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The on-surface synthesis of bisheptahelicene by Ullmann coupling of 9-bromoheptahelicene on Au(111) and its temperature-induced dehydrogenation is studied using temperature-programmed reaction spectroscopy and time-of-flight secondary ion mass spectrometry. Specific dehydrogenation products of bisheptahelicene after loss of 6, 8 and 10 hydrogen atoms are identified, corresponding to molecules having undergone Diels–Alder transformations and intramolecular C–C coupling reactions. By combining with atomic hydrogen produced by dehydrogenation, the Ullmann coupling side-product bromine desorbs as HBr. H2 desorption emerges only after all Br has desorbed. Such characteristic behavior is explained by a kinetic model which explicitly considers the coverage of transient atomic H on the surface. Heating experiments performed with saturated layers of different Br-containing molecules reveal that the onset of HBr desorption depends strictly on the dehydrogenation step and therefore on the structure of the molecules.
Es wird das Computerprogramm HITAB vorgestellt, das die Eingabe pflanzensoziologischer Daten stark erleichtert (rasches, fehlerfreies Eintippen), und die so erfassten Daten in die Formate einiger gängiger Programme konvertiert (TAB, TWINSPAN, DECORANA, CANOCO, SYN-TAX, VEGBASE, FLORA D), sowie die Ausgabe von Aufnahmelisten und Artenlisten in Textformat (ASCII) ermöglicht.
Durch einen Vergleich nach ca. 30 Jahren wiederholter Vegetationsaufnahmen von Glatthaferwiesen an Straßenrändern des Raumes Halle/S. konnten die in der Zwischenzeit stattgefundenen anthropogenen Veränderungen der straßenbegleitenden Vegetation am konkreten Beispiel belegt werden. Zur Interpretation der Veränderungen in der Artenzusammensetzung wurden besonders Zeigerwert-, Hemerobie- und Strategietypenspektren herangezogen. Veränderungen äußern sich vor allem in einer Abnahme der Diversität durch Zunahme euryöker Ubiquisten und einer Erhöhung des Hemerobiegrades. Die Ursachen für diesen Wandel sind besonders in der Intensivierung der Produktion auf den angrenzenden landwirtschaftlichen Nutzflächen und einer weitestgehenden Auflassung der Nutzung der Straßenränder selbst zu sehen, die sich in deren Eutrophierung äußern.
Simple Summary: Early and accurate diagnosis of breast cancer that has spread to other organs and tissues is crucial, as therapeutic decisions and outcome expectations might change. Computed tomography (CT) is often used to detect breast cancer’s spread, but this method has its weaknesses. The computer-assisted technique “radiomics” extracts grey-level patterns, so-called radiomic features, from medical images, which may reflect underlying biological processes. Our retrospective study therefore evaluated whether breast cancer spread can be predicted by radiomic features derived from iodine maps, an application on a new generation of CT scanners visualizing tissue blood flow. Based on 77 patients with newly diagnosed breast cancer, we found that this approach might indeed predict cancer spread to other organs/tissues. In the future, radiomics may serve as an additional tool for cancer detection and risk assessment.
Abstract: Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differ- ences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.
Background: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a novel AI software version for automated BA assessment in comparison to the Greulich-Pyle method.
Methods: Radiographs of 514 patients were analysed in this retrospective study. Total BA was assessed independently by three blinded radiologists applying the GP method and by the AI software. Overall and gender-specific BA assessment results, as well as reading times of both approaches, were compared, while the reference BA was defined by two blinded experienced paediatric radiologists in consensus by application of the Greulich-Pyle method.
Results: Mean absolute deviation (MAD) and root mean square deviation (RSMD) were significantly lower between AI-derived BA and reference BA (MAD 0.34 years, RSMD 0.38 years) than between reader-calculated BA and reference BA (MAD 0.79 years, RSMD 0.89 years; p < 0.001). The correlation between AI-derived BA and reference BA (r = 0.99) was significantly higher than between reader-calculated BA and reference BA (r = 0.90; p < 0.001). No statistical difference was found in reader agreement and correlation analyses regarding gender (p = 0.241). Mean reading times were reduced by 87% using the AI system.
Conclusions: A novel AI software enabled highly accurate automated BA assessment. It may improve efficiency in clinical routine by reducing reading times without compromising the accuracy compared with the Greulich-Pyle method.
The widespread application of human stem-cell-derived neurons for functional studies is impeded by complicated differentiation protocols, immaturity, and deficient optogene expression as stem cells frequently lose transgene expression over time. Here we report a simple but precise Cre-loxP-based strategy for generating conditional, and thereby stable, optogenetic human stem-cell lines. These cells can be easily and efficiently differentiated into functional neurons, and optogene expression can be triggered by administering Cre protein to the cultures. This conditional expression system may be applied to stem-cell-derived neurons whenever timed transgene expression could help to overcome silencing at the stem-cell level.
Channelrhodopsin-2 (ChR2) is a cation-selective light-gated channel from Chlamydomonas reinhardtii (Nagel G, Szellas T, Huhn W, Kateriya S, Adeishvili N, Berthold P, et al. Channelrhodopsin-2, a directly light-gated cation-selective membrane channel. Proc Natl Acad Sci USA 2003;100:13940-5), which has become a powerful tool in optogenetics. Two-dimensional crystals of the slow photocycling C128T ChR2 mutant were exposed to 473 nm light and rapidly frozen to trap the open state. Projection difference maps at 6Å resolution show the location, extent and direction of light-induced conformational changes in ChR2 during the transition from the closed state to the ion-conducting open state. Difference peaks indicate that transmembrane helices (TMHs) TMH2, TMH6 and TMH7 reorient or rearrange during the photocycle. No major differences were found near TMH3 and TMH4 at the dimer interface. While conformational changes in TMH6 and TMH7 are known from other microbial-type rhodopsins, our results indicate that TMH2 has a key role in light-induced channel opening and closing in ChR2.
The sequenced genome of the poly-extremophile Exiguobacterium sp. S17, isolated from modern stromatolites at Laguna Socompa (3,570 m), a High-Altitude Andean Lake (HAAL) in Argentinean Puna revealed a putative proteorhodopsin-encoding gene. The HAAL area is exposed to the highest UV irradiation on Earth, making the microbial community living in the stromatolites test cases for survival strategies under extreme conditions. The heterologous expressed protein E17R from Exiguobacterium (248 amino acids, 85% sequence identity to its ortholog ESR from E. sibiricum) was assembled with retinal displaying an absorbance maximum at 524 nm, which makes it a member of the green-absorbing PR-subfamily. Titration down to low pH values (eventually causing partial protein denaturation) indicated a pK value between two and three. Global fitting of data from laser flash-induced absorption changes gave evidence for an early red-shifted intermediate (its formation being below the experimental resolution) that decayed (τ1 = 3.5 μs) into another red-shifted intermediate. This species decayed in a two-step process (τ2 = 84 μs, τ3 = 11 ms), to which the initial state of E17-PR was reformed with a kinetics of 2 ms. Proton transport capability of the HAAL protein was determined by BLM measurements. Additional blue light irradiation reduced the proton current, clearly identifying a blue light absorbing, M-like intermediate. The apparent absence of this intermediate is explained by closely matching formation and decay kinetics.
Dual-energy CT (DECT) has emerged into clinical routine as an imaging technique with unique postprocessing utilities that improve the evaluation of different body areas. The virtual non-calcium (VNCa) reconstruction algorithm has shown beneficial effects on the depiction of bone marrow pathologies such as bone marrow edema. Its main advantage is the ability to substantially increase the image contrast of structures that are usually covered with calcium mineral, such as calcified vessels or bone marrow, and to depict a large number of traumatic, inflammatory, infiltrative, and degenerative disorders affecting either the spine or the appendicular skeleton. Therefore, VNCa imaging represents another step forward for DECT to image conditions and disorders that usually require the use of more expensive and time-consuming techniques such as magnetic resonance imaging, positron emission tomography/CT, or bone scintigraphy. The aim of this review article is to explain the technical background of VNCa imaging, showcase its applicability in the different body regions, and provide an updated outlook on the clinical impact of this technique, which goes beyond the sole improvement in image quality.
Background: Dual-source dual-energy computed tomography (DECT) offers the potential for opportunistic osteoporosis screening by enabling phantomless bone mineral density (BMD) quantification. This study sought to assess the accuracy and precision of volumetric BMD measurement using dual-source DECT in comparison to quantitative CT (QCT). Methods: A validated spine phantom consisting of three lumbar vertebra equivalents with 50 (L1), 100 (L2), and 200 mg/cm3 (L3) calcium hydroxyapatite (HA) concentrations was scanned employing third-generation dual-source DECT and QCT. While BMD assessment based on QCT required an additional standardised bone density calibration phantom, the DECT technique operated by using a dedicated postprocessing software based on material decomposition without requiring calibration phantoms. Accuracy and precision of both modalities were compared by calculating measurement errors. In addition, correlation and agreement analyses were performed using Pearson correlation, linear regression, and Bland-Altman plots. Results: DECT-derived BMD values differed significantly from those obtained by QCT (p < 0.001) and were found to be closer to true HA concentrations. Relative measurement errors were significantly smaller for DECT in comparison to QCT (L1, 0.94% versus 9.68%; L2, 0.28% versus 5.74%; L3, 0.24% versus 3.67%, respectively). DECT demonstrated better BMD measurement repeatability compared to QCT (coefficient of variance < 4.29% for DECT, < 6.74% for QCT). Both methods correlated well to each other (r = 0.9993; 95% confidence interval 0.9984–0.9997; p < 0.001) and revealed substantial agreement in Bland-Altman plots. Conclusions: Phantomless dual-source DECT-based BMD assessment of lumbar vertebra equivalents using material decomposition showed higher diagnostic accuracy compared to QCT.