Bibliographic record
Abstract
As we take over the reins of Clinical and Experimental Allergy, we must pay tribute to Professor Graham Roberts. He has led the journal for the past 5 years, during which he carefully steered Clinical and Experimental Allergy to its more streamlined online-only format and maintained the independence and the international standing of the journal. Graham will become President of our parent organization next year, the British Society for Allergy and Clinical Immunology, and will therefore remain closely involved in the journal's growth and development. As new joint Editors in Chief, we will focus our efforts in the coming months on providing a rapid, high-quality author experience and increasing the impact of the journal. We will be refreshing the Editorial Board and are keen to hear from enthusiastic researchers and peer reviewers in allergy who would like to contribute to the journal in this way—please do get in touch if you would like to be considered for Editorial Board membership. This first issue of Clinical and Experimental Allergy under our leadership is thought-provoking. A Nobel prize in allergy is waiting for the group that discover why some people develop allergies and others not, or more specifically, why allergic conditions appear to be more common in urban, industrialized settings than some rural farming communities. John Gerrard and colleagues first reported the inverse relationship between microbial exposures and risk of allergic disease in a study of Saskatchewan communities in 1976.1 In over 40 years of subsequent research on this relationship, there has been a singular failure to identify the magic bullet that might account for the observed association between urban living conditions and a high prevalence of allergic disease. The discovery of key genetic variants such as filaggrin mutations which predispose to allergic conditions has given us clues about the mechanisms underlying allergy development, and the epidemiology has contributed useful insights, but translating research findings into a public health approach to reduce the population burden of allergy through primary prevention is proving difficult. In this month's issue of Clinical and Experimental Allergy, three groups present interesting new insights into the origins of allergic conditions. First, a large case–control study from the Medical Research Council unit in Uganda identifies commonalities and overlap in risk factors for allergic conditions in school children.2 The risk factors are mostly familiar—urban living, family history and a potential protective effect of worms which the group has published on previously.3 Perhaps more importantly, and consistent with some of the work from the International Study of Asthma and Allergies in Childhood, the data suggest the possibility of common risk factors across allergic diseases. Food allergy was not evaluated in this new study by Mpairwe and colleagues, but recent work in South Africa suggests that urban living is also a risk factor for food allergy.4 The importance of identifying the key causative factor(s) behind the link between urban living and allergic conditions can hardly be overstated—the epidemiology suggests allergy is preventable. However, we do not yet know how to achieve primary prevention, beyond the allergen-specific approach of oral tolerance induction for specific food allergies. Further insights into oral tolerance are provided by an analysis of the Japanese Environment and Children's cohort study. This large dataset provides an opportunity to explore the aetiology of less common forms of allergic disease, and Tezuka and colleagues have addressed the issue of oral tolerance induction to prevent cow's milk allergy.5 While some assume that oral tolerance will be as effective for preventing milk allergy as it seems to be for egg and peanut allergy, the data are still insufficient to confirm this.6 Human exposure to cow's milk is very different to egg or peanut during infancy—in Europe, and North America first exposure to cow's milk often occurs very early, in a high volume, highly processed form as infant formula. In the original description of oral tolerance, Gideon Wells noted that the neonatal period (in humans, the first month of life) is one where oral tolerance induction works less well than exposures during later infancy.7 Tezuka's study is probably the most extensive cohort study evaluating the relationship between the use of cow's milk-based infant formula and allergy to cow's milk. They found reduced cow's milk allergy at age 12 months in infants who were exposed to regular cow's milk formula in the first months of life, supporting the possibility of oral tolerance induction for cow's milk, despite differences in exposure patterns and allergen processing compared with egg or peanut. We should be cautious about making causal inferences from this observational dataset and clinical trial data are clearly needed. As the authors acknowledge, it would be a mistake to use this information to promote cow's milk formula feeding over alternatives, since low breastfeeding rates already present a major global public health challenge.8 Finally, Feng and colleagues explore the potential role of vitamin D deficiency in the aetiology of allergic conditions—in their case, they evaluated rhinitis and allergic sensitization.9 Feng's consortium used Mendelian randomization to evaluate the potential role of vitamin D. This is a technique which takes advantage of knowledge about genetic variations linked with health outcomes to make causal inferences from observational datasets. They evaluated polymorphisms associated with vitamin D status in a large dataset, including just under 300,000 people with confirmed allergic rhinitis—and found no support for the hypothesis that vitamin D may potentially prevent allergic conditions. This is consistent with clinical trial evidence in the field of asthma and other allergic conditions, which has so far failed to support a link between vitamin D supplementation and disease development.10 Another promising candidate for primary prevention of allergy disappoints. This is, however, an exciting time for allergy research, with significant challenges needing to be addressed and innovative new scientific approaches available to tackle them, in laboratories, clinics and communities. We very much look forward to sharing novel and impactful allergy research findings with you through the pages of Clinical and Experimental Allergy in the coming years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".