MétaCan
Menu
Back to cohort
Record W1996872181 · doi:10.1097/aci.0000000000000010

Human primary immunodeficiencies causing defects in innate immunity

2013· review· en· W1996872181 on OpenAlexafffund
Tiffany Wong, Joanne Yeung, Kyla J. Hildebrand, Anne Junker, Stuart E. Turvey

Bibliographic record

VenueCurrent Opinion in Allergy and Clinical Immunology · 2013
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversity of British ColumbiaChild and Family Research Institute
FundersCanadian Institutes of Health Research
KeywordsInnate immune systemMedicineContext (archaeology)ImmunologyPrimary immunodeficiencyIntrinsic immunityAcquired immune systemImmune systemBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: There have been exciting recent advances in identifying new mutations that cause human primary immunodeficiencies which impact innate immune defences. In this review, we will highlight the most important and influential advances published in the last 18 months related to the defects of the innate immune system. We will also provide clinical context to facilitate the incorporation of these discoveries into clinical practice. RECENT FINDINGS: We will specifically focus on three areas that have seen recent significant advances: defects in Toll-like receptor signalling that enhance susceptibility to viral infection, particularly herpes simplex encephalitis; defects in innate immunity that impact phagocyte function predisposing to mycobacterial infection; and the discovery of genes responsible for isolated congenital asplenia. SUMMARY: The field of innate immunodeficiency has benefited greatly from the recent improvements in genome sequencing technology and has advanced dramatically in the last 18 months. For clinicians confronted with patients with suspected innate immunodeficiency, these new discoveries not only increase the likelihood that a patient will receive a specific molecular diagnosis and tailored therapy, but also add significant complexity to the diagnostic workup. Future challenges will include identifying accurate, cost-effective diagnostic approaches to these novel immunodeficiencies, so these impressive advances in our understanding of innate immunity can be translated into improved health outcomes for our affected patients and their families.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.109
GPT teacher head0.398
Teacher spread0.289 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCurrent Opinion in Allergy and Clinical ImmunologySame topicImmunodeficiency and Autoimmune DisordersFrench-language works237,207