Institution
University of New Mexico
Education•Albuquerque, New Mexico, United States•
About: University of New Mexico is a education organization based out in Albuquerque, New Mexico, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 28870 authors who have published 64767 publications receiving 2578371 citations. The organization is also known as: UNM & Universitatis Novus Mexico.
Topics: Population, Poison control, Laser, Health care, Large Hadron Collider
Papers published on a yearly basis
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National Institutes of Health1, Indiana University – Purdue University Indianapolis2, George Washington University3, University of Cincinnati4, Emory University5, Case Western Reserve University6, University of Texas Southwestern Medical Center7, University of Miami8, Wayne State University9, University of Tennessee Health Science Center10, Stanford University11, University of New Mexico12, Yale University13
TL;DR: ELBW infants are at significant risk of neurologic abnormalities, developmental delays, and functional delays at 18 to 22 months' corrected age, and factors significantly associated with decreased morbidity included increased birth weight, female gender, higher maternal education, and white race.
Abstract: Objectives. The purposes of this study were to report the neurodevelopmental, neurosensory, and functional outcomes of 1151 extremely low birth weight (401–1000 g) survivors cared for in the 12 participating centers of the National Institute of Child Health and Human Development Neonatal Research Network, and to identify medical, social, and environmental factors associated with these outcomes. Study Design. A multicenter cohort study in which surviving extremely low birth weight infants born in 1993 and 1994 underwent neurodevelopmental, neurosensory, and functional assessment at 18 to 22 months9 corrected age. Data regarding pregnancy and neonatal outcome were collected prospectively. Socioeconomic status and a detailed interim medical history were obtained at the time of the assessment. Logistic regression models were used to identify maternal and neonatal risk factors for poor neurodevelopmental outcome. Results. Of the 1480 infants alive at 18 months of age, 1151 (78%) were evaluated. Study characteristics included a mean birth weight of 796 ± 135 g, mean gestation (best obstetric dates) 26 ± 2 weeks, and 47% male. Birth weight distributions of infants included 15 infants at 401 to 500 g; 94 at 501 to 600 g; 208 at 601 to 700 g; 237 at 701 to 800 g; 290 at 801 to 900 g; and 307 at 901 to 1000 g. Twenty-five percent of the children had an abnormal neurologic examination, 37% had a Bayley II Mental Developmental Index Conclusion. ELBW infants are at significant risk of neurologic abnormalities, developmental delays, and functional delays at 18 to 22 months9 corrected age.
1,117 citations
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Fred Hutchinson Cancer Research Center1, Center for International Blood and Marrow Transplant Research2, University of California, San Francisco3, National Marrow Donor Program4, University of Texas MD Anderson Cancer Center5, Thomas Jefferson University Hospital6, Georgetown University Medical Center7, University of Minnesota8, University of New Mexico9
TL;DR: In multivariate modeling, patient age, race, disease stage, and cytomegalovirus status were as predictive of survival as donor HLA matching, and high-resolution DNA matching for HLA-A, -B, -C, and -DRB1 alleles is associated with higher rates of survival.
1,105 citations
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TL;DR: McGraw and Wong as mentioned in this paper described an appealing index of effect size, called CL, which measures the difference between two populations in terms of the probability that a score sampled at random from...
Abstract: McGraw and Wong (1992) described an appealing index of effect size, called CL, which measures the difference between two populations in terms of the probability that a score sampled at random from ...
1,104 citations
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TL;DR: Associations between inherited cellular transport gene variants and risk of EOC histologic subtypes are revealed on a large cohort of women.
Abstract: BACKGROUND: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons. RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4). CONCLUSION: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.
1,100 citations
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Michigan State University1, J. Craig Venter Institute2, National Institutes of Health3, Wellcome Trust Sanger Institute4, Plymouth Marine Laboratory5, University of Maryland, Baltimore6, University of Cambridge7, University of York8, United States Department of Energy9, Ghent University10, Pennsylvania State University11, Argonne National Laboratory12, University of California, San Diego13, Jacobs University Bremen14, University of Colorado Boulder15, National Science Foundation16, Edinburgh Napier University17, Boston Children's Hospital18, University of Georgia19, University of California, Berkeley20, Newcastle University21, Lawrence Berkeley National Laboratory22, University of California, Irvine23, University of Oxford24, Howard University25, Abertay University26, University of Manchester27, Technical University of Denmark28, University of Wyoming29, University of Pennsylvania30, University of New Mexico31
TL;DR: Here, the minimum information about a genome sequence (MIGS) specification is introduced with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange.
Abstract: With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC). Here, we introduce the minimum information about a genome sequence (MIGS) specification with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange. As part of its wider goals, the GSC also supports improving the 'transparency' of the information contained in existing genomic databases.
1,097 citations
Authors
Showing all 29120 results
Name | H-index | Papers | Citations |
---|---|---|---|
Bruce S. McEwen | 215 | 1163 | 200638 |
David Miller | 203 | 2573 | 204840 |
Jing Wang | 184 | 4046 | 202769 |
Paul M. Thompson | 183 | 2271 | 146736 |
David A. Weitz | 178 | 1038 | 114182 |
David R. Williams | 178 | 2034 | 138789 |
John A. Rogers | 177 | 1341 | 127390 |
George F. Koob | 171 | 935 | 112521 |
John D. Minna | 169 | 951 | 106363 |
Carlos Bustamante | 161 | 770 | 106053 |
Lewis L. Lanier | 159 | 554 | 86677 |
Joseph Wang | 158 | 1282 | 98799 |
John E. Morley | 154 | 1377 | 97021 |
Fabian Walter | 146 | 999 | 83016 |
Michael F. Holick | 145 | 767 | 107937 |