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We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
One of the most commonly diagnosed cancers in men is prostate cancer (PCa). Understanding tumor progression can help diagnose and treat the disease at an early stage. Components of the extracellular matrix (ECM) play a key role in the development and progression of PCa. Elastin is an essential component of the ECM and constantly changes during tumor development. This article visualizes and quantifies elastin in magnetic resonance imaging (MRI) using a small molecule probe. Results were correlated with histological examinations. Using an elastin-specific molecular probe, we were able to make predictions about the cellular structure in relation to elastin and thus draw conclusions about the size of the tumor, with smaller tumors having a higher elastin content than larger tumors.
Human prostate cancer (PCa) is a type of malignancy and one of the most frequently diagnosed cancers in men. Elastin is an important component of the extracellular matrix and is involved in the structure and organization of prostate tissue. The present study examined prostate cancer in a xenograft mouse model using an elastin-specific molecular probe for magnetic resonance molecular imaging. Two different tumor sizes (500 mm3 and 1000 mm3) were compared and analyzed by MRI in vivo and histologically and analytically ex vivo. The T1-weighted sequence was used in a clinical 3-T scanner to calculate the relative contrast enhancement before and after probe administration. Our results show that the use of an elastin-specific probe enables better discrimination between tumors and surrounding healthy tissue. Furthermore, specific binding of the probe to elastin fibers was confirmed by histological examination and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). Smaller tumors showed significantly higher signal intensity (p > 0.001), which correlates with the higher proportion of elastin fibers in the histological evaluation than in larger tumors. A strong correlation was seen between relative enhancement (RE) and Elastica–van Gieson staining (R2 = 0.88). RE was related to inductively coupled plasma–mass spectrometry data for Gd and showed a correlation (R2 = 0.78). Thus, molecular MRI could become a novel quantitative tool for the early evaluation and detection of PCa.
Background: Prevention of metastatic invasion is one of the main challenges in the treatment of alveolar rhabdomyosarcoma. Still the therapeutic options are limited. Therefore, an anti-tumor screening was initiated focusing on the anti-metastatic and anti-invasion properties of selected medicinal plant extracts and phytoestrogens, already known to be effective in the prevention and treatment of different cancer entities.
Methods: Treatment effects were first evaluated by cell viability, migration, invasion, and colony forming assays on the alveolar rhabdomyosarcoma cell line RH-30 in comparison with healthy primary cells.
Results: Initial anti-tumor screenings of all substances analyzed in this study, identified the plant extract of Vincetoxicum arnottianum (VSM) as the most promising candidate, harboring the highest anti-metastatic potential. Those significant anti-motility properties were proven by a reduced ability for migration (60%), invasion (99%) and colony formation (61%) under 48 h exposure to 25 μg/ml VSM. The restricted motility features were due to an induction of the stabilization of the cytoskeleton – actin fibers were 2.5-fold longer and were spanning the entire cell. Decreased proliferation (PCNA, AMT, GCSH) and altered metastasis (e. g. SGPL1, CXCR4, stathmin) marker expression on transcript and protein level confirmed the significant lowered tumorigenicity under VSM treatment. Finally, significant alterations in the cell metabolism were detected for
25 metabolites, with levels of uracil, N-acetyl serine and propanoyl phosphate harboring the greatest alterations. Compared to the conventional therapy with cisplatin, VSM treated cells demonstrated a similar metabolic shutdown of the primary cell metabolism. Primary control cells were not affected by the VSM treatment.
Conclusions: This study revealed the VSM root extract as a potential, new migrastatic drug candidate for the putative treatment of pediatric alveolar rhabdomyosarcoma with actin filament stabilizing properties and accompanied by a marginal effect on the vitality of primary cells.
Vergleichende Darstellung SARS-CoV-2-spezifischer Nanobodys aus unterschiedlichen Wirtsorganismen
(2021)
Aufgrund der anhaltenden COVID-19-Pandemie werden neutralisierende Therapeutika benötigt. Eine Möglichkeit zur Behandlung stellt die Verwendung monoklonaler Anti-SARS-CoV-2-Immun-globuline dar. Ihre Produktion in Säugetierzellen ist jedoch schwer skalierbar, um den weltweiten Bedarf zu decken. VHH-Antikörper, auch Nanobodys genannt, bieten hierfür eine Alternative, da sie eine hohe Temperaturstabilität aufweisen und eine kostengünstige Produktion in prokaryotischen Wirtsorganismen ermöglichen.
The increasingly sophisticated nature of modern, more environmentally friendly cementitious binders requires a better understanding and control particularly of the complex, dynamic processes involved in the early phase of cement hydration. In-situ monitoring of properties of a constantly changing system over a defined period of time calls for simple, sensitive, fast, and preferably also non-invasive methods like optical spectroscopy
Per- und polyfluorierte Alkylverbindungen (PFAS) sind eine Substanzklasse mit über 5200 Verbindungen. Aufgrund der Persistenz, Bioakkumulation in Nahrungsketten, Toxizität und der ubiquitären Verbreitung von PFAS zählen sie zu den „emerging pollutants“. Die PFAS-Analytik ist wegen den vielfältigen physikalisch-chemischen Eigenschaften und der sehr hohen Anzahl an PFAS eine große Herausforderung. Da es für viele Anwendungen noch ungewiss ist, welche PFAS verwendet werden, wie sie in die Umwelt gelangen und welche Transformations- bzw. Abbauprodukte entstehen, stoßen analytische Ansätze, die nur auf Einzelsubstanzen abzielen, hier an ihre Grenzen. Weiterhin wird die Analytik aufgrund der Substitution von bereits regulierten PFAS mit ständig steigenden Anzahlen an PFAS-Verbindungen in der Umwelt konfrontiert. PFAS-Summenparameter-Methoden, die ein nahezu vollständiges Abbild der PFAS-Belastungssituation wiedergeben, werden daher immer wichtiger. In unserer Studie haben wir die zwei meistverwendeten PFAS-Summenparameter, das adsorbierbare organisch gebundene Fluor (AOF) und das extrahierbare organisch gebundene Fluor (EOF), miteinander verglichen. Beide Summenparameter können zur Analyse mit entweder combustion-Ionenchromatographie (CIC) oder hochauflösender Molekülabsorptionsspektrometrie (HR-CS-GFMAS) gekoppelt werden. Hierbei diskutieren wir die Vor- und Nachteile sowohl von beiden Summenparameter- als auch beider Detektions-Methoden. Die Untersuchungen wurden mit Oberflächenwasserproben aus der Spree in Berlin durchgeführt. Neben AOF und EOF wurde auch der Gesamt-Fluorgehalt (TF) mit CIC sowie HR-CS-GFMAS bestimmt. Die Fluor-Massenbilanzierung zeigte, dass das Verhältnis AOF/TF höher als das Verhältnis EOF/TF war. Dabei machte der AOF 0.14–0.81% vom TF und der EOF 0.04–0.28% vom TF aus. Insgesamt war die neue EOF/HR-CS-GFMAS-Methode schneller, präziser und sensitiver als die bereits etablierte AOF/CIC-Methode. Beide Methoden sind vielversprechend für die zukünftige Überwachung von Umweltproben und bilden die Grundlage für mögliche Grenzwerte, die auf die Summe PFAS abzielen.
Only a few scientific evidences for the use of Egyptian blue in Early Medieval wall paintings in Central and Southern Europe have been reported so far. The monochrome blue fragment discussed here belongs to the second church building of St. Peter above Gratsch (South Tyrol, Northern Italy, fifth/ sixth century A.D.). Beyond cuprorivaite and carbon black (underpainting), 26 accessory minerals down to trace levels were detected by means of Raman microspectroscopy, providing unprecedented insights into the raw materials blend and conversion reactions during preparation, application, and ageing of the pigment. In conjunction with archaeological evidences for the manufacture of Egyptian blue in Cumae and Liternum and the concordant statements of the antique Roman writers Vitruvius and Pliny the Elder, natural impurities of the quartz sand speak for a pigment produced at the northern Phlegrean Fields (Campania, Southern Italy). Chalcocite (and chalcopyrite) suggest the use of a sulphidic copper ore, and water-insoluble salts a mixed-alkaline flux in the form of plant ash. Not fully reacted quartz crystals partly intergrown with cuprorivaite and only minimal traces of silicate glass portend solid-state reactions predominating the chemical reactions during synthesis, while the melting of the raw materials into glass most likely played a negligible role.
Welcome to the poster Towards Determination of Surface Roughness from a SEM Image, a contribution from BAM in Berlin, Germany. This work is part of the MamaLoCA project, which aims to develop a biosensor for the detection of mycotoxins in cereals. Biosensors come in a great variety, one of which makes use of microscopic beads produced by homogenous coating of polystyrene microspheres. The beads are functionalized by decorating them with bioreceptors – in our case antibodies – which then specifically react with the analyte – in our case mycotoxins – and emit an electrical or optical signal. The functionalization of the beads depends on the surface roughness because this determines the amount and orientation of binders. In other words, the surface roughness affects the accessibility to the binding sites and influences device sensitivity, hence its quantitative determination is an important step in evaluating the quality of the biosensor in general.
The presented solution to the problem of the estimation of surface roughness relies in the repetitive characteristics on the surface of the beads. A SEM image of the bead shows a raspberry like microparticle with a variation of grayscale values, which arise from the secondary electron yield. The principle of the measurement measures the variation of grayscale values along a circumference of a circle centred in the centre of the particle and with an arbitrary radius. The grayscale value variation along the given circumference gives the so-called z-modulation or the lateral profile. By performing Fast Fourier Transform on this profile we obtain the power spectrum as a function of the spatial frequencies through which the grayscales vary. The maximal value for spatial frequency then reveals the most common feature along one given circumference. Surface roughness then is the feature frequency in the spatial domain. This calculation is repeated for several concentric circles with different radii over the particle.
The results for the same particle but recorded at two different accelerating voltages show that the applied method has a potential to reveal the roughness. Interpretation of results from an SE InLens SEM image obtained using 3 kV shows that surface roughness is about 21 nm, which is in a good agreement with an alternative method given in a different presentation. The results from the 10 kV are underestimated due to the loss of surface sensitivity on the SE InLens detection at high voltages.
In conclusion, this method shows promise in determining quantitatively the surface roughness from a single SEM image and its validation is being sought using 3D SEM images and AFM methods.