36 research outputs found
The gene coding for variant hepatic nuclear factor 1 ( Tcf-2 ), maps between the Edp-1 and Erba genes on mouse Chromosome 11
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46992/1/335_2004_Article_BF00352466.pd
Localization of sequences related to the human RAD6 DNA repair gene on mouse Chromosomes 11 and 13
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47025/1/335_2004_Article_BF00352425.pd
Lysyl oxidase ( Lox ) maps between Grl-1 and Adrb-2 on mouse Chromosome 18
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47002/1/335_2004_Article_BF00352234.pd
Localization of the human Chromosome 5q genes Gabra-1, Gabrg-2, Il-4, Il-5 , and Irf-1 on mouse Chromosome 11
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46991/1/335_2004_Article_BF00350629.pd
Mouse Chromosome 11
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46996/1/335_2004_Article_BF00648429.pd
Spatial organization of neurons in the frontal pole sets humans apart from great apes
Few morphological differences have been identified so far that distinguish the human brain from the brains of our closest relatives, the apes. Comparative analyses of the spatial organization of cortical neurons, including minicolumns, can aid our understanding of the functionally relevant aspects of microcircuitry. We measured horizontal spacing distance and gray-level ratio in layer III of 4 regions of human and ape cortex in all 6 living hominoid species: frontal pole (Brodmann area [BA] 10), and primary motor (BA 4), primary somatosensory (BA 3), and primary visual cortex (BA 17). Our results identified significant differences between humans and apes in the frontal pole (BA 10). Within the human brain, there were also significant differences between the frontal pole and 2 of the 3 regions studied (BA 3 and BA 17). Differences between BA 10 and BA 4 were present but did not reach significance. These findings in combination with earlier findings on BA 44 and BA 45 suggest that human brain evolution was likely characterized by an increase in the number and width of minicolumns and the space available for interconnectivity between neurons in the frontal lobe, especially the prefrontal cortex
Serum Neuron-Specific Enolase Levels from the Same Patients Differ Between Laboratories: Assessment of a Prospective Post-cardiac Arrest Cohort
BACKGROUND: In comatose post-cardiac arrest patients, a serum neuron-specific enolase (NSE) level of >33 mug/L within 72 h was identified as a reliable marker for poor outcome in a large Dutch study (PROPAC), and this level was subsequently adopted in an American Academy of Neurology practice parameter. Later studies reported that NSE >33 mug/L is not a reliable predictor of poor prognosis. To test whether different clinical laboratories contribute to this variability, we compared NSE levels from the laboratory used in the PROPAC study (DLM-Nijmegen) with those of our hospital's laboratory (ARUP) using paired blood samples. METHODS: We prospectively enrolled cardiac arrest patients who remained comatose after resuscitation. During the first 3 days, paired blood samples for serum NSE were drawn at a median of 10 min apart. After standard preparation for each lab, one sample was sent to ARUP laboratories and the other to DLM-Nijmegen. RESULTS: Fifty-four paired serum samples from 33 patients were included. Although the serum NSE measurements correlated well between laboratories (R = 0.91), the results from ARUP were approximately 30 % lower than those from DLM-Nijmegen. Therapeutic hypothermia did not affect this relationship. Two patients had favorable outcomes after hypothermia despite NSE levels measured by DLM-Nijmegen as >33 mug/L. CONCLUSIONS: Absolute serum NSE levels of comatose cardiac arrest patients differ between laboratories. Any specific absolute cut-off levels proposed to prognosticate poor outcome should not be used without detailed data on how neurologic outcomes correspond to a particular laboratory's method, and even then only in conjunction with other prognostic variables