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Record W1755519748 · doi:10.1093/cid/civ615

T-Cell Therapy: Options for Infectious Diseases: Table 1.

2015· review· en· W1755519748 on OpenAlexaff
Shreemanta K. Parida, Thomas Poiret, Qingda Meng, Jan Heyckendorf, Christoph Lange, Aditya Ambati, Martin Rao, Davide Valentini, Giovanni Ferrara, Elena Rangelova, Ernest Dodoo, Alimuddin Zumla, Markus Maeurer

Bibliographic record

VenueClinical Infectious Diseases · 2015
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsInstitute of Infection and Immunity
FundersMedical Research CouncilUBS Optimus FoundationEuropean and Developing Countries Clinical Trials PartnershipEuropean Commission
KeywordsMedicineTable (database)Infectious disease (medical specialty)Intensive care medicineVirologyInternal medicineDiseaseData mining

Abstract

fetched live from OpenAlex

The emergence of drug-resistant tuberculosis is challenging tuberculosis control worldwide. In the absence of an effective vaccine to prevent primary infection with Mycobacterium tuberculosis and tuberculosis disease, host-directed therapies may offer therapeutic options, particularly for patients with multidrug-resistant and extensively drug-resistant tuberculosis where prognosis is often limited. CD8(+) and CD4(+) T cells mediate antigen-specific adaptive cellular immune responses. Their use in precision immunotherapy in clinical conditions, especially in treating cancer as well as for prevention of life-threatening viral infections in allogeneic transplant recipients, demonstrated safety and clinical efficacy. We review key achievements in T-cell therapy, including the use of recombinant immune recognition molecules (eg, T-cell receptors and CD19 chimeric antigen receptors), and discuss its potential in the clinical management of patients with drug-resistant and refractory tuberculosis failing conventional therapy.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
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)0.0030.001

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 head0.170
GPT teacher head0.485
Teacher spread0.316 · 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 designNot applicable
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

Citations48
Published2015
Admission routes1
Has abstractyes

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