Browsing by Author "Fennix Agudelo, Mary Andrea"

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Aproximación genómica de la enfermedad periodontal causada por porphyromonas gingivalis
(08/06/2022) Plazas Román, Jaime Enrique; Cuesta Astroz, Yesid; Fennix Agudelo, Mary Andrea; Chavarro Mesa, Edisson; Harris Ricardo, Jonathan; Díaz Caballero, Antonio
OBJETIVO: El propósito del trabajo fue analizar la literatura científica con relación a la diversidad genómica y funcional de las cepas de P. gingivalis implicadas en la enfermedad periodontal. METODOLOGÍA: Se realizó un análisis la literatura científica de la plataforma PATRIC (Pathosystem Resource Integration Center), comparando genómicamente las cepas de Porphyromonas gingivalis implicadas en la enfermedad periodontal, se realizó la filogenia de los genomas (Phylogenetic Tree Building Service), se calcularon los datos del subsistema para cada genoma, la similitud de secuencia de nucleótidos se realizó con el servidor web (JSpeciesWS) y se analizaron los genes conocidos de resistencia a antibióticos en las bases de datos de resistencia antibiótica (CARD y NDARO). RESULTADOS: A través de la filogenia se observaron 3 clados, una identidad de nucleótidos de las 49 cepas en rangos comprendidos entre 99.9% y 98.25%, Se observan resistencias a antibióticos en las 49 cepas, solo se encontraron factores de virulencia en 7 cepas y ausencia de profagos en 2 cepas KCOM 2800 y WW3040. CONCLUSIÓN: En la base de datos PATRIC se encontraron 61 cepas de P. gingivalis, de las cuales 49 cepas estuvieron involucradas en la enfermedad periodontal específicamente en la periodontitis. También se observó que filogenéticamente se encontraban en 3 clados. Existe una diversidad marcada en las 49 cepas de la P. gingivalis, esta identidad de nucleótidos deja entrever que la similitud esta entre 99.9% a 98.25%, por lo tanto, no están tan separadas a nivel de nucleótidos. Las 49 cepas observadas evidenciaron resistencia antibiótica. Con respecto a los genes especiales de homólogos humanos, reportados en la plataforma PATRIC, solo 7 de las 49 cepas lo poseen. Finalmente, solo las cepas KCOM 2800 y WW3040 no están involucradas en los subsistemas y presentan ausencia de prófagos.
Bacterias halófilas del Norte de Colombia /
(2015) Fennix Agudelo, Mary Andrea; Miranda Castro, Wendy Paola; Acevedo Barrios, Rosa
En este estudio, se caracterizaron bacterias nativas a partir de suelos hipersalinos del Norte de Colombia identificándolas microscópicamente por tinción de Gram y bioquímicamente mediante el sistema BBL™ Crystal™ Kit ID para bacterias Gram negativas y Gram positivas, permitiendo así caracterizar tres géneros de bacterias: Vibrio sp., Bacillus sp., y Escherichia coli. Además, se realizaron pruebas de susceptibilidad al cloruro de sodio, comprobando que las bacterias aisladas son halófilas. Basado en los resultados obtenidos se concluye que los géneros Vibrio sp. y Bacillus sp. ser bacterias halófilas y tolerar grandes concentraciones de sal.
Identificación de bacterias por MALDI-TOF MS a partir de muestras de Acropora cervicornis con signos de Banda Blanca (EBB) obtenidas en Islas del Rosario, Colombia
(2021) Fennix Agudelo, Mary Andrea; Chavarro Mesa, Edisson (director)
La enfermedad de Banda Blanca (EBB) es considerada como uno de los síndromes coralinos más perjudiciales del Caribe, siendo capaz de deteriorar la estructura de muchos corales de esta zona durante las décadas de los ochenta y noventa. Esta infección, de la mano con los efectos del cambio climático y el incremento de sedimentos, ha sido relevante en la disminución de las poblaciones del coral Acropora cervicornis, al punto de ser valorada por diversos entes nacionales e internacionales como una especie en peligro crítico de extinción. Por otra parte, ya que la etiología de esta enfermedad no es completamente conocida, el uso de técnicas encaminadas a la identificación de los agentes asociados podría brindar un acercamiento a la composición de las poblaciones bacterianas involucradas, mejorando la comprensión de esta enfermedad y las circunstancias que han conducido al deterioro de A. cervicornis en el Caribe, conllevando además al incremento de las labores restaurativas y productivas de las guarderías de coral. Por ello, la presente investigación tuvo como objetivo el aislamiento y caracterización de bacterias asociadas a la EBB en A. cervicornis provenientes de guarderías colgantes del Parque Nacional Natural Corales del Rosario y San Bernardo, Colombia, utilizando MALDI-TOF MS y PCR. Los resultados de estos ensayos mostraron la presencia de bacterias Bacillus cereus en individuos con señales de blanqueamiento provenientes de guarderías y zonas de trasplante en Isla Tesoro e Isla Ceiner, sumado a que el secuenciamiento y análisis filogenético del gen motB de uno de estos aislamientos mostró que estaba estrechamente emparentado con secuencias de B. cereus y Bacillus thuringiensis alojadas en el NCBI, con similitudes de hasta el 99%. Probablemente, la presencia de B. cereus podría indicar cierta relación entre este microorganismo y la aparición de EBB en A. cervicornis, sin embargo, resulta imperativo realizar más estudios enfocados a identificar las bacterias asociadas a esta enfermedad, con el fin de respaldar estos hallazgos.
Kernel-based machine learning models for the prediction of dengue and chikungunya morbidity in Colombia
(Springer Verlag, 2017) Caicedo Torres, W.; Montes Grajales, D.; Miranda Castro, W.; Fennix Agudelo, Mary Andrea; Agudelo Herrera, N.; Solano, A.; Ordonez, H.
Dengue and Chikungunya fever are two viral diseases of great public health concern in Colombia and other tropical countries as they are both transmitted by Aedes mosquitoes, which are endemic to this area. In recent years, there have been unprecedented outbreaks of these infections. Therefore, the development of computational models to forecast the number of cases based on available epidemiological data would benefit public surveillance health systems to take effective actions regarding the prevention and mitigation of these events. In this work, we present the application of machine learning algorithms to predict the morbidity dynamics of dengue and chikungunya in Colombia using time-series-forecasting methods. Available weekly incidence for dengue (2007–2016) and chikungunya (2014–2016) from the National Health Institute of Colombia was gathered and employed as input to generate and validate the models. Kernel Ridge Regression and Gaussian Processes were used at forecasting the number of cases of both diseases considering horizons of one and four weeks. In order to assess the performance of the algorithms, rolling-origin cross-validation was carried out, and the mean absolute percentage errors (MAPE), mean absolute errors (MAE), R2 and the percentages of explained variance calculated for each model. Kernel Ridge regression with one-step ahead horizon was found to be superior to other models in forecasting both dengue and chikungunya number of cases per week. However, the power of prediction for dengue incidence was higher as there is more epidemiological data available for this disease compared to chikungunya. The results are promising and urge further research and development to achieve a tool which could be used by public health officials to manage more adequately the epidemiological dynamics of these diseases. © Springer International Publishing AG 2017.
MALDI-TOF MS for the identification of bacteria from Acropora cervicornis samples with White Band Disease
(2022) Fennix Agudelo, Mary Andrea; Zarza González, Esteban; Sánchez Quitian, Zilpa Adriana; Castellanos, Nuri; Martínez Santos, Juan Carlos; Parra Giraldo, Claudia Marcela; Chavarro Mesa, Edisson
White Band Disease (WBD) is one of the most harmful coral syndromes in the Caribbean, deteriorating the structure of many corals during the eighties and nineties. Since its etiology is not entirely known, the use of techniques aimed a t identifying the associated agents could provide an approach to the composition of the populations involved in the deterioration of A. cervicornis. Therefore, this research's objective was to isolate and characterize bacteria associated with WBD in A. cervicornis from hanging nurseries of Rosario and San Bernardo Corals National Natural Park, Colombia, using MALDI-TO F MS and PCR. The results showed the presence of Bacillus cereus bacteria in individuals with bleaching signs from nurseries and transplant areas on Isla Tesoro and Isla Ceiner. One of these strains sequenced and phylogenetically analyzed was closely related t o Bacillus thuringiensis, with similarities of up to 99%. The presence of B. cereus could indicate a special relationship between this microorganism and WBD. However, it is imperative to carry out more studies on identifying the bacteria associated with this disease to support these findings. © 2022 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
Occurrence of personal care products as emerging chemicals of concern in water resources: A review
(Elsevier B.V., 2017) Montes-Grajales D.; Fennix Agudelo, Mary Andrea; Miranda-Castro W.
Personal care products (PCPs) are a diverse group of common household substances used for health, beauty and cleaning purposes. These include disinfectants, fragrances, insect repellents, preservatives and UV filters, among others. Some of them are considered chemicals of emerging concern due to their presence and negative impact on aquatic ecosystems, specially related to endocrine disruption and reproductive disorders. The entry of those chemicals to water bodies occurs mainly through the sewage effluents from wastewater treatment plants due to their incomplete or inefficient removal. The purpose of this review was to collect and analyze data about the incidence and concentrations of PCPs reported as emerging pollutants in different water matrices, including wastewater influents and effluents. Our database is composed of 141 articles with information about 72 PCPs recorded as emerging pollutants in 30 countries, in concentrations ranging from 0.029 ng/L to 7.811 × 106 ng/L. Fragrances, antiseptics and sunscreens were the most reported groups. As expected, the largest number of PCPs documented as emerging pollutants were found in wastewater treatment plant effluents with a total of 64 compounds, compared to 43 in surface water and 23 in groundwater, which evidence the anthropological contribution of PCPs to water bodies. These molecules were found in all the continents, however, there is a lack of information regarding the presence of emerging pollutants from PCPs in developing countries. Therefore, we suggest further efforts in assessing the occurrence and concentrations of these chemicals in those areas. © 2017 Elsevier B.V.
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia
(2020-11-09) Chavarro Mesa, Edisson; De la Hoz Domínguez, Enrique José; Fennix Agudelo, Mary Andrea; Miranda-Castro, Wendy; Ángel-Díaz, Jorge Evelio
Citrus greening disease (Huanglongbing-HLB) is considered the most destructive citrus disease worldwide. Of the three species of Candidatus liberibacter associated with HLB, two have been recently reported in Latin America. The first report of HLB in Colombia was in March 2016. In this paper, a dataset was extracted for six departments in the northern zone of Colombia, where has been previously reported, applying image georeferencing with QGIS Software. Preliminary Random Forest and K-Nearest Neighbors (KNN) machine learning models were used in order to test and validate the obtained results, for disease monitoring and HLB incidence prediction. The performance of both models was also compared, obtaining a 100% AUC value with Random Forest model.