Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Coenzyme Q10: Novel Formulations and Medical Trends

The aim of this review is to shed light over the most recent advances in Coenzyme Q₁₀ (CoQ₁₀) applications as well as to provide detailed information about the functions of this versatile molecule, which have proven to be of great interest in the medical field. Traditionally, CoQ₁₀ clinical use was based on its antioxidant properties; however, a wide range of highly interesting alternative functions have recently been discovered. In this line, CoQ₁₀ has shown pain-alleviating properties in fibromyalgia patients, a membrane-stabilizing function, immune system enhancing ability, or a fundamental role for insulin sensitivity, apart from potentially beneficial properties for familial hypercholesterolemia patients. In brief, it shows a remarkable amount of functions in addition to those yet to be discovered. Despite its multiple therapeutic applications, CoQ₁₀ is not commonly prescribed as a drug because of its low oral bioavailability, which compromises its efficacy. Hence, several formulations have been developed to face such inconvenience. These were initially designed as lipid nanoparticles for CoQ₁₀ encapsulation and distribution through biological membranes and eventually evolved towards chemical modifications of the molecule to decrease its hydrophobicity. Some of the most promising formulations will also be discussed in this review.     

Microtubule Destabilizing Sulfonamides as an Alternative to Taxane-Based Chemotherapy

Pan-Gyn cancers entail 1 in 5 cancer cases worldwide, breast cancer being the most commonly diagnosed and responsible for most cancer deaths in women. The high incidence and mortality of these malignancies, together with the handicaps of taxanes—first-line treatments—turn the development of alternative therapeutics into an urgency. Taxanes exhibit low water solubility that require formulations that involve side effects. These drugs are often associated with dose-limiting toxicities and with the appearance of multi-drug resistance (MDR). Here, we propose targeting tubulin with compounds directed to the colchicine site, as their smaller size offer pharmacokinetic advantages and make them less prone to MDR efflux. We have prepared 52 new Microtubule Destabilizing Sulfonamides (MDS) that mostly avoid MDR-mediated resistance and with improved aqueous solubility. The most potent compounds, N-methyl-N-(3,4,5-trimethoxyphenyl-4-methylaminobenzenesulfonamide 38, N-methyl-N-(3,4,5-trimethoxyphenyl-4-methoxy-3-aminobenzenesulfonamide 42, and N-benzyl-N-(3,4,5-trimethoxyphenyl-4-methoxy-3-aminobenzenesulfonamide 45 show nanomolar antiproliferative potencies against ovarian, breast, and cervix carcinoma cells, similar or even better than paclitaxel. Compounds behave as tubulin-binding agents, causing an evident disruption of the microtubule network, in vitro Tubulin Polymerization Inhibition (TPI), and mitotic catastrophe followed by apoptosis. Our results suggest that these novel MDS may be promising alternatives to taxane-based chemotherapy in chemoresistant Pan-Gyn cancers.     

ProVoc: An app to train vocabulary depth in order to foster children's reading comprehension

Many studies have demonstrated the crucial role of vocabulary in predicting reading performance in general. More recent work has indicated that one particular facet of vocabulary (its depth) is more closely related to language comprehension, especially inferential comprehension. On this basis, we developed a training application to specifically improve vocabulary depth. The objective of this study was to test the effectiveness of a mobile application designed to improve vocabulary depth. The effectiveness of this training was examined on 3rd and 4th grade children's vocabulary (breadth and depth), decoding and comprehension performances. A randomized waiting-list control paradigm was used in which an experimental group first received the intervention during the first 4 weeks (between pretest and post-test1), thereafter, a waiting control group received the training for the next 4 weeks (between postest1 and posttest2). Results showed that the developed application led to significant improvements in terms of vocabulary depth performance, as well as a significant transfer effect to reading comprehension. However, we did not observe such a beneficial effect on either vocabulary breadth or written word identification. These results are discussed in terms of the links between vocabulary depth and comprehension, and the opportunities the app presents for remedying language comprehension deficits in children.     

A local and global tour on MOMoT

Software and Systems Modeling - Many model transformation scenarios require flexible execution strategies as they should produce models with the highest possible quality. At the same time,...     

One-Pot Methods for the Protection and Assembly of Sugars

In recent years, there has been rapid expansion of glycan synthesis, fueled by the recognition that the structural complexity of sugars translates to a myriad of biological functions. Such chemical syntheses involve many challenges, mostly due to the regio- and stereochemical aspects of glycosidic bond formation. One-pot strategies were developed to assist in attaining faster and more economical access to the glycan constructs. In this front, achievements in protecting group manipulation, glycosylation, and combinations of these have been reported. Protecting group manipulations in one pot take advantage of the reaction compatibility of commonly used transformations, many of which occur in high regioselectivity. Sequential glycosylations, on the other hand, rely on leaving group orthogonalities and reactivity tuning, as well as the preactivation technique. Altogether, these approaches offer attractive means to the much needed glycan structures and, consequently, help usher in advances in glycoscience.     

Intersecting Xenobiology and Neometabolism To Bring Novel Chemistries to Life

The diversity of life relies on a handful of chemical elements (carbon, oxygen, hydrogen, nitrogen, sulfur and phosphorus) as part of essential building blocks; some other atoms are needed to a lesser extent, but most of the remaining elements are excluded from biology. This circumstance limits the scope of biochemical reactions in extant metabolism – yet it offers a phenomenal playground for synthetic biology. Xenobiology aims to bring novel bricks to life that could be exploited for (xeno)metabolite synthesis. In particular, the assembly of novel pathways engineered to handle nonbiological elements (neometabolism) will broaden chemical space beyond the reach of natural evolution. In this review, xeno-elements that could be blended into nature's biosynthetic portfolio are discussed together with their physicochemical properties and tools and strategies to incorporate them into biochemistry. We argue that current bioproduction methods can be revolutionized by bridging xenobiology and neometabolism for the synthesis of new-to-nature molecules, such as organohalides.     

On the use of 2-D coding techniques for ECG signals.

This paper discusses the convenience of using two-dimensional (2-D) coding techniques for the compression of electrocardiogram (ECG) signals. These signals present a very clear periodicity that can be exploited by the use of a 2-D time/frequency transform to decorrelate it as much as possible. A brief theoretical approach is given to justify the use of this technique, and a comparison is made between a 2-D and a one-dimensional (1-D) uniform quantization scenarios. The influence of the error as well as the frame size on the estimation of the fundamental period is studied.     

A multiwinding modeling method for high frequency transformers and inductors

This paper presents a method to obtain an electric model for transformers and inductors, including both frequency and geometry effects in the windings, which can be linked with existing core models. One-dimensional distributions for magnetic and electric fields are assumed, and from Maxwell's equations an equivalent electric circuit is easily obtained. This equivalent circuit has been included in analog simulators (Spice, AnalogWorkBench, Saber ...), and comparisons between measured and simulated results are shown, both in time domain and in AC sweep, which verify the model accuracy. The model described in this paper allows designers to deal with key issues in the design of high-frequency magnetic components (copper losses, leakage inductance, skin and proximity effects) by using analog simulators, which are usually more familiar to them than finite-element analysis tools.