10 reglas para hacer la mejor ciencia

1. Drop modesty (strive for excellence)
2. Prepare your mind (luck favors the prepared minds)
3. Age is important (research strategies should be different depending on your age, although I'm not sure I agree with that one)
4. Brains are not enough, you also need courage (I assume this means taking risks)
5. Make the best of your working condition (don't let your environment limit you, but exploit the advantages you have)
6. Work hard and effectively (all the successful scientists I know are workaholics)
7. Believe and doubt your hypothesis at the same time (so be skeptical and accept data for what it is, but don't give up on ideas before you test them)
8. Work on the important problems in your field (work on something interesting and relevant, no matter what the current trends are)
9. Be committed to your problem (because it might take a looong time to solve it)
10. Leave your door open (interact as much as you can with other people, you never know where the insights might come from)

De PLOS Computational Biology

HIV via Haiti

Al parecer se ha encontrado la migracion del HIV, viniendo de Africa via Haiti a los Estados Unidos.
http://www.sciencenews.org/articles/20071103/fob1.asp
Esto es interesante por muchas razones, una de las cuales es localizar el inicio de la infeccion por los 60s (el paso al humano ya habia sido calculado por los 30s)

Lineas contaminadas, incluyendo KB y Hep2

List of contaminated cell lines

From Wikipedia, the free encyclopedia

This is a list of cell cultures which have been cross-contaminated and overgrown by other cells. A project is currently underway to enumerate and rename contaminated cell lines to avoid errors in research caused by misattribution (Masters, 2002). Estimates based on screening of leukemia-lymphoma cell lines suggest that about 15% of these cell lines are not representative of what they are usually assumed to be (Drexler et al., 2002).

Contaminated cell lines have been extensively used in research without knowledge of their true character. For example, most if not all research on the "endothelium" ECV-304 or the "megakaryocyte" DAMI cell lines has in reality been conducted on bladder carcinoma and erythroleukemia cells, respectively. Thus, all research on endothelium- or megakaryocyte-specific functions utilizing these cell lines has turned out to be worthless, except as a warning example.

There are two principal ways a cell line can become contaminated: cell cultures are often exchanged between research groups; if, during handling, a sample gets contaminated and then passed on, subsequent exchanges of cells will lead to the contaminating population being established, although parts of the supposed cell line are still genuine. More serious is contamination at the source: during establishment of the original cell line, some contaminating cells are accidentally introduced into the cultures, where they in time outgrow the desired cells. The initial testing, in this case, still suggested that the cell line is genuine and novel, but in reality, it has disappeared soon after being established and all samples of such cell lines are actually the contaminant cells. It requires lengthy research to determine the precise point where cell lines have become contaminated.

Estándares para Experimentos en Biología (incluyendo para RNAi)

Un estándar se define como una serie de especificaciones uniformes para parte o todos los aspectos de un producto o actividad que promueve la cooperación y la interoperabilidad [1].

Desde hace unos años existe un impetu en la biología para crear estándares para los reportes experimentales, sobre todo para experimentos tipo hightroughput (microarreglos, proteómica, etc). Uno de los principales problemas de los experimentos hightrougput es la reproductibilidad entre diversos laboratorios o plataformas (ej. un microarreglo de Affimetrix vs uno hecho con un chip Perkin Elmer). El objetivo de lograr estándares es facilitar el reporte, la reproductibilidad y lograr compartir los datos entre diversas plataformas. Se espera además que la implementación de estos estándares faciliten la interoperabilidad entre datos genómicos, proteómicos y metabolómicos. Tales iniciativas son por ejemplo MIAME (Minimal Information about a Microarray Experiment), PSI (Proteomics Standards Initiative), etc. [1]

Es interesante para nuestro laboratorio notar que existe una iniciativa para reportar RNAi llamada Minimum Information About an RNAi Experiment (MIARE)

El URL de esa iniciativa es http://miare.sourceforge.net/HomePage

En el siguiente link a mi página pongo un archivo de excel provisto por MIARE para reportar experimentos de RNAi y un PDF con info general de MIARE. Además incluyo información de MIARE de como reportar los reactivos usados para construir el RNAi:

http://franzpruefer.googlepages.com/rnaiguidelines

Ref:
1) Standard operating procedures.Nat Biotechnol. 2006 Nov;24(11):1299.

microRNAs

Nature Reviews presenta una colección sobre microRNAs.
Estos artículos fueron seleccionados para proporcionar una introducción en los diversos aspectos de la biología del microRNA, incluyendo su biogénesis, su función en el desarrollo normal y cáncer, y las implicaciones en el impacto de la regulación genética.

www.nature.com/reviews/focus/microrna