Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Background: Hemolysis is an important preanalytical factor that influences laboratory test results. Because arterial blood gas analysis (ABGA) is performed using whole blood, it is difficult to visually check whether a specimen is hemolyzed, and even blood gas analyzers cannot detect hemolysis. However, there is insufficient consensus on the parameters that are influenced by hemolyzed specimens. This study aimed to determine the effect of hemolysis on ABGA results. Methods: One hundred residual arterial blood specimens were collected from Severance Hospital between March and April 2022. Samples were aliquoted into three groups for mechanical hemolysis. Hemolysis was induced using 16-, 22-, and 26-gauge needles and measured using the Profile pHOx Ultra Blood Gas Analyzer (Nova Biomedical, USA). The remaining blood was centrifuged, and the hemolysis index was determined using the plasma. Results: Among the parameters, pH and K increased, whereas pCO 2 , Na,Ca 2+ , and HCO 3− decreased. The values of Hb, Mg2+ , and Hct did not change with the degree of hemolysis, although there was a difference between the two groups. The values of pCO 2 , Hb, K, and Ca 2+ increased as the degree of hemolysis increased, with % biases exceeding the desirable bias. Conclusions This study confirmed that hemolysis significantly influences pH, pCO 2 , and K. Therefore, when clinical findings and blood gas analysis results are inconsistent, clinicians should be cautious of spurious hemolysis when interpreting the results.

Purpose: Vascular endothelial growth factor tyrosine kinase inhibitors (TKIs) have been the standard of care for advanced and metastatic clear cell renal cell carcinoma (ccRCC). However, the therapeutic effect of TKI monotherapy remains unsatisfactory given the high rates of acquired resistance to TKI therapy despite favorable initial tumor response. Materials and Methods: To define the TKI-resistance mechanism and identify new therapeutic target for TKI-resistant ccRCC, an integrative differential gene expression analysis was performed using acquired resistant cohort and a public dataset. Sunitinib-resistant RCC cell lines were established and used to test their malignant behaviors of TKI resistance through in vitro and in vivo studies. Immunohistochemistry was conducted to compare expression between the tumor and normal kidney and verify expression of pathway-related proteins. Results: Integrated differential gene expression analysis revealed increased interferon-induced transmembrane protein 3 (IFITM3) expression in post-TKI samples. IFITM3 expression was increased in ccRCC compared with the normal kidney. TKI-resistant RCC cells showed high expression of IFITM3 compared with TKI-sensitive cells and displayed aggressive biologic features such as higher proliferative ability, clonogenic survival, migration, and invasion while being treated with sunitinib. These aggressive features were suppressed by the inhibition of IFITM3 expression and promoted by IFITM3 overexpression, and these findings were confirmed in a xenograft model. IFITM3-mediated TKI resistance was associated with the activation of TRAF6 and MAPK/AP-1 pathways. Conclusions These results demonstrate IFITM3-mediated activation of the TRAF6/MAPK/AP-1 pathways as a mechanism of acquired TKI resistance, and suggest IFITM3 as a new target for TKI-resistant ccRCC.

Genomic analysis indicated that the genome of Drosophila melanogaster contains more than 80 cytochrome P450 genes. To date, the enzymatic activity of these P450s has not been extensively studied. Here, the biochemical properties of CYP6A8 were characterized. CYP6A8 was cloned into the pCW vector, and its recombinant enzyme was expressed in Escherichia coli and purified using Ni2+ -nitrilotriacetate affinity chromatography. Its expression level was approximately 130 nmol per liter of culture. Purified CYP6A8 exhibited a low-spin state in the absolute spectra of the ferric forms. Binding titration analysis indicated that lauric acid and capric acid produced type І spectral changes, with Kd values 28 ± 4 and 144 ± 20 μM, respectively. Ultra-performance liquid chromatography–mass spectrometry analysis showed that the oxidation reaction of lauric acid produced (ω-1)-hydroxylated lauric acid as a major product and ω-hydroxy-lauric acid as a minor product. Steady-state kinetic analysis of lauric acid hydroxylation yielded a kcat value of 0.038 ± 0.002 min –1 and a Km value of 10 ± 2 μM. In addition, capric acid hydroxylation of CYP6A8 yielded kinetic parameters with a kcat value of 0.135 ± 0.007 min –1 and a Km value of 21 ± 4 μM. Because of the importance of various lipids as carbon sources, the metabolic analysis of fatty acids using CYP6A8 in this study can provide an understanding of the biochemical roles of P450 enzymes in many insects, including Drosophila melanogaster.

Background: Accurate measurement of glycated hemoglobin (HbA1c) is crucial for a diabetes diagnosis and subsequent patient management. The detection method and presence of variant Hb can interfere with HbA1c measurements. We evaluated the HbA1c-measuring performance of the DxC 700 AU (Beckman Coulter, Brea, CA, USA) immunoassay-based device in comparison with another immunoassay device and the reference method. Methods: A total of 120 normal and 14 variant Hb samples were analyzed using the Cobas c 513 (Roche Diagnostics, Mannheim, Germany) and DxC 700 AU analyzers. Variant Hb samples were also analyzed using the reference method, along with 20 normal samples. The accuracy, precision, linearity, and carryover were determined. Results: DxC 700 AU results strongly correlated with those of Cobas c 513 and exhibited accuracy in comparison with the reference method. The within-run, between-run, between-day, and total imprecision (%CV) values for the low- and high-concentration control materials were below 2%. The results of DxC 700 AU were linear over a wide HbA1c range (3.39%–18.30%). Although DxC 700 AU performed well in the presence of variant Hb, the HbA1c concentration was underestimated in the presence of fetal Hb. The possibility of interference from a high HbH proportion could not be ruled out. Conclusions The overall analytical performance of DxC 700 AU was acceptable. The device is accurate, precise, and linear over a wide HbA1c concentration range. Although DxC 700 AU results highly correlated with those of Cobas c 513, caution should be exercised in cases of high HbF and HbH concentrations.

Background: Despite the superiority of non-HDL cholesterol (non-HDL-C) and apolipoprotein B (ApoB) as lipid markers for atherosclerotic cardiovascular disease (ASCVD), these are only suitable as secondary markers. We compared LDL cholesterol (LDL-C), non-HDL-C, and ApoB concentrations with respect to the occurrence of cardiovascular disease in adults enrolled in the Korean Genome and Epidemiology Study (KoGES). Methods: We used information on age; sex; medical history; family history of ASCVD; current lipid-lowering therapy; current smoking status; and creatinine, total cholesterol, HDL-C, LDL-C, triglyceride, and ApoB concentrations from 5,872 KoGES participants without ASCVD. New ASCVD development was monitored during the 8-year follow-up period. Adjusted hazard ratios (aHRs) for ASCVD of LDL-C, non-HDL-C, and ApoB concentrations were calculated based on the multivariate Cox regression analyses. The participants were also grouped as low and high according to the median values for each lipid marker, and calculated aHRs of each group combined by two lipid makers. Results: ApoB showed the highest aHR per 1-SD for ASCVD (1.26; 95% confidence interval [CI], 1.11–1.43), followed by non-HDL-C (1.25; 95% CI, 1.11–1.41) and LDL-C (1.20; 95% CI, 1.06–1.37). The group with low LDL-C and high ApoB concentrations had a significantly higher aHR for ASCVD (1.61; 95% CI, 1.05–2.48) compared to the reference group values (low LDL-C and low ApoB concentrations). The aHR for the group with high LDL-C and low ApoB concentrations was not significant (1.30; 95% CI, 0.79–2.16). Conclusions ApoB, non-HDL-C, and LDL-C are independent risk factors for ASCVD. Increases in the aHR per 1-SD for ASCVD were more strongly affected by ApoB, followed by non-HDL-C and LDL-C. Participants with low LDL-C and high ApoB concentrations showed increased ASCVD risk. For individuals with ASCVD risk factors, even those presenting normal LDL-C concentrations, measuring ApoB concentrations can provide useful information for better evaluation of ASCVD risk.