Antivirulence and antipathogenic activity of Mayan herbal remedies against Pseudomonas aeruginosa.

ETHNOPHARMACOLOGICAL RELEVANCE: The Yucatan Peninsula has a privileged wealth of vascular plants with which various Mayan herbal formulations have been developed. However, studies on their antipathogenic and antivirulence properties are scarce. AIM OF THE STUDY: Identify antivirulence properties in Mayan herbal remedies and determine their antipathogenic capacity in burn wounds infected with Pseudomonas aeruginosa. MATERIALS AND METHODS: An ethnobotanical study was conducted in Mayan communities in central and southern Quintana Roo, Mexico. Furthermore, the antipathogenic capacity of three Mayan herbal remedies was analyzed using an animal model of thermal damage and P. aeruginosa infection. Antivirulence properties were determined by inhibiting phenotypes regulated by quorum sensing (pyocyanin, biofilm, and swarming) and by the secretion of the ExoU toxin. The chemical composition of the most active herbal remedy was analyzed using molecular network analysis. RESULTS: It was found that topical administration of the remedy called "herbal soap" (HS) for eleven days maintained 100% survival of the animals, reduced establishment of the bacteria in the burn and prevented its systemic dispersion. Although no curative effect was recorded on tissue damaged by HS treatment, its herbal composition strongly reduced swarming and ExoU secretion. Through analysis of Molecular Networks, it was possible to carry out a global study of its chemical components, and identify the family of oxindole monoterpenoid alkaloids and carboline and tetrahydropyrididole alkaloids. In addition, flavonols, flavan-3-ols, and quinic acid derivatives were detected. CONCLUSIONS: The antipathogenic and antivirulence capacity of ancient Mayan remedies makes them a potential resource for developing new antibacterial therapies to treat burns infected by P. aeruginosa.

Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico. / Factores de riesgo de bajo peso al nacer según el modelo de regresión logística múltiple. Estudio de cohorte retrospectiva en el municipio José María Morelos, Quintana Roo, México.

INTRODUCTION: Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. OBJECTIVE: To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. METHODS: Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. RESULTS: In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3.59, 95% confidence interval: 0.43 to 29.87); number of deliveries = 1 (3.86, 95% confidence interval: 0.33 to 44.85); personal pathological history (4.78, 95% confidence interval: 2.16 to 10.59); pathological obstetric history (5.01, 95% confidence interval: 1.66 to 15.18); maternal height < 150 cm (5.16, 95% confidence interval: 3.08 to 8.65); number of births ≥ 5 (5.99, 95% confidence interval: 0.51 to 69.99); and smoking (15.63, 95% confidence interval: 1.07 to 227.97). CONCLUSIONS: Four of the independent variables (personal pathological history, obstetric pathological history, maternal stature <150 centimeters and smoking) showed a significant positive contribution, thus they can be considered as clear risk factors for low birth weight. The use of the logistic regression model in the Mayan municipality of José María Morelos, will allow estimating the probability of low birth weight for each pregnant woman in the future, which will be useful for the health authorities of the region.

INTRODUCCIÓN: El bajo peso al nacer ha constituido un enigma para la ciencia a través de los tiempos. Múltiples han sido los trabajos de investigación realizados con respecto a las causas que lo producen y los efectos que provoca. El bajo peso al nacer es un indicador que permite predecir la probabilidad de sobrevivencia de un niño. De hecho, existe una relación exponencial entre el déficit de peso, la edad gestacional y la mortalidad perinatal. La regresión logística múltiple es uno de los instrumentos estadísticos más expresivos y versátiles de que se dispone para el análisis de datos tanto en clínica y en epidemiología como en salud pública. OBJETIVO: Evaluar de forma multivariada la importancia de 17 variables independientes en el bajo peso al nacer (variable dependiente), de niños nacidos en el municipio maya de José María Morelos, Quintana Roo, México. MÉTODOS: Estudio epidemiológico observacional analítico de cohortes, con temporalidad retrospectiva. Se registraron todos los nacimientos que cumplieron con los criterios de inclusión, ocurridos en el Hospital Integral José María Morelos de la Secretaría de Salud, correspondientes al municipio maya de José María Morelos, durante el período comprendido del 1 de agosto de 2014 al 31 de julio de 2015. El número total de recién nacidos registrados fue de 1147; 84 de estos (7,32%) tenían bajo peso al nacer. Para evaluar la asociación independiente entre las variables explicativas o factores de riesgo y la variable respuesta, se realizó un análisis de regresión logística múltiple utilizando el software IBM SPSS Statistics 22. RESULTADOS: En orden numérico ascendente de valores de odds ratios > 1 señalaron la contribución positiva de las variables explicativas o factores de riesgo: estado civil no–casada (1,08, intervalo de confianza del 95%: 0,55 a 2,10); edad a la menarca ≤ 12 años (1,08, intervalo de confianza del 95%: 0,64 a 1,84); antecedentes de aborto (1,14, intervalo de confianza del 95%: 0,44 a 2,93); peso materno < 50 kilogramos (1,51, intervalo de confianza del 95%: 0,83 a 2,76); número de consultas prenatales ≤ 5 (1,86, intervalo de confianza del 95%: 0,94 a 3,66); edad materna ≥ 36 años (3,5, intervalo de confianza del 95%: 0,40 a 30,47); edad materna ≤ 19 años (3,59, intervalo de confianza del 95%: 0,43 a 29,87); primiparidad (3,86, intervalo de confianza del 95%: 0,33 a 44,85); antecedentes personales patológicos (4,78, intervalo de confianza del 95%: 2,16 a 10,59); antecedentes obstétricos patológicos (5,01, intervalo de confianza del 95%: 1,66 a 15,18); estatura materna < 150 centímetros (5,16, intervalo de confianza del 95%; 3,08 a 8,65); número de partos ≥ 5 (5,99, intervalo de confianza del 95%: 0,51 a 69,99); y tabaquismo (15,63, intervalo de confianza del 95%: 1,07 a 227,97). El modelo de regresión logística mostró ajuste aceptable (Hosmer-Lemeshow con p=0,873). CONCLUSIÓN: Se demuestra que cuatro de las variables independientes (antecedentes personales patológicos, antecedentes obstétricos patológicos, estatura materna < 150 centímetros y tabaquismo) resultaron con contribución positiva significativa por lo que pueden considerarse claros factores de riesgo de bajo peso al nacer. El uso de este modelo de regresión logística en municipio maya de José María Morelos, permitirá estimar la probabilidad de peso al nacer de cada embarazada en el futuro lo que será de utilidad para las autoridades sanitarias de la región.