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Tremor is one of the most common neurological symptoms. Its clinical and neurobiological complexity necessitates novel approaches for granular phenotyping. Instrumented neurophysiological analyses have proven useful, but are highly resource-intensive and lack broad accessibility. In contrast, bedside scores are simple to administer, but lack the granularity to capture subtle but relevant tremor features. We utilise the open-source computer vision pose tracking algorithm Mediapipe to track hands in clinical video recordings and use the resulting time series to compute canonical tremor features. This approach is compared to marker-based 3D motion capture, wrist-worn accelerometry, clinical scoring and a second, specifically trained tremor-specific algorithm in two independent clinical cohorts. These cohorts consisted of 66 patients diagnosed with essential tremor, assessed in different task conditions and states of deep brain stimulation therapy. We find that Mediapipe-derived tremor metrics exhibit high convergent clinical validity to scores (Spearman's ρ = 0.55–0.86, p≤.01) as well as an accuracy of up to 2.60 mm (95% CI [−3.13, 8.23]) and ≤0.21 Hz (95% CI [−0.05, 0.46]) for tremor amplitude and frequency measurements, matching gold-standard equipment. Mediapipe, but not the disease-specific algorithm, was capable of analysing videos involving complex configurational changes of the hands. Moreover, it enabled the extraction of tremor features with diagnostic and prognostic relevance, a dimension which conventional tremor scores were unable to provide. Collectively, this demonstrates that current computer vision algorithms can be transformed into an accurate and highly accessible tool for video-based tremor analysis, yielding comparable results to gold standard tremor recordings. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this article is to evaluate to the masticatory function performance and Oral Health-related Quality of Life (OHRQoL) in implant-retained overdenture compared with different implant number placements in the edentulous mandible. Methods: From 2013 to 2015, each patients received 3 implants (iSy-Implant, Camlog, Wimsheim, Germany) in intraforaminal mandible (34, 41/31, 44). After operation, inserted implants were gradually loaded and incorporated into an overdenture with a self-aligning attachment system (Locator abutments) in 3 + 3 + 3 months. Five checked points were performed chewing cycle test with multicolored chewing gum and OHIP-G14 questionnaire and a sum score questionnaire as following: pre-operation, one implant load (41/31), two implants loaded (33,43), three implants loaded and 1-year follow up. Result: A total of 10 patients with 30 implants were placed, the survival rate of the implants was 100% within 1-year follow-up. Regarding the masticatory function analysis, for the higher number of chewing cycles, the higher mixing rate was observed. After 1 year, the inter-mixing rate without significant changes was found compared to the time after three implants were loaded with attachment system. The mean value of OHIP-G14 was 30.4 preoperatively, 21.1 after loading the first locator, 10.7 after loading two locator abutments, and 3.2 after loading all three locator abutments. After 1 year, OHIP-G14 was 2.6 without significantly changed. The mean of the sum score was 15.5 preoperatively, 27.8 after activation of the first locator, 39.4 after activation of two locators, 46.2 after activation of all three locators, and 47.3 after 1 year. An increase of 0.7 sum score units per time point was observed. No significance was detectable, analogous to OHIP-G14, compared to the time of activation of all three locator setups (p-value = 0.22). Conclusions: A significant improvement in masticatory function performance and OHRQoL was evaluated with the increasing number of implants with locator attachment in edentulous mandible. With the investigation of the OHIP-G14 and sum score, the results of patient report outcome might be associated with the increase in the number of implants. [ABSTRACT FROM AUTHOR]

To determine the intraspecific variability of microscopic organisms such as dinophytes is challenging, but can be achieved using cultured material. Unusual morphologies of Peridinium tuberosum assigned to the Peridinium cinctum species group have been described as bulges on the posterior end of the cell a hundred years ago and more, but its taxonomic significance is unclear at present. We collected field material in Germany and Poland in order to establish strains to study cell morphology using light and scanning electron microscopy. For the cultured material, DNA sequence data from the rRNA operon was gained as well and included in molecular phylogenetics (including 22 new partial rRNA sequences). Two new, closely related ribotypes were detected, and all strains showed the principle morphology of P. cinctum having an asymmetric epitheca, a large first apical plate and a sulcus extending onto the epitheca. In the single-strain GeoM*979 assigned to one of the two new ribotypes, cells with bulges appeared rarely but consistently, mostly on the hypotheca, but other variations also occurred. Overall, cells of this strain display traits not observed before while studying cultured P. cinctum, and this distinction is further supported by molecular data and additional details of epithecal opening. However, there does not remain enough information to determine strain GeoM*979 as a separate species (namely P. tuberosum) and therefore, it is identified as Peridinium aff. cinctum until further notice. [ABSTRACT FROM AUTHOR]

Sustainable weed management strategies are critical to feeding the world's population while preserving ecosystems and biodiversity. Therefore, site-specific weed control strategies based on automation are needed to reduce the additional time and effort required for weeding. Machine vision-based methods appear to be a promising approach for weed detection, but require high quality data on the species in a specific agricultural area. Here we present a dataset, the Moving Fields Weed Dataset (MFWD), which captures the growth of 28 weed species commonly found in sorghum and maize fields in Germany. A total of 94,321 images were acquired in a fully automated, high-throughput phenotyping facility to track over 5,000 individual plants at high spatial and temporal resolution. A rich set of manually curated ground truth information is also provided, which can be used not only for plant species classification, object detection and instance segmentation tasks, but also for multiple object tracking. [ABSTRACT FROM AUTHOR]

Copyright of Kölner Zeitschrift für Soziologie und Sozialpsychologie ( KZfSS) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Anti-retinal autoantibodies are assumed to be associated with age-related macular degeneration (AMD). To our knowledge, this is the first evaluation of autoantibodies in human sera of participants with different stages of AMD in a large population-based, observational cohort study in Germany. Methods: The Gutenberg Health Study (GHS) is a population-based, observational cohort study in Germany, including 15,010 participants aged between 35 and 74. Amongst others, non-mydriatic fundus photography (Visucam PRO NM™, Carl Zeiss Meditec AG, Jena, Germany) was performed. Fundus images of the first 5000 participants were graded based on the Rotterdam Eye Study classification. Sera of participants with AMD (n=541) and sera of age-matched participants without AMD (n=490) were analyzed by antigen-microarrays. Besides descriptive statistics, autoantibody-levels were compared by Mann-Whitney-U test and the associations of level of autoantibodies with AMD were calculated by logistic regression analysis. Likewise, possible associations of the autoantibodies and both clinical and laboratory parameters on AMD subjects were analyzed. Results: Autoantibodies against transferrin (p<0.001) were significantly downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only compared to Controls. Mitogen-activated protein kinase 3 (p=0.041), glutathione peroxidase 4 (p=0.048), clusterin (p=0.045), lysozyme (p=0.19), protein kinase C substrate 80K-H (p=0.02), heat shock 70 kDa protein 1A (p=0.04) and insulin (p=0.018) show a trend between Control and participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only. Conclusions: This study contributes to a growing knowledge of autoantibodies in association with different AMD stages compared to controls in the context of a large population-based study in Germany. Especially autoantibodies against inflammatory proteins were downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only. [ABSTRACT FROM AUTHOR]

Purpose: Dental implant abutments are defined as medical devices by their intended use. Surfaces of custom-made CAD/CAM two-piece abutments may become contaminated during the manufacturing process in the dental lab. Inadequate reprocessing prior to patient care may contribute to implant-associated complications. Risk-adapted hygiene management is required to meet the requirements for medical devices. Methods: A total of 49 CAD/CAM-manufactured zirconia copings were bonded to prefabricated titanium bases. One group was bonded, polished, and cleaned separately in dental laboratories throughout Germany (LA). Another group was left untreated (NC). Five groups received the following hygiene regimen: three-stage ultrasonic cleaning (CP and FP), steam (SC), argon–oxygen plasma (PL), and simple ultrasonic cleaning (UD). Contaminants were detected using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) and segmented and quantified using interactive machine learning (ML) and thresholding (SW). The data were statistically analysed using non-parametric tests (Kruskal–Wallis test, Dunn's test). Results: Significant differences in contamination levels with the different cleaning procedures were found (p ≤ 0.01). The FP–NC/LA groups showed the most significant difference in contamination levels for both measurement methods (ML, SW), followed by CP–LA/NC and UD–LA/NC for SW and CP–LA/NC and PL–LA/NC for ML (p ≤ 0.05). EDS revealed organic contamination in all specimens; traces of aluminum, silicon, and calcium were detected. Conclusions: Chemothermal cleaning methods based on ultrasound and argon–oxygen plasma effectively removed process-related contamination from zirconia surfaces. Machine learning is a promising assessment tool for quantifying and monitoring external contamination on zirconia abutments. [ABSTRACT FROM AUTHOR]

Heterogeneous flow pathways through the soil determine the transport of dissolved and particle-bound nutritional elements like phosphorus (P) to ground and surface waters. This study was designed to understand the spatial patterns of P in agriculturally used soils and the mechanisms causing P accumulation and depletion at the centimetre scale. We conducted dye tracer experiments using Brilliant Blue on a loamy Stagnosol in North-Eastern-Germany. The plant-available P was analysed using double lactate extraction (DL-P). The plant-available P content of the topsoil was significantly higher than that of the subsoil in all three replicates (p < 0.001). The topsoil's stained areas showed significantly higher P contents than unstained areas (p < 0.05), while the opposite was found for the subsoil. The P content varied enormously across all observed soil profiles (4 to 112 mg P kg−1 soil) and different categories of flow patterns (matrix flow, flow fingers, macropore flow, and no visible transport pathways). The P contents of these transport pathways differed significantly and followed the order: Pmatrix flow > Pfinger flow > Pno visible transport pathways > Pmacropore flow. We conclude that P tends to accumulate along flow pathways in the topsoil in the observed fertilized and tilled mineral soil. In contrast, in the subsoil at a generally lower P level, P is depleted from the prominent macroporous flow domains. [ABSTRACT FROM AUTHOR]

Copyright of Kölner Zeitschrift für Soziologie und Sozialpsychologie ( KZfSS) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose : To develop a CT-based radiomic signature to predict biochemical recurrence (BCR) in prostate cancer patients after sRT guided by positron-emission tomography targeting prostate-specific membrane antigen (PSMA-PET). Material and methods: Consecutive patients, who underwent 68Ga-PSMA11-PET/CT-guided sRT from three high-volume centers in Germany, were included in this retrospective multicenter study. Patients had PET-positive local recurrences and were treated with intensity-modulated sRT. Radiomic features were extracted from volumes of interests on CT guided by focal PSMA-PET uptakes. After preprocessing, clinical, radiomics, and combined clinical-radiomic models were developed combining different feature reduction techniques and Cox proportional hazard models within a nested cross validation approach. Results: Among 99 patients, median interval until BCR was the radiomic models outperformed clinical models and combined clinical-radiomic models for prediction of BCR with a C-index of 0.71 compared to 0.53 and 0.63 in the test sets, respectively. In contrast to the other models, the radiomic model achieved significantly improved patient stratification in Kaplan-Meier analysis. The radiomic and clinical-radiomic model achieved a significantly better time-dependent net reclassification improvement index (0.392 and 0.762, respectively) compared to the clinical model. Decision curve analysis demonstrated a clinical net benefit for both models. Mean intensity was the most predictive radiomic feature. Conclusion: This is the first study to develop a PSMA-PET-guided CT-based radiomic model to predict BCR after sRT. The radiomic models outperformed clinical models and might contribute to guide personalized treatment decisions. [ABSTRACT FROM AUTHOR]

We present a deep learning-based framework for individual tree crown delineation in aerial and satellite images. This is an important task, e.g., for forest yield or carbon stock estimation. In contrast to earlier work, the presented method creates irregular polygons instead of bounding boxes and also provides a tree cover mask for areas that are not separable. Furthermore, it is trainable with low amounts of training data and does not need 3D height information from, e.g., laser sensors. We tested the approach in two scenarios: (1) with 30 cm WorldView-3 satellite imagery from an urban region in Bengaluru, India, and (2) with 5 cm aerial imagery of a densely forested area near Gartow, Germany. The intersection over union between the reference and predicted tree cover mask is 71.2% for the satellite imagery and 81.9% for the aerial images. On the polygon level, the method reaches an accuracy of 46.3% and a recall of 63.7% in the satellite images and an accuracy of 52% and recall of 66.2% in the aerial images, which is comparable to previous works that only predicted bounding boxes. Depending on the image resolution, limitations to separate individual tree crowns occur in situations where trees are hardly separable even for human image interpreters (e.g., homogeneous canopies, very small trees). The results indicate that the presented approach can efficiently delineate individual tree crowns in high-resolution optical images. Given the high availability of such imagery, the framework provides a powerful tool for tree monitoring. The source code and pretrained weights are publicly available at https://github.com/AWF-GAUG/TreeCrownDelineation. [ABSTRACT FROM AUTHOR]

Current dynamic MRA techniques are limited by temporal resolution and signal-to-noise penalties. GRASP, a fast and flexible MRI technique combining compressed-sensing, parallel imaging, and golden-angle radial sampling, acquires volumetric data continuously and can be reconstructed post hoc for user-defined applications. We describe a custom pipeline to retrospectively reconstruct ultrahigh temporal resolution, dynamic MRA from GRASP imaging obtained in the course of routine practice. GRASP scans were reconstructed using a custom implementation of the GRASP algorithm and post-processed with MeVisLab (MeVis Medical Solutions AG, Germany). Twenty consecutive examinations were scored by three neuroradiologists for angiographic quality of specific vascular segments and imaging artifacts using a 4-point scale. Unsubtracted images, baseline-subtracted images, and a temporal gradient dataset were available in 2D and 3D reconstructions. Distinct arterial and capillary phases were identified in all reconstructions, with a median of 2 frames (IQR1-3 and 2–3, respectively). Median rating for vascular segments was 3 (excellent) in all reconstructions and for nearly all segments, with excellent intraclass correlation (range 0.91–1.00). No cases were degraded by artifacts. GRASP-MRI obtained in routine practice can be seamlessly repurposed to produce high quality 4D MRA with 1–2-s resolved isotropic cerebrovascular angiography. Further exploration into diagnostic accuracy in disease-specific applications is warranted. [ABSTRACT FROM AUTHOR]

While it is known that cultural background influences the healthy brain, less is known about how it affects cortical changes in schizophrenia. Here, we tested whether schizophrenia differentially affected the brain in Japanese and German patients. In a sample of 155 patients with a diagnosis of schizophrenia and 191 healthy controls from Japan and Germany, we acquired 3 T-MRI of the brain. We subsequently compared cortical thickness and cortical surface area to identify whether differences between healthy controls and patients might be influenced by ethnicity. Additional analyses were performed to account for effects of duration of illness and medication. We found pronounced interactions between schizophrenia and cultural background in the cortical thickness of several areas, including the left inferior and middle temporal gyrus, as well as the right lateral occipital cortex. Regarding cortical surface area, interaction effects appeared in the insula and the occipital cortex, among others. Some of these brain areas are related to the expression of psychotic symptoms, which are known to differ across cultures. Our results indicate that cultural background impacts cortical structures in different ways, probably resulting in varying clinical manifestations, and call for the inclusion of more diverse samples in schizophrenia research. [ABSTRACT FROM AUTHOR]

Purpose: Development of best practices for dealing with incidental findings on neuroimaging requires insight in their frequency and clinical relevance. Methods: Here, we delineate prevalence estimates with 95% confidence intervals and clinical management of incidental findings, based on the first 3589 participants of the population-based Rhineland Study (age range 30–95 years) who underwent 3 Tesla structural neuroimaging (3D, 0.8 mm3 isotropic resolution). Two trained raters independently assessed all scans for abnormalities, with confirmation and adjudication where needed by neuroradiologists. Participants were referred for diagnostic work-up depending on the potential benefit. Results: Of 3589 participants (mean age 55 ± 14 years, 2072 women), 867 had at least one possible incidental finding (24.2%). Most common were pituitary abnormalities (12.3%), arachnoid cysts (4.1%), developmental venous anomalies (2.5%), non-acute infarcts (1.8%), cavernomas (1.0%), and meningiomas (0.7%). Forty-six participants were informed about their findings, which was hitherto unknown in 40 of them (1.1%). Of these, in 19 participants (48%), a wait-and-see policy was applied and nine (23%) received treatment, while lesions in the remainder were benign, could not be confirmed, or the participant refused to inform us about their clinical diagnosis. Conclusion: Nearly one-quarter of participants had an incidental finding, but only 5% of those required referral, that mostly remained without direct clinical consequences. [ABSTRACT FROM AUTHOR]

Branches are not only of vital importance to tree physiology and growth but are also one of the most influential features in wood quality. To improve the availability of data throughout the forest-to-industry production, information on internal quality (e.g. knots) of both felled and standing trees in the forest would be desirable. This study presents models for predicting the internal knot diameter of Douglas-fir logs based on characteristics measured in the field. The data were composed of 87 trees (aged from 32 to 78 years), collected from six trial sites in southwest Germany, and cut into 4–5 m logs on-site. The internal knot diameter was obtained by applying a knot detection algorithm to the CT images of the logs. Applying the Random Forest (RF) technique, two models were developed: (1) MBD: to predict the branch diameter (BD) at different radial positions within the stem, and (2) MBDmax: to predict the maximum internal branch diameter (BDmax). Both models presented a good performance, predicting BD with an RMSE of 4.26 mm (R2 = 0.84) and BDmax with an RMSE of 5.65 mm (R2 = 0.78). In this context, the innovative combination of CT technology and RF modelling technique showed promising potential to be used in future investigations, as it provided a good performance while being flexible in terms of input data structure and also allowing the inclusion of otherwise underexplored databases. This study showed a possibility to predict the internal diameter of branches from field measurements, introducing an advance towards connecting forest and sawmill. [ABSTRACT FROM AUTHOR]

Aim: The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability. Subject and methods: Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work. Results: Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system's integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine. Conclusion: Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique. [ABSTRACT FROM AUTHOR]