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Abstract Background Breastfeeding is a leading cause of infant HIV-1 infection in the developing world, yet only a minority of infants exposed to HIV-1 via breastfeeding become infected. As a genetic bottleneck severely restricts the number of postnatally-transmitted variants, genetic or phenotypic properties of the virus Envelope (Env) could be important for the establishment of infant infection. We examined the efficiency of virologic functions required for initiation of infection in the gastrointestinal tract and the neutralization sensitivity of HIV-1 Env variants isolated from milk of three postnatally-transmitting mothers (n=13 viruses), five clinically-matched nontransmitting mothers (n=16 viruses), and seven postnatally-infected infants (n = 7 postnatally-transmitted/founder (T/F) viruses). Results There was no difference in the efficiency of epithelial cell interactions between Env virus variants from the breast milk of transmitting and nontransmitting mothers. Moreover, there was similar efficiency of DC-mediated trans-infection, CCR5-usage, target cell fusion, and infectivity between HIV-1 Env-pseudoviruses from nontransmitting mothers and postnatal T/F viruses. Milk Env-pseudoviruses were generally sensitive to neutralization by autologous maternal plasma and resistant to breast milk neutralization. Infant T/F Env-pseudoviruses were equally sensitive to neutralization by broadly-neutralizing monoclonal and polyclonal antibodies as compared to nontransmitted breast milk Env variants. Conclusion Postnatally-T/F Env variants do not appear to possess a superior ability to interact with and cross a mucosal barrier or an exceptional resistance to neutralization that define their capability to initiate infection across the infant gastrointestinal tract in the setting of preexisting maternal antibodies.

Despite significant progress in vaccine research, the level of protection provided by vaccination can vary significantly across individuals. As a result, understanding immunologic variation across individuals in response to vaccination is important for developing next-generation efficacious vaccines. Accurate outcome prediction and identification of predictive biomarkers would represent a significant step towards this goal. Moreover, in early phase vaccine clinical trials, small datasets are prevalent, raising the need and challenge of building a robust and explainable prediction model that can reveal heterogeneity in small datasets. We propose a new model named Generative Mixture of Logistic Regression (GeM-LR), which combines characteristics of both a generative and a discriminative model. In addition, we propose a set of model selection strategies to enhance the robustness and interpretability of the model. GeM-LR extends a linear classifier to a non-linear classifier without losing interpretability and empowers the notion of predictive clustering for characterizing data heterogeneity in connection with the outcome variable. We demonstrate the strengths and utility of GeM-LR by applying it to data from several studies. GeM-LR achieves better prediction results than other popular methods while providing interpretations at different levels. Author summary: Vaccines have proven to be a powerful tool in preventing infectious diseases, yet their effectiveness can vary significantly from person to person. This variability underscores the need for a better understanding of how individuals' immune systems respond to vaccination, which is essential for achieving successful immunization across a broader population. In our study, we introduce a new model called the Generative Mixture of Logistic Regression (GeM-LR) to predict vaccine effectiveness in different individuals. This model is particularly beneficial when only small datasets are available, a common challenge in vaccine research, whereas many advanced machine learning methods require large training datasets. GeM-LR integrates mixture modeling and logistic regression to provide more accurate predictions while also offering insights into the factors that contribute to varying vaccine responses among individuals. We demonstrate that our model outperforms other standard methods in terms of accuracy and enhances the understanding of data for future research. Our innovative approach holds great promise for improving vaccine development. By revealing hidden patterns within small datasets, GeM-LR aims to make vaccine research more efficient and impactful. [ABSTRACT FROM AUTHOR]

Authorization of the Matrix-M (MM)–adjuvanted R21 vaccine by three countries and its subsequent endorsement by the World Health Organization for malaria prevention in children are a milestone in the fight against malaria. Yet, our understanding of the innate and adaptive immune responses elicited by this vaccine remains limited. Here, we compared three clinically relevant adjuvants [3M-052 + aluminum hydroxide (Alum) (3M), a TLR7/8 agonist formulated in Alum; GLA-LSQ, a TLR4 agonist formulated in liposomes with QS-21; and MM, the now-approved adjuvant for R21] for their capacity to induce durable immune responses to R21 in macaques. R21 adjuvanted with 3M on a 0, 8, and 23–week schedule elicited anti-circumsporozoite antibody responses comparable in magnitude to the R21/MM vaccine administered using a 0-4-8–week regimen and persisted up to 72 weeks with a half-life of 337 days. A booster dose at 72 weeks induced a recall response similar to the R21/MM vaccination. In contrast, R21/GLA-LSQ immunization induced a lower, short-lived response at the dose used. Consistent with the durable serum antibody responses, MM and 3M induced long-lived plasma cells in the bone marrow and other tissues, including the spleen. Furthermore, whereas 3M stimulated potent and persistent antiviral transcriptional and cytokine signatures after primary and booster immunizations, MM induced enhanced expression of interferon- and TH2-related signatures more highly after the booster vaccination. Collectively, these findings provide a resource on the immune responses of three clinically relevant adjuvants with R21 and highlight the promise of 3M as another adjuvant for malarial vaccines. Editor's summary: Most vaccines based on recombinant antigens rely on coadministration with an adjuvant to elicit a robust immune response. Although adjuvants are needed for many vaccines, it is less clear which adjuvant(s) should be paired with each immunogen. In two papers, Bechtold et al. and Arunachalam et al. performed comparative analyses to assess the effect of different adjuvants on the immune response. Bechtold et al. showed that an AS01-adjuvanted hepatitis B virus vaccine, which induces robust CD4+ T cell responses against the vaccine antigen, also elicited trained immunity in human recipients, which was not observed in an alum-adjuvanted vaccine. Arunachalam et al. found that Matrix-M and 3M-052 + aluminum hydroxide (Alum) adjuvantation induced robust immune responses to the R21 malaria vaccine in nonhuman primates, but a third comparator, GLA-LSQ, elicited a lower magnitude of response that was short lived. Although Matrix-M and 3M-052 + Alum induced robust and durable antibody responses, they elicited distinct innate immune responses, demonstrating that multiple innate immune mechanisms can program durable vaccine-induced immunity. These head-to-head comparisons in both humans and nonhuman primates demonstrate that selecting an adjuvant should be done carefully and that different adjuvants have distinct effects on both innate and adaptive immunity. —Courtney Malo [ABSTRACT FROM AUTHOR]

Rapid detection of biologicals is important for a range of applications such as medical screening and diagnostics. Antibodies are typically employed for biosensing with high sensitivity and selectivity but can take months to prepare. Here, we investigate electropolymerized molecularly imprinted polymers (E-MIPs), which are produced in minutes as alternative-antibody rapid biosensors for the selective recognition of model proteins bovine haemoglobin (BHb) and bovine serum albumin (BSA). We evaluated two disposable screen-printed electrodes (SPE) designated AT-Au and BT-Au based on their different annealing temperatures. E-MIPs for BHb demonstrated an imprinting factor of 146 : 1 at 1 nM and 12 : 1 at 0.1 nM, showing high effectiveness of E-MIPs compared to their control non-imprinted polymers. The BHb imprinted E-MIP, when tested against BSA as a non-target protein, gave a selectivity factor of 6 : 1 for BHb. Sensor sensitivity directly depended on the nature of the SPE, with AT-Au SPE demonstrating limits of detection in the sub-micromolar range typically achieved for MIPs, while BT-Au SPE exhibited sensitivity in the sub-nanomolar range for target protein. We attribute this to differences in electrode surface area between AT-Au and BT-Au SPEs. The E-MIPs were also tested in calf serum as a model biological medium. The BT-Au SPE MIPs detected the presence of target protein in <10 min with an LOD of 50 pM and LOQ of 100 pM, suggesting their suitability for protein determination in serum with minimal sample preparation. Using electrochemical impedance spectroscopy, we determine equilibrium dissociation constants (KD) for E-MIPs using the Hill–Langmuir adsorption model. KD of BHb E-MIP was determined to be 0.86 ± 0.11 nM. [ABSTRACT FROM AUTHOR]

This study compared four methods for setting item response time thresholds to differentiate rapid-guessing behavior from solution behavior. Thresholds were either (a) common for all test items, (b) based on item surface features such as the amount of reading required, (c) based on visually inspecting response time frequency distributions, or (d) statistically estimated using a two-state mixture model. The thresholds were compared using the criteria proposed by Wise and Kong to establish the reliability and validity of response time effort scores, which were generated on the basis of the specified threshold values. The four methods yielded very similar results, indicating that response time effort is not very sensitive to the particular threshold identification method used. Recommendations are given regarding use of the various methods. (Contains 5 tables and 1 figure.)

Accountability for educational quality is a priority at all levels of education. Low-stakes testing is one way to measure the quality of education that students receive and make inferences about what students know and can do. Aggregate test scores from low-stakes testing programs are suspect, however, to the degree that these scores are influenced by low test-taker effort. This study examined the generalizability of a recently developed technique called motivation filtering, whereby scores for students of low motivation are systemically filtered from test data to determine aggregate test scores that more accurately reflect student performance and that can be used for reporting purposes. Across assessment tests in five different content areas, motivation filtering was found to consistently increase mean test performance and convergent validity.

The attractiveness of computer-based tests (CBTs) is due largely to their capability to expand the ways we conduct testing. A relatively unexplored application, however, is actively using the computer to reduce construct-irrelevant variance while a test is being administered. This investigation introduces the effort-monitoring CBT, in which the computer monitors examinee effort (based on item response time) in a low-stakes test and displays warning messages to those exhibiting rapid-guessing behavior. The results of an experimental study are presented, which showed that an effort-monitoring CBT increased examinee effort and yielded more valid test scores than a conventional CBT. Thus, unlike previous research that has focused on identifying rapid-guessing behavior after it has occurred, the effort-monitoring CBT proactively attempts to suppress rapid-guessing behavior. This innovative testing procedure extends the capabilities of measurement practitioners to manage the psychometric challenges posed by unmotivated examinees.

With the continual progress of computer technologies, computer automated scoring (CAS) has become a popular tool for evaluating writing assessments. Research of applications of these methodologies to new types of performance assessments is still emerging. While research has generally shown a high agreement of CAS system generated scores with those produced by human raters, concerns and questions have been raised about appropriate analyses and validity of decisions/interpretations based on those scores. In this paper we expand the emerging discussions on validation strategies on CAS by illustrating several analyses can be accomplished with available data. These analyses compare the degree to which two CAS systems accurately score data from a structured interview using the original scores provided by human raters as the criterion. Results suggest key differences across the two systems as well as differences in the statistical procedures used to evaluate them. The use of several statistical and qualitative analyses is recommended for evaluating contemporary CAS systems. (Contains 10 tables and 2 footnotes.)