Improved sensing of capsaicin with TiO2 nanoparticles modified epoxy graphite electrode

Altres ajuts: M. S. thanks to AGAUR, Generalitat de Catalunya and to European Social Fund, European Union for FI fellowship. M. d. V. thanks the support from program ICREA Academia.The presented research focuses on the electrochemical determination of capsaicin, a lipophilic alkaloid which originates hotness in chili peppers. An electrochemical sensor based on epoxy-graphite composite with the modification of titanium dioxide (TiO2) nanoparticles is developed for the determination of this alkaloid. The measurements were carried out in glycine buffer at pH 2.5 using cyclic voltammetry. Two linear concentration ranges were obtained from 6 to 75 μM (R=0.99) and from 12 to 138 μM, with a detection limit of 5.34 μM and 11.3 μM capsaicin, for 1st and 2nd oxidation peak, respectively. The main advantage of developed sensor is its repeatability and robustness against fouling; the relative standard deviation (RSD) value was 2.53 % (n=10). This voltammetric sensing procedure has successfully been applied to quantify capsaicin in various real samples such as hot chili sauce and pharmaceutical preparations

Measles delay in India: the role of parents’ behaviour

Background: Objectives were to identify the factors influencing the timeliness of measles immunisation in India, as well as to explore whether parental behaviour in health care seeking facilities varies depending on the gender of child.Methods: A cross-sectional study was undertaken in India using secondary data from the fourth phase of the district level household and facility survey (DLHS 4). To estimate the age-specific coverage rates scientifically and thoroughly Kaplan-Meier survival analysis was applied. The risk factors for delayed measles immunisation were identified by using cox proportional hazard regression model.Results: Individual factors, social factors, awareness, and facilitatory factors all have a significant impact on the timeliness of measles immunisation in India. Additionally, it can also be concluded that in the case of a male child, institutional delivery significantly improves health-seeking behaviour among the parents compared to a female child. Conclusions: Numerous elements like the place of residence, economic position, and caste limit the timeliness of measles immunisation in India. Parents' health-seeking behaviour is also significant in the list of influential factors, like mother’s antenatal visit during pregnancy, the child's place of delivery, and motivation for child immunisation. In India child's gender and birth order discovered to have an impact on measles immunisation timeliness. Furthermore, we discovered that parents' health-seeking behaviour is not gender-neutral, but rather favours male child more.

Voltammetric sensors and Electronic Tongue for improved sensing of food and pharmaceutical ingredients

Aquesta tesi doctoral se centra principalment en la millora de les propietats de detecció electroquímica de l'elèctrode compòsit de grafit epoxi (GEC) mitjançant l'ús de modificadors. L'elèctrode compòsit de resina epoxi i grafit és la plataforma de detecció fonamental en aquest estudi electroquímic, és a dir, són els elèctrodes de treball en la configuració de la cel·la de tres elèctrodes. Però hi ha diversos problemes com ara el soroll, l'enverinament, l'estabilitat de resposta i els temps de resposta elevats associats a la detecció electroquímica de determinats compostos electroactius. Per resoldre aquests problemes, és important dur a terme una recerca de diferents tècniques de modificació i millorar les característiques de resposta dels elèctrodes de treball. A més, el nostre objectiu final en aquest treball de tesi va ser desenvolupar una llengua electrònica (LE) amb una matriu de sensors optimitzada per resoldre mescles de mostres. Amb aquesta finalitat, volem essencialment elèctrodes modificats per obtenir una resposta diferenciada per als diferents compostos implicats en les nostres aplicacions de llengua electrònica. Aquesta és una condició necessària per a les llengües electròniques: diferents sensors que proporcionen senyals diferents per als diferents compostos. Per això aquí, en aquesta investigació, s'ha treballat per trobar alguns modificadors per incorporar juntament amb el compòsit epoxi i grafit al sensor. S'ha estudiat l'efecte d'aquesta modificació en la millora de les plataformes de detecció. Juntament amb l'elèctrode de resina epoxi modificat, també s'han estudiat les possibilitats d'un elèctrode de metall nu a la plataforma de detecció electroquímica. A més, s'han treballat per a una selecció prèvia de sensors òptims per a una llengua electrònica mitjançant anàlisi canònica de variables, anàlisi de components principals i un factor de clustering "F". Per il·lustrar l'aplicabilitat de la llengua electrònica amb aquesta metodologia de selecció prèvia, s'ha demostrat la quantificació i discriminació simultània de tres ingredients farmacèutics diferents, a saber, paracetamol, àcid úric i àcid ascòrbic. El rendiment de la LE proposada amb aquesta selecció prèvia de sensors es va comparar després amb altres LEs treballades anteriorment que realitzaven la resolució de la mateixa mescla.Esta tesis doctoral se centra principalmente en la mejora de las propiedades de detección electroquímica del electrodo composite de grafito epoxi (GEC) mediante el uso de modificadores. El electrodo composite de resina epoxi y grafito es la plataforma de detección fundamental en este estudio electroquímico, es decir, son los electrodos de trabajo en la configuración de celda de tres electrodos. Pero existen varios problemas como el ruido, el envenenamiento, la estabilidad de respuesta y los tiempos de respuesta largos asociados con la detección electroquímica de determinados compuestos electroactivos. Para resolver esos problemas, es importante realizar una investigación exhaustiva en busca de diferentes técnicas de modificación y mejorar las características de respuesta de los electrodos de trabajo. Adicionalmente, nuestro objetivo final en este trabajo de tesis fue desarrollar una lengua electrónica (LE) con una matriz de sensores optimizada para resolver mezclas de muestras. Para este propósito, esencialmente queremos electrodos modificados para obtener una respuesta diferenciada para los diferentes compuestos involucrados en nuestras aplicaciones de lengua electrónica. Esta es una condición necesaria para las lenguas electrónicas: diferentes sensores que proporcionen señales diferentes para los diferentes compuestos. Por lo tanto, en esta investigación se ha trabajado para encontrar algunos modificadores que se incorporarán junto con el composite de epoxi y grafito en el sensor. Se ha estudiado el efecto de esta modificación en la mejora de las plataformas de detección. Junto con el electrodo de resina epoxi modificado, también se han estudiado las posibilidades del electrodo de metal desnudo en la plataforma de detección electroquímica. Adicionalmente se han realizado trabajos para una selección previa de sensores óptimos para una lengua electrónica utilizando análisis canónico de variables, análisis de componentes principales y un factor de agrupamiento "F". Para ilustrar la aplicabilidad de la lengua electrónica con esta metodología de selección previa, se ha demostrado la cuantificación y discriminación simultáneas de tres ingredientes farmacéuticos diferentes, a saber, paracetamol, ácido úrico y ácido ascórbico. El rendimiento de la LE propuesta con esta selección previa de sensores se comparó con otras LEs trabajadas anteriormente que realizan la resolución de la misma mezcla.This PhD thesis is primarily focused on the improvement of electrochemical sensing properties of graphite epoxy composite (GEC) electrode by means of modification. Graphite epoxy resin composite electrode is the fundamental sensing platform in this electrochemical study i.e. they are the working electrodes in the three electrodes cell configuration. But there are various problems such as noise, fouling, unstable baseline and long response time associated with the sensing of electro-active compounds electrochemically. To solve those problems, it is important to carry out extensive research in search of different modification techniques for working electrodes. Additionally, our final objective in this thesis work was to develop an electronic tongue (ET) with optimal sensors for resolving sample mixtures. For that purpose, essentially we want modified electrodes to obtain differentiated response for the different compounds involved in our electronic tongue applications. This is a necessary condition for electronic tongues: different sensors that provide different signals for the different compounds. Therefore here, in this research, work has been carried out to find some modifiers to be incorporated together with the graphite epoxy composite into the sensor. The effect of this modification on improving the sensing platforms has been studied. Along with modified epoxy resin electrode, possibilities of bare metal electrode in the electrochemical sensing platform have also been studied. Additionally works has been carried out for a priory selection of optimal sensors for an electronic tongue using canonical variate analysis, principal component analysis and a clustering factor "F". To illustrate the applicability of the electronic tongue with this a priory selection methodology, simultaneous quantification and discrimination of three different APIs namely Paracetamol, uric acid and ascorbic acid have been demonstrated. The performance of the proposed ET with this a priory selection of sensors was then benchmarked against other previously reported ETs performing the resolution of the same mixtures.

A decomposition analysis to understand the wealth-based inequalities in child vaccination in rural Southern Assam: A cross-sectional study

Background: The socio-environmental aspects of southern Assam reflect a general pattern of backwardness. Moreover, child healthcare resources in the region are inadequately used, leading to low vaccination coverage. Given this background, this paper attempted to comprehend wealth-based inequality in full vaccination in rural areas of southern Assam. Methodology: Based on a multistage cluster sampling approach, 360 children of 12–23 months were selected from the study area. To identify the predictors of a child, a non-linear model was estimated by using the generalized linear model (GLM) approach followed by Erreygers decomposition technique to quantify the wealth inequality in the obtained predictors in explaining the disparity in full vaccination. Result: The Bacillus Calmette–Guérin (BCG) vaccination recorded the highest vaccination coverage, at nearly 90% and the lowest was observed for the measles vaccine, around 61 percent. Slightly more than half of the eligible children (54 percent) were vaccinated against all the Universal Immunization Programme (UIP)-recommended vaccines. The decomposition analysis revealed that the occupation of the child's father, maternal age, birth order of the child, and health-seeking behavior such as antenatal care (ANC) were the prime factors related to inequality in full vaccination in the region. Conclusion: Vaccination coverage in the region has improved over time, however, full vaccination is concentrated towards the economically advantaged section of the society in rural southern Assam. Targeted, context-specific, and expanded government initiatives could aid in addressing the overall wealth-related full vaccination inequalities in the valley

Optimization of Sensors to be Used in a Voltammetric Electronic Tongue Based on Clustering Metrics

Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former allows us to visually compare the performance of the different sensors, while the latter allows us to numerically assess the impact that the inclusion/removal of the different sensors has on the discrimination ability of the ET. The proposed methodology is based on the measurement of a pure stock solution of each of the compounds under study, and the posterior analysis by PCA/CVA with stepwise iterative removal of the sensors that demote the clustering when retained as part of the array. To illustrate and assess the potential of such an approach, the quantification of paracetamol, ascorbic acid, and uric acid mixtures were chosen as the study case. Initially, an array of eight different electrodes was considered, from which an optimal array of four sensors was derived to build the quantitative ANN model. Finally, the performance of the optimized ET was benchmarked against the results previously reported for the analysis of the same mixtures, showing improved performance