Comparable analysis of six immunoassays for carcinoembryonic antigen detection.

Objective: This study aimed to assess the current status of carcinoembryonic antigen (CEA) detection. We evaluated the correlation, consistency, and comparability of CEA results among six automated immunoassays, and combined with the results of CEA trueness verification of the Beijing Center for Clinical Laboratories (BCCL) for further analysis. Methods: Abbott Architect i2000, Beckman DxI800, Roche Cobas E601, Diasorin Liaison XL, Maccura IS1200, and Autolumo A2000 were used to detect 40 individual serum CEA samples. Taking the optimal analytical quality specifications calculated from data on biological variation as the evaluation criterion. Passing-Bablok regression and Bland-Altman analysis were performed between each assay and all-assays median values to evaluate the correlation and relative difference. The concordance correlation coefficient (CCC) was used for consistency analysis. Additionally, the trueness verification program used samples at three concentration levels to assess the bias, coefficient of variation (CV), and total error (TE) between the average measured values and the target value. Results: The Spearman's rank correlation coefficient (rs) was ≥0.996 and the CCC ranged between 0.9448 and 0.9990 for each assay vs. all-assays median. Considering the all-assays median value of each sample as a reference, there were proportional and systematic differences according to the Passing-bablok regression analysis. The relative difference of the four assays (Abbott Architect i2000, Autolumo A2000, Diasorin Liaison XL, and Maccura IS1200) met the optimal analytical quality specifications. On the other hand, Beckman DxI800 (13.2 %) and Roche Cobas E601 (-9.0 %) were only able to fulfill the desirable analytical quality specifications. The average pass rates for bias, CV, and TE of the trueness verification program were 80 %, 98 %, and 96 %, respectively. Conclusions: The six automated immunoassays vs. all-assays median have a good correlation in CEA detection. However, there is a lack of comparability of CEA results. Further improvements are needed in harmonization among CEA detections.

Simultaneous quantitation of multiple myeloma related dietary metabolites in serum using HILIC-LC-MS/MS.

Background: Recent studies from targeted and untargeted metabolomics have consistently revealed that diet-related metabolites, including carnitine (C0), several species of acylcarnitines (AcyCNs), amino acids, ceramides, and lysophosphatidylcholines (LPCs) may serve as potential multiple myeloma (MM) biomarkers. However, most of these approaches had some intrinsic limitations, namely low reproducibility and compromising the accuracy of the results. Objective: This study developed and validated a precise, efficient, and reliable liquid chromatography tandem mass spectrometric (LC-MS/MS) method for measuring these 28 metabolic risk factors in human serum. Design: This method employed isopropanol to extract the metabolites from serum, gradient elution on a hydrophilic interaction liquid chromatographic column (HILIC) for chromatographic separation, and multiple reaction monitor (MRM) mode with positive electrospray ionization (ESI) for mass spectrometric detection. Results: The correlation coefficients of linear response for this method were more than 0.9984. Analytical recoveries ranged from 91.3 to 106.3%, averaging 99.5%. The intra-run and total coefficients of variation were 1.1-5.9% and 2.0-9.6%, respectively. We have simultaneously determined the serological levels of C0, several subclasses of AcyCNs, amino acids, ceramides, and LPCs within 15 min for the first time. Conclusion: The established LC-MS/MS method was accurate, sensitive, efficient, and could be valuable in providing insights into the association between diet patterns and MM disease and added value in further clinical research.

Commutability evaluation of candidate reference materials and ERM-DA470k/IFCC for immunoglobulin M using two international approaches.

BACKGROUND: This study aimed to assess the commutability of frozen pooled human serum (PHS), high concentration of Immunoglobulin M (IgM) pure diluted materials (HPDM), commercialized pure materials (CPM), and dilutions of ERM-DA470k/IFCC in IgM detection using the CLSI and IFCC approaches, to support standardization or harmonization of IgM measurement. METHODS: Twenty-four serum samples, relevant reference materials (PHS, HPDM, CPM), and different ERM-DA470k/IFCC dilutions were analyzed in triplicate using six routine methods. The commutability of the relevant reference materials was carried out following CLSI EP30-A and IFCC bias analysis. RESULTS: According to the CLSI approach, low, medium, and high concentrations of PHS, HPDM, and CPM were commutable on 10, 13, 15, 13, and 8 of 15 assay combinations, respectively. Using the IFCC approach, low, medium, and high concentrations of PHS, HPDM, and CPM were commutable on 10, 11, 9, 15, and 10 of 15 assay combinations, respectively. The ERM-DA470k/IFCC dilutions with D-PBS and RPMI-1640 Medium were commutable on 13 of 15 assay combinations according to CLSI and were commutable on all 15 assay combinations using IFCC approach. CONCLUSIONS: High concentration of PHS were commutable on all six detection systems using the CLSI approach. Low and medium concentration of PHS showed unsatisfied commutability. HPDM, not CPM have good commutability, has the potential to become reference materials. ERM-DA470k/IFCC diluted with different medium showed different commutability.

TAF15 regulates the BRD4/GREM1 axis and activates the gremlin-1-NF-κB pathway to promote OA progression.

Background: Anterior cruciate ligament (ACL) injury is recognized as a risk factor for osteoarthritis (OA) progression. Herein, the function of TAF15 in ACL injury-induced OA was investigated. Methods: OA cell model and OA mouse model were established by interleukin-1 beta (IL-1ß) stimulation and ACL transection administration, respectively. The pathological changes were analyzed by histopathology. The mRNA and protein expressions were assessed using qRT-PCR, Western blot and IHC. Chondrocyte viability and apoptosis were examined by CCK8 assay and TUNEL staining, respectively. The interactions between TAF15, BRD4 and GREM1 were analyzed by RIP or ChIP assay. Results: TAF15 expression was markedly elevated in OA, and its knockdown suppressed IL-1ß-induced chondrocyte apoptosis and ECM degradation in vivo and cartilage pathological changes in vitro. TAF15 promoted BRD4 mRNA stability, and TAF15 silencing's repression on chondrocyte apoptosis and ECM degradation induced by IL-1ß was abrogated following BRD4 overexpression. BRD4 promoted GREM1 expression by directly binding with GREM1. In addition, the GREM1/NF-κB pathway functioned as the downstream pathway of BRD4 in promoting OA progression. Conclusion: TAF15 upregulation facilitated chondrocyte apoptosis and ECM degradation during OA development by acting on the BRD4/GREM1/NF-κB axis, which provided a theoretical basis for the development of novel therapies for OA.

The Effect of Endogenous PARP-1 in Different Phases of IL-1ß-Induced Chondrocyte Degeneration.

Objective: Poly (ADP-ribose) polymerase-1 (PARP-1) is a regulatory enzyme involved in DNA damage repair, gene transcription, cell growth, death and apoptosis. In our study, we aimed to explore the dynamic role of PARP-1 in chondrocyte (CH) degeneration in vitro. Methods: We used the primary CHs and treated them with interleukin-1 beta for up to 5 days. (IL-1ß) to induce degeneration. Meanwhile, we used AG-14361 (AG) to inhibit endogenous PARP-1 expression. Cell survival and collagen II expression were used to define the cell function of CHs. In addition, other metabolic indicators were measured containing the reactive oxygen species (ROS) level, 8-Hydroxy-2'-deoxyguanosine (8-OH-dG), IL-1ß, tumor necrosis factor alpha (TNF-α) and caspase 3/9 expression. Results: With IL-1ß treatment, the PARP1 expression of CHs was gradually increased from day 1 to day 5, accompanied by a reduction in cell survival and collagen II expression, and an increase in ROS, 8-OH-dG, IL-1ß, TNF-α and caspase 3/9 levels. We suppressed PARP1 expression on the first day of IL-1ß stimulation and found severe destruction of cell survival and collagen II content with a higher expression of caspase 3/9. However, when we cultured the CHs with AG from day 3 of the 5-day IL-1ß stimulation, cell survival and collagen II expression were rescued, and the ROS, 8-OH-dG, IL-1ß, TNF-α, and caspase 3/9 were downregulated. Conclusions: On day 1 of degeneration, increased PARP-1 played a protective role in CHs. However, from days 3 to 5 of degeneration, the accumulated PARP-1 presented a more destructive function in CHs.

Transformation of bread waste into 2,5-furandimethanol via an efficient chemoenzymatic approach in a benign reaction system.

Via combination catalysis with deep eutectic solvent lactic acid:betaine (chemocatalyst) and HMFOMUT cell (biocatalyst: E. coli HMFOMUT whole-cell), one-pot manufacture of 2,5-furandimethanol from waste bioresource was constructed in a chemoenzymatic approach. With bread waste (50 g/L) as substrate, the 5-hydroxymethylfuran yield reached 44.2 Cmol% (based on bread waste) by lactic acid:betaine (15 wt%) at 180 °C for 15 min. With glucose as co-substrate, HMFOMUT could transform 5-hydroxymethylfurfural (150 mM) to 2,5-furandimethanol (84.5 % yield) after 1 day at 37 °C and pH 7.0. In lactic acid:betaine-H2O, HMFOMUT effectively converted bread-derived 5-hydroxymethylfurfural into 2,5-furandimethanol in a productivity of 700 kg 2,5-furandimethanol per kg 5-hydroxymethylfurfural (230 kg 2,5-furandimethanol per kg bread). In an eco-friendly lactic acid:betaine system, an effective one-pot chemoenzymatic strategy was firstly developed to convert bread waste into 2,5-furandimethanol, which would reduce the operation cost and has potential application value for valorizing waste food bioresource into value-added furan.

Local extreme map guided multi-modal brain image fusion.

Multi-modal brain image fusion targets on integrating the salient and complementary features of different modalities of brain images into a comprehensive image. The well-fused brain image will make it convenient for doctors to precisely examine the brain diseases and can be input to intelligent systems to automatically detect the possible diseases. In order to achieve the above purpose, we have proposed a local extreme map guided multi-modal brain image fusion method. First, each source image is iteratively smoothed by the local extreme map guided image filter. Specifically, in each iteration, the guidance image is alternatively set to the local minimum map of the input image and local maximum map of previously filtered image. With the iteratively smoothed images, multiple scales of bright and dark feature maps of each source image can be gradually extracted from the difference image of every two continuously smoothed images. Then, the multiple scales of bright feature maps and base images (i.e., final-scale smoothed images) of the source images are fused by the elementwise-maximum fusion rule, respectively, and the multiple scales of dark feature maps of the source images are fused by the elementwise-minimum fusion rule. Finally, the fused bright feature map, dark feature map, and base image are integrated together to generate a single informative brain image. Extensive experiments verify that the proposed method outperforms eight state-of-the-art (SOTA) image fusion methods from both qualitative and quantitative aspects and demonstrates great application potential to clinical scenarios.

A machine learning-based approach for low-density lipoprotein cholesterol calculation using age, and lipid parameters.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is a critical biomarker for cardiovascular disease. However, no consensus exists on the best method for estimating LDL-C in Chinese laboratories. This study aimed to develop a machine learning (ML) method for LDL-C estimation. METHODS: An extensive data set of 111,448 samples were randomized into five equal subsets. ML-based equations were developed using age, sex, and lipid parameters based on five-fold cross-validation. The trained ML equations were externally validated in three different data sets. The performance of the ML equations was compared with the Friedewald, Martin/Hopkins, and Sampson equations. RESULTS: The selected ML equations showed less bias with direct LDL-C than other LDL-C equations in the Chinese population, including those with triglycerides (TG) ≥ 400 mg / dL and LDL-C < 40 mg / dL. The performance of the ML equations was less susceptible to age. External validation showed the generalization of the ML equations. CONCLUSIONS: This study highlights the potential of integrating sex, age, and lipid parameters into the ML equations to obtain a more robust and reliable LDL-C calculation.

An indirect approach for reference intervals establishment of immunoglobulin A, G and M: the combination of laboratory database and statistics.

Immunoglobulins are affected by sex, age and region, so it is necessary to establish suitable reference intervals (RIs) for clinical diagnosis. Various statistical methods were used to calculate RIs, but there has been a lack of comparison among the methods. Research based on immunoglobulin RIs establishment with various methods would provide a methodological basis for further research. A total of 16,525 individuals were enrolled in the study. Individuals were selected in the medical examination center of First Hospital of Jilin University from 2014 to 2020. The lambda-mu-sigma (LMS) method was performed to evaluate the dynamic changes in analytes. RIs were calculated by parametric, non-parametric, Hoffman method and Bhattacharya method. Sex and age partitions were found for immunoglobulins G and immunoglobulin M. The levels of IgM showed no difference with age in males, but showed differences after 50 years of age in females. Circulating immunoglobulin A concentrations showed an increasing trend with age, and immunoglobulin M showed a fluctuating trend with age. Obvious difference (>5%) was commonly found among the four methods, however, the RIs established by the four methods all passed the verification with a high passing rate. Sex and age differences should be considered for immunoglobulins G and immunoglobulin M in clinical practice. The feasibility of the four indirect methods was proven, which would provides a methodological reference for further studies and benefit the application of clinical data.

Fast parallel implementation for total variation constrained algebraic reconstruction technique.

In computed tomography (CT), the total variation (TV) constrained algebraic reconstruction technique (ART) can obtain better reconstruction quality when the projection data are sparse and noisy. However, the ART-TV algorithm remains time-consuming since it requires large numbers of iterations, especially for the reconstruction of high-resolution images. In this work, we propose a fast algorithm to calculate the system matrix for line intersection model and apply this algorithm to perform the forward-projection and back-projection operations of the ART. Then, we utilize the parallel computing techniques of multithreading and graphics processing units (GPU) to accelerate the ART iteration and the TV minimization, respectively. Numerical experiments show that our proposed parallel implementation approach is very efficient and accurate. For the reconstruction of a 2048 × 2048 image from 180 projection views of 2048 detector bins, it takes about 2.2 seconds to perform one iteration of the ART-TV algorithm using our proposed approach on a ten-core platform. Experimental results demonstrate that our new approach achieves a speedup of 23 times over the conventional single-threaded CPU implementation that using the Siddon algorithm.

Routine blood biomarkers for the detection of multiple myeloma using machine learning.

INTRODUCTION: Primary laboratory tests performed in the diagnosis of multiple myeloma (MM) include bone marrow examination and free light chain assay; however, these may only be ordered after clinical suspicion of disease. In contrast, routine blood test results are readily available. METHODS: Machine learning algorithms (ML) combined with routine blood tests were used to detect MM. Feature selection was performed to achieve improved classification performance. The robustness of the classification models was assessed in an internal and external validation data set. To minimize the divergence, the training and validation data sets were combined and used to assess the performance of the ML algorithms. RESULTS: The AdaBoost-DecisionTable produced the best performance (accuracy =94.75%, sensitivity =87.70%, positive predictive value (PPV) =92.50%, F-measure =90.00%, and areas under the receiver operating characteristic curves (AUC) =97.50%) in the training data set using a 10-fold cross-validation. Performance in the validation data sets was affected by the divergence of the data sets, with accuracy greater than 85% and AUC greater than 90% in the validation data sets. The ML algorithm achieved a high accuracy of 92.61%, high AUC (96.80%), a sensitivity value of 85.20%, a PPV value of 88.50%, and an F-measure of 86.80% in a test set that was randomly selected from the combined data set. CONCLUSIONS: Combining ML and routine serum biomarkers hold a potential benefit in MM diagnosis.

Hydrogen Permeation Behavior of Zirconium Nitride Film on Zirconium Hydride.

Hydrogen permeation barrier plays an important role in reducing hydrogen loss from zirconium hydride matrix when used as neutron moderator. Here, a composite nitride film was prepared on zirconium hydride by in situ reaction method in nitrogen atmosphere. The phase structure, morphology, element distribution, and valence states of the composite film were investigated by XRD, SEM, AES, and XPS analysis. It was found that the composite nitride film was continuous and dense with about 1.6 µm thickness; the major phase of the film was ZrN, with coexistence of ZrO2, ZrO, and ZrN0.36H0.8; and Zr-C, Zr-O, Zr-N, O-H, and N-H bonds were detected in the film. The existence of ZrN0.36H0.8 phase and the bonds of O-H and N-H revealed that the nitrogen and oxygen in the film could capture hydrogen from the zirconium hydride matrix. The hydrogen permeation performance of nitride film was compared with oxide film by permeation reduction factor (PRF), vacuum thermal dehydrogenation (VTD), and hydrogen permeation rate (HPR) methods, and the results showed that the hydrogen permeation barrier effects of nitride film were better than that of oxide film. The zirconium nitride film would be a potential candidate for hydrogen permeation barrier on the surface of zirconium hydride.

Simultaneous elimination of black-odor and stabilization of heavy metals in contaminated sediment using calcium peroxide/hydroxyapatite: Microbial responses and ecotoxicological effects.

In this study, laboratory-scale experiments were conducted to investigate the feasibility of the combined use of calcium peroxide and hydroxyapatite (CaO2/HAP) for simultaneous black-odor sediment remediation and heavy metal stabilization. The ecotoxicological effects of remediated sediment were also evaluated based on biological toxicity. Results showed that CaO2/HAP effectively eliminated the black-odor and simultaneously stabilized heavy metals in the sediment. Under the optimal dosage ratio of CaO2/HAP (1:2), the acid volatile sulfides decreased to approximately 20 mg/kg (dry weight, dw) and oxidation-reduction potential increased from - 165 mV to approximately - 90 mV. The leaching of heavy metals meets the strictest standards (Level I) of the "Technical Specification for Output Disposal of Contaminated Sediment Treatment Plant of River and Lake" (SZDB/Z 236-2017). The indigenous microbial community succession occurred (p < 0.01), Proteobacteria and Firmicutes accounting for 75.54% and 20.19%, respectively, were the predominant bacteria in the remediated sediment. Additionally, CaO2/HAP remediated sediments were safer and more environmentally friendly than raw sediments, and were not biotoxic to the benthic environment (p < 0.01). This study provides new insights into the combined use of the beneficial amendments remediating heavy metal-contaminated black-odor river sediment.

Efficient chemoenzymatic valorization of biobased D-fructose into 2,5-bis(hydroxymethyl)furan with deep eutectic solvent Lactic acid:Betaine and Pseudomonas putida S12 whole cells.

2,5-Bis(hydroxymethyl)furan (BHMF) is one kind of important upgraded derivatives of biobased 5-hydroxymethylfuran (5-HMF). This study verified the feasibility of one-pot chemoenzymatic conversion of biobased D-fructose to BHMF by cascade catalysis with deep eutectic solvent Lactic acid:Betaine (LA:B) and reductase biocatalyst in LA:B - H2O. Using D-fructose (36.0 g/L) as feedstock, the yield of 5-HMF reached 91.6% in DES LA:B - H2O (15:85, v:v) at 150 °C for 1.5 h. Using D-fructose (2 mol D-fructose/mol 5-HMF) as cosubstrate, commercial 5-HMF (125 mM) was converted into BHMF at 90.7% yield by whole-cells of Pseudomonas putida S12 within 24 h at 30 °C and pH 8.0. In addition, Pseudomonas Putida S12 could efficiently transform D-fructose-valorized 5-HMF into BHMF [98.4% yield, based on 5-HMF; 90.1% yield, based on substrate D-fructose] in DES LA:B - H2O. An efficient chemoenzymatic valorization of D-fructose to BHMF was developed in a benign reaction system.

Single-Image Deraining via Recurrent Residual Multiscale Networks.

Existing deraining approaches represent rain streaks with different rain layers and then separate the layers from the background image. However, because of the complexity of real-world rain, such as various densities, shapes, and directions of rain streaks, it is very difficult to decompose a rain image into clean background and rain layers. In this article, we develop a novel single-image deraining method based on residual multiscale pyramid to mitigate the difficulty of rain image decomposition. To be specific, we progressively remove rain streaks in a coarse-to-fine fashion, where heavy rain is first removed in coarse-resolution levels and then light rain is eliminated in fine-resolution levels. Furthermore, based on the observation that residuals between a restored image and its corresponding rain image give critical clues of rain streaks, we regard the residuals as an attention map to remove rains in the consecutive finer level image. To achieve a powerful yet compact deraining framework, we construct our network by recurrent layers and remove rain with the same network in different pyramid levels. In addition, we design a multiscale kernel selection network (MSKSN) to facilitate our single network to remove rain streaks at different levels. In this manner, we reduce 81% of the model parameters without decreasing deraining performance compared with our prior work. Extensive experimental results on widely used benchmarks show that our approach achieves superior deraining performance compared with the state of the art.

Comparability of thyroid-stimulating hormone immunoassays using fresh frozen human sera and external quality assessment data.

BACKGROUND: This study aimed to assess the comparability among assays using freshly frozen human sera and external quality assessment (EQA) data in China. METHODS: Twenty-nine serum samples and two commercial EQA materials, obtained from the National Center for Clinical Laboratories (NCCL), were analyzed in triplicate using eight routine TSH assays. The commutability of commercial EQA materials (NCCL materials) was evaluated in accordance with the CLSI EP30-A and IFCC bias analysis. Median values obtained for the NCCL EQA materials were used to determine the systematic and commutability-related biases among immunoassays through back-calculation. The comparability of TSH measurements from a panel of clinical samples and NCCL EQA data was determined on the basis of Passing-Bablok regression. Furthermore, human serum pools were used to perform commutable EQA. RESULTS: NCCL EQA materials displayed commutability among three or five of seven assay combinations according CLSI or IFCC approach, respectively. The mean of systematic bias ranged from -13.78% to 9.85% for the eight routine TSH assays. After correcting for systematic bias, averaged commutability-related biases ranged between -42.26% and 12.19%. After correction for systematic and commutability -related biases, the slopes indicating interassay relatedness ranged from 0.801 to 1.299 using individual human sera, from 0.735 to 1.254 using NCCL EQA data, and from 0.729 to 1.115 using pooled human serum EQA(the commutable EQA). CONCLUSIONS: The harmonization of TSH measurement is challenging; hence, systematic and commutability-related biases should be determined and corrected for accurate comparisons among assays when using human individual serum and the commercial EQA materials.

EQA/PT scheme to improve the equivalence of enzymatic results between mutual recognition laboratories in Beijing.

BACKGROUND: To utilize the external quality assessment (EQA)/proficiency testing (PT) scheme to evaluate the equivalence of different clinical enzymatic measuring systems in Beijing. METHODS: The Beijing Center for Clinical Laboratory (BCCL) distributed three investigation samples to mutual recognition clinical laboratories in Beijing including alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), creatine kinase (CK), and lactate dehydrogenase (LDH). These samples were derived from serum pools with values assigned by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) enzymatic reference measurement procedures (RMPs). Each laboratory performed duplicate tests of the samples. Then, the samples at level 1 were used to recalibrate individual measuring systems for repeating the tests. BCCL collected data for evaluation of their analytical quality. RESULTS: Before recalibration, the biases of ALT and AST tests were not traceable to the IFCC RMPs, and the bias pass rates of GGT, CK, and LDH tests were only 51.2%, 55.7%, and 48.6% respectively. After recalibration, the pass rates of ALT, AST, GGT, CK, and LDH increased to 95.1%, 82.9%, 95.1%, 97.1%, and 70.0% respectively. The EQA/PT also showed that after recalibration, more than 95% of laboratories met the optimum level specifications of the biological variation for ALT, AST, GGT, and CK tests and the desirable for LDH tests. CONCLUSION: The enzymatic tests in Beijing need to be further standardized by category 1 or 2 EQA/PT scheme for mutual recognition between clinical laboratories. The criteria of biological variation are more relevant for determining the equivalence of clinical enzymatic tests.

Homogeneity and Stability Evaluation of External Quality Assessment Control Materials for Four Coagulation Tests.

BACKGROUND: This study assessed the homogeneity and stability of control materials used in external quality assessment (EQA) of four coagulation tests, aiming to verify that these materials meet clinical testing requirements and to provide an evidence base for future improvement of laboratory coagulation test quality. METHODS: The homogeneity and stability of control materials were assessed according to the relevant guidance. Homogeneity assessment involved 10 vials of samples obtained from 2 batches (each vial tested twice). The homogeneity of control materials in four coagulation tests was assessed using one-way analysis of variance, with standard deviation of uniformity (Ss) 0.3 σ as an assessment criterion. Stability assessment involved two vials of sam-ples obtained from two batches (each vial tested twice). The stability of control materials was assessed at cold storage, room temperature, temperature of 37°C. Reconstitution stability of control materials placed in cold storage and at room temperature, and long-term stability of reconstituted control materials stored frozen (-20°C and -80°C) were observed. Linear regression analysis was performed to assess long-term stability. RESULTS: The Ss values of EQA control materials for four coagulation tests were PT L1 Ss = 0.084, PT L2 Ss = 0.889, APTT L1 Ss = 0.164, APTT L2 Ss = 0.223, Fbg L1 Ss = 6.256, Fbg L2 Ss = 2.251, TT L1 Ss = 0.552, TT L2 Ss = 0.3111. PT, APTT, Fbg, and TT were associated with the standard deviation of uniformity values of 0.3 σ. Non-reconstituted samples were observed at 37°C for 2 hours and 4 hours, and at room temperature for 1 day. Reconstituted samples were observed when stored at 4°C for 4 hours and 8 hours, at room temperature for 4 hours, and at -20°C and -80°C for 6 months. Instability of reconstituted samples was observed in PT and APTT tests at 4°C for 8 hours and at -20°C for 5 months. CONCLUSIONS: EQA control materials presented with satisfactory homogeneity in four coagulation tests. Non-reconstituted samples presented with satisfactory stability at 37°C for 2 hours and 4 hours and at room temperature for 1 day, while reconstituted samples presented with satisfactory stability when refrigerated at 4°C for 4 hours, when kept at room temperature for 4 hours, and when frozen at -80°C for 6 months.

Trueness assessment of routine electrolytes measuring systems using the candidate reference method by ion chromatography.

Electrolytes for sodium, potassium, magnesium, and calcium are important serum ions that are frequently assayed in clinical laboratories. In this study, we assessed the trueness of routine analytical systems for four cations using an inexpensive candidate reference method aimed to promote the standardization of serum electrolyte detection. An ion chromatography (IC) method with Cesium as an internal standard was developed and evaluated. The residual clinical serum samples at Chaoyang Hospital were collected and prepared into three human serum pools of electrolytes, which were used for the trueness evaluation of five routine analytical systems. Furthermore, the agreement between routine methods and the IC method was verified using 40 individual human samples. The recovery rates of sodium, potassium, magnesium and calcium were 99.69%, 100.34%, 100.43% and 99.89%, respectively. The intra-batch standard deviation and intra-laboratory precision of NIST SRM 956c were all less than 1% for the four ions. The certified values were within the validation range, and the deviation between the results and the certified values were less than 0.5%. The three serum pools were homogeneous and stable. All routine systems aligned with the IC method for four cations and achieved the analytical quality specifications for potassium and magnesium at 3 different concentrations. The developed IC method is simple, practical, accurate, and precise, which can be used as a candidate reference method for serum electrolytes measurement. Five routine analytical systems for electrolytes measurement had the acceptable bias for potassium and magnesium and their results showed good concordance.

Establishment of Multiple Myeloma Diagnostic Model Based on Logistic Regression in Clinical Laboratory.

BACKGROUND: Due to the insidious onset of multiple myeloma (MM), missed diagnosis and misdiagnosis have a serious impact on the health of MM patients. Simple, rapid, and valid laboratory screening is critical for MM clinical diagnosis. METHODS: We used routine laboratory tests to establish a simple, inexpensive, and non-invasive diagnostic model for MM based on logistic regression. In the retrospective analysis, a total of 273 newly diagnosed MM inpatients and 288 non-MM participants, from January 2016 to December 2018 in Beijing Chaoyang hospital, Capital Medical University, were divided into training set and validation set. Age, gender, and the related routine laboratory tests for MM, including albumin (ALB), globulin (GLB), lactate dehydrogenase (LDH), creatinine (Cr), calcium (Ca2+), hemoglobin (Hb) and platelet (PLT), were analyzed by multivariate logistic regression to develop a diagnostic model. RESULTS: A diagnostic model was calculated using the formula MM index=-((-18×gender-3×ALB-Hb)/10), based on the logistic regression. The MM index [22 (20 - 25)] of MM patients was significantly lower than that of non-MM [30 (29 - 31)] in the training set (p < 0.001). It showed an excellent diagnostic performance in diagnosing MM through a receiver operating characteristic (ROC) curve, and its corresponding sensitivity, specificity, and area under the curve (AUC) were 95.6%, 96.7%, and 0.982 (0.968, 0.997), respectively. At a diagnostic risk threshold of 28, the model identified MM with a sensitivity of 95.6% and a specificity of 98.1% by using independent validation data. There was a significant positive correlation (r = 0.845, p < 0.001) between the DS grading and the MM index among all the participants. CONCLUSIONS: The established diagnostic model of MM index can successfully identify newly diagnosed MM from healthy controls. The diagnostic model of MM index may also act as a predictor of the severity of MM without therapy.