Study on mitochondrial respiratory function in stored apheresis platelets using real-time energy metabolism detection technology

Objective To explore the optimal parameters for detecting mitochondrial respiratory function (MRF) in apheresis platelets (AP) using real-time energy metabolism detection technology, and to study the change of MRF in AP during storage. Methods AP samples were collected and detected for MRF using the Seahorse XF device. Multiple parameters such as AP loading concentrations, washing conditions and mitochondrial respiratory regulatory drug concentrations were adjusted. Finally, the MRF in AP stored for 1 and 5 days were studied. Results The optimal parameters for detecting MRF in AP were as follows: The loading concentration was 5×107/100 μL and basal respiration was 316±65; Basal respiration in washing group was 329±120 compared with 57±7 in unwashing group; The concentration of FCCP was 2 μmol/L. The basal respiration in AP for 1 day was 683±161, while was 140±23 for 5 days, P<0.05; The maximum respiration in AP for 1 day was 1 044±82, while was less than 200 for 5 days, P<0.05. There was a significant difference in MRF dynamic curves between the two groups. Conclusion The real-time energy metabolism detection technology was able to detect MRF in AP effectively. The MRF significantly damaged during AP storage, indicating that it may be one new mechanism of platelet storage lesion.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.13303/j.cjbt.issn.1004­549x.2024.09.008
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on mitochondrial respiratory function in stored apheresis platelets using real-time energy metabolism detection technology

SHILAP Revista de lepidopterología
Mycorrhizal Fungi and Plant Interactions
article

Study on mitochondrial respiratory function in stored apheresis platelets using real-time energy metabolism detection technology

article en

Abstract

Objective To explore the optimal parameters for detecting mitochondrial respiratory function (MRF) in apheresis platelets (AP) using real-time energy metabolism detection technology, and to study the change of MRF in AP during storage. Methods AP samples were collected and detected for MRF using the Seahorse XF device. Multiple parameters such as AP loading concentrations, washing conditions and mitochondrial respiratory regulatory drug concentrations were adjusted. Finally, the MRF in AP stored for 1 and 5 days were studied. Results The optimal parameters for detecting MRF in AP were as follows: The loading concentration was 5×107/100 μL and basal respiration was 316±65; Basal respiration in washing group was 329±120 compared with 57±7 in unwashing group; The concentration of FCCP was 2 μmol/L. The basal respiration in AP for 1 day was 683±161, while was 140±23 for 5 days, P<0.05; The maximum respiration in AP for 1 day was 1 044±82, while was less than 200 for 5 days, P<0.05. There was a significant difference in MRF dynamic curves between the two groups. Conclusion The real-time energy metabolism detection technology was able to detect MRF in AP effectively. The MRF significantly damaged during AP storage, indicating that it may be one new mechanism of platelet storage lesion.

SHILAP Revista de lepidopterología
Qingdao University (CN), Shandong University (CN), Affiliated Hospital of Qingdao University (CN)
Life below water
Openalex Percentile: Top 49%
Mycorrhizal Fungi and Plant Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.