Controllable CO2 Reduction or Hydrocarbon Oxidation Driven by Entire Solar via Silver Quantum Dots Direct Photocatalysis.

The current solar-chemical-industry based on semiconductor photocatalyst is impractical. Metal catalysts are extensively employed in thermal- and electro-catalysis industries, but unsuitable for direct-driven photocatalysis. Herein, silver quantum dots (Ag-QDs) are synthesized on support via an in situ photoreduction method, and in situ photocatalysis temperature programmed dynamics chemisorption desorption analyses are designed to demonstrate that Ag-QDs should be the actual photocatalytic sites. The surface plasmon resonance of Ag-QDs could harvests entire visible solar, and the plasmon-driven charge-transfer exhibits opposite directions at the interface when supports are different. Consequently, Ag-QDs could be alternatively regulated as oxidation or reduction active centers. Furthermore, Ag-QDs excite electron tunneling transfer with adsorbate, which does not generate high-energy free-radical intermediates. As a result, the efficiencies of hydrocarbon photooxidation and CO2 photoreduction are improved in several orders of magnitude. Evidently, the Ag-QDs direct photocatalytic technology greatly promotes solar-chemical-industry applications.

Prototypical Graph Contrastive Learning.

Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. However, in practice, precise graph annotations are generally very expensive and time-consuming. To address this issue, graph contrastive learning constructs an instance discrimination task, which pulls together positive pairs (augmentation pairs of the same graph) and pushes away negative pairs (augmentation pairs of different graphs) for unsupervised representation learning. However, since for a query, its negatives are uniformly sampled from all graphs, existing methods suffer from the critical sampling bias issue, i.e., the negatives likely having the same semantic structure with the query, leading to performance degradation. To mitigate this sampling bias issue, in this article, we propose a prototypical graph contrastive learning (PGCL) approach. Specifically, PGCL models the underlying semantic structure of the graph data via clustering semantically similar graphs into the same group and simultaneously encourages the clustering consistency for different augmentations of the same graph. Then, given a query, it performs negative sampling via drawing the graphs from those clusters that differ from the cluster of query, which ensures the semantic difference between query and its negative samples. Moreover, for a query, PGCL further reweights its negative samples based on the distance between their prototypes (cluster centroids) and the query prototype such that those negatives having moderate prototype distance enjoy relatively large weights. This reweighting strategy is proven to be more effective than uniform sampling. Experimental results on various graph benchmarks testify the advantages of our PGCL over state-of-the-art methods. The code is publicly available at https://github.com/ha-lins/PGCL.

Relationship between Atmospheric PM-Bound Reactive Oxygen Species, Their Half-Lives, and Regulated Pollutants: Investigation and Preliminary Model.

The concentration, nature, and persistence of particulate matter (PM)-bound reactive oxygen species (ROS) are of significant interest in understanding how atmospheric pollution affects health. However, the inherent difficulties in their measurement, particularly regarding the so-called "short-lived" ROS, have limited our understanding of their persistence and concentrations in the atmosphere. This paper aims to address this limitation through the analysis of PM-bound ROS measurements from the Particle Into Nitroxide Quencher (PINQ) system at an atmospheric monitoring site in the city of Heshan, Guangdong Province, China. The measured daily average and standard deviation for the measurement period was 0.050 ± 0.017 nmol·m-3. The averaged measured concentration of ROS per mass of PM and standard deviation was 0.0012 ± nmol·mg. The dataset was also correlated with standard pollutants, and a simplified model was constructed to separate the contributions of short-lived (t1/2 = 5 min) and long-lived (t1/2 ∼ infinity) ROS to total concentration using ozone, carbon monoxide, and PM mass. This showed that the short-lived ROS contribute an average of 33% of the daily PM-bound ROS burden over the measurement period, up to 52% of daily average on elevated days, and up to 71% for hourly averages. These results highlight the need for accurate measurements of short-lived ROS and provide the starting point for a general model to predict PM-bound ROS concentrations using widely available standard pollutants for future epidemiological research.

tert-Butylhydroperoxide induces apoptosis in RAW264.7 macrophages via a mitochondria-mediated signaling pathway.

Macrophage apoptosis occurs throughout all stages of atherosclerosis, mainly induced by oxidized low density lipoproteins (Ox LDLs), leading to the formation of necrotic cores. Nevertheless, the mechanism of macrophage apoptosis induced by Ox LDLs is not yet clearly understood. In this study, a model of RAW264.7 macrophages exposed to an Ox LDL analogue, i.e. tert-butylhydroperoxide (t-BHP), was established. We thoroughly evaluated the viability and apoptosis of RAW264.7 cells treated with t-BHP at different time intervals. t-BHP treatment decreases the viability of RAW264.7 cells in a dose- and time-dependent manner (IC50: 400 µM) and also induces a loss of the mitochondrial membrane potential (MMP) in RAW264.7 cells. Moreover, the activation of Bid, up-regulation of Bcl-2, and down-regulation of Bax, as well as the proteolysis of pro-caspase 3 and cleavage of PARP, were all also observed in t-BHP treated RAW264.7 cells. Finally, we concluded that t-BHP induces the apoptosis of macrophages via a mitochondria-mediated signaling pathway.

A photostable fluorescent probe for long-time imagining of lysosome in cell and nematode.

Lysosome fluorescent imaging has been widely used in the field of biological staining and diagnostics, which plays a key role in understanding intracellular metabolism and various physiological processes. However, for most currently used small-molecule lysotrackers, the photostability is often unsatisfactory when used for long-term and real-time visualization of lysosomal dynamics. Herein, we reported a new lysosome-targetable photostable fluorescent probe (i.e. MPL-NPA), and results showed that MPL-NAP possesses superior photostability, appreciable tolerance to pH change, low cytotoxicity and high lysosome targeting ability. These findings confirm that MPL-NAP is a well-suited imaging agent for targeting lysosome and enables long-term and real-time monitor of lysosome morphological changes under physiological processes.