Intercomparison of measured and modelled photochemical ozone production rates: Suggestion of chemistry hypothesis regarding unmeasured VOCs.

Ozone (O3) pollution is a severe environmental problem in China. The incomplete understanding of atmospheric photochemical reaction mechanisms prevents us from accurately understanding the chemistry of O3 production. Here, we used an improved dual-channel reaction chamber technique to measure net photochemical O3 production rate (P(O3)net) directly in Dongguan, a typical industrial city in China. The maximum P(O3)net was 46.3 ppbv h-1 during the observation period, which is at a relatively high level compared to previous observations under different environment worldwide. We employed an observation-based box model coupled with the state-of-the-art atmospheric chemical mechanism (MCM v3.3.1) to investigate the chemistry of O3 production. Under the base scenario, the modelling underestimates P(O3)net by ~30 %. Additionally considering HO2 uptake by ambient aerosols, inorganic deposition, and Cl chemistry only caused a small change (< 13 %) in the simulation of P(O3)net. Further analysis indicates that unmeasured reactive volatile organic compounds (VOCs), such as oxygenated VOCs and branched alkenes are potential contributors to the underestimation of P(O3)net. This study underscores the underestimation of P(O3)net in conventional atmospheric modelling setups, providing a crucial scientific foundation for further investigation aimed at promoting our understanding of photochemical O3 formation.

Predicting the Prognosis of Bladder Cancer Patients Through Integrated Multi-omics Exploration of Chemotherapy-Related Hypoxia Genes.

Bladder cancer is a prevalent malignancy with high mortality rates worldwide. Hypoxia is a critical factor in the development and progression of cancers. However, whether and how hypoxia-related genes (HRGs) could affect the development and the chemotherapy response of bladder cancer is still largely unexplored. This study comprehensively explored the complex molecular landscape associated with hypoxia in bladder cancer by analyzing 260 hypoxia genes based on transcriptomic and genomic data in 411 samples. Employing the 109 dysregulated hypoxia genes for consensus clustering, we delineated two distinct bladder cancer clusters characterized by disparate survival outcomes and distinct oncogenic roles. We defined a HPscore that was correlated with a variety of clinical features, including TNM stages and pathologic grades. Tumor immune landscape analysis identified three immune clusters and close interactions between hypoxia genes and the various immune cells. Utilizing a network-based method, we defined 129 HRGs exerting influence on apoptotic processes and critical signaling pathways in cancer. Further analysis of chemotherapy drug sensitivity identified potential drug-target HRGs. We developed a Risk Score model that was related to the overall survival of bladder cancer patients based on doxorubicin-target HRGs: ACTG2, MYC, PDGFRB, DHRS2, and KLRD1. This study not only enhanced our understanding of bladder cancer at the molecular level but also provided promising avenues for the development of targeted therapies, representing a significant step toward the identification of effective treatments and addressing the urgent need for advancements in bladder cancer management.

A Zero-Voltage-Writing Artificial Nervous System Based on Biosensor Integrated on Ferroelectric Tunnel Junction.

The artificial nervous system proves the great potential for the emulation of complex neural signal transduction. However, a more bionic system design for bio-signal transduction still lags behind that of physical signals, and relies on additional external sources. Here, this work presents a zero-voltage-writing artificial nervous system (ZANS) that integrates a bio-source-sensing device (BSSD) for ion-based sensing and power generation with a hafnium-zirconium oxide-ferroelectric tunnel junction (HZO-FTJ) for the continuously adjustable resistance state. The BSSD can use ion bio-source as both perception and energy source, and then output voltage signals varied with the change of ion concentrations to the HZO-FTJ, which completes the zero-voltage-writing neuromorphic bio-signal modulation. In view of in/ex vivo biocompatibility, this work shows the precise muscle control of a rabbit leg by integrating the ZANS with a flexible nerve stimulation electrode. The independence on external source enhances the application potential of ZANS in robotics and prosthetics.

Interindividual- and blood-correlated sweat phenylalanine multimodal analytical biochips for tracking exercise metabolism.

In situ monitoring of endogenous amino acid loss through sweat can provide physiological insights into health and metabolism. However, existing amino acid biosensors are unable to quantitatively assess metabolic status during exercise and are rarely used to establish blood-sweat correlations because they only detect a single concentration indicator and disregard sweat rate. Here, we present a wearable multimodal biochip integrated with advanced electrochemical electrodes and multipurpose microfluidic channels that enables simultaneous quantification of multiple sweat indicators, including phenylalanine and chloride, as well as sweat rate. This combined measurement approach reveals a negative correlation between sweat phenylalanine levels and sweat rates among individuals, which further enables identification of individuals at high metabolic risk. By tracking phenylalanine fluctuations induced by protein intake during exercise and normalizing the concentration indicator by sweat rates to reduce interindividual variability, we demonstrate a reliable method to correlate and analyze sweat-blood phenylalanine levels for personal health monitoring.