Building up molecular complexity via C-H functionalization and skeletal rearrangements

L'obtenció de molècules orgànicas complexes a partir de simpl precursors és, avui en dia encara, de gran interès en el camp de la química sintética. En els darrers anys, la funcionalizació d´enllaços C-H en les molèculas orgàniques i la no necessitat de prefuncionalizació del productes de partida són els principals avantatges pel gran creixement que ha experimentat aquesta metodologia. No obstant això, manquen per resoldre aspectes relacionats amb la poca reactivitat i els problemes associats amb la selectivitat derivats de l´enllaç C-H. En el treball presentat, s´han desenvolupat dues metodologies on s´utilizen enllaços C-H com a parellas d´acoblament d´halurs d´aril amb catàlisis de pal.ladi per la construcció de sisteme bicíclics benzofusionats dált valor: Benzociclobutanones i indans. En el primer cas, un enllaç C(sp2)-H aldehídic és activat per la formació d´anells de 4 membres altament tensionats. En el segon, compostos diazo són combinats amb enllaços C(sp3)-H no activats per a la síntesis d´estructures tipus indanil amb dos centres quaternaris. Cal remarcar, que per primera vegada s´ha utilizat un enllaç C(sp3)-H no activat per la síntesis de centres quaternaris.La formación de diversidad estructural a partir the reactivos comunes es de gran importancion en síntesis orgánica. Durante las últimas décadas, las reacciones de funcionalización C-H han surgido como una excelente alternativa para tal fin. Entre sus principales ventajas destacan el evitar tener que prefuncionalizar los substratos de partida así como la ubicuidad de los enlaces C-H. Lamentablemente, su utilización presenta numerosas dificultades como su falta de reactividad y los problemas de selectividad asociados a su ubicuidad. Durante el presente trabajo, hemos desarrollado dos metodologías basadas en la utilización de enlaces C-H para la formación de sistemas cíclicos con un anillo de benceno, concretamente, benzociclobutenonas e indanos. En el caso de las primeras, hemos llevado a cabo la funcionalización de enlaces aldehídico C(sp2)-H para formar anillos de cuatro miembros con alta tensión anular. En el segundo caso, diazo compuestos han sido acoplados con enlace C-H no activados. Cabe destacar que la presente metodología describe la utilización, por vez primera, de enlaces C (sp3)-H no activados para la síntesis de centros cuaternarios.The construction of molecular complexity from readily available materials is of utmost importance in Organic Synthesis. In the last decades, C-H functionalization reactions have arosed as an excellent approach to such goal. The main advantages of C-H functionalization events is the no need of prefunctionalization of the substrate as well as the ubiquity of the C-H bonds. However, numerous challenges are present as well, such as the poor reactivity of these bonds and selectivity issues. During the present work, we have been able to develop two methodologies that employ C-H bonds as coupling partner with aryl halides under palladium-catalysis for the construction of benzofused bucyclic systems of high added value: Benzocyclobutenones and indanes. In the first case, an aldehydic C(sp2)-H bond is activated for the synthesis of a highly strained four-membered ring. For the second, diazo compounds are combined with non-activated C(sp3)-H bonds for the synthesis of indanyl-cores bearing two quaternary centers

Alteraciones coroideas asociadas al queratocono

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Cirugía. Fecha de Lectura: 10-06-202

Responses of resident (DNA) and active (RNA) microbial communities in fluvial biofilms under different polluted scenarios.

Abstract Pollution from human activities is a major threat to the ecological integrity of fluvial ecosystems. Microbial communities are the most abundant organisms in biofilms, and are key indicators of various pollutants. We investigated the effects some human stressors (nutrients and heavy metals) have on the structure and activity of microbial communities in seven sampling sites located in the Ter River basin (NE Spain). Water and biofilm samples were collected in order to characterize physicochemical and biofilm parameters. The 16S rRNA gene was analysed out from DNA and RNA extracts to obtain α and β diversity. Principal coordinates analyses (PCoA) of the operational taxonomic units (OTUs) in the resident microbial community revealed that nutrients and conductivity were the main driving forces behind the diversity and composition. The effects of mining have had mainly seen on the taxonomic composition of the active microbial community, but also at the OTUs level. Remarkably, metal-impacted communities were very active, which would indicate a close link with the stress faced, that is probably related to the stimulation of detoxification

Relation between diagnosis of atheromatous plaque from orthopantomographs and cardiovascular risk factors. A study of cases and control subjects

Background: In recent years the use of orthopantomography has been proposed as a low-cost, reliable and noninvasive diagnostic medium for detecting atheromatous plaque. The purpose of this study was to correlate the presence of carotid calcifications (atheroma) in orthopantomographs with specific risk factors for cerebrovascular accidents (previous cerebrovascular accidents, arterial hypertension, and diabetes). Patient and Methods: The methods used in this observational study of cases and control subjects followed STROBE (Strengthening the Reporting of Observational studies in Epidemiology) recommendations. The study analyzed a total of 1,602 panoramic radiographs taken for dental diagnostic purposes between January 2010 and February 2014. The main variables analyzed were the incidence of atheromatous plaque and other cardiovascular risk factors. Epidat 3.1 statistical software was used to determine minimum sample sizes and the results were analyzed using PASW (Predictive Analytics Software) Statistics 10.0.0. Results: For all the variables analyzed, the correlation between radiographic detection of atheromatous plaque and the presence of cardiovascular disease risk factors was found to be statistically significant (RR>1.5). Conclusions: The presence of cardiovascular risk factors is related to the incidence of radiopaque lesions at the carotid artery bifurcation, indicating the presence of atheromatous plaque

Downregulation of mTOR Signaling Increases Stem Cell Population Telomere Length during Starvation of Immortal Planarians

Reduction of caloric intake delays and prevents age-associated diseases and extends the life span in many organisms. It may be that these benefits are due to positive effects of caloric restriction on stem cell function. We use the planarian model Schmidtea mediterranea, an immortal animal that adapts to long periods of starvation by shrinking in size, to investigate the effects of starvation on telomere length. We show that the longest telomeres are a general signature of planarian adult stem cells. We also observe that starvation leads to an enrichment of stem cells with the longest telomeres and that this enrichment is dependent on mTOR signaling. We propose that one important effect of starvation for the rejuvenation of the adult stem cell pool is through increasing the median telomere length in somatic stem cells. Such a mechanism has broad implications for how dietary effects on aging are mediated at the whole-organism level.C.G.-E. was funded by a Contrato de Investigadores Miguel Servet (CP12/03214) and by the FLI. The FLI is a member of the Leibniz Association and is financially supported by the Federal Government of Germany and the State of Thuringia. O.G.-G. was funded by an LGSA scholarship. R.P. and B.F.-V. were funded by a grant (PI17-01401) from Fondo de Investigaciones Sanitarias (Instituto de Salud Carlos III, Spain) and FEDER funds. I.F. was funded by grants from Ministerio de Ciencia, Innovación y Universidades (SAF2016-80406-R), Comunidad de Madrid (S2017/BMD-3875), and the Red Temática de Investigación Cooperativa en Enfermedades Cardiovasculares (RD12/0042/0045). The CNIC is supported by the Ministerio de Ciencia, Innovación y Universidades and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505). A.A.A. was funded by grants from the BBSRC (BB/K007564/1) and MRC (MR/M000133/1), and S.S. by a University of Oxford Clarendon Fund Scholarship.S

Contaminación química del agua de lluvia de Santander y su correlación con al cantidad de precipitación y otras variables meteorológicas

Se ha llevado a cabo una serie sistemática de medidas de la composición química del agua de lluvia recogida en la ciudad de Santander durante el año 1981. Se han estudiado las posibles correlaciones existentes entre las concentraciones del ión sulfato, del ión amoniaco y del pH con la cantidad de precipitación. También se han analizado las posibles correlaciones estacionales y la relación de estas características del agua de lluvia con algunas variables meteorológicas. Se encuentra que las máximas concentraciones de los iones citados se presentan durante el invierno, mientras que se observa una disminución con la cantidad de precipitación. También existe una relación acusada entre la concentración de estos iones y la presión atmosférica. El pH de las precipitaciones disminuye cuando existen vientos dominantes procedentes del mar, mientras que parece neutralizarse en situaciones anticiclónicas

Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes

The goal of this study was to evaluate the maturity of current Deep Learning classification techniques for their application in a real maternal-fetal clinical environment. A large dataset of routinely acquired maternal-fetal screening ultrasound images (which will be made publicly available) was collected from two different hospitals by several operators and ultrasound machines. All images were manually labeled by an expert maternal fetal clinician. Images were divided into 6 classes: four of the most widely used fetal anatomical planes (Abdomen, Brain, Femur and Thorax), the mother's cervix (widely used for prematurity screening) and a general category to include any other less common image plane. Fetal brain images were further categorized into the 3 most common fetal brain planes (Trans-thalamic, Trans-cerebellum, Trans-ventricular) to judge fine grain categorization performance. The final dataset is comprised of over 12,400 images from 1,792 patients, making it the largest ultrasound dataset to date. We then evaluated a wide variety of state-of-the-art deep Convolutional Neural Networks on this dataset and analyzed results in depth, comparing the computational models to research technicians, which are the ones currently performing the task daily. Results indicate for the first time that computational models have similar performance compared to humans when classifying common planes in human fetal examination. However, the dataset leaves the door open on future research to further improve results, especially on fine-grained plane categorization

Automatic deep learning-based pipeline for automatic delineation and measurement of fetal brain structures in routine mid-trimester ultrasound images

Introduction: The aim of this study was to develop a pipeline using state-of-the-art deep learning methods to automatically delineate and measure several of the most important brain structures in fetal brain ultrasound (US) images. Methods: The dataset was composed of 5,331 images of the fetal brain acquired during the routine mid-trimester US scan. Our proposed pipeline automatically performs the following three steps: brain plane classification (transventricular, transthalamic, or transcerebellar plane); brain structures delineation (9 different structures); and automatic measurement (from the structure delineations). The methods were trained on a subset of 4,331 images and each step was evaluated on the remaining 1,000 images. Results: Plane classification reached 98.6% average class accuracy. Brain structure delineation obtained an average pixel accuracy higher than 96% and a Jaccard index higher than 70%. Automatic measurements get an absolute error below 3.5% for the four standard head biometries (head circumference, biparietal diameter, occipitofrontal diameter, and cephalic index), 9% for transcerebellar diameter, 12% for cavum septi pellucidi ratio, and 26% for Sylvian fissure operculization degree. Conclusions: The proposed pipeline shows the potential of deep learning methods to delineate fetal head and brain structures and obtain automatic measures of each anatomical standard plane acquired during routine fetal US examination.The research leading to these results has received funding from the Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales,UK) and ASISA foundation.Peer ReviewedPostprint (published version

Analysis of maturation features in fetal brain ultrasound via artificial intelligence for the estimation of gestational age

Background: Optimal prenatal care relies on accurate gestational age dating. After the first trimester, the accuracy of current gestational age estimation methods diminishes with increasing gestational age. Considering that, in many countries, access to first trimester crown rump length is still difficult owing to late booking, infrequent access to prenatal care, and unavailability of early ultrasound examination, the development of accurate methods for gestational age estimation in the second and third trimester of pregnancy remains an unsolved challenge in fetal medicine. Objective. This study aimed to evaluate the performance of an artificial intelligence method based on automated analysis of fetal brain morphology on standard cranial ultrasound sections to estimate the gestational age in second and third trimester fetuses compared with the current formulas using standard fetal biometry. Study Design: Standard transthalamic axial plane images from a total of 1394 patients undergoing routine fetal ultrasound were used to develop an artificial intelligence method to automatically estimate gestational age from the analysis of fetal brain information. We compared its performance—as stand alone or in combination with fetal biometric parameters—against 4 currently used fetal biometry formulas on a series of 3065 scans from 1992 patients undergoing second (n=1761) or third trimester (n=1298) routine ultrasound, with known gestational age estimated from crown rump length in the first trimester. Results: Overall, 95% confidence interval of the error in gestational age estimation was 14.2 days for the artificial intelligence method alone and 11.0 when used in combination with fetal biometric parameters, compared with 12.9 days of the best method using standard biometrics alone. In the third trimester, the lower 95% confidence interval errors were 14.3 days for artificial intelligence in combination with biometric parameters and 17 days for fetal biometrics, whereas in the second trimester, the 95% confidence interval error was 6.7 and 7, respectively. The performance differences were even larger in the small-for-gestational-age fetuses group (14.8 and 18.5, respectively). Conclusion: An automated artificial intelligence method using standard sonographic fetal planes yielded similar or lower error in gestational age estimation compared with fetal biometric parameters, especially in the third trimester. These results support further research to improve the performance of these methods in larger studies.The research leading to these results was partially funded by Transmural Biotech S.L. In addition, the research has received funding from “la Caixa” Foundation under grant agreements LCF/PR/GN14/10270005 and LCF/PR/GN18/10310003, the Instituto de Salud Carlos III (PI16/00861, PI17/00675) within the Plan Nacional de I+D+I and cofinanced by Instituto de Salud Carlos III— Subdirección General de Evaluación together with the Fondo Europeo de Desarrollo Regional (FEDER) “Una manera de hacer Europa,” Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, United Kingdom), Cellex Foundation, ASISA Foundation, and Agency for Management of University and Research Grants under grant 2017 SGR number 1531. In addition, E.E. has received funding from the Departament de Salut under grant number SLT008/18/00156.Peer ReviewedPostprint (published version

Topological structure of plant-bee networks in four Mexican environments

We analyzed the topological structure (e.g., links per species, connectance, core-periphery analyses, specialization, nestedness, modularity) of plant-bee interactions of four areas in Mexico. We used qualitative data (binary networks). Mexico exhibits a complex geography and community variation that can affect bee networks. Network architecture is variable within large spatial scales, thus our results should vary according to site characteristics (La Mancha and Totula in Veracruz, Carrillo Puerto in Quintana Roo, and the Tehuacan-Cuicatlan valley, in Puebla), type of vegetation, endemism, altitude, size of area sampled. Network topology varied among sites, and the presence of nested or modular patterns was analyzed for robustness to simulated species extinctions. The lowest species richness was recorded for the Quintana Roo site (15 plant, 25 bee species), and the highest for the Tehuacan-Cuicatlan valley site (88 plant, 231 bee species). There was a tendency to have more connected networks when species richness was low and networks with greater species richness had a higher number of interactions. The distribution of interactions differed between environments but not due to network size and all were significantly nested. The robustness to cumulative extinctions showed a different pattern at each site; the most robust network was at Carrillo Puerto, which also was the site with less species. Sites with more endemic species (e.g. Tehuacan) had more specialized interactions, and were more susceptible to extinction