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Objectives: All guidelines recommend LC-MS/MS as the analytical method of choice for the quantification of immunosuppressants in whole blood. Until now, the lack of harmonization of methods and the complexity of the analytical technique have prevented its widespread use in clinical laboratories. This can be seen in international proficiency schemes, where more than half of the participants used immunoassays. With the Cascadion SM Clinical analyzer (Thermo Fisher Scientific, Oy, Vantaa, FI) a fully automated LC-MS/MS system has been introduced, which enables the use of LC-MS/MS without being an expert in mass spectrometry.
Methods: To verify the interlaboratory comparison of the immunosuppressant assay on this type of instrument, three centers across Europe compared 1097 routine whole blood samples, each site sharing its own samples with the other two. In other experiments, the effects of freezing and thawing of whole blood samples was studied, and the use of secondary cups instead of primary tubes was assessed.
Results: In the Bland-Altman plot, the comparison of the results of tacrolimus in fresh and frozen samples had an average bias of only 0.36%. The respective data for the comparison between the primary and secondary tubes had an average bias of 1.14%. The correlation coefficients for patient samples with cyclosporine A (n=411), everolimus (n=139), sirolimus (n=114) and tacrolimus (n=433) were 0.993, 0.993, 0.993 and 0.990, respectively.
Conclusions: The outcome of this study demonstrates a new level of result harmonization for LC-MS/MS based immunosuppressant analysis with a commercially available fully automated platform for routine clinical application.
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http://dx.doi.org/10.1515/cclm-2021-1340 | DOI Listing |
Disabil Rehabil Assist Technol
September 2025
International Communication College, Jilin International Studies University, Changchun, Jilin, China.
Background: Conventional automated writing evaluation systems typically provide insufficient support for students with special needs, especially in tonal language acquisition such as Chinese, primarily because of rigid feedback mechanisms and limited customisation.
Objective: This research develops context-aware Hierarchical AI Tutor for Writing Enhancement(CHATWELL), an intelligent tutoring platform that incorporates optimised large language models to deliver instantaneous, customised, and multi-dimensional writing assistance for Chinese language learners, with special consideration for those with cognitive learning barriers.
Methods: CHATWELL employs a hierarchical AI framework with a four-tier feedback mechanism designed to accommodate diverse learning needs.
J Food Sci
September 2025
Faculty of Computing, Federal University of Uberlandia, Uberlândia, Brazil.
The coffee roasting process is a critical factor in determining the final quality of the beverage, influencing its flavour, aroma, and acidity. Traditionally, roast-level classification has relied on manual inspection, which is time-consuming, subjective, and prone to inconsistencies. However, advancements in machine learning (ML) and computer vision, particularly convolutional neural networks (CNNs), have shown great promise in automating and improving the accuracy of this process.
View Article and Find Full Text PDFMol Ecol Resour
September 2025
Centre for Evolutionary Hologenomics (CEH), Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Global efforts to standardise methodologies benefit greatly from open-source procedures that enable the generation of comparable data. Here, we present a modular, high-throughput nucleic acid extraction protocol standardised within the Earth Hologenome Initiative to generate both genomic and microbial metagenomic data from faecal samples of vertebrates. The procedure enables the purification of either RNA and DNA in separate fractions (DREX1) or as total nucleic acids (DREX2).
View Article and Find Full Text PDFCancer Rep (Hoboken)
September 2025
Jian-Zhao Yin Department of Gynecology and Wei-Feng Gao Department of Anesthesiology, Gansu Provincial Hospital, Lanzhou, Gansu, China.
Background: The existing research data cannot fully prove the advantages of single-site Da Vinci robotic surgery (RSS) compared with single-site laparoscopic surgery (LESS) in the treatment of gynecological diseases.
Aims: To evaluate the effectiveness and cost of RSS and LESS in the treatment of gynecological diseases. To provide a theoretical basis for RSS to replace LESS in the treatment of gynecological diseases.
PLoS One
September 2025
School of Medical Engineering, Xinxiang Medical University, Xinxiang, China.
Computer-aided diagnostic (CAD) systems for color fundus images play a critical role in the early detection of fundus diseases, including diabetes, hypertension, and cerebrovascular disorders. Although deep learning has substantially advanced automatic segmentation techniques in this field, several challenges persist, such as limited labeled datasets, significant structural variations in blood vessels, and persistent dataset discrepancies, which continue to hinder progress. These challenges lead to inconsistent segmentation performance, particularly for small vessels and branch regions.
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