Joaquín Jordán

Bio: Joaquín Jordán is an academic researcher from University of Castilla–La Mancha. The author has contributed to research in topics: Mitochondrion & Programmed cell death. The author has an hindex of 45, co-authored 154 publications receiving 12336 citations. Previous affiliations of Joaquín Jordán include University of Chicago & Universidad Miguel Hernández de Elche.

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

The PI 3-kinase/Akt signaling pathway delivers an anti-apoptotic signal.

Abstract: Serum and certain growth factors have the ability to inhibit programmed cell death (apoptosis) and promote survival. The mechanism by which growth factors deliver an anti-apoptotic signal and the mechanism by which this survival signal is uncoupled from mitogenesis are not clear. We studied five downstream effectors of growth factor receptors--Ras, Raf, Src, phosphoinositide 3-kinase (PI 3-kinase), and Akt (PKB)--for their abilities to block apoptosis. Activated forms of Ras, Raf, and Src, although transforming, were not sufficient to deliver a survival signal upon serum withdrawal. In contrast, inhibition of PI 3-kinase accelerated apoptosis, and an activated form of the serine/threonine kinase Akt, a downstream effector of PI 3-kinase, blocked apoptosis. The ability of Akt to promote survival was dependent on and proportional to its kinase activity. In Rat1a fibroblasts, activated Akt did not alter Bcl-2 or Bcl-X(L) expression but inhibited Ced3/ICE-like activity. Thus, the PI 3-kinase/Akt (PKB) signaling pathway transduces a survival signal that ultimately blocks Ced3/ICE-like activity. These results suggest that uncoupling of survival and mitogenesis can be explained by differing abilities of distinct mitogens to efficiently induce the PI 3-kinase/Akt signaling pathway.

Superoxide production in rat hippocampal neurons: selective imaging with hydroethidine

Abstract: Digital-imaging microfluorimetry of the oxidation of hydroethidine (HEt) to ethidium can be used to monitor superoxide (O2-) production selectively within individual rat hippocampal pyramidal neurons in culture and in brain slices. Under assay conditions, oxidation was not accomplished by hydroxyl radical, singlet O2, H2O2, or nitrogen radicals. Neuronal O2- production varied with metabolic activity and age. O2- generation increased after treatment with AMPA, kainic acid, and NMDA, and the mitochondrial uncoupler carbonylcyanide p-(trifluoromethoxy)phenyl hydrazone, but usually not after depolarization (50 mM K+). O2- concentrations were sensitive to scavengers and nitric oxide. HEt oxidation was higher in Ca(2+)-containing versus Ca(2+)-free saline. However, Ca2+ ionophores did not increase oxidation greatly. H2O2 application produced a secondary increase in O2-. The major source of O2- under basal and stimulated conditions appeared to be the mitochondria. Consistent with this, ethidium staining in dendrites was punctate, colocalized with mitochondria, and blocked by CN-.

Mutant Superoxide Dismutase-1-Linked Familial Amyotrophic Lateral Sclerosis: Molecular Mechanisms of Neuronal Death and Protection

Abstract: Mutations in human Cu/Zn superoxide dismutase-1 (SOD) cause approximately 20% of cases of familial amyotrophic lateral sclerosis (FALS). We investigated the mechanism of mutant SOD-induced neuronal degeneration by expressing wild-type and mutant SODs in neuronal cells by means of infection with replication-deficient recombinant adenoviruses. Expression of two FALS-related mutant SODs (A4V and V148G) caused death of differentiated PC12 cells, superior cervical ganglion neurons, and hippocampal pyramidal neurons. Cell death included many features typical of apoptosis. Death could be prevented by copper (Cu2+) chelators, Bcl-2, glutathione, vitamin E, and inhibitors of caspases. Mutant SOD-expressing PC12 cells had higher rates of superoxide (O2-) production under a variety of conditions. The results support the hypothesis that mutant SOD induced-neurodegeneration is associated with disturbances of neuronal free radical homeostasis.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Short-Term Synaptic Plasticity

Abstract: ▪ Abstract Synaptic transmission is a dynamic process. Postsynaptic responses wax and wane as presynaptic activity evolves. This prominent characteristic of chemical synaptic transmission is a crucial determinant of the response properties of synapses and, in turn, of the stimulus properties selected by neural networks and of the patterns of activity generated by those networks. This review focuses on synaptic changes that result from prior activity in the synapse under study, and is restricted to short-term effects that last for at most a few minutes. Forms of synaptic enhancement, such as facilitation, augmentation, and post-tetanic potentiation, are usually attributed to effects of a residual elevation in presynaptic [Ca2+]i, acting on one or more molecular targets that appear to be distinct from the secretory trigger responsible for fast exocytosis and phasic release of transmitter to single action potentials. We discuss the evidence for this hypothesis, and the origins of the different kinetic phases...