Machine learning and materials modelling interpretation of in vivo toxicological response to TiO2 nanoparticles library (UV and non-UV exposure)

Assessing the risks of nanomaterials/nanoparticles (NMs/NPs) under various environmental conditions requires a more systematic approach, including the comparison of effects across many NMs with identified different but related characters/descriptors. Hence, there is an urgent need to provide coherent (eco)toxicological datasets containing comprehensive toxicity information relating to a diverse spectra of NPs characters. These datasets are test benches for developing holistic methodologies with broader applicability. In the present study we assessed the effects of a custom design Fe-doped TiO2 NPs library, using the soil invertebrate Enchytraeus crypticus (Oligochaeta), via a 5-day pulse via aqueous exposure followed by a 21-days recovery period in soil (survival, reproduction assessment). Obviously, when testing TiO2, realistic conditions should include UV exposure. The 11 Fe-TiO2 library contains NPs of size range between 5-27 nm with varying þ (enabling the photoactivation of TiO2 at energy wavelengths in the visible-light range). The NPs were each described by 122 descriptors, being a mixture of measured and atomistic model descriptors. The data were explored using single and univariate statistical methods, combined with machine learning and multiscale modelling techniques. An iterative pruning process was adopted for identifying automatically the most significant descriptors. TiO2 NPs toxicity decreased when combined with UV. Notably, the short-term water exposure induced lasting biological responses even after longer-term recovery in clean exposure. The correspondence with Fe-content correlated with the band-gap hence the reduction of UV oxidative stress. The inclusion of both measured and modelled materials data benefitted the explanation of the results, when combined with machine learning

Time of harvest affects United States-grown Aronia mitschurinii berry polyphenols, ◦Brix, and acidity

The goal of this study was to determine how the date of harvest impacts the quality characteristics of Aronia mitschurinii (A. K. Skvortsov and Maitul.) ‘Viking’ and ‘Galicjanka’ berries. Aronia berries were collected from farms in the Midwestern and Northeastern United States over seven weeks of harvest during 2018, 2019 and 2020. The berries were analyzed for total phenol, anthocyanins, proanthocyanins, sugar, and acid. Aronia berry composition modestly deviated between each year of the study. Berries harvested in 2018 had the highest total phenols and proanthocyanidins, both increasing in content from weeks 1–5 from 15.90 ± 3.15–19.65 mg gallic acid equivalents/g fw, a 24% increase, and 2.22 ± 0.40–2.94 mg (+)-catechin equivalents/g fw, a 32% increase, respectively. Berries harvested in 2019 had the lowest total phenol and proanthocyanidin levels and had increasing anthocyanins until week 4. In 2020, aronia berry proanthocyanidins differed from those in 2018 by having 38% lower levels after the 4th week. Across years, berries had increasing ◦Brix, ◦Brix: acid, and pH throughout the seven weeks of harvest. Additionally, all years had slight, but statistically insignificant decreases in acidity over the harvest period. Moreover, analysis from berries collected in 2019 suggests no significant difference in quality factors between Viking and Galicjanka aronia cultivars. In conclusion, aronia berry total phenols, proanthocyanidins, pH, and berry size can be significantly affected by the growing year and time of harvest. Acidity was impacted more by growing year than harvest week. In contrast, anthocyanins and ◦Brix were consistent between years, but influenced considerably by the week of harvest

Tissue Doppler echocardiographic quantification. Comparison to coronary angiography results in Acute Coronary Syndrome patients

BACKGROUND: Multiples indices have been described using tissue Doppler imaging (DTI) capabilities. The aim of this study was to assess the capability of one or several regional DTI parameters in separating control from ischemic myocardium. METHODS: Twenty-eight patients with acute myocardial infarction were imaged within 24-hour following an emergent coronary angioplasty. Seventeen controls without any coronary artery or myocardial disease were also explored. Global and regional left ventricular functions were assessed. High frame rate color DTI cineloop recordings were made in apical 4 and 2-chamber for subsequent analysis. Peak velocity during isovolumic contraction time (IVC), ejection time, isovolumic relaxation (IVR) and filling time were measured at the mitral annulus and the basal, mid and apical segments of each of the walls studied as well as peak systolic displacement and peak of strain. RESULTS: DTI-analysis enabled us to discriminate between the 3 populations (controls, inferior and anterior AMI). Even in non-ischemic segments, velocities and displacements were reduced in the 2 AMI populations. Peak systolic displacement was the best parameter to discriminate controls from AMI groups (wall by wall, p was systematically < 0.01). The combination IVC + and IVR< 1 discriminated ischemic from non-ischemic segments with 82% sensitivity and 85% specificity. CONCLUSION: DTI-analysis appears to be valuable in ischemic heart disease assessment. Its clinical impact remains to be established. However this simple index might really help in intensive care unit routine practice

Relevance of tissue Doppler in the quantification of stress echocardiography for the detection of myocardial ischemia in clinical practice

In the present article we review the main published data on the application of Tissue Doppler Imaging (TDI) to stress echocardiography for the detection of myocardial ischemia. TDI has been applied to stress echocardiography in order to overcome the limitations of visual analysis for myocardial ischemia. The introduction of a new technology for clinical routine use should pass through the different phases of scientific assessment from feasibility studies to large multicenter studies, from efficacy to effectiveness studies. Nonetheless the pro-technology bias plays a major role in medicine and expensive and sophisticated techniques are accepted before their real usefulness and incremental value to the available ones is assessed. Apparently, TDI is not exempted by this approach : its applications are not substantiated by strong and sound results. Nonetheless, conventional stress echocardiography for myocardial ischemia detection is heavily criticized on the basis of its subjectivity. Stress echocardiography has a long lasting history and the evidence collected over 20 years positioned it as an established tool for the detection and prognostication of coronary artery disease. The quantitative assessment of myocardial ischemia remains a scientific challenge and a clinical goal but time has not come for these newer ultrasonographic techniques which should be restricted to research laboratories

Source apportionment of fine particulate matter in Houston, Texas: insights to secondary organic aerosols

Online and offline measurements of ambient particulate matter (PM) near the urban and industrial Houston Ship Channel in Houston, Texas, USA, during May 2015 were utilized to characterize its chemical composition and to evaluate the relative contributions of primary, secondary, biogenic, and anthropogenic sources. Aerosol mass spectrometry (AMS) on nonrefractory PM1 (PM  ≤  1&thinsp;µm) indicated major contributions from sulfate (averaging 50&thinsp;% by mass), organic aerosol (OA, 40&thinsp;%), and ammonium (14&thinsp;%). Positive matrix factorization (PMF) of AMS data categorized OA on average as 22&thinsp;% hydrocarbon-like organic aerosol (HOA), 29&thinsp;% cooking-influenced less-oxidized oxygenated organic aerosol (CI-LO-OOA), and 48&thinsp;% more-oxidized oxygenated organic aerosol (MO-OOA), with the latter two sources indicative of secondary organic aerosol (SOA). Chemical analysis of PM2.5 (PM  ≤  2.5&thinsp;µm) filter samples agreed that organic matter (35&thinsp;%) and sulfate (21&thinsp;%) were the most abundant components. Organic speciation of PM2.5 organic carbon (OC) focused on molecular markers of primary sources and SOA tracers derived from biogenic and anthropogenic volatile organic compounds (VOCs). The sources of PM2.5 OC were estimated using molecular marker-based positive matric factorization (MM-PMF) and chemical mass balance (CMB) models. MM-PMF resolved nine factors that were identified as diesel engines (11.5&thinsp;%), gasoline engines (24.3&thinsp;%), nontailpipe vehicle emissions (11.1&thinsp;%), ship emissions (2.2&thinsp;%), cooking (1.0&thinsp;%), biomass burning (BB, 10.6&thinsp;%), isoprene SOA (11.0&thinsp;%), high-NOx anthropogenic SOA (6.6&thinsp;%), and low-NOx anthropogenic SOA (21.7&thinsp;%). Using available source profiles, CMB apportioned 41&thinsp;% of OC to primary fossil sources (gasoline engines, diesel engines, and ship emissions), 5&thinsp;% to BB, 15&thinsp;% to SOA (including 7.4&thinsp;% biogenic and 7.6&thinsp;% anthropogenic), and 39&thinsp;% to other sources that were not included in the model and are expected to be secondary.This study presents the first application of in situ AMS-PMF, MM-PMF, and CMB for OC source apportionment and the integration of these methods to evaluate the relative roles of biogenic, anthropogenic, and BB-SOA. The three source apportionment models agreed that  ∼ &thinsp;50&thinsp;% of OC is associated with primary emissions from fossil fuel use, particularly motor vehicles. Differences among the models reflect their ability to resolve sources based upon the input chemical measurements, with molecular marker-based methods providing greater source specificity and resolution for minor sources. By combining results from MM-PMF and CMB, BB was estimated to contribute 11&thinsp;% of OC, with 5&thinsp;% primary emissions and 6&thinsp;% BB-SOA. SOA was dominantly anthropogenic (28&thinsp;%) rather than biogenic (11&thinsp;%) or BB-derived. The three-model approach demonstrates significant contributions of anthropogenic SOA to fine PM. More broadly, the findings and methodologies presented herein can be used to advance local and regional understanding of anthropogenic contributions to SOA.</p

Longitudinal peak strain detects a smaller risk area than visual assessment of wall motion in acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Opening of an occluded infarct related artery reduces infarct size and improves survival in acute ST-elevation myocardial infarction (STEMI). In this study we performed tissue Doppler analysis (peak strain, displacement, mitral annular movement (MAM)) and compared with visual assessment for the study of the correlation of measurements of global, regional and segmental function with final infarct size and transmurality. In addition, myocardial risk area was determined and a prediction sought for the development of infarct transmurality ≥50%.</p> <p>Methods</p> <p>Twenty six patients with STEMI submitted for primary percutaneous coronary intervention (PCI) were examined with echocardiography on the catheterization table. Four to eight weeks later repeat echocardiography was performed for reassessment of function and magnetic resonance imaging for the determination of final infarct size and transmurality.</p> <p>Results</p> <p>On a global level, wall motion score index (WMSI), ejection fraction (EF), strain, and displacement all showed significant differences (p ≤ 0.001, p ≤ 0.001, p ≤ 0.001 and p = 0.03) between the two study visits, but MAM did not (p = 0.17). On all levels (global, regional and segmental) and both pre- and post PCI, WMSI showed a higher correlation with scar transmurality compared to strain. We found that both strain and WMSI predicted the development of scar transmurality ≥50%, but strain added no significant information to that obtained with WMSI in a logistic regression analysis.</p> <p>Conclusions</p> <p>In patients with acute STEMI, WMSI, EF, strain, and displacement showed significant changes between the pre- and post PCI exam. In a ROC-analysis, strain had 64% sensitivity at 80% specificity and WMSI around 90% sensitivity at 80% specificity for the detection of scar with transmurality ≥50% at follow-up.</p

Perioperative risk stratification in non cardiac surgery: role of pharmacological stress echocardiography

Perioperative ischemia is a frequent event in patients undergoing major non-cardiac vascular or general surgery. This is in agreement with clinical, pathophysiological, and epidemiological evidence and constitutes an additional diagnostic therapeutic factor in the assessment of these patients. Form a clinical standpoint, it is well known that multidistrict disease, especially at the coronary level, is a severe aggravation of the operative risk. From a pathophysiological point of view, however, surgery creates conditions able to unmask coronary artery disease. Prolonged hypotension, hemorrhages, and haemodynamic stresses caused by aortic clamping and unclamping during major vascular surgery are the most relevant factors endangering the coronary circulation with critical stenoses. From the epidemiological standpoint, coronary disease is known to be the leading cause of perioperative mortality and morbidity following vascular and general surgery: The diagnostic therapeutic corollary of these considerations is that coronary artery disease – and therefore the perioperative risk – in these patients has to be identified in an effective way preoperatively