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

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

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

Tissue Doppler Imaging

In der vorliegenden Arbeit wurden Strain und Strain Rate zum ersten Mal in der Veterinärmedizin bei einer großen Population von Hunden eingesetzt. Beide Methoden sind, wie das TVI, Techniken des Gewebedopplers. Dieser basiert auf dem gleichen Prinzip wie der Blutflussdoppler. Im Unterschied dazu werden jedoch keine Blutfluss- sondern Myokardsignale aufgezeichnet. Während das TVI nur die globale Myokardfunktion widerspiegelt, erlauben Strain und Strain Rate dagegen eine regionale Funktionsanalyse, da sie weniger durch die Globalbewegung des Herzmuskels beeinflusst werden. Ziel dieser Studie war die Erstellung von Referenzwerten für diese drei Methoden anhand einer Studienpopulation von 199 Hunden. Die Datenakquirierung erfolgte mit einem System Vivid 7 der Firma GE (Horten, Norwegen). Die offline-Analyse wurde mit der Q-Analyse-Software (Version BT04) der Firma GE (Horten, Norwegen) durchgeführt. Die Reproduzierbarkeit für Strain und TVI war für die meisten Parameter gut. Die beste Reproduzierbarkeit aller drei Methoden zeigte die Strain, die höchsten Variationskoeffizienten wurden für Strain-Rate-Parameter verzeichnet. Generell waren diastolische Parameter schlechter reproduzierbar als systolische Parameter. Der Vergleich einzelner Myokardsegmente einer Wand zeigte, dass das TVI einen apikobasalen Geschwindigkeitsgradienten aufweist. In Übereinstimmung mit neueren humanmedizinischen Studien sowie einer Studie bei Katzen waren beide Verformungsparameter ebenfalls nicht homogen im Myokard verteilt. Beim Vergleich der Einzelwände wies zumeist der rechte Ventrikel die höchsten Peaks bei allen Parametern auf. Es wurde nachgewiesen, dass der Gewebedoppler von physiologischen Faktoren wie Gewicht, Alter, Herzfrequenz und Rasse abhängig ist. Gerade die Rasse hatte auf nahezu alle Parameter einen signifikanten Einfluss. Dies macht eine Erstellung von Referenzwerten für einzelne Hunderassen unabdingbar. Ein Einfluss der anderen Faktoren war zwar oftmals vorhanden, signifikante Unterschiede wurden jedoch zumeist nur gegenüber den Gruppen mit den höchsten oder niedrigsten physiologischen Werten (wie z. B. Herzfrequenz oder Gewicht) nachgewiesen. Eine Einschränkung für den klinischen Einsatz ist, dass das Tracken mit der hier verwendeten Q-Analyse-Software zeitaufwändig ist. Neuere Software-Pakete wie die 2D-Strain-Analyse (Firma GE; Horten, Norwegen) beheben diese Problematik. Die vorliegende Studie belegt, dass TVI, Strain und Strain Rate beim nicht sedierten Hund als neue Methoden in der Echokardiographie einsetzbar sind. Diese Arbeit stellt eine Grundlage für weitere Studien auf dem Gebiet der Gewebedopplertechnik dar. Die hier erstellten Referenzwerte dienen als Grundlage für die Verwendung der Technik an kranken Tieren

A palaeoenvironmental reconstruction of the Middle Jurassic of Sardinia (Italy) based on integrated palaeobotanical, palynological and lithofacies data assessment

During the Jurassic, Sardinia was close to continental Europe. Emerged lands started from a single island forming in time a progressively sinking archipelago. This complex palaeogeographic situation gave origin to a diverse landscape with a variety of habitats. Collection- and literature-based palaeobotanical, palynological and lithofacies studies were carried out on the Genna Selole Formation for palaeoenvironmental interpretations. They evidence a generally warm and humid climate, affected occasionally by drier periods. Several distinct ecosystems can be discerned in this climate, including alluvial fans with braided streams (Laconi-Gadoni lithofacies), paralic swamps and coasts (Nurri-Escalaplano lithofacies), and lagoons and shallow marine environments (Ussassai-Perdasdefogu lithofacies). The non-marine environments were covered by extensive lowland and a reduced coastal and tidally influenced environment. Both the river and the upland/hinterland environments are of limited impact for the reconstruction. The difference between the composition of the palynological and palaeobotanical associations evidence the discrepancies obtained using only one of those proxies. The macroremains reflect the local palaeoenvironments better, although subjected to a transport bias (e.g. missing upland elements and delicate organs), whereas the palynomorphs permit to reconstruct the regional palaeoclimate. Considering that the flora of Sardinia is the southernmost of all Middle Jurassic European floras, this multidisciplinary study increases our understanding of the terrestrial environments during that period of time