Evidence map›Paper›PMID 35058200›Full record

ArticleSLAS technology2022

Automation in arthrosis research.

Heidi Fleischer, Thomas Roddelkopf, Christoph Lutter, Andreas Büttner, Wolfram Mittelmeier, Kerstin Thurow

Abstract readComment
PubMed Publisher
In one paragraph

Article in SLAS technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 100% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Heidi FleischerInstitute of Automation, University of Rostock, Friedrich-Barnewitz-Strasse 8, 18119 Rostock, Germany. Electronic address: Heidi.Fleischer@uni-rostock.de.
Thomas RoddelkopfInstitute of Automation, University of Rostock, Friedrich-Barnewitz-Strasse 8, 18119 Rostock, Germany.
Christoph LutterDepartment of Orthopedics, University Medical Center, Rostock, Germany.
Andreas BüttnerInstitute of Legal Medicine, University Medical Center, Rostock, Germany.
Wolfram MittelmeierDepartment of Orthopedics, University Medical Center, Rostock, Germany.
Kerstin ThurowCenter for Life Science Automation (celisca), University of Rostock, Rostock, Germany.
University of Rostock · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Widespread medical studies require the analysis of suitable sample numbers to discover certain effects. Arthrosis treatment with hip and knee joint endoprostheses introduces multiple materials into the human body. Metal-containing implants may release several degradation products. Certain concentrations of chromium, cobalt, nickel, titanium and aluminum may affect multiple organs. The determination of metal concentrations in body fluids is one way to prevent severe intoxication from implants. In addition, the study of metal distribution and accumulation in individual organs will deliver extended information. In contrast to well automated high-throughput screenings, analytical measurements are mostly performed manually due to their complex process structure. A new study published in the journal Molecules presents a semi-automated sample preparation and measurement system for the determination of metals in autopsy tissue using inductively coupled plasma mass spectrometry (ICP-MS). In this auto-commentary, the main findings are highlighted and discussed.

Indexed as

Metals, HeavyOsteoarthritisRoboticsAutomationAutopsyHumansMetals, Heavy

Identifiers

PMID35058200
OpenAlexW4205218194

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.