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Record W1988796685 · doi:10.1586/ers.10.57

What’s new in asthma pathophysiology and immunopathology?

2010· review· en· W1988796685 on OpenAlexafffund
Kanami Orihara, Nyla Dil, Vidyanand Anaparti, Redwan Moqbel

Bibliographic record

VenueExpert Review of Respiratory Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsThymic stromal lymphopoietinImmunologyImmune systemMedicineInnate immune systemInflammationAcquired immune systemAsthmaContext (archaeology)VersicanChemokineExtracellular matrixBiologyCell biology

Abstract

fetched live from OpenAlex

Research on asthma pathophysiology over the past decade has expanded the complex repertoire involved in the pathophysiology of asthma to include inflammatory, immune and structural cells, as well as a wide range of mediators. Studies have identified a role for connective and other mesenchymal tissues involved in airway remodeling. Recent findings have implicated the innate immune response in asthma and have revealed interesting patterns of interaction between the innate and adaptive immune response and the associated complex chronic inflammatory reaction. New immune cell populations have also been added to this repertoire, including Tregs, natural killer T cells and Th17 cells. The role of the eosinophil, a prominent pathological feature in most asthma phenotypes, has also been expanding to include roles such as tissue modifiers and immune regulators via a number of fascinating and hitherto unexplored mechanistic pathways. In addition, new and significant roles have been proposed for airway smooth muscle cells, fibroblasts, epithelial and endothelial cells. Tissue remodeling is now considered an integral element of asthma pathophysiology. Finally, an intricate network of mediators, released from both immune and inflammatory cells, including thymus stromal lymphopoietin and matrix metalloproteinases, have added to the complex milieu of asthma immunity and inflammation. These findings have implications for therapy and the search for novel strategies towards better disease management. Sadly, and perhaps due to the complex nature of asthma, advances in therapeutic discoveries and developments have been limited. Thus, understanding the precise roles played by the numerous dramatis personae in this odyssey, both individually and collectively within the context of asthma pathophysiology, continues to pose new challenges. It is clear that the next stage in this saga is to embark on studies that transcend reductionist approaches to involve system analysis of the complex and multiple variables involved in asthma, including the need to narrow down the phenotypes of this condition based on careful analysis of the organs (lung and airways), cells, mediators and other factors involved in bronchial asthma.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.036
GPT teacher head0.384
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations31
Published2010
Admission routes2
Has abstractyes

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