48 research outputs found
Associations between risk factors and lack of ART initiation among HIV-seropositive patients with CD4 at or below 350 cells/mm<sup>3</sup> enrolled in CNICS (including deaths) with inverse probability of censoring weighting, 2003–2012.
<p>Associations between risk factors and lack of ART initiation among HIV-seropositive patients with CD4 at or below 350 cells/mm<sup>3</sup> enrolled in CNICS (including deaths) with inverse probability of censoring weighting, 2003–2012.</p
Association between clinical characteristics and lack of ART initiation across two enrollment periods among HIV-seropositive patients enrolled in CNICS (including deaths) with inverse probability of censoring weighting, 2003–2012.
<p>Association between clinical characteristics and lack of ART initiation across two enrollment periods among HIV-seropositive patients enrolled in CNICS (including deaths) with inverse probability of censoring weighting, 2003–2012.</p
Characteristics of HIV-seropositive Patients Enrolled in CNICS, 2003–2012.
<p>Characteristics of HIV-seropositive Patients Enrolled in CNICS, 2003–2012.</p
Cumulative mortality for patients in care and lost to clinic.
<p>Crude (grey) and standardized (black) survival curves compare mortality between patients continuously retained in care at CNICS sites (solid lines) and patients lost to clinic (dotted lines) among 7183 patients who initiated antiretroviral therapy between January 1, 1998 and December 31, 2009 and survived for at least one year at 8 US clinical sites, followed for death up for 5 years.</p
Five-year risk ratios and risk differences comparing mortality between patients continuously retained in care at CNICS sites and patients lost to clinic among 7183 patients who initiated antiretroviral therapy between January 1, 1998 and December 31, 2009 and survived for at least one year at 8 US clinical sites, followed for death up to 5 years.
<p>CI, Confidence interval; RR, risk ratio; RD, risk difference.</p>a<p>Cumulative mortality risk was calculated as the complement of the Kaplan-Meier survival curve at 5 and 10 years.</p>b<p>Confidence intervals based on 200 nonparametric bootstrap resamples.</p>c<p>For sex, age, race, ethnicity, AIDS status at baseline, antiretroviral-therapy-naive at baseline, sexual orientation, injection drug use at baseline, CD4 cell count, viral load at baseline, and calendar date of ART initiation, and time-varying CD4 cell count, viral load, and AIDS status.</p
Demographics and clinical characteristics at study entry one year after ART initiation and over 25,581 person-years of follow-up among 7183 patients who initiated antiretroviral therapy between January 1, 1998 and December 31, 2009 and survived for at least one year at 8 US clinical sites, followed for death up to 5 years.
<p>ARV, antiretroviral; IQR, interquartile range; MSM, men who have sex with men; ART, antiretroviral therapy; AIDS, acquired immunodeficiency syndrome; VL, viral load.</p>a<p>Unavailable.</p>b<p><500 copies/ML.</p
Systemically Circulating Viral and Tumor-Derived MicroRNAs in KSHV-Associated Malignancies
<div><p>MicroRNAs (miRNAs) are stable, small non-coding RNAs that modulate many downstream target genes. Recently, circulating miRNAs have been detected in various body fluids and within exosomes, prompting their evaluation as candidate biomarkers of diseases, especially cancer. Kaposi's sarcoma (KS) is the most common AIDS-associated cancer and remains prevalent despite Highly Active Anti-Retroviral Therapy (HAART). KS is caused by KS-associated herpesvirus (KSHV), a gamma herpesvirus also associated with Primary Effusion Lymphoma (PEL). We sought to determine the host and viral circulating miRNAs in plasma, pleural fluid or serum from patients with the KSHV-associated malignancies KS and PEL and from two mouse models of KS. Both KSHV-encoded miRNAs and host miRNAs, including members of the miR-17–92 cluster, were detectable within patient exosomes and circulating miRNA profiles from KSHV mouse models. Further characterization revealed a subset of miRNAs that seemed to be preferentially incorporated into exosomes. Gene ontology analysis of signature exosomal miRNA targets revealed several signaling pathways that are known to be important in KSHV pathogenesis. Functional analysis of endothelial cells exposed to patient-derived exosomes demonstrated enhanced cell migration and IL-6 secretion. This suggests that exosomes derived from KSHV-associated malignancies are functional and contain a distinct subset of miRNAs. These could represent candidate biomarkers of disease and may contribute to the paracrine phenotypes that are a characteristic of KS.</p></div
Exosome purification and analysis of miRNAs in sample subsets.
<p>Exosomes were purified and miRNAs isolated from exosome samples were analyzed for expression in various subsets. (A) Schematic for profiling of circulating miRNAs from plasma, serum and pleural fluid samples. (B–E) Box plots show the distribution of relative levels (CT) for 12 miRNAs for various conditions (mir-106b, mir-150, mir-16, mir-195, mir-197, mir-205, mir-23a, mir-30c, mir-425-5p, mir-548a, mir-92a, U6 snRNA). We selected those miRNAs, as they were highly expressed and as being representative of the different patterns we see across the experimental controls. Two independent experiments were performed and both replicates are shown. The line represents the median expression of microRNAs for a given sample group while individual microRNAs are denoted by closed circles (n = 24). In some cases, the median of the group is equal to 50 and the line is along the x axis due to >50% of miRNAs with a CT = 50. MiRNA expression following RNase treatment of control human plasma supernatants (B), comparison of human and mouse exosomal miRNA expression in control human plasma and mouse serum (C), differential expression in purified subsets from control human plasma (D) and tissue-specific expression (E) are shown. Asterisks denote previously detected plasma miRs <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003484#ppat.1003484-Arroyo1" target="_blank">[35]</a>.</p
GO Pathway analysis of induced oncomiR targets<sup>a</sup>.
a<p>The oncomiRs that were upregulated in the KSHV-associated sample groups were input into a microRNA target prediction database (MAMI). The predicted targets (determined with highest stringency) were used as input for the GO pathway database DAVID and the KEGG pathway terms are listed above. Asterisks denote pathways that have been previously known to be modulated by KSHV.</p>b<p>Pathways involved in cell migration.</p>c<p>The number of predicted microRNA target genes involved in each pathway.</p>d<p>P value. In addition to the predicted targets of the KSHV oncomirs, also shown are predicted targets of WNV-induced microRNAs, demonstrating the differences in pathways affected.</p>e<p>NSCLC, non-small cell lung cancer.</p>f<p>AML, acute myeloid leukemia.</p
Linear, multivariate analysis of scratch assays<sup>a</sup>.
a<p>Total number of assays n = 94.</p>b<p>Estimates relative effect of variable on fraction of closed area of the scratch after 8 hours relative to mock treatment. A negative coefficient indicates inhibition relative to control.</p>c<p>SEM, standard error of the mean.</p>d<p>Unadjusted p-value of F test for significance (p≤0.05 is considered significant.</p>e<p>Intercept term of the linear model.</p>f<p>n.s., not statistically significant.</p>g<p>Total number of independent experiments n = 9.</p>h<p>CHP, control human plasma.</p>i<p>Human IL6.</p>j<p>SN, supernatant fraction after exo quick kit.</p>k<p>Presence of Annexin V, which prevents exosome fusion.</p