Explore the vast range of titles available.

The proposed methodology presents a comprehensive analysis of soft sensor modeling techniques for air ozone prediction. We compare the performance of three different modeling techniques: LR (linear regression), NN (neural networks), and RFR (random forest regression). Additionally, we evaluate the impact of different variable sets on prediction performance. Our findings indicate that neural network models, particularly the RNN (recurrent neural networks), outperform the other modeling techniques in terms of prediction accuracy. The proposed methodology evaluates the impact of different variable sets on prediction performance, finding that variable set E demonstrates exceptional performance and achieves the highest average prediction accuracy among various software sensor models. In comparing variable set E and A, B, C, D, it is observed that the inclusion of an additional input feature, PM 10 , in the latter sets does not improve overall performance, potentially due to multicollinearity between PM 10 and PM 2.5 variables. The proposed methodology provides valuable insights into soft sensor modeling for air ozone prediction.Among the 72 sensors, sensor NN R[Y]C outperforms all other evaluated sensors, demonstrating exceptional predictive performance with an impressive R 2 of 0.8902, low RMSE of 24.91, and remarkable MAE of 19.16. With a prediction accuracy of 81.44%, sensor NN R[Y]C is reliable and suitable for various technological applications.

Ambitions to reach atomic resolution with light have been a major force in shaping nano-optics, whereby a central challenge is achieving highly localized optical fields. A promising approach employs plasmonic nanoantennas, but fluorescence quenching in the vicinity of metallic structures often imposes a strict limit on the attainable spatial resolution, and previous studies have reached only 8 nm resolution in fluorescence mapping. Here, we demonstrate spatially and spectrally resolved photoluminescence imaging of a single phthalocyanine molecule coupled to nanocavity plasmons in a tunnelling junction with a spatial resolution down to ∼8 Å and locally map the molecular exciton energy and linewidth at sub-molecular resolution. This remarkable resolution is achieved through an exquisite nanocavity control, including tip-apex engineering with an atomistic protrusion, quenching management through emitter–metal decoupling and sub-nanometre positioning precision. Our findings provide new routes to optical imaging, spectroscopy and engineering of light–matter interactions at sub-nanometre scales.Through the use of a plasmon-active atomically sharp tip and an ultrathin insulating film, and precise junction control in a highly confined nanocavity plasmon field at the scanning tunnelling microscope junction, sub-nanometre-resolved single-molecule near-field photoluminescence imaging with a spatial resolution down to ∼8 Å is achieved.

Developing efficient and novel methodologies to construct a C–C bond is highly important in both synthetic chemistry and pharmaceutical sciences. In recent years, the visible light-mediated desulfonylative transformation of sulfonyl compounds has emerged as a powerful tool for the synthesis of diverse C–C bond. To emphasize their practical utility, many methodologies have been successfully applied in the modification of a variety of biologically active compounds which possess unprotected amide or hydroxy groups. In this review, we would like to summarize recent advances in C–C bond formation via the visible light-mediated desulfonylation of sulfonyl chlorides, sulfinates, sulfonamides, sulfones, and sulfonylhydrazones. The reaction design, mechanism research, and the application of these protocols in the modification of biologically active compounds are presented. The challenges and future developments in this area are also discussed.

Organic phosphorescence materials offer significant advantages for bioimaging applications. However, most of these materials are excited exclusively by ultraviolet (UV) light, which poses risks to living organisms. Herein, six donor–acceptor-type compounds incorporating triazine groups are designed as guests within doped systems. White-light excitable phosphorescent guests enable doped materials to show efficient afterglow under white-light excitation. By leveraging the ability of white-light to penetrate biological tissues, a bioimaging mode in which the materials are first concentrated within the organism and then excited was developed, yielding superior imaging effects compared with the traditional method in which materials are first excited and then concentrated. Furthermore, these materials are applied in imaging diagnosis of atherosclerosis plaques (male Apoe − / − mice) and intestinal diseases (female BALB/c-nude mice), as well as in navigation for in situ liver tumor surgery (female BALB/c-nude mice), achieving excellent imaging outcomes. This work addresses the limitations of phosphorescent materials that rely on UV-light, significantly enhancing their potential for practical applications in clinical imaging. Organic phosphorescence materials offer advantages for bioimaging applications, but most of them are excited exclusively by ultraviolet light, which poses risks to living organisms. Here, the author report doped materials with white-light activated phosphorescence activity, and a bioimaging mode in which these phosphorescent materials are first concentrated within the organism and then excited.

Wearables and bioelectronics rely on breathable interface devices with bioaffinity, biocompatibility, and smart functionality for interactions between beings and things and the surrounding environment. Elastic fibers/fabrics with mechanical adaptivity to various deformations and complex substrates, are promising to act as fillers, carriers, substrates, dressings, and scaffolds in the construction of biointerfaces for the human body, skins, organs, and plants, realizing functions such as energy exchange, sensing, perception, augmented virtuality, health monitoring, disease diagnosis, and intervention therapy. This review summarizes and highlights the latest breakthroughs of elastic fibers/fabrics for wearables and bioelectronics, aiming to offer insights into elasticity mechanisms, production methods, and electrical components integration strategies with fibers/fabrics, presenting a profile of elastic fibers/fabrics for energy management, sensors, e‐skins, thermal management, personal protection, wound healing, biosensing, and drug delivery. The trans‐disciplinary application of elastic fibers/fabrics from wearables to biomedicine provides important inspiration for technology transplantation and function integration to adapt different application systems. As a discussion platform, here the main challenges and possible solutions in the field are proposed, hopefully can provide guidance for promoting the development of elastic e‐textiles in consideration of the trade‐off between mechanical/electrical performance, industrial‐scale production, diverse environmental adaptivity, and multiscenario on‐spot applications. Elastic fiber/fabric as dynamic matrix/carrier for diverse conductor integration, constructing wearables and bioelectronics to bridge organisms (skin, organs, plants, etc.), objects and their around environment, can realize highly safe and efficient interactions. In terms of mechanism, fabrication, and performance, this article presents a profile of elastic fiber/fabric for energy/thermal management, e‐skins, personalized protection/healthcare, disease diagnosis, and intervention therapy.

Background Diabetes and hyperlipidaemia are both risk factors for coronary artery disease, and both are associated with a high triglyceride-glucose index (TyG index). The TyG index has been presented as a marker of insulin resistance (IR). Its utility in predicting and detecting cardiovascular disease has been reported. However, few studies have found it to be a helpful marker of atherosclerosis in patients with symptomatic coronary artery disease (CAD). The purpose of this study was to demonstrate that the TyG index can serve as a valuable marker for predicting coronary and carotid atherosclerosis in symptomatic CAD patients, regardless of diabetes mellitus and hyperlipidaemia. Methods This study included 1516 patients with symptomatic CAD who underwent both coronary artery angiography and carotid Doppler ultrasound in the Department of Cardiology at Tianjin Union Medical Center from January 2016 to December 2022. The TyG index was determined using the Ln formula. The population was further grouped and analysed according to the presence or absence of diabetes and hyperlipidaemia. The Gensini score and carotid intima-media thickness were calculated or measured, and the patients were divided into four groups according to TyG index quartile to examine the relationship between the TyG index and coronary or carotid artery lesions in symptomatic CAD patients. Results In symptomatic CAD patients, the TyG index showed a significant positive correlation with both coronary lesions and carotid plaques. After adjusting for sex, age, smoking, BMI, hypertension, diabetes, and the use of antilipemic and antidiabetic agents, the risk of developing coronary lesions and carotid plaques increased across the baseline TyG index. Compared with the lowest quartile of the TyG index, the highest quartile (quartile 4) was associated with a greater incidence of coronary heart disease [OR = 2.55 (95% CI 1.61, 4.03)] and carotid atherosclerotic plaque [OR = 2.31 (95% CI 1.27, 4.20)] ( P  < 0.05). Furthermore, when compared to the fasting blood glucose (FBG) or triglyceride (TG) level, the TyG index had a greater area under the ROC curve for predicting coronary lesions and carotid plaques. The subgroup analysis demonstrated the TyG index to be an equally effective predictor of coronary and carotid artery disease, regardless of diabetes and hyperlipidaemia. Conclusion The TyG index is a useful marker for predicting coronary and carotid atherosclerosis in patients with symptomatic CAD, regardless of diabetes mellitus and hyperlipidaemia. The TyG index is of higher value for the identification of both coronary and carotid atherosclerotic plaques than the FBG or TG level alone.

Sleep interacts reciprocally with immune system activity, but its specific relationship with microglia—the resident immune cells in the brain—remains poorly understood. Here, we show in mice that microglia can regulate sleep through a mechanism involving G i -coupled GPCRs, intracellular Ca 2+ signaling and suppression of norepinephrine transmission. Chemogenetic activation of microglia G i signaling strongly promoted sleep, whereas pharmacological blockade of G i -coupled P2Y12 receptors decreased sleep. Two-photon imaging in the cortex showed that P2Y12–G i activation elevated microglia intracellular Ca 2+ , and blockade of this Ca 2+ elevation largely abolished the G i -induced sleep increase. Microglia Ca 2+ level also increased at natural wake-to-sleep transitions, caused partly by reduced norepinephrine levels. Furthermore, imaging of norepinephrine with its biosensor in the cortex showed that microglia P2Y12–G i activation significantly reduced norepinephrine levels, partly by increasing the adenosine concentration. These findings indicate that microglia can regulate sleep through reciprocal interactions with norepinephrine transmission. Immune activity can influence sleep, but the role of microglia has remained unclear. Ma, Li and colleagues show that microglia can promote sleep through P2Y12–G i -coupled GPCR signaling, intracellular calcium increase and suppression of norepinephrine transmission.

The fluorescent light-up aptamer RhoBAST, which binds and activates the fluorophore–quencher conjugate tetramethylrhodamine-dinitroaniline with high affinity, super high brightness, remarkable photostability, and fast exchange kinetics, exhibits excellent performance in super-resolution RNA imaging. Here we determine the co-crystal structure of RhoBAST in complex with tetramethylrhodamine-dinitroaniline to elucidate the molecular basis for ligand binding and fluorescence activation. The structure exhibits an asymmetric “A”-like architecture for RhoBAST with a semi-open binding pocket harboring the xanthene of tetramethylrhodamine at the tip, while the dinitroaniline quencher stacks over the phenyl of tetramethylrhodamine instead of being fully released. Molecular dynamics simulations show highly heterogeneous conformational ensembles with the contact-but-unstacked fluorophore–quencher conformation for both free and bound tetramethylrhodamine-dinitroaniline being predominant. The simulations also show that, upon RNA binding, the fraction of xanthene-dinitroaniline stacked conformation significantly decreases in free tetramethylrhodamine-dinitroaniline. This highlights the importance of releasing dinitroaniline from xanthene tetramethylrhodamine to unquench the RhoBAST–tetramethylrhodamine-dinitroaniline complex. Using SAXS and ITC, we characterized the magnesium dependency of the folding and binding mode of RhoBAST in solution and indicated its strong structural robustness. The structures and binding modes of relevant fluorescent light-up aptamers are compared, providing mechanistic insights for rational design and optimization of this important fluorescent light-up aptamer-ligand system. FLAPs have recently emerged as RNA counterparts to fluorescent proteins. Here, the authors determine the crystal structure of a FLAP called RhoBAST in complex with its ligand TMR-DN and reveal the mechanisms for binding and activation.

The development of simple, versatile strategies for the synthesis of metal-organic framework (MOF)-derived membranes are of increasing scientific interest, but challenges exist in understanding suitable fabrication mechanisms. Here we report a route for the complete transformation of a series of MOF membranes and particles, based on multivalent cation substitution. Through our approach, the effective pore size can be reduced through the immobilization of metal salt residues in the cavities, and appropriate MOF crystal facets can be exposed, to achieve competitive molecular sieving capabilities. The method can also be used more generally for the synthesis of a variety of MOF membranes and particles. Importantly, we design and synthesize promising MOF membranes candidates that are hard to achieve through conventional methods. For example, our CuBTC/MIL-100 membrane exhibits 89, 171, 241 and 336 times higher H 2 permeance than that of CO 2 , O 2 , N 2 and CH 4 , respectively. Metal-organic frameworks (MOFs) are attracting increasing attention as membrane components for molecular sieving due to the range of desirable properties they exhibit. Here, the authors employ in situ cation substitution to transform MOF topologies, and endow the membranes with improved separation capabilities.

Background Lipid metabolic reprogramming in colon cancer shows a potential impact on tumor immune microenvironment and is associated with response to immunotherapy. Therefore, this study aimed to develop a lipid metabolism-related prognostic risk score (LMrisk) to provide new biomarkers and combination therapy strategies for colon cancer immunotherapy. Methods Differentially expressed lipid metabolism-related genes (LMGs) including cytochrome P450 (CYP) 19A1 were screened to construct LMrisk in TCGA colon cancer cohort. The LMrisk was then validated in three GEO datasets. The differences of immune cell infiltration and immunotherapy response between LMrisk subgroups were investigated via bioinformatic analysis. These results were comfirmed by in vitro coculture of colon cancer cells with peripheral blood mononuclear cells, human colon cancer tissue microarray analysis, multiplex immunofluorescence staining and mouse xenograft models of colon cancer. Results Six LMGs including CYP19A1, ALOXE3, FABP4, LRP2, SLCO1A2 and PPARGC1A were selected to establish the LMrisk. The LMrisk was positively correlated with the abundance of macrophages, carcinoma-associated fibroblasts (CAFs), endothelial cells and the levels of biomarkers for immunotherapeutic response including programmed cell death ligand 1 (PD-L1) expression, tumor mutation burden and microsatellite instability, but negatively correlated with CD8 + T cell infiltration levels. CYP19A1 protein expression was an independent prognostic factor, and positively correlated with PD-L1 expression in human colon cancer tissues. Multiplex immunofluorescence analyses revealed that CYP19A1 protein expression was negatively correlated with CD8 + T cell infiltration, but positively correlated with the levels of tumor-associated macrophages, CAFs and endothelial cells. Importantly, CYP19A1 inhibition downregulated PD-L1, IL-6 and TGF-β levels through GPR30-AKT signaling, thereby enhancing CD8 + T cell-mediated antitumor immune response in vitro co-culture studies. CYP19A1 inhibition by letrozole or siRNA strengthened the anti-tumor immune response of CD8 + T cells, induced normalization of tumor blood vessels, and enhanced the efficacy of anti-PD-1 therapy in orthotopic and subcutaneous mouse colon cancer models. Conclusion A risk model based on lipid metabolism-related genes may predict prognosis and immunotherapeutic response in colon cancer. CYP19A1-catalyzed estrogen biosynthesis promotes vascular abnormality and inhibits CD8 + T cell function through the upregulation of PD-L1, IL-6 and TGF-β via GPR30-AKT signaling. CYP19A1 inhibition combined with PD-1 blockade represents a promising therapeutic strategy for colon cancer immunotherapy.