Evaluation of immunoglobulin purification methods and their impact on quality and yield of antigen-specific antibodies

<p>Abstract</p> <p>Background</p> <p>Antibodies are the main effectors against malaria blood-stage parasites. Evaluation of functional activities in immune sera from Phase 2a/b vaccine trials may provide invaluable information in the search for immune correlates of protection. However, the presence of anti-malarial-drugs, improper collection/storage conditions or concomitant immune responses against other pathogens can contribute to non-specific anti-parasite activities when the sera/plasma are tested <it>in vitro</it>. Purification of immunoglobulin is a standard approach for reducing such non-specific background activities, but the purification method itself can alter the quality and yield of recovered Ag-specific antibodies.</p> <p>Methods</p> <p>To address this concern, various immunoglobulin (Ig) purification methods (protein G Sepharose, protein A/G Sepharose, polyethylene glycol and caprylic acid-ammonium sulphate precipitation) were evaluated for their impact on the quality, quantity and functional activity of purified rabbit and human Igs. The recovered Igs were analysed for yield and purity by SDS-PAGE, for quality by Ag-specific ELISAs (determining changes in titer, avidity and isotype distribution) and for functional activity by <it>in vitro </it>parasite growth inhibition assay (GIA).</p> <p>Results</p> <p>This comparison demonstrated that overall polyethylene glycol purification of human serum/plasma samples and protein G Sepharose purification of rabbit sera are optimal for recovering functional Ag-specific antibodies.</p> <p>Conclusion</p> <p>Consequently, critical consideration of the purification method is required to avoid selecting non-representative populations of recovered Ig, which could influence interpretations of vaccine efficacy, or affect the search for immune correlates of protection.</p

Analysis and Prediction of Translation Rate Based on Sequence and Functional Features of the mRNA

Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1) integrating various sequence-derived and functional features, (2) applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3) being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5′UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale

Haptic pop-out of movable stimuli

When, in visual and haptic search, a target is easily found among distractors, this is called a pop-out effect. The target feature is then believed to be salient, and the search is performed in a parallel way. We investigated this effect with movable stimuli in a haptic search task. The task was to find a movable ball among anchored distractors or the other way round. Results show that reaction times were independent of the number of distractors if the movable ball was the target but increased with the number of items if the anchored ball was the target. Analysis of hand movements revealed a parallel search strategy, shorter movement paths, a higher average movement speed, and a narrower direction distribution with the movable target, as compared with a more detailed search for an anchored target. Taken together, these results show that a movable object pops out between anchored objects and this indicates that movability is a salient object feature. Vibratory signals resulting from the movable ball were found to be a reasonable explanation regarding the sensation responsible for the pop-out of movability

The relation between paracetamol use and asthma:a GA2LEN European case-control study

Studies from the UK and USA suggest that frequent use of paracetamol (acetaminophen) may increase the risk of asthma, but data across Europe are lacking. As part of a multicentric case-control study organised by the Global Allergy and Asthma European Network (GA(2)LEN), it was examined whether or not frequent paracetamol use is associated with adult asthma across Europe. The network compared 521 cases with a diagnosis of asthma and reporting of asthma symptoms within the last 12 months with 507 controls with no diagnosis of asthma and no asthmatic symptoms within the last 12 months across 12 European centres. All cases and controls were selected from the same population, defined by age (2045 yrs) and place of residence. In a random effects meta-analysis, weekly use of paracetamol, compared with less frequent use, was strongly positively associated with asthma after controlling for confounders. There was no evidence for heterogeneity across centres. No association was seen between use of other analgesics and asthma. These data add to the increasing and consistent epidemiological evidence implicating frequent paracetamol use in asthma in diverse populations

Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities

Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real-time, real-world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK-air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.© 2022 The Authors. Clinical and Translational Allergy published by John Wiley and Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology

Allergen immunotherapy in MASK-air users in real-life: Results of a Bayesian mixed-effects model

Background Evidence regarding the effectiveness of allergen immunotherapy (AIT) on allergic rhinitis has been provided mostly by randomised controlled trials, with little data from real-life studies. Objective To compare the reported control of allergic rhinitis symptoms in three groups of users of the MASK-air(R) app: those receiving sublingual AIT (SLIT), those receiving subcutaneous AIT (SCIT), and those receiving no AIT. Methods We assessed the MASK-air(R) data of European users with self-reported grass pollen allergy, comparing the data reported by patients receiving SLIT, SCIT and no AIT. Outcome variables included the daily impact of allergy symptoms globally and on work (measured by visual analogue scales-VASs), and a combined symptom-medication score (CSMS). We applied Bayesian mixed-effects models, with clustering by patient, country and pollen season. Results We analysed a total of 42,756 days from 1,093 grass allergy patients, including 18,479 days of users under AIT. Compared to no AIT, SCIT was associated with similar VAS levels and CSMS. Compared to no AIT, SLIT-tablet was associated with lower values of VAS global allergy symptoms (average difference = 7.5 units out of 100; 95% credible interval [95%CrI] = -12.1;-2.8), lower VAS Work (average difference = 5.0; 95%CrI = -8.5;-1.5), and a lower CSMS (average difference = 3.7; 95%CrI = -9.3;2.2). When compared to SCIT, SLIT-tablet was associated with lower VAS global allergy symptoms (average difference = 10.2; 95%CrI = -17.2;-2.8), lower VAS Work (average difference = 7.8; 95%CrI = -15.1;0.2), and a lower CSMS (average difference = 9.3; 95%CrI = -18.5;0.2). Conclusion In patients with grass pollen allergy, SLIT-tablet, when compared to no AIT and to SCIT, is associated with lower reported symptom severity. Future longitudinal studies following internationally-harmonised standards for performing and reporting real-world data in AIT are needed to better understand its 'real-world' effectiveness

Magnetotransport in an aluminum thin film on a GaAs substrate grown by molecular beam epitaxy

Magnetotransport measurements are performed on an aluminum thin film grown on a GaAs substrate. A crossover from electron- to hole-dominant transport can be inferred from both longitudinal resistivity and Hall resistivity with increasing the perpendicular magnetic field B. Also, phenomena of localization effects can be seen at low B. By analyzing the zero-field resistivity as a function of temperature T, we show the importance of surface scattering in such a nanoscale film

DREAM4: Combining Genetic and Dynamic Information to Identify Biological Networks and Dynamical Models

Current technologies have lead to the availability of multiple genomic data types in sufficient quantity and quality to serve as a basis for automatic global network inference. Accordingly, there are currently a large variety of network inference methods that learn regulatory networks to varying degrees of detail. These methods have different strengths and weaknesses and thus can be complementary. However, combining different methods in a mutually reinforcing manner remains a challenge.We investigate how three scalable methods can be combined into a useful network inference pipeline. The first is a novel t-test-based method that relies on a comprehensive steady-state knock-out dataset to rank regulatory interactions. The remaining two are previously published mutual information and ordinary differential equation based methods (tlCLR and Inferelator 1.0, respectively) that use both time-series and steady-state data to rank regulatory interactions; the latter has the added advantage of also inferring dynamic models of gene regulation which can be used to predict the system's response to new perturbations.Our t-test based method proved powerful at ranking regulatory interactions, tying for first out of methods in the DREAM4 100-gene in-silico network inference challenge. We demonstrate complementarity between this method and the two methods that take advantage of time-series data by combining the three into a pipeline whose ability to rank regulatory interactions is markedly improved compared to either method alone. Moreover, the pipeline is able to accurately predict the response of the system to new conditions (in this case new double knock-out genetic perturbations). Our evaluation of the performance of multiple methods for network inference suggests avenues for future methods development and provides simple considerations for genomic experimental design. Our code is publicly available at http://err.bio.nyu.edu/inferelator/

Extensive Adaptive Changes Occur in the Transcriptome of Streptococcus agalactiae (Group B Streptococcus) in Response to Incubation with Human Blood

To enhance understanding of how Streptococcus agalactiae (group B streptococcus, GBS) adapts during invasive infection, we performed a whole-genome transcriptome analysis after incubation with whole human blood. Global changes occurred in the GBS transcriptome rapidly in response to blood contact following shift from growth in a rich laboratory medium. Most (83%) of the significantly altered transcripts were down-regulated after 30 minutes of incubation in blood, and all functional categories of genes were abundantly represented. We observed complex dynamic changes in the expression of transcriptional regulators and stress response genes that allow GBS to rapidly adapt to blood. The transcripts of relatively few proven virulence genes were up-regulated during the first 90 minutes. However, a key discovery was that genes encoding proteins involved in interaction with the host coagulation/fibrinolysis system and bacterial-host interactions were rapidly up-regulated. Extensive transcript changes also occurred for genes involved in carbohydrate metabolism, including multi-functional proteins and regulators putatively involved in pathogenesis. Finally, we discovered that an incubation temperature closer to that occurring in patients with severe infection and high fever (40°C) induced additional differences in the GBS transcriptome relative to normal body temperature (37°C). Taken together, the data provide extensive new information about transcriptional adaptation of GBS exposed to human blood, a crucial step during GBS pathogenesis in invasive diseases, and identify many new leads for molecular pathogenesis research