P2x7 receptor antagonism as a potential therapy in amyotrophic lateral sclerosis

This review focuses on the purinergic ionotropic receptor P2X7 (P2X7R) as a potential target for developing drugs that delay the onset and/or disease progression in patients with amyotrophic lateral sclerosis (ALS). Description of clinical and genetic ALS features is followed by an analysis of advantages and drawbacks of transgenic mouse models of disease based on mutations in a bunch of proteins, particularly Cu/Zn superoxide dismutase (SOD1), TAR-DNA binding protein-43 (TDP-43), Fused in Sarcoma/Translocated in Sarcoma (FUS), and Chromosome 9 open reading frame 72 (C9orf72). Though of limited value, these models are however critical to study the proof of concept of new compounds, before reaching clinical trials. The authors also provide a description of ALS pathogenesis including protein aggregation, calcium-dependent excitotoxicity, dysfunction of calcium-binding proteins, ultrastructural mitochondrial alterations, disruption of mitochondrial calcium handling, and overproduction of reactive oxygen species (ROS). Understanding disease pathogenic pathways may ease the identification of new drug targets. Subsequently, neuroinflammation linked with P2X7Rs in ALS pathogenesis is described in order to understand the rationale of placing the use of P2X7R antagonists as a new therapeutic pharmacological approach to ALS. This is the basis for the hypothesis that a P2X7R blocker could mitigate the neuroinflammatory state, indirectly leading to neuroprotection and higher motoneuron survival in ALS patients.This project has received funding from: (1) the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 766124; (2) the Spanish Ministry of Science, Technology and Innovation SAF2016-78892R; and (3) Fundación Teófilo Hernando

Design and evaluation of biodegradable particulate systems with neuroprotective agents for the treatment of neurodegenerative ocular diseases

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Farmacia, Departamento de Farmacia y Tecnología Farmacéutica, leída el 15/06/2017Las enfermedades neurodegenerativas que afectan al segmento posterior del ojo se caracterizan por ser devastadoras. En su mayoría son crónicas y pueden cursar con un daño progresivo del nervio óptico y la pérdida de células ganglionares de la retina (CGR), fotorreceptores y otras células de la retina ocasionando la pérdida de visión. Una de las estrategias terapéuticas encaminadas al tratamiento de estas patologías es la neuroprotección, que se centra en prevenir, limitar, y en algunos casos revertir, la degeneración o muerte de las células neuronales. En el caso de la neuroprotección ocular, una aproximación terapéutica consiste en la administración de factores neurotróficos exógenos encargados de modular el crecimiento, la diferenciación, la reparación y la supervivencia de las neuronas gracias a su unión a receptores específicos. Estos factores engloban una amplia variedad de sustancias entre las cuales cabe destacar el Factor Neurotrófico Derivado de la Glía (GDNF), cuyo efecto neuroprotector ha sido demostrado en diversas patologías oculares. También existen otras moléculas terapéuticas que ejercen efecto neuroprotector a nivel ocular mediante mecanismos de acción diferentes a los factores neurotróficos. Un ejemplo son los antioxidantes que se destinan a paliar el daño oxidativo que acompaña a las patologías retinianas. En este sentido, la melatonina juega un papel importante ya que presenta un potente carácter antioxidante, atenuando el daño celular causado por los radicales libres tanto en las CGR como en los fotorreceptores. En esta misma línea, la administración de vitaminas antioxidantes se plantea de igual modo como una alternativa terapéutica encaminada a contrarrestar el daño oxidativo. Concretamente, la vitamina E (VitE) ha demostrado actividad en diferentes enfermedades de la retina en las que se produce, entre otros, estrés oxidativo...Neurodegenerative diseases that affect the posterior segment of the eye are characterised by being devastating in nature. The majority of them are chronic and they may involve gradual damage to the optic nerve and loss of retinal ganglion cells (RGCs), photoreceptors and other cells in the retina, thereby causing loss of vision. One therapeutic strategy intended to treat these diseases is neuroprotection, which focuses on preventing, limiting and in some cases reversing the degeneration and death of neuronal cells. In the case of ocular neuroprotection, one therapeutic approach consists of administering exogenous neurotrophic factors responsible for modulating the growth, differentiation, repair and survival of neurons through their binding to specific receptors. These factors encompass a wide variety of substances including glial cell line-derived neurotrophic factor (GDNF), whose neuroprotective effect has been demonstrated in various eye diseases. Other therapeutic molecules also exert a neuroprotective effect on the eye through different mechanisms of action than neurotrophic factors. One example is antioxidants intended to palliate the oxidative damage that accompanies retinal diseases. In this regard, melatonin plays a significant role since it has strong antioxidant properties whereby it attenuates the cell damage caused by free radicals in both RGCs and photoreceptors. Likewise, the administration of antioxidant vitamins has been proposed as a therapeutic alternative intended to counteract oxidative damage. Specifically, vitamin E (VitE) has demonstrated activity in different diseases of the retina with oxidative stress, among other features. However, as this type of disease is multifactorial, the search for new therapeutic strategies is focused on combination treatment, for which various active substances are used depending on the patient's therapeutic requirements...Depto. de Farmacia Galénica y Tecnología AlimentariaFac. de FarmaciaTRUEunpu

Tailoring single-molecule conductance with structured graphene electrodes

Modulation of electric currents through single-molecule junctions is usually achieved by synthesis of molecules with desired functionalities, in conjunction with suitable molecule–electrode contacts through specific anchoring groups. An alternative to this approach, barely explored so far, is to use structured electrodes, where conductivity could eventually be controlled by changing the specific anchoring site within the very same electrode. Here, we theoretically investigate how to exploit the pronounced anisotropy of corrugated graphene deposited on Ru(0001) (Gr/Ru) to tailor single-molecule conductivity in 4-aminophenyl and 4-aminobenzonitrile. We show that currents induced in the upper and lower anchoring positions in the Gr/Ru moiré are substantially different, irrespective of the chosen molecule. The magnitude of these currents can differ by as much as an order of magnitude at specific bias voltages. We also show that both molecules display rectifying properties, which can differ by up to a factor of five in different anchoring sites. Interestingly, the observed modulations strongly depend on the chemical binding nature between the molecule and the electrode, (strong) covalent bond for 4-aminophenyl and (weak) physisorption for 4-aminobenzonitrile. All this suggests that Gr/Ru can be an ideal electrode to modulate single-molecule electric conductivity under experimental conditions that are available in many laboratoriesPID2019-105458RB-I00, PID2019-106732GB-I0

A Review of Artificial Intelligence in the Internet of Things

Humankind has the ability of learning new things automatically due to the capacities with which we were born. We simply need to have experiences, read, study… live. For these processes, we are capable of acquiring new abilities or modifying those we already have. Another ability we possess is the faculty of thinking, imagine, create our own ideas, and dream. Nevertheless, what occurs when we extrapolate this to machines? Machines can learn. We can teach them. In the last years, considerable advances have been done and we have seen cars that can recognise pedestrians or other cars, systems that distinguish animals, and even, how some artificial intelligences have been able to dream, paint, and compose music by themselves. Despite this, the doubt is the following: Can machines think? Or, in other words, could a machine which is talking to a person and is situated in another room make them believe they are talking with another human? This is a doubt that has been present since Alan Mathison Turing contemplated it and it has not been resolved yet. In this article, we will show the beginnings of what is known as Artificial Intelligence and some branches of it such as Machine Learning, Computer Vision, Fuzzy Logic, and Natural Language Processing. We will talk about each of them, their concepts, how they work, and the related work on the Internet of Things fields

The Role of Probiotics and Prebiotics in the Prevention and Treatment of Obesity

Obesity is a global pandemic complex to treat due to its multifactorial pathogenesis—an unhealthy lifestyle, neuronal and hormonal mechanisms, and genetic and epigenetic factors are involved. Scientific evidence supports the idea that obesity and metabolic consequences are strongly related to changes in both the function and composition of gut microbiota, which exert an essential role in modulating energy metabolism. Modifications of gut microbiota composition have been associated with variations in body weight and body mass index. Lifestyle modifications remain as primary therapy for obesity and related metabolic disorders. New therapeutic strategies to treat/prevent obesity have been proposed, based on pre- and/or probiotic modulation of gut microbiota to mimic that found in healthy non-obese subjects. Based on human and animal studies, this review aimed to discuss mechanisms through which gut microbiota could act as a key modifier of obesity and related metabolic complications. Evidence from animal studies and human clinical trials suggesting potential beneficial effects of prebiotic and various probiotic strains on those physical, biochemical, and metabolic parameters related to obesity is presented. As a conclusion, a deeper knowledge about pre-/probiotic mechanisms of action, in combination with adequately powered, randomized controlled follow-up studies, will facilitate the clinical application and development of personalized healthcare strategies.Supported by funds from European Union 7th FP KBBE.2013.2.2-02—MyNewGut Project (“Factors influencing the human gut microbiome and its effect on the development of diet-related diseases and brain development”, Grant Agreement 613979) and from Spanish Ministry of Economy and Competitiveness GD-Brain Projects (SAF2015-69265-c2.2)

Chronic administration of P2X7 receptor antagonist JNJ-47965567 delays disease onset and progression, and improves motor performance in ALS SOD1 (G93A) female mice

Neuroinflammation is one of the main physiopathological mechanisms of amyotrophic lateral sclerosis (ALS), produced by the chronic activation of microglia in the CNS. This process is triggered by the persistent activation of the ATP-gated P2X7 receptor (P2RX7, hereafter referred to as P2X7R). The present study aimed to evaluate the effects of the chronic treatment with the P2X7R antagonist JNJ-47965567 in the development and progression of ALS in the SOD1 murine model. SOD1 mice were intraperitoneally (i.p.) injected with either 30 mg/kg of JNJ-47965567 or vehicle 4 times per week, from pre-onset age (here, postnatal day 60; P60) until study endpoint. Body weight, motor coordination, phenotypic score, disease onset and survival were measured throughout the study, and compared between vehicle- and drug-injected groups. Treatment with the P2X7R antagonist JNJ-47965567 delayed disease onset, reduced body weight loss and improved motor coordination and phenotypic score in female SOD1 mice, although it did not increase lifespan. Interestingly, neither beneficial nor detrimental effects were observed in males in any of the analyzed parameters. Treatment did not affect motor neuron survival or ChAT, Iba-1 and P2X7R protein expression in endpoint individuals of mixed sexes. Overall, chronic administration of JNJ-47965567 for 4 times per week to SOD1 mice from pre-onset stage altered disease progression in female individuals while it did not have any effect in males. Our results suggest a partial, yet important, effect of P2X7R in the development and progression of ALS. G93A G93A G93A G93AThis project was supported by the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement no. 766124; the Spanish Ministry of Science, Technology and Innovation (SAF2016-78892R); and Fundación Teófilo Hernando

BILROST: Handling Actuators of the Internet of Things through Tweets on Twitter using a Domain- Specific Language

In recent years, many investigations have appeared that combine the Internet of Things and Social Networks. Some of them addressed the interconnection of objects as Social Networks interconnect people, and others addressed the connection between objects and people. However, they usually used interfaces created for that purpose instead of using familiar interfaces for users. Why not integrate Smart Objects in traditional Social Networks? Why not control Smart Objects through natural interactions in Social Networks? The goal of this paper is to make easier to create applications that allow non-experts users to control Smart Objects actuators through Social Networks through the proposal of a novel approach to connect objects and people using Social Networks. This proposal will address how to use Twitter so that objects could perform actions based on Twitter users’ posts. Moreover, it will be presented a Domain-Specific language that could help in the task of defining the actions that objects could perform when people publish specific content on Twitter

Towards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problems

Machine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies