A Highly Dispersed Cobalt Electrocatalyst with Electron-Deficient Centers Induced by Boron toward Enhanced Adsorption and Electrocatalysis for Room-Temperature Sodium-Sulfur Batteries.

As vitally prospective candidates for next-generation energy storage systems, room-temperature sodium-sulfur (RT-Na/S) batteries continue to face obstacles in practical implementation due to the severe shuttle effect of sodium polysulfides and sluggish S conversion kinetics. Herein, the study proposes a novel approach involving the design of a B, N co-doped carbon nanotube loaded with highly dispersed and electron-deficient cobalt (Co@BNC) as a highly conductive host for S, aiming to enhance adsorption and catalyze redox reactions. Crucially, the pivotal roles of the carbon substrate in prompting the electrocatalytic activity of Co are elucidated. The experiments and density functional theory (DFT) calculations both demonstrate that after B doping, stronger chemical adsorption toward polysulfides (NaPSs), lower polarization, faster S conversion kinetics, and more complete S transformation are achieved. Therefore, the as-assembled RT-Na/S batteries with S/Co@BNC deliver a high reversible capacity of 626 mAh g-1 over 100 cycles at 0.1 C and excellent durability (416 mAh g-1 over 600 cycles at 0.5 C). Even at 2 C, the capacity retention remains at 61.8%, exhibiting an outstanding rate performance. This work offers a systematic way to develop a novel Co electrocatalyst for RT-Na/S batteries, which can also be effectively applied to other transition metallic electrocatalysts.

cGAS-STING pathway mediates activation of dendritic cell sensing of immunogenic tumors.

Type I interferons (IFN-I) play pivotal roles in tumor therapy for three decades, underscoring the critical importance of maintaining the integrity of the IFN-1 signaling pathway in radiotherapy, chemotherapy, targeted therapy, and immunotherapy. However, the specific mechanism by which IFN-I contributes to these therapies, particularly in terms of activating dendritic cells (DCs), remains unclear. Based on recent studies, aberrant DNA in the cytoplasm activates the cyclic GMP-AMP synthase (cGAS)- stimulator of interferon genes (STING) signaling pathway, which in turn produces IFN-I, which is essential for antiviral and anticancer immunity. Notably, STING can also enhance anticancer immunity by promoting autophagy, inflammation, and glycolysis in an IFN-I-independent manner. These research advancements contribute to our comprehension of the distinctions between IFN-I drugs and STING agonists in the context of oncology therapy and shed light on the challenges involved in developing STING agonist drugs. Thus, we aimed to summarize the novel mechanisms underlying cGAS-STING-IFN-I signal activation in DC-mediated antigen presentation and its role in the cancer immune cycle in this review.

1-Pyrroline-5-carboxylate inhibit T cell glycolysis in prostate cancer microenvironment by SHP1/PKM2/LDHB axis.

BACKGROUND: Our previous studies demonstrated that 1-Pyrroline-5-carboxylate (P5C) released by prostate cancer cells inhibits T cell proliferation and function by increasing SHP1 expression. We designed this study to further explore the influence of P5C on T cell metabolism, and produced an antibody for targeting P5C to restore the functions of T cells. METHOD: We co-immunoprecipated SHP1 from T cells and analyzed the proteins that were bound to it using liquid chromatography mass spectrometry (LC/MS-MS). The influence of P5C on T cells metabolism was also detected by LC/MS-MS. Seahorse XF96 analyzer was further used to identify the effect of P5C on T cells glycolysis. We subsequently designed and produced an antibody for targeting P5C by monoclonal technique and verified its effectiveness to restore the function of T cells in vitro and in vivo. RESULT: PKM2 and LDHB bind SHP1 in T cells, and P5C could increase the levels of p-PKM2 while having no effect on the levels of PKM2 and LDHB. We further found that P5C influences T cell energy metabolism and carbohydrate metabolism. P5C also inhibits the activity of PKM2 and decreases the content of intracellular lactic acid while increasing the activity of LDH. Using seahorse XF96 analyzer, we confirmed that P5C remarkably inhibits glycolysis in T cells. We produced an antibody for targeting P5C by monoclonal technique and verified that the antibody could oppose the influence of P5C to restore the process of glycolysis and function in T cells. Meanwhile, the antibody also inhibits the growth of prostate tumors in an animal model. CONCLUSION: Our study revealed that P5C inhibits the process of glycolysis in T cells by targeting SHP1/PKM2/LDHB complexes. Moreover, it is important that the antibody for targeting P5C could restore the function of T cells and inhibit the growth of prostate tumors.

The impacts of carbon emissions trading scheme on green finance: evidence from China.

China enacted and implemented a carbon emissions trading pilot policy in 2011, and whether this carbon emissions trading scheme (ETS) can promote the development of green finance is crucial to realizing a win-win situation for both environmental and economic performance. Based on the panel data of 30 provinces in China from 2007 to 2019, this study constructs a multi-period double-difference model (DID) to explore the impact of carbon ETS on the development of green finance and uses the spatial Durbin model (SDM) to test whether there is a spatial spillover effect of the carbon ETS on the development of green finance. The results show that (a) the implementation of carbon ETS significantly promotes the development of green finance, and this conclusion still holds through a series of robustness tests; (b) the promotion effect of the carbon ETS on the development of green finance is more significant in eastern and western provinces, non-resource-based provinces, and provinces with a high level of openness to the outside world; (c) industrial structural upgrading and green innovation play pivotal roles in achieving the desired outcomes of carbon ETS; (d) carbon ETS have spatial spillover effects on the development of green finance, with the indirect effects being more significant than the direct effects. The findings of this study can serve as a valuable reference for expediting the establishment of a unified national carbon market and the development of a robust green financial system. This holds immense significance in effectively implementing the "dual-carbon" strategy.

Theaflavin pretreatment ameliorates renal ischemia/reperfusion injury by attenuating apoptosis and oxidative stress in vivo and in vitro.

Oxidative stress-induced apoptosis is an important pathological process in renal ischemia/reperfusion injury (RIRI). Theaflavin (TF) is the main active pigment and polyphenol in black tea. It has been widely reported because of its biological activity that can reduce oxidative stress and protect against many diseases. Here, we explored the role of theaflavin in the pathological process of RIRI. In the present study, the RIRI model of 45 min ischemia and 24 h reperfusion was established in C57BL/6 J male mice, and theaflavin was used as an intervention. Compared with the RIRI group, the renal filtration function, renal tissue damage and antioxidant capacity of the theaflavin intervention group were significantly improved, while the level of apoptosis was reduced. TCMK-1 cells were incubated under hypoxia for 48 h and then reoxygenated for 6 h to simulate RIRI in vitro. The application of theaflavin significantly promoted the translocation of p53 from cytoplasm to nucleus, upregulated the expression of glutathione peroxidase 1 (GPx-1) in cells, and inhibited oxidative stress damage and apoptosis. Transfection with p53 siRNA can partially inhibit the effect of theaflavin. Thus, theaflavin exerted a protective effect against RIRI by inhibiting apoptosis and oxidative stress via regulating the p53/GPx-1 pathway. We conclude that theaflavin has the potential to become a candidate drug for the prevention and treatment of RIRI.

Severe photochemical pollution was found in large petrochemical complexes: A typical case study in North China.

Large petrochemical complex (PC) widely exists in both developing and developed countries, and is expected to have a special photochemical pollution in local scale due to huge VOCs emissions. Here, a typical large-scale PC in North China was selected as the study case, to explore the character, formation and influence of local photochemical pollution regarding PCs based on an improved 0-D chemical model. In the study PC, VOCs-rich character was apparent with THCs level of 90.8 ± 28.0 ppb and THCs/NOx ratio of ∼26.2 mol/mol. Severe O3 pollution was found in warm months with monthly mean MDA1O3 of 67.3-96.0 ppb. Model simulations showed the heavy O3 pollution in this PC was attributed to high precursors rather than to unfavorable meteorology, and was more sensitive to NOx (with response of 1.42 g/g) than to THCs (with response of 0.12 g/g). The photochemical pollution formation potential of the emission plumes of this PC was very enormous, with production rate of 19.6 ppb h-1 for O3, 2.9 ppb h-1 for HCHO and 1.1 ppb h-1 for CH3CHO on daytime average, 1-5 greater than in normal urban areas. The higher production rates happened in morning hours, which explained the earlier peak time of observed O3 in PCs. And about 70% of photochemical pollution (represented by O3) would be transported to surroundings, leading to the significant photochemical-pollution hazard to the vicinity of PCs.

Process-specific volatile organic compounds emission characteristics, environmental impact and health risk assessments of the petrochemical industry in the Beijing-Tianjin-Hebei region.

Volatile organic compounds (VOCs) concentration, source profiles, O3 and SOA formation, and health risks were investigated in the petrochemical industry in Beijing-Tianjin-Hebei. The results showed that total VOCs concentrations were 547.1-1956.5 µg·m-3, and alkanes were the most abundant group in all processes (31.4%-54.6%), followed by alkenes (20.6%-29.2%) and aromatics (10.1%-25.1%). Moreover, ethylene (11.3%), iso-pentane (7.1%), n-hexane (5.1%), benzene (4.9%) and 2,2-dimethylbutae (4.8%) were identified as the top five species released for the whole petrochemical industry. The coefficient of divergence between the source profiles from different processes was 0.49-0.73, indicating that most source profiles must not be similar. Moreover, because of the different raw materials and technologies used, the source profiles in this study are significantly different from those of other regions. The ozone and secondary organic aerosol formation potentials (OFPs and SOAPs) were evaluated, suggesting that ethylene, propylene, 1-butene, m,p-xylene, and 1,3-butadiene should be preferentially controlled to reduce OFPs. That benzene, toluene, ethylbenzene, m,p-xylene, isopropylbenzene, o-ethyltoluene, and 1,3,5-trimethylbenzene should be priority control compounds for SOAPs. Additionally, the total hazard ratio for non-cancer risk ranged from 0.9 to 7.7, and only living area was unlikely to be related to adverse health effects. Cancer risks associated with organic chemicals, rubber synthesis, oil refining, and wastewater collection and treatment have definite risks, whereas other processes have probable risks. This study provides a scientific basis for VOCs emission control and management and guides human health in the petrochemical industry.

Insoluble/soluble fraction ratio determines effects of dietary fiber on gut microbiota and serum metabolites in healthy mice.

Both soluble dietary fiber (SDF) and insoluble dietary fiber (IDF) play pivotal roles in maintaining gut microbiota homeostasis; whether the effects of the different ratios of IDF and SDF are consistent remains unclear. Consequently, we selected SDFs and IDFs from six representative foods (apple, celery, kale, black fungus, oats, and soybeans) and formulated nine dietary fiber recipes composed of IDF and SDF with a ratio from 1 : 9 to 9 : 1 (NDFR) to compare their impact on microbial effects with healthy mice. We discovered that NDFR treatment decreased the abundance of Proteobacteria and the ratio of Firmicutes/Bacteroidetes at the phylum level. The α diversity and relative richness of Parabacteroides and Prevotella at the genus level showed an upward trend along with the ratio of IDF increasing, while the relative abundance of Akkermansia at the genus level and the production of acetic acid and propionic acid exhibited an increased trend along with the ratio of SDF increasing. The relative abundance of Parabacteroides and Prevotella in the I9S1DF group (the ratio of IDF and SDF was 9 : 1) was 1.72 times and 5.92 times higher than that in the I1S9DF group (the ratio of IDF and SDF was 1 : 9), respectively. The relative abundance of Akkermansia in the I1S9DF group was 17.18 times higher than that in the I9S1DF group. Moreover, a high ratio of SDF (SDF reaches 60% or more) enriched the glycerophospholipid metabolism pathway; however, a high ratio of IDF (IDF reaches 80% or more) regulated the tricarboxylic acid cycle. These findings are helpful in the development of dietary fiber supplements based on gut microbiota and metabolites.

Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets.

The training and inference of Graph Neural Networks (GNNs) are costly when scaling up to large-scale graphs. Graph Lottery Ticket (GLT) has presented the first attempt to accelerate GNN inference on large-scale graphs by jointly pruning the graph structure and the model weights. Though promising, GLT encounters robustness and generalization issues when deployed in real-world scenarios, which are also long-standing and critical problems in deep learning ideology. In real-world scenarios, the distribution of unseen test data is typically diverse. We attribute the failures on out-of-distribution (OOD) data to the incapability of discerning causal patterns, which remain stable amidst distribution shifts. In traditional spase graph learning, the model performance deteriorates dramatically as the graph/network sparsity exceeds a certain high level. Worse still, the pruned GNNs are hard to generalize to unseen graph data due to limited training set at hand. To tackle these issues, we propose the Resilient Graph Lottery Ticket (RGLT) to find more robust and generalizable GLT in GNNs. Concretely, we reactivate a fraction of weights/edges by instantaneous gradient information at each pruning point. After sufficient pruning, we conduct environmental interventions to extrapolate potential test distribution. Finally, we perform last several rounds of model averages to further improve generalization. We provide multiple examples and theoretical analyses that underpin the universality and reliability of our proposal. Further, RGLT has been experimentally verified across various independent identically distributed (IID) and out-of-distribution (OOD) graph benchmarks. The source code for this work is available at https://github.com/Lyccl/RGLT for PyTorch implementation.

Electronic, optoelectronic, and thermoelectric properties of single molecular devices of 2D fullerenes with zigzag graphene nanoribbons as electrodes.

Zigzag graphene nanoribbons (GNRs) were selected as electrodes, and the electron transport properties, optical properties, and thermoelectric properties of four fullerene cluster-based molecular devices were studied. By applying different voltages on them, their I-V curves exhibited the multiple negative differential resistance (NDR) effect and the platform effect, which are described in more detail using their density of states (DOS) and projected density of states (PDOS). The results of rotating two types of (C60)4 molecules verify that both the NDR and the platform effects are essential characteristics of them. Furthermore, an examination is conducted on the photocurrent of the devices at the point of maximum light absorption, revealing that α-(C60)4 connected by a [2+2] ring addition bond in the transport direction exhibits superior optical properties and works better as a photoelectric device than ß-(C60)4 connected via a C-C single bond in the transport direction. Finally, the thermoelectric current of the devices was studied. Our results contribute to the understanding and the potential application of single devices based on fullerene clusters in the area of molecular electronics.

Insights into quantitative evaluation technology of PM2.5 transport at multi-perspective and multi-spatial and temporal scales in the north China plain.

Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi-perspective and multi-scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter-urban and outer-regional transport contributed 44.5%-64.6%, 15.2%-27.9% and 18.0%-28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest-northeast, northeast-southwest, and southeast-northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%-24.5% in Beijing, Tianjin and Shijiazhuang, with inter-urban and outer-regional contribution of 29.8%-32.1% and 18.5%-23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1-2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.

DeeperGCN: Training Deeper GCNs With Generalized Aggregation Functions.

Graph Neural Networks (GNNs) have been drawing significant attention to representation learning on graphs. Recent works developed frameworks to train very deep GNNs and showed impressive results in tasks like point cloud learning and protein interaction prediction. In this work, we study the performance of such deep models in large-scale graphs. In particular, we look at the effect of adequately choosing an aggregation function on deep models. We find that GNNs are very sensitive to the choice of aggregation functions (e.g. mean, max, and sum) when applied to different datasets. We systematically study and propose to alleviate this issue by introducing a novel class of aggregation functions named Generalized Aggregation Functions. The proposed functions extend beyond commonly used aggregation functions to a wide range of new permutation-invariant functions. Generalized Aggregation Functions are fully differentiable, where their parameters can be learned in an end-to-end fashion to yield a suitable aggregation function for each task. We show that equipped with the proposed aggregation functions, deep residual GNNs outperform state-of-the-art in several benchmarks from Open Graph Benchmark (OGB) across tasks and domains.

System analysis identifies UBE2C as a novel oncogene target for adrenocortical carcinoma.

Ubiquitin Conjugating Enzyme 2C (UBE2C) is an emerging target gene for tumor progression. However, the tumorigenic effect and mechanism of UBE2C in adrenocortical carcinoma (ACC) remains unclear. Systematic investigation of the tumorigenic effect of UBE2C may help in understanding its prognostic value in adrenocortical carcinoma. First, we exploited the intersection on DFS-related genes, OS-related genes, highly expressed genes in adrenocortical carcinoma as well as differentially expressed genes (DEGs) between tumor and normal, and then obtained 20 candidate genes. UBE2C was identified to be the most significant DEG between tumor and normal. It is confirmed that high expression of UBE2C was strongly associated with poor prognosis in patients with ACC by analyzing RNA-seq data of ACC obtained from the Cancer Genome Atlas (TCGA) database implemented by ACLBI Web-based Tools. UBE2C expression could also promote m6A modification and stemness in ACC. We found that UBE2C expression is positively associated with the expression of CDC20, CDK1, and CCNA2 using ACLBI Web-based Tools, indicated the hyperactive cell cycle progression present in ACC with high UBE2C expression. In addition, UBE2C knockdown could significantly inhibit the proliferation, migration, invasion, EMT of adrenocortical carcinoma cells as well as the cell cycle progression in vitro. Notably, pan-cancer analysis also identified UBE2C as an oncogene in various tumors. Taken together, UBE2C was strongly associated with poor prognosis of patients with ACC by promoting cell cycle progression and EMT. This study provides a new theoretical basis for the development of UBE2C as a molecular target for the treatment of ACC.

P-doped porous carbon from camellia shell for high-performance room temperature sodium-sulfur batteries.

Room-temperature sodium-sulfur batteries are still hampered by severe shuttle effects and sluggish kinetics. Most of the sulfur hosts require high cost and complex synthesis process. Herein, a facile method is proposed to prepare a phosphorous doped porous carbon (CSBP) with abundant defect sites from camellia shell by oxidation pretreatment combined with H3PO4activation. The pretreatment can introduce pores and adjust the structure of biochar precursor, which facilitates the further activation of H3PO4and effectively avoids the occurrence of large agglomeration. Profiting from the synergistic effects of physical confinement and doping effect, the prepared CSBP/S cathode delivers a high reversible capacity of 804 mAh g-1after 100 cycles at 0.1 C and still maintains an outstanding capacity of 458 mAh g-1after 500 cycles at 0.5 C (1 C = 1675 mA g-1). This work provides new insights into the rational design of the microstructures of carbon hosts for high-performance room temperature sodium-sulfur batteries.

Room-temperature assembled 3D macro-porous Ti3C2Tx/RGO hybrid hydrogel and the application as the self-standing electrode for sodium-ion storage.

Assembling two-dimensional (2D) MXene nanosheets into monolithic three-dimensional (3D) structures is an efficient pathway to transfer the nanoscale properties to practical applications. Nevertheless, the majority of the preparation schemes described in the literature are carried out at relatively high temperatures, which inevitably leads to the notorious high-temperature oxidation issue of MXenes. Preparing MXene-based hydrogels at lower temperatures or even room temperature is of great research importance. In this study, we report a novel and efficient room-temperature gelation method for fabricating 3D macro-porous Ti3C2Tx MXene/reduced graphene oxide (RGO) hybrid hydrogels, using anhydrous sodium sulfide (Na2S) as the primary reducing agent and l-cysteine as the auxiliary crosslinker. This room-temperature preparation technique successfully prevents the oxidation issue of MXenes and generates porous aerogels with excellent structural robustness after freeze-drying. As the self-standing anode for sodium-ion storage, the optimized 3D Ti3C2Tx MXene/RGO electrode possesses a specific capacity of 152 mAh/g at 0.1 A/g and good cycling stability with no significant capacity degradation after 500 cycles, which is significantly higher than that of the vacuum-filtered MXene film. This work demonstrates a straightforward room-temperature gelation method for constructing 3D MXene-based hydrogels to avoid the oxidation of MXenes, and casts new insight on the mechanism of the graphene oxide (GO)-assisted gelation.

Overexpression of RACGAP1 by E2F1 Promotes Neuroendocrine Differentiation of Prostate Cancer by Stabilizing EZH2 Expression.

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer. It is characterized by the loss of androgen receptor (AR) signaling in neuroendocrine transdifferentiation, and finally, resistance to AR-targeted therapy. With the application of a new generation of potent AR inhibitors, the incidence of NEPC is gradually increasing. The molecular mechanism of neuroendocrine differentiation (NED) after androgen deprivation therapy (ADT) remains largely unclear. In this study, using NEPC-related genome sequencing database analyses, we screened RACGAP1, a common differentially expressed gene. We investigated RACGAP1 expression in clinical prostate cancer specimens by IHC. Regulated pathways were examined by Western blotting, qRT-PCR, luciferase reporter, chromatin immunoprecipitation, and immunoprecipitation assays. The corresponding function of RACGAP1 in prostate cancer was analyzed by CCK-8 and Transwell assays. The changes of neuroendocrine markers and AR expression in C4-2-R and C4-2B-R cells were detected in vitro. We confirmed that RACGAP1 contributed to NE transdifferentiation of prostate cancer. Patients with high tumor RACGAP1 expression had shorter relapse-free survival time. The expression of RACGAP1 was induced by E2F1. RACGAP1 promoted neuroendocrine transdifferentiation of prostate cancer by stabilizing EZH2 expression in the ubiquitin-proteasome pathway. Moreover, overexpression of RACGAP1 promoted enzalutamide resistance of castration-resistant prostate cancer (CRPC) cells. Our results showed that the upregulation of RACGAP1 by E2F1 increased EZH2 expression, which drove NEPC progression. This study explored the molecular mechanism of NED and may provide novel methods and ideas for targeted therapy of NEPC.

Self-assembled supramolecular immunomagnetic nanoparticles through π-π stacking strategy for the enrichment of circulating tumor cells.

Owing to their high-specific binding toward targets as well as fast and convenient separation operations, immunomagnetic beads (IMBs) are widely used in the capture and detection of circulating tumor cells (CTCs). To construct the IMBs, surface modifications are generally performed to functionalize the magnetic cores (e.g. Fe3O4 nanoparticles), and the employed surface modification strategies normally influence the structure and functions of the prepared IMBs in return. Different from the existing work, we proposed the use of supramolecular layer-by-layer (LBL) self-assembly strategy to construct the IMBs. In general, owing to the π-π stacking interactions, the polydopamine, graphene oxide and 'molecular glue' γ-oxo-1-pyrenebutyric acid were self-assembled on Fe3O4 nanoparticles sequentially, thereby accomplishing the integration of different functional components onto magnetic cores to prepare the self-assembled supramolecular immunomagnetic beads (ASIMBs). The ASIMBs showed high sensitivity, specificity and good biocompatibility to the model CTCs and low nonspecific adsorption to the negative cells (∼93% for MCF-7 cells and 17% for Jurkat cells). Meanwhile, ASIMBs possessed a remarkable potential to screen the rare MCF-7 cells out of large amounts of interfering Jurkat cells with the capture efficiency of 75-100% or out of mouse whole blood with the capture efficiency of 20-90%. The captured cells can be further recultured directly without any more treatment, which showed huge applicability of the ASIMBs for in vitro detection in clinical practices.

Knowledge-Aware Global Reasoning for Situation Recognition.

The task of situation recognition aims to solve the visual reasoning problem with the ability to predict the activity happening (salient action) in an image and the nouns of all associated semantic roles playing in the activity. This poses severe challenges due to long-tailed data distributions and local class ambiguities. Prior works only propagate the local noun-level features on one single image without utilizing global information. We propose a Knowledge-aware Global Reasoning (KGR) framework to endow neural networks with the capability of adaptive global reasoning over nouns by exploiting diverse statistical knowledge. Our KGR is a local-global architecture, which consists of a local encoder to generate noun features using local relations and a global encoder to enhance the noun features via global reasoning supervised by an external global knowledge pool. The global knowledge pool is created by counting the pairwise relationships of nouns in the dataset. In this paper, we design an action-guided pairwise knowledge as the global knowledge pool based on the characteristic of the situation recognition task. Extensive experiments have shown that our KGR not only achieves state-of-the-art results on a large-scale situation recognition benchmark, but also effectively solves the long-tailed problem of noun classification by our global knowledge.

Chemical characterization of volatile organic compounds (VOCs) emitted from multiple cooking cuisines and purification efficiency assessments.

Cooking process can produce abundant volatile organic compounds (VOCs), which are harmful to environment and human health. Therefore, we conducted a comprehensive analysis in which VOCs emissions from multiple cuisines have been sampled based on the simulation and acquisition platform, involving concentration characteristics, ozone formation potential (OFP) and purification efficiency assessments. VOCs emissions varied from 1828.5 to 14,355.1 µg/m3, with the maximum and minimum values from Barbecue and Family cuisine, respectively. Alkanes and alcohol had higher contributions to VOCs from Sichuan and Hunan cuisine (64.1%), Family cuisine (66.3%), Shandong cuisine (69.1%) and Cantonese cuisine (69.8%), with the dominant VOCs species of ethanol, isobutane and n-butane. In comparison, alcohols (79.5%) were abundant for Huaiyang cuisine, while alkanes (19.7%), alkenes (35.9%) and haloalkanes (22.9%) accounted for higher proportions from Barbecue. Specially, carbon tetrachloride, n-hexylene and 1-butene were the most abundant VOCs species for Barbecue, ranging from 8.8% to 14.6%. The highest OFP occurred in Barbecue. The sensitive species of OFP for Huaiyang cuisine were alcohols, while other cuisines were alkenes. Purification efficiency assessments shed light on the removal differences of individual and synergistic control technologies. VOCs emissions exhibited a strong dependence on the photocatalytic oxidation, with the removal efficiencies of 29.0%-54.4%. However, the high voltage electrostatic, wet purification and mechanical separation techniques played a mediocre or even counterproductive role in the VOCs reduction, meanwhile collaborative control technologies could not significantly improve the removal efficiency. Our results identified more effective control technologies, which were conductive to alleviating air pollution from cooking emissions.

Effects of grape seed-derived proanthocyanidin B2 pretreatment on oxidative stress, endoplasmic reticulum stress and apoptosis of renal tubular epithelial cells in renal ischemia-reperfusion injury model of mice.

PURPOSE: To investigate the effect of grape seed-derived proanthocyanidin B2 (GSPB2) pretreatment on acute renal ischemia-reperfusion injury model of mice. METHODS: 50 mice were divided into 5 groups: Sham group: mice were treated with right nephrectomy. GSPB2 group: GSPB2 was injected intraperitoneally 45 min before right nephrectomy. IRI group: right kidney was resected and the left renal arteriovenous vessel was blocked for 45 min. GSPB2 + IRI group: GSPB2 was intraperitoneally injected 45 min before IRI established. GSPB2 + BRU + IRI group: GSPB2 and brusatol (BRU) were injected intraperitoneally 45 min before IRI established. Creatinine and urea nitrogen of mice were detected, and the kidney morphology and pathological changes of each group were detected by HE staining, PAS staining and transmission electron microscopy. Expressions of Nrf2, HO-1, GRP78, CHOP, and cleaved-caspase3 were detected by immunofluorescence staining and western blotting. RESULTS: Morphology and mitochondrial damages of kidney in GSPB2 + IRI group were significantly alleviated than those in IRI group. Expression levels of Nrf2 and HO-1 were significantly higher in GSPB2 + IRI group than those in IRI group. Expression levels of GRP78, CHOP and cleaved-caspase3 were significantly lower in GSPB2 + IRI group than those in IRI group. However, compared to GSPB2 + IRI group, protective effects of GSPB2 pretreatment were weakened in GSPB2 + BRU + IRI group. CONCLUSIONS: GSPB2 pretreatment could alleviate oxidative stress damage and reduce apoptosis of renal tubular epithelial cells, which might be related to activating the antioxidant system, up-regulating the expression of Nrf2 and HO-1, inhibiting the expressions of GRP78, CHOP and cleaved-caspase3. However, the protective effect could be reversed by brusatol.