Depression as a Risk Factor for Dementia and Alzheimer’s Disease

Preventing the onset of dementia and Alzheimer’s disease (AD), improving the diagnosis, and slowing the progression of these diseases remain a challenge. The aim of this study was to elucidate the association between depression and dementia/AD and to identify possible relationships between these diseases and different sociodemographic and clinical features. In this regard, a case-control study was conducted in Spain in 2018–2019. The definition of a case was: A person ≥ 65 years old with dementia and/or AD and a score of 5–7 on the Global Deterioration Scale (GDS). The sample consisted of 125 controls; among the cases, 96 had dementia and 74 had AD. The predictor variables were depression, dyslipidemia, type 2 diabetes mellitus, and hypertension. The results showed that depression, diabetes mellitus, and older age were associated with an increased likelihood of developing AD, with an Odds Ratio (OR) of 12.9 (95% confidence interval (CI): 4.3–39.9), 2.8 (95% CI: 1.1–7.1) and 1.15 (95% CI: 1.1–1.2), respectively. Those subjects with treated dyslipidemia were less likely to develop AD (OR 0.47, 95% CI: 0.22–1.1). Therefore, depression and diabetes mellitus increase the risk of dementia, whereas treated dyslipidemia has been shown to reduce this risk

Aceite de oliva virgen y regulación hormonal de la presión arterial: una revisión del papel de los enzimas proteolíticos

Numerosos estudios realizados en los últimos años, han puesto de manifiesto que los niveles elevados de grasa en la dieta están directamente relacionados con el desarrollo de diversas patologías, entre las que destacan enfermedades cardiovasculares, diabetes o incluso diversos tipos de cánceres. Estudios epidemiológicos también han demostrado que no sólo es importante la cantidad, sino también el tipo de grasa de la dieta. Son especialmente conocidos los efectos beneficiosos de la dieta mediterránea, caracterizada entre otros aspectos, por un consumo elevado de ácidos grasos monoinsaturados como el oleico. En cualquier caso, no se conoce con exactitud las relaciones existentes entre el tipo de grasa de la dieta y el desarrollo de las distintas patologías. Las aminopeptidasas son enzimas proteolíticos implicados en una amplia variedad de procesos biológicos, destacando su papel en el control de la presión arterial a través del sistema renina-angiotensina. En esta revisión se estudia la influencia de una dieta enriquecida en aceite de oliva sobre la actividad aminopeptidásica sérica y de tejidos periféricos, analizando su influencia en la regulación del sistema renina-angiotensina para el control de la presión arterial y el balance de líquidos y electrolitos.The intake of high fat dietary levels is related to the development of several pathologies such as cardiovascular diseases, diabetes and cancer. However, epidemiological studies have demonstrated that not only the amount but also the type of dietary fat participates in the origin of the diseases. In fact, several important beneficts have been attributed to the Mediterranean diet, characterized by the high intake of monoinsaturated fatty acids such as oleic acid preferently. In any case, the relationship between the type of dietary fat an the development of diseases are unknown. Aminopeptidases are proteolytic enzymes involved in several biological proccesses, regulating blood pressure through the renin-angiotensin system. In this review, the influence of an olive oil-enriched diet is presented, analyzing their role in the regulation of blood pressure, local blood flow and fluid and electrolytic balance among other functions

Monitoring and evaluation of nursing practices through the sisep application

El avance tecnológico y la consecuente incorporación de las TICs en el ámbito docente ha conllevado la aparición de nuevas herramientas para facilitar a los docentes el proceso de seguimiento y evaluación del alumnado. De igual forma, dicho avance ha contribuido a la adquisición de un modelo de aprendizaje más proactivo e individualizado por parte del alumnado. El presente proyecto pretende implementar una herramienta informática denominada “Seguimiento y Evaluación de Practicas” (SISEP) en las asignaturas de prácticas clínicas de la titulación de Grado en Enfermería para optimizar el seguimiento y la evaluación de los alumnos durante el desarrollo de sus prácticas externas, así como mejorar el proceso de adquisición de competencias y habilidades. La metodología ha consistido en la elaboración de material didáctico para dicha aplicación y la posterior evaluación del grado de satisfacción de los distintos roles implicados en su uso mediante un cuestionario autoadministrado de elaboración propia. El grado de satisfacción con respecto a la aplicación fue alto, señalando que contribuye de forma decisiva en la adquisición de competencias, aunque no en todos los casos los usuarios han considerado su interfaz como completamente sencilla o intuitiva.The technological advance and consequent incorporation of IT in the teaching field has entailed the appearance of new tools to facilitate teachers the process of monitoring and evaluating students. In the same way, this advance has contributed to the acquisition of a more proactive and individualized learning model on the students' side. The present project intends to implement a computer tool called “Monitoring and Evaluation of Practices” (SISEP) in the subjects of clinical practices of the degree in Nursing in order to optimize the monitoring and evaluation of students during the development of their external practices, as well as improving the process of acquiring skills and abilities. The methodology used consisted in the elaboration of the teaching material and the later evaluation of the degree of satisfaction from the different roles involved through the use of a self-administered, self-produed questionnaire. The degree of satisfaction regarding the application was high, pointing out its decisive contribution to the acquisition of skills, even if not all users have found its interface clear or intuitive enough

Measurement of the azimuthal anisotropy of Y(1S) and Y(2S) mesons in PbPb collisions at √S^{S}NN = 5.02 TeV

The second-order Fourier coefficients (υ$_{2}$) characterizing the azimuthal distributions of Υ(1S) and Υ(2S) mesons produced in PbPb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV are studied. The Υmesons are reconstructed in their dimuon decay channel, as measured by the CMS detector. The collected data set corresponds to an integrated luminosity of 1.7 nb$^{-1}$. The scalar product method is used to extract the υ$_{2}$ coefficients of the azimuthal distributions. Results are reported for the rapidity range |y| < 2.4, in the transverse momentum interval 0 < p$_{T}$ < 50 GeV/c, and in three centrality ranges of 10–30%, 30–50% and 50–90%. In contrast to the J/ψ mesons, the measured υ$_{2}$ values for the Υ mesons are found to be consistent with zero

Performance of the CMS Level-1 trigger in proton-proton collisions at √s = 13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-of-mass energy of 13\TeV. During Run 2 (years 2015–2018) the LHC eventually reached a luminosity of 2.1× 10$^{34}$ cm$^{-2}$s$^{-1}$, almost three times that reached during Run 1 (2009–2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016–2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals

Measurement of prompt D0^{0} and D‾\overline{D}0^{0} meson azimuthal anisotropy and search for strong electric fields in PbPb collisions at root SNN\sqrt{S_{NN}} = 5.02 TeV

The strong Coulomb field created in ultrarelativistic heavy ion collisions is expected to produce a rapiditydependent difference (Av2) in the second Fourier coefficient of the azimuthal distribution (elliptic flow, v2) between D0 (uc) and D0 (uc) mesons. Motivated by the search for evidence of this field, the CMS detector at the LHC is used to perform the first measurement of Av2. The rapidity-averaged value is found to be (Av2) = 0.001 ? 0.001 (stat)? 0.003 (syst) in PbPb collisions at ?sNN = 5.02 TeV. In addition, the influence of the collision geometry is explored by measuring the D0 and D0mesons v2 and triangular flow coefficient (v3) as functions of rapidity, transverse momentum (pT), and event centrality (a measure of the overlap of the two Pb nuclei). A clear centrality dependence of prompt D0 meson v2 values is observed, while the v3 is largely independent of centrality. These trends are consistent with expectations of flow driven by the initial-state geometry. ? 2021 The Author. Published by Elsevier B.V. This is an open access article under the CC BY licens

Measurement of the Y(1S) pair production cross section and search for resonances decaying to Y(1S)μ⁺μ⁻ in proton-proton collisions at √s = 13 TeV

The fiducial cross section for Y(1S)pair production in proton-proton collisions at a center-of-mass energy of 13TeVin the region where both Y(1S)mesons have an absolute rapidity below 2.0 is measured to be 79 ± 11 (stat) ±6 (syst) ±3 (B)pbassuming the mesons are produced unpolarized. The last uncertainty corresponds to the uncertainty in the Y(1S)meson dimuon branching fraction. The measurement is performed in the final state with four muons using proton-proton collision data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9fb$^{-1}$. This process serves as a standard model reference in a search for narrow resonances decaying to Y(1S)μ$^{+}$μ$^{-}$ in the same final state. Such a resonance could indicate the existence of a tetraquark that is a bound state of two bquarks and two b̅ antiquarks. The tetraquark search is performed for masses in the vicinity of four times the bottom quark mass, between 17.5 and 19.5GeV, while a generic search for other resonances is performed for masses between 16.5 and 27GeV. No significant excess of events compatible with a narrow resonance is observed in the data. Limits on the production cross section times branching fraction to four muons via an intermediate Y(1S)resonance are set as a function of the resonance mass

Pileup mitigation at CMS in 13 TeV data

With increasing instantaneous luminosity at the LHC come additional reconstruction challenges. At high luminosity, many collisions occur simultaneously within one proton-proton bunch crossing. The isolation of an interesting collision from the additional "pileup" collisions is needed for effective physics performance. In the CMS Collaboration, several techniques capable of mitigating the impact of these pileup collisions have been developed. Such methods include charged-hadron subtraction, pileup jet identification, isospin-based neutral particle "δβ" correction, and, most recently, pileup per particle identification. This paper surveys the performance of these techniques for jet and missing transverse momentum reconstruction, as well as muon isolation. The analysis makes use of data corresponding to 35.9 fb$^{-1}$ collected with the CMS experiment in 2016 at a center-of-mass energy of 13 TeV. The performance of each algorithm is discussed for up to 70 simultaneous collisions per bunch crossing. Significant improvements are found in the identification of pileup jets, the jet energy, mass, and angular resolution, missing transverse momentum resolution, and muon isolation when using pileup per particle identification

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The identification performances of a variety of algorithms are characterized in simulated events and directly compared with data. The algorithms are validated using proton-proton collision data at √s = 13TeV, corresponding to an integrated luminosity of 35.9 fb−1. Systematic uncertainties are assessed by comparing the results obtained using simulation and collision data. The new techniques studied in this paper provide significant performance improvements over non-ML techniques, reducing the background rate by up to an order of magnitude at the same signal efficiency