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A biosimilar is a biological medicinal product that is comparable to a reference medicinal product in terms of quality, safety, and efficacy. SB4 was developed as a biosimilar to Enbrel® (etanercept) and was approved as Benepali®, the first biosimilar of etanercept licensed in the European Union (EU). The quality assessment of SB4 was performed in accordance with the ICH comparability guideline and the biosimilar guidelines of the European Medicines Agency and Food and Drug Administration. Extensive structural, physicochemical, and biological testing was performed with state-of-the-art technologies during a side-by-side comparison of the products. Similarity of critical quality attributes (CQAs) was evaluated on the basis of tolerance intervals established from quality data obtained from more than 60 lots of EU-sourced and US-sourced etanercept. Additional quality assessment was focused on a detailed investigation of immunogenicity-related quality attributes, including hydrophobic variants, high-molecular-weight (HMW) species, N-glycolylneuraminic acid (NGNA), and α-1,3-galactose. This comprehensive characterization study demonstrated that SB4 is highly similar to the reference product, Enbrel®, in structural, physicochemical, and biological quality attributes. In addition, the levels of potential immunogenicity-related quality attributes of SB4 such as hydrophobic variants, HMW aggregates, and α-1,3-galactose were less than those of the reference product.

Knowledge graph embedding aims to learn distributed representations for entities and relations, and is proven to be effective in many applications. Crossover interactions -bi-directional effects between entities and relations -help select related information when predicting a new triple, but haven't been formally discussed before. In this paper, we propose CrossE, a novel knowledge graph embedding which explicitly simulates crossover interactions. It not only learns one general embedding for each entity and relation as most previous methods do, but also generates multiple triple specific embeddings for both of them, named interaction embeddings. We evaluate embeddings on typical link prediction tasks and find that CrossE achieves state-of-the-art results on complex and more challenging datasets. Furthermore, we evaluate embeddings from a new perspective -giving explanations for predicted triples, which is important for real applications. In this work, an explanation for a triple is regarded as a reliable closed-path between the head and the tail entity. Compared to other baselines, we show experimentally that CrossE, benefiting from interaction embeddings, is more capable of generating reliable explanations to support its predictions. tail entity), or ( h, r , t ) in short. They are useful resources for many AI tasks such as web search [33] and question answering [43]. Knowledge graph embedding (KGE) learns distributed representations [11] for entities and relations, called entity embeddings and relation embeddings. The embeddings are meant to preserve the information in a KG, and are represented as low-dimensional dense vectors or matrices in continuous vector spaces. Many KGEs, such as tensor factorization based RESCAL [26], translation-based TransE [4], neural tensor network NTN [30] and linear mapping method DistMult [41], have been proposed and are proven to be effective in many applications like knowledge graph completion, question answering and relation extraction.Despite their success in modeling KGs, none of existing KGEs has formally discussed crossover interactions, bi-directional effects between entities and relations including interactions from relations to entities and interactions from entities to relations. Crossover interactions are quite common and helpful for related information selection, related information selection is necessary when predicting new triples because there are various information about each entity and relation in KGs. X Z M Y Q T S Figure 1: A hypothetical knowledge graph. Nodes and edges represent entities and relations. Solid lines represent existing triples and dashed lines represent triples to be predicted.

Everywhere in our surroundings we increasingly come in contact with nanostructures that have distinctive complex shape features on a scale comparable to the particle itself. Such shape ensembles can be made by modern nano-synthetic methods and many industrial processes. With the ever growing universe of nanoscale shapes, names such as "nanoflowers" and "nanostars" no longer precisely describe or characterise the distinct nature of the particles. Here we capture and digitise particle shape information on the relevant size scale and create a condensed representation in which the essential shape features can be captured, recognized and correlated. We find the natural emergence of intrinsic shape groups as well-defined ensemble distributions and show how these may be analyzed and interpreted to reveal novel aspects of our nanoscale shape environment. We show how these ideas may be applied to the interaction between the nanoscale-shape and the living universe and provide a conceptual framework for the study of nanoscale shape biological recognition and identity.

The whitebacked planthopper, Sogatella furcifera (Horváth), and small brown planthopper, Laodelphax striatellus (Fallén), both are important crop pests throughout China, especially in rice. Application of chemical insecticides is the major control practice. Consequently, insecticide resistance has become an urgent issue. In this study, resistance levels to six conventional insecticides were evaluated for these two species collected from major occurring areas of China. Additionally, imidacloprid- (resistance ratio [RR] = 10.4-fold) and buprofezin (RR = 15.1-fold)-resistant strains of whitebacked planthopper were obtained through laboratory selections for cross-resistance profiling and synergism assessment to understand resistance mechanisms. The results showed that all tested populations of both species exhibited low to high levels of resistance to chlorpyrifos, while remaining susceptible to thiamethoxam. Three of the 14 whitebacked planthopper populations showed low to moderate resistance to imidacloprid, while all small brown planthopper populations reminded susceptible. All small brown planthopper and whitebacked planthopper (except one) populations showed at least moderate resistance (RR = 10.1-271.1) to buprofezin. All small brown planthopper populations remained susceptible to pymetrozine and nitenpyram, and all whitebacked planthopper populations remained susceptible to isoprocarb. The imidacloprid-resistant whitebacked planthopper strain showed no significant cross-resistance to other tested insecticides. However, the buprofezin-resistant strain exhibited a low-level cross-resistance (CR = 3.1) to imidacloprid. Piperonyl butoxide, triphenyl phosphate, and diethylmaleate displayed no synergism effect on the resistant whitebacked planthopper strains.

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Background Airborne particulate matter (PM) may induce epigenetic changes that potentially lead to chronic diseases. Histone modifications regulate gene expression by influencing chromatin structure that can change gene expression status. We evaluated whether traffic-derived PM exposure is associated with four types of environmentally inducible global histone H3 modifications. Methods The Beijing Truck Driver Air Pollution Study included 60 truck drivers and 60 office workers examined twice, 1–2 weeks apart, for ambient PM10 (both day-of and 14-day average exposures), personal PM2.5, black carbon (BC), and elemental components (potassium, sulfur, iron, silicon, aluminum, zinc, calcium, and titanium). For both PM10 measures, we obtained hourly ambient PM10 data for the study period from the Beijing Municipal Environmental Bureau’s 27 representatively distributed monitoring stations. We then calculated a 24 h average for each examination day and a moving average of ambient PM10 measured in the 14 days prior to each examination. Examinations measured global levels of H3 lysine 9 acetylation (H3K9ac), H3 lysine 9 tri-methylation (H3K9me3), H3 lysine 27 tri-methylation (H3K27me3), and H3 lysine 36 tri-methylation (H3K36me3) in blood leukocytes collected after work. We used adjusted linear mixed-effect models to examine percent changes in histone modifications per each μg/m3 increase in PM exposure. Results In all participants each μg/m3 increase in 14-day average ambient PM10 exposure was associated with lower H3K27me3 (β=−1.1%, 95% CI: −1.6, −0.6) and H3K36me3 levels (β=−0.8%, 95% CI: −1.4, −0.1). Occupation-stratified analyses showed associations between BC and both H3K9ac and H3K36me3 that were stronger in office workers (β=4.6%, 95% CI: 0.9, 8.4; and β=4.1%, 95% CI: 1.3; 7.0 respectively) than in truck drivers (β=0.1%, 95% CI: −1.3, 1.5; and β=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction < 0.05). Sex-stratified analyses showed associations between examination-day PM10 and H3K9ac, and between BC and H3K9me3, were stronger in women (β=10.7%, 95% CI: 5.4, 16.2; and β=7.5%, 95% CI: 1.2, 14.2, respectively) than in men (β=1.4%, 95% CI: −0.9, 3.7; and β=0.9%, 95% CI: −0.9, 2.7, respectively; both pinteraction < 0.05). We observed no associations between personal PM2.5 or elemental components and histone modifications. Conclusions Our results suggest a possible role of global histone H3 modifications in effects of traffic-derived PM exposures, particularly BC exposure. Future studies should assess the roles of these modifications in human diseases and as potential mediators of air pollution-induced disease, in particular BC exposure.

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