Plasmodium falciparum Infection Does Not Affect Human Immunodeficiency Virus Viral Load in Coinfected Rwandan Adults

Background: Plasmodium falciparum infection has been reported to increase human immunodeficiency virus (HIV) viral load (VL), which can facilitate HIV transmission. We prospectively studied the impact of mild P falciparum coinfection on HIV VL in Rwanda. Methods: We measured plasma HIV VL at presentation with malaria infection and weekly for 4 weeks after artemether-lumefantrine treatment in Rwandan adults infected with HIV with P falciparum malaria. Regression analyses were used to examine associations between malaria infection and HIV VL changes. Samples with detectable virus underwent genotypic drug-resistance testing. Results: We enrolled 28 HIV-malaria coinfected patients and observed 27 of them for 5 weeks. Three patients (11%) were newly diagnosed with HIV. Acute P falciparum infection had no significant effect on HIV VL slope over 28 days of follow-up. Ten patients with VL <40 copies/mL at enrollment maintained viral suppression throughout. Seventeen patients had a detectable VL at enrollment including 9 (53%) who reported 100% adherence to ARVs; 3 of these had detectable genotypic drug resistance. Conclusions: Unlike studies from highly malaria-endemic areas, we did not identify an effect of P falciparum infection on HIV VL; therefore, malaria is not likely to increase HIV-transmission risk in our setting. However, routine HIV testing should be offered to adults presenting with acute malaria in Rwanda. Most importantly, we identified a large percentage of patients with detectable HIV VL despite antiretroviral (ARV) therapy. Some of these patients had HIV genotypic drug resistance. Larger studies are needed to define the prevalence and factors associated with detectable HIV VL in patients prescribed ARVs in Rwanda

Social Salience and the Sociolinguistic Monitor: A Case Study of ING and TH-fronting in Britain

This article examines the role of social salience, or the relative ability of a linguistic variable to evoke social meaning, in structuring listeners’ perceptions of quantitative sociolinguistic distributions. Building on the foundational work of Labov et al. (2006, 2011) on the “sociolinguistic monitor” (a proposed cognitive mechanism responsible for sociolinguistic perception), we examine whether listeners’ evaluative judgments of speech change as a function of the type of variable presented. We consider two variables in British English, ING and TH-fronting, which we argue differ in their relative social salience. Replicating the design of Labov et al.’s studies, we test 149 British listeners’ reactions to different quantitative distributions of these variables. Our experiments elicit a very different pattern of perceptual responses than those reported previously. In particular, our results suggest that a variable’s social salience determines both whether and how it is perceptually evaluated. We argue that this finding is crucial for understanding how sociolinguistic information is cognitively processed

CONNECT for quality: protocol of a cluster randomized controlled trial to improve fall prevention in nursing homes

<p>Abstract</p> <p>Background</p> <p>Quality improvement (QI) programs focused on mastery of content by individual staff members are the current standard to improve resident outcomes in nursing homes. However, complexity science suggests that learning is a social process that occurs within the context of relationships and interactions among individuals. Thus, QI programs will not result in optimal changes in staff behavior unless the context for social learning is present. Accordingly, we developed CONNECT, an intervention to foster systematic use of management practices, which we propose will enhance effectiveness of a nursing home Falls QI program by strengthening the staff-to-staff interactions necessary for clinical problem-solving about complex problems such as falls. The study aims are to compare the impact of the CONNECT intervention, plus a falls reduction QI intervention (CONNECT + FALLS), to the falls reduction QI intervention alone (FALLS), on fall-related process measures, fall rates, and staff interaction measures.</p> <p>Methods/design</p> <p>Sixteen nursing homes will be randomized to one of two study arms, CONNECT + FALLS or FALLS alone. Subjects (staff and residents) are clustered within nursing homes because the intervention addresses social processes and thus must be delivered within the social context, rather than to individuals. Nursing homes randomized to CONNECT + FALLS will receive three months of CONNECT first, followed by three months of FALLS. Nursing homes randomized to FALLS alone receive three months of FALLs QI and are offered CONNECT after data collection is completed. Complexity science measures, which reflect staff perceptions of communication, safety climate, and care quality, will be collected from staff at baseline, three months after, and six months after baseline to evaluate immediate and sustained impacts. FALLS measures including quality indicators (process measures) and fall rates will be collected for the six months prior to baseline and the six months after the end of the intervention. Analysis will use a three-level mixed model.</p> <p>Discussion</p> <p>By focusing on improving local interactions, CONNECT is expected to maximize staff's ability to implement content learned in a falls QI program and integrate it into knowledge and action. Our previous pilot work shows that CONNECT is feasible, acceptable and appropriate.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00636675">NCT00636675</a></p

Comparison of antibody breadth and magnitude between HIV+ and HIV- samples for the P. falciparum antigens displaying the greatest breadth of antibody reactivity in HIV+ samples.

<p>Frequency of detection in percent of samples by HIV status is reported. Significant differences in breadth are denoted by *, using Fisher exact test (two tailed, p value <0.05). Significant differences in antibody magnitude are denoted by **, and reported using the Empirical Bayes Moderated t-test, p<0.05, and an absolute log fold change > 1.</p><p>Comparison of antibody breadth and magnitude between HIV+ and HIV- samples for the P. falciparum antigens displaying the greatest breadth of antibody reactivity in HIV+ samples.</p

B cell subset analysis of HIV+ (n = 14) and HIV- (n = 21) subjects at the time of symptomatic malaria.

<p>The B cell subsets were determined by flow cytometry: naïve cells (CD19+CD10-CD21+CD27-), activated MBCs/plasmablasts (CD19+CD10-CD21-CD27+), classical MBCs (CD19+CD10-CD21+CD27+) and atypical MBCs (CD19+CD10-CD21-CD27-). The black bar denotes median values. The frequency was determined as percent of total CD19+ B cells. The Mann Whitney rank-sum test was used to compare variables between groups.</p

Demographics and clinical characteristics of the HIV positive (HIV+) and HIV negative (HIV-) malaria infected patients.

<p>P-values were generated using Mann-Whitney test for continuous variables and the Chi-square test for gender. Median and interquartile values are reported.</p><p>Demographics and clinical characteristics of the HIV positive (HIV+) and HIV negative (HIV-) malaria infected patients.</p

Number of reactive antibodies per sample in the HIV+ group by HIV viral load and CD4+ T cell count.

<p>The four samples with the highest antibody breadth all have CD4⁺ T cell counts >500 cells/μl and low viral loads. Dotted line denotes HIV viral load limit of detection.</p

Breadth and magnitude of the IgG response to <i>P</i>. <i>falciparum</i> antigens by HIV status.

<p>(A) A microarray containing 824 <i>P</i>. <i>falciparum</i> proteins or protein fragments was probed with plasma samples from HIV+ (n = 18) and HIV- (n = 18) adults during symptomatic malaria. A. Venn diagrams showing the number of reactive antigens among HIV+ subjects (orange), HIV- subjects (blue), both HIV+ and HIV- subjects (purple) or neither (254). (B) Antibody breadth of HIV+ individuals (mean 83 antigens) and HIV- individuals (mean 208 antigens). Mean values and standard deviations are shown; Significant differences in breadth (Negative Binomial generalized linear model) (C) Magnitude of <i>P</i>. <i>falciparum</i> IgG responses by HIV status. We examined 384 antigens that were recognized in ≥ 10% of all samples and show the average IgG reactivity of each by HIV status. IgG reactivity is significantly higher in HIV- group (blue bars) compared to HIV+ group (orange bars) for 173 antigens. The red horizontal line indicates a p value of 0.05. (Empirical Bayes Moderated t-test, p<0.05, and an absolute log fold change > 1).</p