Aunque el mapa de como estamos en producción científica es poco halagador, lo interesante es que hemos crecido, sobre todo comparando a otros países (incluído EU). Compare la primera foto con la segunda. Este tipo de gráficas se parecen al homúnculo de Penfield (http://es.wikipedia.org/wiki/Homúnculo) 🙂
CRECIMIENTO PRODUCCION CIENTIFICA
Cancer biology: BET-ting on chromatin
Tumor development often involves genomic changes that affect protein expression, so chromatin alterations have received a lot of attention as possible therapeutic targets. A handful of recent studies support this idea by identifying a role for the bromodomain and extraterminal (BET) family of transcriptional regulators, which bind and recognize histone acetylation, in several human hematological malignancies.
Four independent groups—from Boston’s Dana-Farber Cancer Institute, New York state’s Cold Spring Harbor Laboratory, the UK’s Cambridge University and Massachusetts’s Constellation Pharmaceuticals—started from different points and used different models, but they all converged on the finding that interfering with the function of BET proteins reduces the transcription of key oncogenes such as Myc, arrests cell-cycle progression and leads to apoptosis (Cell 146, 904–917, 2011; Nature 478, 524–528 & 529–533, 2011; Proc. Natl. Acad. Sci. USA 108, 16669–16674, 2011).
Crucially, the four studies highlighted the clinical implications of this finding by showing that small-molecule inhibitors of BET family members had therapeutic effects in mouse models of leukemia, lymphoma and myeloma, as well as in primary cells isolated from people with cancer. —JCL
Nature 464, 993-998 (15 April 2010) doi:10.1038/nature08987
International Cancer Genome Consortium
The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
Characterizing the Epidemiological Transition in Mexico: National and Subnational Burden of Diseases, Injuries, and Risk Factors
1 Harvard School of Public Health, Boston, Massachusetts, United States of America, 2 Harvard Initiative for Global Health, Cambridge, Massachusetts, United States of America, 3 World Health Organization, Geneva, Switzerland, 4 Pennsylvania State University, University Park, Pennsylvania, United States of America, 5 Instituto Nacional de Salud Pública, Cuernavaca, Mexico
Rates of diseases and injuries and the effects of their risk factors can have substantial subnational heterogeneity, especially in middle-income countries like Mexico. Subnational analysis of the burden of diseases, injuries, and risk factors can improve characterization of the epidemiological transition and identify policy priorities.
Methods and Findings
We estimated deaths and loss of healthy life years (measured in disability-adjusted life years [DALYs]) in 2004 from a comprehensive list of diseases and injuries, and 16 major risk factors, by sex and age for Mexico and its states. Data sources included the vital statistics, national censuses, health examination surveys, and published epidemiological studies. Mortality statistics were adjusted for underreporting, misreporting of age at death, and for misclassification and incomparability of cause-of-death assignment. Nationally, noncommunicable diseases caused 75% of total deaths and 68% of total DALYs, with another 14% of deaths and 18% of DALYs caused by undernutrition and communicable, maternal, and perinatal diseases. The leading causes of death were ischemic heart disease, diabetes mellitus, cerebrovascular disease, liver cirrhosis, and road traffic injuries. High body mass index, high blood glucose, and alcohol use were the leading risk factors for disease burden, causing 5.1%, 5.0%, and 7.3% of total burden of disease, respectively. Mexico City had the lowest mortality rates (4.2 per 1,000) and the Southern region the highest (5.0 per 1,000); under-five mortality in the Southern region was nearly twice that of Mexico City. In the Southern region undernutrition and communicable, maternal, and perinatal diseases caused 23% of DALYs; in Chiapas, they caused 29% of DALYs. At the same time, the absolute rates of noncommunicable disease and injury burdens were highest in the Southern region (105 DALYs per 1,000 population versus 97 nationally for noncommunicable diseases; 22 versus 19 for injuries).
Mexico is at an advanced stage in the epidemiologic transition, with the majority of the disease and injury burden from noncommunicable diseases. A unique characteristic of the epidemiological transition in Mexico is that overweight and obesity, high blood glucose, and alcohol use are responsible for larger burden of disease than other noncommunicable disease risks such as tobacco smoking. The Southern region is least advanced in the epidemiological transition and suffers from the largest burden of ill health in all disease and injury groups.
Como hacer busquedas en el pubmed?
Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes
Genome Biology 2002, 3:research0034.1-0034.11doi:10.1186/gb-2002-3-7-research0034
Por favor lean este articulo. Todos aquellos que usen o vayan a usar RT PCR se beneficiaran de este. Valdria la pena estandarizar para cada linea celular
Un numero de acceso libre de bases de datos, muy util en Nucleic Acid Research
y, en particular, la tabla de bases de datos
- Drop modesty (strive for excellence)
- Prepare your mind (luck favors the prepared minds)
- Age is important (research strategies should be different depending on your age, although I’m not sure I agree with that one)
- Brains are not enough, you also need courage (I assume this means taking risks)
- Make the best of your working condition (don’t let your environment limit you, but exploit the advantages you have)
- Work hard and effectively (all the successful scientists I know are workaholics)
- 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)
- Work on the important problems in your field (work on something interesting and relevant, no matter what the current trends are)
- Be committed to your problem (because it might take a looong time to solve it)
- Leave your door open (interact as much as you can with other people, you never know where the insights might come from)
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.