Functionalization of gold nanostars with cationic ß-cyclodextrin-based polymer for drug co-loading and SERS monitoring

Gold nanostars (AuNSs) exhibit modulated plasmon resonance and have a high SERS enhancement factor. However, their low colloidal stability limits their biomedical application as a nanomaterial. Cationic ß-cyclodextrin-based polymer (CCD/P) has low cytotoxicity, can load and transport drugs more efficiently than the corresponding monomeric form, and has an appropriate cationic group to stabilize gold nanoparticles. In this work, we functionalized AuNSs with CCD/P to load phenylethylamine (PhEA) and piperine (PIP) and evaluated SERS-based applications of the products. PhEA and PIP were included in the polymer and used to functionalize AuNSs, forming a new AuNS-CCD/P-PhEA-PIP nanosystem. The system was characterized by UV–VIS, IR, and NMR spectroscopy, TGA, SPR, DLS, zeta potential analysis, FE-SEM, and TEM. Additionally, Raman optical activity, SERS analysis and complementary theoretical studies were used for characterization. Minor adjustments increased the colloidal stability of AuNSs. The loading capacity of the CCD/P with PhEA-PIP was 95 ± 7%. The physicochemical parameters of the AuNS-CCD/P-PhEA-PIP system, such as size and Z potential, are suitable for potential biomedical applications Raman and SERS studies were used to monitor PhEA and PIP loading and their preferential orientation upon interaction with the surface of AuNSs. This unique nanomaterial could be used for simultaneous drug loading and SERS-based detection

Modelling the Longevity of Dental Restorations by means of a CBR system

The lifespan of dental restorations is limited. Longevity depends on the material used and the different characteristics of the dental piece. However, it is not always the case that the best and longest lasting material is used since patients may prefer different treatments according to how noticeable the material is. Over the last 100 years, the most commonly used material has been silver amalgam, which, while very durable, is somewhat aesthetically displeasing. Our study is based on the collection of data from the charts, notes, and radiographic information of restorative treatments performed by Dr. Vera in 1993, the analysis of the information by computer artificial intelligence to determine the most appropriate restoration, and the monitoring of the evolution of the dental restoration. The data will be treated confidentially according to the Organic Law 15/1999 on 13 December on the Protection of Personal Data. This paper also presents a clustering technique capable of identifying the most significant cases with which to instantiate the case-base. In order to classify the cases, a mixture of experts is used which incorporates a Bayesian network and a multilayer perceptron; the combination of both classifiers is performed with a neural network

Retreatment predictions in odontology by means of CBR Systems

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising

Application of Soft Computing Technologies toward Assessment and Skills Development

Schools and universities face multiple challenges when they target initiating or expanding undergraduate programs. Education has traditionally utilized a teacher-centered educational and assessment approach. Only few attempts exist to involve objective feedback and non-traditional assessment methods and technologies to improve the processes of teaching, learning, and education in general. This paper addresses a novel objective multi-parameter assessment methodology based on Soft computing technology to discover the effect of students’ groupings by exploiting the interrelationships between the grades the students received for their laboratory subjects and the grade they obtained in the university enrolment exam. The research results allow for exploring non-desirable discordant teaching and assessment practices for individuals or groups. In addition, the results obtained illustrate opportunities to focus on the individual student during the education process and determine adaptive teaching strategies based on the particular level of knowledge and experience. Toward these results statistical and Soft computing models implementing Unsupervised Neural and Exploratory Projection Techniques have been applied to carry on the objective assessment of the students’ skills development during the entire higher education period. Empirical verification of the proposed assessment model is performed in a real environment, where a case study is defined, and analysed. The real data set to validate the performance of the proposed approach has been collected at the School of Dentistry of the Complutense University of Madrid

Identification of coexisting indigo species in an ancient green thread using direct plasmon-enhanced raman spectroscopy

A green ancient thread sample from a Chilean mummy turban was analyzed by plasmon-enhanced Raman scattering spectroscopy using a direct drop-colloidal method. The enhanced-Raman signals in the sample are associated with biomolecules from the thread and two coexisting dyes, indigo and leuco-indigo. The presence of indigo (blue colour) was identified from its most characteristic vibrational bands. Leuco-indigo (yellow colour) was identified for the first time in an ancient textile; its SERS signals are coincident with the SERS bands of a synthesized leuco-indigo. The interconversion leuco-indigo to indigo was followed by UV-visible spectroscopy. Based on theoretical calculations it is proposed that the interconversion involves a it electron delocalization mainly around the NC-CN bridge. The mixture of both dyes (indigo and leuco-indigo) is the responsible for the green colour observed.Universidad de Playa Ancha (concurso regular de investigacion ano 2018) FONDECYT 3150222 EQM150020 FONDEQUIP CNE 10-1920 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 1115094

Electric-field induced bistability in single-molecule conductance measurements for boron coordinated curcuminoid compounds

© 2018 The Royal Society of Chemistry. We have studied the single-molecule conductance of a family of curcuminoid molecules (CCMs) using the mechanically controlled break junction (MCBJ) technique. The CCMs under study contain methylthio (MeS-) as anchoring groups: MeS-CCM (1), the free-ligand organic molecule, and two coordination compounds, MeS-CCM-BF2 (2) and MeS-CCM-Cu (3), where ligand 1 coordinates to a boron center (BF2 group) and to a CuII moiety, respectively. We found that the three molecules present stable molecular junctions allowing detailed statistical analysis of their electronic properties. Compound 3 shows a slight increase in the conductance with respect to free ligand 1, whereas incorporation of BF2 (compound 2) promotes the presence of two conductance states in the measurements. Additional experiments with control molecules point out that this bistability is related to the combination of MeS- anchoring groups and the BF2 moiety within the structure of the molecules

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status