Secondary metabolite fingerprinting, anti-pathogenic activity, elite chemotype selection and conservation of Curcuma caesia- an ethnomedicinally underutilized species

Curcuma caesia Roxb. is an ethnomedicinally important, essential oil (EO) yielding aromatic plant. A total of twelve accessions of this plant rhizome were collected from six different agro-climatic zones of West Bengal, India and evaluated for their antimicrobial activities against eight disease-causing, multi-drug-resistant pathogenic strains of urinary-tract infection and respiratory-tract infection. The EO and extracts demonstrated antibacterial activity, with the highest inhibition zone of 18.00 ± 0.08 and 17.50 ± 0.14 mm against Klebsiella pneumoniae by accession 06, even where all the broad-spectrum antibiotics failed to respond. In this study, we employed high-performance thin-layer chromatography (HPTLC) to quantify curcumin, the primary secondary metabolite of C. caesia, and the highest 0.228 mg/gm of curcumin resulted from accession 06. Hence, on the basis of all aspects, accession 06 was identified as the elite chemotype among all twelve accessions. The chemical profiling of EO from accession 06 was done using gas chromatography-mass spectroscopy (GC-MS). Conceivably, about 13 medicinally significant compounds were detected. As this plant species is seasonal and has difficulties in conventional breeding due to dormancy, it must be conserved through in vitro tissue culture for a steady supply throughout the year in massive amounts for agricultural demand. A maximum number of 19.28 ± 0.37 shoots has been obtained in MS medium fortified with 6-Benzylaminopurine, Kinetin, and Naphthalene acetic acid. The genetic uniformity of the plants has been studied through Start Codon Targeted Polymorphism. Therefore, this study must help meet the need for essential phytoactive compounds through a simple, validated, and reproducible plant tissue culture protocol throughout the year.

Muscle Transcriptome Sequencing Revealed Thermal Stress-Responsive Regulatory Genes in Farmed Rohu, Labeo rohita (Hamilton, 1822)

Rohu, Labeo rohita, is one of the most important aquaculture species in the Indian subcontinent. Understanding the molecular-level physiological responses to thermal stress or climate change is essential. In the present work, transcriptome sequencing was carried out in the muscle tissue of the rohu in response to heat stress (35 °C) in comparison with the control (28 °C). A total of 125 Gb of sequence data was generated, and the raw-reads were filtered and trimmed, which resulted in 484 million quality reads. Reference-based assembly of reads was performed using L. rohita genome, and a total of 90.17% of reads were successfully mapped. A total of 37,462 contigs were assembled with an N50 value of 1854. The differential expression analysis revealed a total of 107 differentially expressed genes (DEGs) (15 up-, 37 down-, and 55 neutrally regulated) as compared to the control group (Log2FC > 2, P < 0.05). Gene enrichment analysis of DEGs indicates that transcripts were associated with molecular, biological, and cellular activities. The randomly selected differentially expressed transcripts were validated by RT-qPCR and found consistent expression patterns in line with the RNA-seq data. Several transcripts such as SERPINE1(HSP47), HSP70, HSP90alpha, Rano class II histocompatibility A beta, PGC-1 and ERR-induced regulator, proto-oncogene c-Fos, myozenin2, alpha-crystallin B chain-like protein, angiopoietin-like protein 8, and acetyl-CoA carboxylases have been identified in muscle tissue of rohu that are associated with stress/immunity. This study identified the key biomarker SERPINE1 (HSP47), which showed significant upregulation (~ 2- to threefold) in muscle tissue of rohu exposed to high temperature. This study can pave a path for the identification of stress-responsive biomarkers linked with thermal adaptations in the farmed carps.

DNA Methylation Profiling of Ovarian Tissue of Climbing Perch (Anabas testudienus) in Response to Monocrotophos Exposure

Epigenetic modifications like DNA methylation can alter an organism's phenotype without changing its DNA sequence. Exposure to environmental toxicants has the potential to change the resilience of aquatic species. However, little information is available on the dynamics of DNA methylation in fish gonadal tissues in response to organophosphates. In the present work, reduced-representation bisulfite sequencing was performed to identify DNA methylation patterns in the ovarian tissues of Anabas testudienus exposed to organophosphates, specifically monocrotophos (MCP). Through sequencing, an average of 41,087 methylated cytosine sites were identified and distributed in different parts of genes, i.e., in transcription start sites (TSS), promoters, exons, etc. A total of 1058 and 1329 differentially methylated regions (DMRs) were detected as hyper-methylated and hypo-methylated in ovarian tissues, respectively. Utilizing whole-genome data of the climbing perch, the DMRs, and their associated overlapping genes revealed a total of 22 genes within exons, 45 genes at transcription start sites (TSS), and 218 genes in intergenic regions. Through gene ontology analysis, a total of 16 GO terms particularly involved in ovarian follicular development, response to oxidative stress, oocyte maturation, and multicellular organismal response to stress associated with reproductive biology were identified. After functional enrichment analysis, relevant DMGs such as steroid hormone biosynthesis (Cyp19a, 11-beta-HSD, 17-beta-HSD), hormone receptors (ar, esrrga), steroid metabolism (StAR), progesterone-mediated oocyte maturation (igf1ar, pgr), associated with ovarian development in climbing perch showed significant differential methylation patterns. The differentially methylated genes (DMGs) were subjected to analysis using real-time PCR, which demonstrated altered gene expression levels. This study revealed a molecular-level alteration in genes associated with ovarian development in response to chemical exposure. This work provides evidence for understanding the relationship between DNA methylation and gene regulation in response to chemicals that affect the reproductive fitness of aquatic animals.

Salvage Using Polatuzumab Vedotin Based Therapy in Relapsed Refractory Large B-Cell Lymphomas: Early Experience from a Real-World Middle-Income Setting Using Named-Patient Compassionate Access Program

Polatuzumab vedotin is a novel immunotherapy antibody-drug conjugate targeting CD79b. It has been used in relapsed/refractory (R/R) large B-cell lymphomas since its FDA approval in 2019. Presently, this drug is unaffordable or unavailable for patients in Lower-Middle Income Countries (LMIC) like India. This is a retrospective study of adult (> 18 years) patients with R/R large B-cell lymphoma failing two prior lines of therapy, who received Polatuzumab based salvage therapy on a compassionate or named-patient access program. Between May 2019 and April 2022, 10 patients received Polatuzumab vedotin, and 9 were evaluable. The most common regimen used was Polatuzumab-Bendamustine-Rituximab. Out of 43 infusions administered, the adverse event profile was manageable [One grade-2 infusion reaction, 4 patients developed grade 3-4 hematological toxicity and none had grade 3-4 non-hematological toxicities]. Ten infusions were administered in the day care service. After a median of 4.5 cycles (range 1-8), 4 patients achieved CR, 2 had partial response (PR), and 3 had progressive disease (PD). With a median follow up of 491 days (range 8-1048 days), four patients are alive (three in CR and one in PR), three patients have died and three patients were lost to follow up. Early real-world experience from a LMIC setting demonstrates feasibility and a favourable safety profile of Polatuzumab vedotin based approach, along with encouraging response rates in a subset of patients.

Epicardial adipose tissue volume and density is associated with cardiac dysfunction in asymptomatic people with type 2 diabetes

Background

Type 2 diabetes (T2D) is associated with several perturbations of cardiac structure and function, which are precursors to the development of heart failure. Excess accumulation of epicardial adipose tissue (EAT) may contribute to cardiac dysfunction in individuals with T2D. Lipid-laden adipocytes have a lower computed tomography (CT) attenuation and can be readily identified using cardiac CT. Using a multimodality cardiac imaging approach, we aimed to assess the association of total and low attenuation EAT volume with early markers of cardiac dysfunction in people with T2D.

Methods

Prospective case-control study, in which participants with and without T2D and no known cardiovascular disease, underwent comprehensive cardiovascular phenotyping including multiparametric cardiac magnetic resonance imaging (MRI), echocardiography and non-contrast cardiac CT. EAT volume was measured from CT scans using a deep learning method and volumes indexed to body surface area. Total EAT was defined according to CT adipose tissue attenuation range of −30 to −190 Hounsfield Units (HU) and low attenuation EAT as −90 to −190 HU. Left ventricular (LV) volumes, function and strain measurements were derived from cardiac MRI images and diastolic function also assessed using echocardiography. Markers of early cardiac dysfunction in those with T2D were assessed for associations with EAT in T2D participants using multivariable linear regression analyses.

Results

Two hundred and fifty-four participants were included: demographic, anthropometric and imaging variables are displayed in Table 1. Subjects with T2D had increased LV concentric remodelling (higher LV mass/volume ratio), diastolic dysfunction (lower circumferential peak early diastolic strain rate (PEDSR) and average E/e') and reduced systolic function (global longitudinal strain, GLS) compared with controls. Total and low attenuation indexed EAT volumes were 1.6-fold and 2-fold higher, respectively, in participants with T2D compared to controls (Figure 1). After adjustment for age, gender, ethnicity, insulin resistance, systolic blood pressure and waist/hip ratio, total and low attenuation indexed EAT volume were independently associated with LV mass/volume ratio (total indexed EAT volume: β=0.002, p=0.02, low attenuation indexed EAT volume: β=0.004, p=0.01) and LV GLS (total indexed EAT volume: β=−0.02, p&lt;0.01, low attenuation indexed EAT volume: β=−0.04, p=0.02) in subjects with T2D, but not indices of diastolic dysfunction.

Conclusion

Total and low attenuation EAT volumes are higher in individuals with T2D, and excess EAT accumulation is independently associated with early markers of cardiac dysfunction. Further studies into the underlying mechanisms of this interaction may facilitate the development of interventions targeted at EAT, which could mitigate against the development of heart failure in people with T2D.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): United Kingdom National Institute for Health Research

Cardiometabolic predictors of quantitative high-risk plaque features in a diverse patient population

Background/Introduction

Little is known about the prevalence of high-risk plaque features or cardiometabolic predictors in diverse patient populations with underrepresented minorities, in the setting of stable chest pain.

Purpose

The goals of our study are to 1) describe plaque characteristics in a diverse patient population with underrepresented minorities and 2) characterize cardiometabolic risk factors associated with high prevalence of high-risk quantitative low attenuation noncalcified plaque (LDNCP) burden.

Methods

Our study included patients with chest pain undergoing CCTA between June 2016 and October 2021 for stable chest pain, who had a complete cardiometabolic panel including lipoprotein(a) and lipid panel, and at least one blood pressure recording before CCTA. Patients with prior PCI or CABG where excluded. CACS was performed before CCTA as per Agatston method and quantified in Agatston Units (AU). Stenosis was graded as per SCCT guidelines by cardiologists and radiologists with level 3 cardiac CT expertise. Plaque measurements were performed using previously validated semiautomated software (AutoPlaque version 2.5) in all patients with CAD-RADS &gt;0 by expert readers blinded from patients' characteristics. Coronary atherosclerotic plaque volumes were measured. Independent predictors for plaque on CCTA among patients were examined using Wilcox multivariate logistic regression.

Results

A total of 227 consecutive patients were included in our study (see table; age 55.00 [47.50–62.00] years, 63% female, 16% diabetes, 44% hypertension, 40% hyperlipidemia and 32% with current or previous smoking history). Majority of patients were Hispanic (64%) and the rest were Black (27%), White (6%) and Asian (3%).

Patients with LDNCP burden &gt;4% were older (60.00 [52.00–66.50] vs 53.00 [43.75–61.00]; p&lt;0.001), more likely to be diabetic (27.7 vs 11.5%; p=0.005), hypertensive (67.7 vs 33.8%; p&lt;0.001), hyperlipidemic (64.6 vs 29.9%; p&lt;0.001) and present smokers (31.3 vs 13.9%; p=0.003). Almost all patients (63/67) with LDNCP burden &gt;4% had non-obstructive disease (CAD-RADS&lt;4).

Patient with LDNCP burden &gt;4% were more likely to be on statin therapy (46.0 vs 30.4%; p=0.041). There was no differences in ethnicity, hemoglobin A1C, TC, LDL-C, HLD-C, TGs, lipoprotein(a), SBP or DBP.

By logistic regression analysis, age (OR [CI]: 1.06 [1.01–1.08]), hypertension (2.20, [1.06–4.63]) and hyperlipidemia (2.73 [1.37–5.47]) increased the likelihood of LDNCP burden &gt;4%, but not Lipoprotein (a)&gt;175 nmol/L (OR [CI]: 1.07 [0.48–2.31].

Conclusions

In our cohort of patients with high number of unrepresented minorities presenting with stable chest pain, almost all patients (94%) with LDNCP burden &gt;4% had non-obstructive CAD (CAD-RADS&lt;4). There were no differences in prevalence of LDNCP or CAD-RADS among different ethnic groups. Age, hypertension and hyperlipidemia, were the cardiometabolic factors related to LDNCP burden &gt;4%.

Funding Acknowledgement

Type of funding sources: None.

Exercise induced coronary inflammation in masters athletes

Background

Chronic endurance exercise has been linked to increased prevalence of coronary artery disease (CAD) in male master athletes. Data are limited regarding the presence of exercise-induced coronary inflammation and its association with atherosclerosis in master endurance athletes. Human coronary inflammation can be detected non-invasively by imaging pericoronary adipose tissue (PCAT). We tested the hypothesis that chronic endurance exercise leads to increased prevalence of atherosclerosis via coronary inflammation.

Methods

Computed tomography coronary angiogram CTCA scans from 2 cohorts of master athletes and age-matched controls, without known risk factors for CAD, were analysed post-hoc and the PCAT attenuation index was calculated around the proximal right coronary artery (FAIRCA). The athletes and the healthy controls also underwent an electrocardiogram, an echocardiogram, a cardiopulmonary exercise test (CPET), a 24-hour Holter tape and a Cardiac Magnetic Resonance (CMR) scan.

Results

Scans from 243 masters endurance athletes (62% females) and 58 age and Framingham CAD risk score matched healthy controls were analysed. FAIRCA was significantly higher (less negative) in male masters athletes vs female masters athletes [−61.3 Hounsfield Units (HU) vs −62.8 HU, p=0.01], in male athletes vs male controls (−61.3 HU vs −68.6 HU, p&lt;0.001) and in female athletes vs female controls (−62,8 HU vs −67.5 HU, p=0.005). In female masters athletes, peak oxygen consumption during CPET (peak VO2) statistically significantly predicted the FAIRCA, F(1,146) = 22.62, p&lt;0.0001. There was no correlation between the FAIRCA and presence of atherosclerosis in male masters athletes.

Conclusions

Masters athletes show increased markers of coronary inflammation. This effect appears to be greater in male masters athletes and is associated with a higher peak VO2 in female masters athletes. However, we did not identify a link between coronary inflammation and coronary atherosclerosis in this cohort.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Cardiac Risk in the Young, UK

18F-sodium fluoride positron emission tomography and coronary plaque radiomics derived from computed tomography angiography for prediction of myocardial infarction

Background

Assessments of coronary disease activity with 18F-sodium fluoride positron emission tomography (18F-NaF PET) and radiomics-based precision coronary plaque phenotyping derived from contrast-enhanced computed tomography (CT) have both been shown to enhance risk stratification in patients with coronary artery disease (CAD). To date, no study has investigated whether these two promising methods (which can be obtained during a single imaging session on a hybrid PET/CT scanner) are interchangeable or can provide superior predictive performance when used in combination.

Purpose

We sought to investigate whether the prognostic information provided by latent morphological radiomic coronary plaque features and assessments of disease activity by 18F-NaF PET are complementary in prediction of myocardial infarction.

Methods

Patients with known CAD underwent coronary 18F-NaF PET and CT angiography on a hybrid PET/CT scanner. Coronary 18F-NaF uptake was determined by the coronary microcalcification activity (CMA). We performed quantitative plaque analysis of coronary CT angiography datasets. Additionally, coronary plaque segmentations on CT angiography were used to extract 1103 radiomic features. Using weighted correlation network analysis we derived latent morphological features of coronary plaques which were aggregated to patient-level radiomic normograms to predict myocardial infarction using univariate and multivariate Cox proportional hazard models.

Results

The study cohort comprised of 260 patients with established CAD (age: 65±9 years; 84% men); 179 (69%) participants showed increased coronary 18F-NaF activity (CMA &gt;0). Over 53 [40–59] months of follow-up 18 patients had a myocardial infarction. Using weighted correlation network analysis, from the 1103 radiomic features we derived 15 distinct eigen radiomic features representing latent morphological coronary plaque patterns. On univariate cox modelling 7 of these emerged as predictors of myocardial infarction (Figure). Following adjustments for calcified, noncalcified and low-density noncalcified plaque volumes and 18F-NaF CMA 4 radiomic features (related to texture and geometry) remained independent predictors of myocardial infarction (Figure).

Conclusion(s)

In patients with established CAD latent morphological features of coronary plaques are predictors of myocardial infarction above and beyond plaque volumes and 18F-NaF uptake. Comprehensive plaque analysis with radiomics may enhance risk stratification of CAD patients.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIH, Wellcome Trust

Influence of gender on coronary atherosclerosis and inflammatory biomarker profile: a CT angiographic study

Background and aims

The burden of coronary atherosclerosis differs between men and women. Beyond traditional cardiovascular risk factors, inflammatory biomarkers can influence plaque formation and progression. We analyzed the influence of gender difference on coronary atherosclerosis and inflammatory cytokines.

Methods

Coronary CT-Angiography was performed in 301 patients and plaque morphology was quantitatively and qualitatively assessed using semi-automated software (Autoplaque version 2.5, Cedars-Sinai Medical Center, Los Angeles, CA). We analyzed total (TPV), non-calcified (NCPV), calcified (CPV) and low-density plaque volume in mm3 (LDPV, defined as plaque attenuation &lt;30HU). Serum was analyzed for various cytokines including Interleukin (IL)-1a, IL-1b, IL-2, IL-4, IL-6, IL-7, IL-8, IL-10, IL-13, Il-15, IL-17, TNF-a, IFNg, CRP, MCP-1, MIP-1a, Eotaxin, G_CSF and GM-CSF using Luminex assay.

Results

Out of 301 patients, 94 (31%) were female and 207 (69%) were male. As compared to women, men were significantly younger (62 vs. 57 years, p&lt;0.001) and showed a higher BMI (28 vs. 26 kg/m2, p=0.005). No differences were seen for hypertension, hyperlipidemia, diabetes, smoking habits and family history of CAD. All plaque characteristics showed significant higher values in men as compared to women (all p&lt;0.05). In men, cytokine profile showed significantly lower serum levels for IL-2 (3.20 [3.20; 7.01] vs. 4.31 [3.20; 9.68]; p=0.01) and Interferon-gamma (3.20 [3.20; 14.72] vs. 8.76 [3.20; 26.26]; p&lt;0.001) and significantly higher levels for MCP-1 (224 [117; 327] vs. 155 [49; 260]; p&lt;0.001). In multivariable logistic regression analysis, Interferon-gamma showed significant inverse association to male gender (OR 0.35; 95% CI: 0.17–0.72; p=0.004), but IL-2 and MCP-1 did not. The association of Interferon-gamma to gender was independent of age (OR 0.57; 95% CI: 0.43–0.76; p&lt;0.001) and BMI (OR 2.12; 95% CI 1.25–3.62; p=0.006)

Conclusion

Coronary plaque volume and morphology significantly differs between men and women and so does the inflammatory cytokine profile. Albeit significantly lower coronary plaque burden in women, serum levels of interferon-gamma - a known pro-inflammatory cytokine - was significantly higher in women with independent association to gender. Whether interferon-gamma plays contradicting roles in the process of coronary atherosclerosis in men and women needs to be explored in future studies to identify potential gender-specific targets for therapeutic interventions.

Funding Acknowledgement

Type of funding sources: None.

The effect of vitamin K2 supplementation on coronary artery disease in a randomized multicenter trial

Background

Coronary artery calcification (CAC) and especially progression in CAC is a strong predictor of acute myocardial infarction (AMI) and cardiovascular mortality [1]. Observational studies suggest a protective role of vitamin K2 in the development of CAC [2]. Measurement of CAC score in Agatston Units (AU) is common practice, while novel software as AutoPlaque introduces new opportunities to measure coronary plaques [3].

Purpose

The aim of this double-blinded randomized multicenter trial is to investigate if vitamin K2 supplementation can reduce the progression of CAC in a population without known coronary disease.

Methods

AVADEC is a multicenter trial investigating 389 participants randomized to vitamin K2 (720 μg/day) and vitamin D (25 μg/day) versus placebo with a 2-year follow-up from 2018–2019 [4]. The primary endpoint of AVADEC is change in aortic valve calcification. In this substudy, we examined the progression of CAC in participants with no prior coronary disease (no myocardial infarction and/or revascularization) at baseline. Secondary, the change in CAC was evaluated in two prespecified subgroups (low-risk: CAC score &lt;400 AU and high-risk: CAC ≥400 AU at baseline). Non-contrast CT-scans were performed at baseline, 12 and 24 months of follow-up. Contrast CT-scans were performed at baseline and 24 months. CAC score was measured with established software and expressed in Agatston Units (AU). On contrast CT-scans, quantitative coronary plaque composition evaluations were performed by using Autoplaque. Moreover, events (AMI, revascularization and all cause death) were assessed.

Results

304 participants (male, mean age 71 years) with no prior coronary disease were identified. The intervention and placebo groups were similar in all traditional cardiovascular risk factors except familial predisposition for cardiovascular disease (14.4% vs. 6.7%, p=0.046). We found progression of CAC in both the intervention and placebo group from baseline to 24 month follow-up (203 AU vs. 254 AU, p=0.089) (Figure 1). The patients with CAC score &lt;400 AU at baseline were equal in progression (77 AU vs. 81 AU, p=0.846). In patients with CAC score ≥400, the progression of CAC was significantly lower in the intervention group (288 AU vs. 380 AU, p=0.047). Yet, preliminary analyses of contrast CT-scans in 180 participants showed no difference in the progression of non-calcified plaque volume (10 mm3 vs. 37 mm3, p=0.276). In addition, the number of events was significantly lower in participants receiving vitamin K2 and D (1.9% vs. 6.7%, p=0.048).

Conclusion

Patients with no prior coronary disease randomized to vitamin K2 supplementation had a non-significant reduction in CAC development over a 2-year follow-up period. High-risk patients with CAC ≥400 AU had a significantly lower progression of CAC. Additionally, vitamin K2 supplementation significantly reduced the risk of AMI, revascularization and all-cause death.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Danish Cardiovascular Academy (2/3) and the Region of Southern Denmark (1/3).

Pericardial fat from a single horizontal long axis cardiac magnetic resonance cine image: a validation study against three-dimensional cardiac computed tomography

Background

Excess fat accumulation around the heart (i.e., pericardial fat) is positively associated with cardiovascular disease. Pericardial fat is composed of two distinct depots: (1) epicardial fat, which is a metabolically active adipose tissue located between the heart and the pericardium, and (2) paracardial fat, which is the fat deposit in the mediastinum outside of the parietal pericardium. Both depots are visible on the horizontal long axis cardiac magnetic resonance (CMR) cine (i.e., four chamber view), offering an attractive opportunity to quantify pericardial fat from standard CMR cine images.

Purpose

To validate pericardial fat area measured from a single horizontal long axis CMR cine against whole-heart volumetric non-contrast cardiac computed tomography (CT) measurements.

Methods

To accomplish our goal, we leveraged 25 cases from the Women's Ischemia Syndrome Evaluation – Coronary Vascular Dysfunction Continuation cohort who underwent both cardiac MRI and cardiac CT within a median of 35 days apart. For MRI, pericardial fat area was measured from a single high resolution steady state free precession cine image in the horizontal long axis imaging plane using commercially available software (CVI42 V5.13.5, Circle Cardiovascular Imaging, Figure 1A). For CT, pericardial fat volume was measured using a fully automated deep learning algorithm (QFAT 2.0, Figure 1A).

Results

Fat area measured from a single horizontal long axis cine image was closely related to fat volume measured by three-dimensional cardiac CT, with strong correlations for epicardial fat (R2=0.72, p&lt;0.01, Figure 1B), paracardial fat (R2=0.80, p&lt;0.01, Figure 1C), and pericardial fat (R2=0.91, p&lt;0.01, Figure 1D).

Conclusions

Measuring pericardial fat area, and its constituent parts, from a single horizontal long axis cine image is both feasible and strongly related to reference standard pericardial fat volume by cardiac CT.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): National Institutes of Health

Level of vascular inflammation is higher in acute coronary syndromes compared to chronic coronary disease

Background

Vascular inflammation has been recognized as one of the key factors in the pathogenesis of acute coronary syndromes (ACS). Peri-coronary adipose tissue (PCAT) attenuation by computed tomography angiography (CTA) has emerged as a marker specific for coronary artery inflammation. We examined the relationship between clinical presentation and coronary artery inflammation assessed by PCAT attenuation and coronary plaque characteristics.

Methods

Patients with ACS or stable angina pectoris (SAP) who underwent pre-intervention coronary CTA and optical coherence tomography (OCT) were enrolled. PCAT attenuation was measured around the culprit lesion and in the proximal 40 mm of all coronary arteries. PCAT attenuation and OCT findings were compared between patients with ACS versus SAP.

Results

Among 471 patients (ACS: 198, SAP: 273), PCAT attenuation was higher in ACS patients than in SAP patients both at the culprit plaque level (−67.5±9.6 Hounsfield unit [HU] vs. −71.5±11.0 HU, p&lt;0.001) and the culprit vessel level (−68.3±7.7 HU vs. −71.1±7.9 HU, p&lt;0.001). The mean PCAT attenuation of all 3 coronary arteries was also significantly higher in ACS patients than in SAP patients (−68.8±6.3 HU vs. −70.5±7.1 HU, p=0.007). After adjusting patient characteristics, not only thin-cap fibroatheroma (OR: 2.44; 95% CI: 1.63–3.65) and macrophages (OR: 2.07; 95% CI: 1.34–3.21) but also PCAT attenuation in the culprit plaque (OR: 1.04; 95% CI: 1.02–1.06) was associated with the clinical presentation of ACS.

Conclusions

PCAT attenuation at culprit plaque, culprit vessel, and pan-coronary levels was higher in ACS patients than in SAP patients. Vascular inflammation appears to play a crucial role in the development of ACS.

Funding Acknowledgement

Type of funding sources: None.

Novel contrast-computed tomography method based on a Gaussian Mixture Model for assessment of fibrocalcific volume in aortic valve stenosis

Background

Discordant echocardiography is observed in up to one third of patients with aortic stenosis (AS), in whom computed tomography (CT) derived aortic valve calcium scoring is now recommended. However, CT calcium scoring only assesses calcific valve thickening and ignores non-calcific fibrotic thickening, which could be an important contributor of AS.

Purpose

To generate a quick and robust contrast-CT method based on a gaussian mixture model (GMM) for assessment of fibro-calcific aortic valve thickening in patients with AS, and to investigate its reproducibility and associations with echo parameters of AS severity and disease progression.

Methods

A post-hoc analysis of 136 patients with calcific AS (24 with severe, 81 moderate and 31 mild AS) enrolled in the SALTIRE2 trial (NCT-02132026) was performed. Aortic valve fibrocalcific volume was calculated using a GMM applied on contrast-CT at baseline and at 1-year follow up. The software estimated the Hounsfield Units (HU) distribution of 3 compartments (blood pool, non-calcific and calcific tissue) within the aortic valve volume of interest, automatically generating thresholds for non-calcific and calcific tissue, respectively computed as the lower 99.7 and the upper 99.7 percentile of the blood pool HU distribution (Figure 1). Fibrocalcific volume was measured as the sum of calcific and non-calcific volumes, indexed for CT annulus area and compared to echo parameters of AS severity. Evaluation of scan-rescan reproducibility and AS progression were also assessed.

Results

Image analysis took 5.8±1.0 minutes per scan and showed excellent scan-rescan reproducibility (mean difference −1%, limits of agreement −9% to 7%). Indexed-fibrocalcific volume correlated well with echocardiographic aortic peak velocity (rho=0.70, p&lt;0.0001), better than non-calcific and calcific volumes alone (rho=0.30 and rho=0.61 respectively, both p&lt;0.0001) and Agatston calcium score (rho=0.63, p&lt;0.0001). Baseline indexed-fibrocalcific volume was also the strongest predictor of subsequent AS progression in terms of change in aortic valve peak velocity (rho=0.29, p=0.006) and mean gradient (rho=0.39, p&lt;0.0001). Progression-to-noise ratio for fibrocalcific volume was favourable (Cohen's statistic d=0.62), indicating that groups sizes of 21, 46 and 170 participants would be required to demonstrate 30%, 20% and 10% reductions in fibro-calcific volume progression with a novel drug respectively (alpha=0.05, power=80%).

Conclusions

This novel contrast CT-based approach can provide robust and rapid assessment of fibrocalcific thickening in AS patients. Fibrocalcific volume measured using this technique, correlates well with other markers of AS severity, predicts disease progression and holds promise in tracking disease progression and response to novel therapies.

Funding Acknowledgement

Type of funding sources: None.

Phytogenic silver nanoparticles from tissue-cultured Kaempferia angustifolia - an underutilized medicinal herb: a comparative antibacterial study on urinary pathogens

Background

Ethnomedicinally important Kaempferia angustifolia is a rhizomatous aromatic herb belonging to the family Zingiberaceae. The present manuscript deals with the green synthesis of silver nanoparticles through a rapid reduction process mediated by the rhizome extract of tissue culture-raised plants. The present study was conducted to evaluate the antimicrobial activity of the bio-nanoparticles, and the plant extracts themselves against seven multidrug-resistant urinary tract infecting (MDR-UTI) pathogens.

Result

The ethanolic extracts of the rhizomes of the plant executed a very rapid synthesis of silver bio-nanoparticles, and the generation of the nanoparticles was confirmed through UV-vis spectrophotometry, dynamic light scattering (DLS), and electron dispersion spectroscopic (EDS) analysis. Finally, the precise shapes and dimensions of these nanoparticles were confirmed under the transmission electron microscope (TEM). The shapes of the nanoparticles obtained were diverse in nature and varied from rod, triangular, spherical, to oval shaped, with the size, ranging from 10–60 nm. Silver nanoparticles exhibited a maximum zone of inhibition (ZI) of 16.93 ± 0.04 mm against isolate no. 42332. The ex vitro and in vivo extracts exhibited ZI 14.03 ± 0.04 mm and 11.56 ± 0.04 mm, respectively, against the same strain, which are comparatively lower than the nanoparticles but unignorable.

Conclusion

Although the pathogens used in the present study are resistant to at least three or more types of pharmacologically important antibiotics, nanoparticles, as well as the plant extracts, exhibited significant inhibition to all the seven MDR-UTI pathogens, which confirms that they are highly antimicrobic. Hence, this underutilized medicinal plant extracts of K. angustifolia and the bio-nanoparticles synthesized from these can be explored in pharmaceutical industries to treat multidrug-resistant human pathogenic bacteria. Furthermore, their broad-spectrum activity leads to the opportunity for the synthesis of future generation drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00414-4.

Silver nanoparticle synthesis and their potency against multidrug-resistant bacteria: a green approach from tissue-cultured Coleus forskohlii

Drug resistance is a major concern nowadays, and finding alternatives of the well-known antibiotic is necessary. Green nanoparticles are emerging as a tenable alternative to this with a large spectrum of activity. The present manuscript describes an eco-friendly approach for green synthesis of silver nanoparticles from both in vitro and in vivo leaf extract of Coleus forskohlii. Leaf extracts were used in synthesis of nanoparticles which were further analyzed through UV-Vis, dynamic light scattering, energy-dispersive spectroscopy, and transmission electron microscopy. Antimicrobial activity of silver nanoparticles alone, as well as crude extract of the plant itself, was carried out against eight multidrug-resistant respiratory tract infecting pathogenic strains. Satisfactory antimicrobial activities were found with nanoparticles, in vitro and in vivo leaf extracts. However, gradually higher to lower inhibition potential against pathogenic bacterial strains was found in silver nanoparticles, in vitro and in vivo leaf extracts. Seven bioactive compounds were detected in the crude extract through gas chromatography-mass spectroscopy analysis. Results revealed that nanoparticle formation occurred in a wide range of sizes (10-50 nm) and shapes (trigonal, hexagonal, spherical, rod). The diversity in size and shape of the nanoparticles makes them biologically active. Silver nanoparticle exhibits significantly better antimicrobial activities as compared to the plant extract in case of nearly all pathogens with a maximum zone of inhibition of 15.33 ± 0.94 mm where more than 12 well-known antibiotics failed to respond. Because of this broad-spectrum activity of nanoparticles as well as the leaf extracts against life-threatening microbes, it can be used as future generation drugs.

Simple Treadmill Score: Does It Have Better Predictability for Coronary Artery Disease?

Coronary artery disease is one of the most prevalent causes of increasing mortalitiy in current time. Early detection of such dreadful condition by a non-invasive test like exercise treadmill test, is a much-required option to prevent future complications like myocardial infarction. The aim of this study was to find out how different the predictability of simple treadmill score in comparison to other treadmill scores namely the well-known Duke treadmill score and Cleveland clinic score. In a cross-sectional analytical study of total 130 individuals with stable angina were included according to criteria set before the study. The treadmill scores of these patients were calculated and compared to coronary angiogram findings where coronary artery angiograms were done according to clinical need. Simple treadmill test had similar predictability for coronary artery disease when we compared it with much-applied Duke Treadmill Test and Cleveland Clinic Score- which is currently used for mortality prediction. Receiver Operator Characteristics (ROC) Curve showd all scores had around 0.7 area under the curve (AUC) which is highly statistically significant (p<0.0001) though simple treadmill score in females has higher sensitivity (92.3%). Simple treadmill score can be considered to exclude female patients from undergoing invasive investigation as it has higher sensitivity than other currently practiced treadmill scores i.e., Duke treadmill score.

Calcium scoring in low-dose ungated chest CT scans using convolutional long-short term memory networks

We aimed to develop a novel deep-learning based method for automatic coronary artery calcium (CAC) quantification in low-dose ungated computed tomography attenuation correction maps (CTAC). In this study, we used convolutional long-short -term memory deep neural network (conv-LSTM) to automatically derive coronary artery calcium score (CAC) from both standard CAC scans and low-dose ungated scans (CT-attenuation correction maps). We trained convLSTM to segment CAC using 9543 scans. A U-Net model was trained as a reference method. Both models were validated in the OrCaCs dataset (n=32) and in the held-out cohort (n=507) without prior coronary interventions who had CTAC standard CAC scan acquired contemporarily. Cohen's kappa coefficients and concordance matrices were used to assess agreement in four CAC score categories (very low: <10, low:10-100; moderate:101-400 and high >400). The median time to derive results on a central processing unit (CPU) was significantly shorter for the conv-LSTM model- 6.18s (inter quartile range [IQR]: 5.99, 6.3) than for UNet (10.1s, IQR: 9.82, 15.9s, p<0.0001). The memory consumption during training was much lower for our model (13.11Gb) in comparison with UNet (22.31 Gb). Conv-LSTM performed comparably to UNet in terms of agreement with expert annotations, but with significantly shorter inference times and lower memory consumption.

Independent predictors of major cardiovascular events as quantitatively assessed by coronary CT-angiography: a long-term follow-up analysis

Introduction

Quantitative CT coronary angiography using semi-automated software provides detailed information about plaque volume and high-risk plaque characteristics, beyond traditional measures like diameter stenosis. We assessed the potential value of plaque quantity and morphology to independently predict MACE in a cohort with long-term follow up.

Methods

In this secondary analysis of 301 symptomatic patients undergoing coronary CTA at baseline, total plaque volume (TPV), non-calcified- (NCPV), calcified- (CPV) and vulnerable coronary plaque volume (in mm3), diameter stenosis (in %) and remodeling index were quantified using semi-automated software (Autoplaque version 2.5, Cedars-Sinai Medical Center, Los Angeles, CA). Patients were followed for major cardiovascular events (MACE), defined as a composite of cardiovascular death, myocardial infarction and coronary revascularization. Optimal thresholds for each quantitative CTA measure were computed using CART-algorithm (Classification and Regression Trees).

Results

Complete follow-up was available for 234 (78%) patients. The mean age was 59±10 years. Over a median follow-up of 10.7 years, the composite outcome occurred in 34 (15%) patients (5 patients with cardiovascular death, 6 with myocardial infarction, 26 with revascularization). Patients experiencing MACE had more frequently hypertension (p=0.03) and a higher Framingham risk score (p=0.002). Survival anaylsis using cox proportional hazard ratios showed significant univariate associations between MACE and TPV (HR 5.16; 95% CI 1.58–16.89; p=0.007), NCPV (HR 4.83; 95% CI 1.45–15.81; p=0.009), CPV (HR 2.86; 95% CI 1.39–5.86; p=0.004), vulnerable plaque volume (HR 3.35; 95% CI 1.52–7.41; p=0.003), diameter stenosis (HR 5.19; 95% CI 2.64–10.22; p&lt;0.001) and remodeling index (HR 4.24; 95% CI 2.03–8.86; p&lt;0.001). In multivariable cox regression analysis diameter stenosis (HR 3.70; 95% CI 1.72–7.93; p=0.001) and remodeling index (HR 2.69; 95% CI 1.19–6.09; p=0.018) remained significant independent predictors of MACE, adjusted for Framingham risk score (HR 2.56; 95% CI 1.26–5.22; p=0.010), however plaque volume and plaque subcomponents did not.

Conclusion

On long term follow-up, remodeling index and coronary diameter stenosis obtained by quantitative coronary CT angiography independently predicted MACE on multivariable assessment. More comprehensive plaque assessment algorithms including plaque volume as well as plaque subcomponents were significantly associated with MACE in univariate, but not multivariate analysis after adjustment for diameter stenosis and remodeling index.

Funding Acknowledgement

Type of funding sources: None.

Machine learning from quantitative coronary computed tomography angiography predicts ischemia and impaired myocardial blood flow

Background

Atherosclerotic plaque characteristics influence the hemodynamic consequences of coronary lesions. This study sought to assess the performance of a machine learning (ML) score integrating coronary computed tomography angiography (CCTA)-based quantitative plaque features for the prediction of ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by [15O]H2O positron emission tomography (PET).

Methods

This post-hoc analysis of the PACIFIC (Prospective Comparison of Cardiac PET/CT, SPECT/CT Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography) trial included 208 patients with suspected coronary artery disease who underwent CCTA, [15O]H2O PET, and 3-vessel invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. A boosted ensemble ML algorithm (XGBoost) trained on data from the NXT (Analysis of Coronary Blood Flow using CT Angiography: Next Steps) trial was used to develop a ML score for the prediction of per-vessel ischemia (invasive FFR ≤0.80). The performance of the ML score was evaluated in 551 vessels from the PACIFIC trial for external validation. Thereafter, we assessed the discriminative ability of the ML score for per-vessel impaired hyperemic MBF (≤2.30 mL/min/g).

Results

In total, 138 (25.0%) vessels had ischemia and 195 (35.4%) vessels had impaired hyperemic MBF. CCTA-derived quantitative percent diameter stenosis and low-density noncalcified plaque (LDNCP) volume were higher in ischemic vessels compared with non-ischemic vessels (60.8% vs. 19.9%; and 42.3 mm3 vs. 9.1 mm3; both p&lt;0.001). The ML score demonstrated a significantly higher area under the receiver-operating characteristic curve (AUC) for predicting ischemia (0.92, 95% confidence interval [CI] 0.89–0.94) compared with visual stenosis grade (0.84, 95% CI 0.80–0.87; p&lt;0.001). Overall, quantitative percent diameter stenosis and LDNCP volume had greatest feature importance for ML, followed by percent area stenosis, minimum luminal diameter, and contrast density drop (Figure 1). An individualized explanation of ML ischemia prediction is shown in Figure 2. When applied for impaired MBF discrimination, the ML score exhibited an AUC of 0.82 (95% CI 0.78–0.85) and was superior to visual stenosis grade (AUC 0.76, 95% CI 0.72–0.80; p=0.03).

Conclusions

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and abnormal MBF by PET, outperforming standard visual CCTA interpretation.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States Performance of the ML scoreIndividual explanation of ML prediction

Computed tomography-derived characterisation of pericoronary,epicardial and paracardial adipose tissue and its association with myocardial ischemia as assessed by computed and invasive fractional flow

Introduction

Increased pericoronary adipose tissue (PCAT) computed tomography (CT) attenuation derived from coronary CT angiography (CTA) around the right coronary artery (RCA) reflects coronary inflammation and relates to cardiac mortality.

Purpose

We aimed to investigate the yet unclear association between CT-derived characterisation of different cardiac adipose tissue compartments and the presence of myocardial ischemia as assessed by fractional flow reserve (FFR).

Methods

133 stable individuals (64 years, 74% male) with coronary artery disease (CAD) underwent CTA including computed FFR (FFR-CT) measurement followed by invasive angiography with FFR (invasive FFR) assessment. The CT attenuation (HU) and volume (mm3) of PCAT were quantified around the RCA (10 to 50 mm from RCA ostium), the proximal 40 mm of the left anterior descending artery (LAD) and the circumflex artery (LCX) with the help of semi-automated software. The per patient PCAT CT attenuation was calculated as followed: (PCAT CT attenuation of RCA+LAD+LCX)/3. Quantification of epicardial adipose tissue (EAT) and paracardial adipose tissue (PAT; all intrathoracic adipose tissue outside the pericardium) were performed in non-contrast cardiac CT data sets using a fully automated deep-learning based algorithm.

Results

Median FFR-CT was 0.86 [0.79, 0.91] and median invasive FFR was 0.87 [0.81, 0.93]. Patients with presence of myocardial ischemia (n=26) defined by a FFR-CT threshold of ≤0.75 showed a significant higher PCAT CT attenuation of RCA (−75.1 HU vs. −81.1 HU, p=0.011) and per patient (−74.5 HU vs. −77.7 HU, p=0.045) than individuals without myocardial ischemia (n=107). In multivariable analysis adjusted for age, BMI, gender and traditional risk factors, both RCA and per patient PCAT CT attenuation were significant predictors of myocardial ischemia as assessed by FFRCT ≤0.75. Between individuals with myocardial ischemia compared to individuals without myocardial ischemia there was no significant difference neither in the volume and CT attenuation of EAT and PAT nor in the PCAT volume of RCA, LAD, LCX and per patient PCAT volume.

Conclusions

Our observations suggest that PCAT CT attenuation instead of PCAT volume, EAT and PAT measures might be associated with the presence of myocardial ischemia as assessed by FFR.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): German Heart Foundation e.V.

Deep learning-based plaque quantification from coronary computed tomography angiography: external validation and comparison with intravascular ultrasound

Background

Atherosclerotic plaque quantification from coronary computed tomography angiography (CTA) enables accurate assessment of coronary artery disease burden, progression, and prognosis. However, quantitative plaque analysis is time-consuming and requires high expertise. We sought to develop and externally validate an artificial intelligence (AI)-based deep learning (DL) approach for CTA-derived measures of plaque volume and stenosis severity. We compared the performance of DL to expert readers and the gold standard of intravascular ultrasound (IVUS).

Methods

This was a multicenter study of patients undergoing coronary CTA at 11 sites, with software-based quantitative plaque measurements performed at a per-lesion level by expert readers. AI-based plaque analysis was performed by a DL novel convolutional neural network which automatically segmented the coronary artery wall, lumen, and plaque for the computation of plaque volume and stenosis severity. Using expert measurements as ground truth, the DL algorithm was trained on 887 patients (4,686 lesions). Thereafter, the algorithm was applied to an independent test set of 221 patients (1,234 lesions), which included an external validation cohort of 171 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) trial as well as 50 patients who underwent IVUS within one month of CTA. We report the performance of AI-based plaque analysis in the independent test set.

Results

Within the external validation cohort, there was excellent agreement between DL and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0.876), noncalcified plaque volume (ICC 0.869), and percent diameter stenosis (ICC 0.850; all p&lt;0.001). When compared with IVUS, there was excellent agreement for DL total plaque volume (ICC 0.945), total plaque burden (ICC 0.853), minimal luminal area (ICC 0.864), and percent area stenosis (ICC 0.805; all p&lt;0.001); with strong correlation between DL and IVUS for total plaque volume (r=0.915; p&lt;0.001; Figure). The average DL plaque analysis time was 20 seconds per patient, compared with 25–30 minutes taken by experts.

Conclusions

AI-based plaque quantification from coronary CTA using an externally validated DL approach enables rapid measurements of plaque volume and stenosis severity in close agreement with expert readers and IVUS.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States