Die Prädiktion der Leseleistung von Schülerinnen und Schülern im Rahmen von Lernverlaufsdiagnostik. Evidenz für einen Geschlechter-Bias

Learning progress monitoring (LPM) is an effective tool for teachers to improve students’ performance by systematically and quickly responding to achievement data. However, studies show that in-service and preservice teachers often have difficulties using LPM because of lacking graph literacy, especially with high data ambiguity. The present study examines whether (a) preservice teachers are biased by gender stereotypes when predicting students’ performance based on progress data, (b) the preservice teachers’ gender affected their predictions differentially depending on student gender, and (c) the insertion of a trend line or lowered data variability diminishes the gender bias in predictions. N = 134 preservice teachers received 16 experimental student vignettes online via the internet in random order which depicted the learning progress of boys and girls in oral reading fluency assessment over a period of 11 weeks. Half of the participants were presented with progress data accompanied by a trend line, the other half received progress data only. Results evidenced that preservice teachers were prone to a gender bias favoring girls. The gender bias was attenuated when a trend line was presented or when data variability was low, with male participants benefitting more from the trend line, and female participants benefitting more from low data variability. The adaptation of international training programs to enhance graph literacy and to diminish gender stereotyping in German teachers is recommendable. (DIPF/Orig.)Lernverlaufsdiagnostik stellt ein wirksames Instrument für Lehrkräfte dar, um die Leistung von Schüler:innen zu verbessern, indem Lehrkräfte systematisch und schnell auf die Schülerleistung reagieren können. Allerdings hat sich gezeigt, dass Lehrkräfte häufig Schwierigkeiten haben, Lernverlaufsdaten korrekt zu interpretieren. Wir haben mit der vorliegenden Studie untersucht, ob Lehramtsstudierende dazu neigen, Mädchen besser als Jungen zu bewerten, wenn sie auf Grundlage von Lernverlaufsdaten eine Prognose für künftige Leistungen erstellen müssen. Darüber hinaus haben wir die Hypothesen geprüft, dass der Geschlechter-Bias bei männlichen Lehramtsstudierenden zugunsten männlicher Schüler abgeschwächt ist und dass die Bereitstellung einer Trendlinie in den Lernverlaufsdaten bzw. eine geringere Variabilität der Daten zu einer Verringerung des Geschlechter-Bias führen. Insgesamt N = 134 Lehramtsstudierende erhielten 16 experimentelle Vignetten, in denen der Verlauf der Leseleistung von 8 weiblichen und 8 männlichen Grundschüler:innen über einen Zeitraum von 11 Wochen als Lernverlaufsgraph dargestellt war. Bei der Hälfte der Versuchspersonen waren die Lernverlaufsgraphen durch eine Trendlinie ergänzt. Die Ergebnisse zeigten, dass die Lehramtsstudierenden im Durchschnitt höhere Leistungen für Mädchen im Vergleich zu Jungen prognostizierten und dass der Geschlechter-Bias durch die Trendlinie und durch eine geringe Datenvariabilität abgeschwächt wurde. Wir empfehlen die Adaptation bereits international verwendeter Trainingsmaßnahmen zur Schulung von Lehramtsstudierenden und Lehrkräften in der Interpretation von Lernverlaufsdaten und zur Prävention von systematischen Verzerrungen von Interpretationen von Lernverlaufsdaten. (DIPF/Orig.

Accuracy of a chatbot (Ada) in the diagnosis of mental disorders : comparative case study with lay and expert users

Background: Health apps for the screening and diagnosis of mental disorders have emerged in recent years on various levels (eg, patients, practitioners, and public health system). However, the diagnostic quality of these apps has not been (sufficiently) tested so far. Objective: The objective of this pilot study was to investigate the diagnostic quality of a health app for a broad spectrum of mental disorders and its dependency on expert knowledge. Methods: Two psychotherapists, two psychology students, and two laypersons each read 20 case vignettes with a broad spectrum of mental disorders. They used a health app (Ada—Your Health Guide) to get a diagnosis by entering the symptoms. Interrater reliabilities were computed between the diagnoses of the case vignettes and the results of the app for each user group. Results: Overall, there was a moderate diagnostic agreement (kappa=0.64) between the results of the app and the case vignettes for mental disorders in adulthood and a low diagnostic agreement (kappa=0.40) for mental disorders in childhood and adolescence. When psychotherapists applied the app, there was a good diagnostic agreement (kappa=0.78) regarding mental disorders in adulthood. The diagnostic agreement was moderate (kappa=0.55/0.60) for students and laypersons. For mental disorders in childhood and adolescence, a moderate diagnostic quality was found when psychotherapists (kappa=0.53) and students (kappa=0.41) used the app, whereas the quality was low for laypersons (kappa=0.29). On average, the app required 34 questions to be answered and 7 min to complete. Conclusions: The health app investigated here can represent an efficient diagnostic screening or help function for mental disorders in adulthood and has the potential to support especially diagnosticians in their work in various ways. The results of this pilot study provide a first indication that the diagnostic accuracy is user dependent and improvements in the app are needed especially for mental disorders in childhood and adolescence

Quantifying absolute addressability in DNA origami with molecular resolution

Self-assembled DNA nanostructures feature an unprecedented addressability with sub-nanometer precision and accuracy. This addressability relies on the ability to attach functional entities to single DNA strands in these structures. The efficiency of this attachment depends on two factors: incorporation of the strand of interest and accessibility of this strand for downstream modification. Here we use DNA-PAINT super-resolution microscopy to quantify both incorporation and accessibility of all individual strands in DNA origami with molecular resolution. We find that strand incorporation strongly correlates with the position in the structure, ranging from a minimum of 48% on the edges to a maximum of 95% in the center. Our method offers a direct feedback for the rational refinement of the design and assembly process of DNA nanostructures and provides a long sought-after quantitative explanation for efficiencies of DNA-based nanomachines

DNA-barcoded labeling probes for highly multiplexed Exchange-PAINT imaging† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc05420j Click here for additional data file.

Recent advances in super-resolution fluorescence imaging allow researchers to overcome the classical diffraction limit of light, and are already starting to make an impact in biology. However, a key challenge for traditional super-resolution methods is their limited multiplexing capability, which prevents a systematic understanding of multi-protein interactions on the nanoscale. Exchange-PAINT, a recently developed DNA-based multiplexing approach, in theory facilitates spectrally-unlimited multiplexing by sequentially imaging target molecules using orthogonal dye-labeled ‘imager’ strands. While this approach holds great promise for the bioimaging community, its widespread application has been hampered by the availability of DNA-conjugated ligands for protein labeling. Herein, we report a universal approach for the creation of DNA-barcoded labeling probes for highly multiplexed Exchange-PAINT imaging, using a variety of affinity reagents such as primary and secondary antibodies, nanobodies, and small molecule binders. Furthermore, we extend the availability of orthogonal imager strands for Exchange-PAINT to over 50 and assay their orthogonality in a novel DNA origami-based crosstalk assay. Using our optimized conjugation and labeling strategies, we demonstrate nine-color super-resolution imaging in situ in fixed cells

Photo-Induced Depletion of Binding Sites in DNA-PAINT Microscopy

The limited photon budget of fluorescent dyes is the main limitation for localization precision in localization-based super-resolution microscopy. Points accumulation for imaging in nanoscale topography (PAINT)-based techniques use the reversible binding of fluorophores and can sample a single binding site multiple times, thus elegantly circumventing the photon budget limitation. With DNA-based PAINT (DNA-PAINT), resolutions down to a few nanometers have been reached on DNA-origami nanostructures. However, for long acquisition times, we find a photo-induced depletion of binding sites in DNA-PAINT microscopy that ultimately limits the quality of the rendered images. Here we systematically investigate the loss of binding sites in DNA-PAINT imaging and support the observations with measurements of DNA hybridization kinetics via surface-integrated fluorescence correlation spectroscopy (SI-FCS). We do not only show that the depletion of binding sites is clearly photo-induced, but also provide evidence that it is mainly caused by dye-induced generation of reactive oxygen species (ROS). We evaluate two possible strategies to reduce the depletion of binding sites: By addition of oxygen scavenging reagents, and by the positioning of the fluorescent dye at a larger distance from the binding site

Bayesian Multiple Emitter Fitting using Reversible Jump Markov Chain Monte Carlo

In single molecule localization-based super-resolution imaging, high labeling density or the desire for greater data collection speed can lead to clusters of overlapping emitter images in the raw super-resolution image data. We describe a Bayesian inference approach to multiple-emitter fitting that uses Reversible Jump Markov Chain Monte Carlo to identify and localize the emitters in dense regions of data. This formalism can take advantage of any prior information, such as emitter intensity and density. The output is both a posterior probability distribution of emitter locations that includes uncertainty in the number of emitters and the background structure, and a set of coordinates and uncertainties from the most probable model

Complex multicomponent patterns rendered on a 3D DNA-barrel pegboard

DNA origami, in which a long scaffold strand is assembled with a many short staple strands into parallel arrays of double helices, has proven a powerful method for custom nanofabrication. However, currently the design and optimization of custom 3D DNA-origami shapes is a barrier to rapid application to new areas. Here we introduce a modular barrel architecture, and demonstrate hierarchical assembly of a 100 megadalton DNA-origami barrel of similar to 90nm diameter and similar to 250nm height, that provides a rhombic-lattice canvas of a thousand pixels each, with pitch of similar to 8nm, on its inner and outer surfaces. Complex patterns rendered on these surfaces were resolved using up to twelve rounds of Exchange-PAINT super-resolution microscopy. We envision these structures as versatile nanoscale pegboards for applications requiring complex 3D arrangements of matter, which will serve to promote rapid uptake of this technology in diverse fields beyond specialist groups working in DNA nanotechnology

One visceral artery may be enough; successful pancreatectomy in a patient with total occlusion of the celiac and superior mesenteric arteries

Abstract Background The anatomic variations of the visceral arteries are not uncommon. The liver arterial blood supply shows 50% variability between humans, with the most common anatomy being one hepatic artery arising from the celiac trunk and one pancreatico-duodenal arcade between the celiac trunk and the superior mesenteric artery. Occlusion of one artery are mostly asymptomatic but may become clinically relevant when surgery of the liver, bile duct or the pancreas is required. If these pathologies are not reversible, an oncologic pancreatic head resection cannot be performed. Case presentation We report the case of a 64-year-old Caucasian female patient with a locally advanced, resectable adenocarcinoma of the pancreas with complete atherosclerotic occlusion of the celiac trunk and the superior mesenteric artery. This vascular anomaly was missed on the preoperative imaging and became known postoperatively. A collateral circulation from a hypertrophic inferior mesenteric artery to the celiac trunk and the superior mesenteric artery compensated the blood supply to the visceral organs. The postoperative course was complicated by an elevation of the transaminases AST/ALT, which normalized under conservative treatment with alprostadil (prostavasin™) and anticoagulation, since angiographic recanalization failed. The patient recovered fully and was discharged at the 14th postoperative day. Two years later, she required endovascular repair of an aortic rupture during which the inferior mesenteric artery was preserved. Conclusion This case underlines the natural potential of the human body to adapt to chronic arterial malperfusion by creating a collateral circulation and supports the need for adequate preoperative imaging, including a proper arterial phase before upper abdominal surgery

Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry

Objectives: We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. Materials and Methods: During a national meeting for AI, eHealth, and IT infrastructure in 2019, we conducted a survey to obtain participants' attitudes. A total of 123 participants completed 28 items exploring AI usage in medicine. The Kruskal-Wallis test was used to identify differences between radiologists, IT specialists, and industry representatives. Results: The strongest agreement between all respondents occurred with the following: plausibility checks are important to understand the decisions of the AI (93% agreement), validation of AI algorithms is mandatory (91%), and medicine becomes more efficient in the age of AI (86%). In contrast, only 25% of the respondents had confidence in the AI results, and only 17% believed that medicine will become more human through the use of AI. The answers were significantly different between the three professions for four items: relevance for protocol selection in cross-sectional imaging (p = 0.034), medical societies should be involved in validation (p = 0.028), patients should be informed about the use of AI (p = 0.047), and AI should be part of medical education (p = 0.026). Conclusion: Currently, a discrepancy exists between high expectations for the future role of AI and low confidence in the results. This attitude was similar across all three groups. The demand for plausibility checks and the need to prove the usefulness in randomized controlled studies indicate what is needed in future research