SERS study of thiocarbonyl compounds adsorbed on metal nanoparticles

Thiocarbonyl compounds have been reported to exhibit interesting biological and pharmacological properties but they are many often characterized by their toxicological effects. However the chemistry of thiobenzoic acid (TBA) and thiobenzamide (TB) has not been fully studied yet. Some of the biological studies of TBA are related to the tautomerism of thiocarboxylic acids and the important role that the -C(=O)-S and -C(=S)-O functional groups play in the catalytic activities of enzymes such as cysteine or serine proteases.1 On the other hand, TB and derivatives are well known hepatotoxins and have been used as inhibitor in enzymatic reactions and in pharmacy due to their microbial activity.2 From a chemical point of view, thiocarboxylates are an interesting type of molecules having two different donor atoms, a soft sulfur donor atom and a hard oxygen donor one. The presence of these unlike groups can lead to the bonding with metal surfaces. Likewise the interaction of thiobenzamide and their derivatives with metals is of great interest because both the sulfur and nitrogen atoms are also able to coordinate with the surface. Therefore the high affinity of these molecules for metal surfaces makes them suitable SERS target adsorbates. Taking advantage of the fact that SERS spectroscopy is both surface selective and highly sensitive we have attempted to determine the molecular structure of TBA and TB once they are adsorbed on the metal. The main objective of this work is focussed on discussing the observed vibrational wavenumber shifts of TBA and TB upon adsorption on silver nanoparticles. In this work the SERS substrates have been prepared by using different colloidal silver solutions according to the method described by Creighton et al.3 and Leopold and Lendl.4 The analysis of the vibrational wavenumbers shifts of the Raman and SERS spectra allow us to know the adsorption process (Figure 1). In the case of TBA, the wavenumber of the SERS band assigned to (C=O) vibrational mode shows an important blue shift up to 40 cm-1 with respect to the Raman whereas the (C-S) band undergoes a red shift up to 40 cm-1. These results suggest a unidentate coordination of TBA to the silver surface through the sulfur atom. On the other hand, the SERS band assigned in the case of TB to Amide III (mainly (CN)) exhibits a significant blueshift up to 41 cm-1, and the SERS band assigned to Amide I (mainly (CS)) shows a red shift up to 11 cm-1. These wavenumber shifts indicate that TB interacts to the silver surface through the sulfur atom. Interestingly, in previous SERS studies of pyridinecarboxamides and benzamide we have observed that some SERS bands assigned to 1;ring, Amide I (mainly (C=O)) and Amide III (mainly C-N)) show wavenumber shifts of +50, -50 and +10 cm-1, respectively, which were attributed to the deprotonation of carboxamide group.5,6 Finally, in order to verify experimental results DFT calculations have been carried out for different silver complexes of TBA and TB concluding that the unidentate coordination is the most likely interaction of both of them.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The Longitudinal Association Between a Discrepancy Measure of Anosognosia in Patients with Dementia, Caregiver Burden and Depression

Anosognòsia; Cuidadors; Estudis longitudinalsAnosognosia; Cuidadores; Estudios longitudinalesAnosognosia; Caregivers; Longitudinal studiesBackground: According to cross-sectional studies, there is an association between anosognosia in people with dementia and caregiver’s burden and depression. Anosognosia in patients may be a cause of caregiver burden and depression. However, variability in caregiver anosognosia ratings may exist as caregivers with burden and depression may have a more pessimistic view of the patients’ health. Objective: To assess the variability of caregiver anosognosia ratings of patients with dementia using a widely used anosognosia scale and its longitudinal relationship with caregiver burden and depression. Methods: A convenience cohort of 221 consecutive dementia outpatient and caregiver dyads was followed up at 12 and 24 months. The main instruments used were the Anosognosia Questionnaire-Dementia (AQ-D), Caregiver Burden Interview, and Geriatric Depression Scale. Linear mixed models were used including time as a factor in every model. Multivariate analyses controlled for caregiver’s socio-demographic and possible confounding factors. Results: Attrition at 12 and 24 months was 24.9% and 42.5% respectively. Patients at baseline were on average 77.8 years of age, 63.3% were women, and 63.3% had < 5 years of education. In the bivariate analyses, caregiver burden, depression, and gender were associated with caregiver ratings of total, cognitive, and personality AQ-D of the patient at different time points. Multivariate analyses revealed burden as the caregiver variable most consistently associated with total, cognitive, and personality caregiver AQ-D ratings of the patient. Conclusion: Some caregiver characteristics, especially burden, are associated with caregiver ratings of AQ-D with regard to the patientPSI 2010-1901

Inestabilidad microsatelital en pacientes con cáncer colorectal hereditario sin poliposis (cchsp)

Determinar la frecuencia de Inestabilidad Microsatelital (IM) en pacientes con sospecha clínica de CCHSP, con el fin de iniciar el desarrollo de programas de aproximación diagnóstica

Using geographically weighted regression to explore the spatially heterogeneous spread of bovine tuberculosis in England and Wales

An understanding of the factors that affect the spread of endemic bovine tuberculosis (bTB) is critical for the development of measures to stop and reverse this spread. Analyses of spatial data need to account for the inherent spatial heterogeneity within the data, or else spatial autocorrelation can lead to an overestimate of the significance of variables. This study used three methods of analysis—least-squares linear regression with a spatial autocorrelation term, geographically weighted regression (GWR) and boosted regression tree (BRT) analysis—to identify the factors that influence the spread of endemic bTB at a local level in England and Wales. The linear regression and GWR methods demonstrated the importance of accounting for spatial differences in risk factors for bTB, and showed some consistency in the identification of certain factors related to flooding, disease history and the presence of multiple genotypes of bTB. This is the first attempt to explore the factors associated with the spread of endemic bTB in England and Wales using GWR. This technique improves on least-squares linear regression approaches by identifying regional differences in the factors associated with bTB spread. However, interpretation of these complex regional differences is difficult and the approach does not lend itself to predictive models which are likely to be of more value to policy makers. Methods such as BRT may be more suited to such a task. Here we have demonstrated that GWR and BRT can produce comparable outputs

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Thermal Neutron Relative Biological Effectiveness Factors for Boron Neutron Capture Therapy from In Vitro Irradiations

The experimental determination of the relative biological effectiveness of thermal neutron factors is fundamental in Boron Neutron Capture Therapy. The present values have been obtained while using mixed beams that consist of both neutrons and photons of various energies. A common weighting factor has been used for both thermal and fast neutron doses, although such an approach has been questioned. At the nuclear reactor of the Institut Laue-Langevin a pure low-energy neutron beam has been used to determine thermal neutron relative biological effectiveness factors. Different cancer cell lines, which correspond to glioblastoma, melanoma, and head and neck squamous cell carcinoma, and non-tumor cell lines (lung fibroblast and embryonic kidney), have been irradiated while using an experimental arrangement designed to minimize neutron-induced secondary gamma radiation. Additionally, the cells were irradiated with photons at a medical linear accelerator, providing reference data for comparison with that from neutron irradiation. The survival and proliferation were studied after irradiation, yielding the Relative Biological Effectiveness that corresponds to the damage of thermal neutrons for the different tissue types.Asociacion Espanola Contra el Cancer (AECC) PS16163811PORRSpanish MINECO FIS2015-69941-C2-1-PJunta de Andalucia P11-FQM-8229Campus of International Excellence BioTic P-BS-64University of Granada Chair Neutrons for Medicine: the Spanish Fundacion ACSAsociacion Capitan AntonioFundacion ACSLa Kuadrilla de IznallozSonriendo Se Puede Gana

Relación del mindfulness, inteligencia emocional y síndrome de burnout en el proceso de enseñanza-aprendizaje: una revisión sistemática

Emotional intelligence is important in the way emotions are acquired, processed, and regulated. One of the possible psychosocial risks is Burnout syndrome, understood as emotional fatigue. The mindfulness, is a practice that makes us aware of internal events that we feel, where it adopts an attitude of self-acceptance. The aim of this work is to carry out a systematic review that addresses the relationships between emotional intelligence and Burnout syndrome, through the practice of Mindfulness... The search was carried out in the Web of Science, which after applying the inclusion and exclusion criteria obtained a sample of 22 articles between the years 2000-2017. The main conclusions are the close relationship between psychosocial and emotional aspects, since stressful processes differ with emotional intelligence, a fact that is controlled with Mindfulness.La inteligencia emocional es importante en la forma en que las emociones son adquiridas, procesadas y reguladas. Uno de los posibles riesgos psicosociales es el síndrome de Burnout, entendiéndose como el cansancio emocional. El mindfulness, es una práctica que nos hace tomar la conciencia de los sucesos internos que sentimos, donde se adopta una actitud de aceptación propia. El presente trabajo tiene como objetivo realizar una revisión sistemática que aborden las relaciones entre la inteligencia emocional y el síndrome de Burnout, a través de la práctica de Mindfulness. La búsqueda se realizó en la Web of Science, que tras aplicar los criterios de inclusión y exclusión se obtuvo una muestra de 22 artículos entre los años 2000-2017. Como principales conclusiones se expone la estrecha relación entre aspectos psicosociales y emocionales, pues los procesos estresantes difieren con la inteligencia emocional, hecho que se controla con el Mindfulness

Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network

Missing data is one of the most common preprocessing problems. In this paper, we experimentally research the use of generative and non-generative models for feature reconstruction. Variational Autoencoder with Arbitrary Conditioning (VAEAC) and Generative Adversarial Imputation Network (GAIN) were researched as representatives of generative models, while the denoising autoencoder (DAE) represented non-generative models. Performance of the models is compared to traditional methods k-nearest neighbors (k-NN) and Multiple Imputation by Chained Equations (MICE). Moreover, we introduce WGAIN as the Wasserstein modification of GAIN, which turns out to be the best imputation model when the degree of missingness is less than or equal to 30%. Experiments were performed on real-world and artificial datasets with continuous features where different percentages of features, varying from 10% to 50%, were missing. Evaluation of algorithms was done by measuring the accuracy of the classification model previously trained on the uncorrupted dataset. The results show that GAIN and especially WGAIN are the best imputers regardless of the conditions. In general, they outperform or are comparative to MICE, k-NN, DAE, and VAEAC.Comment: Preprint of the conference paper (ICCS 2020), part of the Lecture Notes in Computer Scienc

Extracellular ATP released by osteoblasts is a key local inhibitor of bone mineralisation

Previous studies have shown that exogenous ATP (>1µM) prevents bone formation in vitro by blocking mineralisation of the collagenous matrix. This effect is thought to be mediated via both P2 receptor-dependent pathways and a receptor-independent mechanism (hydrolysis of ATP to produce the mineralisation inhibitor pyrophosphate, PPi). Osteoblasts are also known to release ATP constitutively. To determine whether this endogenous ATP might exert significant biological effects, bone-forming primary rat osteoblasts were cultured with 0.5-2.5U/ml apyrase (which sequentially hydrolyses ATP to ADP to AMP + 2Pi). Addition of 0.5U/ml apyrase to osteoblast culture medium degraded extracellular ATP to <1% of control levels within 2 minutes; continuous exposure to apyrase maintained this inhibition for up to 14 days. Apyrase treatment for the first 72 hours of culture caused small decreases (≤25%) in osteoblast number, suggesting a role for endogenous ATP in stimulating cell proliferation. Continuous apyrase treatment for 14 days (≥0.5U/ml) increased mineralisation of bone nodules by up to 3-fold. Increases in bone mineralisation were also seen when osteoblasts were cultured with the ATP release inhibitors, NEM and brefeldin A, as well as with P2X1 and P2X7 receptor antagonists. Apyrase decreased alkaline phosphatase (TNAP) activity by up to 60%, whilst increasing the activity of the PPi-generating ecto-nucleotide pyrophosphatase/phosphodiesterases (NPPs) up to 2.7-fold. Both collagen production and adipocyte formation were unaffected. These data suggest that nucleotides released by osteoblasts in bone could act locally, via multiple mechanisms, to limit mineralisation

Radiobiology data of melanoma cells after low-energy neutron irradiation and boron compound administration

The cold neutron beam at the PF1b line at the Institut Laue-Langevin (ILL), without fast neutrons and a low contribution of gamma rays, is a very suitable facility to measure cell damage following low-energy neutron irradiation. The biological damage associated with the thermal and the boron doses can be obtained in order to evaluate the relative biological effectiveness (RBE) for Boron Neutron Capture Therapy. Three different experiments were carried out on the A375 melanoma cell line: the first one in a hospital LINAC, to obtain the reference radiation data, and the other two at the ILL, in which the damage to cells with and without boron compounds added was measured