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Background: For patients who treated with tacrolimus after kidney transplant, therapeutic drug monitoring is essential to improve their prognosis. However, previous detection methods have limitations, such as the overestimation and unacceptable bias in the immunoassays. Precision medicine has been challenged. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) method is recognized as the gold standard due to its accuracy and specificity, but lack of throughput and complex process limits its clinical application. Therefore, an accurate, simple and high throughput method for tacrolimus monitoring is needed for clinical practice. Methods: A modified LC-MS/MS method was introduced and validated. Whole blood samples were prepared by a one-step protein precipitation method. Chromatographic separation was achieved using a Phenomenex Kinetex 2.6 μm XB-C18 2.1 × 50 mm column with a total run time of 3.5 min to avoid matrix effect. An electrospray ionization source (ESI) was used in positive ion multiple reaction monitoring (MRM) mode for mass spectrometric detection. In order to protect the mass spectrometer, only part of the sample after LC separation was allowed to enter the mass spectrum, through a two HPLC systems coupled one mass spectrometry design. In this way, the instrument throughput is also improved and realizing the detection of 2 samples within 3.5 min and carried out a shorter analyzing time for each sample of 1.75 min. Additionally, we calculated tacrolimus-intrapatient variant (Tac-IPV) based on this modified method and assessed the prognostic value of Tac-IPV in Chinese kidney transplant patients. Results: The LC-MS/MS was modified by streamlining the procedure and increasing the throughput. The method proved to be accurate and reproducible with all performance parameters suitably meeting the clinical requirements over a calibration ranged from 0.37 to 42.90 ng/mL. Parameters such as linearity, limit of quantification (LoQ) and dilution integrity were validated with a clinical reportable range from 0.37 to 343.20 ng/mL, which was particularly useful for high drug concentrations patients (rare but very serious). Both cross-contamination and matrix effects were negligible. Clinical data of 83 patients showed that Tac-IPV was associated with poor kidney transplant outcome in Chinese (Hazard Ratio (HR) = 3.96, 4.75; 95% Cl: 1.10–14.21, 1.23–18.36; P < 0.05). Conclusions: This modified LC-MS/MS method possessed high throughput and simple sample preparation, allowing it to meet daily clinical needs. At the same time, Tac-IPV based on this modified LC-MS/MS had excellent prognostic value in kidney transplantation. These advantages have great significance for the individualized treatment of Chinese kidney transplant patients and broad application of Tac-IPV.

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

BackgroundInduction chemotherapy (IC) can alleviate locoregionally advanced nasopharyngeal carcinoma (LA-NPC), but effectiveness differs between patients, toxicity is problematic, and effective blood-based IC efficacy predictors are lacking. Here, we aimed to identify biomarkers for early identification of IC beneficiaries.MethodsSixty-four pairs of matched plasma samples collected before and after IC from LA-NPC patients including 34 responders and 30 non-responders, as well as 50 plasma samples of healthy individuals, were tested using data-independent acquisition mass spectrometry. The proteins associated with clinical traits or IC benefits were investigated by weighted gene co-expression network analysis (WGCNA) and soft cluster analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional annotations were performed to determine the potential function of the identified proteins. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of candidate biomarkers in predicting IC beneficiaries.ResultsCompared with healthy individuals, 1027 differentially expressed proteins (DEPs) were found in the plasma of LA-NPC patients. Based on feedback from IC outcomes, 463 DEPs were identified in the pre-IC plasma between responders and non-responders. A total of 1212 DEPs represented the proteomic changes before and after IC in responders, while 276 DEPs were identified in post-IC plasma between responders and non-responders. WGCNA identified nine protein co-expression modules correlated with clinical traits. Soft cluster analysis identified four IC benefits-related protein clusters. Functional enrichment analysis showed that these proteins may play a role in IC via immunity, complement, coagulation, glycosaminoglycan and serine. Four proteins differentially expressed in all group comparisons, paraoxonase/arylesterase 1 (PON1), insulin-like growth factor-binding protein 3 (IGFBP-3), rheumatoid factor D5 light chain (v-kappa-3) and RNA helicase (DDX55), were associated with clinical traits or IC benefits. A four-protein model accurately identified potential IC beneficiaries (AUC=0.95) while diagnosing LA-NPC (AUC=0.92), and the prediction performance was verified using the models to confirm the effective IC (AUC=0.97) and evaluate IC outcome (AUC=0.94).ConclusionThe plasma protein profiles among IC responders and non-responders were different. PON1, IGFBP3, v-kappa-3 and DDX55 could serve as potential biomarkers for early identification of IC beneficiaries for individualised treatment of LA-NPC.

Gliomas are the most aggressive and common type of malignant brain tumor, with limited treatment options and a dismal prognosis. Angiogenesis, a hallmarks of cancer, is one of two critical events in the progression of gliomas. Accumulating evidence has demonstrated that in glioma dysregulated molecules like long noncoding RNAs (lncRNAs), are closely linked to tumorigenesis and prognosis. However, the effects of and mechanisms of action of lncRNAs during tumor angiogenesis are poorly understood. The effect of lncRNA RP11-732M18.3 on angiogenesis was elucidated through an intracranial orthotopic glioma model, immunohistochemistry, and an in vitro angiogenesis assay. Co-culture experiments and cell migration assays were performed to investigate the function of lncRNA RP11-732M18.3 in vitro. lncRNA RP11-732M18.3 increased CD31+ microvessel density, and overexpression of lncRNA RP11-732M18.3 resulted in poor mouse survival. lncRNA RP11-732M18.3 promoted endothelial cell migration and tube formation. Nomogram and Kaplan-Meier survival analyses indicated that higher VEGFA is correlated with a poor prognosis. Mechanistically, lncRNA RP11-732M18.3 promotes angiogenesis by increasing the nuclear level of EP300 and facilitating the transcription and secretion of VEGFA. Our study contributes to the latest understanding of glioma angiogenesis and prognosis. lncRNA RP11-732M18.3 may be a potential treatment target in glioma.

Background: COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which was discovered in 2019 and spread around the world in a short time. SARS-CoV-2 nucleic acid amplification tests (NAATs) have been rapidly developed and quickly applied to clinical testing of COVID-19. Aim of this study was to evaluate the performance of four NAAT assays. Methods: Limit of detection (LOD), precision, accuracy, analytical specificity and analytical interference studies on four NAATs (Daan, Sansure, Hybribio, and Bioperfectus) were performed according to Clinical Laboratory Standards Institute protocols and guidelines. The four NAATs were compared using 46 clinical samples. Results: The LOD of the N gene for Daan, Sansure, and Hybribio was 500 copies/mL, and that for Bioperfectus was 1,000 copies/mL. The LOD of the ORF1ab gene for Daan, Bioperfectus, and Hybribio was 3,000 copies/mL, and that for Sansure was 2,000 copies/mL. A good precision was shown at the concentration above 20% of the LOD for all four NAATs, with all individual coefficients of variation below 3.6%. Satisfactory results were also observed in the accuracy, analytical specificity, and analytical interference tests. The results of the comparison test showed that Daan, Sansure, and Hybribio NAATs could detect the samples with a specificity of 100% (30/30) and a sensitivity of 100% (16/16), whereas Bioperfectus NAAT detected the samples with a specificity of 100% (30/30) and a sensitivity of 81.25% (13/16). However, no significant difference in sensitivity was found between Bioperfectus NAAT and the three other NAATs (p > 0.05). Conclusions: The four SARS-CoV-2 NAATs showed comparable performance, with the LOD of the N gene lower than the LOD of the ORF1ab gene. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of antiphospholipid syndrome (APS) relies predominantly on the laboratory measurement of antiphospholipid antibodies (aPLs). We attempt to verify the analytical performance of anticardiolipin antibodies (aCL) IgA/IgG/IgM and anti-β2-glycoprotein I antibodies (aβ2GPI) IgA/IgG/IgM on a high-throughput automated immunoassay platform. Methods: Limit of blank (LOB), limit of detection (LOD), imprecision, and linearity were calculated according to the corresponding Clinical and Laboratory Standards Institute (CLSI) guidelines protocols. The biological reference intervals (RIs) were verified in healthy individuals. Results: The LoB of aCL IgA/IgG/IgM and aβ2GPI IgA/IgG/IgM were 0.000, 1.200, 0.200, and 0.400, 1.250, 0.100, respectively. The LoD were 0.093, 1.715, 0.337 and 0.547, 2.174, 0.185 CU, respectively. All the within-run CVs and total CVs were less than the criterion at 10%. The linear analysis showed a good correlation between the predictive values and observed values with correlation coefficients greater than 0.99. Conclusions: The BIO-FLASH automated chemiluminescent analyzer performed well in measuring aPLs. [ABSTRACT FROM AUTHOR]