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Supplementary Figure from A Recurrent ADPRHL1 Germline Mutation Activates PARP1 and Confers Prostate Cancer Risk in African American Families

Supplementary Table from A Recurrent ADPRHL1 Germline Mutation Activates PARP1 and Confers Prostate Cancer Risk in African American Families

African American (AA) families have the highest risk of prostate cancer. However, the genetic factors contributing to prostate cancer susceptibility in AA families remain poorly understood. We performed whole-exome sequencing of one affected and one unaffected brother in an AA family with hereditary prostate cancer. The novel non-synonymous variants discovered only in the affected individuals were further analyzed in all affected and unaffected men in 20 AA-PC families. Here, we report one rare recurrent ADPRHL1 germline mutation (c.A233T; p.D78V) in four of the 20 families affected by prostate cancer. The mutation co-segregates with prostate cancer in two families and presents in two affected men in the other two families, but was absent in 170 unrelated healthy AA men. Functional characterization of the mutation in benign prostate cells showed aberrant promotion of cell proliferation, whereas expression of the wild-type ADPRHL1 in prostate cancer cells suppressed cell proliferation and oncogenesis. Mechanistically, the ADPRHL1 mutant activates PARP1, leading to an increased H2O2 or cisplatin-induced DNA damage response for prostate cancer cell survival. Indeed, the PARP1 inhibitor, olaparib, suppresses prostate cancer cell survival induced by mutant ADPRHL1. Given that the expression levels of ADPRHL1 are significantly high in normal prostate tissues and reduce stepwise as Gleason scores increase in tumors, our findings provide genetic, biochemical, and clinicopathological evidence that ADPRHL1 is a tumor suppressor in prostate tissue. A loss of function mutation in ADPRHL1 induces prostate tumorigenesis and confers prostate cancer susceptibility in high-risk AA families.Implications:This study highlights a potential strategy for ADPRHL1 mutation detection in prostate cancer–risk assessment and a potential therapeutic application for individuals with prostate cancer in AA families.

It is a common approach to dichotomize a continuous biomarker in clinical setting for the convenience of application. Analytically, results from using a dichotomized biomarker are often more reliable and resistant to outliers, bi-modal and other unknown distributions. There are two commonly used methods for selecting the best cutoff value for dichotomization of a continuous biomarker, using either maximally selected chi-square statistic or a ROC curve, specifically the Youden Index. In this paper, we explained that in many situations, it is inappropriate to use the former. By using the Maximum Absolute Youden Index (MAYI), we demonstrated that the integration of a MAYI and the Kolmogorov–Smirnov test is not only a robust non-parametric method, but also provides more meaningful p value for selecting the cutoff value than using a Mann-Whitney test. In addition, our method can be applied directly in clinical settings.

Affymetrix high-density oligonucleotide microarray makes it pos- sible to simultaneously measure, and thus compare the expression profiles of hundreds of thousands of genes in living cells. Genes differentially ex- pressed in different conditions are very important to both basic and medical research. However, before detecting these differentially expressed genes from a vast number of candidates, it is necessary to normalize the microarray data due to the significant variation caused by non-biological factors. During the last few years, normalization methods based on probe level or probeset level intensities were proposed in the literature. These methods were motivated by different purposes. In this paper, we propose a multivariate normaliza- tion method, based on partial least squares regression, aiming to equalize the central tendency, reduce and equalize the variation of the probe level intensities in any probeset across the replicated arrays. By so doing, we hope that one can precisely estimate the gene expression indexes.

Simple Summary Previous studies have shown heavy intake of different alcoholic beverages affects prostate cancer (PCa) clinical outcomes differently. However, the intake patterns of specific alcoholic beverages for PCa status are understudied. The study's objective is to evaluate intake patterns of total alcohol and three types of alcoholic beverage (beer, wine, and spirits) by PCa risk and aggressiveness status. This study included 10,029 men with European ancestry (4676 non-PCa men and 5353 PCa patients). We found PCa patients had a similar total heavy alcohol intake compared with non-PCa men. However, PCa patients were likely to drink more wine and spirits than non-PCa men. Patients with aggressive PCa drank more beer but not wine and spirits. Interestingly, heavy wine intake was inversely associated with PCa aggressiveness. These findings suggest that the intake patterns of specific alcoholic beverages differ by PCa status, and this information might help develop personalized alcohol intervention for PCa patients. Background: Previous studies have shown that different alcoholic beverage types impact prostate cancer (PCa) clinical outcomes differently. However, intake patterns of specific alcoholic beverages for PCa status are understudied. The study's objective is to evaluate intake patterns of total alcohol and the three types of beverage (beer, wine, and spirits) by the PCa risk and aggressiveness status. Method: This is a cross-sectional study using 10,029 men (4676 non-PCa men and 5353 PCa patients) with European ancestry from the PCa consortium. Associations between PCa status and alcohol intake patterns (infrequent, light/moderate, and heavy) were tested using multinomial logistic regressions. Results: Intake frequency patterns of total alcohol were similar for non-PCa men and PCa patients after adjusting for demographic and other factors. However, PCa patients were more likely to drink wine (light/moderate, OR = 1.11, p = 0.018) and spirits (light/moderate, OR = 1.14, p = 0.003; and heavy, OR = 1.34, p = 0.04) than non-PCa men. Patients with aggressive PCa drank more beer than patients with non-aggressive PCa (heavy, OR = 1.48, p = 0.013). Interestingly, heavy wine intake was inversely associated with PCa aggressiveness (OR = 0.56, p = 0.009). Conclusions: The intake patterns of some alcoholic beverage types differed by PCa status. Our findings can provide valuable information for developing custom alcohol interventions for PCa patients.

African American (AA) families have the highest risk of prostate cancer. However, the genetic factors contributing to prostate cancer susceptibility in AA families remain poorly understood. We performed whole-exome sequencing of one affected and one unaffected brother in an AA family with hereditary prostate cancer. The novel non-synonymous variants discovered only in the affected individuals were further analyzed in all affected and unaffected men in 20 AA-PC families. Here, we report one rare recurrent ADPRHL1 germline mutation (c.A233T; p.D78V) in four of the 20 families affected by prostate cancer. The mutation co-segregates with prostate cancer in two families and presents in two affected men in the other two families, but was absent in 170 unrelated healthy AA men. Functional characterization of the mutation in benign prostate cells showed aberrant promotion of cell proliferation, whereas expression of the wild-type ADPRHL1 in prostate cancer cells suppressed cell proliferation and oncogenesis. Mechanistically, the ADPRHL1 mutant activates PARP1, leading to an increased H2O2 or cisplatin-induced DNA damage response for prostate cancer cell survival. Indeed, the PARP1 inhibitor, olaparib, suppresses prostate cancer cell survival induced by mutant ADPRHL1. Given that the expression levels of ADPRHL1 are significantly high in normal prostate tissues and reduce stepwise as Gleason scores increase in tumors, our findings provide genetic, biochemical, and clinicopathological evidence that ADPRHL1 is a tumor suppressor in prostate tissue. A loss of function mutation in ADPRHL1 induces prostate tumorigenesis and confers prostate cancer susceptibility in high-risk AA families. Implications: This study highlights a potential strategy for ADPRHL1 mutation detection in prostate cancer–risk assessment and a potential therapeutic application for individuals with prostate cancer in AA families.

Liquid biopsy is a new area in cancer diagnostics that measures cell-free DNA in plasma from tumor that may serve as a monitoring tool in colorectal cancer patients.Multiplexed real-time polymerase chain reaction based on multicopy retro-transposable elements (targeting 80 base pair and 265 base pair sequences and an internal-positive-control) was used to evaluate the ability of cell-free DNA concentration and DNA Integrity Index to discriminate cancer from healthy patients. A cohort of 40 healthy controls and 39 stage IV colorectal patient's plasma were interrogated. The potency of each biomarker was measured by using receiver operating characteristic curves and derived area under the curve measures.Significant differences in cell-free DNA concentration and DNA integrity index were observed between controls and stage IV patients with a limit of detection0.1 pg/μL. Investigation of the ability of both biomarker candidates to differentiate cancer from healthy patients showed an area under the curve of 0.9891 and 0.9859 for 80 base pair and 265 amplicons respectively and 0.8603 for DNA integrity index-265/80.After establishing differences in cell-free DNA levels between healthy and treated and untreated stage IV patients, the multiplexed real-time polymerase chain reaction measurements of retro-transposable elements in cancer patient plasma potentially possess the ability to monitor therapy responsiveness in near real time.

Background The practice of surgeons running overlapping operating rooms has recently come under scrutiny. Objective To examine the impact of hospital policy allowing overlapping rooms in the case of patients admitted to a tertiary care, safety-net hospital for urgent neurosurgical procedures. Methods The neurosurgery service at the hospital being studied transitioned from routinely allowing 1 room per day (period 1) to overlapping rooms (period 2), with the second room being staffed by the same attending surgeon. Patients undergoing neurosurgical intervention in each period were retrospectively compared. Demographics, indication, case type, complications, outcomes, and total charges were tracked. Results There were 59 urgent cases in period 1 and 63 in period 2. In the case of these patients, the length of stay was significantly decreased in period 2 (13.09 d vs 19.52; P = .006). The time from admission to surgery (wait time) was also significantly decreased in period 2 (5.12 d vs 7.00; P = .04). Total charges also trended towards less in period 2 (${\$}$150 942 vs ${\$}$200 075; P = .05). Surgical complications were no different between the groups (16.9% vs 14.3%; P = .59), but medical complications were significantly decreased in period 2 (14.3% vs 30.5%; P = .009). Significantly more patients were discharged to home in period 2 (69.8% vs 42.4%; P = .003). Conclusion As a matter of policy, allowing overlapping rooms significantly reduces the length of stay in the case of a vulnerable population in need of urgent surgery at a single safety-net academic institution. This may be due to a reduction in medical complications in these patients.

With continuing cooperation from 18 domestic and international brain banks over the last 36 years, we have analyzed the aluminum content of the temporal lobe neocortex of 511 high-quality human female brain samples from 16 diverse neurological and neurodegenerative disorders, including 2 groups of age-matched controls. Temporal lobes (Brodmann areas A20–A22) were selected for analysis because of their availability and their central role in massive information-processing operations including efferent-signal integration, cognition, and memory formation. We used the analytical technique of (i) Zeeman-type electrothermal atomic absorption spectrophotometry (ETAAS) combined with (ii) preliminary analysis from the advanced photon source (APS) hard X-ray beam (7 GeV) fluorescence raster-scanning (XRFR) spectroscopy device (undulator beam line 2-ID-E) at the Argonne National Laboratory, US Department of Energy, University of Chicago IL, USA. Neurological diseases examined were Alzheimer’s disease (AD; N = 186), ataxia Friedreich’s type (AFT; N = 6), amyotrophic lateral sclerosis (ALS; N = 16), autism spectrum disorder (ASD; N = 26), dialysis dementia syndrome (DDS; N = 27), Down’s syndrome (DS; trisomy, 21; N = 24), Huntington’s chorea (HC; N = 15), multiple infarct dementia (MID; N = 19), multiple sclerosis (MS; N = 23), Parkinson’s disease (PD; N = 27), and prion disease (PrD; N = 11) that included bovine spongiform encephalopathy (BSE; “mad cow disease”), Creutzfeldt-Jakob disease (CJD) and Gerstmann-Straussler-Sheinker syndrome (GSS), progressive multifocal leukoencephalopathy (PML; N = 11), progressive supranuclear palsy (PSP; N = 24), schizophrenia (SCZ; N = 21), a young control group (YCG; N = 22; mean age, 10.2 ± 6.1 year), and an aged control group (ACG; N = 53; mean age, 71.4 ± 9.3 year). Using ETAAS, all measurements were performed in triplicate on each tissue sample. Among these 17 common neurological conditions, we found a statistically significant trend for aluminum to be increased only in AD, DS, and DDS compared to age- and gender-matched brains from the same anatomical region. This is the largest study of aluminum concentration in the brains of human neurological and neurodegenerative disease ever undertaken. The results continue to suggest that aluminum’s association with AD, DDS, and DS brain tissues may contribute to the neuropathology of those neurological diseases but appear not to be a significant factor in other common disorders of the human brain and/or CNS.

Accurate online density estimation is crucial to numerous applications that are prevalent with streaming data. Existing online approaches for density estimation somewhat lack prompt adaptability and robustness when facing concept-drifting and noisy streaming data, resulting in delayed or even deteriorated approximations. To alleviate this issue, in this work, we first propose an adaptive local online kernel density estimator (ALoKDE) for real-time density estimation on data streams. ALoKDE consists of two tightly integrated strategies: (1) a statistical test for concept drift detection and (2) an adaptive weighted local online density estimation when a drift does occur. Specifically, using a weighted form, ALoKDE seeks to provide an unbiased estimation by factoring in the statistical hallmarks of the latest learned distribution and any potential distributional changes that could be introduced by each incoming instance. A robust variant of ALoKDE, i.e., R-ALoKDE, is further developed to effectively handle data streams with varied types/levels of noise. Moreover, we analyze the asymptotic properties of ALoKDE and R-ALoKDE, and also derive their theoretical error bounds regarding bias, variance, MSE and MISE. Extensive comparative studies on various artificial and real-world (noisy) streaming data demonstrate the efficacies of ALoKDE and R-ALoKDE in online density estimation and real-time classification (with noise).

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P –9) and 3145 (P –5) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

Key Points Question Unlike candidate biomarkers inclusive for all forms of systemic inflammation, can dysfunction in host management of microbiota have a high positive predictive value as a biomarker for necrotizing enterocolitis? Findings In this diagnostic study of 136 premature infants, high amounts of intestinal alkaline phosphatase protein in stool and low intestinal alkaline phosphatase enzyme activity were associated with diagnosis of necrotizing enterocolitis. There was no association of intestinal alkaline phosphatase measures with non–gastrointestinal tract infections. Meaning Measuring the inability of intestinal alkaline phosphatase to maintain host-microbiota homeostasis can potentially guide decisions for personalized care and treatment when an infant is most susceptible to developing necrotizing enterocolitis., This diagnostic study evaluates whether aberrant intestinal alkaline phosphatase biochemistry in infant stool is a molecular biomarker for necrotizing enterocolitis and not associated with sepsis in the absence of necrotizing enterocolitis., Importance Necrotizing enterocolitis (NEC) in preterm infants is an often-fatal gastrointestinal tract emergency. A robust NEC biomarker that is not confounded by sepsis could improve bedside management, lead to lower morbidity and mortality, and permit patient selection in randomized clinical trials of possible therapeutic approaches. Objective To evaluate whether aberrant intestinal alkaline phosphatase (IAP) biochemistry in infant stool is a molecular biomarker for NEC and not associated with sepsis. Design, Setting, and Participants This multicenter diagnostic study enrolled 136 premature infants (gestational age

In this paper, we consider the problem of seeking locally optimal designs for nonlinear dose-response models with binary outcomes. Applying the theory of Tchebycheff Systems and other algebraic tools, we show that the locally D-, A-, and c-optimal designs for three binary dose-response models are minimally supported in finite, closed design intervals. The methods to obtain such designs are presented along with examples. The efficiencies of these designs are also discussed.

By sequence homology search, the list of all the functions found and the counts of reads being aligned to them present the functional profile of a metagenomic sample. However, a significant obstacle has been observed in this approach due to the short read length associated with many next generation sequencing technologies. This includes artificial families, cross-annotations, length bias and conservation bias. The widely applied cutoff methods, such as BLAST E-value, are not able to solve the problems. Following the published successful procedures on the artificial families and the cross-annotation issue, we propose in this paper to use zero-truncated Poisson and Binomial (ZTP-Bin) hierarchical modelling to correct the length bias and the conservation bias. Goodness-of-fit of the modelling and cross-validation for the prediction using a bioinformatic simulated sample show the validity of this approach. Evaluated on an in vitro-simulated data set, the proposed modelling method outperforms other traditional methods. All three steps were then sequentially applied on real-life metagenomic samples to show that the proposed framework will lead to a more accurate functional profile of a short read metagenomic sample.

Interferon-stimulated gene 15 (ISG15), an antagonist of the ubiquitin pathway, is elevated in cells and brain tissues obtained from ataxia telangiectasia (A-T) patients. Previous studies reveal that an elevated ISG15 pathway inhibits ubiquitin-dependent protein degradation, leading to activation of basal autophagy as a compensatory mechanism for protein turnover in A-T cells. Also, genotoxic stress (ultraviolet [UV] radiation) deregulates autophagy and induces aberrant degradation of ubiquitylated proteins in A-T cells. In the current study, we show that, as in A-T cells, ISG15 protein expression is elevated in cerebellums and various other tissues obtained from Atm-compromised mice in an Atm-allele-dependent manner (Atm+/+

In this article we investigate the optimal design problem for some wavelet regression models. Wavelets are very flexible in modeling complex relations, and optimal designs are appealing as a means of increasing the experimental precision. In contrast to the designs for the Haar wavelet regression model (Herzberg and Traves 1994; Oyet and Wiens 2000), the I-optimal designs we construct are different from the D-optimal designs. We also obtain c-optimal designs. Optimal (D- and I-) quadratic spline wavelet designs are constructed, both analytically and numerically. A case study shows that a significant saving of resources may be realized by employing an optimal design. We also construct model robust designs, to address response misspecification arising from fitting an incomplete set of wavelets.

Background: African American (AA) men have a higher risk of developing prostate cancer than white men. SNPs are known to play an important role in developing prostate cancer. The impact of PVT1 and its neighborhood genes (CASC11 and MYC) on prostate cancer risk are getting more attention recently. The interactions among these three genes associated with prostate cancer risk are understudied, especially for AA men. The objective of this study is to investigate SNP–SNP interactions in the CASC11–MYC–PVT1 region associated with prostate cancer risk in AA men. Methods: We evaluated 205 SNPs using the 2,253 prostate cancer patients and 2,423 controls and applied multiphase (discovery-validation) design. In addition to SNP individual effects, SNP–SNP interactions were evaluated using the SNP Interaction Pattern Identifier, which assesses 45 patterns. Results: Three SNPs (rs9642880, rs16902359, and rs12680047) and 79 SNP–SNP pairs were significantly associated with prostate cancer risk. These two SNPs (rs16902359 and rs9642880) in CASC11 interacted frequently with other SNPs with 56 and 9 pairs, respectively. We identified the novel interaction of CASC11–PVT1, which is the most common gene interaction (70%) in the top 79 pairs. Several top SNP interactions have a moderate to large effect size (OR, 0.27–0.68) and have a higher prediction power to prostate cancer risk than SNP individual effects. Conclusions: Novel SNP–SNP interactions in the CASC11–MYC–PVT1 region have a larger impact than SNP individual effects on prostate cancer risk in AA men. Impact: This gene–gene interaction between CASC11 and PVT1 can provide valuable information to reveal potential biological mechanisms of prostate cancer development.

Aluminum is a ubiquitous neurotoxin highly enriched in our biosphere, and has been implicated in the etiology and pathology of multiple neurological diseases that involve inflammatory neural degeneration, behavioral impairment and cognitive decline. Over the last 36 years our group has analyzed the aluminum content of the temporal lobe neocortex of 511 high quality coded human brain samples from 18 diverse neurological and neurodegenerative disorders, including 2 groups of age-matched controls. Brodmann anatomical areas including the inferior, medial and superior temporal gyrus (A20-A22) were selected for analysis: (i) because of their essential functions in massive neural information processing operations including cognition and memory formation; and (ii) because subareas of these anatomical regions are unique to humans and are amongst the earliest areas affected by progressive neurodegenerative disorders such as Alzheimer's disease (AD). Coded brain tissue samples were analyzed using the analytical technique of: (i) Zeeman-type electrothermal atomic absorption spectrophotometry (ETAAS) combined with (ii) an experimental multi-elemental analysis using the advanced photon source (APS) ultra-bright storage ring-generated hard X-ray beam (7 GeV) and fluorescence raster scanning (XRFR) spectroscopy device at the Argonne National Laboratory, US Department of Energy, University of Chicago IL, USA. These data represent the largest study of aluminum concentration in the brains of human neurological and neurodegenerative disease ever undertaken. Neurological diseases examined were AD (N=186), ataxia Friedreich's type (AFT; N=6), amyotrophic lateral sclerosis (ALS; N=16), autism spectrum disorder (ASD; N=26), dialysis dementia syndrome (DDS; N=27), Down's syndrome (DS; trisomy21; N=24), Huntington's chorea (HC; N=15), multiple infarct dementia (MID; N=19), multiple sclerosis (MS; N=23), Parkinson's disease (PD; N=27), prion disease (PrD; N=11) including bovine spongiform encephalopathy (BSE; 'mad cow disease'), Creutzfeldt-Jakob disease (CJD) and Gerstmann-Straussler-Sheinker syndrome (GSS), progressive multifocal leukoencephalopathy (PML; N=11), progressive supranuclear palsy (PSP; N=24), schizophrenia (SCZ; N=21), a young control group (YCG; N=22) and an aged control group (ACG; N=53). Amongst these 18 common neurological conditions and controls we report a statistically significant trend for aluminum to be increased only in AD, DS and DDS compared to age- and gender-matched brains from the same anatomical region. The results continue to suggest that aluminum's association with AD, DDS and DS brain tissues may contribute to the neuropathology of these neurological diseases but appear not to be a significant factor in other common disorders of the human central nervous system (CNS).

Background DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization. Results In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression. Conclusions Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.

Paired sequencing data are commonly collected in genomic studies to control biological variation. However, existing data processing strategies suffer at low coverage regions, which are unavoidable due to the limitation of current sequencing technology. Furthermore, information contained in the absolute values of the read counts is commonly ignored. We propose a read count ratio processing/modification method, to not only incorporate information contained in the absolute values of paired counts into one variable, but also mitigate the discrete artifact, especially when both counts are small. Simulation shows that the processed variable fits well with a Beta distribution, thus providing an easy tool for down-stream inference analysis.

We consider the problem of constructing static (or non sequential), approximate optimal designs for a class of dose–response models with continuous outcomes. We obtain conditions for a design being D-optimal or c-optimal. The designs are locally optimal in that they depend on the model parameters. The efficiency studies show that these designs have high efficiency when the mis-specification of the initial values of model parameters is not severe. A case study indicates that using an optimal design may result in a significant saving of resources.

Sparse online learning and cost-sensitive learning are two important areas of machine learning and data mining research. Each has been well studied with many interesting algorithms developed. However, very limited published work addresses the joint study of these two fields. In this paper, to tackle the high-dimensional data streams with skewed distributions, we introduce a framework of cost-sensitive sparse online learning. Our proposed framework is a substantial extension of the influential Truncated Gradient (TG) method by formulating a new convex optimization problem, where the two mutual restraint factors, misclassification cost and sparsity, can be simultaneously and favorably balanced. We theoretically analyze the regret and cost bounds of the proposed algorithm, and pinpoint its theoretical merit compared to the existing related approaches. Large-scale empirical comparisons to five baseline methods on eight real-world streaming datasets demonstrate the encouraging performance of the developed method. Algorithm implementation and datasets are available upon request.

Introduction: While effective HIV treatments have decreased the likelihood of AIDS-defining illnesses among people aging with HIV, HIV-associated non-AIDS conditions are more common in individuals with long-standing HIV infection, including cardiovascular disease (CVD), hypertension, diabetes mellitus, and renal failure among others. It has been estimated that 30% of deaths among those with well-controlled viral load has been attributed to CVD, compared to 23.5% in the general US population. The purpose of this study was to determine the prevalence trends of CVD in people living with HIV/AIDS (PLWHA) in South Louisiana. Methods: A ten-year retrospective cohort study was conducted using data abstracted from the Louisiana State University (LSU) Health Care Services Division, Disease Management Evaluation Database (DMED) that included patients who received care within the LSU Medical System 7 state facilities. Inclusion criteria included 18 years of age or above, a positive HIV lab test, and a HIV diagnose code. Total sample size for the analysis was 9,374. The presence of CVD was established using ICD9 Diagnosis codes, patient vitals, and lab results. CVD outcomes evaluated included myocardial infarction, coronary artery disease, hypertension, heart failure, and stroke. All analyses were conducted in SAS 9.4. Results: The racial distribution was 24% white, 67% black, 2% other, and 7% unknown; distribution by sex remained stabled over the ten-year period approximately 58% male and 42% female. The mean age of the clinic population increased from 39.24±10.17 to 45.09±10.46 over the ten year period. There has been a positive trend in CVD among the HIV Clinic population, from 23.0% to 50.7% prevalence. There was an increase in hypertension, heart failure, stroke, and coronary artery disease among PLWHA. Hypertension showed the largest increase in prevalence from 19.4% to 44.8%. A positive trend and in increased Framingham Risk score was also observed (p< 0.05). Conclusion: As PLWHA continue to increase in age, mortality and hospital admissions attributed to CVD has the potential to continue to increase. Data from this project has the potential to guide additional screening recommendations and practices, ultimately resulting in more timely detection of disease, which improves outcomes for patients.

Background: In recent years, metagenomics, as a combination of research techniques without the process of cultivation, has become more and more popular in studying the genomic/genetic variation of microbes in environmental or clinical samples. Though generated from similar sequencing technologies, there is increasing evidence that metagenomic sequence data may not be treated as another variant of RNA-Seq count data, especially due to its compositional characteristics. While it is often of primary interest to compare taxonomic or functional profiles of microbial communities between conditions, normalization for library size is usually an inevitable step prior to a typical differential abundance analysis. Some methods have been proposed for such normalization. But the existing performance evaluation of normalization methods for metagenomic sequence data does not adequately consider the compositional characteristics.

Background and Purpose Sodium butyrate (NaB), an epigenetic modifier, is effective in promoting insulin sensitivity. The specific genomic loci and mechanisms underlying epigenetically induced obesity and insulin resistance and the targets of NaB are not fully understood.