Identification and quantification of acetyl tributyl citrate (ATBC) metabolites using human liver microsomes and human urine.

Plasticizers are chemicals that make plastics flexible, and phthalates are commonly used. Due to the toxic effects of phthalates, there is increasing use of non-phthalate plasticizers like acetyl tributyl citrate (ATBC). ATBC has emerged as a safer alternative, yet concerns about its long-term safety persist due to its high leachability and potential endocrine-disrupting effects. This study aims to identify ATBC metabolites using human liver microsomes and suspect screening methods, and to explore potential urinary biomarkers for ATBC exposure. Using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry, we identified ATBC metabolites, including acetyl dibutyl citrate (ADBC), tributyl citrate (TBC), and dibutyl citrate (DBC). Urine samples from 15 participants revealed the presence of ADBC in 5, TBC in 11, and DBC in all samples, with DBC concentrations pointedly higher than the other metabolites. These metabolites show promise as biomarkers for ATBC exposure, though further validation with human data is required. Our results underscore the need for comprehensive studies on ATBC metabolism, exposure pathways, and urinary excretion to accurately assess human exposure levels.

Quantitative analysis of blooming artifact caused by calcification based on X-ray energy difference using computed tomography.

Blooming artifacts caused by calcifications appearing on computed tomography (CT) images lead to an underestimation of the coronary artery lumen size, and higher X-ray energy levels are suggested to reduce the blooming artifacts with subjective visual assessment. This study aimed to evaluate the effect of higher X-ray energy levels on the quantitative measurement of adjacent pixels affected by calcification using CT images. In this two-part study, CT images were acquired from dual-energy CT scanners by changing the X-ray energy levels such as kilovoltage peak (kVp) and kilo-electron volts (keV). Adjacent pixels affected by calcification were measured using the brightened length, excluding the actual calcified length, as determined by the full width at third maximum. In a separate clinical study, the adjacent affected pixels associated with 23 calcifications across 10 patients were measured using the same method as that used in the phantom study. Phantom and clinical studies showed that the change in kVp (field of view [FOV] 300 mm: p = 0.167, 0.494, and 0.861 for vendors 1, 2, and 3, respectively) and keV levels (p = 0.178 for vendor 2) failed to reduce the adjacent pixels affected by calcification, respectively. Moreover, the change in keV levels showed different aspects of adjacent pixels affected by calcification in the phantom study (FOV 300 mm: no significant difference [p = 0.191], increase [p < 0.001], and decrease [p < 0.001] for vendors 1, 2, and 3, respectively). Quantitative measurements revealed no significant relationship between higher X-ray energy levels and the adjacent pixels affected by calcification.

A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software.

Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the most important factors. This study aimed to analyze the performance of the coronary artery segmentation of a software platform with a deep learning-based location-adaptive threshold method (DL-LATM) against commercially available software platforms using CCTA. The dataset from intravascular ultrasound (IVUS) of 26 vessel segments from 19 patients was used as the gold standard to evaluate the performance of each software platform. Statistical analyses (Pearson correlation coefficient [PCC], intraclass correlation coefficient [ICC], and Bland-Altman plot) were conducted for the lumen or plaque parameters by comparing the dataset of each software platform with IVUS. The software platform with DL-LATM showed the bias closest to zero for detecting lumen volume (mean difference = -9.1 mm3, 95% confidence interval [CI] = -18.6 to 0.4 mm3) or area (mean difference = -0.72 mm2, 95% CI = -0.80 to -0.64 mm2) with the highest PCC and ICC. Moreover, lumen or plaque area in the stenotic region was analyzed. The software platform with DL-LATM showed the bias closest to zero for detecting lumen (mean difference = -0.07 mm2, 95% CI = -0.16 to 0.02 mm2) or plaque area (mean difference = 1.70 mm2, 95% CI = 1.37 to 2.03 mm2) in the stenotic region with significantly higher correlation coefficient than other commercially available software platforms (p < 0.001). The result shows that the software platform with DL-LATM has the potential to serve as an aiding system for CAD evaluation.

[Coronary CT Angiography-Based Assessment of Coronary in-Stent Restenosis: A Journey through Past and Present Trends]. / 관상동맥 CT ì¡°ì˜ìˆ ì„ 활용한 ìŠ¤í íŠ¸ 재협착 평가: 과거와 현재 ìµœì‹ ë™í–¥ìœ¼ë¡œì˜ ì—¬ì •.

Treatment of patients with coronary artery disease commonly involves the use of balloon-expandable stent placements, currently recognized as the most prevalent approach for coronary artery revascularization. Nevertheless, the occurrence of restenosis remains a significant complication following percutaneous coronary interventions. The diagnostic role of coronary CT angiography (CCTA) in detecting stent restenosis has limitations primarily attributable to challenges in accurately discerning the lumen, due to issues such as blooming and motion artifacts. As a result, many cases often necessitate a transition to conventional coronary angiography. However, recent advancements in CT technology have led to notable improvements in both sensitivity and specificity, underscoring the growing significance of CCTA as a diagnostic tool. The consistent reporting of high negative predictive value is particularly noteworthy. This review aims to explore the historical context, current status, and recent trends in diagnosing coronary artery stent restenosis using CCTA.

Impact of Myocardial Viability on Long-term Outcomes after Surgical Revascularization.

BACKGROUND: This study was conducted to evaluate whether myocardial viability assessed with cardiac magnetic resonance (CMR) affected long-term clinical outcomes after coronary artery bypass grafting (CABG) in patients with ischemic cardiomyopathy (ICMP). METHODS: Preoperative CMR with late gadolinium enhancement (LGE) was performed in 103 patients (64.9 ± 10.1 years, male:female = 82:21) with 3-vessel disease and left ventricular dysfunction (ejection fraction ≤ 0.35). Transmural extent of LGE was evaluated on a 16-segment model, and transmurality was graded on a 5-point scale: grades-0, absence; 1, 1 to 25%; 2, 26 to 50%; 3, 51 to 75%; 4, 76 to 100%. Median follow-up duration was 65.5 months (interquartile range = 27.5-95.3 months). Primary endpoint was the composite of all-cause mortality or hospitalization for congestive heart failure. RESULTS: Operative mortality was 1.9%. During the follow-up, all-cause mortality and readmission for congestive heart failure occurred in 29 and 8 patients, respectively. The cumulative incidence of the primary endpoint was 31.3 and 46.8% at 5 and 10 years, respectively. Multivariable analysis demonstrated that the number of segments with LGE grade 4 was a significant risk factor (hazard ratio 1.42, 95% confidence interval 1.10-1.83, p = 0.007) for the primary endpoint among the variables assessed by CMR. Other risk factors included age, dialysis, chronic obstructive pulmonary disease, and EuroSCORE II. CONCLUSION: The number of myocardial segments with transmurality of LGE >75% might be a prognostic factor associated with the composite of all-cause mortality or hospitalization for congestive heart failure after CABG in patients with 3-vessel disease and ICMP.

Deep Learning-Based Automated Quantification of Coronary Artery Calcification for Contrast-Enhanced Coronary Computed Tomographic Angiography.

BACKGROUND: We evaluated the accuracy of a deep learning-based automated quantification algorithm for coronary artery calcium (CAC) based on enhanced ECG-gated coronary CT angiography (CCTA) with dedicated coronary calcium scoring CT (CSCT) as the reference. METHODS: This retrospective study included 315 patients who underwent CSCT and CCTA on the same day, with 200 in the internal and 115 in the external validation sets. The calcium volume and Agatston scores were calculated using both the automated algorithm in CCTA and the conventional method in CSCT. The time required for computing calcium scores using the automated algorithm was also evaluated. RESULTS: Our automated algorithm extracted CACs in less than five minutes on average with a failure rate of 1.3%. The volume and Agatston scores by the model showed high agreement with those from CSCT with concordance correlation coefficients of 0.90-0.97 for the internal and 0.76-0.94 for the external. The accuracy for classification was 92% with a 0.94 weighted kappa for the internal and 86% with a 0.91 weighted kappa for the external set. CONCLUSIONS: The deep learning-based and fully automated algorithm efficiently extracted CACs from CCTA and reliably assigned categorical classification for Agatston scores without additional radiation exposure.

Functional Differentiation of Cyclins and Cyclin-Dependent Kinases in Giardia lamblia.

Cyclin-dependent kinases (CDKs) are serine/threonine kinases that control the eukaryotic cell cycle. Limited information is available on Giardia lamblia CDKs (GlCDKs), GlCDK1 and GlCDK2. After treatment with the CDK inhibitor flavopiridol-HCl (FH), division of Giardia trophozoites was transiently arrested at the G1/S phase and finally at the G2/M phase. The percentage of cells arrested during prophase or cytokinesis increased, whereas DNA synthesis was not affected by FH treatment. Morpholino-mediated depletion of GlCDK1 caused arrest at the G2/M phase, while GlCDK2 depletion resulted in an increase in the number of cells arrested at the G1/S phase and cells defective in mitosis and cytokinesis. Coimmunoprecipitation experiments with GlCDKs and the nine putative G. lamblia cyclins (Glcyclins) identified Glcyclins 3977/14488/17505 and 22394/6584 as cognate partners of GlCDK1 and GlCDK2, respectively. Morpholino-based knockdown of Glcyclin 3977 or 22394/6584 arrested cells in the G2/M phase or G1/S phase, respectively. Interestingly, GlCDK1- and Glcyclin 3977-depleted Giardia showed significant flagellar extension. Altogether, our results suggest that GlCDK1/Glcyclin 3977 plays an important role in the later stages of cell cycle control and in flagellar biogenesis. In contrast, GlCDK2 along with Glcyclin 22394 and 6584 functions from the early stages of the Giardia cell cycle. IMPORTANCE Giardia lamblia CDKs (GlCDKs) and their cognate cyclins have not yet been studied. In this study, the functional roles of GlCDK1 and GlCDK2 were distinguished using morpholino-mediated knockdown and coimmunoprecipitation. GlCDK1 with Glcyclin 3977 plays a role in flagellum formation as well as cell cycle control of G. lamblia, whereas GlCDK2 with Glcyclin 22394/6584 is involved in cell cycle control.

Results after Tricuspid Valve Surgery for Preserved and Dysfunctional Right Ventricle.

BACKGROUND: This study aimed to compare long-term outcomes after tricuspid valve (TV) repair (TVr) with those after TV replacement (TVR) by adjusting the right ventricular (RV) volume and function. METHODS: We enrolled 147 patients who underwent TVr (n = 78) and TVR (n = 69) for grade 3 or 4 tricuspid regurgitation and had preoperative cardiac magnetic resonance data. Long-term clinical outcomes were compared between the two groups using inverse probability treatment weighting (IPTW) to adjust for differences in preoperative characteristics between the two groups. Subgroup analyses were performed in patients with preserved and dysfunctional RV (ejection fraction < 50%). RESULTS: There were no significant differences in operative mortality or postoperative complications between the two groups before and after the IPTW adjustment. Five- and 10-year overall survival rates were 84.2 and 67.1%, respectively. Five- and 10-year cumulative incidences of TV-related events (TVREs) were 33.1 and 55.6%, respectively. There were no significant differences in overall survival and cumulative incidence of TVREs after IPTW adjustment (p = 0.236 and p = 0.989, respectively). The risk-adjusted overall survival was marginally higher in the TVr group of patients with preserved RV function (p = 0.054), while no such significant difference was found between the two groups of patients with dysfunctional RV (p = 0.513). CONCLUSION: Adjusted long-term clinical outcomes after TVr and TVR were comparable. TVr might be beneficial for patients with preserved RV function in terms of long-term survival; however, this benefit might disappear in patients with RV dysfunction.

Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring.

OBJECTIVE: To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) using deep learning (DL)-based denoising technique. METHODS: This retrospective, intra-individual comparative study consisted of four image datasets of 131 participants who underwent LDCT and calcium CT on the same day between January and February 2020; 1-mm LDCT with DL, 1-mm LDCT with iterative reconstruction (IR), 3-mm LDCT, and calcium CT. CACS from calcium CT were considered as reference and CACS were categorized as 0, 1-10, 11-100, 101-400, and > 400. We compared CACS from LDCTs with that from calcium CT. RESULTS: Mean CACS was 104.8 ± 249.1 and proportion of positive CACS was 45% (59/131). CACS from LDCT images tended to be underestimated than those from calcium CT: 1-mm LDCT with DL (93.5 ± 249.6, p = 0.002), 1-mm LDCT with IR (94.7 ± 249.9, p < 0.001), and 3-mm LDCT (90.3 ± 245.3, p = 0.004). All LDCT datasets showed excellent agreement with calcium CT: intraclass correlation coefficient (ICC) = 0.961 (95% confidence interval (CI), 0.945-0.972) for DL, 0.969 (95% CI, 0.956-0.978) for IR, and 0.952 (95% CI, 0.932-0.966) for 3-mm LDCT; weighted kappa for CACS classification, 0.930 (95% CI, 0.893-0.966) for 1-mm LDCT with DL, 0.908 (95% CI, 0.866-0.950) for 1-mm LDCT with IR, and 0.846 (95% CI, 0.780-0.912) for 3-mm LDCT. The accuracy of CACS classification of 1-mm LDCT with DL (90%) tended to be better than 1-mm LDCT with IR (87%) and 3-mm LDCT (84.7%) (p = 0.10). CONCLUSION: DL-based noise reduction algorithm can offer reliable calcium scores in 1-mm LDCT reconstructed with sharp kernel. KEY POINTS: • Deep learning (DL)-based noise reduction enables calcium scoring at 1-mm, sharp kernel reconstructed low-dose chest CT (LDCT). • Both iterative reconstruction and DL-based noise reduction underestimated calcium score, but agreement were excellent with those from calcium CT. • Accuracy of categorical classification of calcium scoring tended to be highest in 1-mm LDCT with DL compared to 1-mm LDCT with IR and 3-mm LDCT (90%, 87%, and 84.7%, p = 0.10).

Reliability and feasibility of visual grading systems and quantitative indexes on [99mTc]Tc-DPD imaging for cardiac amyloidosis.

We aimed to evaluate the reliability and feasibility of visual grading systems and various quantitative indexes of [99mTc]Tc-DPD imaging for cardiac amyloidosis (CA). Patients who underwent [99mTc]Tc-DPD imaging with suspicion of CA were enrolled. On the planar image, myocardial uptake was visually graded using Perugini's and Dorbala's methods (PS and DS). As [99mTc]Tc-DPD indexes, heart-to-whole body ratio (H/WB) and heart-to-contralateral lung ratio (H/CL) were measured on planar image. SUVmax, SUVmean, total myocardial uptake (TMU), and C-index were measured on SPECT/CT. Inter-observer agreement of the indexes and their association with visual grading and clinical factors were evaluated. A total of 152 [99mTc]Tc-DPD images, of which 18 were positive, were analyzed. Inter-observer agreement was high for both DS (κ = 0.95) and PS (κ = 0.96). However, DS showed a higher correlation with quantitative indexes than PS. Inter-observer agreement was also high for SPECT/CT indexes, particularly SUVmax. SUVmax was significantly different between different DS groups (P = 0.014-0.036), and showed excellent correlations with H/WB and H/CL (r = 0.898 and 0.910). SUVmax also showed significant differences between normal, AL, and ATTR pathology (P = 0.022-0.037), and a significant correlation with extracellular volume on cardiac MRI (r = 0.772, P < 0.001). DS is a visual grading system for CA that is more significantly matched with quantitative indexes than PS. SUVmax is a reliable quantitative index on SPECT/CT, with a high inter-observer agreement, correlations with the visual grade, and potential association with cardiac MRI findings.