Recent advances and challenges in the recovery and purification of cellular exosomes

Exosomes are nanovesicles secreted by most cellular types that carry important biochemical compounds throughout the body with different purposes, playing a preponderant role in cellular communication. Because of their structure, physicochemical properties and stability, recent studies are focusing in their use as nanocarriers for different therapeutic compounds for the treatment of different diseases ranging from cancer to Parkinson's disease. However, current bioseparation protocols and methodologies are selected based on the final exosome application or intended use and present both advantages and disadvantages when compared among them. In this context, this review aims to present the most important technologies available for exosome isolation while discussing their advantages and disadvantages and the possibilities of being combined with other strategies. This is critical since the development of novel exosome‐based therapeutic strategies will be constrained to the effectiveness and yield of the selected downstream purification methodologies for which a thorough understanding of the available technological resources is needed.     

A Comparative Analysis of Machine Learning Techniques for Muon Count in UHECR Extensive Air-Showers

The main goal of this work is to adapt a Physics problem to the Machine Learning (ML) domain and to compare several techniques to solve it. The problem consists of how to perform muon count from the signal registered by particle detectors which record a mix of electromagnetic and muonic signals. Finding a good solution could be a building block on future experiments. After proposing an approach to solve the problem, the experiments show a performance comparison of some popular ML models using two different hadronic models for the test data. The results show that the problem is suitable to be solved using ML as well as how critical the feature selection stage is regarding precision and model complexity.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

Highly Selective Copper‐Catalyzed Asymmetric [3+2] Cycloaddition of Azomethine Ylides with Acyclic 1,3‐Dienes

The first examples of the catalytic asymmetric 1,3‐dipolar cycloaddition of azomethine ylides with acyclic activated 1,3‐dienes (and 1,3‐enynes) are described. Under copper catalysis, a selective cycloaddition at the terminal γ,δ‐C?C bond is observed. In addition, depending on the ligand used, either the exo or the endo adduct can be obtained with high selectivity. Under appropriate reaction conditions, the acyclic 1,6‐addition product is detected, suggesting a stepwise mechanism. The resulting C4‐alkenyl‐substituted pyrrolidines are suitable substrates for further access to polycyclic systems, as highlighted by the preparation of hexahydrochromeno[4,3‐b]pyrrole and the tetracyclic core of the alkaloid gracilamine.     

Excited-State Dynamics of Thienoguanosine,an Isomorphic Highly Fluorescent Analogue of Guanosine

Thienoguanosine (^thG) is an isomorphic analogue of guanosine with promising potentialities as fluorescent DNA label. As a free probe in protic solvents, ^thG exists in two tautomeric forms, identified as the H1, being the only one observed in nonprotic solvents, and H3 keto–amino tautomers. We herein investigate the photophysics of ^thG in solvents of different polarity, from water to dioxane, by combining time-resolved fluorescence with PCM/TD-DFT and CASSCF calculations. Fluorescence lifetimes of 14.5–20.5 and 7–13 ns were observed for the H1 and H3 tautomers, respectively, in the tested solvents. In methanol and ethanol, an additional fluorescent decay lifetime (≈3 ns) at the blue emission side (λ≈430 nm) as well as a 0.5 ns component with negative amplitude at the red edge of the spectrum, typical of an excited-state reaction, were observed. Our computational analysis explains the solvent effects observed on the tautomeric equilibrium. The main radiative and nonradiative deactivation routes have been mapped by PCM/TD-DFT calculations in solution and CASSCF in the gas phase. The most easily accessible conical intersection, involving an out-of plane motion of the sulfur atom in the five-membered ring of ^thG, is separated by a sizeable energy barrier (≥0.4 eV) from the minimum of the spectroscopic state, which explains the large experimental fluorescence quantum yield.     

Exploring mathematical connections of pre-university students through tasks involving rates of change

This paper reports the results of a research exploring the mathematical connections of pre-university students while they solving tasks which involving rates of change. We assume mathematical connections as a cognitive process through which a person finds real relationships between two or more ideas, concepts, definitions, theorems, procedures, representations or meanings or with other disciplines or the real-world. Four tasks were proposed to the 33 pre-university students that participated in this research; the central concept of the first task is the slope, the last three tasks contain concepts like velocity, speed and acceleration. Task-based interviews were conducted to collect data and later analysed with thematic analysis. Results showed most of the students made mathematical connections of the procedural type, the mathematical connections of the common features type are made in smaller quantities and the mathematical connection of the generalization type is scarcely made. Furthermore, students considered slope as a concept disconnected from velocity, speed and acceleration.