Gender-dependent difference in serum paraoxonase 1 levels of Hanwoo, Korean native cattle, and a positive association with meat quality

Objective Paraoxonase 1 (PON1), a calcium-dependent serum enzyme, has been shown to be involved in lipid metabolism. In this study, we examined the putative correlation of the serum PON1 level of Hanwoo, Korean native cattle, with gender and meat quality grade. Methods PON1 levels were estimated by determining the arylesterase and paraoxonase activities (AE and PO, respectively) in serum samples from Hanwoo individuals (n = 56). Serum PON1 levels were analyzed in different gender groups (female [n = 21], castrated male [n = 17], and male [n = 18]), and meat quality grades (≥1 [n = 23], 2 [n = 21], and 3 [n = 12]). Results Serum PON1 levels were similar in female (AE = 120±55 U/mL, PO = 84±43 mU/mL) and castrated male (123±44 U/mL, PO = 89±30 mU/mL), while male showed a significantly lower level (AE = 65±43 U/mL, PO = 44±34 mU/mL). Furthermore, analysis of serum PON1 levels in three different grades of meat quality showed similar levels in the grades ≥1 (AE = 118±49 U/mL, PO = 84±37 mU/mL) and 2 (AE = 116±54 U/mL, PO = 82±43 mU/mL), while the level was significantly lower in the grade 3 (AE = 58±35 U/mL, PO = 39±27 mU/mL) of lower meat quality. Conclusion We discovered the gender-dependent differences in serum PON1 levels of Hanwoo and a positive association of the serum PON1 level with meat quality. Results in this study suggest that PON1 would be a useful serum marker for preliminary screening of Hanwoo individuals with high-quality meat and applicable for genetic improvement

Effects of feeding ethanol on growth performances, carcass characteristics, and lipid metabolism of finishing Korean cattle (Hanwoo) steers

Objective The purpose of this study was to determine the effects of feeding ethanol on growth performances, carcass characteristics, and lipid metabolism of finishing Korean cattle (Hanwoo) steers. Methods Thirty (30) Hanwoo steers (average 25.1 months of age, body weight 660.1 kg) were assigned to three treatments: control (0% ethanol), E-3 (1.44% ethanol for 3 months), or E-5 (0.72% ethanol for 2 months followed by 1.44% ethanol for 3 months). The animals were allotted by treatment group into six pens and fed concentrate and perennial ryegrass. Ethanol (30%, v/v) was supplemented into drinking water twice a day to meet final concentrations based on average water consumption of finishing Hanwoo steers. Results There were no statistical differences among the groups in final body weight, average daily gain, or carcass yield grade indices such as cold carcass weight, fat thickness, and loin area. The marbling score tended (p = 0.228) to increase with the highest score (6.7) in the E-5 group followed by 6.3 and 6.0 in E-3 and control groups, respectively. The appearance frequencies of quality grades of 1++ (the best), 1+, 1, and 2, were; 30%, 50%, 0%, and 20% for control, 10%, 80%, 10%, and 0% for E-3, and 10%, 80%, 0%, and 10% for E-5 groups, respectively, indicating improvements of quality grades by feeding ethanol. Concentrations of serum glucose tended to decrease whereas those of insulin and non-esterified fatty acid to increase by feeding ethanol (E-3 and E-5; p>0.05). Conclusion Feeding ethanol directly into drinking water of finishing Hanwoo steers stimulated lipogenesis in intramuscular adipose tissue (marbling) and thereby improved carcass quality grade. The serum metabolites results supported the hypothesis of lipolysis of existing adipose tissue, such as abdominal fats, and lipogenesis in intramuscular adipocytes

Non-randomized comparison between revascularization and deferral for intermediate coronary stenosis with abnormal fractional flow reserve and preserved coronary flow reserve.

Limited data are available regarding comparative prognosis after percutaneous coronary intervention (PCI) versus deferral of revascularization in patients with intermediate stenosis with abnormal fractional flow reserve (FFR) but preserved coronary flow reserve (CFR). From the International Collaboration of Comprehensive Physiologic Assessment Registry (NCT03690713), a total of 330 patients (338 vessels) who had coronary stenosis with FFR ≤ 0.80 but CFR > 2.0 were selected for the current analysis. Patient-level clinical outcome was assessed by major adverse cardiac events (MACE) at 5 years, a composite of all-cause death, target-vessel myocardial infarction (MI), or target-vessel revascularization. Among the study population, 231 patients (233 vessels) underwent PCI and 99 patients (105 vessels) were deferred. During 5 years of follow-up, cumulative incidence of MACE was 13.0% (31 patients) without significant difference between PCI and deferred groups (12.7% vs. 14.0%, adjusted HR 1.301, 95% CI 0.611-2.769, P = 0.495). Multiple sensitivity analyses by propensity score matching and inverse probability weighting also showed no significant difference in patient-level MACE and vessel-specific MI or revascularization. In this hypothesis-generating study, there was no significant difference in clinical outcomes between PCI and deferred groups among patients with intermediate stenosis with FFR ≤ 0.80 but CFR > 2.0. Further study is needed to confirm this finding.Clinical Trial Registration: International Collaboration of Comprehensive Physiologic Assessment Registry (NCT03690713; registration date: 10/01/2018).S

A CREDENCE Trial Substudy

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.OBJECTIVES: The study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography angiography (AI-QCT) analyses to core lab-interpreted coronary computed tomography angiography (CTA), core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). BACKGROUND: Clinical reads of coronary CTA, especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. AI-based solutions applied to coronary CTA may overcome these limitations. METHODS: Coronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. RESULTS: Disease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. CONCLUSIONS: A novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab-interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275).proofepub_ahead_of_prin

The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography

Publisher Copyright: © 2022 The AuthorsObjectives: To determine whether coronary computed tomography angiography (CCTA) scanning, scan preparation, contrast, and patient based parameters influence the diagnostic performance of an artificial intelligence (AI) based analysis software for identifying coronary lesions with ≥50% stenosis. Background: CCTA is a noninvasive imaging modality that provides diagnostic and prognostic benefit to patients with coronary artery disease (CAD). The use of AI enabled quantitative CCTA (AI-QCT) analysis software enhances our diagnostic and prognostic ability, however, it is currently unclear whether software performance is influenced by CCTA scanning parameters. Methods: CCTA and quantitative coronary CT (QCT) data from 303 stable patients (64 ± 10 years, 71% male) from the derivation arm of the CREDENCE Trial were retrospectively analyzed using an FDA-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. The algorithm's diagnostic performance measures (sensitivity, specificity, and accuracy) for detecting coronary lesions of ≥50% stenosis were determined based on concordance with QCA measurements and subsequently compared across scanning parameters (including scanner vendor, model, single vs dual source, tube voltage, dose length product, gating technique, timing method), scan preparation technique (use of beta blocker, use and dose of nitroglycerin), contrast administration parameters (contrast type, infusion rate, iodine concentration, contrast volume) and patient parameters (heart rate and BMI). Results: Within the patient cohort, 13% demonstrated ≥50% stenosis in 3 vessel territories, 21% in 2 vessel territories, 35% in 1 vessel territory while 32% had 400 mg/ml 95.2%; p = 0.0287) in the context of low injection flow rates. On a per patient basis there were no significant differences in AI diagnostic performance measures across all measured scanner, scan technique, patient preparation, contrast, and individual patient parameters. Conclusion: The diagnostic performance of AI-QCT analysis software for detecting moderate to high grade stenosis are unaffected by commonly used CCTA scanning parameters and across a range of common scanning, scanner, contrast and patient variables. Condensed abstract: An AI-enabled quantitative CCTA (AI-QCT) analysis software has been validated as an effective tool for the identification, quantification and characterization of coronary plaque and stenosis through comparison to blinded expert readers and quantitative coronary angiography. However, it is unclear whether CCTA screening parameters related to scanner parameters, scan technique, contrast volume and rate, radiation dose, or a patient's BMI or heart rate at time of scan affect the software's diagnostic measures for detection of moderate to high grade stenosis. AI performance measures were unaffected across a broad range of commonly encountered scanner, patient preparation, scan technique, intravenous contrast and patient parameters.publishersversionpublishe

Clinical Characteristics of a Nationwide Hospital-based Registry of Mild-to-Moderate Alzheimer's Disease Patients in Korea: A CREDOS (Clinical Research Center for Dementia of South Korea) Study

With rapid population aging, the socioeconomic burden caused by dementia care is snowballing. Although a few community-based studies of Alzheimer's disease (AD) have been performed in Korea, there has never been a nationwide hospital-based study thereof. We aimed to identify the demographics and clinical characteristics of mild-to-moderate AD patients from the Clinical Research Center for Dementia of Korea (CREDOS) registry. A total of 1,786 patients were consecutively included from September 2005 to June 2010. Each patient underwent comprehensive neurological examination, interview for caregivers, laboratory investigations, neuropsychological tests, and brain MRI. The mean age was 74.0 yr and the female percentage 67.0%. The mean period of education was 7.1 yr and the frequency of early-onset AD (< 65 yr old) was 18.8%. Among the vascular risk factors, hypertension (48.9%) and diabetes mellitus (22.3%) were the most frequent. The mean score of the Korean version of Mini-Mental State Examination (K-MMSE) was 19.2 and the mean sum of box scores of Clinical Dementia Rating (CDR-SB) 5.1. Based on the well-structured, nationwide, and hospital-based registry, this study provides the unique clinical characteristics of AD and emphasizes the importance of vascular factors in AD in Korea

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence

Objective: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT). Methods: This is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (\u3c50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age \u3c65 and ≥65 years. Results: The cohort was 64.4±10.2 years and 29% women. Overall, patients \u3e65 had more PV and CP than patients \u3c65. On a lesion level, patients \u3e65 had more CP than younger patients in both obstructive (29.2 mm3 vs 48.2 mm3; p\u3c0.04) and non-obstructive lesions (22.1 mm3 vs 49.4 mm3; p\u3c0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p\u3c0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients. Conclusion: AI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment