Evidence map›Paper›PMID 25326873›Full record

ReviewJournal of pharmacokinetics and pharmacodynamics2014

A review of quantitative modeling of B cell responses to antigenic challenge.

Timothy P Hickling, Xiaoying Chen, Paolo Vicini, Satyaprakash Nayak

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of pharmacokinetics and pharmacodynamics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Timothy P HicklingPharmacokinetics, Dynamics and Metabolism - New Biological Entities, Pfizer, Andover, MA, USA.
Xiaoying Chen
Paolo Vicini
Satyaprakash Nayak

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key role of B cells in the mammalian immune response is the generation of antibodies that serve to protect the organism against antigenic challenges. The same process may also be detrimental in the context of autoimmunity. Several modeling approaches have been applied to this aspect of the immune response, from predicting potential epitopes to describing B cells progress through developmental models and simulating antibody production. Here we review some of the modeling techniques, and summarize models that describe different activation mechanisms for B cells, including T cell dependent and independent models. We focus on viral infection as a prototype system, and briefly describe case studies in other disease areas such as bacterial infection and oncology. We single out aspects of the B cell response for which there are current knowledge gaps. We outline areas in need of further research in modeling applications to ultimately produce a "B cell module" for a complete immune response model.

Indexed as

Models, ImmunologicalBacterial InfectionsB-LymphocytesHumansNeoplasmsT-LymphocytesVirus Diseases

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.