A platform for stop flow gradient generation to investigate chemotaxis

The ability of artificial microswimmers to respond to external stimuli and the mechanistical details of their origins belong to the most disputed challenges in interdisciplinary science. Therein, the creation of chemical gradients is technically challenging, because they quickly level out due to diffusion. Inspired by pivotal stopped flow experiments in chemical kinetics, we show that microfluidics gradient generation combined with a pressure feedback loop for precisely controlling the stop of the flows, can enable us to study mechanistical details of chemotaxis of artificial Janus micromotors, based on a catalytic reaction. We find that these copper Janus particles display a chemotactic motion along the concentration gradient in both, positive and negative direction and we demonstrate the mechanical reaction of the particles to small forces deviations, explaining this behaviour.

229 Long-term clinical and echocardiographic outcome following TAVR in patients with severe aortic stenosis and different transvalvular flow state

Aims Haemodynamic classifications of severe aortic stenosis (AS) have important prognostic implications, with low flow state (defined on the basis of a stroke volume index, SVi<35 mL/m2) known to be a predictor of worse prognosis. As transcatheter aortic valve replacement (TAVR) has become widely used for patients with severe AS, issues were raised concerning its efficacy in patients with different haemodynamic classifications combining transvalvular flow state and pressure gradients. In fact, data on TAVR outcomes in patients with low gradient (LG) AS are limited and in some cases controversial. The aim of this study was to evaluate the efficacy and long-term clinical and echocardiographic outcome of TAVR in patients with different transvalvular flow-gradient patterns. Methods In this single centre study, 1078 patients (mean age 81±7 years) with severe symptomatic AS (AVA<1 cm2) undergoing TAVR were categorized according to flow-gradient patterns as follow: 867 patients (80%) with normal flow-high gradient (NF-HG: mean transaortic gradient DP mean>40 mmHg), 94 (9%) with paradoxical low flow LG (pLF-LG: DP mean<40 mmHg, ejection fraction EF > 50%, and SVi<35 mL/m2), and 117 (11%) classical LF-LG (DP mean<40 mmHg, EF < 50%, SVi<35 mL/m2). Results TAVR was feasible in all AS subtypes with similar rate of unsuccessful procedure (1.3% NF-HG, 1.1% pLF-LG, 0% LF-LG P=470). Valvular function after TAVR was excellent over time with respect to aortic pressure gradient (mean and peak) and aortic valve area regardless of flow state group (Figure A). Overall, intraoperative (P=957) and 30-day mortality (P=817) did not differ significantly among the 3 groups. Longer follow-up showed that, compared to NF-HG patients, pLF-LG had similar all-cause mortality rate [HR 1.35(0.95–1.90), P=0.094] up to 5 years and LF-LG had a significant higher mortality rate [HR 1.89(1.43–2.49), P<0.001],(Figure B). Moreover, LF-LG patients had higher rehospitalization for heart failure (NF-HG: 3%, pLF-LG: 6%, LF-LG 10%, P=0.001). Conclusions We provided evidence that TAVR is an effective procedure in all patients with severe AS regardless of transvalvular flow-gradient patterns. A careful haemodynamic classifications of severe AS is of utmost importance for identifying patients who benefits the most from TAVR procedure.

Circulating metabolome does not predict development of aortic stenosis

Background Calcific aortic valve disease (CAVD) is the most common valvular heart disease in Western world. CAVD is ranging from mild aortic valve sclerosis to severe obstructive aortic stenosis (AS). The development of AS has been associated with several risk factors including age, sex and hypertension. However, there is limited knowledge about factors that predict the development of aortic stenosis. Purpose We investigated if the circulating metabolite profile can predict the development of aortic stenosis in Finnish males. Methods We did a non-targeted LC-MS metabolomics analysis to baseline (1984–1989) serum samples from a prospective population-based Kuopio Ischemic Heart Disease risk factor study (KIHD) cohort of 2682 random Finnish males aged from 42 to 60 years. During the follow-up (until year 2020), 53 subjects developed either moderate (peak flow gradient 36–64mmHg or mean flow gradient 20–40mmHg) or severe aortic valvular stenosis (peak flow gradient over 64mmHg or mean gradient over 40mmHg). The AS patients were collected from the KIHD database using appropriate ICD-10 -codes for aortic valvular disease (from baseline to the end of the year 2017) and the diagnosis was checked manually using hospital medical records of the individuals. Results The AS patients seemed to have altered lipid metabolism and possibly altered composition of gut microbiota, since several acylcarnitines (e.g. octanoylcarnitine [Cohen's d=−0.40], decanoylcarnitine [d=−0.43], layroylcarnitine [d=−0.41], and oleoylcarnitine [d=−0.40]), and branched chain amino acids (BCAA, e.g. leucine [d=0.39], and isoleucine [d=0.49]) had p-values below 0.05. However, after correction for multiple testing, there were no significant differences between the cases and controls. Conclusions The present preliminary results, in need of verification with a larger set of samples, suggest that subjects, who will later develop AS might have reduced levels of acylcarnitines and increased levels of BCAA when compared to matched controls. However, these changes do not have large effects sizes and are likely not good candidates for biomarkers to predict future diagnosis of AS. FUNDunding Acknowledgement Type of funding sources: Foundation. Main funding source(s): The Finnish Cultural Foundation, The Finnish Foundation for Cardiovascular Research.

Novel Approach to Groundwater Contaminant Transport Modelling

This paper comprehensively investigates literature about modelling techniques used in groundwater contaminant transport modelling. Modelling of groundwater is a useful way for the management of groundwater resources, also assessing the fate of contaminants and their remediation. Models very conveniently help to study complex real conditions and examine specific phenomena in addition to predicting the future behaviour of any problem. The use of groundwater simulation programming tools such as MODFLOW, MT3DMS, RT3D, FEFLOW, and MODPATH to model multi-directional contamination transport yields accurate results. Movement, storage, and change of solute concentration are largely regulated by groundwater flow gradient. As a result, a precise description of the flow mechanism is very important. If models are not properly constructed and interpreted, they can become complicated and may generate wide errors. Well-defined and clear modelling objectives produce suitable models for efficient error-free modelling processes. The study will assist modellers to clearly define their model objective and select appropriate modelling tools.

Demographic characteristics, aortic valve intervention rates and all-cause mortality in 4 flow-gradient sub-types of severe aortic stenosis

Introduction Severe aortic stenosis (AS), defined as aortic valve area (AVA) <1.0 cm2, can be divided into 4 categories based on flow status and mean gradient. Stroke volume index <35 ml/m2 has classically been used to define low flow, but recent data suggest that flow rate (FR) <200ml/sec may be a more accurate and robust marker of low flow. Methods We prospectively collected demographic, echocardiographic, aortic valve intervention (AVI) and all-cause mortality data on 1562 patients with symptomatic severe AS from 2010 to 2017 with a mean follow up period of 35±22 months. Patients were divided into 4 flow-gradient sub-groups based on a FR threshold of 200ml/s and mean pressure gradient of 40mmHg. Comparative analyses were performed among the 4 groups using analysis of variance. Results The prevalence of normal flow high gradient (NFHG) severe AS was 30%, NF low gradient (NFLG) 21%, low flow HG (LFHG) 18% and LFLG 31% (Table). Across these 4 sub-groups, there was a graded reduction in LVEF and FR, and an increase in age and all–cause mortality. Conclusions Classification of aortic stenosis based on flow-gradient patterns, shows important differences in the demographic profile and clinical outcome among the 4 groups. Classical NFHG AS was associated with the highest rate of AVI and lowest all-cause mortality compared to the 3 discordant flow-gradient subtypes. The LFLG group had the lowest AVI rates and worst outcome. Funding Acknowledgement Type of funding source: None

Left ventricular mechanical dispersion in flow-gradient patterns of severe aortic stenosis

Purpose Patients with severe aortic stenosis are classified according to flow-gradient patterns. We investigated whether left ventricular (LV) mechanical dispersion, a marker of dyssynchrony and predictor of mortality, is associated with low-flow status in aortic stenosis. Methods and results 400 consecutive patients with QRS duration <120ms were included in the retrospective analysis. Patients with severe aortic stenosis (aortic valve area ≤1.0cm2) were classified as normal-flow (NF; stroke volume index >35ml/m2) high-gradient (HG; mean transvalvular gradient ≥40mmHg) (n=79), NF low-gradient (LG) (n=62), low-flow (LF) LG ejection fraction (EF) ≥50% (n=57), and LF LG EF<50% (n=23). Patients with moderate aortic stenosis (aortic valve area 1.5–1.0cm2; n=95) and patients with chronic systolic heart failure (n=84) without aortic stenosis served as comparison groups. Similar values of mechanical dispersion (calculated as standard deviation of time from Q/S onset on electrocardiogram to peak longitudinal strain in 17 left ventricular segments) was observed in patients with NF HG (49.4±14.7ms), NF LG (43.5±12.9ms), LF LG EF≥50% (47.2±16.3ms) and moderate aortic stenosis (44.2±15.7ms). Mechanical dispersion was increased in patients with LF LG EF<50% (60.8±20.7ms) and in chronic heart failure (59.4±16.7ms) (p<0.05 for both vs. NF HG‡, NF LG†, LF LG EF≥50%§ and moderate*; Figure). Mechanical dispersion correlated with LV end-systolic volume index (r=0.2530, p<0.0001), LVEF (r=−0.2895, p<0.0001) and global longitudinal strain (r=0.3108, p<0.0001), but not with parameters of aortic stenosis. Conclusion Mechanical dispersion was similar among flow-gradient subgroups of severe aortic stenosis with preserved LVEF, but increased in patients with low-flow low-gradient and reduced LVEF. These findings indicate that mechanical dispersion is rather a marker of systolic myocardial dysfunction than of aortic stenosis. Figure 1 Funding Acknowledgement Type of funding source: None