Search

Achieving an excellent device performance with slow roll-off efficiency is still a crucial requirement for phosphorescent OLEDs in displays and white lighting applications. Three bipolar host materials comprised of carbazole, pyridine and triazole units, namely o -CzTPy, p -CzTPy, and 3-CzTPy were synthesized and developed. They are designed by selecting the pyridine and triazole groups together as an electron-transporting unit, and varying the different linking modes of the functional groups to optimize performance. These materials possessed high triplet energies (2.66 eV–2.69 eV), and good bipolar charge transporting abilities. FIrpic and Ir(ppy) 3 based blue and green PhOLEDs incorporating these bipolar hosts show low turn-on voltage, high efficiencies and slow efficiency roll-off. Among them, a maximum efficiency of 22.25% (41.98 cd A−1) was achieved for o -CzTPy based blue device. More importantly, the o -CzTPy based green device achieved the desirable high efficiency of 29.08% (96.98 cd A−1), which is among the highest values for PhOLEDs with dopant Ir(ppy) 3 ever reported in public scientific literatures. These excellent results demonstrated that these bipolar hosts possess high practical value for application in commercial PhOLEDs. [Display omitted] • Three bipolar host materials comprising carbazole, pyridine and triazole moieties have been designed and synthesized. • The hosts have high triplet energies and good bipolar transporting abilities. • These materials hosted PhOLEDs showed excellent performances with low efficiency roll-off. [ABSTRACT FROM AUTHOR]

• The operation of GO-based biosensor is easy. • Simplify the purification process of the material. • The sensitivity of this biosensor via GO enhancing signal is high. • This method is cost-effective. Atom transfer radical polymerization (ATRP) is an effective polymerization technology, and low ppm ATRP attracts unceasing interest in biological field. In this work, a fast and effective electrochemical biosensor based on graphene oxide (GO) via electrochemically mediated ATRP (eATRP) realized the ultrasensitive detection of lung cancer DNA. Peptide nucleic acid (PNA) was used as capture probes to specifically recognize target DNA, GO was connected to PNA/DNA heteroduplexes via phosphate-Zr4+-carboxylate chemistry to introduce eATRP initiators. Under a potentiostatic condition, eATRP was initiated with the help of reducibility of electrons, and numerous monomers labeled with ferrocene moieties were grafted onto GO. GO was synthesized by modified Hummer's method and was characterized by Fourier transform infra-red spectra (FT-IR) and X-ray diffraction (XRD). The analytical performance of this biosensor was evaluated by square wave voltammetry (SWV) under optimal conditions, its limit of detection (LOD) was 0.213 aM (R2 = 0.994) with a linear range from 1.0 aM to 100 fM. High selectivity of this biosensor indicated a good application potential of genotyping of single nucleotide polymorphisms (SNPs), and simple operation and highly sensitive analytical performance endowed this biosensor a superior application prospect. More importantly, a novel thinking for material application in biological detection was provided in this work. [ABSTRACT FROM AUTHOR]

CdS/ZnO nanoparticle/nanorod hetero-structure with a certain amount of CdS resulted in a 17 and 2.3 fold increase of Cr(VI) photoreduction and MB degradation rates compared with ZnO nanorods, respectively, due to the enhancement of hole-electron separation of hetero-structure. The CdS/ZnO nanoparticle/nanorod hetero-structure was directly synthesized via the chemical deposition of CdS nanoparticles on the ZnO nanorods, which displayed 17 and 2.3 fold increase of Cr(VI) reduction and Methylene Blue degradation rates compared with ZnO nanorod, respectively, under visible light, due to the enhancement of separation of electron–hole pairs of the hetero-structure. [ABSTRACT FROM AUTHOR]

• Ag nanoparticles-ZIF-67 nanopinnas composite (Ag- ZIF-67 p) was fabricated for the first time. • The Ag- ZIF-67 nanopinnas exhibited large surface area, conductivity, and excellent catalytic activity. • Ag- ZIF-67 nanopinnas showed excellent performance for electrochemical detection of DA and AP. Hybridizing nanostructured metal nanoparticles with metal-organic framework is greatly promising for the enhancement of electrochemical performance of sensor. In the present study, an Ag nanoparticles-ZIF-67 nanopinnas composite material (Ag-ZIF-67p) has been fabricated by ultrasonication and reduction of a metal precursor (AgNO 3) within ZIF-67 nanopinnas template. The desired Ag-ZIF-67p was characterized by transmission electron microscopy with energy dispersive X-ray analysis and elemental mapping, powder X-ray diffraction, X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy. The Ag-ZIF-67p was modified on the GCE and demonstrated enhanced electrocatalytic activity toward dopamine (DA) and acetaminophen (AP) owing to synergetic properties of large porosity and surface area of ZIF-67 and the high conductivity and excellent catalytic activity of Ag nanoparticles. The results revealed broader linear range toward analysis of DA and AP with low detection limit of 0.2 and 0.05 μM (S/ N = 3) for AP and DA, respectively. In addition, this Ag-ZIF-67p modified electrode also showed excellent selectivity for the detection of two compounds and prospective results in real tablets and dopamine hydrochloride injection samples. [ABSTRACT FROM AUTHOR]

Metal oxide nanostructures with single-atomic heteroatom incorporation are of interest for many applications. However, a universal and scalable synthesis approach with high heteroatom concentrations represents a formidable challenge, primarily due to the pronounced structural disparities between M hetero -O and M sub -O units. Here, focusing on TiO 2 as the exemplified substrate, we present a diethylene glycol-assisted synthetic platform tailored for the controlled preparation of a library of M 1 -TiO 2 nanostructures, encompassing 15 distinct unary M 1 -TiO 2 nanostructures, along with two types of binary and ternary composites. Our approach capitalizes on the unique properties of diethylene glycol, affording precise kinetic control by passivating the hydrolytic activity of heteroatom and simultaneously achieving thermodynamic control by introducing short-range order structures to dissipate the free energy associated with heteroatom incorporation. The M 1 -TiO 2 nanostructures, characterized by distinctive and abundant M-O-Ti units on the surface, exhibit high efficiency in photochromic photothermal catalysis toward recycling waste polyesters. This universal synthetic platform contributes to the preparation of materials with broad applicability and significance across catalysis, energy conversion, and biomedicine., (© 2024. The Author(s).)

Although Mo 2 C and earth-abundant 3d transition metals are regarded as potential catalysts to replace noble metal catalysts for effective hydrogen evolution reaction, their large-scale application is still inhibited by their own defects. Here, a facile thermal treatment method for nonprecious metal catalysts is developed to prepare a porous Ni/Mo 2 C composite catalyst. The loading density of Ni nanoparticles on the Mo 2 C surface has an important effect on the activity of the catalyst. By optimizing the Ni doping ratio, the Ni-40/Mo 2 C-17 sample exhibits the lowest onset overpotential and lowest overpotential at 10 mA cm -2 in both acidic and alkaline electrolytes, compared to other reported Ni- and Mo 2 C-based catalysts. In addition, theoretical calculations have also confirmed the synergistic effect between Ni nanoparticles and Mo 2 C, which can balance the thermodynamics between H adsorption and desorption of H 2 . This work provides an avenue for designing high-performance water-splitting catalytic materials using low-cost species, which exhibit excellent HER activity in a wide pH range.

Background: The Centre for Disease Control and Prevention in Yangquan, China, has taken a series of preventive and control measures in response to the increasing trend of Kala-Azar. In response, we propose a new model to more scientifically evaluate the effectiveness of these interventions., Methods: We obtained the incidence data of Kala-Azar from 2017 to 2021 from the Centre for Disease Control and Prevention (CDC) in Yangquan. We constructed Poisson segmented regression model, harmonic Poisson segmental regression model, and improved harmonic Poisson segmented regression model, and used the three models to explain the intervention effect, respectively. Finally, we selected the optimal model by comparing the fitting effects of the three models., Results: The primary analysis showed an underlying upward trend of Kala-Azar before intervention [incidence rate ratio (IRR): 1.045, 95% confidence interval (CI): 1.027-1.063, p  < 0.001]. In terms of long-term effects, the rise of Kala-Azar slowed down significantly after the intervention (IRR:0.960, 95%CI:0.927-0.995, p  = 0.026), and the risk of Kala-Azar increased by 0.3% for each additional month after intervention ( β 1  +  β 3  = 0.003, IRR = 1.003). The results of the model fitting effect showed that the improved harmonic Poisson segmental regression model had the best fitting effect, and the values of MSE, MAE, and RMSE were the lowest, which were 0.017, 0.101, and 0.130, respectively., Conclusion: In the long term, the intervention measures taken by the Yangquan CDC can well curb the upward trend of Kala-Azar. The improved harmonic Poisson segmented regression model has higher fitting performance, which can provide a certain scientific reference for the evaluation of the intervention effect of seasonal infectious diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hao, Zhao, Zhang, Wu, Ren, Wang, Qiao, Cui and Qiu.)

The adsorbate-mediated strong metal-support interaction (A-SMSI) offers a reversible means of altering the selectivity of supported metal catalysts, thereby providing a powerful tool for facile modulation of catalytic performance. However, the fundamental understanding of A-SMSI remains inadequate and methods for tuning A-SMSI are still in their nascent stages, impeding its stabilization under reaction conditions. Here, we report that the initial concentration of oxygen vacancy in oxide supports plays a key role in tuning the A-SMSI between Ru nanoparticles and defected titania (TiO 2-x ). Based on this new understanding, we demonstrate the in situ formation of A-SMSI under reaction conditions, obviating the typically required CO 2 -rich pretreatment. The as-formed A-SMSI layer exhibits remarkable stability at various temperatures, enabling excellent activity, selectivity and long-term stability in catalyzing the reverse water gas-shift reaction. This study deepens the understanding of the A-SMSI and the ability to stabilize A-SMSI under reaction conditions represents a key step for practical catalytic applications., (© 2024 Wiley-VCH GmbH.)

The abnormality of the p53 tumor suppressor is crucial in lung cancer development, because p53 regulates target gene promoters to combat cancer. Recent studies have shown extensive p53 binding to enhancer elements. However, whether p53 exerts a tumor suppressor role by shaping the enhancer landscape remains poorly understood. In the current study, we employed several functional genomics approaches to assess the enhancer activity at p53 binding sites throughout the genome based on our established TP53 knockout (KO) human bronchial epithelial cells (BEAS-2B). A total of 943 active regular enhancers and 370 super-enhancers (SEs) disappeared upon the deletion of p53, indicating that p53 modulates the activity of hundreds of enhancer elements. We found that one p53-dependent SE, located on chromosome 9 and designated as KLF4 -SE, regulated the expression of the Krüppel-like factor 4 ( KLF4 ) gene. Furthermore, the deletion of p53 significantly decreased the KLF4 -SE enhancer activity and the KLF4 expression, but increased colony formation ability in the nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone-induced cell transformation model. Subsequently, in TP53 KO cells, the overexpression of KLF4 partially reversed the increased clonogenic capacity caused by p53 deficiency. Consistently, KLF4 expression also decreased in lung cancer tissues and cell lines. It appeared that overexpression of KLF4 significantly suppressed the proliferation and migration of lung cancer cells. Collectively, our results suggest that the regulation of enhancer formation and activity by p53 is an integral component of the p53 tumor suppressor function. Therefore, our findings offer some novel insights into the regulation mechanism of p53 in lung oncogenesis and introduce a new strategy for screening therapeutic targets.

While Ru-catalyzed hydrogenolysis holds significant promise in converting waste polyolefins into value-added alkane fuels, a major constraint is the high cost of noble metal catalysts. In this work, we propose, for the first time, that Co-based catalysts derived from CoAl-layered double hydroxide (LDH) are alternatives for efficient polyolefin hydrogenolysis. Leveraging the chemical flexibility of the LDH platform, we reveal that metallic Co species serve as highly efficient active sites for polyolefin hydrogenolysis. Furthermore, we introduced Ni into the Co framework to tackle the issue of restricted hydrogenation ability associated with contiguous Co-Co sites. In-situ analysis indicates that the integration of Ni induces electron transfer and facilitates hydrogen spillover. This dual effect synergistically enhances the hydrogenation/desorption of olefin intermediates, resulting in a significant reduction in the yield of low-value CH 4 from 27.1 to 12.6%. Through leveraging the unique properties of LDH, we have developed efficient and cost-effective catalysts for the sustainable recycling and valorization of waste polyolefin materials.

Cancer risk loci provide special clues for uncovering pathogenesis of cancers. The TNFRSF19 gene located within the 13q12.12 lung cancer risk locus encodes TNF receptor superfamily member 19 (TNFRSF19) protein and has been proved to be a key target gene of a lung tissue-specific tumor suppressive enhancer, but its functional role in lung cancer pathogenesis remains to be elucidated. Here we showed that the TNFRSF19 gene could protect human bronchial epithelial Beas-2B cells from pulmonary carcinogen nicotine-derived nitrosamine ketone (NNK)-induced malignant transformation. Knockout of the TNFRSF19 significantly increased NNK-induced colony formation rate on soft agar. Moreover, TNFRSF19 expression was significantly reduced in lung cancer tissues and cell lines. Restoration of TNFRSF19 expression in A549 lung cancer cell line dramatically suppressed the tumor formation in xenograft mouse model. Interestingly, the TNFRSF19 protein that is an orphan membrane receptor could compete with LRP6 to bind Wnt3a, thereby inhibiting the Wnt/β-catenin signaling pathway that is required for NNK-induced malignant transformation as indicated by protein pulldown, site mutation, and fluorescence energy resonance transfer experiments. Knockout of the TNFRSF19 enhanced LRP6-Wnt3a interaction, promoting β-catenin nucleus translocation and the downstream target gene expression, and thus sensitized the cells to NNK carcinogen. In conclusion, our study demonstrated that the TNFRSF19 inhibited lung cancer carcinogenesis by competing with LRP6 to combine with Wnt3a to inhibit the Wnt/β-catenin signaling pathway., Implications: These findings revealed a novel anti-lung cancer mechanism, highlighting the special significance of TNFRSF19 gene within the 13q12.12 risk locus in lung cancer pathogenesis., (©2023 American Association for Cancer Research.)

Rechargeable aqueous zinc ion batteries (AZIBs) have gained considerable attention owing to their low cost and high safety, but dendrite growth, low plating/stripping efficiency, surface passivation, and self-erosion of the Zn metal anode are hindering their application. Herein, a one-step in situ molecular engineering strategy for the simultaneous construction of hierarchical MoS 2 double-layer nanotubes (MoS 2 -DLTs) with expanded layer-spacing, oxygen doping, structural defects, and an abundant 1T-phase is proposed, which are designed as an intercalation-type anode for "rocking-chair" AZIBs, avoiding the Zn anode issues and therefore displaying a long cycling life. Benefiting from the structural optimization and molecular engineering, the Zn 2+ diffusion efficiency and interface reaction kinetics of MoS 2 -DLTs are enhanced. When coupled with a homemade ZnMn 2 O 4 cathode, the assembled MoS 2 -DLTs//ZnMn 2 O 4 full battery exhibited impressive cycling stability with a capacity retention of 86.6% over 10 000 cycles under 1 A g -1 anode , outperforming most of the reported "rocking-chair" AZIBs. The Zn 2+ /H + cointercalation mechanism of MoS 2 -DLTs is investigated by synchrotron in situ powder X-ray diffraction and multiple ex situ characterizations. This research demonstrates the feasibility of MoS 2 for Zn-storage anodes that can be used to construct reliable aqueous full batteries.

Background: Since the inconspicuous nature of early signs associated with Chronic Obstructive Pulmonary Disease (COPD), individuals often remain unidentified, leading to suboptimal opportunities for timely prevention and treatment. The purpose of this study was to create an explainable artificial intelligence framework combining data preprocessing methods, machine learning methods, and model interpretability methods to identify people at high risk of COPD in the smoking population and to provide a reasonable interpretation of model predictions., Methods: The data comprised questionnaire information, physical examination data and results of pulmonary function tests before and after bronchodilatation. First, the factorial analysis for mixed data (FAMD), Boruta and NRSBoundary-SMOTE resampling methods were used to solve the missing data, high dimensionality and category imbalance problems. Then, seven classification models (CatBoost, NGBoost, XGBoost, LightGBM, random forest, SVM and logistic regression) were applied to model the risk level, and the best machine learning (ML) model's decisions were explained using the Shapley additive explanations (SHAP) method and partial dependence plot (PDP)., Results: In the smoking population, age and 14 other variables were significant factors for predicting COPD. The CatBoost, random forest, and logistic regression models performed reasonably well in unbalanced datasets. CatBoost with NRSBoundary-SMOTE had the best classification performance in balanced datasets when composite indicators (the AUC, F1-score, and G-mean) were used as model comparison criteria. Age, COPD Assessment Test (CAT) score, gross annual income, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), anhelation, respiratory disease, central obesity, use of polluting fuel for household heating, region, use of polluting fuel for household cooking, and wheezing were important factors for predicting COPD in the smoking population., Conclusion: This study combined feature screening methods, unbalanced data processing methods, and advanced machine learning methods to enable early identification of COPD risk groups in the smoking population. COPD risk factors in the smoking population were identified using SHAP and PDP, with the goal of providing theoretical support for targeted screening strategies and smoking population self-management strategies., (© 2023. The Author(s).)

Background: Topical lidocaine microemulsion preparations with low toxicity, low irritation, strong transdermal capability and convenient administration are urgently needed. Methods: Box-Behnken design was performed for three preparation conditions of 5% lidocaine microemulsions: mass ratio of the mass ratio of surfactant/(oil phase + surfactant) (X 1 ), the mass ratio of olive oil/(α-linolenic acid + linoleic acid) (X 2 ) and the water content W% (X 3 ). Then, five multi-objective genetic algorithms were used to optimize the three evaluation indices to optimize the effects of lidocaine microemulsion preparations. Finally, the ideal optimization scheme was experimentally verified. Results: Non-dominated Sorting Genetic Algorithm-II was used for 30 random searches. Among these, Scheme 2: X 1 = 0.75, X 2 = 0.35, X 3 = 75%, which resulted in Y 1 = 0.17 μg/(cm 2 ·s) and Y 2 = 0.74 mg/cm 2 ; and the Scheme 19: X 1 = 0.68, X 2 = 1.42, X 3 = 75% which resulted in Y 1 = 0.14 μg/(cm 2 ·s) and Y 2 = 0.80 mg/cm 2 , provided the best matches for the objective function requirements. The maximum and average fitness of the method have reached stability after 3 generations of evolution. Experimental verification of the above two schemes showed that there were no statistically significant differences between the measured values of Y 1 and Y 2 and the predicted values obtained by optimization ( p > 0.05) and are close to the target value. Conclusion: Two lidocaine microemulsion preparation protocols were proposed in this study. These preparations resulted in good transdermal performance or long anesthesia duration, respectively., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Qiao, Wang, Ren, Cui, Ren, Hao, Zhao, Liu, Zhao, Li, Tian and Qiu.)

Single-atom or atomically dispersed metal materials have emerged as highly efficient catalysts, but their potential as excellent supports has rarely been reported. In this work, we prepared Mg-N-C materials derived from annealing of a Mg-based metal-organic framework (MOF). By introducing Pt, Mg-N-C not only serves as a platform for anchoring Pt nanoparticles but also facilitates the integration of Mg into the Pt face-centered cubic lattice, resulting in the formation of highly crystalline Pt 3 Mg nanoalloys via the metal-support interfacial interaction. Synchrotron radiation-based X-ray absorption spectroscopy (XAS) enables us to study the interfacial interaction and the surface electronic structure of this intricate system. The formation of Pt 3 Mg nanoalloys induces a downshift of the Pt d-band (gaining d-charge), as revealed by the decrease in the Pt L 3 -edge white-line (WL) area under the curve. This downshift can weaken the binding of oxygen reduction reaction (ORR) intermediates, hence improving the ORR performance.

Diabetes mellitus (DM) has become the third chronic non-infectious disease affecting patients after tumor, cardiovascular and cerebrovascular diseases, becoming one of the major public health issues worldwide. Detection of early warning risk factors for DM is key to the prevention of DM, which has been the focus of some previous studies. Therefore, from the perspective of residents' self-management and prevention, this study constructed Bayesian networks (BNs) combining feature screening and multiple resampling techniques for DM monitoring data with a class imbalance in Shanxi Province, China, to detect risk factors in chronic disease monitoring programs and predict the risk of DM. First, univariate analysis and Boruta feature selection algorithm were employed to conduct the preliminary screening of all included risk factors. Then, three resampling techniques, SMOTE, Borderline-SMOTE (BL-SMOTE) and SMOTE-ENN, were adopted to deal with data imbalance. Finally, BNs developed by three algorithms (Tabu, Hill-climbing and MMHC) were constructed using the processed data to find the warning factors that strongly correlate with DM. The results showed that the accuracy of DM classification is significantly improved by the BNs constructed by processed data. In particular, the BNs combined with the SMOTE-ENN resampling improved the most, and the BNs constructed by the Tabu algorithm obtained the best classification performance compared with the hill-climbing and MMHC algorithms. The best-performing joint Boruta-SMOTE-ENN-Tabu model showed that the risk factors of DM included family history, age, central obesity, hyperlipidemia, salt reduction, occupation, heart rate, and BMI., (© 2023. Springer Nature Limited.)

Driving metal-cluster-catalyzed high-temperature chemical reactions by sunlight holds promise for the development of negative-carbon-footprint industrial catalysis, which has yet often been hindered by the poor ability of metal clusters to harvest and utilize the full spectrum of solar energy. Here, we report the preparation of Mo 2 TiC 2 MXene-supported Ru clusters (Ru/Mo 2 TiC 2 ) with pronounced broadband sunlight absorption ability and high sintering resistance. Under illumination of focused sunlight, Ru/Mo 2 TiC 2 can catalyze the reverse water-gas shift (RWGS) reaction to produce carbon monoxide from the greenhouse gas carbon dioxide and renewable hydrogen with enhanced activity, selectivity, and stability compared to their nanoparticle counterparts. Notably, the CO production rate of MXene-supported Ru clusters reached 4.0 mol·g Ru -1 ·h -1 , which is among the best reported so far for photothermal RWGS catalysts. Detailed studies suggest that the production of methane is kinetically inhibited by the rapid desorption of CO from the surface of the Ru clusters.

Fabricating high-capacity electrode materials toward supercapacitors has attracted increasing attention. Here we report a three-dimensional CNTs/NiCo 2 S 4 nanocomposite material synthesized successfully by a facile one-step hydrothermal technique. As expected, a CNTs/NiCo 2 S 4 electrode shows remarkable capacitive properties with a high specific capacitance of 890 C g -1 at 1 A g -1 . It also demonstrates excellent cycle stability with an 83.5% capacitance retention rate after 5000 cycles at 10 A g -1 . Importantly, when assembled into a asymmetric supercapacitor, it exhibits a high energy density (43.3 W h kg -1 ) and power density (800 W kg -1 ). The exceptional electrochemical capacity is attributed to the structural features, refined grains, and enhanced conductivity. The above results indicate that CNTs/NiCo 2 S 4 composite electrode materials have great potential application in energy-storage devices., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Lead halide perovskite nanocrystals (CsPbX 3 NCs) have been regarded as promising materials in photocatalysis. Combining metal single atoms with CsPbX 3 NCs may be a practical way in exploring perovskite-based catalysts. However, such hybrids have not been achieved experimentally yet, mainly due to the weak interaction between the metal atom and the CsPbX 3 surface. Here, we demonstrate that Pt single atoms can be deposited on CsPbBr 3 NCs through a photoassisted approach, in which the surface was partially oxidized first, followed by the anchoring of Pt single atoms through the formation of Pt-O and Pt-Br bonds. The deposition of Pt single atoms can significantly change the photophysical properties of CsPbBr 3 NCs by inducing the generation of deep trap states in the band gap. The as-prepared Pt-SA/CsPbBr 3 can be used as efficient and durable catalysts for photocatalytic semi-hydrogenation of propyne. A CsPbBr 3 nanocrystal might be a suitable substrate for anchoring other metal single atoms, such as Cu, Au, Ag, Pd, and so on.

The structural properties such as high specific surface area, good electrical conductivity, rich-defects of the catalyst surface guarantee outstanding catalytic performance and durability of oxygen reduction reaction (ORR) electrocatalysts. It is still a challenging task to construct ORR catalysts with excellent performance. Herein, we have reported column-like MoS 2 /rGO with defect-rich ultrathin nanosheets prepared by a convenient solvothermal method. The structure and composition of MoS 2 /rGO are systematically investigated. MoS 2 /rGO shows a remarkable electrocatalytic performance, which is characterized by an outstanding onset potential of 0.97 V, a half-wave potential of 0.83 V, noticeable methanol tolerance, and durability of 93.7% current retention, superior to commercial Pt/C. The ORR process occurring on MoS 2 /rGO is a typical four electron pathway. Therefore, this study achieves the design of a low-cost, highly efficient and stable nonprecious metal ORR electrocatalyst in alkaline media., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Background: This article aims to understand the prevalence of hyperlipidemia and its related factors in Shanxi Province. On the basis of multivariate Logistic regression analysis to find out the influencing factors closely related to hyperlipidemia, the complex network connection between various variables was presented through Bayesian networks(BNs)., Methods: Logistic regression was used to screen for hyperlipidemia-related variables, and then the complex network connection between various variables was presented through BNs. Since some drawbacks stand out in the Max-Min Hill-Climbing (MMHC) hybrid algorithm, extra hybrid algorithms are proposed to construct the BN structure: MMPC-Tabu, Fast.iamb-Tabu and Inter.iamb-Tabu. To assess their performance, we made a comparison between these three hybrid algorithms with the widely used MMHC hybrid algorithm on randomly generated datasets. Afterwards, the optimized BN was determined to explore to study related factors for hyperlipidemia. We also make a comparison between the BN model with logistic regression model., Results: The BN constructed by Inter.iamb-Tabu hybrid algorithm had the best fitting degree to the benchmark networks, and was used to construct the BN model of hyperlipidemia. Multivariate logistic regression analysis suggested that gender, smoking, central obesity, daily average salt intake, daily average oil intake, diabetes mellitus, hypertension and physical activity were associated with hyperlipidemia. BNs model of hyperlipidemia further showed that gender, BMI, and physical activity were directly related to the occurrence of hyperlipidemia, hyperlipidemia was directly related to the occurrence of diabetes mellitus and hypertension; the average daily salt intake, daily average oil consumption, smoking, and central obesity were indirectly related to hyperlipidemia., Conclusions: The BN of hyperlipidemia constructed by the Inter.iamb-Tabu hybrid algorithm is more reasonable, and allows for the overall linking effect between factors and diseases, revealing the direct and indirect factors associated with hyperlipidemia and correlation between related variables, which can provide a new approach to the study of chronic diseases and their associated factors., (© 2021. The Author(s).)

Background: Diabetes Mellitus (DM) has become the third chronic non-communicable disease that hits patients after tumors, cardiovascular and cerebrovascular diseases, and has become one of the major public health problems in the world. Therefore, it is of great importance to identify individuals at high risk for DM in order to establish prevention strategies for DM., Methods: Aiming at the problem of high-dimensional feature space and high feature redundancy of medical data, as well as the problem of data imbalance often faced. This study explored different supervised classifiers, combined with SVM-SMOTE and two feature dimensionality reduction methods (Logistic stepwise regression and LAASO) to classify the diabetes survey sample data with unbalanced categories and complex related factors. Analysis and discussion of the classification results of 4 supervised classifiers based on 4 data processing methods. Five indicators including Accuracy, Precision, Recall, F1-Score and AUC are selected as the key indicators to evaluate the performance of the classification model., Results: According to the result, Random Forest Classifier combining SVM-SMOTE resampling technology and LASSO feature screening method (Accuracy = 0.890, Precision = 0.869, Recall = 0.919, F1-Score = 0.893, AUC = 0.948) proved the best way to tell those at high risk of DM. Besides, the combined algorithm helps enhance the classification performance for prediction of high-risk people of DM. Also, age, region, heart rate, hypertension, hyperlipidemia and BMI are the top six most critical characteristic variables affecting diabetes., Conclusions: The Random Forest Classifier combining with SVM-SMOTE and LASSO feature reduction method perform best in identifying high-risk people of DM from individuals. And the combined method proposed in the study would be a good tool for early screening of DM.

A series of novel CdS/CdIn 2 S 4 composite materials were prepared via a one-pot solvothermal process. The as-obtained photocatalysts were characterized by several techniques and the photocatalytic properties of CdS/CdIn 2 S 4 photocatalysts were studied by photocascade synthesis of Schiff base compounds in a photocatalytic reaction system of aromatic alcohols and nitrobenzene irradiated with visible light. The results reveal that the resulting CdS/CdIn 2 S 4 heterostructure samples show outstanding photocatalytic activities toward the photocascade production of Schiff base compounds in an aromatic alcohols and nitrobenzene reaction system irradiated with visible light. An optimized 50.0% CdS/CdIn 2 S 4 heterostructure sample shows the highest Schiff base yield of 42.0% irradiated with visible light for 4 h, which is approximately 19.1 and 1.54 times higher than those of sole CdS and CdIn 2 S 4 samples, respectively. The fabrication of heterogeneous structure improves the spatial separation and migration of photoinduced electron-hole pairs, thus contributing to the enhancement of photocatalytic properties. We foresee that this finding can offer a strategy to develop heterostructure composites for efficient synthesis of organics by photocatalysis under mild conditions.

The use of solar energy to drive organic reactions under mild conditions provides a sustainable pathway for green synthesis and has been one of the primary goals pursued by scientists. In this research, the cadmium indium sulfide (CdIn2S4) photocatalyst was prepared using a simple solvothermal method and was thoroughly characterized using X-ray powder diffraction, UV-visible absorption spectra, nitrogen adsorption-desorption isotherms, scanning electron microscopy, transmission electron microscopy and X-ray spectroscopy measurements. The photocatalytic performance of the CdIn2S4 photocatalyst was evaluated using photocatalytic synthesis of Schiff base compounds in a coupled system of aromatic alcohols and nitrobenzene under visible light irradiation. The yield of N-benzylideneaniline reached up to 32% in the coupled system of benzyl alcohol and nitrobenzene under visible light illumination for 8 h. Furthermore, the changes for the amounts of aromatic aldehydes and AL as intermediate products during the photocatalytic process were also investigated. Using isotopic tracing, a possible reaction mechanism for the photocatalytic synthesis of N-benzylideneaniline and the redox reactions in the coupled system of benzyl alcohol and nitrobenzene was proposed. It is hoped that this strategy can provide an effective pathway for the traditional organic synthesis and transformation using photocatalytic technology under mild conditions.

We report, for the first time, that an encapsulated silver nanoparticle can be directly converted to a silver nanoshell through a nanoscale localized oxidation and reduction process in the gas phase. Silver can be etched when exposed to a mixture of NH3/O2 gases through a mechanism analogous to the formation of aqueous Tollens' reagent, in which a soluble silver-ammonia complex was formed. Starting with Ag@resorcinol-formaldehyde (RF) resin core-shell nanoparticles, we demonstrate that RF-core@Ag-shell nanoparticles can be prepared successfully when the etching rate and RF thickness were well controlled. Due to the strong surface plasmon resonance (SPR) coupling effect among neighboring silver nanoparticles, the RF@Ag nanoparticle showed great SPR and SERS performance. This process provides a general route to the conversion of Ag-core to Ag-shell nanostructures and might be extended to other systems.

An 'off-on' rhodamine-based fluorescence probe for the selective detection of Cu(II) has been designed, exploiting the guest-induced structure transform mechanism. This system shows a sharp Cu(II)-selective fluorescence enhancement response in an aqueous system under physiological pH, and possesses high selectivity against a background of environmentally and biologically relevant metal ions. Under optimum conditions, the fluorescence intensity enhancement of this system is linearly proportional to the Cu(II) concentration from 50 nM to 6.0 μM with a detection limit of 29 nM., (Copyright © 2014 John Wiley & Sons, Ltd.)