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Purpose of ReviewThe basophil activation test (BAT) using flow cytometry has supplanted traditional methods of measuring basophil degranulation using histamine and other mediator release, and can be used for clinical applications as well as to explore the immune mechanisms of effector cell response to allergen. This review discusses the advancements made in clinical, diagnostic and laboratory research of allergy utilizing an ever-evolving BAT.Recent FindingsBeing an in vitro surrogate of the allergic reaction that happens in vivo in the sick patient, the BAT can be used to support the diagnosis of various allergic conditions, such as food, drug, respiratory and insect venom allergies, and the assessment of clinical response to allergen-specific immunotherapy and other immunomodulatory treatments. The BAT can also be used for research purposes to explore the mechanisms of allergy and tolerance at the level of the basophil, for instance by manipulating IgE and IgG and their receptors and by studying intracellular signalling cascade in response to allergen.SummaryThis review covers the applications of the BAT to the clinical management of allergic patients and the increased understanding of the mechanisms of immune response to allergens as well as technological advancements made in recent years.

Background. Antibody titers decrease with time following influenza vaccination, raising concerns that vaccine efficacy might wane. However, the relationship between time since vaccination and protection is unclear. Methods. Time-varying vaccine efficacy (VE[t]) was examined in healthy adult participants (age range, 18-49 years) in a placebo-controlled trial of inactivated influenza vaccine (IIV) and live-attenuated influenza vaccine (LAIV) performed during the 2007-2008 influenza season. Symptomatic respiratory illnesses were laboratory-confirmed as influenza. VE(t) was estimated by fitting a smooth function based on residuals from Cox proportional hazards models. Subjects had blood samples collected immediately prior to vaccination, 30 days after vaccination, and at the end of the influenza season for testing by hemagglutination inhibition and neuraminidase inhibition assays. Results. Overall efficacy was 70% (95% confidence interval [CI], 50%-82%) for IIV and 38% (95% CI.5%-59%) for LAIV. Statistically significant waning was detected for IIV (P = .03) but not LAIV (P = .37); however, IIV remained significantly efficacious until data became sparse at the end of the season. Similarly, antibody titers against influenza virus hemagglutinin and neuraminidase significantly decreased over the season among IIV recipients. Conclusions. Both vaccines were efficacious but LAIV less so. IIV efficacy decreased slowly over time, but the vaccine remained significantly efficacious for the majority of the season.

In an observer blind, phase 2 trial, 55 adults were randomized to receive one dose of Ad35.CS.01 vaccine followed by two doses of RTS,S/AS01 (ARR-group) or three doses of RTS,S/AS01 (RRR-group) at months 0, 1, 2 followed by controlled human malaria infection. ARR and RRR vaccine regimens were well tolerated. Efficacy of ARR and RRR groups after controlled human malaria infection was 44% (95% confidence interval 21%-60%) and 52% (25%-70%), respectively. The RRR-group had greater anti-CS specific IgG titers than did the ARR-group. There were higher numbers of CS-specific CD4 T-cells expressing > 2 cytokine/activation markers and more ex vivo IFN-γ enzyme-linked immunospots in the ARR-group than the RRR-group. Protected subjects had higher CS-specific IgG titers than non-protected subjects (geometric mean titer, 120.8 vs 51.8 EU/ml, respectively; P = .001). An increase in vaccine efficacy of ARR-group over RRR-group was not achieved. Future strategies to improve upon RTS,S-induced protection may need to utilize alternative highly immunogenic prime-boost regimens and/or additional target antigens. ClinicalTrials.gov NCT01366534.

The clinical application of IFN-gamma release assays (IGRAs) has recently improved the diagnosis of latent tuberculosis infection. In a multicenter study of the Tuberculosis Network European Trialsgroup (TBNET) we aimed to ascertain in routine clinical practice the accuracy of a novel assay using selected peptides encoded in the mycobacterial genomic region of difference (RD) 1 for the diagnosis of active tuberculosis in comparison with tuberculin skin test (TST), QuantiFERON-TB GOLD In-Tube (Cellestis Ltd., Carnegie, Australia) and T-SPOT.TB (Oxfordimmunotec, Abingdon, UK). 425 individuals from 6 different European centres were prospectively enrolled. We found that sensitivity of the novel test, TST, QuantiFERON-TB GOLD In-Tube and T-SPOT.TB was respectively 73.1%, 85.3%, 78.1%, and 85.2%; specificity was respectively 70.6%, 48.0%, 61.9% and 44.3%; positive likelihood ratios were respectively 2.48, 1.64, 2.05, and 1.53; negative likelihood ratios were respectively 0.38, 0.31, 0.35, 0.33. Sensitivity of TST combined with the novel test, QuantiFERON-TB GOLD In-Tube and T-SPOT.TB increased up to 92.4%, 97.7% and 97.1%, respectively. The likelihood ratios of combined negative results of TST with, respectively, the novel test, QuantiFERON-TB GOLD In-Tube and T-SPOT.TB were 0.19, 0.07 and 0.10. The assay based on RD1 selected peptides has similar accuracy for active tuberculosis compared with TST and commercial IGRAs. Then, independently of the spectrum of antigens used in the assays to elicit mycobacterial specific immune responses, the novel test, IGRAs, and the TST do not allow an accurate identification of active tuberculosis in clinical practice. However, the combined use of the novel assay or commercial IGRAs with TST may allow exclusion of tuberculosis.

The number of genetically defined Primary Immunodeficiency Diseases (PID) has increased exponentially, especially in the past decade. The biennial classification published by the IUIS PID expert committee is therefore quickly expanding, providing valuable information regarding the disease-causing genotypes, the immunological anomalies, and the associated clinical features of PIDs. These are grouped in eight, somewhat overlapping, categories of immune dysfunction. However, based on this immunological classification, the diagnosis of a specific PID from the clinician’s observation of an individual clinical and/or immunological phenotype remains difficult, especially for non-PID specialists. The purpose of this work is to suggest a phenotypic classification that forms the basis for diagnostic trees, leading the physician to particular groups of PIDs, starting from clinical features and combining routine immunological investigations along the way. We present 8 colored diagnostic figures that correspond to the 8 PID groups in the IUIS Classification, including all the PIDs cited in the 2011 update of the IUIS classification and most of those reported since.

In this study, we developed a portable smartphone-based diffusometry for analyzing the C-reactive protein (CRP) concentration. An optimized fluorescence microscopic add-on system for a smartphone was used to image the 300 nm fluorescent beads. Sequential nanobead images were recorded for a period and the image data were used for fluorescence correlation spectrometric (FCS) analysis. Through the analysis, the nanobeads’ diffusion coefficient was obtained. Further, the diffusion coefficients of the anti-CRP-coated nanobeads, which were suspended in the samples with various CRP concentrations, were estimated using smartphone-based diffusometry. After 10 min of reaction, the anti-CRP-coated nanobeads in a higher CRP concentration solution led to a lower diffusion coefficient. Based on the experiments, a linear sensing range of 1~8 µg/mL was found.

Background. Poor access to diagnosis stymies control of visceral leishmaniasis (VL). Antibody-detecting rapid diagnostic tests (RDTs) can be performed in peripheral health settings. However, there are many brands available and published reports of variable accuracy. Methods. Commercial VL RDTs containing bound rK39 or rKE16 antigen were evaluated using archived human sera from confirmed VL cases (n = 750) and endemic non-VL controls (n = 754) in the Indian subcontinent (ISC), Brazil, and East Africa to assess sensitivity and specificity with 95% confidence intervals. A subset of RDTs were also evaluated after 60 days' heat incubation (37°C, 45°C). Interlot and interobserver variability was assessed. Results. All test brands performed well against ISC panels (sensitivity range, 92.8%–100%; specificity range, 96%–100%); however, sensitivity was lower against Brazil and East African panels (61.5%–91% -and 36.8%–87.2%, respectively). Specificity was consistently >95% in Brazil and ranged between 90.8% and 98% in East Africa. Performance of some products was adversely affected by high temperatures. Agreement between lots and readers was good to excellent (κ > 0.73–0.99). Conclusions. Diagnostic accuracy of VL RDTs varies between the major endemic regions. Many tests performed well and showed good heat stability in the ISC; however, reduced sensitivity against Brazilian and East African panels suggests that in these regions, used alone, several RDTs are inadequate for excluding a VL diagnosis. More research is needed to assess ease of use and to compare performance using whole blood instead of serum and in patients coinfected with human immunodeficiency virus.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as ‘asthma endotypes’. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique—latent class analysis—and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

In the fecal immunological test, a suitable cut-off value may be selected to classify results as either positive or negative. Our aim is to estimate the optimal cut-off value for detecting colorectal cancer in different age and sex groups. This is a multicentric retrospective cohort study of participants in CRC screening programs with FIT between 2006 and 2012. A total of 545,505 participations were analyzed. Cancers diagnosed outside of the program were identified after a negative test result (IC_test) up until 2014. The Wilcoxon test was used to compare fecal hemoglobin levels. ROC curves were used to identify the optimal cut-off value for each age and sex group. Screening program results were estimated for different cut-off values. The results show that the Hb concentration was higher in colorectal cancer (average = 179.6μg/g) vs. false positives (average = 55.2μg/g), in IC_test (average = 3.1μg/g) vs. true negatives (average = 0μg/g), and in men (average = 166.2μg/g) vs. women (average = 140.2μg/g) with colorectal cancer. The optimal cut-off values for women were 18.3μg/g (50-59y) and 14.6μg/g (60-69y), and 16.8μg/g (50-59y) and 19.9μg/g (60-69y) for men. Using different cut-off values for each age and sex group lead to a decrease in the IC_test rate compared to the 20μg/g cut-off value (from 0.40‰ to 0.37‰) and an increase in the false positive rate (from 6.45% to 6.99%). Moreover, test sensitivity improved (90.7%), especially in men and women aged 50-59y (89.4%; 90%) and women aged 60-69y (90.2%). In conclusion, the optimal cut-off value varies for different sex and age groups and the use of an optimal cut-off value for each group improves sensitivity and leads to a small decrease in IC_tests, but also to a larger increase in false positives.

Systemic lupus erythematosus (SLE) is a heterogeneous condition characterized by a wide range of symptoms, rendering its diagnosis an often difficult task. In this article, the authors highlight the current approaches and challenges in SLE diagnosis, propose an algorithm to facilitate this process, and argue for the development of endorsed diagnostic criteria. Systemic lupus erythematosus (SLE) is a multiorgan disease with protean manifestations. Because SLE is uncommon and heterogeneous, its diagnosis can pose a considerable challenge, especially for clinicians with limited expertise of the disease. This is particularly true at the early stages of SLE, when an inadequate number of features to secure the diagnosis might be present, and for patients presenting with uncommon features, which can nonetheless be severe and require prompt treatment. Furthermore, the suboptimal performance of immunological testing in patients referred for possible SLE has been highlighted. As a result, SLE remains largely a clinical diagnosis that is made after excluding alternative diagnoses. Diagnostic criteria can expedite diagnosis and treatment, but are not available for SLE. Thus, SLE classification criteria are often used, but strict adherence to these criteria could delay diagnosis. Therefore, while eagerly awaiting diagnostic criteria for this disease, we propose interim potential solutions to facilitate its diagnosis.