Evidence map›Paper›PMID 26794364›Full record

ArticleMethods in enzymology2016

A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

Neela H Yennawar, Julia A Fecko, Scott A Showalter, Philip C Bevilacqua

Abstract read
In one paragraph

Article in Methods in enzymology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.8field-weighted citation impact, top 5% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. 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 at 1 institution in 1 country.

Neela H YennawarHuck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA.
Julia A FeckoHuck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA.
Scott A ShowalterHuck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA; Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania, USA; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA; Center for RNA Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA.
Philip C BevilacquaHuck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA; Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania, USA; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA; Center for RNA Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, USA. Electronic address: pcb5@psu.edu.
Pennsylvania State University · US

Funding

Coupling of structure and dynamics in RNA catalysisR01GM095923 · NIGMS · PURDUE UNIVERSITY · PI GOLDEN, BARBARA LYNN · 2011 to 2015
$1.5M
Specificity of miRNA Processing Provided by Double-Stranded RNA Binding DomainsR01GM098451 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI SHOWALTER, SCOTT A · 2011 to 2015
$1.5M
NIGMS NIH HHS R01 GM095923NIGMS NIH HHS R01-GM095923NIGMS NIH HHS R01 GM098451NIGMS NIH HHS R01-GM098451
6 · The paper itself

Abstract

Many labs have conventional calorimeters where denaturation and binding experiments are setup and run one at a time. While these systems are highly informative to biopolymer folding and ligand interaction, they require considerable manual intervention for cleaning and setup. As such, the throughput for such setups is limited typically to a few runs a day. With a large number of experimental parameters to explore including different buffers, macromolecule concentrations, temperatures, ligands, mutants, controls, replicates, and instrument tests, the need for high-throughput automated calorimeters is on the rise. Lower sample volume requirements and reduced user intervention time compared to the manual instruments have improved turnover of calorimetry experiments in a high-throughput format where 25 or more runs can be conducted per day. The cost and efforts to maintain high-throughput equipment typically demands that these instruments be housed in a multiuser core facility. We describe here the steps taken to successfully start and run an automated biological calorimetry facility at Pennsylvania State University. Scientists from various departments at Penn State including Chemistry, Biochemistry and Molecular Biology, Bioengineering, Biology, Food Science, and Chemical Engineering are benefiting from this core facility. Samples studied include proteins, nucleic acids, sugars, lipids, synthetic polymers, small molecules, natural products, and virus capsids. This facility has led to higher throughput of data, which has been leveraged into grant support, attracting new faculty hire and has led to some exciting publications.

Indexed as

CalorimetryCalorimetry, Differential ScanningCalorimetryDSCFacilityHigh throughputITC

Identifiers

PMID26794364
PMCPMC6474912
OpenAlexW2464974718

What OpenQuestion holds

Textmetadata
LicenceTDM
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.