When non-salient information becomes salient in conversational memory: Collaboration shapes the effects of emotion and self-production

International audiencePeople’s memory of what was said and who said what during dialogue plays a central role in mutual comprehension and subsequent adaptation. This article outlines that well-established effects in conversational memory such as the self-production and the emotional effects actually depend on the nature of the interaction. We specifically focus on the impact of the collaborative nature of the interaction, comparing participants’ conversational memory in non-collaborative and collaborative interactive settings involving interactions between two people (i.e., dialogue). The findings reveal that the amplitude of these conversational memory effects depends on the collaborative vs. non-collaborative nature of the interaction. The effects are attenuated when people have the opportunity to collaborate because information that remained non-salient in the non-collaborative condition (neutral and partner-produced words) became salient in the collaborative condition to a level similar to otherwise salient information (emotional and self-produced words). We highlight the importance of these findings in the study of dialogue and conversational memory

Fluorescent bead-based serological detection of Toxoplasma gondii infection in chickens

International audienceBackground: Free-ranging chickens are often infected with Toxoplasma gondii and seroconvert upon infection. This indicates environmental contamination with T. gondii. Methods: Here, we established a bead-based multiplex assay (BBMA) using the Luminex technology for the detection of T. gondii infections in chickens. Recombinant biotinylated T. gondii surface antigen 1 (TgSAG1 bio) bound to streptavidin-conjugated magnetic Luminex beads served as antigen. Serum antibodies were detected by a fluorophore-coupled secondary antibody. Beads of differing color codes were conjugated with anti-chicken IgY or chicken serum albumin and served for each sample as an internal positive or negative control, respectively. The assay was validated with sera from experimentally and naturally infected chickens. The results were compared to those from reference methods, including other serological tests, PCRs and bioassay in mice. Results: In experimentally infected chickens, the vast majority (98.5%, n = 65/66) of birds tested seropositive in the BBMA. This included all chickens positive by magnetic-capture PCR (100%, n = 45/45). Most, but not all inoculated and TgSAG1 bio-BBMA-positive chickens were also positive in two previously established TgSAG1-ELISAs (TgSAG1-ELISA SL , n = 61/65; or TgSAG1-ELISA SH , n = 60/65), or positive in an immunofluorescence assay (IFAT, n = 64/65) and in a modified agglutination test (MAT, n = 61/65). All non-inoculated control animals (n = 28/28, 100%) tested negative. In naturally exposed chickens, the TgSAG1 bio-BBMA showed a high sensitivity (98.5%; 95% confidence interval, CI: 90.7-99.9%) and specificity (100%; 95% CI: 85.0-100%) relative to a reference standard established using ELISA, IFAT and MAT. Almost all naturally exposed chickens that were positive in bioassay or by PCR tested positive in the TgSAG1 bio-BBMA (93.5%; 95% CI: 77.1-98.9%), while all bioassay-or PCR-negative chickens remained negative (100%; 95% CI: 85.0-100%). Conclusions: The TgSAG1 bio-BBMA represents a suitable method for the detection of T. gondii infections in chickens with high sensitivity and specificity, which is comparable or even superior to other tests. Since assays based on this methodology allow for the simultaneous analysis of a single biological sample with respect to multiple analytes, the described assay may represent a component in future multiplex assays for broad serological monitoring of poultry and other farm animals for various pathogens

Conducting active screening for human African trypanosomiasis with rapid diagnostic tests: The Guinean experience (2016–2021)

International audienceStrategies to detect Human African Trypanosomiasis (HAT) cases rely on serological screening of populations exposed to trypanosomes. In Guinea, mass medical screening surveys performed with the Card Agglutination Test for Trypanosomiasis have been progressively replaced by door-to-door approaches using Rapid Diagnostic Tests (RDTs) since 2016. However, RDTs availability represents a major concern and medical teams must often adapt, even in the absence of prior RDT performance evaluation. For the last 5 years, the Guinean HAT National Control Program had to combine three different RDTs according to their availability and price: the SD Bioline HAT (not available anymore), the HAT Sero-K-SeT (most expensive), and recently the Abbott Bioline HAT 2.0 (limited field evaluation). Here, we assess the performance of these RDTs, alone or in different combinations, through the analysis of both prospective and retrospective data. A parallel assessment showed a higher positivity rate of Abbott Bioline HAT 2.0 (6.0%, n = 2,250) as compared to HAT Sero-K-SeT (1.9%), with a combined positive predictive value (PPV) of 20.0%. However, an evaluation of Abbott Bioline HAT 2.0 alone revealed a low PPV of 3.9% (n = 6,930) which was surpassed when using Abbott Bioline HAT 2.0 in first line and HAT Sero-K-SeT as a secondary test before confirmation, with a combined PPV reaching 44.4%. A retrospective evaluation of all 3 RDTs was then conducted on 189 plasma samples from the HAT-NCP biobank, confirming the higher sensitivity (94.0% [85.6–97.7%]) and lower specificity (83.6% [76.0–89.1%]) of Abbott Bioline HAT 2.0 as compared to SD Bioline HAT (Se 64.2% [52.2–74.6%]—Sp 98.4% [94.2–99.5%]) and HAT Sero-K-SeT (Se 88.1% [78.2–93.8%]—Sp 98.4% [94.2–99.5%]). A comparison of Abbott Bioline HAT 2.0 and malaria-RDT positivity rates on 479 subjects living in HAT-free malaria-endemic areas further revealed that a significantly higher proportion of subjects positive in Abbott Bioline HAT 2.0 were also positive in malaria-RDT, suggesting a possible cross-reaction of Abbott Bioline HAT 2.0 with malaria-related biological factors in about 10% of malaria cases. This would explain, at least in part, the limited specificity of Abbott Bioline HAT 2.0. Overall, Abbott Bioline HAT 2.0 seems suitable as first line RDT in combination with a second HAT RDT to prevent confirmatory lab overload and loss of suspects during referral for confirmation. A state-of-the-art prospective comparative study is further required for comparing all current and future HAT RDTs to propose an optimal combination of RDTs for door-to-door active screening

Map of the HAT foci in Guinea.

Endemic transmission foci in red, old foci with last cases reported before 2004 in orange, zones at risk in yellow, Atlantic Ocean in blue. This map was elaborated in-house with QGIS 3.28.12 from an OSM standard layer (www.openstreetmap.org).</p

Usage and performance of Coris HAT Sero-K-SeT for D2D active screening in Guinea from 2019 to 2021.

Usage and performance of Coris HAT Sero-K-SeT for D2D active screening in Guinea from 2019 to 2021.</p

False positive results with Abbott Bioline HAT 2.0 in malaria-RDT negative vs. positive subjects in Friah (Local Health Center, September 2021) and Conakry (Saint Gabriel Dispensary, October-November 2021).

False positive results with Abbott Bioline HAT 2.0 in malaria-RDT negative vs. positive subjects in Friah (Local Health Center, September 2021) and Conakry (Saint Gabriel Dispensary, October-November 2021).</p

Comparison of the sensitivity and specificity of HAT RDTs on frozen plasma samples from the HAT-NCP biobank (2017–2020) as compared to the initial parasitological diagnostic by mAECT and/or direct examination of lymph node aspirates.

Comparison of the sensitivity and specificity of HAT RDTs on frozen plasma samples from the HAT-NCP biobank (2017–2020) as compared to the initial parasitological diagnostic by mAECT and/or direct examination of lymph node aspirates.</p

Usage and performance of Abbott Bioline HAT 2.0 for D2D active screening in Guinea in 2021.

Usage and performance of Abbott Bioline HAT 2.0 for D2D active screening in Guinea in 2021.</p

Usage of the different HAT-RDTs for door-to-door active medical surveys from 2016 to 2021 in Guinea.

The evolution of the total annual number of HAT cases detected by both passive and active surveillance is shown on the upper graph. Different strategies have been successively implemented according to the availability and cost of the different RDTs. From 2016 to 2018, SD Bioline HAT was applied (details in Table 1). From 2019 to mid-2021, HAT Sero-K-SeT was used either alone, or in combination with SD Bioline HAT then with Abbott Bioline HAT 2.0 (details Table 2). From mid-2021 to date, Abbott Bioline HAT 2.0 was applied alone, then with HAT Sero-K-SeT used as secondary test (details in Table 3). The positivity rates (number of positive RDTs / number of screened individuals) were only calculated for RDTs used as first line tests. The Positive Predictive Values (PPVs) were calculated by combining results from primary and secondary RDTs.</p