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Institution

University of New Mexico

EducationAlbuquerque, 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.


Papers
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Journal ArticleDOI
TL;DR: The detection of clonal histiocytes in all forms of Langerhans'-cell histiocytosis indicates that this disease is probably a clonal neoplastic disorder with highly variable biologic behavior.
Abstract: Background The lesions of Langerhans'-cell histiocytosis (histiocytosis X), a proliferative histiocytic disorder of unknown cause, contain histiocytes similar in phenotype to dendritic Langerhans' cells. The disease ranges in severity from a fatal leukemia-like disorder to an isolated lytic lesion of bone. Intermediate forms of the disease are usually characterized by multiorgan involvement, diabetes insipidus, and a chronic course. Methods To determine whether Langerhans' histiocytosis is a polyclonal reactive disease or a clonal disorder, we used X-linked polymorphic DNA probes (HUMARA, PGK, M27β[DXS255], and HPRT) to assess clonality in lesional tissues and control leukocytes from 10 female patients with various forms of the disease. Lymphoid clonality was also assessed by analysis of rearrangements at immunoglobulin and T-cell-receptor gene loci. Results The HUMARA assay detected clonal cells in the lesions of 9 of the 10 patients: 3 patients had acute disseminated disease, 3 had unifocal disease, and...

903 citations

Journal ArticleDOI
TL;DR: In the era of intrapartum chemoprophylaxis to reduce GBS, rates of EO infection have declined but reflect a continued burden of disease, suggesting that Escherichia coli is an important EO pathogen.
Abstract: BACKGROUND: Guidelines for prevention of group B streptococcal (GBS) infection have successfully reduced early onset (EO) GBS disease. Study results suggest that Escherichia coli is an important EO pathogen. OBJECTIVE: To determine EO infection rates, pathogens, morbidity, and mortality in a national network of neonatal centers. METHODS: Infants with EO infection were identified by prospective surveillance at Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Network centers. Infection was defined by positive culture results for blood and cerebrospinal fluid obtained from infants aged ≤72 hours plus treatment with antibiotic therapy for ≥5 days. Mother and infant characteristics, treatments, and outcomes were studied. Numbers of cases and total live births (LBs) were used to calculate incidence. RESULTS: Among 396 586 LBs (2006–2009), 389 infants developed EO infection (0.98 cases per 1000 LBs). Infection rates increased with decreasing birth weight. GBS (43%, 0.41 per 1000 LBs) and E coli (29%, 0.28 per 1000 LBs) were most frequently isolated. Most infants with GBS were term (73%); 81% with E coli were preterm. Mothers of 67% of infected term and 58% of infected preterm infants were screened for GBS, and results were positive for 25% of those mothers. Only 76% of mothers with GBS colonization received intrapartum chemoprophylaxis. Although 77% of infected infants required intensive care, 20% of term infants were treated in the normal newborn nursery. Sixteen percent of infected infants died, most commonly with E coli infection (33%). CONCLUSION: In the era of intrapartum chemoprophylaxis to reduce GBS, rates of EO infection have declined but reflect a continued burden of disease. GBS remains the most frequent pathogen in term infants, and E coli the most significant pathogen in preterm infants. Missed opportunities for GBS prevention continue. Prevention of E coli sepsis, especially among preterm infants, remains a challenge.

903 citations

Journal ArticleDOI
TL;DR: In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS, which is shown to be effective at detecting intrusions, while maintaining low false positive rates.
Abstract: An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.

902 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a complete description of the CHOOZ experiment, including the source and detector, the calibration methods and stability checks, the event reconstruction procedures and the Monte Carlo simulation.
Abstract: This final article about the CHOOZ experiment presents a complete description of the $\bar{ u}_e$ source and detector, the calibration methods and stability checks, the event reconstruction procedures and the Monte Carlo simulation. The data analysis, systematic effects and the methods used to reach our conclusions are fully discussed. Some new remarks are presented on the deduction of the confidence limits and on the correct treatment of systematic errors.

898 citations


Authors

Showing all 29120 results

NameH-indexPapersCitations
Bruce S. McEwen2151163200638
David Miller2032573204840
Jing Wang1844046202769
Paul M. Thompson1832271146736
David A. Weitz1781038114182
David R. Williams1782034138789
John A. Rogers1771341127390
George F. Koob171935112521
John D. Minna169951106363
Carlos Bustamante161770106053
Lewis L. Lanier15955486677
Joseph Wang158128298799
John E. Morley154137797021
Fabian Walter14699983016
Michael F. Holick145767107937
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202390
2022595
20213,060
20203,049
20192,779
20182,729