Fluorescence detecting glycopeptide antibiotics via a dynamic molecular switch.

BACKGROUND: Glycopeptide antibiotics (GPAs) represented by vancomycin (VAN) are clinically used as a first-line treatment for serious infections caused by Gram-positive pathogens. The use and dosing methods of GPAs are rigorously managed for safety considerations, which calls for fast and accurate quantification approaches. RESULT: A new sort of fluorescent probes for GPAs has been proposed, each of which was integrated by a fluorescein-based reporter and a GPAs' recognition peptide D-alanyl-D-alanine (D-Ala-D-Ala). These probes work as dynamic molecular switches, which mainly exist as non-fluorescent spirolactam forms in the absence of GPAs. GPAs binding with the dipeptide regulates the dynamic balance between fluorescence OFF lactam form and fluorescence ON ring-opened form, rendering these probes capable of GPAs detecting. The most promising one P1 exhibits excellent sensitivity and selectivity towards GPAs detection. SIGNIFICANCE: Different to previous developments, P1 consists of a single fluorophore without the need of a fluorescence-quenching group or a secondary dye, which is the smallest fluorescent probe for GPAs up to now. P1 realizes direct VAN quantification from complex biological samples including real serums, dispensing with additional drug extraction. More interestingly, both P1 and P6 can distinguish GPAs with different peptide backbones, which has not been achieved previously.

Chemoselective and Divergent Synthesis of Chlorohydrins and Oxaheterocycles via Ir-Catalyzed Asymmetric Hydrogenation.

Chlorohydrins and oxaheterocycles are synthetically valuable building blocks for diverse natural products and therapeutic substances. A highly efficient Ir/f-phamidol-catalyzed asymmetric hydrogenation of ω-chloroketones was successfully developed, and various chlorohydrins and oxaheterocycles were obtained divergently with excellent yields and enantioselectivities (up to >99% yield and >99% ee). Synthetic utilities of this divergent transformation were demonstrated by gram-scale synthesis of key intermediates of several enantiomerically enriched drugs via this catalytic methodology.

Inheritance and Innovation of Pottery Sculpture Technique in Shiwan, China: A Grounded Study from Cultural Ecology.

Ceramics play an important role in human daily life and production practice. Pottery sculpture technique is the core of ceramic making. However, the production process of traditional ceramics is accompanied by high pollution, which has a great impact on human health and the ecological environment. Rapid development of industrialization has exacerbated this consequence. As the "Pottery Capital of Southern China", Foshan has been involved in environmental crises while relying on the ceramic industry to develop. Since the 21st century, Foshan has gradually successfully driven to upgrade the city from industrial to culture-led by carrying out positive innovations in Shiwan pottery sculpture technique. Therefore, based on the theoretical perspective of cultural ecology, this paper selects Shiwan pottery sculpture technique as the object, uses Python (Octopus Collector) to obtain data, and applies grounded theory to generate the ecological evolution model. This study discussed how the Shiwan pottery sculpture technique promotes the harmonious coexistence of human beings, industries, and cities in the new cultural ecological environment of the 21st century by exploring and clarifying the interaction and function of different elements in different stages of evolution. Finally, this study not only makes up for the current lack of research on Shiwan's cultural ecology, but also provides meaningful reference for environmental reform in other industrialized cities.

Icariin Attenuates Amyloid-ß (Aß)-Induced Neuronal Insulin Resistance Through PTEN Downregulation.

Neuronal insulin resistance is implicated in neurodegenerative diseases. Icariin has been reported to improve insulin resistance in skeletal muscle cells and to restore impaired hypothalamic insulin signaling in the rats with chronic unpredictable mild stress. In addition, icariin can exert the neuroprotective effects in the mouse models of neurodegenerative diseases. However, the molecular mechanisms by which icariin affects neuronal insulin resistance are poorly understood. In the present study, amyloid-ß (Aß) was used to induce insulin resistance in human neuroblastoma SK-N-MC cells. Insulin sensitivity was evaluated by measuring insulin-stimulated Akt T308 phosphorylation and glucose uptake. We found that the phosphatase and tensin homologue deleted on chromosome 10 (PTEN) mediated Aß-induced insulin resistance. Icariin treatment markedly reduced Aß-enhanced PTEN protein levels, leading to an improvement in Aß-induced insulin resistance. Accordingly, PTEN overexpression obviously abolished the protective effects of icariin on Aß-induced insulin resistance. Furthermore, icariin activated proteasome activity. The proteasome inhibitor MG132 attenuated the effects of icariin on PTEN protein levels. Taken together, these results suggest that icariin protects SK-N-MC cells against Aß-induced insulin resistance by activating the proteasome-dependent degradation of PTEN. These findings provide an experimental background for the identification of novel molecular targets of icariin, which may help in the development of alternative therapeutic approaches for neurodegenerative diseases.

Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias.

Sentiment analysis is widely studied to extract opinions from user generated content (UGC), and various methods have been proposed in recent literature. However, these methods are likely to introduce sentiment bias, and the classification results tend to be positive or negative, especially for the lexicon-based sentiment classification methods. The existence of sentiment bias leads to poor performance of sentiment analysis. To deal with this problem, we propose a novel sentiment bias processing strategy which can be applied to the lexicon-based sentiment analysis method. Weight and threshold parameters learned from a small training set are introduced into the lexicon-based sentiment scoring formula, and then the formula is used to classify the reviews. In this paper, a completed sentiment classification framework is proposed. SentiWordNet (SWN) is used as the experimental sentiment lexicon, and review data of four products collected from Amazon are used as the experimental datasets. Experimental results show that the bias processing strategy reduces polarity bias rate (PBR) and improves performance of the lexicon-based sentiment analysis method.

Microblog sentiment analysis using social and topic context.

Analyzing massive user-generated microblogs is very crucial in many fields, attracting many researchers to study. However, it is very challenging to process such noisy and short microblogs. Most prior works only use texts to identify sentiment polarity and assume that microblogs are independent and identically distributed, which ignore microblogs are networked data. Therefore, their performance is not usually satisfactory. Inspired by two sociological theories (sentimental consistency and emotional contagion), in this paper, we propose a new method combining social context and topic context to analyze microblog sentiment. In particular, different from previous work using direct user relations, we introduce structure similarity context into social contexts and propose a method to measure structure similarity. In addition, we also introduce topic context to model the semantic relations between microblogs. Social context and topic context are combined by the Laplacian matrix of the graph built by these contexts and Laplacian regularization are added into the microblog sentiment analysis model. Experimental results on two real Twitter datasets demonstrate that our proposed model can outperform baseline methods consistently and significantly.