ABSTRACT
We aimed to characterize the satisfaction and perceptions of the residents of Lima about different aspects of urban life that can affect their quality of life and health, identifying differences by socioeconomic status (SES) and changes over time. A secondary data analysis of the "Lima Cómo Vamos" survey was conducted between 2010 and 2019. Results are reported through percentages, with differences between SES for each year and between years. In 2019, satisfaction and perceptions were mostly unfavorable, and have decreased by up to 30% over time. People with lower SES had more unfavorable evaluations and with greater reductions over time. This dissatisfaction and unfavorable perceptions reveal deficiencies in public services and urban conditions that could negatively affect the quality of life and health, making it necessary to design and implement policies that reduce socioeconomic gaps and improve the health of Lima citizens.
Se buscó caracterizar la satisfacción y percepciones de los residentes de Lima Metropolitana sobre distintos aspectos de la ciudad que pueden afectar su calidad de vida y salud, identificando diferencias por nivel socioeconómico (NSE) y cambios en el tiempo. Se realizó un análisis secundario de la Encuesta «Lima Cómo Vamos¼ entre 2010 y 2019, reportando los resultados mediante porcentajes, con diferencias entre NSE para cada año y entre años. En 2019 la satisfacción y percepciones eran mayoritariamente desfavorables, y han disminuido hasta en 30 puntos porcentuales con el tiempo. Las personas de NSE más bajos tenían valoraciones más desfavorables y con mayores reducciones en el tiempo. Esta insatisfacción y percepciones desfavorables revelan deficiencias en servicios públicos y condiciones urbanas que podrían afectar negativamente la calidad de vida y salud, haciendo necesarias políticas que reduzcan las brechas socioeconómicas y mejoren la salud de los ciudadanos de Lima Metropolitana.
Subject(s)
Personal Satisfaction , Quality of Life , Cities , Humans , Social Class , Socioeconomic Factors , Surveys and QuestionnairesABSTRACT
An indirect enzyme-linked immunosorbent assay (ELISA) was developed for differentiation of animals infected with foot-and-mouth disease virus (FMDV) from vaccinated animals. The test was based on a highly pure and concentrated preparation of recombinant 3AB1 protein obtained by expression in a prokaryotic system, protein separation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and electro elution. Experimental- and field-serum samples from naive, vaccinated, and infected cattle were tested for anti3AB1 antibody using the ELISA. A cutoff level was set at 35% of the maximum absorbance obtained with a positive control serum (FMDV-infected animal, 21 days postinfection [dpi]). This assay could detect antibodies from sera of animals experimentally infected by contact (n = 118) with a sensitivity of 97.5%. The specificity was 100%, based on negative test results obtained on 109 sera from naive animals. Remarkably, all sera from animals vaccinated either once (n = 102) or twice (n = 30) were negative. In addition, this 3AB1-ELISA could detect seroconversion at 7 dpi in animals inoculated intradermolingually. This assay constitutes an important tool for the rapid detection of FMDV outbreaks in a vaccinated population. In addition, it presents a reliable, economical, and simple method for testing large numbers of serum samples.
Subject(s)
Antigens, Viral/isolation & purification , Enzyme-Linked Immunosorbent Assay/veterinary , Foot-and-Mouth Disease Virus/immunology , Foot-and-Mouth Disease/diagnosis , Viral Nonstructural Proteins/isolation & purification , Viral Vaccines , Animals , Cattle , Enzyme-Linked Immunosorbent Assay/methods , Foot-and-Mouth Disease/immunology , Foot-and-Mouth Disease/prevention & control , Male , Recombinant Proteins/isolation & purificationABSTRACT
A capillary electrophoresis-mass spectrometry (CE-MS) method has been developed to perform routine, automated analysis of low-molecular-weight peptides in human serum. The method incorporates transient isotachophoresis for in-line preconcentration and a sheathless electrospray interface. To evaluate the performance of the method and demonstrate the utility of the approach, an experiment was designed in which peptides were added to sera from individuals at each of two different concentrations, artificially creating two groups of samples. The CE-MS data from the serum samples were divided into separate training and test sets. A pattern-recognition/feature-selection algorithm based on support vector machines was used to select the mass-to-charge (m/z) values from the training set data that distinguished the two groups of samples from each other. The added peptides were identified correctly as the distinguishing features, and pattern recognition based on these peptides was used to assign each sample in the independent test set to its respective group. A twofold difference in peptide concentration could be detected with statistical significance (p-value < 0.0001). The accuracy of the assignment was 95%, demonstrating the utility of this technique for the discovery of patterns of biomarkers in serum.
