4.2.2.2.1. Aplicación del modelo de abajo-arriba

El modelo se puede aplicar desde un procesamiento abajo-arriba¹, por el que las unidades lingüísticas sucesivas van conformando u orientando la modificación de la estructura de expectativa original (Muñoz Martín 1995: 174). Se atribuyen las funciones a conceptos generales de modo que se establezca una red conceptual entre todos los elementos que se interrelacionan. Por ejemplo, el concepto DNA damage se puede organizar atendiendo a sus funciones terminológicas a través de la búsqueda de las palabras clave en el corpus.

A continuación se muestra esta metodología:

A question of DNA repair

For unicellular organisms, the response to DNA damage is simple – the damage is contained by arresting the replicative machinery, then DNA-repair programmes are activated to fix it. Any mutations that are acquired in the process are merely the spice of unicellular genetic diversity. But metazoan cells must delegate their autonomy to the needs of the multicellular organism of which they are part: if a mutation occurs in the wrong genes, the rogue cell and its progeny could stir up neoplastic Armageddon. So DNA repair is probably reserved for mending minor DNA lesions, rather than for mounting rescue operations to save just one cell. In metazoans it is almost always ‘safer’ to delete the affected cell as opposed to trying to rebuild it, particularly as most somatic mutations occur in proliferating tussues, wherein the replacement of cells is trivial.

In fact, just a single double-stranded DNA break is enough to trigger –through p53- either permanent growth arrest or apoptosis. Such sensitivity to the activation of cell deletion pathways following DNA damage raises complicated questions concerning the fates of cells that can no longer sense DNA damage effectively. Would such cells be resistant to ionizing radiation, because they fail to activate their apoptotic programme, or sensitive, because they fail to mount any repair response and so accumulate unrepaired DNA damage? Would the organism harbouring such cells be more at risk form cancer, because its somatic cells fail to arrest or die following DNA damage, so they survive with their mutated DNA? Or would such an organism be less prone to cancer because its cells fail to repair damaged DNA? The answers to these critical questions require further insight into how the sensing and effector responses of DNA damage are integrated and configured.

(Texto extraído de Nature 387, mayo 1997).

  Las funciones terminológicas que se dejan entrever a partir del texto son las siguientes:

(105) A₀(DNA) = genetic
(106) A₁(DNA) = damaged
(107) A₂(DNA) = double stranded
(108) Able₁(DNA) = mutate
(109) Nocer (cell) = delete

La dificultad de la aplicación del modelo disminuye a medida que la búsqueda se hace más concreta, y a la inversa, los resultados se optimizan si las palabras clave en las que se centra el objeto de la búsqueda son más concretas. Es más productivo partir de microcampos conceptuales para ir estableciendo la red conceptual.

A continuación aplicamos las funciones léxicas a un fragmento textual sobre las anomalías en el ADN de células con cáncer de pulmón. Es decir, procedemos con metodología de abajo-arriba.

Much work has been carried out on determining the prognostic significance of the DNA content of lung cancer cells determined by flow citometry. For a variety of different tumours, including breast cancer and lymphomas, a significant correlation exists between the degree of aneuploidy and survival. In flow cytometry studies (FCM) of tumours from lung cancer patients approximately 85% of tumours have an aneuploid DNA content, ranging from hypodiploid to tetraploid. In addition stem cell lines are observed in 10-20% of such specimens. In studies of lung cancer patients correlations have been evaluated between the total DNA content, the proliferative characteristics and the number of stem cell lines present, with the overall survival and outcome of the patients treated. In SCLC patients little correlation has been demonstrated beween the DNA content and proliferative characteristics of the patients with patient survival.

Texto extraído de Genes and Cancer, p. 306.

Tomamos como eje conceptual de las entradas DNA y lung cancer cells.

(110) S₁(DNA) = content
(111) S_locS₁S₁ = Lung cancer cells
(112) S_meansS₁ = flow cytometry
(113) [S₁(lymphomas)S₂(breast cancer)]Involv₁(correlation) = aneuploidy
(114) [S₁(lymphomas)S₂(breast cancer)]Involv₂(correlation) = survival
(115) S_instr1(tumours) = flow citometry
(116) S_res1Si_nstr1 = aneuploid DNA
(117) Manif [S_res1S_instr1] = 85% of tumours
(118) S₁[S_res1S_instr1] = hypodiploid
(119) S₂[S_res1S_instr] = tetraploid
(120) S_res2S_instr = stem cell lines
(121) Manif₂[S_res2S_instr] = 10-20% of tumours
(122) Qual₁[tumours] = proliferative
(123) [S_res2S_instr2]Qual₁[[S₁(lymphomas)S₂(breast cancer)]Involv₂(correlation)]] Manif₁(SCLC) = small

Con la reducción del texto a sus funciones terminológicas obtenemos un esquema conceptual del tema del texto y a la vez nos damos cuenta de las distintas UF que pueden tratarse en la ficha fraseológica. A través de este análisis se estima conveniente el desarrollo de la información fraseológica siguiente: SCLC, flow cytometry como unidades fijas (términos compuestos), Aneuploid DNA, lung cancer cells, stem-cell lines y patient survival como colocaciones.

El análisis sistemático de los textos desde las funciones léxicas y terminológicas ofrece una forma muy válida de complementar el análisis de frecuencia-recurrencia para establecer el radio colocacional de las unidades léxicas.

NOTAS

1. La descripción del procesamiento abajo-arriba y arriba-abajo queda descrita con exhaustividad en Kurcz (1984).

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