Establishment of reference intervals for plasma IL-2, IL-4, IL-5, and IL-17A in healthy adults from the Jiangsu region of eastern China using flow cytometry: A single-center study.

BACKGROUND: Cytokines are of utmost importance in both the physiological and pathological immune responses of the human body. This study utilized flow cytometry to measure the levels of plasma interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-5 (IL-5) and interleukin-17A (IL-17A) and established their reference intervals, aiming to provide data support for the diagnosis and treatment of clinical diseases. METHODS: According to the inclusion and exclusion criteria, a total of 728 reference individuals were included in this study from January 2023 to June 2023. The Kolmogorov-Smirnov test was used to analyse the distributions of plasma IL-2, IL-4, IL-5 and IL-17A. The reference intervals of plasma IL-2, IL-4, IL-5 and IL-17A were established by the unilateral percentile method (95th percentile) based on the guidelines of C28-A 3 and WS/T 402-2012. RESULTS: In this study, the levels of plasma IL-2, IL-4, IL-5 and IL-17A were nonnormally distributed. The concentrations of plasma IL-2, IL-4, IL-5 and IL-17A in healthy adults were not significantly different by sex or age (all P > 0.05). Therefore, all the reference individuals were combined into one group, and the reference intervals of plasma IL-2, IL-4, IL-5 and IL-17 were established by flow cytometry (IL-2 ≤ 10.25 pg/mL, IL-4 ≤ 9.87 pg/mL, IL-5 ≤ 3.36 pg/mL and IL-17A ≤ 9.46 pg/mL). CONCLUSIONS: We first established the reference intervals of plasma IL-2, IL-4, IL-5 and IL-17A in healthy adults based on a single-center population in the Jiangsu region in eastern China, which will provide an important reference value for evaluating human immune status and the diagnosis and treatment of clinical diseases.

Gastric Cancer Mesenchymal Stem Cells Trigger Endothelial Cell Functional Changes to Promote Cancer Progression.

Our previous studies have highlighted the pivotal role of gastric cancer mesenchymal stem cells (GCMSCs) in tumor initiation, progression, and metastasis. In parallel, it is well-documented that endothelial cells (ECs) undergo functional alterations in response to challenging tumor microenvironment. This study aims to elucidate whether functional changes in ECs might be induced by GCMSCs and thus influence cancer progression. Cell proliferation was assessed through CCK-8 and colony formation assays, while cell migration and invasion capabilities were evaluated by wound-healing and Transwell assays. Immunohistochemistry was employed to examine protein distribution and expression levels. Additionally, quantitative analysis of protein and mRNA expression was carried out through Western blotting and qRT-PCR respectively, with gene knockdown achieved using siRNA. Our findings revealed that GCMSCs effectively stimulate cell proliferation, migration, and angiogenesis of human umbilical vein endothelial cells (HUVECs), both in vitro and in vivo. GCMSCs promote the migration and invasion of gastric cancer cells by inducing the expression of Slit2 in HUVECs. Notably, the inhibition of phosphorylated AKT partially mitigates the aforementioned effects. In conclusion, GCMSCs may exert regulatory control over Slit2 expression in ECs via the AKT signaling pathway, thereby inducing functional changes in ECs that promote tumor progression.

Comparison of the Profile and Management of Chronic Pancreatitis between China and Western Countries: A Single-Center Experience and Literature Review.

OBJECTIVE: The etiology, clinical presentation, diagnosis, and treatment strategies of chronic pancreatitis (CP) vary significantly between countries. Specifically, the etiology and surgical approaches to treating CP differ between China and Western countries. Therefore, this study aims to compare the disparities in CP profiles and management based on our single-center experience and recent data from the West. METHODS: From January 2007 to December 2017, a total of 130 consecutive patients with histologically confirmed chronic pancreatitis (CP) underwent surgical treatment at the First Affiliated Hospital of Nanjing Medical University. The clinical features, etiology, risk factors, and operative procedures of these CP patients were analyzed and compared with recent data from Western countries. RESULTS: Our patient cohort was predominantly male (3.19:1), with a median age of 50.2 ± 9.8 years. Upper abdominal pain was the most common symptom, present in 102 patients (78.5%). The most common etiology was obstructive factors (47.7%), followed by alcohol (34.6%). The incidence of genic mutation was 2%, significantly lower than rates reported in Western research. Steatorrhea, weight loss, and jaundice were present in 6.9%, 18.5%, and 17.7% of patients, respectively. Pancreatic cysts or pseudocysts were diagnosed in 7 patients (5.4%). The following procedures were performed: Partington procedure in 33 patients (25.4%), Frey procedure in 17 patients (13.2%), Berne procedure in 5 patients (3.9%), Beger procedure in 1 patient (0.8%), pancreaticoduodenectomy in 17 patients (13.1%), pylorus-preserving pancreaticoduodenectomy in 18 patients (13.9%), middle pancreatectomy in 1 patient (0.8%), and distal pancreatectomy in 9 patients (6.9%). Choledochojejunostomy was performed in 14 patients (10.8%), gastroenterostomy in 2 (1.5%), and 15 patients (11.5%) underwent aspiration biopsy. CONCLUSION: Our study confirms that, etiologically, obstructive chronic pancreatitis (CP) is more frequent in the Chinese population than in Western populations. Although diagnostic instruments and operative procedures in China and Western countries are roughly comparable, slight differences exist in relation to diagnostic flowcharts/criteria and the indications and optimal timing of surgery.

A Novel LDLC Equation is Superior to the NIH LDLC Equation and the Friedewald Equation.

Background: LDLC equations have varying levels of underestimation for the calculated LDLC. Therefore, underestimating LDLC should be avoided as much as possible. We need to establish LDLC equations that underestimate LDLC as little as possible. Methods: We established the equations with a healthy cohort from Shuyang Hospital and validated the equations with an unselected patient cohort from The Second People's Hospital of Lianyungang. We established the novel LDLC equations by using the regression equation. The relationship between two markers was analysed using Pearson's approach. The 95% limits of measuring agreement within ±2 SD for the LDLC equations was performed using Bland‒Altman analysis. ROC curve analysis was used to predict LDLC levels and the accuracy of the LDLC equation for determining the direct LDLC levels at LDLC cut-offs was assessed. Results: We obtained two novel LDLC equations (LDL_nonHDLC equation=-0.899+1.195*nonHDLC-0.00347*nonHDLC2 and LDL_TC(total cholesterol) equation=-2.775+1.29*TC -0.00990* TC 2). The correlation coefficient between the novel LDLC equation and the direct LDLC measurements is not lower than that between the LDL_NIH equation and the direct LDLC measurements. The AUCs of our novel LDLC equations were greater than those of the LDL_NIH equation and the LDL_F equation at the LDLC cut-offs for clinical decision-making. The measuring agreement in the methods of the LDL_nonHDL equation is superior to that of the LDL_NIH equation. Conclusion: LDLC calculated by the novel LDL_nonHDL equation exhibited superiority over the LDL_NIH equation. Combining the LDL_NIH equation and our novel LDLC equation may improve accuracy and avoid undertreatment of high LDLC levels.

Gastric cancer mesenchymal stem cells promote tumor glycolysis and chemoresistance by regulating B7H3 in gastric cancer cells.

Despite surgical treatment combined with multidrug therapy having made some progress, chemotherapy resistance is the main cause of recurrence and death of gastric cancer (GC). Gastric cancer mesenchymal stem cells (GCMSCs) have been reported to be correlated with the limited efficacy of chemotherapy in GC, but the mechanism of GCMSCs regulating GC resistance needs to be further studied. The gene set enrichment analysis (GSEA) was performed to explore the glycolysis-related pathways heterogeneity across different cell subpopulations. Glucose uptake and lactate production assays were used to evaluate the importance of B7H3 expression in GCMSCs-treated GC cells. The therapeutic efficacy of oxaliplatin (OXA) and paclitaxel (PTX) was determined using CCK-8 and colony formation assays. Signaling pathways altered by GCMSCs-CM were revealed by immunoblotting. The expression of TNF-α in GCMSCs and bone marrow mesenchymal stem cells (BMMSCs) was detected by western blot analysis and qPCR. Our results showed that the OXA and PTX resistance of GC cells were significantly enhanced in the GCMSCs-CM treated GC cells. Acquired OXA and PTX resistance was characterized by increased cell viability for OXA and PTX, the formation of cell colonies, and decreased levels of cell apoptosis, which were accompanied by reduced levels of cleaved caspase-3 and Bax expression, and increased levels of Bcl-2, HK2, MDR1, and B7H3 expression. Blocking TNF-α in GCMSCs-CM, B7H3 knockdown or the use of 2-DG, a key enzyme inhibitor of glycolysis in GC cells suppressed the OXA and PTX resistance of GC cells that had been treated with GCMSCs-CM. This study shows that GCMSCs-CM derived TNF-α could upregulate the expression of B7H3 of GC cells to promote tumor chemoresistance. Our results provide a new basis for the treatment of GC.

A Comparative Study on Fixed-order Event Sequence Visualizations: Gantt, Extended Gantt, and Stringline Charts.

We conduct two in-lab experiments (N=93) to evaluate the effectiveness of Gantt charts, extended Gantt charts, and stringline charts for visualizing fixed-order event sequence data. We first formulate five types of event sequences and define three types of sequence elements: point events, interval events, and the temporal gaps between them. Our two experiments focus on event sequences with a pre-defined, fixed order, and measure task error rates and completion time. The first experiment shows single sequences and assesses the three charts' performance in comparing event duration or gap. The second experiment shows multiple sequences and evaluates how well the charts reveal temporal patterns. The results suggest that when visualizing single fixed-order event sequences, 1) Gantt and extended Gantt charts lead to comparable error rates in the duration-comparing task; 2) Gantt charts exhibit either shorter or equal completion time than extended Gantt charts; 3) both Gantt and extended Gantt charts demonstrate shorter completion times than stringline charts; 4) however, stringline charts outperform the other two charts with fewer errors in the comparing task when event type counts are high. Additionally, when visualizing multiple point-based fixed-order event sequences, stringline charts require less time than Gantt charts for people to find temporal patterns. Based on these findings, we discuss design opportunities for visualizing fixed-order event sequences and discuss future avenues for optimizing these charts.

Swaying the Public? Impacts of Election Forecast Visualizations on Emotion, Trust, and Intention in the 2022 U.S. Midterms.

We conducted a longitudinal study during the 2022 U.S. midterm elections, investigating the real-world impacts of uncertainty visualizations. Using our forecast model of the governor elections in 33 states, we created a website and deployed four uncertainty visualizations for the election forecasts: single quantile dotplot (1-Dotplot), dual quantile dotplots (2-Dotplot), dual histogram intervals (2-Interval), and Plinko quantile dotplot (Plinko), an animated design with a physical and probabilistic analogy. Our online experiment ran from Oct. 18, 2022, to Nov. 23, 2022, involving 1,327 participants from 15 states. We use Bayesian multilevel modeling and post-stratification to produce demographically-representative estimates of people's emotions, trust in forecasts, and political participation intention. We find that election forecast visualizations can heighten emotions, increase trust, and slightly affect people's intentions to participate in elections. 2-Interval shows the strongest effects across all measures; 1-Dotplot increases trust the most after elections. Both visualizations create emotional and trust gaps between different partisan identities, especially when a Republican candidate is predicted to win. Our qualitative analysis uncovers the complex political and social contexts of election forecast visualizations, showcasing that visualizations may provoke polarization. This intriguing interplay between visualization types, partisanship, and trust exemplifies the fundamental challenge of disentangling visualization from its context, underscoring a need for deeper investigation into the real-world impacts of visualizations. Our preprint and supplements are available at https://doi.org/osf.io/ajq8f.

Adaptive Assessment of Visualization Literacy.

Visualization literacy is an essential skill for accurately interpreting data to inform critical decisions. Consequently, it is vital to understand the evolution of this ability and devise targeted interventions to enhance it, requiring concise and repeatable assessments of visualization literacy for individuals. However, current assessments, such as the Visualization Literacy Assessment Test (VLAT), are time-consuming due to their fixed, lengthy format. To address this limitation, we develop two streamlined computerized adaptive tests (CATs) for visualization literacy, A-VLAT and A-CALVI, which measure the same set of skills as their original versions in half the number of questions. Specifically, we (1) employ item response theory (IRT) and non-psychometric constraints to construct adaptive versions of the assessments, (2) finalize the configurations of adaptation through simulation, (3) refine the composition of test items of A-CALVI via a qualitative study, and (4) demonstrate the test-retest reliability (ICC: 0.98 and 0.98) and convergent validity (correlation: 0.81 and 0.66) of both CATs via four online studies. We discuss practical recommendations for using our CATs and opportunities for further customization to leverage the full potential of adaptive assessments. All supplemental materials are available at https://osf.io/a6258/.

Establishment of Reference Intervals for SII, NLR, PLR, and LMR in Healthy Adults in Jiangsu Region in Eastern China.

BACKGROUND: We preliminarily established the reference intervals for the systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) in healthy adults in Jiangsu region in Eastern China to guide the interpretation and application of these indicators in clinical practice. METHODS: In total, 29,947 ostensibly healthy subjects from December 2020 to March 2021 were included in this study. The distributions of the SII, NLR, PLR, and LMR were analyzed using the Kolmogorov-Smirnov test. According to the C28-A3 guidelines, the 2.5th and 97.5th percentiles (P2.5 to P97.5) of the SII, NLR, PLR, and LMR were used to establish the reference intervals based on nonparametric methods. RESULTS: All SII, NLR, PLR, and LMR data were non-normally distributed. The levels of the SII, NLR, PLR, and LMR in healthy adults were significantly different between males and females (all p < 0.05). However, there were no significant differences in the SII, NLR, PLR or LMR among the different age groups, regardless of gender (all p > 0.05). Therefore, the reference intervals for the SII, NLR, PLR, and LMR were established based on the Sysmex testing platform for males (162 × 109/L - 811 × 109/L; 0.89 - 3.26; 63.15 - 191.34; 3.18 - 9.61) and females (165 × 109/L - 792 × 109/L; 0.87 - 3.16; 69.04 - 205.62; 3.46 - 10.96). CONCLUSIONS: We have established the reference intervals for SII, NLR, PLR, and LMR in healthy adults based on the Sysmex detection platform and large sample size, which may provide important guidance for its clinical application.

Application of a six sigma model to evaluate the analytical performance of cerebrospinal fluid biochemical analytes and the design of quality control strategies for these assays: A single-centre study.

BACKGROUND: In this study, we applied a six sigma model to examine cerebrospinal fluid (CSF) biochemical analytes for the first time. Our goal was to evaluate the analytical performance of various CSF biochemical analytes, design an optimized internal quality control (IQC) strategy, and formulate scientific and reasonable improvement plans. METHODS: The sigma values of CSF total protein (CSF-TP), albumin (CSF-ALB), chloride (CSF-Cl), and glucose (CSF-GLU) were calculated using the following formula: sigma = [TEa(%)-|bias(%)|]/CV(%). The analytical performance of each analyte was shown using a normalized sigma method decision chart. Individualized IQC schemes and improvement protocols for CSF biochemical analytes were formulated using the Westgard sigma rule flow chart with batch size and quality goal index (QGI). RESULTS: The distribution of sigma values for CSF biochemical analytes ranged from 5.0 to 9.9, and the sigma values varied for different concentrations of the same analyte. The analytical performance of the CSF assays at the two QC levels is displayed visually in normalized sigma method decision charts. Individualized IQC strategies for CSF biochemical analytes were as follows: for CSF-ALB, CSF-TP and CSF-Cl, use 13s with N = 2 and R = 1000; for CSF-GLU, use 13s/22s/R4s with N = 2 and R = 450. In addition, priority improvement measures for analytes with sigma values less than 6 (CSF-GLU) were formulated based on the QGI, and their analytical performance was improved after the corresponding improvement measures were taken. CONCLUSIONS: The six sigma model has significant advantages in practical applications involving CSF biochemical analytes and is highly useful for quality assurance and quality improvement.

Visual Cue Effects on a Classification Accuracy Estimation Task in Immersive Scatterplots.

Immersive visualization in virtual reality (VR) allows us to exploit visual cues for perception in 3D space, yet few existing studies have measured the effects of visual cues. Across a desktop monitor and a head-mounted display (HMD), we assessed scatterplot designs which vary their use of visual cues-motion, shading, perspective (graphical projection), and dimensionality-on two sets of data. We conducted a user study with a summary task in which 32 participants estimated the classification accuracy of an artificial neural network from the scatterplots. With Bayesian multilevel modeling, we capture the intricate visual effects and find that no cue alone explains all the variance in estimation error. Visual motion cues generally reduce participants' estimation error; besides this motion, using other cues may increase participants' estimation error. Using an HMD, adding visual motion cues, providing a third data dimension, or showing a more complicated dataset leads to longer response times. We speculate that most visual cues may not strongly affect perception in immersive analytics unless they change people's mental model about data. In summary, by studying participants as they interpret the output from a complicated machine learning model, we advance our understanding of how to use the visual cues in immersive analytics.

Heparin-Induced Thrombocytopenia Caused by Preventive Anticoagulation After Femoral Intertrochanteric Fracture Surgery: a Case Report.

BACKGROUND: Heparin-induced thrombocytopenia (HIT) is a severe complication caused by heparin. It is characterized by occult onset and missed diagnosis. Misdiagnosis easily occurs. METHODS: This paper reported an 85-year-old woman with an intertrochanteric fracture of the femur which was treated with low molecular weight heparin (LMWH) and fondaparinux sodium to prevent venous thrombosis. Then, the patient developed HIT. This is the first case report of HIT induced by LMWH and fondaparinux in a patient with a hip fracture. This case highlights the severity of HIT in elderly patients with hip fractures using LMWH and fondaparinux and the need for platelet monitoring in these patients. RESULTS: LMWH was ceased in this HIT-confirmed patient, and non-heparin treatment was begun instead. Apixaban was given twice daily for therapeutic anticoagulation therapy. In the end, the platelet levels gradually returned to normal. CONCLUSIONS: We should pay more attention to HIT and platelets during the perioperative period of orthopedic surgery, especially in elderly patients. Once the disease is confirmed, it is necessary to stop heparin-related drugs immediately and administer oral anticoagulants instead.

Associations of serum amyloid A and 25-hydroxyvitamin D with diabetic nephropathy: A cross-sectional study.

BACKGROUND: The present study investigated the relationships between serum amyloid A (SAA), 25-hydroxyvitamin D (25(OH)VD) and diabetic nephropathy (DN) to provide evidence for the prevention and management of DN. METHODS: A total of 182 patients with type 2 diabetes mellitus (T2DM) were enrolled in this study. The levels of SAA, 25(OH)VD, and other conventional indicators were measured and analyzed. Receiver operating characteristic curve analysis was applied for the combined measurement of SAA and 25(OH)VD, and risk factors for DN were evaluated using binary logistic regression analysis. RESULTS: The levels of SAA in T2DM patients were significantly higher than those in healthy subjects, and the level significantly increased with the progression of DN (p < 0.05). In contrast, the level of 25(OH)VD in T2DM patients was significantly lower than that in healthy subjects, and the level significantly decreased with the progression of DN (p < 0.05). The combined measurement of SAA and 25(OH)VD distinguished DN patients from T2DM patients better than the measurement of SAA or 25(OH)VD alone. SAA was an independent risk factor for DN, and 25(OH)VD was an independent protective factor for DN. CONCLUSION: SAA and 25(OH)VD might be used as potential markers to identify patients at increased risk of developing DN.

Rethinking the Ranks of Visual Channels.

Data can be visually represented using visual channels like position, length or luminance. An existing ranking of these visual channels is based on how accurately participants could report the ratio between two depicted values. There is an assumption that this ranking should hold for different tasks and for different numbers of marks. However, there is surprisingly little existing work that tests this assumption, especially given that visually computing ratios is relatively unimportant in real-world visualizations, compared to seeing, remembering, and comparing trends and motifs, across displays that almost universally depict more than two values. To simulate the information extracted from a glance at a visualization, we instead asked participants to immediately reproduce a set of values from memory after they were shown the visualization. These values could be shown in a bar graph (position (bar)), line graph (position (line)), heat map (luminance), bubble chart (area), misaligned bar graph (length), or 'wind map' (angle). With a Bayesian multilevel modeling approach, we show how the rank positions of visual channels shift across different numbers of marks (2, 4 or 8) and for bias, precision, and error measures. The ranking did not hold, even for reproductions of only 2 marks, and the new probabilistic ranking was highly inconsistent for reproductions of different numbers of marks. Other factors besides channel choice had an order of magnitude more influence on performance, such as the number of values in the series (e.g., more marks led to larger errors), or the value of each mark (e.g., small values were systematically overestimated). Every visual channel was worse for displays with 8 marks than 4, consistent with established limits on visual memory. These results point to the need for a body of empirical studies that move beyond two-value ratio judgments as a baseline for reliably ranking the quality of a visual channel, including testing new tasks (detection of trends or motifs), timescales (immediate computation, or later comparison), and the number of values (from a handful, to thousands).

Upregulated miR-9-5p inhibits osteogenic differentiation of bone marrow mesenchymal stem cells under high glucose treatment.

INTRODUCTION: Diabetic osteoporosis (DOP) is a chronic diabetic complication, which is attributed to high glucose (HG)-induced dysfunction of bone marrow mesenchymal stem cells (BMSCs). Studies have revealed that microRNAs (miRNAs) play critical roles in osteogenic differentiation of BMSCs in DOP. Here, the role of miR-9-5p in DOP progression was explored. MATERIALS AND METHODS: The rat model of DOP was established by intraperitoneal injection of streptozotocin (STZ). BMSCs were treated with high glucose (HG) to establish in vitro models. Gene expression in BMSCs and bone tissues of rats was tested by RT-qPCR. The degree of osteogenic differentiation of BMSCs was examined by Alizarin Red staining and ALP activity analysis. The protein levels of collagen-I (COL1), osteocalcin (OCN), osteopontin (OPN), runt-related transcription factor-2 (RUNX2), and DEAD-Box Helicase 17 (DDX17) in BMSCs were evaluated by western blotting. The interaction between miR-9-5p and DDX17 was identified by luciferase reporter assay. H&E staining was used to test morphological structure of femurs of rats with STZ treatment. RESULTS: MiR-9-5p was overexpressed in HG-treated BMSCs, while DDX17 was downregulated. Functionally, miR-9-5p knockdown promoted BMSCs osteogenic differentiation under HG condition. Mechanically, miR-9-5p targeted DDX17. DDX17 knockdown reversed the effect of miR-9-5p silencing on osteogenic differentiation of HG-treated BMSCs. In in vivo studies, miR-9-5p downregulation ameliorated the DOP condition of rats and miR-9-5p expression was negatively correlated with DDX17 expression in bone tissues of rats with STZ treatment. CONCLUSION: MiR-9-5p knockdown promotes HG-induced osteogenic differentiation BMSCs in vitro and mitigates the DOP condition of rats in vivo by targeting DDX17.

Reference interval for urinary neutrophil gelatinase-associated lipocalin in healthy adults in Jiangsu region in Eastern China: a multicenter study.

Aim: We explored the concentrations of urinary neutrophil gelatinase-associated lipocalin (NGAL) in healthy adults in the Jiangsu region in Eastern China and established a reference interval using latex-enhanced immunoturbidimetry to provide important guidelines for the interpretation and application of urinary NGAL in clinical practice. Methods: In total, 1970 eligible subjects from four regions were included in this study. The urinary NGAL levels were measured using an AU5800 automatic biochemical analyzer with its matched reagents. The urinary NGAL reference interval was established using the one-sided percentile method (95th percentile). Results: The urinary NGAL data were non-normally distributed. The urinary NGAL levels were not significantly different by sex or age. Therefore, the urinary NGAL reference interval in healthy adults in the Jiangsu region in Eastern China was <87.5 ng/ml (95th percentile of the upper limit). Conclusion: Urinary NGAL reference interval will play an important role in promoting the clinical value of urinary NGAL.

Significance of serum miR-29a in the occurrence and progression of diabetic nephropathy: A cross-sectional study.

BACKGROUND: Diabetic nephropathy (DN), a common microvascular complication of type 2 diabetes mellitus (T2DM), is an important factor causing chronic kidney disease. However, the relationship between miR-29a and DN remains unknown. Therefore, a cross-sectional study was conducted to identify a potential molecular biomarker for DN prevention and management by detecting the serum miR-29a levels. METHODS: The serum miR-29a levels were measured in 360 subjects (180 T2DM patients and 180 healthy controls) using quantitative reverse transcription PCR (qRT-PCR), and other conventional indicators were measured and analysed. A binary logistic regression was used to evaluate the DN risk factors; a receiver operating characteristic (ROC) curve was applied to analyse the diagnostic efficacy of miR-29a for DN, and a Spearman's rank correlation analysis was used to evaluate the correlation between serum miR-29a and cystatin C. RESULTS: The serum miR-29 levels in the T2DM patients were higher than those in the healthy subjects and significantly increased with the progression of DN (p < 0.05). Serum miR-29a and cystatin C are independent predictors of the occurrence of DN. Compared with a single indicator, the combination of serum miR-29a and cystatin C has better DN diagnostic performance. In addition, the serum miR-29a levels were positively correlated with cystatin C in the patients with DN (r = 0.521, p < 0.001). CONCLUSION: The expression of serum miR-29a was significantly associated with the occurrence and progression of DN and is expected to become a potential biomarker for the diagnosis of DN.

Application of a six sigma model to evaluate the analytical performance of urinary biochemical analytes and design a risk-based statistical quality control strategy for these assays: A multicenter study.

BACKGROUND: The six sigma model has been widely used in clinical laboratory quality management. In this study, we first applied the six sigma model to (a) evaluate the analytical performance of urinary biochemical analytes across five laboratories, (b) design risk-based statistical quality control (SQC) strategies, and (c) formulate improvement measures for each of the analytes when needed. METHODS: Internal quality control (IQC) and external quality assessment (EQA) data for urinary biochemical analytes were collected from five laboratories, and the sigma value of each analyte was calculated based on coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts for these urinary biochemical analytes were then generated. Risk-based SQC strategies and improvement measures were formulated for each laboratory according to the flowchart of Westgard sigma rules, including run sizes and the quality goal index (QGI). RESULTS: Sigma values of urinary biochemical analytes were significantly different at different quality control levels. Although identical detection platforms with matching reagents were used, differences in these analytes were also observed between laboratories. Risk-based SQC strategies for urinary biochemical analytes were formulated based on the flowchart of Westgard sigma rules, including run size and analytical performance. Appropriate improvement measures were implemented for urinary biochemical analytes with analytical performance lower than six sigma according to the QGI calculation. CONCLUSIONS: In multilocation laboratory systems, a six sigma model is an excellent quality management tool and can quantitatively evaluate analytical performance and guide risk-based SQC strategy development and improvement measure implementation.

Distribution of urinary N-acetyl-beta-D-glucosaminidase and the establishment of reference intervals in healthy adults.

BACKGROUND: Urinary N-acetyl-beta-D-glucosaminidase (NAG) plays an important role in the early diagnosis and progression of diseases related to renal tubular injury. We detected the urinary NAG concentration, assessed the preliminary statistics of its distribution, and established reference intervals for healthy adults in China using the rate method. METHODS: A total of 1,095 reference individuals (aged 20 to 79 years) met the requirements for inclusion in this study. Urinary NAG concentrations were detected using an AU5800 automatic biochemical analyzer with its matched reagents. The Kolmogorov-Smirnov test was used to analyze the normality of the data. According to the guidelines of C28-A3 and WS/T 402-2012, the reference intervals of urinary NAG were established using the nonparametric percentile method (unilateral 95th percentile). RESULTS: The urinary NAG data showed a non-normal distribution. The distribution of urinary NAG was significantly different by sex and age. Therefore, the reference intervals of urinary NAG were established using the rate method: males (aged 20-59 years) <19.4 U/L (90% CI: 18.0-20.3 U/L); males (aged 60-79 years) <22.3 U/L (90% CI: 20.2-22.6 U/L); females (aged 20-59 years) <15.7 U/L (90% CI: 15.2-16.5 U/L); and females (aged 60-79 years) <21.4 U/L (90% CI: 20.3-22.3 U/L). CONCLUSIONS: We established preliminary reference intervals of urinary NAG for healthy adults in China to provide guidance for health screening, auxiliary diagnosis, and treatment monitoring of renal tubule-related diseases.

Application of a six sigma model to the evaluation of the analytical performance of serum enzyme assays and the design of a quality control strategy for these assays: A multicentre study.

BACKGROUND: Six medical testing laboratories at six different sites in China participated in this study. We applied a six sigma model for (a) the evaluation of the analytical performance of serum enzyme assays at each of the laboratories, (b) the design of individualized quality control programs and (c) the development of improvement measures for each of the assays, as appropriate. METHODS: Internal quality control (IQC) and external quality assessment (EQA) data for selected serum enzyme assays were collected from each of the laboratories. Sigma values for these assays were calculated using coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts were generated using these parameters. IQC design and improvement measures were defined using the Westgard sigma rules. The quality goal index (QGI) was used to assist with identification of deficiencies (bias problems, precision problems, or their combination) affecting the analytical performance of assays with sigma values <6. RESULTS: Sigma values for the selected serum enzyme assays were significantly different at different levels of enzyme activity. Differences in assay quality in different laboratories were also seen, despite the use of identical testing instruments and reagents. Based on the six sigma data, individualized quality control programs were outlined for each assay with sigma <6 at each laboratory. CONCLUSIONS: In multi-location laboratory systems, a six sigma model can evaluate the quality of the assays being performed, allowing management to design individualized IQC programs and strategies for continuous improvement as appropriate for each laboratory. This will improve patient care, especially for patients transferred between sites within multi-hospital systems.