, filters, and frequency control devices. The working principle of Lamb wave sensors relies on the excitation and propagation of this guided wave within piezoelectric material. Lamb wave sensors exhibit significant advantages in various sensing applications due to their unique wave characteristics and design flexibility. Compared to traditional surface acoustic wave (SAW) and bulk acoustic wave (BAW) sensors, Lamb wave sensors can not only achieve higher frequencies and quality factors in smaller dimensions but also exhibit superior integration and multifunctionality. In this paper, we briefly introduce Lamb wave sensors, summarizing methods for enhancing their sensitivity through optimizing electrode configurations and adjusting piezoelectric thin plate structures. Furthermore, this paper systematically explores the development of Lamb wave sensors in various sensing applications and provides new insights into their future development. [ABSTRACT FROM AUTHOR]

By employing the whale optimization algorithm's (WOA) capability to reduce the probability of being stuck in a locally optimal solution, this study proposed an improved WOA-DQN algorithm based on the Deep Q-Network algorithm (DQN). Firstly, the mathematical model of Fiber Bragg Grating (FBG) sensor placement was established to calculate the reward of DQN. Secondly, the effectiveness and applicability of WOA-DQN were validated through experiments in nine cases. It indicated that the algorithm is far superior to other methods (Noisy DQN, Prioritized DQN, DQN, WOA), especially with the learning rate of 0.001, the initial noise 0.4, the hidden layer 3–512, and the updated frequency of 20. Finally, the FBG sensors were placed at [0°, 27°, 30°, 47°, 51°, 111°, 126°, 219°, 221°, 289°] to detect the accurate deformation of the tunnel with the maximum error 8.66 mm, which is better than the traditional placement. In conclusion, the algorithm provides a theoretical foundation for sensor placement and improves monitoring accuracy. It further shows great promise for deformation monitoring in tunnels. [ABSTRACT FROM AUTHOR]

Self-assembled monolayers (SAMs) have become pivotal in achieving high-performance perovskite solar cells (PSCs) and organic solar cells (OSCs) by significantly minimizing interfacial energy losses. In this study, we propose a co-adsorb (CA) strategy employing a novel small molecule, 2-chloro-5-(trifluoromethyl)isonicotinic acid (PyCA-3F), introducing at the buried interface between 2PACz and the perovskite/organic layers. This approach effectively diminishes 2PACz’s aggregation, enhancing surface smoothness and increasing work function for the modified SAM layer, thereby providing a flattened buried interface with a favorable heterointerface for perovskite. The resultant improvements in crystallinity, minimized trap states, and augmented hole extraction and transfer capabilities have propelled power conversion efficiencies (PCEs) beyond 25% in PSCs with a p-i-n structure (certified at 24.68%). OSCs employing the CA strategy achieve remarkable PCEs of 19.51% based on PM1:PTQ10:m-BTP-PhC6 photoactive system. Notably, universal improvements have also been achieved for the other two popular OSC systems. After a 1000-hour maximal power point tracking, the encapsulated PSCs and OSCs retain approximately 90% and 80% of their initial PCEs, respectively. This work introduces a facile, rational, and effective method to enhance the performance of SAMs, realizing efficiency breakthroughs in both PSCs and OSCs with a favorable p-i-n device structure, along with improved operational stability.Self-assembled monolayers are essential for achieving high performance solar cells by minimizing interfacial energy losses. Here, authors the develop a co-adsorb strategy with a small molecule to provide a favorable heterointerface, realizing high efficiency in p-i-n perovskite and organic devices. [ABSTRACT FROM AUTHOR]