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It is demonstrated that the di‐\(\pi\)‐methane (DPM) rearrangement of carbonyl‐substituted dibenzobarrelene (9,10‐dihydro‐9,10‐ethenoanthracene) derivatives is induced by visible‐light‐induced triplet photosensitization with Ir(ppy)\(_{3}\), Ir(dFppy)\(_{3}\) or 1‐butyl‐7,8‐dimethoxy‐3‐methylalloxazine as catalysts, whereas derivatives that lack carbonyl substituents are photoinert under these conditions. Notably, the products are formed almost quantitatively.
A visual stimulus at a particular location of the visual field may elicit a behavior while at the same time equally salient stimuli in other parts do not. This property of visual systems is known as selective visual attention (SVA). The animal is said to have a focus of attention (FoA) which it has shifted to a particular location. Visual attention normally involves an attention span at the location to which the FoA has been shifted. Here the attention span is measured in Drosophila. The fly is tethered and hence has its eyes fixed in space. It can shift its FoA internally. This shift is revealed using two simultaneous test stimuli with characteristic responses at their particular locations. In tethered flight a wild type fly keeps its FoA at a certain location for up to 4s. Flies with a mutation in the radish gene, that has been suggested to be involved in attention-like mechanisms, display a reduced attention span of only 1s.
PURPOSE:
We aimed to (a) elucidate the concordance of visual assessment of an initial I-ioflupane scan by a human interpreter with comparison to results using a fully automatic semiquantitative method and (b) to assess the accuracy compared to follow-up (f/u) diagnosis established by movement disorder specialists.
METHODS:
An initial I-ioflupane scan was performed in 382 patients with clinically uncertain Parkinsonian syndrome. An experienced reader performed a visual evaluation of all scans independently. The findings of the visual read were compared with semiquantitative evaluation. In addition, available f/u clinical diagnosis (serving as a reference standard) was compared with results of the human read and the software.
RESULTS:
When comparing the semiquantitative method with the visual assessment, discordance could be found in 25 (6.5%) of 382 of the cases for the experienced reader (ĸ = 0.868). The human observer indicated region of interest misalignment as the main reason for discordance. With neurology f/u serving as reference, the results of the reader revealed a slightly higher accuracy rate (87.7%, ĸ = 0.75) compared to semiquantification (86.2%, ĸ = 0.719, P < 0.001, respectively). No significant difference in the diagnostic performance of the visual read versus software-based assessment was found.
CONCLUSIONS:
In comparison with a fully automatic semiquantitative method in I-ioflupane interpretation, human assessment obtained an almost perfect agreement rate. However, compared to clinical established diagnosis serving as a reference, visual read seemed to be slightly more accurate as a solely software-based quantitative assessment.
There is such vast amount of visual information in our surroundings at any time that filtering out the important information for further processing is a basic requirement for any visual system. This is accomplished by deploying attention to focus on one source of sensory inputs to the exclusion of others (Luck and Mangun 2009). Attention has been studied extensively in humans and non human primates (NHPs). In Drosophila, visual attention was first demonstrated in 1980 (Wolf and Heisenberg 1980) but this field remained largely unexplored until recently. Lately, however, studies have emerged that hypothesize the role of attention in several behaviors but do not specify the characteristic properties of attention. So, the aim of this research was to characterize the phenomenon of visual attention in wild-type Drosophila, including both externally cued and covert attention using tethered flight at a torque meter. Development of systematic quantifiable behavioral tests was a key aspect for this which was not only important for analyzing the behavior of a population of wild-type flies but also for comparing the wild-type flies with mutant flies. The latter would help understand the molecular, genetic, and neuronal bases of attention. Since Drosophila provides handy genetic tools, a model of attention in Drosophila will serve to the greater questions about the neuronal circuitry and mechanisms involved which might be analogous to those in primates. Such a model might later be used in research involving disorders of attention. Attention can be guided to a certain location in the visual field by the use of external cues. Here, using visual cues the attention of the fly was directed to one or the other of the two visual half-fields. A simple yet robust paradigm was designed with which the results were easily quantifiable. This paradigm helped discover several interesting properties of the cued attention, the most substantial one being that this kind of external guidance of attention is restricted to the lower part of the fly’s visual field. The guiding cue had an after-effect, i.e. it could occur at least up to 2 seconds before the test and still bias it. The cue could also be spatially separated from the test by at least 20° and yet attract the attention although the extent of the focus of attention (FoA) was smaller than one lower visual half-field. These observations excluded the possibility of any kind of interference between the test and the cue stimuli. Another interesting observation was the essentiality of continuous visibility of the test stimulus but not the cue for effective cuing. When the contrast of the visual scene was inverted, differences in response frequencies and cuing effects were observed. Syndirectional yaw torque responses became more frequent than the antidirectional responses and cuing was no longer effective in the lower visual field with inverted contrast. Interestingly, the test stimulus with simultaneous displacement of two stripes not only effectuated a phasic yaw torque response but also a landing response. A 50 landing response was produced in more than half of the cases whenever a yaw torque response was produced. Elucidation of the neuronal correlates of the cued attention was commenced. Pilot experiments with hydroxyurea (HU) treated flies showed that mushroom bodies were not required for the kind of guidance of attention tested in this study. Dopamine mutants were also tested for the guidance of attention in the lower visual field. Surprisingly, TH-Gal4/UAS-shits1 flies flew like wild-type flies and also showed normal optomotor response during the initial calibration phase of the experiment but did not show any phasic yaw torque or landing response at 18 °C, 25 °C or 30 °C. dumb2 flies that have almost no D1 dopamine receptor dDA1 expression in the mushroom bodies and the central complex (Kim et al. 2007) were also tested and like THGal4/ UAS-shits1 flies did not show any phasic yaw torque or landing response. Since the dopamine mutants did not show the basic yaw torque response for the test the role of dopamine in attention could not be deduced. A different paradigm would be needed to test these mutants. Not only can attention be guided through external cues, it can also be shifted endogenously (covert attention). Experiments with the windows having oscillating stripes nicely demonstrated the phenomenon of covert attention due to the production of a characteristic yaw torque pattern by the flies. However, the results were not easily quantifiable and reproducible thereby calling for a more systematic approach. Experiments with simultaneous opposing displacements of two stripes provide a promising avenue as the results from these experiments showed that the flies had a higher tendency to deliver one type of response than when the responses would be produced stochastically suggesting that attention increased this tendency. Further experiments and analysis of such experiments could shed more light on the mechanisms of covert attention in flies.
Visual Attention in Flies-Dopamine in the Mushroom Bodies Mediates the After-Effect of Cueing
(2016)
Visual environments may simultaneously comprise stimuli of different significance. Often such stimuli require incompatible responses. Selective visual attention allows an animal to respond exclusively to the stimuli at a certain location in the visual field. In the process of establishing its focus of attention the animal can be influenced by external cues. Here we characterize the behavioral properties and neural mechanism of cueing in the fly Drosophila melanogaster. A cue can be attractive, repulsive or ineffective depending upon (e.g.) its visual properties and location in the visual field. Dopamine signaling in the brain is required to maintain the effect of cueing once the cue has disappeared. Raising or lowering dopamine at the synapse abolishes this after-effect. Specifically, dopamine is necessary and sufficient in the αβ-lobes of the mushroom bodies. Evidence is provided for an involvement of the αβ\(_{posterior}\) Kenyon cells.
Visual Blood, a 3D animated computer model to optimize the interpretation of blood gas analysis
(2023)
Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care.
Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95% CI, 0.92–1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95% CI, 1.42–3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95% CI, 0.58–1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95% CI, −0.09–4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters’ perception. However, the study also highlighted the limitations of today’s virtual reality headsets and Visual Blood.
Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.
Pictorial stimuli can vary on many dimensions, several aspects of which are captured by the term ‘visual complexity.’ Visual complexity can be described as, “a picture of a few objects, colors, or structures would be less complex than a very colorful picture of many objects that is composed of several components.” Prior studies have reported a relationship between affect and visual complexity, where complex pictures are rated as more pleasant and arousing. However, a relationship in the opposite direction, an effect of affect on visual complexity, is also possible; emotional arousal and valence are known to influence selective attention and visual processing. In a series of experiments, we found that ratings of visual complexity correlated with affective ratings, and independently also with computational measures of visual complexity. These computational measures did not correlate with affect, suggesting that complexity ratings are separately related to distinct factors. We investigated the relationship between affect and ratings of visual complexity, finding an ‘arousal-complexity bias’ to be a robust phenomenon. Moreover, we found this bias could be attenuated when explicitly indicated but did not correlate with inter-individual difference measures of affective processing, and was largely unrelated to cognitive and eyetracking measures. Taken together, the arousal-complexity bias seems to be caused by a relationship between arousal and visual processing as it has been described for the greater vividness of arousing pictures. The described arousal-complexity bias is also of relevance from an experimental perspective because visual complexity is often considered a variable to control for when using pictorial stimuli.
It is the aim of this thesis to present a visual body weight estimation, which is suitable for medical applications. A typical scenario where the estimation of the body weight is essential, is the emergency treatment of stroke patients: In case of an ischemic stroke, the patient has to receive a body weight adapted drug, to solve a blood clot in a vessel. The accuracy of the estimated weight influences the outcome of the therapy directly. However, the treatment has to start as early as possible after the arrival at a trauma room, to provide sufficient treatment. Weighing a patient takes time, and the patient has to be moved. Furthermore, patients are often not able to communicate a value for their body weight due to their stroke symptoms. Therefore, it is state of the art that physicians guess the body weight. A patient receiving a too low dose has an increased risk that the blood clot does not dissolve and brain tissue is permanently damaged. Today, about one-third gets an insufficient dosage. In contrast to that, an overdose can cause bleedings and further complications. Physicians are aware of this issue, but a reliable alternative is missing.
The thesis presents state-of-the-art principles and devices for the measurement and estimation of body weight in the context of medical applications. While scales are common and available at a hospital, the process of weighing takes too long and can hardly be integrated into the process of stroke treatment. Sensor systems and algorithms are presented in the section for related work and provide an overview of different approaches.
The here presented system -- called Libra3D -- consists of a computer installed in a real trauma room, as well as visual sensors integrated into the ceiling. For the estimation of the body weight, the patient is on a stretcher which is placed in the field of view of the sensors. The three sensors -- two RGB-D and a thermal camera -- are calibrated intrinsically and extrinsically. Also, algorithms for sensor fusion are presented to align the data from all sensors which is the base for a reliable segmentation of the patient.
A combination of state-of-the-art image and point cloud algorithms is used to localize the patient on the stretcher. The challenges in the scenario with the patient on the bed is the dynamic environment, including other people or medical devices in the field of view.
After the successful segmentation, a set of hand-crafted features is extracted from the patient's point cloud. These features rely on geometric and statistical values and provide a robust input to a subsequent machine learning approach. The final estimation is done with a previously trained artificial neural network.
The experiment section offers different configurations of the previously extracted feature vector. Additionally, the here presented approach is compared to state-of-the-art methods; the patient's own assessment, the physician's guess, and an anthropometric estimation. Besides the patient's own estimation, Libra3D outperforms all state-of-the-art estimation methods: 95 percent of all patients are estimated with a relative error of less than 10 percent to ground truth body weight. It takes only a minimal amount of time for the measurement, and the approach can easily be integrated into the treatment of stroke patients, while physicians are not hindered.
Furthermore, the section for experiments demonstrates two additional applications: The extracted features can also be used to estimate the body weight of people standing, or even walking in front of a 3D camera. Also, it is possible to determine or classify the BMI of a subject on a stretcher. A potential application for this approach is the reduction of the radiation dose of patients being exposed to X-rays during a CT examination.
During the time of this thesis, several data sets were recorded. These data sets contain the ground truth body weight, as well as the data from the sensors. They are available for the collaboration in the field of body weight estimation for medical applications.