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The advent of digital resources, the Internet, and an interconnected globe has deeply affected the humanities and its research. Music scholars in Latin America, like everywhere else, have observed this explosion of digital information sharing, but not everyone has been able to take advantage of the new opportunities afforded by this technology. On the one hand, advantages of digitization are slowly becoming recognized as tools to fight the enormous size of the region (Latin America), especially through technology's ability to easily and promptly disperse sources across great distances. In addition, digitization acts as an aid in countering the endemic lack of economic resources, and more broadly offers a path towards making the academic world a more connected and equal place. On the other hand, it is undeniable that the digital revolution has not reached people across the globe equally. Digital segregation is a problem that deeply impacts numerous nations around world; and for Latin America and the Caribbean, it has meant a slower pace of incorporation into the digital era. Key databases like JSTOR and the various READEX products are still largely unavailable to scholars in Latin America, and, given the steep price of such resources, the fight for a world of open-source information is becoming increasingly political.

In the present research, storage conditions of extra virgin olive oil (EVOO) have been monitored using cost-effective fluorescence sensors integrated with intelligent algorithms. Three different Spanish pure EVOOs (Arbequina, Cornicabra, and Picual varieties), as well as samples adulterated with expired EVOO, were kept under different environmental conditions: presence or absence of light, bottle material (plastic or glass), and clearness of glass (uncolored or brown glass). To evaluate the effect of these conditions, 54 samples were prepared, and their emission spectra were measured 10 times during a 58-day period. The most statistically relevant information from these spectra was located by the relief-F feature selection method, which led to the design of machine learning-based models. With this aim, up to 158,250 artificial neural network-based models were designed and tested. It was possible to distinguish different storage conditions in terms of light exposure, bottle material, and clearness, as well as locate adulterations. All of the trained and optimized classifiers for all three EVOO varietals reached accuracies ranging between 91 and 100% after meticulous validations. The used technique is fast, portable, user-friendly, inexpensive, and non-destructive, and, therefore, it could be of great use for the olive oil sector as it enables real-time quality control and fraud detection.

Extra virgin olive oil (EVOO), the star of the Mediterranean diet, is a valuable product within the food sector. In certain cases, due to specific and special olive varietals and blends, as well as organoleptic properties, EVOOs are even authenticated with protected designation of origin (PDO) labels. Because of this, false labeling and even adulterations have been reported in this sector. During this research, a laser diode has been used to gather 254 fluorescence spectra from that many artificially prepared samples of fresh PDO EVOO mixed with small amounts of old olive oils (adulterants). The database was then treated and employed to train and optimize an intelligent model based on a supervised artificial neural network known as multilayer perceptron (MLP). The goal of this non-linear model was dual: to identify the PDO of every sample and to quantify the amount of fresh EVOO. After meticulous validation using blinded samples to assess the performance of the MLP, the outcome was successful. The algorithm could perfectly distinguish the PDOs and determine the amount of fresh EVOO with a mean absolute error of around 1.5% (w/w). Therefore, the combination of a laser diode and cognitive modeling leads to a fast and cost-effective tool able to authenticate PDO labels of EVOOs and estimate the amount of potential adulterating agents such as olive oils from old harvests.

Cystic fibrosis (CF) is a multisystem, autosomal recessive disease that leads to progressive loss of lung function. Respiratory symptoms for both CF and asthma include cough, wheezing, and dyspnea. There is debate within the CF community on how to best define and distinguish CF-asthma overlap syndrome (CFAOS) from asthma-like features, though CFAOS is well-recognized. We aim to review the epidemiology, diagnosis, and treatment of asthma in CF and explore areas where further research is needed. There has been considerable improvement in the understanding and treatment of asthma over the past two decades leading to novel therapies such as biologic agents that target the airway inflammation in asthmatics based on their asthma phenotype. These therapies are being studied in CFAOS and are promising treatments. This review provides a comprehensive overview of the definition, epidemiology, diagnosis, and current treatment of CFAOS.

[EN] Innovation is becoming a fundamental part of many sectors and environments, including universities, not only regarding their research but also how education is approached. In this line, one of the ways to achieve these objectives is based on a collaboration between society, which presents a need to be solved, and the University. This society-university integration is achievable via the Service-Learning methodology (SLM), which has always been based on establishing strong links between the educational world and society. This paper presents a SLM-based project linked to technological development for the health sector during the SARS-CoV-2 pandemic. Specifically, undergraduate chemistry students, and Ph.D. students led by professors have presented part of their technological developments to people in society who are at risk of exclusion to help them understand aspects of infection as well as diagnosis of diseases. In short, the objective is to transfer in an enjoyable fashion, a set of technological developments and knowledge that can help society understand aspects related to the COVID-19 pandemic., This work has been carried out with the financial support of the SL UCM 2018/19_16 and SL UCM 2019/21_14 project and the Madrid City Council.

In this research, more than 27,000 images (samples) of five different types of rice (Oryza sativa L.) have been used to design and validate a deep learning-based system to carry out their classification. A typical photographic camera was used to obtain images from five different varieties of rice, which will be used for their classification after proper treatment. The resulting photographs were processed by convolutional neural networks (CNNs), which have been trained and optimized using these images to identify different types of rice. Finally, the model was successfully validated using images which were initially isolated from the training database. The result was an algorithm capable of detecting and classifying all five rice types accurately. Therefore, CNNs have shown to be a compelling tool for the evaluation of this type of cereal, including for quality purposes, thanks to traits which include high sensitivity, speed, and not requiring highly specialized personnel to implement the optimized version of the algorithm.

A new and reliable method to detect adulterations is presented in this work by comparing the thermal evolution of pure and adulterated extra virgin olive oil (EVOO) during its cooling process. For this purpose, algorithms based on convolutional neural networks have been tested for the analysis and classification of different thermographic images of pure and adulterated EVOO containing amounts ≤ 8% in weight of different adulterants (refined olive oil, olive pomace oil, and sunflower oil). Eight convolutional neural network models have been designed for the classification of EVOO samples and for the estimation of adulterant concentrations. Finally, other similar models were developed that included all the samples, containing any of the adulterants, to reach a global more versatile tool. The statistical performance of the convolutional neural networks in terms of classification accuracy range from 97 to 100%.

In this research, 56 samples of pure honey have been mixed with different concentrations of rice syrup simulating a set of adulterated samples. A thermographic camera was used to extract data regarding the thermal development of the honey. The resulting infrared images were processed via convolutional neural networks (CNNs), a subset of algorithms within deep learning. The CNNs have been trained and optimized using these images to detect the commonly elusive rice syrup in honey in concentrations as low as 1% in weight, as well as quantify it. Finally, the model was successfully validated using images which were initially isolated from the training database. The result was an algorithm capable of identifying adulterated honey from different floral origins and quantifying rice syrup with accuracies of 95% and 93%, respectively. Therefore, CNNs have complemented the thermographic analysis and have shown to be a compelling tool for the control of food quality, thanks to traits such as high sensitivity, speed, and being independent of highly specialized personnel.

A computerized approach to quickly, easily, and efficiently detect discharged sewage of the cheese sector into rivers or reservoirs has been presented in this work. It is based on developing and/or training linear regression, linear multiple regression, and multilayer perceptron-based models using the data obtained from measuring different contaminated waters with a portable digital refractometer. This equipment measures the refractive index, Brix degrees, and salinity of aqueous samples. To carry it out, 451 samples were made by mixing five different waters with cheese whey from the Spanish “Fabrica de quesos de Villalon de Campos S.L.”. The water samples used were distilled water and four non-drinkable waters taken from four different Spanish locations (the Valmayor Reservoir, the Mari Pascuala Lagoon, the Manzanares River and the Guadarrama River). The lowest mean absolute percentage error (0.79%) was achieved using three independent variables and a multilayer perceptron-based model. The validation of this approach has been done in two ways: k-fold cross-validation and internal validation. The outcome of this research is a new method for a fast detection of waste spillages into rivers and reservoirs.

Introduction: Madrid is undergoing an interesting time of transformation of care model and the engine that promotes this change is the Strategy for the Care of Patients with Chronic Diseases. One of the main projects arising from the Strategy which is the development of a map of indicators for addressing chronic disease in the Madrid Region. Methods : A working group involving experts on indicators with decision-making capacity was established. A set of indicators from the ones already included in our organization dashboard were identified selected, prioritized and classified within the framework of the Triple Aim: population health, patient experience with care and costs. Once the matrix was constructed, sources of indicators were identified. A total of 9 different data sources were used: primary care electronic health record (AP Madrid), scorecard for primary care (eSOAP), Hospital Minimum Basic Data Set (CMBD), Information System of Public Health and Food (SISPAL), Cibeles (basic information needed to identify Madrid health organization), System Risk Factor Surveillance for Non Communicable Diseases associated with adult and youngsters (SIVFRENT A and J), Health Education Database (EpSalud), Madrid Satisfaction Survey and drug prescription information (F@rmadrid). Extraction and presentation of data was normalized and the values achieved for each of the indicators in 2012, 2013 and 2014, depending on the availability of the information obtained. Results : 118 indicators were identified: 71 about population health, 13 about patient experience with care and 34 related to costs. After prioritization by relevance, 82 indicators were finally selected: 73 about population health, 5 about patient experience with the care received and 4 with costs related to pharmaceutical expenditure (Table 1). We think it is a quite wide data set to start with. Besides classifying the indicators according to the Triple Aim, 16 different Classes of indicators were identified as display contents for every block. Each Class is summarized by a Class Index, a value that represents all of the indicators included within the Class. In five cases the Class Index represents the most relevant indicator of the group: Patients classified in the High Level of Risk, Patients with Cardiovascular Disease and Care Plans, Hypertensive Patients with Blood Pressure values under control, Global Satisfaction with Care and Pharmaceutical Expenditure on Chronic Medication. In the remaining, the Class Index represents a global indicator comprising the most relevant chronic diseases included in each Class or it is an aggregated indicator that already exists in the organization (such as for disability and mortality in non-communicable diseases). Different number of indicators based on the feasibility and relevance were included in each of the Classes. The range goes from 1 indicator for Group Health Education (Programs) to 14 indicators within the Class of Chronic Diseases Programs Coverage. For each Class, the Class Index and indicators were plotted. show the 2013 – 2014 trace. Finally, using some selected indicators and based on the Classes defined, some processes of selected chronic diseases were designed transversally. This gives us a picture of the process considering the prevalence, the related major risks factors including preventing activities and programs, intermediate health outcomes and admissions. The first report on indicators in chronicity has just been published, which today is available on the Intranet. Conclusion : The purpose of this project was not only to create a tool that would allow the organization to address outcomes with a focus on chronic diseases for the Madrid Region, but also to provide to all professionals a set of indicators that can be used to evaluate the results of the different projects that are being locally implemented as part of the cultural change promoted by the Strategy for the Care of Patients with Chronic Diseases. Although we still have a long way to go, we have taken an important step forward to have a tool that allows us to put the focus on the outcomes of our population. We are working on developing a tool to advance in the measurement of patient experience with the health professionals and with the health system. As well, there is a need to introduce the measurement of quality of life as an outcome to monitor the effectiveness of our interventions as well as more indicators related with social care The map of indicators for addressing chronic disease in the Madrid Region will allow us to periodically evaluate and improve our final outcomes to further advance in the transformation of our Health and Social Systems.

Background Elevated levels of total cholesterol and low-density lipoprotein play an important role in the development of atheromas and, therefore, in cardiovascular diseases. Cholesterol biosynthesis follows a circadian rhythm and is principally produced at night (between 12:00 am and 6:00 am). The adjustment of hypolipaemic therapy to biologic rhythms is known as chronotherapy. Chronotherapy is based on the idea that medication can have different effects depending on the hour at which it is taken. Statins are one of the most widely used drugs for the prevention of cardiovascular events. In usual clinical practice, statins are administered once per day without specifying the time when they should be taken. It is unknown whether the timing of statin administration is important for clinical outcomes. Objectives To critically evaluate and analyse the evidence available from randomised controlled trials regarding the effects of chronotherapy on the effectiveness and safety of treating hyperlipidaemia with statins. Search methods We searched the CENTRAL, MEDLINE, Embase, LILACS, ProQuest Health & Medical Complete, OpenSIGLE, Web of Science Conference Proceedings, and various other resources including clinical trials registers up to November 2015. We also searched the reference lists of relevant reviews for eligible studies. Selection criteria We included randomised controlled trials (RCTs), enrolling people with primary or secondary hyperlipidaemia. To be included, trials must have compared any chronotherapeutic lipid-lowering regimen with statins and any other statin lipid-lowering regimen not based on chronotherapy. We considered any type and dosage of statin as eligible, as long as the control and experimental arms differed only in the timing of the administration of the same statin. Quasi-randomised studies were excluded. Data collection and analysis We used the standard methodological procedures expected by Cochrane. We extracted the key data from studies in relation to participants, interventions, and outcomes for safety and efficacy. We calculated odds ratios (OR) for dichotomous data and mean differences (MD) for continuous data with 95% confidence intervals (CI). Using the GRADE approach, we assessed the quality of the evidence and we used the GRADEpro Guideline Development Tool to import data from Review Manager to create 'Summary of findings' tables. Main results This review includes eight RCTs (767 participants analysed in morning and evening arms). The trials used different lipid-lowering regimens with statins (lovastatin: two trials; simvastatin: three trials; fluvastatin: two trials; pravastatin: one trial). All trials compared the effects between morning and evening statin administration. Trial length ranged from four to 14 weeks. We found a high risk of bias in the domain of selective reporting in three trials and in the domain of incomplete outcome data in one trial of the eight trials included. None of the studies included were judged to be at low risk of bias. None of the included RCTs reported data on cardiovascular mortality, cardiovascular morbidity, incidence of cardiovascular events, or deaths from any cause. Pooled results showed no evidence of a difference in total cholesterol (MD 4.33, 95% CI -1.36 to 10.01), 514 participants, five trials, mean follow-up 9 weeks, low-quality evidence), low-density lipoprotein cholesterol (LDL-C) levels (MD 4.85 mg/dL, 95% CI -0.87 to 10.57, 473 participants, five trials, mean follow-up 9 weeks, low-quality evidence), high-density lipoprotein cholesterol (HDL-C) (MD 0.54, 95% CI -1.08 to 2.17, 514 participants, five trials, mean follow-up 9 weeks, low-quality evidence) or triglycerides (MD -8.91, 95% CI -22 to 4.17, 510 participants, five trials, mean follow-up 9 weeks, low-quality evidence) between morning and evening statin administration. With regard to safety outcomes, five trials (556 participants) reported adverse events. Pooled analysis found no differences in statins adverse events between morning and evening intake (OR 0.71, 95% CI 0.44 to 1.15, 556 participants, five trials, mean follow-up 9 weeks, low-quality evidence). Authors' conclusions Limited and low-quality evidence suggested that there were no differences between chronomodulated treatment with statins in people with hyperlipidaemia as compared to conventional treatment with statins, in terms of clinically relevant outcomes. Studies were short term and therefore did not report on our primary outcomes, cardiovascular clinical events or death. The review did not find differences in adverse events associated with statins between both regimens. Taking statins in the evening does not have an effect on the improvement of lipid levels with respect to morning administration. Further high-quality trials with longer-term follow-up are needed to confirm the results of this review.

ResumenObjetivoEvaluar los resultados de un plan de mejora de los indicadores de farmacia de un Área Sanitaria de Atención Primaria (AP).DiseñoEstudio cuasiexperimental con grupo control. Se valoró la diferencia entre el periodo postintervención (ene–dic 2008) y preintervención (ene–dic 2007).Emplazamiento y participantesGrupo de intervención: médicos del Área 7 de AP de la Comunidad de Madrid (n=397). Grupo control: resto de médicos de AP de la Comunidad de Madrid (n=4.428).IntervenciónPlan de mejora multifocal cuyas principales acciones fueron: sesiones en los centros de salud con peores resultados, implicación de los responsables de Uso Racional del Medicamento, entrevistas con los médicos con indicadores más mejorables, reconocimiento de aquellos con buenos indicadores, elaboración notas breves sobre medicamentos.Mediciones principalesIndicadores de prescripción y de notificaciones relacionadas con la seguridad de los medicamentos.ResultadosEn relación a Madrid, las mejoras absolutas del Área 7 en los indicadores acumulados %EFG, %Estatinas elección, %ARAII y %Omeprazol fueron 0,29; 1,17; 0,61 y 0,37 puntos porcentuales, respectivamente. DHD Osteoporosis igualó la mejora de Madrid. En el Área 7, el incremento en las notificaciones de sospechas de RAM graves fue 180% y en el número de notificadores de RAM 233%, mejorando los datos de Madrid (48 y 21%). La notificación de errores de medicación presentó incrementos similares en ambos grupos (AP7 1.567% vs Madrid AP 1.633%).ConclusionesImplementar un plan de mejora multifocal con acciones factibles y concretas, puede ser una herramienta útil para la mejora de los indicadores de farmacia.AbstractObjectiveTo evaluate the results of a plan for improving pharmacy indicators in a Primary Care (PC) Health Area.DesignQuasi-experimental study with a control group. The differences between the pre-intervention (Jan-Dec 2007) and post-intervention (Jan-Dec 2008) periods were evaluated.Setting and participantsIntervention group: Primary Care doctors from PC Area 7 of the Community of Madrid (n=397). Control group: the rest of PC doctors of the Community of Madrid (n=4428).MethodA multi-focus plan in which the main activities were: sessions in the health centres with the worst results, involvement of those responsible for the Rational Use of Drugs, interviews with the doctors with the most improvable indicators, recognition of those with good indicators, and preparing short notes on drugs.Main measurementsPrescription and notification indicators associated with the safety of drugs.ResultsIn relation to Madrid, the absolute improvements of Area 7 in the accumulated indicators, %Generic drugs, %Statins, %ARAII y %Omeprazole were 0.29; 1.17; 0.61 and 0.37 percentage points, respectively. DHD Osteoporosis equalled the improvement of Madrid. In Area 7, the increase in notifications of suspected serious ADRs was 180% and number of ADR notifications of ADRs was 233%, better than the Madrid data (48% and 21%). The notification of medication errors showed similar increases in both groups (PC Area 7 1567% vs. Madrid PC 1633%).ConclusionsImplementing a multi-focus improvement plan with feasible and specific actions can be a useful tool for improving pharmacy indicators.

Objective: To evaluate the expression of p53, c-erb-B-2, MIB1 and Bcl-2 in normal endometrium, endometriosis, atypical endometriosis and ovarian cancer associated with endometriosis, looking for immunohistochemical markers that may help determine endometriosis with premalignant potential. Study design: Between 1948 and 1999, 410 epithelial ovarian cancers and 521 cases of endometriosis were surgically treated at Fundacion Jimenez Diaz. Pathology reports and slides were reviewed. Four groups were defined: (1) endometriosis/cancer (n=17); (2) atypical endometriosis (n=6); (3) endometriosis (n=17); (4) endometrium (n=7). Tumors and controls were immunostained and evaluated for expression of p53, c-erb-B-2, MIB1 and Bcl-2. Statistical analysis was performed using Chi-square for linear trends, Fisher exact and Kruskal–Wallis tests. Results: Of the 410 cancers, 17 (4.1%) had associated endometriosis and of the 521 endometriosis, 6 (1.2 %) had atypical changes. Fourteen of 17 (82.4%) cancers associated with endometriosis and all atypical endometriosis had p53 overexpression. Only 2 of 17 (11.8%) endometriosis and none of the endometriums had mutant p53 (P

A strategy for performing synchronous undulator–monochromator scans (SUMS) compatible with the control system of Synchrotron Soleil has been developed. The implementation of the acquisition scheme has required the development of an electronic interface between the undulator and the beamline. The characterization of delays and jitters in the synchronous movement of various motor axes has motivated the development of a new electronic synchronization scheme among various axes, including the case when one of the axes is electronically accessible in `read-only' mode. A software prototype has been developed to allow the existing hard continuous software to work in user units. The complete strategy has been implemented and successfully tested at the TEMPO beamline.