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Exploring energy selection methods for robust biologically optimized carbon ion arc for head&neck cancer patients
Get PDFBackground: Due to the advantageous depth dose profile of carbon ion beams, carbon ion therapy is commonly applied in the form of intensity modulated particle therapy (IMPT) with few treatment fields. Carbon ion arc therapy (C-Arc) has recently been proposed to improve dose conformity and increase the dose-averaged linear energy transfer (LETd) inside the target to levels relevant for overcoming tumor radioresistance. In this work, we investigate different energy selection approaches for C-Arc, including a novel greedy energy layer refinement strategy.
Methods: Robust biologically optimized C-Arc plans were generated for six head &neck cancer patient previously treated at the Shanghai Proton and Heavy Ion Center (SPHIC). Different heuristic approaches for mono- and dual-energy C-Arc were implemented, and compared to carbon IMPT pans. A novel greedy energy layer refinement was developed, acting directly on the dose influence matrix, rather than on an iterative plan optimization. A key challenge in C-Arc with few energy layers per angle is the sharpness of the carbon ion Bragg peak, which is challenging for plan robustness. To improve robustness and plan quality, we propose the use of a 6 mm ripple filter instead of the typical 3 mm ripple filter used for carbon IMPT.
Results: Most mono-energetic C-Arc plans were able to meet the established clinical goals, but some of the heuristic energy selection schemes were not universally applicable with low plan quality in some patients. The developed energy layer refinement strategy delivered high quality plans even for complex cases. Mono-energetic C-Arc plans presented an average increase between 10% and 33% in the maximum LETd in the target, with similar or up to 19% improved average target LETd50% compared to the IMPT carbon ion plans. C-Arc plans with 2 energies per treatment angle, for the employed energy selection heuristic, improved dosimetric quality compared to mono-energetic C-Arc plans, but did not provide the same natural improvement in LETd compared to IMPT.
Conclusions: For small, centrally located targets C-Arc demonstrates the greatest potential, but feasible plans could also be achieved for more complex cases in this work. Further development is necessary for improving C-Arc delivery efficiency and plan quality toward possible clinical application
Designing Behavior Change Support Systems Targeting Blood Donation Behavior
Get PDFWhile blood is crucial for many surgeries and patient treatments worldwide, it cannot be produced artificially. Fulfilling the demand for blood products on average days is already a major challenge in countries like South Africa and Ghana. In these countries, less than 1 % of the population donates blood and most of the donations come from first-time donors who do not return. Sufficient new, first-time and even lapsed donors must be motivated to donate regularly. This study argues that blood donation behavior change support systems (BDBCSS) can be beneficially applied to support blood donor management in African countries. In this study, the design science research (DSR) approach is applied in order to derive generic design principles for BDBCSS and instantiate the design knowledge in prototypes for a blood donation app and a chatbot. The design principles were evaluated in a field study in South Africa. The results demonstrate the positive effects of BDBCSS on users’ intentional and developmental blood donation behavior. This study contributes to research and practice by proposing a new conceptualization of blood donation information systems support and a nascent design theory for BDBCSS that builds on behavioral theories as well as related work on blood donation information systems. Thus, the study provides valuable implications for designing preventive health BCSS by stating three design principles for a concrete application context in healthcare
AI Literacy for the top management: An upper echelons perspective on corporate AI orientation and implementation ability
Get PDFWe draw on upper echelons theory to examine whether the AI literacy of a firm’s top management team (i.e., TMT AI literacy) has an effect on two firm characteristics paramount for value generation with AI—a firm’s AI orientation, enabling it to identify AI value potentials, and a firm’s AI implementation ability, empowering it to realize these value potentials. Building on the notion that TMT effects are contingent upon firm contexts, we consider the moderating influence of a firm’s type (i.e., startups vs. incumbents). To investigate these relationships, we leverage observational literacy data of 6986 executives from a professional social network (LinkedIn.com) and firm data from 10-K statements. Our findings indicate that TMT AI literacy positively affects AI orientation as well as AI implementation ability and that AI orientation mediates the effect of TMT AI literacy on AI implementation ability. Further, we show that the effect of TMT AI literacy on AI implementation ability is stronger in startups than in incumbent firms. We contribute to upper echelons literature by introducing AI literacy as a skill-oriented perspective on TMTs, which complements prior role-oriented TMT research, and by detailing AI literacy’s role for the upper echelons-based mechanism that explains value generation with AI
Day-of-the-week effect: a meta-analysis
Get PDFThis study conducts a meta-analysis on the day-of-the-week effect to shed more light on the replication crisis of this stock market anomaly. The findings confirm that Mondays and Tuesdays provide, on average, lower daily returns. In addition, Wednesdays and Fridays indicate higher returns, with an unexpectedly strong middle-of-the-week effect on Wednesdays. The study highlights the influence of study design on these findings and notes a more substantial effect in the 1980s and 1990s. While differences in empirical methods do not impact the anomaly, index choices affect findings on day-dependent returns. The real estate sector especially stands out with a stronger day-of-the-week effect. However, geographic differences are mostly insignificant except for Oceania. Cultural differences demonstrate a weak but significant effect on abnormal daily returns. From a meta-perspective, outliers remain an essential driver for this stock market anomaly, indicating that study design is not the only factor driving the replication crisis
Recent developments in visible light induced polymerization towards its application to nanopores
Get PDFVisible light induced polymerizations are a strongly emerging field in recent years. Besides the often mild reaction conditions, visible light offers advantages of spatial and temporal control over chain growth, which makes visible light ideal for functionalization of surfaces and more specifically of nanoscale pores. Current challenges in nanopore functionalization include, in particular, local and highly controlled polymer functionalizations. Using spatially limited light sources such as lasers or near field modes for light-induced polymer functionalization is envisioned to allow local functionalization of nanopores and thereby improve nanoporous material performance. These light sources are usually providing visible light while classical photopolymerizations are mostly based on UV-irradiation. In this review, we highlight developments in visible light induced polymerizations and especially in visible light induced controlled polymerizations as well as their potential for nanopore functionalization. Existing examples of visible light induced polymerizations in nanopores are emphasized
Combination of inverse electron-demand Diels–Alder reaction with highly efficient oxime ligation expands the toolbox of site-selective peptide conjugations
Get PDFA modular approach combining inverse electron-demand Diels–Alder coupling (DARinv) and oxime ligation expands the toolbox of bioorthogonal peptide chemistry. Applicability of versatile site-specific bifunctional building blocks is demonstrated by generation of defined conjugates comprising linear, cystine-bridged and multi-disulfide functional peptides as well as their conjugation with hybrid silsesquioxane nanoparticles
Surface charge density and induced currents by self-charging sliding drops
Get PDFSpontaneous charge separation in drops sliding over a hydrophobized insulator surface is a well-known phenomenon and lots of efforts have been made to utilize this effect for energy harvesting. For maximizing the efficiency of such devices, a comprehensive understanding of the dewetted surface charge would be required to quantitatively predict the electric current signals, in particular for drop sequences. Here, we use a method based on mirror charge detection to locally measure the surface charge density after drops move over a hydrophobic surface. For this purpose, we position a metal electrode beneath the hydrophobic substrate to measure the capacitive current induced by the moving drop. Furthermore, we investigate drop-induced charging on different dielectric surfaces together with the surface neutralization processes. The surface neutralizes over a characteristic time, which is influenced by the substrate and the surrounding environment. We present an analytical model that describes the slide electrification using measurable parameters such as the surface charge density and its neutralization time. Understanding the model parameters and refining them will enable a targeted optimization of the efficiency in solid–liquid charge separation
Engineering of ultraID, a compact and hyperactive enzyme for proximity-dependent biotinylation in living cells
Get PDFProximity-dependent biotinylation (PDB) combined with mass spectrometry analysis has established itself as a key technology to study protein-protein interactions in living cells. A widespread approach, BioID, uses an abortive variant of the E. coli BirA biotin protein ligase, a quite bulky enzyme with slow labeling kinetics. To improve PDB versatility and speed, various enzymes have been developed by different approaches. Here we present a small-size engineered enzyme: ultraID. We show its practical use to probe the interactome of Argonaute-2 after a 10 min labeling pulse and expression at physiological levels. Moreover, using ultraID, we provide a membrane-associated interactome of coatomer, the coat protein complex of COPI vesicles. To date, ultraID is the smallest and most efficient biotin ligase available for PDB and offers the possibility of investigating interactomes at a high temporal resolution
S-Sulfocysteine – Investigation of cellular uptake in CHO cells
Get PDFFor the generation of therapeutic proteins in cell culture, high producing clones are used. These clones have a high demand in amino acids to support cell growth and productivity. l-cysteine (Cys) is critical in highly concentrated feeds due to low stability of Cys and low solubility of the oxidation product cystine at neutral pH. S-sulfocysteine (SSC) was developed to substitute the Cys source and fed-batch experiments using SSC showed good cellular performance regarding viable cell density and titer, indicating uptake and metabolization of SSC by Chinese hamster ovary cells. However, the responsible transporter allowing cellular uptake remains unclear and was studied in this work. Due to the structure similarity of SSC with cystine and glutamate, it was proposed that the cystine/glutamate antiporter () allows cellular uptake of SSC. The uptake was assessed via transporter inhibition using sulfasalazine and transporter overexpression using either sulforaphane or sulforaphane-N-acetylcysteine during fed-batch experiments. Following daily addition of 50 μM and 100 μM sulfasalazine, the extracellular SSC concentration was increased by 65 % and 177 % respectively, suggesting a reduced uptake due to inhibition. In contrast, enhanced transporter activity through 15 μM sulforaphane and sulforaphane-N-acetylcysteine treatment, induced a 60 % and 52 % reduced extracellular SSC concentration, respectively. These inverse uptake results strongly suggest that is facilitating the transport of SSC
A laboratory scale fast feedback characterization loop for optimizing coated catalysts for emission control
Get PDFCoating of structured substrates like ceramic honeycombs plays an important role in heterogenous gas-phase catalysis. This work aims at understanding the effects of different coating parameters on the activity of a noble metal-based oxidation catalyst by using a novel fast and non-invasive photo-based channel analysis approach. The impact of the milling intensity, binder amount, catalyst layer thickness and distribution in the ceramic cordierite channels were systematically correlated with the activity profiles for CO, methane and propylene oxidation over a 1.8% Pd/Al₂O₃ catalyst. High milling intensities led to the formation of thinner catalyst layers with smaller particles, which were more evenly distributed throughout all channels and allowed the reactants to penetrate more efficiently. In contrast, the amount of binder added had a negligible influence on the catalyst activity. These findings were validated by X-ray tomography and complemented by SEM-analysis, a diffuse backlight-illumination imaging method, and mercury intrusion porosimetry