Browsing by Subject "risk"

Now showing 1 - 10 of 10

Boys and Risk in Utero
(The Texas Scientist, 2021) The Texas Scientist
Dynamic Financial Index Models: Modeling Conditional Dependencies Via Graphs
(2011) Wang, Hao; Reeson, Craig; Carvalho, Carlos M.; Carvalho, Carlos M.
We discuss the development and application of dynamic graphical models for multivariate financial time series in the context of Financial Index Models. The use of graphs generalizes the independence residual variation assumption of index models with a more complex yet still parsimonious alternative. Working with the dynamic matrix-variate graphical model framework, we develop general time-varying index models that are analytically tractable. In terms of methodology, we carefully explore strategies to deal with graph uncertainty and discuss the implementation of a novel computational tool to sequentially learn about the conditional independence relationships defining the model. Additionally, motivated by our applied context, we extend the DGM framework to accommodate random regressors. Finally, in a case study involving 100 stocks, we show that our proposed methodology is able to generate improvements in covariance forecasting and portfolio optimization problems.
Frequency Of Development Of Connective Tissue Disease In Statin-Users Versus Nonusers
(2013-09) Schmidt, Thomas; Battafarano, Daniel F.; Mortensen, Eric M.; Frei, Christopher R.; Mansi, Ishak; Frei, Christopher R.
Statins have pleiotropic properties that may affect the development of connective tissue diseases (CTD). The objective of this study was to compare the risk of CTD diagnoses in statin users and nonusers. This study was a propensity score-matched analysis of adult patients (30 to 85 years old) in the San Antonio military medical community. The study was divided into baseline (October 1, 2003 to September 30, 2005), and follow-up (October 1, 2005 to March 5, 2010) periods. Statin users received a statin prescription during fiscal year 2005. Nonusers did not receive a statin at any time during the study. The outcome measure was the occurrence of 3 diagnosis codes of the International Classification of Diseases, 9th Revision, Clinical Modification consistent with CTD. We described co-morbidities during the baseline period using the Charlson Comorbidity Index. We created a propensity score based on 41 variables. We then matched statin users and nonusers 1:1, using a caliper of 0.001. Of 46,488 patients who met study criteria (13,640 statin users and 32,848 nonusers), we matched 6,956 pairs of statin users and nonusers. Matched groups were similar in terms of patient age, gender, incidence of co-morbidities, total Charlson Comorbidity Index, health care use, and medication use. The odds ratio for CTD was lower in statin users than nonusers (odds ratio: 0.80; 95% confidence interval: 0.64 to 0.99; p = 0.05). Secondary analysis and sensitivity analysis confirmed these results. In conclusion, statin use was associated with a lower risk of CTD. Published by Elsevier Inc.
Impaired Function of Antibodies to Pneumococcal Surface Protein A but not to Capsular Polysaccharide in Mexican American Adults with Type 2 Diabetes Mellitus
(2012-09) Mathews, Christine E.; Brown, Eric L.; Martinez, Perla J.; Bagaria, Upasana; Nahm, Moon H.; Burton, Robert L.; Fisher-Hoch, Susan P.; McCormick, Joseph B.; Mirza, Sharper; Nahm, Moon H.
The goal of the study was to determine baseline protective titers of antibodies to Streptococcus pneumoniae surface protein A (PspA) and capsular polysaccharide in individuals with and individuals without type 2 diabetes mellitus. A total of 561 individuals (131 individuals with diabetes and 491 without) were screened for antibodies to PspA using a standard enzyme-linked immunosorbent assay (ELISA). A subset of participants with antibodies to PspA were retested using a WHO ELISA to determine titers of antibodies to capsular polysaccharide (CPS) (serotypes 4, 6B, 9V, 14, 18C, 19A, 19F, and 23F). Functional activity of antibodies was measured by assessing their ability to enhance complement (C3) deposition on pneumococci and promote killing of opsonized pneumococci. Titers of antibodies to protein antigens (PspA) were significantly lower in individuals with diabetes than controls without diabetes (P = 0.01), and antibodies showed a significantly reduced complement deposition ability (P = 0.02). Both antibody titers and complement deposition were negatively associated with hyperglycemia. Conversely, titers of antibodies to capsular polysaccharides were either comparable between the two groups or were significantly higher in individuals with diabetes, as was observed for CPS 14 (P = 0.05). The plasma specimens from individuals with diabetes also demonstrated a higher opsonophagocytic index against CPS serotype 14. Although we demonstrate comparable protective titers of antibodies to CPS in individuals with and individuals without diabetes, those with diabetes had lower PspA titers and poor opsonic activity strongly associated with hyperglycemia. These results suggest a link between diabetes and impairment of antibody response.
Optimal Risk-Based Design of Hydraulic Structures
(University of Texas at Austin, 1980-08) Tung, Y.K.; Mays, L.W.
Rare Key Functional Domain Missense Substitutions in MRE11A, RAD50, and NBN Contribute to Breast Cancer Susceptibility: Results From a Breast Cancer Family Registry Case-Control Mutation-Screening Study
(2014) Damiola, Francesca; Pertesi, Maroulio; Oliver, Javier; Le Calvez-Kelm, Florence; Voegele, Catherine; Young, Erin L.; Robinot, Nivonirina; Forey, Nathalie; Durand, Geoffroy; Vallee, Maxime P.; Tao, Kayoko; Roane, Terrell C.; Williams, Gareth J.; Hopper, John L.; Southey, Melissa C.; Andrulis, Irene L.; John, Esther M.; Goldgar, David E.; Lesueur, Fabienne; Tavtigian, Sean V.; Roane, Terrell C.
The MRE11A-RAD50-Nibrin (MRN) complex plays several critical roles related to repair of DNA double-strand breaks. Inherited mutations in the three components predispose to genetic instability disorders and the MRN genes have been implicated in breast cancer susceptibility, but the underlying data are not entirely convincing. Here, we address two related questions: (1) are some rare MRN variants intermediate-risk breast cancer susceptibility alleles, and if so (2) do the MRN genes follow a BRCA1/BRCA2 pattern wherein most susceptibility alleles are protein-truncating variants, or do they follow an ATM/CHEK2 pattern wherein half or more of the susceptibility alleles are missense substitutions? Methods: Using high-resolution melt curve analysis followed by Sanger sequencing, we mutation screened the coding exons and proximal splice junction regions of the MRN genes in 1,313 early-onset breast cancer cases and 1,123 population controls. Rare variants in the three genes were pooled using bioinformatics methods similar to those previously applied to ATM, BRCA1, BRCA2, and CHEK2, and then assessed by logistic regression. Results: Re-analysis of our ATM, BRCA1, and BRCA2 mutation screening data revealed that these genes do not harbor pathogenic alleles (other than modest-risk SNPs) with minor allele frequencies > 0.1% in Caucasian Americans, African Americans, or East Asians. Limiting our MRN analyses to variants with allele frequencies of < 0.1% and combining protein-truncating variants, likely spliceogenic variants, and key functional domain rare missense substitutions, we found significant evidence that the MRN genes are indeed intermediate-risk breast cancer susceptibility genes (odds ratio (OR) = 2.88, P = 0.0090). Key domain missense substitutions were more frequent than the truncating variants (24 versus 12 observations) and conferred a slightly higher OR (3.07 versus 2.61) with a lower P value (0.029 versus 0.14). Conclusions: These data establish that MRE11A, RAD50, and NBN are intermediate-risk breast cancer susceptibility genes. Like ATM and CHEK2, their spectrum of pathogenic variants includes a relatively high proportion of missense substitutions. However, the data neither establish whether variants in each of the three genes are best evaluated under the same analysis model nor achieve clinically actionable classification of individual variants observed in this study.
Risk For Poor Performance On A Language Screening Measure For Bilingual Preschoolers And Kindergarteners
(2011-11) Pena, Elizabeth D.; Gillam, Ronald B.; Bedore, Lisa M.; Bohman, Thomas M.; Pena, Elizabeth D.; Bedore, Lisa M.; Bohman, Thomas M.
Purpose: This study documents the risk for language impairment in Latino children who had different levels of exposure to English and Spanish. Method: A total of 1,029 preschool- and kindergarten-age children were screened in the domains of semantics and morphosyntax in both Spanish and English. Parent report was used to document current exposure to and use of Spanish and English, as well as year of first exposure to English. Risk for language impairment was compared for language group, year of first English exposure, age, and mother's education. Results: While bilingual children's scores on each subtest were significantly lower compared to their functional monolingual peers, they were no more likely to fall in the at-risk range based on a combination of all 4 subtests. Maternal education and year of first English exposure were weakly associated with risk for language impairment but not with language group (via 5 levels of first and second language exposure). Conclusions: Prevalence of risk for language impairment when both languages are tested is not related to language group.
A Seasonal Periodicity in Relapses of Multiple Sclerosis? A Single-Center, Population-Based, Preliminary Study Conducted in Bologna, Italy
(2010-11) Salvi, Fabrizio; Bartolomei, Ilaria; Smolensky, Michael H.; Lorusso, Angelo; Barbarossa, Elena; Malagoni, Anna Maria; Zamboni, Paolo; Manfredini, Roberto; Smolensky, Michael H.
Temporal, i.e., 24-hour, weekly, and seasonal patterns in the occurrence of acute cardiovascular and cerebrovascular events are well documented; however, little is known about temporal, especially seasonal, variation in multiple sclerosis (MS) and its relapses. This study investigated, by means of a validated chronobiological method, whether severe relapses of MS, ones requiring medical specialty consultation, display seasonal differences, and whether they are linked with seasonal differences in local meteorological variables. Results: We considered 96 consecutive patients with severe MS relapse (29 men, 67 women, mean age 38.5 +/- 8.8 years), referred to the Multiple Sclerosis Center, Bellaria Hospital, Bologna, Italy, between January 1, 2007 and December 31, 2008. Overall, we analyzed 164 relapses (56 in men, 108 in women; 115 in patients aged < 40 years, 49 in patients >= 40 years). Relapses were more frequent in May and June (12.2% each) and the least frequent in September (3.7%). Chronobiological analysis showed a biphasic pattern (major peak in May-June, secondary peak in November-December, p = 0.030). Analysis of monthly mean meteorological data showed a significant seasonal pattern in ambient temperature (peak in July, p < 0.001), relative humidity (peak in January, p < 0.001), and wind speed (peak in June, p = 0.011). Conclusions: In this Italian setting, we found a biphasic pattern (peaks in spring and autumn) in severe MS relapses requiring medical consultation by doctors of the MS specialty center, apparently unrelated to meteorological variables. Confirmations of the findings on larger multi-center populations residing in different climatic conditions are needed to further explore the potential seasonality of MS relapses and associated environmental triggers.
“Success Is Invisible, But Failure Is Public”: Examining The U.S. Office Of Personnel Management Data Records Breach
(2018-05) Lin, Zeyi
In 2015, the U.S. Office of Personnel Management (OPM) suffered one of the largest governmentrelated data breaches in U.S. history. A total of 4.2 million personnel records, 21.5 million background check records, and 5.6 million sets of fingerprints were exfiltrated in a sophisticated, multi-stage cyber espionage operation linked to state-sponsored actors. Such a large data breach invited bipartisan criticism of the agency’s handling of the incidents and thrust the federal government’s cybersecurity preparedness into the limelight. This paper seeks to answer a set of five interrelated questions: 1) What happened in the 2015 U.S. Office of Personnel Management Data breach, and what were the impacts? 2) Did a lack of technical capability hinder OPM’s efforts to detect and block unauthorized access to its network? 3) Were organizational and management weaknesses more to blame? 4) Did the cybersecurity posture at OPM before the incidents change after the events in 2014 and 2015? 5) What can be done by the Office of Personnel Management to prevent or mitigate the damage from similar cyber activities in the future? To answer these questions, this paper first introduces the concept of the “cybersecurity toolkit” to better understand contemporary cyber issues. Second, the OPM case study is discussed, including a timeline of events and key actors. Third, this paper examines the technical, management, and compliance-related factors that contributed to the breaches, including a compilation and analysis of OPM Inspector General cybersecurity audit data from 2007 to 2017. Finally, this paper discusses the short- and long-term impacts of the OPM breach and offers recommendations to improve cybersecurity at OPM and within the federal government.
A Tractable State-Space Model for Symmetric Positive-Definite Matrices
(2014-12) Windle, Jesse; Carvalho, Carlos M.; Carvalho, Carlos M.
The Bayesian analysis of a state-space model includes computing the posterior distribution of the system's parameters as well as its latent states. When the latent states wander around R-n there are several well-known modeling components and computational tools that may be profitably combined to achieve this task. When the latent states are constrained to a strict subset of R-n these models and tools are either impaired or break down completely. State-space models whose latent states are covariance matrices arise in finance and exemplify the challenge of devising tractable models in the constrained setting. To that end, we present a state-space model whose observations and latent states take values on the manifold of symmetric positive-definite matrices and for which one may easily compute the posterior distribution of the latent states and the system's parameters as well as filtered distributions and one-step ahead predictions. Employing the model within the context of finance, we show how one can use realized covariance matrices as data to predict latent time-varying covariance matrices. This approach out-performs factor stochastic volatility.