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- Klinik und Poliklinik für Unfall-, Hand-, Plastische und Wiederherstellungschirurgie (Chirurgische Klinik II) (3)
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Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
Converging evidence from controlled experiments suggests that the mere processing of a number and its attributes such as value or parity might affect free choice decisions between different actions. For example the spatial numerical associations of response codes (SNARC) effect indicates the magnitude of a digit to be associated with a spatial representation and might therefore affect spatial response choices (i.e., decisions between a "left" and a "right" option). At the same time, other (linguistic) features of a number such as parity are embedded into space and might likewise prime left or right responses through feature words [odd or even, respectively; markedness association of response codes (MARC) effect]. In this experiment we aimed at documenting such influences in a natural setting. We therefore assessed number space and parity space association effects by exposing participants to a fair distribution task in a card playing scenario. Participants drew cards, read out loud their number values, and announced their response choice, i.e., dealing it to a left vs. right player, indicated by Playmobil characters. Not only did participants prefer to deal more cards to the right player, the card's digits also affected response choices and led to a slightly but systematically unfair distribution, supported by a regular SNARC effect and counteracted by a reversed MARC effect. The experiment demonstrates the impact of SNARC- and MARC-like biases in free choice behavior through verbal and visual numerical information processing even in a setting with high external validity.
Background:
Diagnostic guidelines recommend using a variety of methods to assess and diagnose ADHD. Applying subjective measures always incorporates risks such as informant biases or large differences between ratings obtained from diverse sources. Furthermore, it has been demonstrated that ratings and tests seem to assess somewhat different constructs. The use of objective measures might thus yield valuable information for diagnosing ADHD. This study aims at evaluating the role of objective measures when trying to distinguish between individuals with ADHD and controls. Our sample consisted of children (n = 60) and adults (n = 76) diagnosed with ADHD and matched controls who completed self- and observer ratings as well as objective tasks. Diagnosis was primarily based on clinical interviews. A popular pattern recognition approach, support vector machines, was used to predict the diagnosis.
Results:
We observed relatively high accuracy of 79% (adults) and 78% (children) applying solely objective measures. Predicting an ADHD diagnosis using both subjective and objective measures exceeded the accuracy of objective measures for both adults (89.5%) and children (86.7%), with the subjective variables proving to be the most relevant.
Conclusions:
We argue that objective measures are more robust against rater bias and errors inherent in subjective measures and may be more replicable. Considering the high accuracy of objective measures only, we found in our study, we think that they should be incorporated in diagnostic procedures for assessing ADHD.
Periodontitis is one of the most prevalent diseases worldwide. The degree of radiographic bone loss can be used to assess the course of therapy or the severity of the disease. Since automated bone loss detection has many benefits, our goal was to develop a multi-object detection algorithm based on artificial intelligence that would be able to detect and quantify radiographic bone loss using standard two-dimensional radiographic images in the maxillary posterior region. This study was conducted by combining three recent online databases and validating the results using an external validation dataset from our organization. There were 1414 images for training and testing and 341 for external validation in the final dataset. We applied a Keypoint RCNN with a ResNet-50-FPN backbone network for both boundary box and keypoint detection. The intersection over union (IoU) and the object keypoint similarity (OKS) were used for model evaluation. The evaluation of the boundary box metrics showed a moderate overlapping with the ground truth, revealing an average precision of up to 0.758. The average precision and recall over all five folds were 0.694 and 0.611, respectively. Mean average precision and recall for the keypoint detection were 0.632 and 0.579, respectively. Despite only using a small and heterogeneous set of images for training, our results indicate that the algorithm is able to learn the objects of interest, although without sufficient accuracy due to the limited number of images and a large amount of information available in panoramic radiographs. Considering the widespread availability of panoramic radiographs as well as the increasing use of online databases, the presented model can be further improved in the future to facilitate its implementation in clinics.
Primary involvement of skeletal muscle is a very rare event in ALK-1 positive anaplastic large cell lymphoma (ALCL). We describe a case of a 10-year old boy presenting with a three week history of pain and a palpable firm swelling at the dorsal aspect of the left thigh. Histological examination of the lesion revealed a tumoral and diffuse polymorphic infiltration of the muscle by large lymphoid cells. Tumor cells displayed eccentric, lobulated "horse shoe" or "kidney-shape" nuclei. The cells showed immunohistochemical positivity for CD30, ALK-1, CD2, CD3, CD7, CD8, and Perforin. Fluorescence in situ hybridization analysis revealed a characteristic rearrangement of the ALK-1 gene in 2p23 leading to the diagnosis of ALK-1 positive ALCL. Chemotherapy according to the ALCL-99-NHL-BFM protocol was initiated and resulted in a complete remission after two cycles. This case illustrates the unusual presentation of a pediatric ALCL in soft tissue with a good response to chemotherapy.
Introduction
We characterized dermal innervation in patients with fibromyalgia syndrome (FMS) as potential contribution to small fiber pathology.
Methods
Skin biopsies of the calf were collected (86 FMS patients, 35 healthy controls). Skin was immunoreacted with antibodies against protein gene product 9.5, calcitonine gene-related peptide, substance P, CD31, and neurofilament 200 for small fiber subtypes. We assessed two skin sections per patient; on each skin section, two dermal areas (150 x 700 mu m each) were investigated for dermal nerve fiber length (DNFL).
Results
In FMS patients we found reduced DNFL of fibers with vessel contact compared to healthy controls (p<0.05). There were no differences for the other nerve fiber subtypes.
Discussion
We found less dermal nerve fibers in contact with blood vessels in FMS patients than in controls. The pathophysiological relevance of this finding is unclear, but we suggest the possibility of a relationship with impaired thermal tolerance commonly reported by FMS patients.
Background
The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy.
Methods
MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman’s rank correlation.
Results
Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01).
Conclusion
The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.
Background and Objectives: Cycloid psychoses are characterized by polymorphic symptomatology with intraphasic bipolarity, a remitting and recurrent course and favourable prognosis. Perris and Brocicington (P&B) described the first set of operational criteria that were partly incorporated in ICD-10. The present study investigates psychopathological profiles according to the P&B criteria and the original descriptions by Leonhard, both against the background of the criteria from the prevailing international classification systems.
Methods: Eighty patients with psychotic disorders were recruited and assessed with various psychometric instruments at baseline and after six weeks of antipsychotic treatment in order to investigate the presence of cycloid psychoses according to Leonhard (LCP) and the effect of treatment with antipsychotics. The overlap between LCP and DSM-IV Brief Psychotic Disorder (BPD), ICD Acute Polymorphic Psychotic Disorder (APP) and P&B criteria was calculated.
Results: Using P&B criteria and a symptom checklist adapted from the original descriptions by Leonhard, 14 and 12 cases of cycloid psychosis were identified respectively reflecting a prevalence of 15-18%. Small though significant concordance rates were found between LCP and both DSM-BPD and ICD-APP. Concordance between LCP and P&B criteria was also significant, but modest.
Conclusions: This study demonstrates that LCP can be identified in a substantial number of patients with psychotic disorders. Cycloid psychoses are not adequately covered in current classification systems and criteria. Since they are demonstrated to have a specific psychopathological profile, relapsing course and favourable prognosis, it is advocated to include these psychoses in daily differential diagnostic procedures.
Iconography of the Genus Hieracium in central Europe - Part 1: General Description and Morphotypes
(2005)
The genus Hieracium comprises more than one thousand sexual and apomictic species in Europe, with numerous intermediates and microspecies. Only a small fraction of the members of the genus Hieracium has been illustrated or photo-documented in the literature. Since many of these publications are difficult to obtain, only a few specialists are familiar with most of the species and subspecies described in the literature. In order to overcome this problem and encourage geobotanical research on the genus Hieracium, we decided to edit an iconography of central and southern European Hieracia in an electronical journal (Forum geobotanicum) with free international access through the internet. Part I of this endeavour contains descriptions and photographs of the morphological spectrum of the genus Hieracium. Here, we categorize the genus into 15 basic morphotypes. These types conform partly to the sections and subsections of the genus Hieracium, but are in some cases informal and may even include members of different sections. Classification of morphotypes is considered helpful to obtain a first rough picture of an unknown species that then can be traced to the species and subspecies level by using keys or, after completion of this iconography, simply by screening the relevant images. One particularly novel aspect of the present endeavour will be the regular inclusion of magnified images and scanning electron micrographs.
Background
Morphology and glenoid involvement determine the necessity of surgical management in scapula fractures. While being present in only a small share of patients with shoulder trauma, numerous classification systems have been in use over the years for categorization of scapula fractures. The purpose of this study was to evaluate the established AO/OTA classification in comparison to the classification system of Euler and Rüedi (ER) with regard to interobserver reliability and confidence in clinical practice.
Methods
Based on CT imaging, 149 patients with scapula fractures were retrospectively categorized by two trauma surgeons and two radiologists using the classification systems of ER and AO/OTA. To measure the interrater reliability, Fleiss kappa (κ) was calculated independently for both fracture classifications. Rater confidence was stated subjectively on a five-point scale and compared with Wilcoxon signed rank tests. Additionally, we computed the intraclass correlation coefficient (ICC) based on absolute agreement in a two-way random effects model to assess the diagnostic confidence agreement between observers.
Results
In scapula fractures involving the glenoid fossa, interrater reliability was substantial (κ = 0.722; 95% confidence interval [CI] 0.676–0.769) for the AO/OTA classification in contrast to moderate agreement (κ = 0.579; 95% CI 0.525–0.634) for the ER classification system. Diagnostic confidence for intra-articular fracture patterns was superior using the AO/OTA classification compared to ER (p < 0.001) with higher confidence agreement (ICC: 0.882 versus 0.831). For extra-articular fractures, ER (κ = 0.817; 95% CI 0.771–0.863) provided better interrater reliability compared to AO/OTA (κ = 0.734; 95% CI 0.692–0.776) with higher diagnostic confidence (p < 0.001) and superior agreement between confidence ratings (ICC: 0.881 versus 0.912).
Conclusions
The AO/OTA classification is most suitable to categorize intra-articular scapula fractures with glenoid involvement, whereas the classification system of Euler and Rüedi appears to be superior in extra-articular injury patterns with fractures involving only the scapula body, spine, acromion and coracoid process.