Intelligent design - Wikipedia: "Intelligent design (ID) is the phrase coined for the argument that life and living things show signs of having been designed by an intelligent agent, and that therefore abiogenesis must be a false hypothesis. Specifically, the conjecture focuses on the 'what' of the origin of life on Earth, i.e. saying that it is not possible for 'non-living' matter to become 'living' matter (with the level of organization that is observed today) without intervention, and that life itself shows signs of design. The 'Who, why, when, where and how' are theoretically excluded from the debate, although the idea is more often than not identified with religious arguments, with inevitable extension into those other domains. Religious proponents of ID use the argument from design to argue for the existence of a god, usually � in the context of Christianity � God.
Opponents of ID, who include the overwhelming majority of the scientific community, claim that this argument is deceptive and has no standing as a scientific hypothesis, i.e. it is considered pseudoscience. They say that ID does not present falsifiable hypotheses, and violates the principle of naturalism within scientific philosophy. They also point to examples of seemingly poor design within biology."
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String theory - Wikipedia, the free encyclopedia: "string theory is a physical model whose fundamental building blocks are one-dimensional extended objects (strings) rather than the zero-dimensional points (particles) that were the basis of most earlier physics. For this reason, string theories are able to avoid problems associated with the presence of pointlike particles in a physical theory. Detailed study of string theories has revealed that they describe not just strings but other objects, variously including points, membranes, and higher-dimensional objects. As discussed below, it is important to realize that no string theory has yet made firm predictions that would allow it to be experimentally tested."
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A New Culprit In Depression? Study Finds Surprising Differences In Gene Activity In The Brains Of Depressed People: "Source: University Of Michigan Health System
Date: 2004-10-18
A New Culprit In Depression? Study Finds Surprising Differences In Gene Activity In The Brains Of Depressed People
ANN ARBOR, MI - The brains of people with severe depression have lower levels of several related molecules that are key to the development, organization, growth and repair of the brain than the brains of people without the disease, or those with the bipolar form of depression, a new study finds.
Postmortem Brain Analysis in Sleep Disorder Patients: National Sleep Disorders Research Plan, 2003, NCSDR, NHLBI, NIH: "Currently, human neuropathology involves analysis at the structural, neurochemical, cellular, and molecular levels, and its modern tools hold promise of much-needed insights into central and autonomic mechanisms in sleep disorders. A potential revolutionary tool for human brain analysis is microarray analysis of gene expression in autopsied tissues. The potential of this genomic technology in human neuropathology to uncover critical molecular abnormalities is illustrated by its recent application to postmortem brain analysis in schizophrenia. With cDNA microarrays, altered gene expression was found in the frontal cortex in schizophrenic patients compared to autopsy controls. The most changed gene, which was never before linked to schizophrenia, was a regulator of G-protein signaling 4, suggesting schizophrenia is a disease of the synapse and thus providing an opportunity to better understand a devastating disorder whose basic mechanism(s) has been elusive"
The Use of Microarrays to Study Childhood Developmental Brain Disorders: "The application of gene expression analysis across the diverse biological sciences
Gene expression is selectively regulated in specific times of development and body regions. While many transcripts are expressed at uniform rates, others are dynamically regulated. Particular transcripts are differentially regulated dependent upon physiological state, pharmacological intervention, or diseased state. A premise of gene expression studies of neurodevelopmental disorders is that some mRNA transcripts are significantly, differentially regulated as a consequence of the disease process.
DNA microarrays encompassing entire genomes have been used to characterize transcriptional programs underlying diverse biological functions in model organisms such as S. cerevisae, C. elegans, and D. melangaster [26-35]. Models of human biology and disease have been investigated using microarray analysis in mice [36-38]. In human tissue, microarrays have been extensively applied to the study of cancers [39-46], as well as brain disease [47-50] and other biological questions [51-53]. Microarrays have been used to understand how mutations a transcription factor result in peripheral myelination disorders [54]. Gene expression analysis at the single-cell level has been successfully undertaken in the study of Alzheimer�s Disease [55-57] and neuronal apoptosis [58]."
Progress in the use of microarray technology to study the neurobiology of disease - Nature Neuroscience: "Challenges in analyzing human brain tissue
Working with human postmortem brain material has a major influence on experimental design, data analysis and interpretation for several reasons7, 8, 9. First, DNA microarray analysis of brain tissue is highly complex. Although the brain has a limited number of primary cell types, these show immense phenotypic diversity, and gene expression changes may affect only subpopulations of cells. Consequently, even profound transcriptome changes in a small subpopulation of brain cells may not be detected: more abundant sources of transcripts can mask these changes (for review, see ref. 5). In addition, de novo expression, induction and repression are rarely seen in the mature nervous system. As a result, the magnitude of expression changes found with microarrays is often only modest and hard to separate from experimental noise. Finally, as many neurons project to remote areas, gene expression changes and protein changes may occur in different brain compartments. The vast majority of transcripts are most abundant in the cell soma, whereas the protein is often localized to axonal projections or nerve terminals a considerable distance away, complicating interpretation10. Moreover, it is possible for the levels of a transcript to be up- or down-regulated while the protein is significantly regulated in the opposite direction. Combined study of RNA and protein levels using high-throughput approaches is desirable whenever possible, although in general these levels show limited correlation11.
Second, the genetic background and lifestyle of humans is diverse. This gives rise to a new level of complexity that is usually not encountered in well-controlled animal experiments. The genetic makeup of each individual is unique, and so is the transcriptome profile. Experiences also shape our brain transcriptome individually. Thus, functionally important differences in gene expression that are relevant to disease processes may be masked by other changes. Unfortunately, we have no firm estimates of combined genetic and epigenetic influences on the human brain transcriptome.
Third, the transcriptome is also shaped by disease treatment. Separating the effects of the disease from the effects of treatment remains one of the most challenging aspects of human postmortem research. Postmortem material from unmedicated patients is rarely available, making interpretation difficult. Rodent animal models and tissue culture systems are extremely valuable in assessing the effects of medication on the neural transcriptome. It is unclear, however, how well the animal data translate to drug-treatment effects in the diseased human brain. Transcriptome analyses in non-human primate models of chronic drug treatment are probably the most informative in this regard12, although this approach is expensive and low-throughput.
Fourth, brain disorders are typically not uniform within a diagnosis class. For example, schizophrenia and Alzheimer disease show a continuum of clinical phenotypes13. Even for single-gene disorders such as adrenoleukodystrophy (the most common genetic disorder affecting peroxisomes), a single mutation leads to a broad range of clinical phenotypes. This disease continuum is also apparent at the level of the transcriptome.
Fifth, the availability of postmortem material is limited. Brain tissue donations from well-characterized subjects are hard to obtain14. As a result, without a coordinated effort, studies are done on limited sample sizes, seriously restricting their power. Furthermore, there is extreme diversity among the brains with respect to age, race, postmortem interval, medication history, lifestyle and other factors. This diversity, combined with co-morbidity with other disorders, represents a significant challenge in the interpretation. As an example, about 8% of individuals with Down syndrome also have autism.
Sixth, the age of death is not controlled. For developmental brain disorders, the available tissue is typically from older patients, long after the initial insult occurred. Thus, samples may reflect the state of the brain as it adapts to the disease state over time, rather than reflecting immediate downstream consequences of a disease-causing condition. Similarly, it is hard to separate neurodegenerative disease from the normal progression of aging.
Seventh, sample integrity is the most critical aspect in postmortem brain research. Although these samples are characterized by postmortem intervals (PMI) of up to 30 hours, most of the postmortem brains contain high-integrity mRNA that is suitable for DNA microarray analysis. However, PMI alone is a poor predictor of sample integrity15. RNA integrity (measured indirectly by brain pH levels) primarily depends on the circumstances of death. Samples of pH less than 6.25 rarely contain intact RNA, and high-quality microarray analysis of these samples is usually not feasible.
Gene expression profiling of individual cases reveals consistent transcriptional changes in alcoholic human brain - J Neurochem, Vol 90, Issue 5, pp. 1050-1058 (Abstract): "Journal of Neurochemistry
Volume 90 Issue 5 Page 1050 - September 2004
doi:10.1111/j.1471-4159.2004.02570.x
Gene expression profiling of individual cases reveals consistent transcriptional changes in alcoholic human brain
Jianwen Liu*, Joanne M. Lewohl, Peter R. Dodd, Patrick K. Randall, R. Adron Harris* and R. Dayne Mayfield*
Abstract
Chronic alcohol exposure induces lasting behavioral changes, tolerance, and dependence. This results, at least partially, from neural adaptations at a cellular level. Previous genome-wide gene expression studies using pooled human brain samples showed that alcohol abuse causes widespread changes in the pattern of gene expression in the frontal and motor cortices of human brain. Because these studies used pooled samples, they could not determine variability between different individuals. In the present study, we profiled gene expression levels of 14 postmortem human brains (seven controls and seven alcoholic cases) using cDNA microarrays (46 448 clones per array). Both frontal cortex and motor cortex brain regions were studied. The list of genes differentially expressed confirms and extends previous studies of alcohol responsive genes. Genes identified as differentially expressed in two brain regions fell generally into similar functional groups, including metabolism, immune response, cell survival, cell communication, signal transduction and energy production. Importantly, hierarchical clustering of differentially expressed genes accurately distinguished between control and alcoholic cases, particularly in the frontal cortex."
UMHS Press Release: Depressed brains different, study finds: "The results are published online this week in the early edition of the Proceedings of the National Academy of Sciences by researchers from the Pritzker Neuropsychiatric Disorders Research Consortium, which is supported by the Pritzker Family Philanthropic Fund and by the National Institute of Mental Health.
The research team consisted of scientists from the University of Michigan's Mental Health Research Institute and Department of Psychiatry, working in close collaboration with researchers from the University of California's Davis and Irvine campuses and from Stanford University.
“This finding comes from a completely unbiased search that began with no hypothesis, to find what genes best differentiate major depression brains from normal and bipolar brains,” says senior author Huda Akil, Ph.D., the Gardner C. Quarton Distinguished Professor of Neurosciences in Psychiatry at U-M. “A wide set of individual genes came up as different between the depressed and control individuals, but the family of genes that was most different and showed the highest significance as a coherent group was the FGF family. This suggests a more profound change in an entire system of communication and control within the brain.”
No previous studies have directly examined the role of FGFs or their receptors in psychiatric illnesses. Another growth factor, called Brain Derived Neurotrophic Factor, has been hypothesized to play a role in the effects of stress on the brain and in the mode of action of antidepressants."
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