Nano materials generate great benefits as well as new potential risks. Animal studies and in vitro experiments show that nanoparticles can result in lung damage and other toxicity, but no reports on the clinical toxicity in humans due to nanoparticles have yet been made.The present study aimed to examine the relationship between a group of workers' presenting with mysterious symptomatic findings and their nanoparticle exposure.Seven young female workers (aged 18-47 yrs), exposed to nanoparticles for 5-13 months, all with shortness of breath and pleural effusions were admitted to hospital. Immunological tests, examinations of bacteriology, virology and tumour markers, bronchoscopy, internal thoracoscopy and video-assisted thoracic surgery were performed. Surveys of the workplace, clinical observations and examinations of the patients were conducted.Polyacrylate, consisting of nanoparticles, was confirmed in the workplace. Pathological examinations of patients' lung tissue displayed nonspecific pulmonary inflammation, pulmonary fibrosis and foreign-body granulomas of pleura. Using transmission electron microscopy, nanoparticles were observed to lodge in the cytoplasm and caryoplasm of pulmonary epithelial and mesothelial cells, but are also located in the chest fluid. These cases arouse concern that long-term exposure to some nanoparticles without protective measures may be related to serious damage to human lungs.

Aims/hypothesis A meta-analysis was performed to assess the association of C47T (rs4880) (also called Val16Ala) polymorphism in SOD2 gene with reduced risk of diabetes mellitus, including type 1 and type 2 diabetes, and diabetic microvascular complications (DMI) including diabetic nephropathy, diabetic retinopathy and diabetic polyneuropathy. Methods A comprehensive search was conducted to identify all case-control or cohort design studies of the abovementioned associations. The fixed or random effect pooled measure was selected on the basis of homogeneity test among studies. Heterogeneity among studies was evaluated using the I 2 . Meta-regression and the 'leave one out' sensitive analysis of Patsopoulos et al. were used to explore potential sources of between-study heterogeneity. Publication bias was estimated using modified Egger's linear regression test as proposed by Harbord et al. Results Seventeen articles were included. After excluding articles that deviated from Hardy-Weinberg equilibrium in cases and/or in controls, and were also the key contributors to between-study heterogeneity, the meta-analysis showed a significant association of the C allele with reduced risk of DMI in dominant (OR 0.788, 95% CI 0.680-0.914), recessive (OR 0.808, 95% CI 0.685-0.953) and codominant (OR 0.828, 95% CI 0.751-0.913) models. It also showed a significant association with reduced risk of diabetic nephropathy in the dominant model (OR 0.801,, and reduced risk of diabetic retinopathy in the dominant (OR 0.601, 95% CI 0.423-0.855), recessive (OR 0.548, 95% CI 0.369-0.814) and codominant (OR 0.651, 95% CI 0.517-0.820) models. Conclusions/interpretation The meta-analysis suggested that C allele of C47T polymorphism in SOD2 gene has protective effects on risk of DMI, diabetic nephropathy and diabetic retinopathy. This risk needs to be confirmed by further studies.

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The identification of the TLRs as key sensors of microbial infection has presented a series of new targets for drug development. The TLRs are linked to the most powerful inflammatory pathways in mammals. The question arises from the start: do we wish to stimulate TLR signaling in order to eradicate specific infections and/or neoplastic diseases? Or do we wish to block TLR signaling to treat inflammatory diseases? If we accept that it would be useful to modulate TLR signaling, the next step is to identify the correct molecular target(s) for the task. Perhaps it might even be possible to exercise selectivity, modulating some aspects of TLR signaling and not others. Classical and reverse genetic analyses offer insight into the possibilities that exist, and point to specific checkpoints within signaling pathways at which modulation might normally be imposed.

Abstract.Chemotherapy is an important treatment modality for gastric cancer, and multidrug resistance (MDR) represents a major obstacle for successful cancer chemotherapy. There is a lack of research on whether microRNA (miR)-30a regulation affects the chemosensitivity of resistant gastric cancer cells, and mechanisms underlying the effects of miR-30a on drug resistance and cell autophagy require further investigation. In the present study, the expression of miR-30a and its effects in cisplatin (CDDP)-resistant human gastric cancer cells were investigated. A CDDP-resistant variant of the SGC-7901 cell line (SGC-7901/CDDP) was established by exposing the cells to gradually increasing drug concentrations, and miR-30a expression was detected by reverse transcription-semi quantitative polymerase chain reaction (RT-sqPCR). To examine the effect of miR-30a expression in the SGC-7901/CDDP cells, miR30a mimics or negative control miRNA were transfected into the cells, and a Cell Counting Kit-8 assay was performed to analyze the chemosensitivity of the different cell groups. RT-sqPCR and western blot analysis were also used to measure MDR1 mRNA and P-glycoprotein expression, and the light chain (LC)3-II/LC3-I ratio. Furthermore, apoptosis induced by the chemotherapeutic CDDP in the different groups was assessed using flow cytometry. The results demonstrated that low expression of miR-30a was associated with chemoresistance in gastric cancer cells, and in the chemoresistant cell line SGC7901/CDDP, CDDP-induced apoptosis was weakened. Additionally, it was demonstrated that the LC3-II/LC3-I ratio was elevated in SGC7901/CDDP cells compared with chemosensitive SGC7901 cells (P<0.001), which could be attenuated by upregulating miR-30a expression (P<0.001 vs. SGC7901/CDDP control cells). These results suggested that autophagy may contribute to drug resistance in gastric cancer cells, and that the reduction of LC3-II in response to miR-30a overexpression may inhibit chemoresistance-associated autophagy in gastric cancer cells.

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Purpose Educational data mining (EDM) and learning analytics, which are highly related subjects but have different definitions and focuses, have enabled instructors to obtain a holistic view of student progress and trigger corresponding decision-making. Furthermore, the automation part of EDM is closer to the concept of artificial intelligence. Due to the wide applications of artificial intelligence in assorted fields, the authors are curious about the state-of-art of related applications in Education. Design/methodology/approach This study focused on systematically reviewing 1,219 EDM studies that were searched from five digital databases based on a strict search procedure. Although 33 reviews were attempted to synthesize research literature, several research gaps were identified. A comprehensive and systematic review report is needed to show us: what research trends can be revealed and what major research topics and open issues are existed in EDM research. Findings Results show that the EDM research has moved toward the early majority stage; EDM publications are mainly contributed by “actual analysis” category; machine learning or even deep learning algorithms have been widely adopted, but collecting actual larger data sets for EDM research is rare, especially in K-12. Four major research topics, including prediction of performance, decision support for teachers and learners, detection of behaviors and learner modeling and comparison or optimization of algorithms, have been identified. Some open issues and future research directions in EDM field are also put forward. Research limitations/implications Limitations for this search method include the likelihood of missing EDM research that was not captured through these portals. Originality/value This systematic review has not only reported the research trends of EDM but also discussed open issues to direct future research. Finally, it is concluded that the state-of-art of EDM research is far from the ideal of artificial intelligence and the automatic support part for teaching and learning in EDM may need improvement in the future work.

Asymmetric and semi-symmetric amphiphilic diblock copolymers polystyrene-block-poly (dimethylaminoethyl methacrylate) (PS-b-PDMAEMA) with the same PS block length of 62 repeat units and quite short (3 repeat units) or equivalent (47 repeat units) length of PDMAEMA have been prepared simply by varying the ratio of the bromine-terminated macroinitiator polystyrene (PS-Br) to DMAEMA using atom transfer radical polymerization (ATRP). The chemical structures and compositions of the PS-b-PDMAEMA block copolymers are studied by nuclear magnetic resonance (NMR) spectroscopy, gel permeation chromatography (GPC), and elementary analysis (EA). The self-assembly behaviors of copolymers in N,N-dimethyl formamide (DMF) with different pH and dioxane/water binary solvent mixture by direct dissolution method (DD), are studied by transmission electron microscopy (TEM), electron diffracting analysis (EDA), and energy-dispersive analysis of X-rays (EDAX) techniques. Transmission electron microscopy results suggest that asymmetric block copolymer PS62-b-PDMAEMA3 (the numbers in the form of footnotes represent repeated units of each monomer in the copolymer) can form spherical core-shell micelles, large compound reverse micelles (LCRMs), hexagonal/rhombic phases, reverse hexagonal/rhombic phases, vesicles, reverse vesicles and necklace-like reverse micelles, controlled by common or selective solvent and pH, while most of the aggregates of semi-symmetric PS62-b-PDMAEMA47 are simply spherical, such as spherical core-shell micelles and reverse spherical core-shell micelles, besides hexagonal/rhombic phases. All above structures are controlled by three components of the free energy of aggregation: core-chain stretching, interfacial energy and intercoronal chain interaction