Assessing the Structural and Functional Similarity of Insulin Glargine Biosimilars

Background: A biosimilar product is expected to exhibit similar safety, efficacy, and quality as that of the approved reference product. Only a few reports of thorough evaluation of the quality of insulin glargine biosimilars are available in literature. Here, we examine the structural and functional similarity of biosimilars of insulin glargine, the first basal long-acting insulin analogue with respect to its innovator product (Lantus® from Sanofi Aventis). Methods: Structural similarity was established using mass spectrometry, chromatographic, and spectroscopic techniques. Stability was compared by performing accelerated thermal stress studies. Functional similarity was established via in vitro assay. Results: Biosimilar 4 exhibited greater content of high molecular weight species (HMWs) (0.80%) and related substances (RS) (0.45±0.06%) vs others (HMWs of 0.04% and RS of 0.17%). Biosimilars 1 and 3 exhibited higher rate of impurity generation (0.78% and 0.73% per week, respectively), as compared with other drug products (0.02% to 0.43% per week). Furthermore, %aggregation at 14 days was found to statistically correlate ( R2= 0.99, root mean square error (RMSE) = 0.095) with %aggregation at 0 day (linearly) and the number of months from expiry (nonlinearly), highlighting the overpowering impact of the latter. Conclusions: While an overall structural and functional similarity was observed across insulin glargine biosimilars with respect to the innovator product, low amounts of product-related variants were seen in some biosimilars and these impact product stability. The %aggregation at 14 days exhibits statistical correlation with %aggregation at 0 day and the number of months from expiry. The order of biosimilarity was denoted as Lantus®>Biosimilar 2>Biosimilar 4>Biosimilar 1>Biosimilar 3.

Anthropomorphic Metaphor in the English Veterinary Terminology

Introduction. The article is devoted to the presentation of the results of the study of metaphorization and the study of metaphorical terms, widely represented in the English terminology of veterinary medicine. The purpose of the article is to represent the features of the anthropomorphic metaphorical name in the English terminology of veterinary medicine. Materials and methods of research. The study of metaphorization as a way of forming English veterinary terms was conducted by us on the basis of lexicographic data recorded in English terminological dictionaries of veterinary medicine. Results of the research. The analysis of lexicographic material allowed to identify four donor domains that served as a source of metaphorical names in the terminology of veterinary medicine: HUMAN, LIVING ORGANISM, NATURAL FACT, ARTIFACT. Conceptual analysis of metaphorical terms of veterinary medicine revealed that one of the most productive metaphors used in the creation of terminological units is anthropomorphic. In anthropomorphic metaphorization, the names are transferred from the donor domain HUMAN to the recipient domain VETERINARY. The article attempts to consider the cognitive basis of anthropomorphic metaphor as one of the mechanisms of creation of veterinary terms in English. Based on the theory of conceptual metaphor, it was found that the sources of anthropomorphic metaphor are the biological characteristics of people, the names of body parts and properties of a living organism. Semantic groups of metaphorical terms formed on the basis of cognitive transfer of tokens related to the structure of the human body, its behavior, inherent qualities, life and way of life in the field of veterinary medicine based on external or functional similarity between donor and recipient domains are considered. Сonclusions. Thus, the study allows us to conclude that the terms-metaphors occupy a certain niche in the terminology of veterinary medicine in English and ensure their effective functioning in the language of veterinarians. Conceptual analysis of metaphorical terms of veterinary medicine revealed that one of the most productive is anthropomorphic metaphor. As a result of anthropomorphic metaphorization, new terms of veterinary medicine are formed on the basis of cognitive transfer of tokens that relate to the social characteristics of a person that determine his appearance, behavior or condition, in the field of veterinary medicine on the basis of external or functional similarity between donor and recipient domains.

TopoFun: a machine learning method to improve the functional similarity of gene co-expression modules

A comprehensive, accurate functional annotation of genes is key to systems-level approaches. As functionally related genes tend to be co-expressed, one possible approach to identify functional modules or supplement existing gene annotations is to analyse gene co-expression. We describe TopoFun, a machine learning method that combines topological and functional information to improve the functional similarity of gene co-expression modules. Using LASSO, we selected topological descriptors that discriminated modules made of functionally related genes and random modules. Using the selected topological descriptors, we performed linear discriminant analysis to construct a topological score that predicted the type of a module, random-like or functional-like. We combined the topological score with a functional similarity score in a fitness function that we used in a genetic algorithm to explore the co-expression network. To illustrate the use of TopoFun, we started from a subset of the Gene Ontology Biological Processes (GO-BPs) and showed that TopoFun efficiently retrieved genes that we omitted, and aggregated a number of novel genes to the initial GO-BP while improving module topology and functional similarity. Using an independent protein-protein interaction database, we confirmed that the novel genes gathered by TopoFun were functionally related to the original gene set.

Evaluating Quantitative Measures for Assessing Functional Similarity in Engineering Design

The development of example-based design support tools, such as those used for design-by-analogy, relies heavily on the computation of similarity between designs. Various vector- and graph-based similarity measures operationalize different principles to assess the similarity of designs. Despite the availability of various types of similarity measures and the widespread adoption of some, these measures have not been tested for cross-measure agreement, especially in a design context. In this paper, several vector- and graph-based similarity measures are tested across two datasets of functional models of products to explore the ways in which they find functionally similar designs. The results show that the network-based measures fundamentally operationalize functional similarity in a different way than vector-based measures. Based upon the findings, we recommend a graph-based similarity measure such as NetSimile in the early stages of design when divergence is desirable and a vector-based measure such as cosine similarity in a period of convergence, when the scope of the desired function implementation is clearer.

Aligning Human and Computational Evaluations of Functional Design Similarity

Function drives many early design considerations in product development. Therefore, finding functionally similar examples is important when searching for sources of inspiration or evaluating designs against existing technology. However, it is difficult to capture what people consider to be functionally similar and therefore, if measures that compare function directly from the products themselves are meaningful. In this work, we compare human evaluations of similarity to computationally determined values, shedding light on how quantitative measures align with human perceptions of functional similarity. Human perception of functional similarity is considered at two levels of abstraction: (1) the high-level purpose of a product, and (2) a detailed view of how the product works. Human evaluations of similarity are quantified by crowdsourcing 1360 triplet ratings at each functional abstraction, and then compared to similarity that is computed between functional models. We demonstrate how different levels of abstraction and the fuzzy line between what is considered “similar” and “similar enough” may impact how these similarity measures are utilized, finding that different measures better align with human evaluations along each dimension. The results inform how product similarity can be leveraged by designers. Therefore, applications lie in creativity support tools, such as those used for design-by-analogy, or future computational methods in design that incorporate product function in addition to form.

Functional similarity, not phylogenetic relatedness, predicts the relative strength of competition

Predicting the outcome and strength of species interactions is a central goal of community ecology. Researchers have proposed that outcomes of species interactions (competitive exclusion and coexistence) are a function of both phylogenetic relatedness and functional similarity. Studies relating phylogenetic distance to competition strength have shown conflicting results. Work investigating the role of phylogenetic relatedness and functional similarity in driving competitive outcomes has been limited in terms of the breadth of taxa and ecological contexts examined, which makes the generality of these studies unclear. Consequently, we gathered 1,748 pairwise competition effect sizes from 269 species and 424 unique species pairs with divergence times ranging from 1.14 to 1,275 million years and used meta-regression and model selection approaches to investigate the importance of phylogenetic relatedness and functional similarity to competition across ecological contexts. We revealed that functional similarity, but not phylogenetic relatedness, predicted the relative strength of interspecific competition (defined as the strength of interspecific competition relative to intraspecific competition). Further, we found that the presence of predators, certain habitats, increasing density of competitors, and decreasing spatial grain of experiments were all associated with more intense interspecific competition relative to intraspecific competition. Our results demonstrate that functional similarity, not phylogenetic relatedness, may explain patterns of competition-associated community assembly, highlighting the value of trait-based approaches in clarifying biotic assembly dynamics.