José M. Alonso

Gold catalyzed oxycyclizations of alkynols and alkyndiols

Alkynols and alkyndiols represent excellent building blocks for oxycyclization reactions, leading to a large number of different cyclic structures in one single step. Recently, the use of gold salts and gold complexes has been introduced as an alternative to the traditional methods, providing mild reaction conditions and high group compatibility. This overview focuses on the most recent achievements on gold-catalyzed oxycyclizations, both from alkynols and alkyndiols, and their use in different cascade processes and total synthesis.

Evidence for the involvement of ethylene in the expression of specific RNAs during maturation of the orange, a non-climacteric fruit.

Twelve cDNAs corresponding to mRNAs inducible by ethylene were isolated by differential screening of a cDNA library from ethylene-treated Citrus sinensis fruits. Northern analysis of RNA extracted from flavedo of ethylene-treated fruits and from fruits at different maturation stages showed that some of the mRNAs corresponding to these cDNAs were regulated both by ethylene treatment and during fruit maturation. The effect of exogenous ethylene on leaves and of endogenous ethylene on flowers showed that gene induction was not restricted to the flavedo tissue. The possible role of ethylene during maturation of the non-climacteric Citrus fruit is discussed.

Gold-Catalyzed Cyclizations of Alkynol-Based Compounds: Synthesis of Natural Products and Derivatives

The last decade has witnessed dramatic growth in the number of reactions catalyzed by gold complexes because of their powerful soft Lewis acid nature. In particular, the gold-catalyzed activation of propargylic compounds has progressively emerged in recent years. Some of these gold-catalyzed reactions in alkynes have been optimized and show significant utility in organic synthesis. Thus, apart from significant methodology work, in the meantime gold-catalyzed cyclizations in alkynol derivatives have become an efficient tool in total synthesis. However, there is a lack of specific review articles covering the joined importance of both gold salts and alkynol-based compounds for the synthesis of natural products and derivatives. The aim of this Review is to survey the chemistry of alkynol derivatives under gold-catalyzed cyclization conditions and its utility in total synthesis, concentrating on the advances that have been made in the last decade, and in particular in the last quinquennium.

Carbocyclization versus oxycyclization on the metal-catalyzed reactions of oxyallenyl C3-linked indoles.

The preparation of previously unknown (indol-3-yl)-α-allenols and -allenones was accomplished from indole-3-carbaldehydes, through indium-mediated Barbier allenylation reaction taking advantage of the N-(2-pyridyl)sulfonyl group. Metal-catalyzed cyclizations of oxyallenyl C3-linked indoles proceeded in two ways depending on the presence or absence of the N-(2-pyridyl)sulfonyl group. For allenols, gold-catalyzed oxycyclization occurred in the presence of the protecting group; in the absence of the protecting group, palladium- and gold-catalyzed benzannulations operated. On the contrary, under gold catalysis furyl-indoles were obtained as exclusive products from NH-allenones, while 5-endo carbocyclization adducts were the major components starting from N-SO2py-protected allenones. These cyclization reactions have been developed experimentally, and their mechanisms have additionally been investigated by a computational study.

Embedding HILK in a three-objective evolutionary algorithm with the aim of modeling highly interpretable fuzzy rule-based classifiers

HILK (Highly Interpretable Linguistic Knowledge) is a fuzzy modeling methodology especially thought for designing interpretable fuzzy rule-based systems. As starting point, it trusts on a domain expert able to define the most influential variables along with the most suitable number of linguistic terms for each of them. However, such task is not easy because problems often involve too many variables. To tackle with this problem, present paper proposes embedding HILK in a three-objective evolutionary algorithm (HILKMO) with the aim of making genetic feature selection and fuzzy partition learning. The use of two-objective (maximizing accuracy and interpretability) evolutionary algorithm has become very popular and effective when dealing with modeling interpretable fuzzy systems. There are also works dealing with three objectives but two of them are usually related to interpretability regarding only the readability of the system description. We have already emphasized, in previous works, the importance of addressing also the system comprehensibility. Therefore, the main contribution of this work is introducing two contradictory goals for characterizing interpretability: maximizing readability of the system explanation. The former objective prefers rules as compact as possible, while the latter one favors the use of rules with low interaction among them because rule interaction is difficult to explain. Both objectives are contradictory because the more compact the rule base, the higher the chance of having rules simultaneously fired by the same input vector. We have chosen NSGA-II as multi-objective evolutionary algorithm and our proposal is tested in the well-known GLASS benchmark problem.

Palladium-catalyzed carbocyclization–cross-coupling reactions of two different allenic moieties: synthesis of 3-(buta-1,3-dienyl) carbazoles and mechanistic insights

A palladium-catalyzed chemo-, regio- and stereoselective carbocyclization-cross-coupling sequence of two different α-allenols to afford 3-(E-buta-1,3-dienyl) carbazoles is reported.

Multi-objective design of highly interpretable fuzzy rule-based classifiers with semantic cointension

Although recently there has been many papers dealing with how to characterize and assess interpretability, there is still a lot of work to be done. Interpretability assessment is usually addressed by evaluating the complexity and/or readability of fuzzy rule-based systems. However, comprehensibility is usually not taken into account because it implies more cognitive aspects which are difficult to formalize and to deal with. In this work we show the importance of considering not only readability but also comprehensibility during the design process of fuzzy systems. We introduce the use of a novel index for evaluating comprehensibility in the context of a three-objective evolutionary framework for designing highly interpretable fuzzy rule-based classifiers. It is named as logical view index (LVI) and it is based on a semantic cointension approach. The proposed evolutionary algorithm consists of embedding the HILK (Highly Interpretable Linguistic Knowledge) fuzzy modeling methodology into the classical NSGA-II with the aim of maximizing accuracy, readability, and comprehensibility of the generated fuzzy rule-based classifiers. Our proposal is tested in the well-known PIMA benchmark problem which corresponds to a medical diagnosis problem where interpretability is a strong requirement.

Rapid entry to enantiopure polycyclic β-lactams via intramolecular nitrone-alkene cycloaddition of 2-azetidinone-tethered alkenylaldehydes

Abstract New enantiomerically pure fused 2 or bridged 3 polycyclic β-lactam systems are regio- and stereoselectively prepared via intramolecular nitrone-alkene cycloaddition of 2-azetidinone-tethered alkenyl-aldehydes 1. The regioselectivity of the cycloaddition can be tuned by moving the alkene substituent from N1 to C3 on the 2-azetidinone ring.

Iodine recycling via 1,3-migration in iodoindoles under metal catalysis

3-Substituted (indol-2-yl)-α-allenols show divergent patterns of reactivity under metal catalysis. An unprecedented intramolecular 1,3-iodine migration is described.

Highly Interpretable Linguistic Knowledge Bases Optimization: Genetic Tuning versus Solis-Wetts. Looking for a good interpretability-accuracy trade-off

This work shows how to achieve a good interpretability-accuracy trade-off through keeping the strong fuzzy partition property along the whole fuzzy modeling process. First, a small compact knowledge base is built. It is highly interpretable and reasonably accurate. Second, an optimization procedure, which only affects the fuzzy partitions defining the system variables, is carried out. It improves the system accuracy while preserving the system interpretability. Two optimization strategies are compared: Solis-Wetts, a local search based strategy; and Genetic Tuning, a global search based strategy. Results obtained in a well-known benchmark medical classification problem, related to breast cancer diagnosis, show that our methodology is able to achieve knowledge bases with high interpretability and accuracy comparable to that obtained by other methodologies.