Antibiotic Resistance Gene Abundances Associated with Waste Discharges to the Almendares River near Havana, Cuba

Considerable debate exists over the primary cause of increased antibiotic resistance (AR) worldwide. Evidence suggests increasing AR results from overuse of antibiotics in medicine and therapeutic and nontherapeutic applications in agriculture. However, pollution also can influence environmental AR, particularly associated with heavy metal, pharmaceutical, and other waste releases, although the relative scale of the “pollution” contribution is poorly defined, which restricts targeted mitigation efforts. The question is “where to study and quantify AR from pollution versus other causes to best understand the pollution effect”. One useful site is Cuba because industrial pollution broadly exists; antibiotics are used sparingly in medicine and agriculture; and multiresistant bacterial infections are increasing in clinical settings without explanation. Within this context, we quantified 13 antibiotic resistance genes (ARG; indicators of AR potential), 6 heavy metals, 3 antibiotics, and 17 other organic pollutants at 8 locations along the Almendares River in western Havana at sites bracketing known waste discharge points, including a large solid waste landfill and various pharmaceutical factories. Significant correlations (p < 0.05) were found between sediment ARG levels, especially for tetracyclines and β-lactams (e.g., tet(M), tet(O), tet(Q), tet(W), blaOXA), and sediment Cu and water column ampicillin levels in the river. Further, sediment ARG levels increased by up to 3 orders of magnitude downstream of the pharmaceutical factories and were highest where human population densities also were high. Although explicit links are not shown, results suggest that pollution has increased background AR levels in a setting where other causes of AR are less prevalent

Compartimental Stochastic Models for the Evolution of AIDS Patients

Editorial. ¿Cuanto Vale la Salud?Salinas, Pedro JoséAcción del Piroxicam en ratones hembras cepa C57BL/6 con Melanoma B16F1Piroxicam action on female mice C57BL/6 with Melanoma B16Fl.Quiñones, BelkisUrbina de Velandia, EloísaPérez Feo, MirnaCyclotron Produced Iodine Isotopes for Therapeutical Medicinal Uselodo radiactivo para uso terapéutico, producido en el ciclotrón.Oropeza, M.Spavieri, GianfrancoZambelli, M.Modelos Aleatorios de Compartimientos para la Evolución de Pacientes Afectados de SidaCompartmental stochastic models for the evolution of AIDS patients.Alonso Fernández, Andrés M.Olivares Rieumont, PabloNiveles Séricos de Mucoproteínas en Escolares Sanos Residentes en la Ciudad de Mérida, VenezuelaMucoproteins serum levels is in school children from Mérida.Alarcón Corredor, Oscar MarinoGarcia de Camacaro, L.Carnevali de Tata, ElizabethSilva Larralte, TaniaPadrón, F.E.Serrano, J.O.Chacón, A.F.El Médico de Familia y los Otros EspecialistasThe family Physician and the other specialists.Bahsas Bahsas, FadlallaFactores de Riesgo en Niños en Observación del Hospital Central de San Cristóbal y Medicina FamiliarRisk factors in children under observation in the Central Hospital of San Cristóbal,and family medicine.Araujo de Dávila, NoraGranadillo Vera, DervisSalinas, Pedro JoséLos Diuréticos: Aspectos Básicos y Clínico-TerapéuticosDiuretics: Basic and therapeutic properties.Rondón Nucete, MiguelOrence Leonett, OneliaRodríguez Aular, LisbethRelación entre el Funcionalismo Familiar, el Estrés y la AnsiedadRelationship between familiar function, stress and anxiety.Alchaer Alchaer, Jorge RamónBahsas Bahsas, FadlallaHernández Nieto, RafaelSalinas, Pedro JoséSemblanza. Dr. Justo Miguel Bonomie Ahoua.Salinas, Pedro JoséCastro Peñalver, Pedro Elías56-59Nivel analíticosemestra

Bottom-up Subtree Isomorphism for Unordered Labeled Trees

A bottom-up subtree P of a labeled unordered tree T is such that, for each internal vertex u of P, all the children of u in T are also vertices of P, and the labels in corresponding positions also match. We aim at finding all the occurrences of a pattern tree P of m vertices as a bottom-up subtree of a text tree T of n vertices, m ≤ n. If the labels are single characters of a constant or of an n-integer alphabet the problem is solved in O(m + log n) time and (m) additional space, after a preprocessing of T is done in (n) time and (n) additional space. Note that the number of occurrences of P in T does not appear in the search time. For more complex labels the running times increase, becoming a function of the total length of all the labels in T and P if such labels are sequences of characters. Regarding T as a static text and P as the contents of a query on T, and assuming m = o(n), the response time for each P is sublinear in the size of the overall structure

Bottom-up Subtree Isomorphism for Unordered Labeled Trees

A subtree P of a given tree T is a bottom-up subtree of T if, for each internal vertex u of P, all the children of u in T are also vertices of P. Our problem is deciding if a pattern tree P of m vertices is a bottom-up subtree of a text tree T of n vertices, m <= n, and, in the affirmative case, finding all the occurrences of P in T. If the vertices are labeled, the labels in the corresponding positions in P and T must match. We consider unordered rooted trees with labeled vertices, which are reconducted to simpler ordered trees through an ordering algorithm. Processing time depends on the label format. If the labels are single characters of a constant or of an n-integer alphabet \Sigma (respectively, |\Sigma| = constant, or \Sigma is composed of integers in the range [1 \div n]), the problem is solved in O(m +\log n) time and \Theta(m) additional space, after a preprocessing of T is done in \Theta(n) time and \Theta(n) additional space. The number of occurrences of P in T does not appear in the search time because all such occurrences can be directly reconstructed from a constant output information. For more complex labelsthe running times slightly increase. In particular if the labels are sequences of characters (e.g. as in XML files) the running time becomes a function of the total length of all the labels in T and P. Although directed to the "simple problem" of exact subtree matching, our work is the first one to solve it in linear time for unordered trees. Moreover our approach is the one of dictionary search. Regarding $T$ as a static text on which several queries are made, $P$ as the contents of one such a query, and assuming $m=o(n)$, the response time for each $P$ is sublinear in the size of the overall structure

Exact Rooted Subtree Matching in Sublinear Time

The problem of exact subtree matching is the one of deciding if a pattern tree P of m vertices is a subtree of a text tree T of n vertices, m<= n, and, in the affirmative case, finding all the occurrences of P in T. We consider ordered and non-ordered rooted trees with labeled vertices (the case of unlabeled vertices is a special case of this), and show how the problem can be solved in Theta(m + log n) time once a proper data structure is built for T in a preprocessing phase which requires Theta(n) time and space. Regarding T as an immutable text on which several queries are made, P as the contents of one such query, and assuming m=o(n), we can speak of search time sublinear in the size m+n of the overall structure. The number of occurrences of P in T does not appear in the search time because all such occurrences can be directly reconstructed from a constant output information